System

Abstract

To provide a system allowing a user to efficiently retrieve and compare commodities and smoothly purchase a desired commodity.SOLUTION: A data input means for inputting the kind of a commodity which a user is considering to purchase, a desired function and feature, and a budget, a data transmission means for transmitting the inputted data to a server, and a data retrieval means for retrieving the corresponding commodity from a plurality of shopping sites and databases on the Internet based on the data transmitted by the data transmission means; The system includes a data processing means for comparing a charge, a function and a feature, a report generation means for providing a comparison result to a user, an additional request input means for inputting an additional request to the report by the user, a data reprocessing means for retrieving and comparing merchandise again based on the data inputted by the additional request input means, and a purchase procedure substitution means for substituting a purchase procedure on an online shopping site based on an instruction of the user who finally decides merchandise to be purchased.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In conventional online shopping, users have to search for detailed information about the products they want to purchase and then compare and consider them, which is a cumbersome process, making it difficult to efficiently find the products they want. In particular, comparing prices and features across multiple shopping sites is time-consuming, and there is also the problem of wasting a lot of time searching for the perfect product. There has been a demand for a system that can solve these issues and enable users to efficiently search and compare products and smoothly purchase the products they want. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system including: a data input means for a user to input the type of product they are considering purchasing, their desired functions and features, and their budget; a data transmission means for transmitting the data input from the data input means to a server; a data processing means for searching for relevant products from multiple shopping sites and databases on the Internet based on the data transmitted by the data transmission means and comparing prices, functions, and features; a report generation means for providing the user with the comparison results obtained by the data processing means; an additional request input means for the user to input additional requests for the report; a data reprocessing means for searching for and comparing products again based on the data input by the additional request input means; and a purchase procedure agent means for performing the purchase procedure on an online shopping site based on instructions from the user who has finally decided on the product to purchase.

[0006] "User" refers to an individual or corporation that uses the system to search, compare, and purchase products.

[0007] "Data input means" refers to an interface or device that allows a user to input the type of product they are considering purchasing, their desired functions and features, and their budget.

[0008] The "data transmission means" refers to a communication means or protocol for transmitting data input from the data input means to a server.

[0009] The "server" is a computer system that processes data received from the data transmission means and searches for and compares relevant products.

[0010] "Data processing means" refers to algorithms or programs that are used by the server to search for relevant products from multiple shopping sites and databases on the Internet based on the transmitted data, and compare prices, functions, and features.

[0011] The "report generation means" is a program or process that creates a report to provide the user with the comparison results obtained by the data processing means.

[0012] The "additional request input means" is an interface or device that allows the user to input additional wishes or requests based on the report.

[0013] The "data reprocessing means" refers to an algorithm or program for searching and comparing products again based on the data entered through the additional request input means.

[0014] The "purchase procedure proxy means" refers to a means or program that acts as a proxy for the purchase procedure at an online shopping site for the product that the user has finally decided to purchase.

[0015] A "product" is a good or service that a user is considering purchasing.

[0016] "Comparison results" refer to the results of a comprehensive evaluation of the prices, functions, features, etc. of products searched from multiple shopping sites and databases.

[0017] A "shopping site" is a website that sells products and services over the Internet. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5]FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0022] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0023] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0024] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] The present invention relates to a system that enables users to efficiently search for, compare, and purchase desired products, and is configured as follows.

[0040] First, a user enters the type of product they are considering purchasing, their desired functions and features, and their budget through an interface. This data entry method is realized, for example, as a web form or an input screen in a mobile application. Once the user enters this information, the data is sent from the device to the server. The data transmission method is realized by an HTTP request or other communication protocol over the Internet.

[0041] The server analyzes the received data and uses data processing means to search for relevant products across multiple online shopping sites and internal databases. At this stage, the server compares products based on price, functionality, and features to find the best option. Data processing means include product search algorithms and price comparison engines.

[0042] Once the comparison results are obtained, the server uses the report generation means to generate a simple report summarizing these results. The report includes product names, prices, and key features, allowing the user to evaluate and compare products. This report is sent to the terminal and displayed on the user's screen.

[0043] The user can then input additional requests based on the displayed report, for example, specifying a particular brand or requesting more specific features, and this information is retransmitted to the server via the additional request input means.

[0044] The server searches for products again based on the newly received request and updates the comparison results. Using the data reprocessing means, a new search is performed taking into account the additional conditions added to the initial search results. The updated comparison results are compiled again by the report generation means, sent to the terminal, and displayed to the user again.

[0045] Finally, when the user decides on the desired product, the server uses a purchasing agent to carry out the purchasing procedure on the online shopping site. At this stage, the server adds the product to the cart through the shopping site's API and completes the purchase. This process includes payment procedures and inputting shipping information.

[0046] As a specific example, if a user wants to purchase a "tablet," the following operations are performed.

[0047] 1. The user types "tablet, large screen, high resolution, 50000" into the interface.

[0048] 2. The device sends this information to the server.

[0049] 3. The server searches for suitable tablets on multiple shopping sites and compares prices and features.

[0050] 4. The server sends the generated report to the terminal, and the user checks the report.

[0051] 5. The user inputs "a device with a longer battery life" as an additional request.

[0052] 6. The server searches again based on the new conditions, updates the results, and sends them to the device.

[0053] 7. The user selects a specific tablet and requests a purchase.

[0054] 8. The server processes the purchase on the shopping site and the purchase is completed.

[0055] As described above, the present invention is a system that enables users to efficiently select desired products and smoothly complete the purchasing procedure.

[0056] The processing flow will be explained below.

[0057] Step 1:

[0058] Through the interface, users input the type of product they are considering purchasing, their desired functions and features, and their budget. Specifically, they enter information such as "tablet, large screen, high resolution, 50,000 yen" on the input screen of a web form or mobile application.

[0059] Step 2:

[0060] The terminal sends the data entered by the user to the server. This is done over the Internet using a communication protocol such as an HTTP POST request.

[0061] Step 3:

[0062] The server analyzes the received data and extracts conditions such as "tablet," "large screen," "high resolution," and "under 50,000 yen," which are used in the next step.

[0063] Step 4:

[0064] The server uses data processing means to search for relevant products from multiple shopping sites on the Internet and internal databases, using techniques such as API calls and web scraping to obtain a list of products that meet the criteria.

[0065] Step 5:

[0066] The server compares products from the retrieved product list based on price, functionality, and features. Using a specific evaluation algorithm, it comprehensively compares and evaluates each product based on price, features, user ratings, etc.

[0067] Step 6:

[0068] The server generates a report based on the comparison results, including product names, prices, key features, and user ratings, in simple text or HTML format.

[0069] Step 7:

[0070] The server sends the generated report to the terminal, which then displays the report on the user's screen. The user can then review the product by checking the report.

[0071] Step 8:

[0072] The user inputs additional requests based on the report, for example, "longer battery life." The user again uses the interface to input the additional information, which is then sent to the server via the terminal.

[0073] Step 9:

[0074] The server searches for products again based on the additional request, and uses the data reprocessing means to search for products again based on the new conditions and update the comparison results.

[0075] Step 10:

[0076] The server generates a new report based on the updated comparison results and sends it to the terminal, where the user can view the revised report.

[0077] Step 11:

[0078] The user finally decides which products to purchase. The user selects the products to purchase based on the report and makes a final confirmation. After that, the user sends a purchase instruction to the server via the terminal.

[0079] Step 12:

[0080] The server uses a purchasing agent to process purchases on an online shopping site. The server makes an API request to the shopping site, adds products to the cart, and completes payment procedures and inputs shipping information.

[0081] Step 13:

[0082] Once the purchase procedure is complete, the server sends confirmation information to the terminal, and the user receives a notification that the purchase has been completed.

[0083] These are the specific processing steps of the system. This flow allows users to efficiently search and compare desired products and smoothly complete the purchasing process.

[0084] Example 1

[0085] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0086] The problem that this invention aims to solve is to enable users to efficiently browse multiple shopping sites and databases on the Internet and easily search, compare, and purchase desired products. Furthermore, by quickly performing re-searches based on the user's additional requests and selecting optimal products, and by carrying out the purchasing procedure on the user's behalf, the invention aims to reduce the user's operational burden and facilitate the purchasing process.

[0087] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0088] In this invention, the server includes an input device for a user to input the type of product the user is considering purchasing, the desired functions and features, and the user's budget; a data transmission device for transmitting the data input from the input device to the server; a data processing device for searching for relevant products from multiple product sales platforms and databases on an information network based on the data transmitted by the data transmission device and comparing prices, functions, and features; an information generation device for providing the user with the comparison results obtained by the data processing device; an additional request input device for the user to input additional requests regarding the information; a data reprocessing device for searching for and comparing products again based on the data input by the additional request input device; a purchase procedure agent device for performing a purchase procedure on an online shopping site based on instructions from a user who has finally decided on a product to purchase; an algorithm optimization device for optimizing a product search algorithm using a generative AI model; and an input assistance device for inputting prompt sentences to assist in inputting data to the generative AI model. This enables a user to efficiently search for and compare desired products from multiple shopping sites and quickly re-search for products that meet additional requests, ultimately enabling a smooth purchase procedure on an online shopping site.

[0089] The "input device" is a means for a user to input the type of product they are considering purchasing, the desired functions and features, and their budget.

[0090] The "data transmission device" is a means for transmitting data input from an input device to a server.

[0091] The "data processing device" is a means for searching for relevant products from multiple product sales platforms and databases on an information network based on the data transmitted by the data transmission device, and comparing prices, functions, and features.

[0092] The "information generating device" is a means for providing the comparison results obtained by the data processing device to the user.

[0093] The "additional request input device" is a means for a user to input additional requests for information.

[0094] The "data reprocessing device" is a means for searching and comparing products again based on the data inputted by the additional request input device.

[0095] A "purchase procedure agent device" is a means for carrying out purchase procedures on an online shopping site on behalf of a user who has finally decided on the product to purchase, based on instructions from the user.

[0096] An "algorithm optimization device" is a means for optimizing a product search algorithm using a generative AI model.

[0097] An "input assistance device" is a means for inputting prompt sentences to assist in inputting data into a generative AI model.

[0098] This invention relates to a system that allows users to efficiently search, compare, and purchase desired products. This system is realized using the following hardware and software.

[0099] Hardware Configuration

[0100] 1. User device: This refers to the device on which a user enters product information and checks search results. Examples include PCs, smartphones, and tablets. These devices have input devices that provide interfaces for web forms and mobile applications.

[0101] 2. Server: A central device that performs various processes and communicates with terminals via the Internet. It analyzes data, searches for products, generates comparison results, reprocesses user requests for additional products, and handles purchasing procedures on behalf of users. The server is equipped with a high-performance processor and large-capacity storage.

[0102] Software Configuration

[0103] 1. Input device: Provides a web form or mobile application input screen for users to enter the type of product they are considering purchasing, desired functions and features, and their budget. This screen is built using web technologies such as HTML, CSS, and JavaScript (registered trademark).

[0104] 2. Data transmission device: This device has the function of transmitting product information entered by the user to the server. The input data is sent to the server using HTTP requests and Ajax technology.

[0105] 3. Data Processing Device: Runs on the server and uses product search algorithms and price comparison engines based on the received data to search and compare relevant products from multiple shopping sites and internal databases. This process is performed using scripting languages ​​such as Python and Ruby.

[0106] 4. Information generator: Based on the comparison results, a report is generated to be provided to the user. This is done using the Pandas library and an Excel file generation tool. The report includes the product name, price, and key features.

[0107] 5. Additional Request Input Device: Provides an interface for users to input additional requests for reports. This function can also be realized by a web form or a mobile application.

[0108] 6. Data reprocessing: Search for products again based on additional requests and update the comparison results. This reprocessing also uses the same technology as the data processing device.

[0109] 7. Purchase procedure agent: This device handles the purchase procedure on an online shopping site based on the instructions of the user who has finally decided on the product to purchase. It uses the shopping site's API to add the product to the cart and enters payment and delivery information.

[0110] 8. Algorithm Optimizer: Optimizes product search algorithms using generative AI models. Specifically, it uses machine learning libraries (TENSORFLOW (registered trademark) and PyTorch) to improve search and comparison accuracy.

[0111] 9. Input assistance device: This device has a function to assist input data to the generative AI model by inputting prompt sentences. This enables more accurate searches that meet the user's search needs.

[0112] Specific examples

[0113] For example, if a user enters "tablet, large screen, high resolution, 50,000" into the interface, the device will send this information to the server. The server will collect relevant product information from various shopping sites and compare prices and features. The server will generate a report based on this information and send it to the device. The user will then review the report and add a request for "something with a long battery life." The server will then search again using the new criteria and send the updated report back to the device. Finally, the user will select the desired product and request the purchase, and the server will complete the purchase process on the online shopping site.

[0114] This system allows users to efficiently search and compare desired products from multiple shopping sites, quickly search for additional products that meet additional requests, and ultimately allows users to smoothly proceed with the purchase process on online shopping sites.

[0115] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0116] Step 1: User Input

[0117] Through the interface, users input the type of product they want to purchase, the features and functions they want, and their budget. Specifically, they enter specific requirements, such as "tablet, large screen, high resolution, 50,000," into a web form or mobile application.

[0118] Input: User data including product type, desired functions, features, and budget

[0119] Output: The data necessary for product search is prepared on the user's device

[0120] Step 2: Send data

[0121] The terminal receives the product information entered by the user and sends it to the server using an HTTP request, packaging the user's input data in JSON format.

[0122] Input: User-entered data

[0123] Output: Product information data sent to the server

[0124] Step 3: Data analysis and product search

[0125] The server analyzes the data and extracts product information (e.g., "tablet, large screen, high resolution, 50,000"). It then searches for the relevant product on multiple product sales platforms on the information network and in an internal database. It uses a Python script to obtain data via APIs and web scraping.

[0126] Input: User's submitted product information data

[0127] Output: Product data collected from multiple shopping sites

[0128] Step 4: Compare product information

[0129] The server processes the collected product data using a comparison algorithm to compare products based on price, functionality, and features, for example, "Tablet A, Price: ¥48,000, Screen Size: 10 inches, Resolution: 4K" and "Tablet B, Price: ¥52,000, Screen Size: 10 inches, Resolution: Full HD."

[0130] Input: Collected product data

[0131] Output: Product data including comparison results

[0132] Step 5: Generate a report

[0133] The server generates a report based on the comparison results, which is provided to the user using the Pandas library and an Excel file generation tool. The report includes product names, prices, and key features.

[0134] Input: Product comparison data

[0135] Output: Generated report data

[0136] Step 6: Send and view the report

[0137] The server sends the generated report to the terminal, which then displays it on the user's screen, where the user can view the product information and check the details.

[0138] Input: Generated report data

[0139] Output: The report that is displayed on the user's screen

[0140] Step 7: Enter additional requests

[0141] The user reviews the displayed report and enters additional requests, for example, a specific request such as "long battery life," again entering the request into the interface.

[0142] Input: Additional requested data based on the report

[0143] Output: Additional requests recorded on the input device

[0144] Step 8: Submit your additional requests

[0145] The device receives the additional request and sends it to the server again using an HTTP request, with the additional request data packaged in JSON format.

[0146] Input: Additional requested data

[0147] Output: Additional requested data resent to the server

[0148] Step 9: Re-search and update the comparison results

[0149] The server uses the data reprocessing device to perform a new search based on the newly received additional request. At this time, it adds new conditions while taking into account the existing search results. It retrieves product data again and compares prices and features.

[0150] Input: Resubmitted additional request data

[0151] Output: Updated product data and comparison results

[0152] Step 10: Generate and send the update report

[0153] The server generates an updated report based on the results of the re-search and sends it to the terminal, which then displays the updated report to the user.

[0154] Input: Updated product data

[0155] Output: Updated report data

[0156] Step 11: Start Checkout

[0157] The user finally selects the desired product, enters purchase account information and delivery information, and requests the purchase procedure.

[0158] Input: Last selected product information and user purchase request data

[0159] Output: Purchase preparation data

[0160] Step 12: Purchasing on your behalf

[0161] The server uses a purchasing agent to complete the purchasing process through the API of the online shopping site, including adding products to the cart, entering payment information, and entering shipping information.

[0162] Input: Checkout preparation data and shopping site API

[0163] Output: Purchase completion notification and delivery arrangement information

[0164] The above is the specific flow of the system's processing steps and how it works. This system allows users to efficiently search, compare, and purchase the products they want.

[0165] (Application example 1)

[0166] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0167] Currently, there are many e-commerce sites, and users spend a lot of time and effort selecting the right product. It is also difficult to efficiently search, compare, and purchase products based on desired specifications and features. Furthermore, technology for recommending products to users is not yet fully developed. A new approach is needed to solve these issues and enable users to more efficiently purchase the products they desire.

[0168] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0169] In this invention, the server includes: a data input means for a user to input the type of product the user is considering purchasing, the desired specifications and features, and the user's budget; a data transmission means for transmitting the data input from the data input means to the server; a data processing means for searching for relevant products from multiple e-commerce sites and databases on the Internet based on the data transmitted by the data transmission means and comparing prices, specifications, and features; a report generation means for providing the user with the comparison results obtained by the data processing means; an additional request input means for the user to input additional requests for the report; a re-search data processing means for searching for and comparing products again based on the data input by the additional request input means; a purchase procedure agent means for performing the purchase procedure on the e-commerce site on behalf of the user who has finally decided on the product to purchase; a data processing means operating as part of the system; a product recommendation means using a generative AI model to recommend products based on their features and the user's requests; a prompt generation means for generating and inputting prompt sentences for the generative AI model; and an AI support means for searching, comparing, and recommending products based on the prompt generation means. This will enable users to efficiently search, compare, and purchase the products they want, improving their purchasing experience.

[0170] The "data input means" is a means for a user to input the type of product he or she is considering purchasing, the desired specifications and features, and the budget.

[0171] The "data transmission means" is a means for transmitting data inputted from the data input means to the server.

[0172] The "data processing means" is a means for searching for relevant products from multiple e-commerce sites and databases on the Internet based on the data transmitted by the data transmission means, and comparing prices, specifications, and features.

[0173] The "report generating means" is a means for generating a report to provide the user with the comparison results obtained by the data processing means.

[0174] The "additional request input means" is a means for the user to input additional requests for the report.

[0175] The "re-search data processing means" is a means for searching for and comparing products again based on the data inputted by the additional request input means.

[0176] The "purchase procedure proxy means" is a means for carrying out the purchase procedure on an e-commerce site on behalf of the user who has finally decided on the product to purchase, based on the user's instructions.

[0177] A "generative AI model" is an artificial intelligence model that recommends products based on data processing means, their characteristics, and user preferences.

[0178] A "prompt generation means" is a means for generating and inputting a prompt sentence to a generative AI model.

[0179] An "AI-enabled means" is an artificial intelligence-enabled means for product search, comparison, and recommendation based on the prompt generation means.

[0180] The present invention relates to a system that enables a user to efficiently search for, compare, and purchase desired products. The present invention is specifically implemented as follows.

[0181] First, the user enters the type of product they are considering purchasing, their desired specifications and features, and their budget through a data input means. The data input means is realized as an input screen for a smartphone application. Once the user enters this information, the data is sent from the device to the server via an HTTP request.

[0182] The server uses the received data to search for relevant products from multiple e-commerce sites on the Internet and internal databases. At this stage, the server compares products based on price, specifications, and features. The data processing means includes product search algorithms and price comparison engines.

[0183] Once the comparison results are obtained, the server uses a report generation means to generate a report summarizing these results. The report includes product names, prices, and key features, allowing the user to evaluate and compare products. This report is sent to the terminal and displayed on the user's smartphone screen.

[0184] The user can then input additional preferences based on the displayed report, for example, specifying a particular brand or requesting more detailed specifications, and this information is retransmitted to the server via the additional preference input means.

[0185] The server searches for products again based on the newly received request and updates the results. The re-search data processing means performs a re-search taking into account the additional conditions for the initial search results. The updated comparison results are again compiled by the report generation means, sent to the terminal, and displayed to the user again.

[0186] Finally, when the user decides on the desired product, the server uses a purchasing agent to complete the purchasing process on the e-commerce site. At this stage, the server adds the product to the cart through the e-commerce site's API and completes the purchasing process. This process includes payment procedures and inputting shipping information.

[0187] Furthermore, the server recommends products using the generative AI model. A prompt generation means generates and inputs prompt sentences for the generative AI model, and the AI ​​support means performs product search, comparison, and recommendation based on the prompt sentences, thereby enabling users to efficiently find more suitable products.

[0188] Specific examples are shown below.

[0189] If a user searches for "smartphone, large screen, high resolution, 60000," the server searches multiple e-commerce sites for matching smartphones, generates results, and displays them to the user. If the user adds "long battery life," the server performs a second search and presents products that match the criteria. In this way, users can efficiently search, compare, and purchase the products they want.

[0190] An example of a prompt for the generative AI model is to search for "smartphone, large screen, high resolution, 60000" and then search again with the additional criteria "long battery life."

[0191] This system allows users to efficiently search for products based on their desired criteria and make optimal purchasing decisions. In addition, by utilizing a generative AI model, users can receive product recommendations in a format that is easy for them to input, improving the purchasing experience.

[0192] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0193] Step 1:

[0194] A user launches a smartphone application and enters the type of product they are considering purchasing, their desired specifications and features, and their budget into the data input means. An example of input is "smartphone, large screen, high resolution, 60000." Once this input is made, the device constructs the input data in JSON format and sends it to the server as an HTTP POST request using the data transmission means. The input data is sent to the server's API endpoint.

[0195] Step 2:

[0196] The server analyzes the data received via the data transmission means. Based on the analyzed data, the server searches for relevant products from multiple e-commerce sites on the Internet and from an internal database. The data processing means aggregates the prices, specifications, and features of the searched products. The server performs product comparison calculations based on this aggregated data. Comparison result data is generated as output.

[0197] Step 3:

[0198] The server uses the comparison results obtained by the data processing means to activate the report generation means and generate a report to be provided to the user. The report includes the product name, price, and main features. The generated report is packaged in JSON format and sent back to the terminal. The terminal receives this data and displays the report on the user's smartphone screen.

[0199] Step 4:

[0200] The user checks the displayed report and inputs additional preferences (e.g., "longer battery life"). This additional preference data is sent to the server again through the additional preference input means. The input data is again constructed in JSON format and sent to the server as an HTTP POST request.

[0201] Step 5:

[0202] The server receives the data again and uses the re-search data processing means to search for products again, taking into account the newly received conditions. The search results are again accumulated and comparison operations are performed. The server then generates an updated report again using the report generation means. The re-generated report is again sent to the terminal. As an output, the updated report is displayed on the user's smartphone screen.

[0203] Step 6:

[0204] Once the user has finally selected the desired product and instructed the purchase through the purchasing procedure proxy, the server will use the API of the e-commerce site to carry out the purchasing procedure on their behalf. Specifically, the server will add the product to the cart, and handle payment procedures and input delivery information. As an output, a notification of the completion of the purchasing procedure will be sent to the user's device.

[0205] Step 7:

[0206] The server uses the generative AI model to launch a product recommendation means based on the user's preferences and input data. It then launches a prompt generation means to generate a prompt sentence for the generative AI model. Using the generated prompt sentence, the AI-enabled means searches, compares, and recommends products. An example of a prompt sentence is to enter "smartphone, large screen, high resolution, 60000" and search again with "long battery life" as an additional condition. As an output, recommended product information is presented to the user.

[0207] This allows users to efficiently search and compare the products they want and make better purchasing decisions.

[0208] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0209] This invention improves the user experience by combining an emotion engine with a system that allows users to efficiently search, compare, and purchase the products they desire. The specific configuration and operation of the system are described below.

[0210] First, the user enters the type of product they are considering purchasing, their desired functions and features, and their budget through an interface. This is done using a web form or a mobile application input screen. For example, they enter information such as "tablet, large screen, high resolution, 50,000 yen." The entered data is then sent from the device to the server. The data is sent via a communication protocol such as an HTTP POST request over the Internet.

[0211] The server then analyzes the received data and uses data processing means to search for the relevant products from each shopping site or internal database. This process uses techniques such as API calls and web scraping to obtain a list of products that match the criteria. The server then compares prices, functions, and features based on the obtained product list. This comparison uses a specific evaluation algorithm to analyze product prices, features, user ratings, etc.

[0212] After obtaining the comparison results, the server generates a comparison report using a report generation means, which includes product names, prices, main features, user ratings, etc. This report is sent to the terminal, and the user can use it to consider purchasing.

[0213] This is where the emotion engine, a key feature of the present invention, comes into play. The emotion engine analyzes the user's reactions and inputs while the report is displayed and recognizes the user's emotions. For example, it determines whether the user is happy, troubled, or anxious. The emotion engine can analyze keystroke patterns and speed, the frequency and timing of screen operations, and even facial expressions and voice using a camera or microphone.

[0214] Once the user's emotions are recognized, the server can adjust the product recommendations based on the results. For example, if the user is in a difficult situation, the server can narrow down the recommendations to only those with particularly high ratings. The emotion engine can also adapt the interface display. If the user is tired, the interface can be simplified and only the most important recommended products can be highlighted.

[0215] After the emotion engine has completed its adjustments, another report is sent to the user. The user can review this new report and enter more specific requests. For example, the user can enter "long battery life" as an additional request. The server then searches for products again based on the newly received request and updates the results. Using the reprocessing means, the server performs a new search taking into account the additional conditions added to the initial search results, and provides the user with a revised report.

[0216] Finally, once the user has decided on the product they want, the server uses a purchasing procedure proxy to carry out the purchasing procedure on the online shopping site. The server uses the shopping site's API to add the product to the cart and completes the payment procedure and input of shipping information. Once the purchasing procedure is complete, confirmation information is sent to the terminal and the user is notified that the purchase has been completed.

[0217] As a concrete example, if a user wants to purchase a "tablet," the system works as follows.

[0218] 1. The user enters "tablet, large screen, high resolution, 50,000 yen."

[0219] 2. The device sends this information to the server.

[0220] 3. The server searches for the appropriate tablet on each shopping site and compares prices and features.

[0221] 4. The server sends the generated report to the terminal, and the user checks the report.

[0222] 5. While viewing the report, the emotion engine detects the user's "anxiety."

[0223] 6. The server tailors the report to recommend only highly rated products based on user sentiment and provides a simplified interface.

[0224] 7. The user specifies "longer battery life" as an additional requirement.

[0225] 8. The server searches again based on the new criteria, updates the results, and provides the report again.

[0226] 9. The user selects a specific tablet and requests a purchase.

[0227] 10. The server uses the shopping site's API to complete the purchase process on behalf of the customer.

[0228] In this way, the present invention is a system that significantly improves the user experience by recognizing the user's emotions and adjusting product recommendations, supporting efficient and satisfying product selection and purchasing procedures.

[0229] The processing flow will be explained below.

[0230] Step 1:

[0231] Through the interface, users input the type of product they are considering purchasing, the desired features and functionality, and their budget. For example, they input "tablet, large screen, high resolution, 50,000 yen." This data input method is realized through a web form or a mobile application input screen.

[0232] Step 2:

[0233] The terminal transmits the data input by the user to the server, which can be achieved by an HTTP POST request or other communication protocol via the Internet.

[0234] Step 3:

[0235] The server analyzes the received data and extracts search criteria, such as "tablet," "large screen," "high resolution," and "under 50,000 yen."

[0236] Step 4:

[0237] The server uses data processing means to search for relevant products from multiple shopping sites and databases on the Internet, and obtains a list of products that meet the criteria using API calls and web scraping technology.

[0238] Step 5:

[0239] The server compares products from the retrieved product list based on price, functionality, and features. It uses a specific evaluation algorithm to analyze data such as the price, features, and user ratings of each product.

[0240] Step 6:

[0241] The server generates a report based on the comparison results, including product name, price, key features, and user ratings. The report is generated in simple text or HTML format.

[0242] Step 7:

[0243] The server sends the generated report to the terminal, where the user can check the report. The user can view the report displayed through the interface and evaluate the product.

[0244] Step 8:

[0245] While viewing a report, the emotion engine recognizes the user's emotions. For example, it analyzes keystroke patterns and speed, the frequency and timing of screen operations, and even facial expressions and voice using a camera and microphone. This determines the user's emotions, such as "joy," "confusion," or "anxiety."

[0246] Step 9:

[0247] The server adjusts product recommendations based on the user's emotions recognized by the emotion engine. For example, if the user is "confused," the server modifies the report to prioritize highly rated products.

[0248] Step 10:

[0249] The emotion engine allows the interface display to adapt according to the user's emotions. For example, if the user is feeling "tired," the interface will be simplified by highlighting only the main recommended products.

[0250] Step 11:

[0251] The server sends the adjusted report back to the terminal and displays it to the user, who then reviews the updated report and makes further evaluations.

[0252] Step 12:

[0253] The user inputs additional requests based on the report. For example, a request such as "a device with a long battery life" is input through the interface. The additional requests are sent from the terminal to the server.

[0254] Step 13:

[0255] The server searches for the product again based on the additional request, and uses the data reprocessing means to search for the product again based on the additional request and update the result.

[0256] Step 14:

[0257] The server generates a new report based on the updated comparison results and sends it to the terminal, where the user can check the revised report.

[0258] Step 15:

[0259] The user finally decides which products to purchase. Based on the report, the user selects the products to purchase and sends a final confirmation instruction to the server via the terminal.

[0260] Step 16:

[0261] The server uses a purchasing agent to process purchases on an online shopping site, adding products to the cart using the shopping site's API and entering payment and delivery information.

[0262] Step 17:

[0263] Once the purchase procedure is complete, the server sends confirmation information to the terminal, and the user receives a notification that the purchase has been completed.

[0264] The above are the specific processing steps of the system that combines the emotion engine of the present invention. This flow enables efficient product recommendations and purchasing procedures that take into account the user's emotions.

[0265] Example 2

[0266] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0267] In conventional online shopping systems, users are required to input the type of product they are considering purchasing, their desired functions, features, and budget, and then compare the search results. Furthermore, because the system does not take into account the user's emotional state, selecting the optimal product takes time and effort. Furthermore, the system also leaves users with psychological burdens when checking reports and anxiety about the operations involved in the purchase process. There is a need to address these issues and improve the user experience.

[0268] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes emotion engine means that analyzes the user's reactions and inputs while the report is being displayed and recognizes their emotions, adjustment means that adjusts product recommendations based on the concern results analyzed by the emotion engine means to improve the user experience, and purchase procedure proxy means that performs the purchase procedure on the sales website on behalf of the user based on instructions from the user who has finally decided on the product to purchase. This makes it possible to adjust product recommendations according to the user's emotional state and perform the purchase procedure on behalf of the user.

[0269] The "data input means" is a means for a user to input the type of product they are considering purchasing, the functions and features they desire, and their budget.

[0270] The "data transmission means" is a means for transmitting data inputted from the data input means to the server.

[0271] "Data processing means" refers to a means for searching for relevant products from multiple sales websites and information bases on the Internet based on the data transmitted by the data transmission means, and for comparing prices, functions and features.

[0272] The "report generating means" is a means for providing the user with the comparison results obtained by the data processing means.

[0273] The "emotion engine means" is a means for analyzing the user's reactions and inputs while the report is being displayed, and recognizing emotions.

[0274] The "adjustment means" is a means for adjusting product recommendations based on the concern results analyzed by the emotion engine means, thereby improving the user experience.

[0275] The "additional request input means" is a means for the user to input additional requests for the report.

[0276] The "data reprocessing means" is a means for searching for and comparing products again based on the data input by the additional request input means.

[0277] The "purchase procedure proxy means" is a means for carrying out the purchase procedure on the sales website on behalf of the user who has finally decided on the product to purchase, based on the instructions of the user.

[0278] This invention improves the user experience by combining an emotion engine with a system that allows users to efficiently search, compare, and purchase the products they desire. The specific configuration and operation of the system are described below.

[0279] First, the user enters the type of product they are considering purchasing, their desired functions and features, and their budget through an interface. This interface uses a web form or a mobile application input screen. As a specific example, let's say the user enters "tablet, large screen, high resolution, 50,000 yen." The interface used could be a React-based web form or a mobile application using Swift. The entered data is sent from the device to the server. At this time, a communication protocol such as an HTTP POST request via the Internet is used as the data transmission method. The communication protocol assumes HTTPS.

[0280] The server then analyzes the received data and searches for relevant products on each sales website or internal information base. This process uses API calls and web scraping techniques, including the Amazon API, Rakuten API, and Python's BeautifulSoup library. Based on the analyzed data, the server retrieves a list of products and compares prices, functions, and features. For this comparison, Python's Pandas library is used to calculate a product score and create a ranking list.

[0281] Based on the comparison results of the acquired data, the server generates a report that includes product name, price, key features, user ratings, etc. This report is generated in Markdown format and can be converted to the required format such as HTML or PDF. The server then sends the report to the terminal as an HTTP response.

[0282] This is where the emotion engine, a key feature of the present invention, comes into play. While the user is viewing the report, the emotion engine analyzes the user's reactions and inputs to recognize their emotions. Specifically, it collects typing speed and click patterns, and uses the device's camera and microphone to analyze the user's facial expressions and voice using OpenCV and the Google® Cloud Speech-to-Text API. This allows it to determine whether the user is happy, troubled, anxious, or other such emotions.

[0283] Once the user's emotions are recognized, the server adjusts the product recommendations based on the results. For example, if the user is in a difficult situation, the server will narrow down the recommendations to only highly rated products and provide a simplified interface. The user interface is dynamically changed using HTML / CSS and JavaScript.

[0284] After the emotion engine has completed its adjustments, another report is sent to the user. The user can review the new report and enter more specific requests. For example, they can enter "long battery life" as an additional request. The device again sends this information in JSON format to the server, and the server performs a new search. Using the reprocessing means, a new search is performed taking into account the additional conditions from the initial search results.

[0285] Finally, once the user has decided on the product they want, the server uses a purchasing procedure proxy to carry out the purchasing procedure on the online shopping site on their behalf. The server uses the shopping site's API to add the product to the cart and complete the payment procedure. Purchase confirmation information is then sent to the user as an email notification.

[0286] Below are some examples of prompt sentences to input to the generative AI model.

[0287] 1. I am looking for a tablet, so please tell me about products that meet the following criteria: large screen, high resolution, and under 50,000 yen.

[0288] 2. I would like to conduct a thorough sentiment analysis to find out how users react when they detect they are in a difficult situation.

[0289] 3. Generate new product search results that take into account the additional requirement "long battery life."

[0290] In this way, the present invention is a system that significantly improves the user experience by recognizing the user's emotions and adjusting product recommendations, supporting efficient and satisfying product selection and purchasing procedures.

[0291] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0292] Step 1:

[0293] Data Entry

[0294] Users enter the type of product they are considering purchasing, the features and functionality they are looking for, and their budget through an interface that can be a web form or a mobile application.

[0295] Input: User enters "tablet, large screen, high resolution, 50,000 yen."

[0296] Output: Input data ("Tablet, large screen, high resolution, 50,000 yen").

[0297] What happens: A user enters information into a React-based web form or a Swift-powered mobile application.

[0298] Step 2:

[0299] Data transmission

[0300] The device sends the entered data to the server using a communication protocol such as an HTTP POST request over the Internet.

[0301] Input: Input data ("Tablet, large screen, high resolution, 50,000 yen").

[0302] Output: The data sent to the server.

[0303] Specific operation: The terminal packs the user's input data into JSON format and sends it to the server using the HTTPS protocol.

[0304] Step 3:

[0305] Data analysis and product search

[0306] The server analyzes the received data and searches for relevant products on each sales website or internal information base, using API calls and web scraping techniques.

[0307] Input: Data sent to the server ("Tablet, large screen, high resolution, 50,000 yen").

[0308] Output: A list of matching products.

[0309] Specific operation: The server sends a search query to the Amazon API or Rakuten API based on the input data and retrieves a product list. Web scraping is performed using the Python BeautifulSoup library.

[0310] Step 4:

[0311] Product comparison

[0312] The server compares the prices, features, and characteristics of the products it receives, using a specific rating algorithm.

[0313] Input: A list of applicable products.

[0314] Output: Comparison results (including price, features, and characteristics).

[0315] Specific operation: The server generates a product comparison table using an algorithm (Python's Pandas library) that analyzes product prices, user ratings, and features, calculates a score for each product, and creates a ranked list.

[0316] Step 5:

[0317] Report Generation

[0318] The server generates a report based on the comparison results and sends it to the device, which includes product names, prices, key features, and user ratings.

[0319] Input: Comparison result.

[0320] Output: Report (including product name, price, key features, and user ratings).

[0321] Specific operation: The server generates a report in Markdown format, converts it to the required format such as HTML or PDF, and sends the generated report data to the terminal as an HTTP response.

[0322] Step 6:

[0323] Emotion analysis

[0324] The emotion engine analyzes the user's reactions and inputs while the report is displayed, and recognizes the user's emotions. It analyzes keystroke patterns and speed, frequency of screen operations, facial expressions and voice using a camera and microphone.

[0325] Input: User responses and input data (keystrokes, click patterns, facial expressions, voice, etc.).

[0326] Output: Sentiment analysis results (happiness, confusion, anxiety, etc.).

[0327] Specific operation: While the user is viewing the report, the system collects typing speed and click patterns. The system uses the device's camera and microphone to analyze the user's facial expressions and voice using OpenCV and the Google Cloud Speech-to-Text API.

[0328] Step 7:

[0329] Adjusted recommendations and adapted interface

[0330] The server adjusts product recommendations and adapts the interface based on the results of sentiment analysis.

[0331] Input: Sentiment analysis results.

[0332] Output: A tailored list of recommended products and an adapted interface.

[0333] Specific behavior: The server lists only highly rated products and switches to a simple UI. The user interface is dynamically changed using HTML / CSS and JavaScript.

[0334] Step 8:

[0335] Enter additional requests

[0336] The user inputs a new request, which is received by the server and the search is carried out again.

[0337] Input: User's additional requests (e.g. "something with a longer battery life").

[0338] Output: Updated product list and report.

[0339] Specific operation: The user enters additional requests, and the device again sends this information in JSON format to the server. The server then performs a new search based on the new conditions and updates the results.

[0340] Step 9:

[0341] Purchase procedure proxy

[0342] Once the user has decided on the product they want, the server will use the shopping site's API to carry out the purchase process on their behalf.

[0343] Input: The product decided by the user.

[0344] Output: Purchase confirmation information.

[0345] Specific operations: The server adds the selected product to the shopping cart on the sales website, completes the payment process, and sends the purchase confirmation information to the user via email.

[0346] In this way, by describing the processing flow at each step and the specific actions that correspond to them in detail, a system that improves the user experience is realized.

[0347] (Application example 2)

[0348] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0349] Conventional online shopping systems often fail to efficiently search for and compare products that users desire. Furthermore, product recommendations are not optimized based on user emotions and reactions, resulting in a lack of user experience. This can leave users feeling lost or confused when selecting or purchasing a product, resulting in no purchase at all. These issues need to be addressed.

[0350] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0351] In this invention, the server includes: data input means for a user to input the type of product the user is considering purchasing, the desired functions and features, and the user's budget; data transmission means for transmitting the data input from the data input means to the server; data processing means for searching for relevant products from multiple shopping sites and databases on the Internet based on the data transmitted by the data transmission means and comparing prices, functions, and features; report generation means for providing the user with the comparison results obtained by the data processing means; emotion recognition means for recognizing the user's emotions and dynamically adjusting product recommendations and interface display methods based on the results; additional request input means for the user to input additional requests for the report; data reprocessing means for searching for and comparing products again based on the data input by the additional request input means; and purchase procedure proxy means for carrying out the purchase procedure at the online shopping site on behalf of the user who has finally decided on the product to purchase. This enables the user to efficiently search for, compare, and purchase the product they desire, and the use of the emotion recognition means significantly improves the user experience, making it easier for the user to select an appropriate product without hesitation or confusion.

[0352] The "data input means" is a means for a user to input the type of product they are considering purchasing, the functions and features they desire, and their budget.

[0353] The "data transmission means" is a means for transmitting data inputted from the data input means to the server.

[0354] The "data processing means" is a means for searching for relevant products from multiple shopping sites and databases on the Internet based on the data transmitted by the data transmission means, and comparing prices, functions, and features.

[0355] The "report generating means" is a means for providing the user with the comparison results obtained by the data processing means.

[0356] The "emotion recognition means" is a means for recognizing the user's emotions and dynamically adjusting the product recommendations and interface display method based on the results.

[0357] The "additional request input means" is a means for the user to input additional requests for the report.

[0358] The "data reprocessing means" is a means for searching for and comparing products again based on the data input by the additional request input means.

[0359] The "purchase procedure proxy means" is a means for carrying out the purchase procedure on an online shopping site on behalf of the user who has finally decided on the product to purchase, based on instructions from the user.

[0360] This invention improves the user experience by combining emotion recognition means with a system that allows users to efficiently search, compare, and purchase desired products. The specific configuration and operation of the system are described below.

[0361] First, the user uses the data input means to input the type of product they are considering purchasing, their desired functions and features, and their budget. For example, they input information such as "tablet, large screen, high resolution, 50,000 yen." This data is then sent from the device to the server. The data transmission means is implemented via the Internet using a communication protocol such as an HTTP POST request.

[0362] Next, the server uses data processing means to search for relevant products from multiple shopping sites and internal databases based on the received data. This process uses techniques such as API calls and web scraping to obtain a list of products that match the criteria. The server then compares prices, functions, and features based on the obtained product list. This comparison process uses a specific evaluation algorithm to analyze product prices, features, user ratings, etc.

[0363] After obtaining the comparison results, the server generates a comparison report using a report generation means, which includes product names, prices, main features, user ratings, etc. This report is sent to the terminal, and the user can use it to consider purchasing.

[0364] This is where the emotion recognition means, a feature of the present invention, comes into play. The emotion recognition means analyzes the user's reactions and inputs while the report is displayed and recognizes the user's emotions. For example, it determines whether the user is happy, troubled, or anxious. The emotion recognition means can analyze key input patterns and speed, the frequency and timing of screen operations, and even facial expressions and voice using a camera or microphone. The hardware used includes the smartphone's camera and microphone. The software uses an emotion recognition API (e.g., OpenCV, DeepFace).

[0365] Once the user's emotions are recognized, the server can adjust the product recommendations based on the results. For example, if the user is in a difficult situation, the server can narrow down the recommendations to only highly rated products. The emotion recognition method can also adapt the interface display. If the user is tired, the interface can be simplified and only the most important recommended products can be highlighted.

[0366] After the emotion recognition process has completed its adjustments, another report is sent to the user. The user can review this new report and enter more specific requests. For example, they could enter "longer battery life" as an additional request. Examples of prompts include:

[0367] product_type = 'tablet'

[0368] features = ['large screen', 'high resolution', 'battery life']

[0369] budget = 50000

[0370] The server then searches for products again based on the newly received request, updates the results, and provides a new report.The server then uses the data reprocessing means to perform a new search that takes into account additional conditions added to the initial search results, and provides a revised report to the user.

[0371] Finally, once the user has decided on the product they want, the server uses a purchasing procedure proxy to carry out the purchasing procedure on the online shopping site. The server uses the shopping site's API to add the product to the cart and completes the payment procedure and input of shipping information. Once the purchasing procedure is complete, confirmation information is sent to the terminal and the user is notified that the purchase has been completed.

[0372] In this way, users can efficiently search, compare, and purchase desired products, and the use of emotion recognition means can significantly improve the user experience.

[0373] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0374] Step 1:

[0375] The user uses the data input means to input the type of product they are considering purchasing, their desired functions and features, and their budget. The input data includes information such as "tablet, large screen, high resolution, 50,000 yen." Based on this information, the device uses the data transmission means to send the data to the server via a communication protocol (e.g., HTTP POST request).

[0376] Step 2:

[0377] The server uses data processing means to search for relevant products from multiple shopping sites and databases based on the received user information. This search process utilizes API calls and web scraping technology.

[0378] Input: The user's desired product type, functions, features, and budget.

[0379] Output: A list of searched products.

[0380] Step 3:

[0381] The server uses a data processing means to compare prices, functions, and features based on the retrieved product list. In this comparison process, product prices, features, user ratings, etc. are analyzed and a specific rating algorithm is used.

[0382] Input: Searched product list.

[0383] Output: The comparison result.

[0384] Step 4:

[0385] The server uses the report generating means to generate a comparison report from the comparison results obtained by the data processing means, which includes product names, prices, main features, user ratings, etc.

[0386] Input: Comparison result.

[0387] Output: Comparison report.

[0388] Step 5:

[0389] The terminal receives the comparison report sent from the server and displays it to the user, who then considers purchasing based on the report.

[0390] Step 6:

[0391] While the report is being displayed, the emotion recognition means analyzes the pattern and speed of key input, the frequency and timing of screen operations, and even the user's facial expressions and voice using a camera and microphone to recognize the user's emotions.

[0392] Input: User input patterns, facial expressions, and voice.

[0393] Output: Emotion recognition result.

[0394] Step 7:

[0395] The server adjusts the product recommendations based on the user's emotions recognized by the emotion recognition means, such as prioritizing highly rated products and simplifying the interface.

[0396] Input: Emotion recognition results.

[0397] Output: Tailored recommendation results or interface.

[0398] Step 8:

[0399] The server regenerates a report based on the adjusted recommendations and the new interface and sends it to the terminal, where the user can review the report again and enter any additional requests using the data input means.

[0400] Input: Adjusted recommendation results.

[0401] Output: New comparison report or adjusted interface display.

[0402] Step 9:

[0403] The server searches for the relevant product again based on the additional request from the user, and performs a re-search using a data re-processing means that takes the additional conditions into consideration in the original search results.

[0404] Input: User's additional request.

[0405] Output: Updated product list and comparison results.

[0406] Step 10:

[0407] Once the user has finally decided on the product to purchase, the server uses the purchasing procedure proxy to add the product to the cart using the online shopping site's API, and completes the payment procedure and input of shipping information. Once the purchasing procedure is complete, confirmation information is sent to the terminal, and the user is notified that the purchase has been completed.

[0408] Input: The user's final selection.

[0409] Output: Purchase completion notification.

[0410] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0411] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0412] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0413] [Second embodiment]

[0414] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0415] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0416] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0417] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0418] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0419] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0420] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0421] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0422] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0423] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0424] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0425] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0426] The present invention relates to a system that enables users to efficiently search for, compare, and purchase desired products, and is configured as follows.

[0427] First, a user enters the type of product they are considering purchasing, their desired functions and features, and their budget through an interface. This data entry method is realized, for example, as a web form or an input screen in a mobile application. Once the user enters this information, the data is sent from the device to the server. The data transmission method is realized by an HTTP request or other communication protocol over the Internet.

[0428] The server analyzes the received data and uses data processing means to search for relevant products across multiple online shopping sites and internal databases. At this stage, the server compares products based on price, functionality, and features to find the best option. Data processing means include product search algorithms and price comparison engines.

[0429] Once the comparison results are obtained, the server uses the report generation means to generate a simple report summarizing these results. The report includes product names, prices, and key features, allowing the user to evaluate and compare products. This report is sent to the terminal and displayed on the user's screen.

[0430] The user can then input additional requests based on the displayed report, for example, specifying a particular brand or requesting more specific features, and this information is retransmitted to the server via the additional request input means.

[0431] The server searches for products again based on the newly received request and updates the comparison results. Using the data reprocessing means, a new search is performed taking into account the additional conditions added to the initial search results. The updated comparison results are compiled again by the report generation means, sent to the terminal, and displayed to the user again.

[0432] Finally, when the user decides on the desired product, the server uses a purchasing agent to carry out the purchasing procedure on the online shopping site. At this stage, the server adds the product to the cart through the shopping site's API and completes the purchase. This process includes payment procedures and inputting shipping information.

[0433] As a specific example, if a user wants to purchase a "tablet," the following operations are performed.

[0434] 1. The user types "tablet, large screen, high resolution, 50000" into the interface.

[0435] 2. The device sends this information to the server.

[0436] 3. The server searches for suitable tablets on multiple shopping sites and compares prices and features.

[0437] 4. The server sends the generated report to the terminal, and the user checks the report.

[0438] 5. The user inputs "a device with a longer battery life" as an additional request.

[0439] 6. The server searches again based on the new conditions, updates the results, and sends them to the device.

[0440] 7. The user selects a specific tablet and requests a purchase.

[0441] 8. The server processes the purchase on the shopping site and the purchase is completed.

[0442] As described above, the present invention is a system that enables users to efficiently select desired products and smoothly complete the purchasing procedure.

[0443] The processing flow will be explained below.

[0444] Step 1:

[0445] Through the interface, users input the type of product they are considering purchasing, their desired functions and features, and their budget. Specifically, they enter information such as "tablet, large screen, high resolution, 50,000 yen" on the input screen of a web form or mobile application.

[0446] Step 2:

[0447] The terminal sends the data entered by the user to the server. This is done over the Internet using a communication protocol such as an HTTP POST request.

[0448] Step 3:

[0449] The server analyzes the received data and extracts conditions such as "tablet," "large screen," "high resolution," and "under 50,000 yen," which are used in the next step.

[0450] Step 4:

[0451] The server uses data processing means to search for relevant products from multiple shopping sites on the Internet and internal databases, using techniques such as API calls and web scraping to obtain a list of products that meet the criteria.

[0452] Step 5:

[0453] The server compares products from the retrieved product list based on price, functionality, and features. Using a specific evaluation algorithm, it comprehensively compares and evaluates each product based on price, features, user ratings, etc.

[0454] Step 6:

[0455] The server generates a report based on the comparison results, including product names, prices, key features, and user ratings, in simple text or HTML format.

[0456] Step 7:

[0457] The server sends the generated report to the terminal, which then displays the report on the user's screen. The user can then review the product by checking the report.

[0458] Step 8:

[0459] The user inputs additional requests based on the report, for example, "longer battery life." The user again uses the interface to input the additional information, which is then sent to the server via the terminal.

[0460] Step 9:

[0461] The server searches for products again based on the additional request, and uses the data reprocessing means to search for products again based on the new conditions and update the comparison results.

[0462] Step 10:

[0463] The server generates a new report based on the updated comparison results and sends it to the terminal, where the user can view the revised report.

[0464] Step 11:

[0465] The user finally decides which products to purchase. The user selects the products to purchase based on the report and makes a final confirmation. After that, the user sends a purchase instruction to the server via the terminal.

[0466] Step 12:

[0467] The server uses a purchasing agent to process purchases on an online shopping site. The server makes an API request to the shopping site, adds products to the cart, and completes payment procedures and inputs shipping information.

[0468] Step 13:

[0469] Once the purchase procedure is complete, the server sends confirmation information to the terminal, and the user receives a notification that the purchase has been completed.

[0470] These are the specific processing steps of the system. This flow allows users to efficiently search and compare desired products and smoothly complete the purchasing process.

[0471] Example 1

[0472] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0473] The problem that this invention aims to solve is to enable users to efficiently browse multiple shopping sites and databases on the Internet and easily search, compare, and purchase desired products. Furthermore, by quickly performing re-searches based on the user's additional requests and selecting optimal products, and by carrying out the purchasing procedure on the user's behalf, the invention aims to reduce the user's operational burden and facilitate the purchasing process.

[0474] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0475] In this invention, the server includes an input device for a user to input the type of product the user is considering purchasing, the desired functions and features, and the user's budget; a data transmission device for transmitting the data input from the input device to the server; a data processing device for searching for relevant products from multiple product sales platforms and databases on an information network based on the data transmitted by the data transmission device and comparing prices, functions, and features; an information generation device for providing the user with the comparison results obtained by the data processing device; an additional request input device for the user to input additional requests regarding the information; a data reprocessing device for searching for and comparing products again based on the data input by the additional request input device; a purchase procedure agent device for performing a purchase procedure on an online shopping site based on instructions from a user who has finally decided on a product to purchase; an algorithm optimization device for optimizing a product search algorithm using a generative AI model; and an input assistance device for inputting prompt sentences to assist in inputting data to the generative AI model. This enables a user to efficiently search for and compare desired products from multiple shopping sites and quickly re-search for products that meet additional requests, ultimately enabling a smooth purchase procedure on an online shopping site.

[0476] The "input device" is a means for a user to input the type of product they are considering purchasing, the desired functions and features, and their budget.

[0477] The "data transmission device" is a means for transmitting data input from an input device to a server.

[0478] The "data processing device" is a means for searching for relevant products from multiple product sales platforms and databases on an information network based on the data transmitted by the data transmission device, and comparing prices, functions, and features.

[0479] The "information generating device" is a means for providing the comparison results obtained by the data processing device to the user.

[0480] The "additional request input device" is a means for a user to input additional requests for information.

[0481] The "data reprocessing device" is a means for searching and comparing products again based on the data inputted by the additional request input device.

[0482] A "purchase procedure agent device" is a means for carrying out purchase procedures on an online shopping site on behalf of a user who has finally decided on the product to purchase, based on instructions from the user.

[0483] An "algorithm optimization device" is a means for optimizing a product search algorithm using a generative AI model.

[0484] An "input assistance device" is a means for inputting prompt sentences to assist in inputting data into a generative AI model.

[0485] This invention relates to a system that allows users to efficiently search, compare, and purchase desired products. This system is realized using the following hardware and software.

[0486] Hardware Configuration

[0487] 1. User device: This refers to the device on which a user enters product information and checks search results. Examples include PCs, smartphones, and tablets. These devices have input devices that provide interfaces for web forms and mobile applications.

[0488] 2. Server: A central device that performs various processes and communicates with terminals via the Internet. It analyzes data, searches for products, generates comparison results, reprocesses user requests for additional products, and handles purchasing procedures on behalf of users. The server is equipped with a high-performance processor and large-capacity storage.

[0489] Software Configuration

[0490] 1. Input device: Provides a web form or mobile application input screen where users can enter the type of product they are considering purchasing, desired features and budget. This screen is built using web technologies such as HTML, CSS, and JavaScript.

[0491] 2. Data transmission device: This device has the function of transmitting product information entered by the user to the server. The input data is sent to the server using HTTP requests and Ajax technology.

[0492] 3. Data Processing Device: Runs on the server and uses product search algorithms and price comparison engines based on the received data to search and compare relevant products from multiple shopping sites and internal databases. This process is performed using scripting languages ​​such as Python and Ruby.

[0493] 4. Information generator: Based on the comparison results, a report is generated to be provided to the user. This is done using the Pandas library and an Excel file generation tool. The report includes the product name, price, and key features.

[0494] 5. Additional Request Input Device: Provides an interface for users to input additional requests for reports. This function can also be realized by a web form or a mobile application.

[0495] 6. Data reprocessing: Search for products again based on additional requests and update the comparison results. This reprocessing also uses the same technology as the data processing device.

[0496] 7. Purchase procedure agent: This device handles the purchase procedure on an online shopping site based on the instructions of the user who has finally decided on the product to purchase. It uses the shopping site's API to add the product to the cart and enters payment and delivery information.

[0497] 8. Algorithm Optimizer: Optimizes product search algorithms using generative AI models, specifically using machine learning libraries (TensorFlow and PyTorch) to improve search and comparison accuracy.

[0498] 9. Input assistance device: This device has a function to assist input data to the generative AI model by inputting prompt sentences. This enables more accurate searches that meet the user's search needs.

[0499] Specific examples

[0500] For example, if a user enters "tablet, large screen, high resolution, 50,000" into the interface, the device will send this information to the server. The server will collect relevant product information from various shopping sites and compare prices and features. The server will generate a report based on this information and send it to the device. The user will then review the report and add a request for "something with a long battery life." The server will then search again using the new criteria and send the updated report back to the device. Finally, the user will select the desired product and request the purchase, and the server will complete the purchase process on the online shopping site.

[0501] This system allows users to efficiently search and compare desired products from multiple shopping sites, quickly search for additional products that meet additional requests, and ultimately allows users to smoothly proceed with the purchase process on online shopping sites.

[0502] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0503] Step 1: User Input

[0504] Through the interface, users input the type of product they want to purchase, the features and functions they want, and their budget. Specifically, they enter specific requirements, such as "tablet, large screen, high resolution, 50,000," into a web form or mobile application.

[0505] Input: User data including product type, desired functions, features, and budget

[0506] Output: The data necessary for product search is prepared on the user's device

[0507] Step 2: Send data

[0508] The terminal receives the product information entered by the user and sends it to the server using an HTTP request, packaging the user's input data in JSON format.

[0509] Input: User-entered data

[0510] Output: Product information data sent to the server

[0511] Step 3: Data analysis and product search

[0512] The server analyzes the data and extracts product information (e.g., "tablet, large screen, high resolution, 50,000"). It then searches for the relevant product on multiple product sales platforms on the information network and in an internal database. It uses a Python script to obtain data via APIs and web scraping.

[0513] Input: User's submitted product information data

[0514] Output: Product data collected from multiple shopping sites

[0515] Step 4: Compare product information

[0516] The server processes the collected product data using a comparison algorithm to compare products based on price, functionality, and features, for example, "Tablet A, Price: ¥48,000, Screen Size: 10 inches, Resolution: 4K" and "Tablet B, Price: ¥52,000, Screen Size: 10 inches, Resolution: Full HD."

[0517] Input: Collected product data

[0518] Output: Product data including comparison results

[0519] Step 5: Generate a report

[0520] The server generates a report based on the comparison results, which is provided to the user using the Pandas library and an Excel file generation tool. The report includes product names, prices, and key features.

[0521] Input: Product comparison data

[0522] Output: Generated report data

[0523] Step 6: Send and view the report

[0524] The server sends the generated report to the terminal, which then displays it on the user's screen, where the user can view the product information and check the details.

[0525] Input: Generated report data

[0526] Output: The report that is displayed on the user's screen

[0527] Step 7: Enter additional requests

[0528] The user reviews the displayed report and enters additional requests, for example, a specific request such as "long battery life," again entering the request into the interface.

[0529] Input: Additional requested data based on the report

[0530] Output: Additional requests recorded on the input device

[0531] Step 8: Submit your additional requests

[0532] The device receives the additional request and sends it to the server again using an HTTP request, with the additional request data packaged in JSON format.

[0533] Input: Additional requested data

[0534] Output: Additional requested data resent to the server

[0535] Step 9: Re-search and update the comparison results

[0536] The server uses the data reprocessing device to perform a new search based on the newly received additional request. At this time, it adds new conditions while taking into account the existing search results. It retrieves product data again and compares prices and features.

[0537] Input: Resubmitted additional request data

[0538] Output: Updated product data and comparison results

[0539] Step 10: Generate and send the update report

[0540] The server generates an updated report based on the results of the re-search and sends it to the terminal, which then displays the updated report to the user.

[0541] Input: Updated product data

[0542] Output: Updated report data

[0543] Step 11: Start Checkout

[0544] The user finally selects the desired product, enters purchase account information and delivery information, and requests the purchase procedure.

[0545] Input: Last selected product information and user purchase request data

[0546] Output: Purchase preparation data

[0547] Step 12: Purchasing on your behalf

[0548] The server uses a purchasing agent to complete the purchasing process through the API of the online shopping site, including adding products to the cart, entering payment information, and entering shipping information.

[0549] Input: Checkout preparation data and shopping site API

[0550] Output: Purchase completion notification and delivery arrangement information

[0551] The above is the specific flow of the system's processing steps and how it works. This system allows users to efficiently search, compare, and purchase the products they want.

[0552] (Application example 1)

[0553] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0554] Currently, there are many e-commerce sites, and users spend a lot of time and effort selecting the right product. It is also difficult to efficiently search, compare, and purchase products based on desired specifications and features. Furthermore, technology for recommending products to users is not yet fully developed. A new approach is needed to solve these issues and enable users to more efficiently purchase the products they desire.

[0555] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0556] In this invention, the server includes: a data input means for a user to input the type of product the user is considering purchasing, the desired specifications and features, and the user's budget; a data transmission means for transmitting the data input from the data input means to the server; a data processing means for searching for relevant products from multiple e-commerce sites and databases on the Internet based on the data transmitted by the data transmission means and comparing prices, specifications, and features; a report generation means for providing the user with the comparison results obtained by the data processing means; an additional request input means for the user to input additional requests for the report; a re-search data processing means for searching for and comparing products again based on the data input by the additional request input means; a purchase procedure agent means for performing the purchase procedure on the e-commerce site on behalf of the user who has finally decided on the product to purchase; a data processing means operating as part of the system; a product recommendation means using a generative AI model to recommend products based on their features and the user's requests; a prompt generation means for generating and inputting prompt sentences for the generative AI model; and an AI support means for searching, comparing, and recommending products based on the prompt generation means. This will enable users to efficiently search, compare, and purchase the products they want, improving their purchasing experience.

[0557] The "data input means" is a means for a user to input the type of product he or she is considering purchasing, the desired specifications and features, and the budget.

[0558] The "data transmission means" is a means for transmitting data inputted from the data input means to the server.

[0559] The "data processing means" is a means for searching for relevant products from multiple e-commerce sites and databases on the Internet based on the data transmitted by the data transmission means, and comparing prices, specifications, and features.

[0560] The "report generating means" is a means for generating a report to provide the user with the comparison results obtained by the data processing means.

[0561] The "additional request input means" is a means for the user to input additional requests for the report.

[0562] The "re-search data processing means" is a means for searching for and comparing products again based on the data inputted by the additional request input means.

[0563] The "purchase procedure proxy means" is a means for carrying out the purchase procedure on an e-commerce site on behalf of the user who has finally decided on the product to purchase, based on the user's instructions.

[0564] A "generative AI model" is an artificial intelligence model that recommends products based on data processing means, their characteristics, and user preferences.

[0565] A "prompt generation means" is a means for generating and inputting a prompt sentence to a generative AI model.

[0566] An "AI-enabled means" is an artificial intelligence-enabled means for product search, comparison, and recommendation based on the prompt generation means.

[0567] The present invention relates to a system that enables a user to efficiently search for, compare, and purchase desired products. The present invention is specifically implemented as follows.

[0568] First, the user enters the type of product they are considering purchasing, their desired specifications and features, and their budget through a data input means. The data input means is realized as an input screen for a smartphone application. Once the user enters this information, the data is sent from the device to the server via an HTTP request.

[0569] The server uses the received data to search for relevant products from multiple e-commerce sites on the Internet and internal databases. At this stage, the server compares products based on price, specifications, and features. The data processing means includes product search algorithms and price comparison engines.

[0570] Once the comparison results are obtained, the server uses a report generation means to generate a report summarizing these results. The report includes product names, prices, and key features, allowing the user to evaluate and compare products. This report is sent to the terminal and displayed on the user's smartphone screen.

[0571] The user can then input additional preferences based on the displayed report, for example, specifying a particular brand or requesting more detailed specifications, and this information is retransmitted to the server via the additional preference input means.

[0572] The server searches for products again based on the newly received request and updates the results. The re-search data processing means performs a re-search taking into account the additional conditions for the initial search results. The updated comparison results are again compiled by the report generation means, sent to the terminal, and displayed to the user again.

[0573] Finally, when the user decides on the desired product, the server uses a purchasing agent to complete the purchasing process on the e-commerce site. At this stage, the server adds the product to the cart through the e-commerce site's API and completes the purchasing process. This process includes payment procedures and inputting shipping information.

[0574] Furthermore, the server recommends products using the generative AI model. A prompt generation means generates and inputs prompt sentences for the generative AI model, and the AI ​​support means performs product search, comparison, and recommendation based on the prompt sentences, thereby enabling users to efficiently find more suitable products.

[0575] Specific examples are shown below.

[0576] If a user searches for "smartphone, large screen, high resolution, 60000," the server searches multiple e-commerce sites for matching smartphones, generates results, and displays them to the user. If the user adds "long battery life," the server performs a second search and presents products that match the criteria. In this way, users can efficiently search, compare, and purchase the products they want.

[0577] An example of a prompt for the generative AI model is to search for "smartphone, large screen, high resolution, 60000" and then search again with the additional criteria "long battery life."

[0578] This system allows users to efficiently search for products based on their desired criteria and make optimal purchasing decisions. In addition, by utilizing a generative AI model, users can receive product recommendations in a format that is easy for them to input, improving the purchasing experience.

[0579] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0580] Step 1:

[0581] A user launches a smartphone application and enters the type of product they are considering purchasing, their desired specifications and features, and their budget into the data input means. An example of input is "smartphone, large screen, high resolution, 60000." Once this input is made, the device constructs the input data in JSON format and sends it to the server as an HTTP POST request using the data transmission means. The input data is sent to the server's API endpoint.

[0582] Step 2:

[0583] The server analyzes the data received via the data transmission means. Based on the analyzed data, the server searches for relevant products from multiple e-commerce sites on the Internet and from an internal database. The data processing means aggregates the prices, specifications, and features of the searched products. The server performs product comparison calculations based on this aggregated data. Comparison result data is generated as output.

[0584] Step 3:

[0585] The server uses the comparison results obtained by the data processing means to activate the report generation means and generate a report to be provided to the user. The report includes the product name, price, and main features. The generated report is packaged in JSON format and sent back to the terminal. The terminal receives this data and displays the report on the user's smartphone screen.

[0586] Step 4:

[0587] The user checks the displayed report and inputs additional preferences (e.g., "longer battery life"). This additional preference data is sent to the server again through the additional preference input means. The input data is again constructed in JSON format and sent to the server as an HTTP POST request.

[0588] Step 5:

[0589] The server receives the data again and uses the re-search data processing means to search for products again, taking into account the newly received conditions. The search results are again accumulated and comparison operations are performed. The server then generates an updated report again using the report generation means. The re-generated report is again sent to the terminal. As an output, the updated report is displayed on the user's smartphone screen.

[0590] Step 6:

[0591] Once the user has finally selected the desired product and instructed the purchase through the purchasing procedure proxy, the server will use the API of the e-commerce site to carry out the purchasing procedure on their behalf. Specifically, the server will add the product to the cart, and handle payment procedures and input delivery information. As an output, a notification of the completion of the purchasing procedure will be sent to the user's device.

[0592] Step 7:

[0593] The server uses the generative AI model to launch a product recommendation means based on the user's preferences and input data. It then launches a prompt generation means to generate a prompt sentence for the generative AI model. Using the generated prompt sentence, the AI-enabled means searches, compares, and recommends products. An example of a prompt sentence is to enter "smartphone, large screen, high resolution, 60000" and search again with "long battery life" as an additional condition. As an output, recommended product information is presented to the user.

[0594] This allows users to efficiently search and compare the products they want and make better purchasing decisions.

[0595] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0596] This invention improves the user experience by combining an emotion engine with a system that allows users to efficiently search, compare, and purchase the products they desire. The specific configuration and operation of the system are described below.

[0597] First, the user enters the type of product they are considering purchasing, their desired functions and features, and their budget through an interface. This is done using a web form or a mobile application input screen. For example, they enter information such as "tablet, large screen, high resolution, 50,000 yen." The entered data is then sent from the device to the server. The data is sent via a communication protocol such as an HTTP POST request over the Internet.

[0598] The server then analyzes the received data and uses data processing means to search for the relevant products from each shopping site or internal database. This process uses techniques such as API calls and web scraping to obtain a list of products that match the criteria. The server then compares prices, functions, and features based on the obtained product list. This comparison uses a specific evaluation algorithm to analyze product prices, features, user ratings, etc.

[0599] After obtaining the comparison results, the server generates a comparison report using a report generation means, which includes product names, prices, main features, user ratings, etc. This report is sent to the terminal, and the user can use it to consider purchasing.

[0600] This is where the emotion engine, a key feature of the present invention, comes into play. The emotion engine analyzes the user's reactions and inputs while the report is displayed and recognizes the user's emotions. For example, it determines whether the user is happy, troubled, or anxious. The emotion engine can analyze keystroke patterns and speed, the frequency and timing of screen operations, and even facial expressions and voice using a camera or microphone.

[0601] Once the user's emotions are recognized, the server can adjust the product recommendations based on the results. For example, if the user is in a difficult situation, the server can narrow down the recommendations to only those with particularly high ratings. The emotion engine can also adapt the interface display. If the user is tired, the interface can be simplified and only the most important recommended products can be highlighted.

[0602] After the emotion engine has completed its adjustments, another report is sent to the user. The user can review this new report and enter more specific requests. For example, the user can enter "long battery life" as an additional request. The server then searches for products again based on the newly received request and updates the results. Using the reprocessing means, the server performs a new search taking into account the additional conditions added to the initial search results, and provides the user with a revised report.

[0603] Finally, once the user has decided on the product they want, the server uses a purchasing procedure proxy to carry out the purchasing procedure on the online shopping site. The server uses the shopping site's API to add the product to the cart and completes the payment procedure and input of shipping information. Once the purchasing procedure is complete, confirmation information is sent to the terminal and the user is notified that the purchase has been completed.

[0604] As a concrete example, if a user wants to purchase a "tablet," the system works as follows.

[0605] 1. The user enters "tablet, large screen, high resolution, 50,000 yen."

[0606] 2. The device sends this information to the server.

[0607] 3. The server searches for the appropriate tablet on each shopping site and compares prices and features.

[0608] 4. The server sends the generated report to the terminal, and the user checks the report.

[0609] 5. While viewing the report, the emotion engine detects the user's "anxiety."

[0610] 6. The server tailors the report to recommend only highly rated products based on user sentiment and provides a simplified interface.

[0611] 7. The user specifies "longer battery life" as an additional requirement.

[0612] 8. The server searches again based on the new criteria, updates the results, and provides the report again.

[0613] 9. The user selects a specific tablet and requests a purchase.

[0614] 10. The server uses the shopping site's API to complete the purchase process on behalf of the customer.

[0615] In this way, the present invention is a system that significantly improves the user experience by recognizing the user's emotions and adjusting product recommendations, supporting efficient and satisfying product selection and purchasing procedures.

[0616] The processing flow will be explained below.

[0617] Step 1:

[0618] Through the interface, users input the type of product they are considering purchasing, the desired features and functionality, and their budget. For example, they input "tablet, large screen, high resolution, 50,000 yen." This data input method is realized through a web form or a mobile application input screen.

[0619] Step 2:

[0620] The terminal transmits the data input by the user to the server, which can be achieved by an HTTP POST request or other communication protocol via the Internet.

[0621] Step 3:

[0622] The server analyzes the received data and extracts search criteria, such as "tablet," "large screen," "high resolution," and "under 50,000 yen."

[0623] Step 4:

[0624] The server uses data processing means to search for relevant products from multiple shopping sites and databases on the Internet, and obtains a list of products that meet the criteria using API calls and web scraping technology.

[0625] Step 5:

[0626] The server compares products from the retrieved product list based on price, functionality, and features. It uses a specific evaluation algorithm to analyze data such as the price, features, and user ratings of each product.

[0627] Step 6:

[0628] The server generates a report based on the comparison results, including product name, price, key features, and user ratings. The report is generated in simple text or HTML format.

[0629] Step 7:

[0630] The server sends the generated report to the terminal, where the user can check the report. The user can view the report displayed through the interface and evaluate the product.

[0631] Step 8:

[0632] While viewing a report, the emotion engine recognizes the user's emotions. For example, it analyzes keystroke patterns and speed, the frequency and timing of screen operations, and even facial expressions and voice using a camera and microphone. This determines the user's emotions, such as "joy," "confusion," or "anxiety."

[0633] Step 9:

[0634] The server adjusts product recommendations based on the user's emotions recognized by the emotion engine. For example, if the user is "confused," the server modifies the report to prioritize highly rated products.

[0635] Step 10:

[0636] The emotion engine allows the interface display to adapt according to the user's emotions. For example, if the user is feeling "tired," the interface will be simplified by highlighting only the main recommended products.

[0637] Step 11:

[0638] The server sends the adjusted report back to the terminal and displays it to the user, who then reviews the updated report and makes further evaluations.

[0639] Step 12:

[0640] The user inputs additional requests based on the report. For example, a request such as "a device with a long battery life" is input through the interface. The additional requests are sent from the terminal to the server.

[0641] Step 13:

[0642] The server searches for the product again based on the additional request, and uses the data reprocessing means to search for the product again based on the additional request and update the result.

[0643] Step 14:

[0644] The server generates a new report based on the updated comparison results and sends it to the terminal, where the user can check the revised report.

[0645] Step 15:

[0646] The user finally decides which products to purchase. Based on the report, the user selects the products to purchase and sends a final confirmation instruction to the server via the terminal.

[0647] Step 16:

[0648] The server uses a purchasing agent to process purchases on an online shopping site, adding products to the cart using the shopping site's API and entering payment and delivery information.

[0649] Step 17:

[0650] Once the purchase procedure is complete, the server sends confirmation information to the terminal, and the user receives a notification that the purchase has been completed.

[0651] The above are the specific processing steps of the system that combines the emotion engine of the present invention. This flow enables efficient product recommendations and purchasing procedures that take into account the user's emotions.

[0652] Example 2

[0653] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0654] In conventional online shopping systems, users are required to input the type of product they are considering purchasing, their desired functions, features, and budget, and then compare the search results. Furthermore, because the system does not take into account the user's emotional state, selecting the optimal product takes time and effort. Furthermore, the system also leaves users with psychological burdens when checking reports and anxiety about the operations involved in the purchase process. There is a need to address these issues and improve the user experience.

[0655] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes emotion engine means that analyzes the user's reactions and inputs while the report is being displayed and recognizes their emotions, adjustment means that adjusts product recommendations based on the concern results analyzed by the emotion engine means to improve the user experience, and purchase procedure proxy means that performs the purchase procedure on the sales website on behalf of the user based on instructions from the user who has finally decided on the product to purchase. This makes it possible to adjust product recommendations according to the user's emotional state and perform the purchase procedure on behalf of the user.

[0656] The "data input means" is a means for a user to input the type of product they are considering purchasing, the functions and features they desire, and their budget.

[0657] The "data transmission means" is a means for transmitting data inputted from the data input means to the server.

[0658] "Data processing means" refers to a means for searching for relevant products from multiple sales websites and information bases on the Internet based on the data transmitted by the data transmission means, and for comparing prices, functions and features.

[0659] The "report generating means" is a means for providing the user with the comparison results obtained by the data processing means.

[0660] The "emotion engine means" is a means for analyzing the user's reactions and inputs while the report is being displayed, and recognizing emotions.

[0661] The "adjustment means" is a means for adjusting product recommendations based on the concern results analyzed by the emotion engine means, thereby improving the user experience.

[0662] The "additional request input means" is a means for the user to input additional requests for the report.

[0663] The "data reprocessing means" is a means for searching for and comparing products again based on the data input by the additional request input means.

[0664] The "purchase procedure proxy means" is a means for carrying out the purchase procedure on the sales website on behalf of the user who has finally decided on the product to purchase, based on the instructions of the user.

[0665] This invention improves the user experience by combining an emotion engine with a system that allows users to efficiently search, compare, and purchase the products they desire. The specific configuration and operation of the system are described below.

[0666] First, the user enters the type of product they are considering purchasing, their desired functions and features, and their budget through an interface. This interface uses a web form or a mobile application input screen. As a specific example, let's say the user enters "tablet, large screen, high resolution, 50,000 yen." The interface used could be a React-based web form or a mobile application using Swift. The entered data is sent from the device to the server. At this time, a communication protocol such as an HTTP POST request via the Internet is used as the data transmission method. The communication protocol assumes HTTPS.

[0667] The server then analyzes the received data and searches for relevant products on each sales website or internal information base. This process uses API calls and web scraping techniques, including the Amazon API, Rakuten API, and Python's BeautifulSoup library. Based on the analyzed data, the server retrieves a list of products and compares prices, functions, and features. For this comparison, Python's Pandas library is used to calculate a product score and create a ranking list.

[0668] Based on the comparison results of the acquired data, the server generates a report that includes product name, price, key features, user ratings, etc. This report is generated in Markdown format and can be converted to the required format such as HTML or PDF. The server then sends the report to the terminal as an HTTP response.

[0669] This is where the emotion engine, a key feature of the present invention, comes into play. While the user is viewing the report, the emotion engine analyzes the user's reactions and inputs to recognize their emotions. Specifically, it collects typing speed and click patterns, and uses the device's camera and microphone to analyze the user's facial expressions and voice using OpenCV and the Google Cloud Speech-to-Text API. This allows it to determine whether the user is happy, troubled, anxious, etc.

[0670] Once the user's emotions are recognized, the server adjusts the product recommendations based on the results. For example, if the user is in a difficult situation, the server will narrow down the recommendations to only highly rated products and provide a simplified interface. The user interface is dynamically changed using HTML / CSS and JavaScript.

[0671] After the emotion engine has completed its adjustments, another report is sent to the user. The user can review the new report and enter more specific requests. For example, they can enter "long battery life" as an additional request. The device again sends this information in JSON format to the server, and the server performs a new search. Using the reprocessing means, a new search is performed taking into account the additional conditions from the initial search results.

[0672] Finally, once the user has decided on the product they want, the server uses a purchasing procedure proxy to carry out the purchasing procedure on the online shopping site on their behalf. The server uses the shopping site's API to add the product to the cart and complete the payment procedure. Purchase confirmation information is then sent to the user as an email notification.

[0673] Below are some examples of prompt sentences to input to the generative AI model.

[0674] 1. I am looking for a tablet, so please tell me about products that meet the following criteria: large screen, high resolution, and under 50,000 yen.

[0675] 2. I would like to conduct a thorough sentiment analysis to find out how users react when they detect they are in a difficult situation.

[0676] 3. Generate new product search results that take into account the additional requirement "long battery life."

[0677] In this way, the present invention is a system that significantly improves the user experience by recognizing the user's emotions and adjusting product recommendations, supporting efficient and satisfying product selection and purchasing procedures.

[0678] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0679] Step 1:

[0680] Data Entry

[0681] Users enter the type of product they are considering purchasing, the features and functionality they are looking for, and their budget through an interface that can be a web form or a mobile application.

[0682] Input: User enters "tablet, large screen, high resolution, 50,000 yen."

[0683] Output: Input data ("Tablet, large screen, high resolution, 50,000 yen").

[0684] What happens: A user enters information into a React-based web form or a Swift-powered mobile application.

[0685] Step 2:

[0686] Data transmission

[0687] The device sends the entered data to the server using a communication protocol such as an HTTP POST request over the Internet.

[0688] Input: Input data ("Tablet, large screen, high resolution, 50,000 yen").

[0689] Output: The data sent to the server.

[0690] Specific operation: The terminal packs the user's input data into JSON format and sends it to the server using the HTTPS protocol.

[0691] Step 3:

[0692] Data analysis and product search

[0693] The server analyzes the received data and searches for relevant products on each sales website or internal information base, using API calls and web scraping techniques.

[0694] Input: Data sent to the server ("Tablet, large screen, high resolution, 50,000 yen").

[0695] Output: A list of matching products.

[0696] Specific operation: The server sends a search query to the Amazon API or Rakuten API based on the input data and retrieves a product list. Web scraping is performed using the Python BeautifulSoup library.

[0697] Step 4:

[0698] Product comparison

[0699] The server compares the prices, features, and characteristics of the products it receives, using a specific rating algorithm.

[0700] Input: A list of applicable products.

[0701] Output: Comparison results (including price, features, and characteristics).

[0702] Specific operation: The server generates a product comparison table using an algorithm (Python's Pandas library) that analyzes product prices, user ratings, and features, calculates a score for each product, and creates a ranked list.

[0703] Step 5:

[0704] Report Generation

[0705] The server generates a report based on the comparison results and sends it to the device, which includes product names, prices, key features, and user ratings.

[0706] Input: Comparison result.

[0707] Output: Report (including product name, price, key features, and user ratings).

[0708] Specific operation: The server generates a report in Markdown format, converts it to the required format such as HTML or PDF, and sends the generated report data to the terminal as an HTTP response.

[0709] Step 6:

[0710] Emotion analysis

[0711] The emotion engine analyzes the user's reactions and inputs while the report is displayed, and recognizes the user's emotions. It analyzes keystroke patterns and speed, frequency of screen operations, facial expressions and voice using a camera and microphone.

[0712] Input: User responses and input data (keystrokes, click patterns, facial expressions, voice, etc.).

[0713] Output: Sentiment analysis results (happiness, confusion, anxiety, etc.).

[0714] Specific operation: While the user is viewing the report, the system collects typing speed and click patterns. The system uses the device's camera and microphone to analyze the user's facial expressions and voice using OpenCV and the Google Cloud Speech-to-Text API.

[0715] Step 7:

[0716] Adjusted recommendations and adapted interface

[0717] The server adjusts product recommendations and adapts the interface based on the results of sentiment analysis.

[0718] Input: Sentiment analysis results.

[0719] Output: A tailored list of recommended products and an adapted interface.

[0720] Specific behavior: The server lists only highly rated products and switches to a simple UI. The user interface is dynamically changed using HTML / CSS and JavaScript.

[0721] Step 8:

[0722] Enter additional requests

[0723] The user inputs a new request, which is received by the server and the search is carried out again.

[0724] Input: User's additional requests (e.g. "something with a longer battery life").

[0725] Output: Updated product list and report.

[0726] Specific operation: The user enters additional requests, and the device again sends this information in JSON format to the server. The server then performs a new search based on the new conditions and updates the results.

[0727] Step 9:

[0728] Purchase procedure proxy

[0729] Once the user has decided on the product they want, the server will use the shopping site's API to carry out the purchase process on their behalf.

[0730] Input: The product decided by the user.

[0731] Output: Purchase confirmation information.

[0732] Specific operations: The server adds the selected product to the shopping cart on the sales website, completes the payment process, and sends the purchase confirmation information to the user via email.

[0733] In this way, by describing the processing flow at each step and the specific actions that correspond to them in detail, a system that improves the user experience is realized.

[0734] (Application example 2)

[0735] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0736] Conventional online shopping systems often fail to efficiently search for and compare products that users desire. Furthermore, product recommendations are not optimized based on user emotions and reactions, resulting in a lack of user experience. This can leave users feeling lost or confused when selecting or purchasing a product, resulting in no purchase at all. These issues need to be addressed.

[0737] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0738] In this invention, the server includes: data input means for a user to input the type of product the user is considering purchasing, the desired functions and features, and the user's budget; data transmission means for transmitting the data input from the data input means to the server; data processing means for searching for relevant products from multiple shopping sites and databases on the Internet based on the data transmitted by the data transmission means and comparing prices, functions, and features; report generation means for providing the user with the comparison results obtained by the data processing means; emotion recognition means for recognizing the user's emotions and dynamically adjusting product recommendations and interface display methods based on the results; additional request input means for the user to input additional requests for the report; data reprocessing means for searching for and comparing products again based on the data input by the additional request input means; and purchase procedure proxy means for carrying out the purchase procedure at the online shopping site on behalf of the user who has finally decided on the product to purchase. This enables the user to efficiently search for, compare, and purchase the product they desire, and the use of the emotion recognition means significantly improves the user experience, making it easier for the user to select an appropriate product without hesitation or confusion.

[0739] The "data input means" is a means for a user to input the type of product they are considering purchasing, the functions and features they desire, and their budget.

[0740] The "data transmission means" is a means for transmitting data inputted from the data input means to the server.

[0741] The "data processing means" is a means for searching for relevant products from multiple shopping sites and databases on the Internet based on the data transmitted by the data transmission means, and comparing prices, functions, and features.

[0742] The "report generating means" is a means for providing the user with the comparison results obtained by the data processing means.

[0743] The "emotion recognition means" is a means for recognizing the user's emotions and dynamically adjusting the product recommendations and interface display method based on the results.

[0744] The "additional request input means" is a means for the user to input additional requests for the report.

[0745] The "data reprocessing means" is a means for searching for and comparing products again based on the data input by the additional request input means.

[0746] The "purchase procedure proxy means" is a means for carrying out the purchase procedure on an online shopping site on behalf of the user who has finally decided on the product to purchase, based on instructions from the user.

[0747] This invention improves the user experience by combining emotion recognition means with a system that allows users to efficiently search, compare, and purchase desired products. The specific configuration and operation of the system are described below.

[0748] First, the user uses the data input means to input the type of product they are considering purchasing, their desired functions and features, and their budget. For example, they input information such as "tablet, large screen, high resolution, 50,000 yen." This data is then sent from the device to the server. The data transmission means is implemented via the Internet using a communication protocol such as an HTTP POST request.

[0749] Next, the server uses data processing means to search for relevant products from multiple shopping sites and internal databases based on the received data. This process uses techniques such as API calls and web scraping to obtain a list of products that match the criteria. The server then compares prices, functions, and features based on the obtained product list. This comparison process uses a specific evaluation algorithm to analyze product prices, features, user ratings, etc.

[0750] After obtaining the comparison results, the server generates a comparison report using a report generation means, which includes product names, prices, main features, user ratings, etc. This report is sent to the terminal, and the user can use it to consider purchasing.

[0751] This is where the emotion recognition means, a feature of the present invention, comes into play. The emotion recognition means analyzes the user's reactions and inputs while the report is displayed and recognizes the user's emotions. For example, it determines whether the user is happy, troubled, or anxious. The emotion recognition means can analyze key input patterns and speed, the frequency and timing of screen operations, and even facial expressions and voice using a camera or microphone. The hardware used includes the smartphone's camera and microphone. The software uses an emotion recognition API (e.g., OpenCV, DeepFace).

[0752] Once the user's emotions are recognized, the server can adjust the product recommendations based on the results. For example, if the user is in a difficult situation, the server can narrow down the recommendations to only highly rated products. The emotion recognition method can also adapt the interface display. If the user is tired, the interface can be simplified and only the most important recommended products can be highlighted.

[0753] After the emotion recognition process has completed its adjustments, another report is sent to the user. The user can review this new report and enter more specific requests. For example, they could enter "longer battery life" as an additional request. Examples of prompts include:

[0754] product_type = 'tablet'

[0755] features = ['large screen', 'high resolution', 'battery life']

[0756] budget = 50000

[0757] The server then searches for products again based on the newly received request, updates the results, and provides a new report.The server then uses the data reprocessing means to perform a new search that takes into account additional conditions added to the initial search results, and provides a revised report to the user.

[0758] Finally, once the user has decided on the product they want, the server uses a purchasing procedure proxy to carry out the purchasing procedure on the online shopping site. The server uses the shopping site's API to add the product to the cart and completes the payment procedure and input of shipping information. Once the purchasing procedure is complete, confirmation information is sent to the terminal and the user is notified that the purchase has been completed.

[0759] In this way, users can efficiently search, compare, and purchase desired products, and the use of emotion recognition means can significantly improve the user experience.

[0760] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0761] Step 1:

[0762] The user uses the data input means to input the type of product they are considering purchasing, their desired functions and features, and their budget. The input data includes information such as "tablet, large screen, high resolution, 50,000 yen." Based on this information, the device uses the data transmission means to send the data to the server via a communication protocol (e.g., HTTP POST request).

[0763] Step 2:

[0764] The server uses data processing means to search for relevant products from multiple shopping sites and databases based on the received user information. This search process utilizes API calls and web scraping technology.

[0765] Input: The user's desired product type, functions, features, and budget.

[0766] Output: A list of searched products.

[0767] Step 3:

[0768] The server uses a data processing means to compare prices, functions, and features based on the retrieved product list. In this comparison process, product prices, features, user ratings, etc. are analyzed and a specific rating algorithm is used.

[0769] Input: Searched product list.

[0770] Output: The comparison result.

[0771] Step 4:

[0772] The server uses the report generating means to generate a comparison report from the comparison results obtained by the data processing means, which includes product names, prices, main features, user ratings, etc.

[0773] Input: Comparison result.

[0774] Output: Comparison report.

[0775] Step 5:

[0776] The terminal receives the comparison report sent from the server and displays it to the user, who then considers purchasing based on the report.

[0777] Step 6:

[0778] While the report is being displayed, the emotion recognition means analyzes the pattern and speed of key input, the frequency and timing of screen operations, and even the user's facial expressions and voice using a camera and microphone to recognize the user's emotions.

[0779] Input: User input patterns, facial expressions, and voice.

[0780] Output: Emotion recognition result.

[0781] Step 7:

[0782] The server adjusts the product recommendations based on the user's emotions recognized by the emotion recognition means, such as prioritizing highly rated products and simplifying the interface.

[0783] Input: Emotion recognition results.

[0784] Output: Tailored recommendation results or interface.

[0785] Step 8:

[0786] The server regenerates a report based on the adjusted recommendations and the new interface and sends it to the terminal, where the user can review the report again and enter any additional requests using the data input means.

[0787] Input: Adjusted recommendation results.

[0788] Output: New comparison report or adjusted interface display.

[0789] Step 9:

[0790] The server searches for the relevant product again based on the additional request from the user, and performs a re-search using a data re-processing means that takes the additional conditions into consideration in the original search results.

[0791] Input: User's additional request.

[0792] Output: Updated product list and comparison results.

[0793] Step 10:

[0794] Once the user has finally decided on the product to purchase, the server uses the purchasing procedure proxy to add the product to the cart using the online shopping site's API, and completes the payment procedure and input of shipping information. Once the purchasing procedure is complete, confirmation information is sent to the terminal, and the user is notified that the purchase has been completed.

[0795] Input: The user's final selection.

[0796] Output: Purchase completion notification.

[0797] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0798] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0799] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0800] [Third embodiment]

[0801] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0802] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0803] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0804] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0805] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0806] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0807] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0808] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0809] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0810] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0811] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0812] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0813] The present invention relates to a system that enables users to efficiently search for, compare, and purchase desired products, and is configured as follows.

[0814] First, a user enters the type of product they are considering purchasing, their desired functions and features, and their budget through an interface. This data entry method is realized, for example, as a web form or an input screen in a mobile application. Once the user enters this information, the data is sent from the device to the server. The data transmission method is realized by an HTTP request or other communication protocol over the Internet.

[0815] The server analyzes the received data and uses data processing means to search for relevant products across multiple online shopping sites and internal databases. At this stage, the server compares products based on price, functionality, and features to find the best option. Data processing means include product search algorithms and price comparison engines.

[0816] Once the comparison results are obtained, the server uses the report generation means to generate a simple report summarizing these results. The report includes product names, prices, and key features, allowing the user to evaluate and compare products. This report is sent to the terminal and displayed on the user's screen.

[0817] The user can then input additional requests based on the displayed report, for example, specifying a particular brand or requesting more specific features, and this information is retransmitted to the server via the additional request input means.

[0818] The server searches for products again based on the newly received request and updates the comparison results. Using the data reprocessing means, a new search is performed taking into account the additional conditions added to the initial search results. The updated comparison results are compiled again by the report generation means, sent to the terminal, and displayed to the user again.

[0819] Finally, when the user decides on the desired product, the server uses a purchasing agent to carry out the purchasing procedure on the online shopping site. At this stage, the server adds the product to the cart through the shopping site's API and completes the purchase. This process includes payment procedures and inputting shipping information.

[0820] As a specific example, if a user wants to purchase a "tablet," the following operations are performed.

[0821] 1. The user types "tablet, large screen, high resolution, 50000" into the interface.

[0822] 2. The device sends this information to the server.

[0823] 3. The server searches for suitable tablets on multiple shopping sites and compares prices and features.

[0824] 4. The server sends the generated report to the terminal, and the user checks the report.

[0825] 5. The user inputs "a device with a longer battery life" as an additional request.

[0826] 6. The server searches again based on the new conditions, updates the results, and sends them to the device.

[0827] 7. The user selects a specific tablet and requests a purchase.

[0828] 8. The server processes the purchase on the shopping site and the purchase is completed.

[0829] As described above, the present invention is a system that enables users to efficiently select desired products and smoothly complete the purchasing procedure.

[0830] The processing flow will be explained below.

[0831] Step 1:

[0832] Through the interface, users input the type of product they are considering purchasing, their desired functions and features, and their budget. Specifically, they enter information such as "tablet, large screen, high resolution, 50,000 yen" on the input screen of a web form or mobile application.

[0833] Step 2:

[0834] The terminal sends the data entered by the user to the server. This is done over the Internet using a communication protocol such as an HTTP POST request.

[0835] Step 3:

[0836] The server analyzes the received data and extracts conditions such as "tablet," "large screen," "high resolution," and "under 50,000 yen," which are used in the next step.

[0837] Step 4:

[0838] The server uses data processing means to search for relevant products from multiple shopping sites on the Internet and internal databases, using techniques such as API calls and web scraping to obtain a list of products that meet the criteria.

[0839] Step 5:

[0840] The server compares products from the retrieved product list based on price, functionality, and features. Using a specific evaluation algorithm, it comprehensively compares and evaluates each product based on price, features, user ratings, etc.

[0841] Step 6:

[0842] The server generates a report based on the comparison results, including product names, prices, key features, and user ratings, in simple text or HTML format.

[0843] Step 7:

[0844] The server sends the generated report to the terminal, which then displays the report on the user's screen. The user can then review the product by checking the report.

[0845] Step 8:

[0846] The user inputs additional requests based on the report, for example, "longer battery life." The user again uses the interface to input the additional information, which is then sent to the server via the terminal.

[0847] Step 9:

[0848] The server searches for products again based on the additional request, and uses the data reprocessing means to search for products again based on the new conditions and update the comparison results.

[0849] Step 10:

[0850] The server generates a new report based on the updated comparison results and sends it to the terminal, where the user can view the revised report.

[0851] Step 11:

[0852] The user finally decides which products to purchase. The user selects the products to purchase based on the report and makes a final confirmation. After that, the user sends a purchase instruction to the server via the terminal.

[0853] Step 12:

[0854] The server uses a purchasing agent to process purchases on an online shopping site. The server makes an API request to the shopping site, adds products to the cart, and completes payment procedures and inputs shipping information.

[0855] Step 13:

[0856] Once the purchase procedure is complete, the server sends confirmation information to the terminal, and the user receives a notification that the purchase has been completed.

[0857] These are the specific processing steps of the system. This flow allows users to efficiently search and compare desired products and smoothly complete the purchasing process.

[0858] Example 1

[0859] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0860] The problem that this invention aims to solve is to enable users to efficiently browse multiple shopping sites and databases on the Internet and easily search, compare, and purchase desired products. Furthermore, by quickly performing re-searches based on the user's additional requests and selecting optimal products, and by carrying out the purchasing procedure on the user's behalf, the invention aims to reduce the user's operational burden and facilitate the purchasing process.

[0861] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0862] In this invention, the server includes an input device for a user to input the type of product the user is considering purchasing, the desired functions and features, and the user's budget; a data transmission device for transmitting the data input from the input device to the server; a data processing device for searching for relevant products from multiple product sales platforms and databases on an information network based on the data transmitted by the data transmission device and comparing prices, functions, and features; an information generation device for providing the user with the comparison results obtained by the data processing device; an additional request input device for the user to input additional requests regarding the information; a data reprocessing device for searching for and comparing products again based on the data input by the additional request input device; a purchase procedure agent device for performing a purchase procedure on an online shopping site based on instructions from a user who has finally decided on a product to purchase; an algorithm optimization device for optimizing a product search algorithm using a generative AI model; and an input assistance device for inputting prompt sentences to assist in inputting data to the generative AI model. This enables a user to efficiently search for and compare desired products from multiple shopping sites and quickly re-search for products that meet additional requests, ultimately enabling a smooth purchase procedure on an online shopping site.

[0863] The "input device" is a means for a user to input the type of product they are considering purchasing, the desired functions and features, and their budget.

[0864] The "data transmission device" is a means for transmitting data input from an input device to a server.

[0865] The "data processing device" is a means for searching for relevant products from multiple product sales platforms and databases on an information network based on the data transmitted by the data transmission device, and comparing prices, functions, and features.

[0866] The "information generating device" is a means for providing the comparison results obtained by the data processing device to the user.

[0867] The "additional request input device" is a means for a user to input additional requests for information.

[0868] The "data reprocessing device" is a means for searching and comparing products again based on the data inputted by the additional request input device.

[0869] A "purchase procedure agent device" is a means for carrying out purchase procedures on an online shopping site on behalf of a user who has finally decided on the product to purchase, based on instructions from the user.

[0870] An "algorithm optimization device" is a means for optimizing a product search algorithm using a generative AI model.

[0871] An "input assistance device" is a means for inputting prompt sentences to assist in inputting data into a generative AI model.

[0872] This invention relates to a system that allows users to efficiently search, compare, and purchase desired products. This system is realized using the following hardware and software.

[0873] Hardware Configuration

[0874] 1. User device: This refers to the device on which a user enters product information and checks search results. Examples include PCs, smartphones, and tablets. These devices have input devices that provide interfaces for web forms and mobile applications.

[0875] 2. Server: A central device that performs various processes and communicates with terminals via the Internet. It analyzes data, searches for products, generates comparison results, reprocesses user requests for additional products, and handles purchasing procedures on behalf of users. The server is equipped with a high-performance processor and large-capacity storage.

[0876] Software Configuration

[0877] 1. Input device: Provides a web form or mobile application input screen where users can enter the type of product they are considering purchasing, desired features and budget. This screen is built using web technologies such as HTML, CSS, and JavaScript.

[0878] 2. Data transmission device: This device has the function of transmitting product information entered by the user to the server. The input data is sent to the server using HTTP requests and Ajax technology.

[0879] 3. Data Processing Device: Runs on the server and uses product search algorithms and price comparison engines based on the received data to search and compare relevant products from multiple shopping sites and internal databases. This process is performed using scripting languages ​​such as Python and Ruby.

[0880] 4. Information generator: Based on the comparison results, a report is generated to be provided to the user. This is done using the Pandas library and an Excel file generation tool. The report includes the product name, price, and key features.

[0881] 5. Additional Request Input Device: Provides an interface for users to input additional requests for reports. This function can also be realized by a web form or a mobile application.

[0882] 6. Data reprocessing: Search for products again based on additional requests and update the comparison results. This reprocessing also uses the same technology as the data processing device.

[0883] 7. Purchase procedure agent: This device handles the purchase procedure on an online shopping site based on the instructions of the user who has finally decided on the product to purchase. It uses the shopping site's API to add the product to the cart and enters payment and delivery information.

[0884] 8. Algorithm Optimizer: Optimizes product search algorithms using generative AI models, specifically using machine learning libraries (TensorFlow and PyTorch) to improve search and comparison accuracy.

[0885] 9. Input assistance device: This device has a function to assist input data to the generative AI model by inputting prompt sentences. This enables more accurate searches that meet the user's search needs.

[0886] Specific examples

[0887] For example, if a user enters "tablet, large screen, high resolution, 50,000" into the interface, the device will send this information to the server. The server will collect relevant product information from various shopping sites and compare prices and features. The server will generate a report based on this information and send it to the device. The user will then review the report and add a request for "something with a long battery life." The server will then search again using the new criteria and send the updated report back to the device. Finally, the user will select the desired product and request the purchase, and the server will complete the purchase process on the online shopping site.

[0888] This system allows users to efficiently search and compare desired products from multiple shopping sites, quickly search for additional products that meet additional requests, and ultimately allows users to smoothly proceed with the purchase process on online shopping sites.

[0889] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0890] Step 1: User Input

[0891] Through the interface, users input the type of product they want to purchase, the features and functions they want, and their budget. Specifically, they enter specific requirements, such as "tablet, large screen, high resolution, 50,000," into a web form or mobile application.

[0892] Input: User data including product type, desired functions, features, and budget

[0893] Output: The data necessary for product search is prepared on the user's device

[0894] Step 2: Send data

[0895] The terminal receives the product information entered by the user and sends it to the server using an HTTP request, packaging the user's input data in JSON format.

[0896] Input: User-entered data

[0897] Output: Product information data sent to the server

[0898] Step 3: Data analysis and product search

[0899] The server analyzes the data and extracts product information (e.g., "tablet, large screen, high resolution, 50,000"). It then searches for the relevant product on multiple product sales platforms on the information network and in an internal database. It uses a Python script to obtain data via APIs and web scraping.

[0900] Input: User's submitted product information data

[0901] Output: Product data collected from multiple shopping sites

[0902] Step 4: Compare product information

[0903] The server processes the collected product data using a comparison algorithm to compare products based on price, functionality, and features, for example, "Tablet A, Price: ¥48,000, Screen Size: 10 inches, Resolution: 4K" and "Tablet B, Price: ¥52,000, Screen Size: 10 inches, Resolution: Full HD."

[0904] Input: Collected product data

[0905] Output: Product data including comparison results

[0906] Step 5: Generate a report

[0907] The server generates a report based on the comparison results, which is provided to the user using the Pandas library and an Excel file generation tool. The report includes product names, prices, and key features.

[0908] Input: Product comparison data

[0909] Output: Generated report data

[0910] Step 6: Send and view the report

[0911] The server sends the generated report to the terminal, which then displays it on the user's screen, where the user can view the product information and check the details.

[0912] Input: Generated report data

[0913] Output: The report that is displayed on the user's screen

[0914] Step 7: Enter additional requests

[0915] The user reviews the displayed report and enters additional requests, for example, a specific request such as "long battery life," again entering the request into the interface.

[0916] Input: Additional requested data based on the report

[0917] Output: Additional requests recorded on the input device

[0918] Step 8: Submit your additional requests

[0919] The device receives the additional request and sends it to the server again using an HTTP request, with the additional request data packaged in JSON format.

[0920] Input: Additional requested data

[0921] Output: Additional requested data resent to the server

[0922] Step 9: Re-search and update the comparison results

[0923] The server uses the data reprocessing device to perform a new search based on the newly received additional request. At this time, it adds new conditions while taking into account the existing search results. It retrieves product data again and compares prices and features.

[0924] Input: Resubmitted additional request data

[0925] Output: Updated product data and comparison results

[0926] Step 10: Generate and send the update report

[0927] The server generates an updated report based on the results of the re-search and sends it to the terminal, which then displays the updated report to the user.

[0928] Input: Updated product data

[0929] Output: Updated report data

[0930] Step 11: Start Checkout

[0931] The user finally selects the desired product, enters purchase account information and delivery information, and requests the purchase procedure.

[0932] Input: Last selected product information and user purchase request data

[0933] Output: Purchase preparation data

[0934] Step 12: Purchasing on your behalf

[0935] The server uses a purchasing agent to complete the purchasing process through the API of the online shopping site, including adding products to the cart, entering payment information, and entering shipping information.

[0936] Input: Checkout preparation data and shopping site API

[0937] Output: Purchase completion notification and delivery arrangement information

[0938] The above is the specific flow of the system's processing steps and how it works. This system allows users to efficiently search, compare, and purchase the products they want.

[0939] (Application example 1)

[0940] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0941] Currently, there are many e-commerce sites, and users spend a lot of time and effort selecting the right product. It is also difficult to efficiently search, compare, and purchase products based on desired specifications and features. Furthermore, technology for recommending products to users is not yet fully developed. A new approach is needed to solve these issues and enable users to more efficiently purchase the products they desire.

[0942] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0943] In this invention, the server includes: a data input means for a user to input the type of product the user is considering purchasing, the desired specifications and features, and the user's budget; a data transmission means for transmitting the data input from the data input means to the server; a data processing means for searching for relevant products from multiple e-commerce sites and databases on the Internet based on the data transmitted by the data transmission means and comparing prices, specifications, and features; a report generation means for providing the user with the comparison results obtained by the data processing means; an additional request input means for the user to input additional requests for the report; a re-search data processing means for searching for and comparing products again based on the data input by the additional request input means; a purchase procedure agent means for performing the purchase procedure on the e-commerce site on behalf of the user who has finally decided on the product to purchase; a data processing means operating as part of the system; a product recommendation means using a generative AI model to recommend products based on their features and the user's requests; a prompt generation means for generating and inputting prompt sentences for the generative AI model; and an AI support means for searching, comparing, and recommending products based on the prompt generation means. This will enable users to efficiently search, compare, and purchase the products they want, improving their purchasing experience.

[0944] The "data input means" is a means for a user to input the type of product he or she is considering purchasing, the desired specifications and features, and the budget.

[0945] The "data transmission means" is a means for transmitting data inputted from the data input means to the server.

[0946] The "data processing means" is a means for searching for relevant products from multiple e-commerce sites and databases on the Internet based on the data transmitted by the data transmission means, and comparing prices, specifications, and features.

[0947] The "report generating means" is a means for generating a report to provide the user with the comparison results obtained by the data processing means.

[0948] The "additional request input means" is a means for the user to input additional requests for the report.

[0949] The "re-search data processing means" is a means for searching for and comparing products again based on the data inputted by the additional request input means.

[0950] The "purchase procedure proxy means" is a means for carrying out the purchase procedure on an e-commerce site on behalf of the user who has finally decided on the product to purchase, based on the user's instructions.

[0951] A "generative AI model" is an artificial intelligence model that recommends products based on data processing means, their characteristics, and user preferences.

[0952] A "prompt generation means" is a means for generating and inputting a prompt sentence to a generative AI model.

[0953] An "AI-enabled means" is an artificial intelligence-enabled means for product search, comparison, and recommendation based on the prompt generation means.

[0954] The present invention relates to a system that enables a user to efficiently search for, compare, and purchase desired products. The present invention is specifically implemented as follows.

[0955] First, the user enters the type of product they are considering purchasing, their desired specifications and features, and their budget through a data input means. The data input means is realized as an input screen for a smartphone application. Once the user enters this information, the data is sent from the device to the server via an HTTP request.

[0956] The server uses the received data to search for relevant products from multiple e-commerce sites on the Internet and internal databases. At this stage, the server compares products based on price, specifications, and features. The data processing means includes product search algorithms and price comparison engines.

[0957] Once the comparison results are obtained, the server uses a report generation means to generate a report summarizing these results. The report includes product names, prices, and key features, allowing the user to evaluate and compare products. This report is sent to the terminal and displayed on the user's smartphone screen.

[0958] The user can then input additional preferences based on the displayed report, for example, specifying a particular brand or requesting more detailed specifications, and this information is retransmitted to the server via the additional preference input means.

[0959] The server searches for products again based on the newly received request and updates the results. The re-search data processing means performs a re-search taking into account the additional conditions for the initial search results. The updated comparison results are again compiled by the report generation means, sent to the terminal, and displayed to the user again.

[0960] Finally, when the user decides on the desired product, the server uses a purchasing agent to complete the purchasing process on the e-commerce site. At this stage, the server adds the product to the cart through the e-commerce site's API and completes the purchasing process. This process includes payment procedures and inputting shipping information.

[0961] Furthermore, the server recommends products using the generative AI model. A prompt generation means generates and inputs prompt sentences for the generative AI model, and the AI ​​support means performs product search, comparison, and recommendation based on the prompt sentences, thereby enabling users to efficiently find more suitable products.

[0962] Specific examples are shown below.

[0963] If a user searches for "smartphone, large screen, high resolution, 60000," the server searches multiple e-commerce sites for matching smartphones, generates results, and displays them to the user. If the user adds "long battery life," the server performs a second search and presents products that match the criteria. In this way, users can efficiently search, compare, and purchase the products they want.

[0964] An example of a prompt for the generative AI model is to search for "smartphone, large screen, high resolution, 60000" and then search again with the additional criteria "long battery life."

[0965] This system allows users to efficiently search for products based on their desired criteria and make optimal purchasing decisions. In addition, by utilizing a generative AI model, users can receive product recommendations in a format that is easy for them to input, improving the purchasing experience.

[0966] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0967] Step 1:

[0968] A user launches a smartphone application and enters the type of product they are considering purchasing, their desired specifications and features, and their budget into the data input means. An example of input is "smartphone, large screen, high resolution, 60000." Once this input is made, the device constructs the input data in JSON format and sends it to the server as an HTTP POST request using the data transmission means. The input data is sent to the server's API endpoint.

[0969] Step 2:

[0970] The server analyzes the data received via the data transmission means. Based on the analyzed data, the server searches for relevant products from multiple e-commerce sites on the Internet and from an internal database. The data processing means aggregates the prices, specifications, and features of the searched products. The server performs product comparison calculations based on this aggregated data. Comparison result data is generated as output.

[0971] Step 3:

[0972] The server uses the comparison results obtained by the data processing means to activate the report generation means and generate a report to be provided to the user. The report includes the product name, price, and main features. The generated report is packaged in JSON format and sent back to the terminal. The terminal receives this data and displays the report on the user's smartphone screen.

[0973] Step 4:

[0974] The user checks the displayed report and inputs additional preferences (e.g., "longer battery life"). This additional preference data is sent to the server again through the additional preference input means. The input data is again constructed in JSON format and sent to the server as an HTTP POST request.

[0975] Step 5:

[0976] The server receives the data again and uses the re-search data processing means to search for products again, taking into account the newly received conditions. The search results are again accumulated and comparison operations are performed. The server then generates an updated report again using the report generation means. The re-generated report is again sent to the terminal. As an output, the updated report is displayed on the user's smartphone screen.

[0977] Step 6:

[0978] Once the user has finally selected the desired product and instructed the purchase through the purchasing procedure proxy, the server will use the API of the e-commerce site to carry out the purchasing procedure on their behalf. Specifically, the server will add the product to the cart, and handle payment procedures and input delivery information. As an output, a notification of the completion of the purchasing procedure will be sent to the user's device.

[0979] Step 7:

[0980] The server uses the generative AI model to launch a product recommendation means based on the user's preferences and input data. It then launches a prompt generation means to generate a prompt sentence for the generative AI model. Using the generated prompt sentence, the AI-enabled means searches, compares, and recommends products. An example of a prompt sentence is to enter "smartphone, large screen, high resolution, 60000" and search again with "long battery life" as an additional condition. As an output, recommended product information is presented to the user.

[0981] This allows users to efficiently search and compare the products they want and make better purchasing decisions.

[0982] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0983] This invention improves the user experience by combining an emotion engine with a system that allows users to efficiently search, compare, and purchase the products they desire. The specific configuration and operation of the system are described below.

[0984] First, the user enters the type of product they are considering purchasing, their desired functions and features, and their budget through an interface. This is done using a web form or a mobile application input screen. For example, they enter information such as "tablet, large screen, high resolution, 50,000 yen." The entered data is then sent from the device to the server. The data is sent via a communication protocol such as an HTTP POST request over the Internet.

[0985] The server then analyzes the received data and uses data processing means to search for the relevant products from each shopping site or internal database. This process uses techniques such as API calls and web scraping to obtain a list of products that match the criteria. The server then compares prices, functions, and features based on the obtained product list. This comparison uses a specific evaluation algorithm to analyze product prices, features, user ratings, etc.

[0986] After obtaining the comparison results, the server generates a comparison report using a report generation means, which includes product names, prices, main features, user ratings, etc. This report is sent to the terminal, and the user can use it to consider purchasing.

[0987] This is where the emotion engine, a key feature of the present invention, comes into play. The emotion engine analyzes the user's reactions and inputs while the report is displayed and recognizes the user's emotions. For example, it determines whether the user is happy, troubled, or anxious. The emotion engine can analyze keystroke patterns and speed, the frequency and timing of screen operations, and even facial expressions and voice using a camera or microphone.

[0988] Once the user's emotions are recognized, the server can adjust the product recommendations based on the results. For example, if the user is in a difficult situation, the server can narrow down the recommendations to only those with particularly high ratings. The emotion engine can also adapt the interface display. If the user is tired, the interface can be simplified and only the most important recommended products can be highlighted.

[0989] After the emotion engine has completed its adjustments, another report is sent to the user. The user can review this new report and enter more specific requests. For example, the user can enter "long battery life" as an additional request. The server then searches for products again based on the newly received request and updates the results. Using the reprocessing means, the server performs a new search taking into account the additional conditions added to the initial search results, and provides the user with a revised report.

[0990] Finally, once the user has decided on the product they want, the server uses a purchasing procedure proxy to carry out the purchasing procedure on the online shopping site. The server uses the shopping site's API to add the product to the cart and completes the payment procedure and input of shipping information. Once the purchasing procedure is complete, confirmation information is sent to the terminal and the user is notified that the purchase has been completed.

[0991] As a concrete example, if a user wants to purchase a "tablet," the system works as follows.

[0992] 1. The user enters "tablet, large screen, high resolution, 50,000 yen."

[0993] 2. The device sends this information to the server.

[0994] 3. The server searches for the appropriate tablet on each shopping site and compares prices and features.

[0995] 4. The server sends the generated report to the terminal, and the user checks the report.

[0996] 5. While viewing the report, the emotion engine detects the user's "anxiety."

[0997] 6. The server tailors the report to recommend only highly rated products based on user sentiment and provides a simplified interface.

[0998] 7. The user specifies "longer battery life" as an additional requirement.

[0999] 8. The server searches again based on the new criteria, updates the results, and provides the report again.

[1000] 9. The user selects a specific tablet and requests a purchase.

[1001] 10. The server uses the shopping site's API to complete the purchase process on behalf of the customer.

[1002] In this way, the present invention is a system that significantly improves the user experience by recognizing the user's emotions and adjusting product recommendations, supporting efficient and satisfying product selection and purchasing procedures.

[1003] The processing flow will be explained below.

[1004] Step 1:

[1005] Through the interface, users input the type of product they are considering purchasing, the desired features and functionality, and their budget. For example, they input "tablet, large screen, high resolution, 50,000 yen." This data input method is realized through a web form or a mobile application input screen.

[1006] Step 2:

[1007] The terminal transmits the data input by the user to the server, which can be achieved by an HTTP POST request or other communication protocol via the Internet.

[1008] Step 3:

[1009] The server analyzes the received data and extracts search criteria, such as "tablet," "large screen," "high resolution," and "under 50,000 yen."

[1010] Step 4:

[1011] The server uses data processing means to search for relevant products from multiple shopping sites and databases on the Internet, and obtains a list of products that meet the criteria using API calls and web scraping technology.

[1012] Step 5:

[1013] The server compares products from the retrieved product list based on price, functionality, and features. It uses a specific evaluation algorithm to analyze data such as the price, features, and user ratings of each product.

[1014] Step 6:

[1015] The server generates a report based on the comparison results, including product name, price, key features, and user ratings. The report is generated in simple text or HTML format.

[1016] Step 7:

[1017] The server sends the generated report to the terminal, where the user can check the report. The user can view the report displayed through the interface and evaluate the product.

[1018] Step 8:

[1019] While viewing a report, the emotion engine recognizes the user's emotions. For example, it analyzes keystroke patterns and speed, the frequency and timing of screen operations, and even facial expressions and voice using a camera and microphone. This determines the user's emotions, such as "joy," "confusion," or "anxiety."

[1020] Step 9:

[1021] The server adjusts product recommendations based on the user's emotions recognized by the emotion engine. For example, if the user is "confused," the server modifies the report to prioritize highly rated products.

[1022] Step 10:

[1023] The emotion engine allows the interface display to adapt according to the user's emotions. For example, if the user is feeling "tired," the interface will be simplified by highlighting only the main recommended products.

[1024] Step 11:

[1025] The server sends the adjusted report back to the terminal and displays it to the user, who then reviews the updated report and makes further evaluations.

[1026] Step 12:

[1027] The user inputs additional requests based on the report. For example, a request such as "a device with a long battery life" is input through the interface. The additional requests are sent from the terminal to the server.

[1028] Step 13:

[1029] The server searches for the product again based on the additional request, and uses the data reprocessing means to search for the product again based on the additional request and update the result.

[1030] Step 14:

[1031] The server generates a new report based on the updated comparison results and sends it to the terminal, where the user can check the revised report.

[1032] Step 15:

[1033] The user finally decides which products to purchase. Based on the report, the user selects the products to purchase and sends a final confirmation instruction to the server via the terminal.

[1034] Step 16:

[1035] The server uses a purchasing agent to process purchases on an online shopping site, adding products to the cart using the shopping site's API and entering payment and delivery information.

[1036] Step 17:

[1037] Once the purchase procedure is complete, the server sends confirmation information to the terminal, and the user receives a notification that the purchase has been completed.

[1038] The above are the specific processing steps of the system that combines the emotion engine of the present invention. This flow enables efficient product recommendations and purchasing procedures that take into account the user's emotions.

[1039] Example 2

[1040] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1041] In conventional online shopping systems, users are required to input the type of product they are considering purchasing, their desired functions, features, and budget, and then compare the search results. Furthermore, because the system does not take into account the user's emotional state, selecting the optimal product takes time and effort. Furthermore, the system also leaves users with psychological burdens when checking reports and anxiety about the operations involved in the purchase process. There is a need to address these issues and improve the user experience.

[1042] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes emotion engine means that analyzes the user's reactions and inputs while the report is being displayed and recognizes their emotions, adjustment means that adjusts product recommendations based on the concern results analyzed by the emotion engine means to improve the user experience, and purchase procedure proxy means that performs the purchase procedure on the sales website on behalf of the user based on instructions from the user who has finally decided on the product to purchase. This makes it possible to adjust product recommendations according to the user's emotional state and perform the purchase procedure on behalf of the user.

[1043] The "data input means" is a means for a user to input the type of product they are considering purchasing, the functions and features they desire, and their budget.

[1044] The "data transmission means" is a means for transmitting data inputted from the data input means to the server.

[1045] "Data processing means" refers to a means for searching for relevant products from multiple sales websites and information bases on the Internet based on the data transmitted by the data transmission means, and for comparing prices, functions and features.

[1046] The "report generating means" is a means for providing the user with the comparison results obtained by the data processing means.

[1047] The "emotion engine means" is a means for analyzing the user's reactions and inputs while the report is being displayed, and recognizing emotions.

[1048] The "adjustment means" is a means for adjusting product recommendations based on the concern results analyzed by the emotion engine means, thereby improving the user experience.

[1049] The "additional request input means" is a means for the user to input additional requests for the report.

[1050] The "data reprocessing means" is a means for searching for and comparing products again based on the data input by the additional request input means.

[1051] The "purchase procedure proxy means" is a means for carrying out the purchase procedure on the sales website on behalf of the user who has finally decided on the product to purchase, based on the instructions of the user.

[1052] This invention improves the user experience by combining an emotion engine with a system that allows users to efficiently search, compare, and purchase the products they desire. The specific configuration and operation of the system are described below.

[1053] First, the user enters the type of product they are considering purchasing, their desired functions and features, and their budget through an interface. This interface uses a web form or a mobile application input screen. As a specific example, let's say the user enters "tablet, large screen, high resolution, 50,000 yen." The interface used could be a React-based web form or a mobile application using Swift. The entered data is sent from the device to the server. At this time, a communication protocol such as an HTTP POST request via the Internet is used as the data transmission method. The communication protocol assumes HTTPS.

[1054] The server then analyzes the received data and searches for relevant products on each sales website or internal information base. This process uses API calls and web scraping techniques, including the Amazon API, Rakuten API, and Python's BeautifulSoup library. Based on the analyzed data, the server retrieves a list of products and compares prices, functions, and features. For this comparison, Python's Pandas library is used to calculate a product score and create a ranking list.

[1055] Based on the comparison results of the acquired data, the server generates a report that includes product name, price, key features, user ratings, etc. This report is generated in Markdown format and can be converted to the required format such as HTML or PDF. The server then sends the report to the terminal as an HTTP response.

[1056] This is where the emotion engine, a key feature of the present invention, comes into play. While the user is viewing the report, the emotion engine analyzes the user's reactions and inputs to recognize their emotions. Specifically, it collects typing speed and click patterns, and uses the device's camera and microphone to analyze the user's facial expressions and voice using OpenCV and the Google Cloud Speech-to-Text API. This allows it to determine whether the user is happy, troubled, anxious, etc.

[1057] Once the user's emotions are recognized, the server adjusts the product recommendations based on the results. For example, if the user is in a difficult situation, the server will narrow down the recommendations to only highly rated products and provide a simplified interface. The user interface is dynamically changed using HTML / CSS and JavaScript.

[1058] After the emotion engine has completed its adjustments, another report is sent to the user. The user can review the new report and enter more specific requests. For example, they can enter "long battery life" as an additional request. The device again sends this information in JSON format to the server, and the server performs a new search. Using the reprocessing means, a new search is performed taking into account the additional conditions from the initial search results.

[1059] Finally, once the user has decided on the product they want, the server uses a purchasing procedure proxy to carry out the purchasing procedure on the online shopping site on their behalf. The server uses the shopping site's API to add the product to the cart and complete the payment procedure. Purchase confirmation information is then sent to the user as an email notification.

[1060] Below are some examples of prompt sentences to input to the generative AI model.

[1061] 1. I am looking for a tablet, so please tell me about products that meet the following criteria: large screen, high resolution, and under 50,000 yen.

[1062] 2. I would like to conduct a thorough sentiment analysis to find out how users react when they detect they are in a difficult situation.

[1063] 3. Generate new product search results that take into account the additional requirement "long battery life."

[1064] In this way, the present invention is a system that significantly improves the user experience by recognizing the user's emotions and adjusting product recommendations, supporting efficient and satisfying product selection and purchasing procedures.

[1065] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1066] Step 1:

[1067] Data Entry

[1068] Users enter the type of product they are considering purchasing, the features and functionality they are looking for, and their budget through an interface that can be a web form or a mobile application.

[1069] Input: User enters "tablet, large screen, high resolution, 50,000 yen."

[1070] Output: Input data ("Tablet, large screen, high resolution, 50,000 yen").

[1071] What happens: A user enters information into a React-based web form or a Swift-powered mobile application.

[1072] Step 2:

[1073] Data transmission

[1074] The device sends the entered data to the server using a communication protocol such as an HTTP POST request over the Internet.

[1075] Input: Input data ("Tablet, large screen, high resolution, 50,000 yen").

[1076] Output: The data sent to the server.

[1077] Specific operation: The terminal packs the user's input data into JSON format and sends it to the server using the HTTPS protocol.

[1078] Step 3:

[1079] Data analysis and product search

[1080] The server analyzes the received data and searches for relevant products on each sales website or internal information base, using API calls and web scraping techniques.

[1081] Input: Data sent to the server ("Tablet, large screen, high resolution, 50,000 yen").

[1082] Output: A list of matching products.

[1083] Specific operation: The server sends a search query to the Amazon API or Rakuten API based on the input data and retrieves a product list. Web scraping is performed using the Python BeautifulSoup library.

[1084] Step 4:

[1085] Product comparison

[1086] The server compares the prices, features, and characteristics of the products it receives, using a specific rating algorithm.

[1087] Input: A list of applicable products.

[1088] Output: Comparison results (including price, features, and characteristics).

[1089] Specific operation: The server generates a product comparison table using an algorithm (Python's Pandas library) that analyzes product prices, user ratings, and features, calculates a score for each product, and creates a ranked list.

[1090] Step 5:

[1091] Report Generation

[1092] The server generates a report based on the comparison results and sends it to the device, which includes product names, prices, key features, and user ratings.

[1093] Input: Comparison result.

[1094] Output: Report (including product name, price, key features, and user ratings).

[1095] Specific operation: The server generates a report in Markdown format, converts it to the required format such as HTML or PDF, and sends the generated report data to the terminal as an HTTP response.

[1096] Step 6:

[1097] Emotion analysis

[1098] The emotion engine analyzes the user's reactions and inputs while the report is displayed, and recognizes the user's emotions. It analyzes keystroke patterns and speed, frequency of screen operations, facial expressions and voice using a camera and microphone.

[1099] Input: User responses and input data (keystrokes, click patterns, facial expressions, voice, etc.).

[1100] Output: Sentiment analysis results (happiness, confusion, anxiety, etc.).

[1101] Specific operation: While the user is viewing the report, the system collects typing speed and click patterns. The system uses the device's camera and microphone to analyze the user's facial expressions and voice using OpenCV and the Google Cloud Speech-to-Text API.

[1102] Step 7:

[1103] Adjusted recommendations and adapted interface

[1104] The server adjusts product recommendations and adapts the interface based on the results of sentiment analysis.

[1105] Input: Sentiment analysis results.

[1106] Output: A tailored list of recommended products and an adapted interface.

[1107] Specific behavior: The server lists only highly rated products and switches to a simple UI. The user interface is dynamically changed using HTML / CSS and JavaScript.

[1108] Step 8:

[1109] Enter additional requests

[1110] The user inputs a new request, which is received by the server and the search is carried out again.

[1111] Input: User's additional requests (e.g. "something with a longer battery life").

[1112] Output: Updated product list and report.

[1113] Specific operation: The user enters additional requests, and the device again sends this information in JSON format to the server. The server then performs a new search based on the new conditions and updates the results.

[1114] Step 9:

[1115] Purchase procedure proxy

[1116] Once the user has decided on the product they want, the server will use the shopping site's API to carry out the purchase process on their behalf.

[1117] Input: The product decided by the user.

[1118] Output: Purchase confirmation information.

[1119] Specific operations: The server adds the selected product to the shopping cart on the sales website, completes the payment process, and sends the purchase confirmation information to the user via email.

[1120] In this way, by describing the processing flow at each step and the specific actions that correspond to them in detail, a system that improves the user experience is realized.

[1121] (Application example 2)

[1122] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1123] Conventional online shopping systems often fail to efficiently search for and compare products that users desire. Furthermore, product recommendations are not optimized based on user emotions and reactions, resulting in a lack of user experience. This can leave users feeling lost or confused when selecting or purchasing a product, resulting in no purchase at all. These issues need to be addressed.

[1124] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1125] In this invention, the server includes: data input means for a user to input the type of product the user is considering purchasing, the desired functions and features, and the user's budget; data transmission means for transmitting the data input from the data input means to the server; data processing means for searching for relevant products from multiple shopping sites and databases on the Internet based on the data transmitted by the data transmission means and comparing prices, functions, and features; report generation means for providing the user with the comparison results obtained by the data processing means; emotion recognition means for recognizing the user's emotions and dynamically adjusting product recommendations and interface display methods based on the results; additional request input means for the user to input additional requests for the report; data reprocessing means for searching for and comparing products again based on the data input by the additional request input means; and purchase procedure proxy means for carrying out the purchase procedure at the online shopping site on behalf of the user who has finally decided on the product to purchase. This enables the user to efficiently search for, compare, and purchase the product they desire, and the use of the emotion recognition means significantly improves the user experience, making it easier for the user to select an appropriate product without hesitation or confusion.

[1126] The "data input means" is a means for a user to input the type of product they are considering purchasing, the functions and features they desire, and their budget.

[1127] The "data transmission means" is a means for transmitting data inputted from the data input means to the server.

[1128] The "data processing means" is a means for searching for relevant products from multiple shopping sites and databases on the Internet based on the data transmitted by the data transmission means, and comparing prices, functions, and features.

[1129] The "report generating means" is a means for providing the user with the comparison results obtained by the data processing means.

[1130] The "emotion recognition means" is a means for recognizing the user's emotions and dynamically adjusting the product recommendations and interface display method based on the results.

[1131] The "additional request input means" is a means for the user to input additional requests for the report.

[1132] The "data reprocessing means" is a means for searching for and comparing products again based on the data input by the additional request input means.

[1133] The "purchase procedure proxy means" is a means for carrying out the purchase procedure on an online shopping site on behalf of the user who has finally decided on the product to purchase, based on instructions from the user.

[1134] This invention improves the user experience by combining emotion recognition means with a system that allows users to efficiently search, compare, and purchase desired products. The specific configuration and operation of the system are described below.

[1135] First, the user uses the data input means to input the type of product they are considering purchasing, their desired functions and features, and their budget. For example, they input information such as "tablet, large screen, high resolution, 50,000 yen." This data is then sent from the device to the server. The data transmission means is implemented via the Internet using a communication protocol such as an HTTP POST request.

[1136] Next, the server uses data processing means to search for relevant products from multiple shopping sites and internal databases based on the received data. This process uses techniques such as API calls and web scraping to obtain a list of products that match the criteria. The server then compares prices, functions, and features based on the obtained product list. This comparison process uses a specific evaluation algorithm to analyze product prices, features, user ratings, etc.

[1137] After obtaining the comparison results, the server generates a comparison report using a report generation means, which includes product names, prices, main features, user ratings, etc. This report is sent to the terminal, and the user can use it to consider purchasing.

[1138] This is where the emotion recognition means, a feature of the present invention, comes into play. The emotion recognition means analyzes the user's reactions and inputs while the report is displayed and recognizes the user's emotions. For example, it determines whether the user is happy, troubled, or anxious. The emotion recognition means can analyze key input patterns and speed, the frequency and timing of screen operations, and even facial expressions and voice using a camera or microphone. The hardware used includes the smartphone's camera and microphone. The software uses an emotion recognition API (e.g., OpenCV, DeepFace).

[1139] Once the user's emotions are recognized, the server can adjust the product recommendations based on the results. For example, if the user is in a difficult situation, the server can narrow down the recommendations to only highly rated products. The emotion recognition method can also adapt the interface display. If the user is tired, the interface can be simplified and only the most important recommended products can be highlighted.

[1140] After the emotion recognition process has completed its adjustments, another report is sent to the user. The user can review this new report and enter more specific requests. For example, they could enter "longer battery life" as an additional request. Examples of prompts include:

[1141] product_type = 'tablet'

[1142] features = ['large screen', 'high resolution', 'battery life']

[1143] budget = 50000

[1144] The server then searches for products again based on the newly received request, updates the results, and provides a new report.The server then uses the data reprocessing means to perform a new search that takes into account additional conditions added to the initial search results, and provides a revised report to the user.

[1145] Finally, once the user has decided on the product they want, the server uses a purchasing procedure proxy to carry out the purchasing procedure on the online shopping site. The server uses the shopping site's API to add the product to the cart and completes the payment procedure and input of shipping information. Once the purchasing procedure is complete, confirmation information is sent to the terminal and the user is notified that the purchase has been completed.

[1146] In this way, users can efficiently search, compare, and purchase desired products, and the use of emotion recognition means can significantly improve the user experience.

[1147] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1148] Step 1:

[1149] The user uses the data input means to input the type of product they are considering purchasing, their desired functions and features, and their budget. The input data includes information such as "tablet, large screen, high resolution, 50,000 yen." Based on this information, the device uses the data transmission means to send the data to the server via a communication protocol (e.g., HTTP POST request).

[1150] Step 2:

[1151] The server uses data processing means to search for relevant products from multiple shopping sites and databases based on the received user information. This search process utilizes API calls and web scraping technology.

[1152] Input: The user's desired product type, functions, features, and budget.

[1153] Output: A list of searched products.

[1154] Step 3:

[1155] The server uses a data processing means to compare prices, functions, and features based on the retrieved product list. In this comparison process, product prices, features, user ratings, etc. are analyzed and a specific rating algorithm is used.

[1156] Input: Searched product list.

[1157] Output: The comparison result.

[1158] Step 4:

[1159] The server uses the report generating means to generate a comparison report from the comparison results obtained by the data processing means, which includes product names, prices, main features, user ratings, etc.

[1160] Input: Comparison result.

[1161] Output: Comparison report.

[1162] Step 5:

[1163] The terminal receives the comparison report sent from the server and displays it to the user, who then considers purchasing based on the report.

[1164] Step 6:

[1165] While the report is being displayed, the emotion recognition means analyzes the pattern and speed of key input, the frequency and timing of screen operations, and even the user's facial expressions and voice using a camera and microphone to recognize the user's emotions.

[1166] Input: User input patterns, facial expressions, and voice.

[1167] Output: Emotion recognition result.

[1168] Step 7:

[1169] The server adjusts the product recommendations based on the user's emotions recognized by the emotion recognition means, such as prioritizing highly rated products and simplifying the interface.

[1170] Input: Emotion recognition results.

[1171] Output: Tailored recommendation results or interface.

[1172] Step 8:

[1173] The server regenerates a report based on the adjusted recommendations and the new interface and sends it to the terminal, where the user can review the report again and enter any additional requests using the data input means.

[1174] Input: Adjusted recommendation results.

[1175] Output: New comparison report or adjusted interface display.

[1176] Step 9:

[1177] The server searches for the relevant product again based on the additional request from the user, and performs a re-search using a data re-processing means that takes the additional conditions into consideration in the original search results.

[1178] Input: User's additional request.

[1179] Output: Updated product list and comparison results.

[1180] Step 10:

[1181] Once the user has finally decided on the product to purchase, the server uses the purchasing procedure proxy to add the product to the cart using the online shopping site's API, and completes the payment procedure and input of shipping information. Once the purchasing procedure is complete, confirmation information is sent to the terminal, and the user is notified that the purchase has been completed.

[1182] Input: The user's final selection.

[1183] Output: Purchase completion notification.

[1184] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1185] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1186] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1187] [Fourth embodiment]

[1188] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1189] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1190] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1191] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1192] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1193] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1194] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1195] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1196] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1197] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1198] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1199] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1200] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1201] The present invention relates to a system that enables users to efficiently search for, compare, and purchase desired products, and is configured as follows.

[1202] First, a user enters the type of product they are considering purchasing, their desired functions and features, and their budget through an interface. This data entry method is realized, for example, as a web form or an input screen in a mobile application. Once the user enters this information, the data is sent from the device to the server. The data transmission method is realized by an HTTP request or other communication protocol over the Internet.

[1203] The server analyzes the received data and uses data processing means to search for relevant products across multiple online shopping sites and internal databases. At this stage, the server compares products based on price, functionality, and features to find the best option. Data processing means include product search algorithms and price comparison engines.

[1204] Once the comparison results are obtained, the server uses the report generation means to generate a simple report summarizing these results. The report includes product names, prices, and key features, allowing the user to evaluate and compare products. This report is sent to the terminal and displayed on the user's screen.

[1205] The user can then input additional requests based on the displayed report, for example, specifying a particular brand or requesting more specific features, and this information is retransmitted to the server via the additional request input means.

[1206] The server searches for products again based on the newly received request and updates the comparison results. Using the data reprocessing means, a new search is performed taking into account the additional conditions added to the initial search results. The updated comparison results are compiled again by the report generation means, sent to the terminal, and displayed to the user again.

[1207] Finally, when the user decides on the desired product, the server uses a purchasing agent to carry out the purchasing procedure on the online shopping site. At this stage, the server adds the product to the cart through the shopping site's API and completes the purchase. This process includes payment procedures and inputting shipping information.

[1208] As a specific example, if a user wants to purchase a "tablet," the following operations are performed.

[1209] 1. The user types "tablet, large screen, high resolution, 50000" into the interface.

[1210] 2. The device sends this information to the server.

[1211] 3. The server searches for suitable tablets on multiple shopping sites and compares prices and features.

[1212] 4. The server sends the generated report to the terminal, and the user checks the report.

[1213] 5. The user inputs "a device with a longer battery life" as an additional request.

[1214] 6. The server searches again based on the new conditions, updates the results, and sends them to the device.

[1215] 7. The user selects a specific tablet and requests a purchase.

[1216] 8. The server processes the purchase on the shopping site and the purchase is completed.

[1217] As described above, the present invention is a system that enables users to efficiently select desired products and smoothly complete the purchasing procedure.

[1218] The processing flow will be explained below.

[1219] Step 1:

[1220] Through the interface, users input the type of product they are considering purchasing, their desired functions and features, and their budget. Specifically, they enter information such as "tablet, large screen, high resolution, 50,000 yen" on the input screen of a web form or mobile application.

[1221] Step 2:

[1222] The terminal sends the data entered by the user to the server. This is done over the Internet using a communication protocol such as an HTTP POST request.

[1223] Step 3:

[1224] The server analyzes the received data and extracts conditions such as "tablet," "large screen," "high resolution," and "under 50,000 yen," which are used in the next step.

[1225] Step 4:

[1226] The server uses data processing means to search for relevant products from multiple shopping sites on the Internet and internal databases, using techniques such as API calls and web scraping to obtain a list of products that meet the criteria.

[1227] Step 5:

[1228] The server compares products from the retrieved product list based on price, functionality, and features. Using a specific evaluation algorithm, it comprehensively compares and evaluates each product based on price, features, user ratings, etc.

[1229] Step 6:

[1230] The server generates a report based on the comparison results, including product names, prices, key features, and user ratings, in simple text or HTML format.

[1231] Step 7:

[1232] The server sends the generated report to the terminal, which then displays the report on the user's screen. The user can then review the product by checking the report.

[1233] Step 8:

[1234] The user inputs additional requests based on the report, for example, "longer battery life." The user again uses the interface to input the additional information, which is then sent to the server via the terminal.

[1235] Step 9:

[1236] The server searches for products again based on the additional request, and uses the data reprocessing means to search for products again based on the new conditions and update the comparison results.

[1237] Step 10:

[1238] The server generates a new report based on the updated comparison results and sends it to the terminal, where the user can view the revised report.

[1239] Step 11:

[1240] The user finally decides which products to purchase. The user selects the products to purchase based on the report and makes a final confirmation. After that, the user sends a purchase instruction to the server via the terminal.

[1241] Step 12:

[1242] The server uses a purchasing agent to process purchases on an online shopping site. The server makes an API request to the shopping site, adds products to the cart, and completes payment procedures and inputs shipping information.

[1243] Step 13:

[1244] Once the purchase procedure is complete, the server sends confirmation information to the terminal, and the user receives a notification that the purchase has been completed.

[1245] These are the specific processing steps of the system. This flow allows users to efficiently search and compare desired products and smoothly complete the purchasing process.

[1246] Example 1

[1247] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1248] The problem that this invention aims to solve is to enable users to efficiently browse multiple shopping sites and databases on the Internet and easily search, compare, and purchase desired products. Furthermore, by quickly performing re-searches based on the user's additional requests and selecting optimal products, and by carrying out the purchasing procedure on the user's behalf, the invention aims to reduce the user's operational burden and facilitate the purchasing process.

[1249] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1250] In this invention, the server includes an input device for a user to input the type of product the user is considering purchasing, the desired functions and features, and the user's budget; a data transmission device for transmitting the data input from the input device to the server; a data processing device for searching for relevant products from multiple product sales platforms and databases on an information network based on the data transmitted by the data transmission device and comparing prices, functions, and features; an information generation device for providing the user with the comparison results obtained by the data processing device; an additional request input device for the user to input additional requests regarding the information; a data reprocessing device for searching for and comparing products again based on the data input by the additional request input device; a purchase procedure agent device for performing a purchase procedure on an online shopping site based on instructions from a user who has finally decided on a product to purchase; an algorithm optimization device for optimizing a product search algorithm using a generative AI model; and an input assistance device for inputting prompt sentences to assist in inputting data to the generative AI model. This enables a user to efficiently search for and compare desired products from multiple shopping sites and quickly re-search for products that meet additional requests, ultimately enabling a smooth purchase procedure on an online shopping site.

[1251] The "input device" is a means for a user to input the type of product they are considering purchasing, the desired functions and features, and their budget.

[1252] The "data transmission device" is a means for transmitting data input from an input device to a server.

[1253] The "data processing device" is a means for searching for relevant products from multiple product sales platforms and databases on an information network based on the data transmitted by the data transmission device, and comparing prices, functions, and features.

[1254] The "information generating device" is a means for providing the comparison results obtained by the data processing device to the user.

[1255] The "additional request input device" is a means for a user to input additional requests for information.

[1256] The "data reprocessing device" is a means for searching and comparing products again based on the data inputted by the additional request input device.

[1257] A "purchase procedure agent device" is a means for carrying out purchase procedures on an online shopping site on behalf of a user who has finally decided on the product to purchase, based on instructions from the user.

[1258] An "algorithm optimization device" is a means for optimizing a product search algorithm using a generative AI model.

[1259] An "input assistance device" is a means for inputting prompt sentences to assist in inputting data into a generative AI model.

[1260] This invention relates to a system that allows users to efficiently search, compare, and purchase desired products. This system is realized using the following hardware and software.

[1261] Hardware Configuration

[1262] 1. User device: This refers to the device on which a user enters product information and checks search results. Examples include PCs, smartphones, and tablets. These devices have input devices that provide interfaces for web forms and mobile applications.

[1263] 2. Server: A central device that performs various processes and communicates with terminals via the Internet. It analyzes data, searches for products, generates comparison results, reprocesses user requests for additional products, and handles purchasing procedures on behalf of users. The server is equipped with a high-performance processor and large-capacity storage.

[1264] Software Configuration

[1265] 1. Input device: Provides a web form or mobile application input screen where users can enter the type of product they are considering purchasing, desired features and budget. This screen is built using web technologies such as HTML, CSS, and JavaScript.

[1266] 2. Data transmission device: This device has the function of transmitting product information entered by the user to the server. The input data is sent to the server using HTTP requests and Ajax technology.

[1267] 3. Data Processing Device: Runs on the server and uses product search algorithms and price comparison engines based on the received data to search and compare relevant products from multiple shopping sites and internal databases. This process is performed using scripting languages ​​such as Python and Ruby.

[1268] 4. Information generator: Based on the comparison results, a report is generated to be provided to the user. This is done using the Pandas library and an Excel file generation tool. The report includes the product name, price, and key features.

[1269] 5. Additional Request Input Device: Provides an interface for users to input additional requests for reports. This function can also be realized by a web form or a mobile application.

[1270] 6. Data reprocessing: Search for products again based on additional requests and update the comparison results. This reprocessing also uses the same technology as the data processing device.

[1271] 7. Purchase procedure agent: This device handles the purchase procedure on an online shopping site based on the instructions of the user who has finally decided on the product to purchase. It uses the shopping site's API to add the product to the cart and enters payment and delivery information.

[1272] 8. Algorithm Optimizer: Optimizes product search algorithms using generative AI models, specifically using machine learning libraries (TensorFlow and PyTorch) to improve search and comparison accuracy.

[1273] 9. Input assistance device: This device has a function to assist input data to the generative AI model by inputting prompt sentences. This enables more accurate searches that meet the user's search needs.

[1274] Specific examples

[1275] For example, if a user enters "tablet, large screen, high resolution, 50,000" into the interface, the device will send this information to the server. The server will collect relevant product information from various shopping sites and compare prices and features. The server will generate a report based on this information and send it to the device. The user will then review the report and add a request for "something with a long battery life." The server will then search again using the new criteria and send the updated report back to the device. Finally, the user will select the desired product and request the purchase, and the server will complete the purchase process on the online shopping site.

[1276] This system allows users to efficiently search and compare desired products from multiple shopping sites, quickly search for additional products that meet additional requests, and ultimately allows users to smoothly proceed with the purchase process on online shopping sites.

[1277] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1278] Step 1: User Input

[1279] Through the interface, users input the type of product they want to purchase, the features and functions they want, and their budget. Specifically, they enter specific requirements, such as "tablet, large screen, high resolution, 50,000," into a web form or mobile application.

[1280] Input: User data including product type, desired functions, features, and budget

[1281] Output: The data necessary for product search is prepared on the user's device

[1282] Step 2: Send data

[1283] The terminal receives the product information entered by the user and sends it to the server using an HTTP request, packaging the user's input data in JSON format.

[1284] Input: User-entered data

[1285] Output: Product information data sent to the server

[1286] Step 3: Data analysis and product search

[1287] The server analyzes the data and extracts product information (e.g., "tablet, large screen, high resolution, 50,000"). It then searches for the relevant product on multiple product sales platforms on the information network and in an internal database. It uses a Python script to obtain data via APIs and web scraping.

[1288] Input: User's submitted product information data

[1289] Output: Product data collected from multiple shopping sites

[1290] Step 4: Compare product information

[1291] The server processes the collected product data using a comparison algorithm to compare products based on price, functionality, and features, for example, "Tablet A, Price: ¥48,000, Screen Size: 10 inches, Resolution: 4K" and "Tablet B, Price: ¥52,000, Screen Size: 10 inches, Resolution: Full HD."

[1292] Input: Collected product data

[1293] Output: Product data including comparison results

[1294] Step 5: Generate a report

[1295] The server generates a report based on the comparison results, which is provided to the user using the Pandas library and an Excel file generation tool. The report includes product names, prices, and key features.

[1296] Input: Product comparison data

[1297] Output: Generated report data

[1298] Step 6: Send and view the report

[1299] The server sends the generated report to the terminal, which then displays it on the user's screen, where the user can view the product information and check the details.

[1300] Input: Generated report data

[1301] Output: The report that is displayed on the user's screen

[1302] Step 7: Enter additional requests

[1303] The user reviews the displayed report and enters additional requests, for example, a specific request such as "long battery life," again entering the request into the interface.

[1304] Input: Additional requested data based on the report

[1305] Output: Additional requests recorded on the input device

[1306] Step 8: Submit your additional requests

[1307] The device receives the additional request and sends it to the server again using an HTTP request, with the additional request data packaged in JSON format.

[1308] Input: Additional requested data

[1309] Output: Additional requested data resent to the server

[1310] Step 9: Re-search and update the comparison results

[1311] The server uses the data reprocessing device to perform a new search based on the newly received additional request. At this time, it adds new conditions while taking into account the existing search results. It retrieves product data again and compares prices and features.

[1312] Input: Resubmitted additional request data

[1313] Output: Updated product data and comparison results

[1314] Step 10: Generate and send the update report

[1315] The server generates an updated report based on the results of the re-search and sends it to the terminal, which then displays the updated report to the user.

[1316] Input: Updated product data

[1317] Output: Updated report data

[1318] Step 11: Start Checkout

[1319] The user finally selects the desired product, enters purchase account information and delivery information, and requests the purchase procedure.

[1320] Input: Last selected product information and user purchase request data

[1321] Output: Purchase preparation data

[1322] Step 12: Purchasing on your behalf

[1323] The server uses a purchasing agent to complete the purchasing process through the API of the online shopping site, including adding products to the cart, entering payment information, and entering shipping information.

[1324] Input: Checkout preparation data and shopping site API

[1325] Output: Purchase completion notification and delivery arrangement information

[1326] The above is the specific flow of the system's processing steps and how it works. This system allows users to efficiently search, compare, and purchase the products they want.

[1327] (Application example 1)

[1328] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1329] Currently, there are many e-commerce sites, and users spend a lot of time and effort selecting the right product. It is also difficult to efficiently search, compare, and purchase products based on desired specifications and features. Furthermore, technology for recommending products to users is not yet fully developed. A new approach is needed to solve these issues and enable users to more efficiently purchase the products they desire.

[1330] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1331] In this invention, the server includes: a data input means for a user to input the type of product the user is considering purchasing, the desired specifications and features, and the user's budget; a data transmission means for transmitting the data input from the data input means to the server; a data processing means for searching for relevant products from multiple e-commerce sites and databases on the Internet based on the data transmitted by the data transmission means and comparing prices, specifications, and features; a report generation means for providing the user with the comparison results obtained by the data processing means; an additional request input means for the user to input additional requests for the report; a re-search data processing means for searching for and comparing products again based on the data input by the additional request input means; a purchase procedure agent means for performing the purchase procedure on the e-commerce site on behalf of the user who has finally decided on the product to purchase; a data processing means operating as part of the system; a product recommendation means using a generative AI model to recommend products based on their features and the user's requests; a prompt generation means for generating and inputting prompt sentences for the generative AI model; and an AI support means for searching, comparing, and recommending products based on the prompt generation means. This will enable users to efficiently search, compare, and purchase the products they want, improving their purchasing experience.

[1332] The "data input means" is a means for a user to input the type of product he or she is considering purchasing, the desired specifications and features, and the budget.

[1333] The "data transmission means" is a means for transmitting data inputted from the data input means to the server.

[1334] The "data processing means" is a means for searching for relevant products from multiple e-commerce sites and databases on the Internet based on the data transmitted by the data transmission means, and comparing prices, specifications, and features.

[1335] The "report generating means" is a means for generating a report to provide the user with the comparison results obtained by the data processing means.

[1336] The "additional request input means" is a means for the user to input additional requests for the report.

[1337] The "re-search data processing means" is a means for searching for and comparing products again based on the data inputted by the additional request input means.

[1338] The "purchase procedure proxy means" is a means for carrying out the purchase procedure on an e-commerce site on behalf of the user who has finally decided on the product to purchase, based on the user's instructions.

[1339] A "generative AI model" is an artificial intelligence model that recommends products based on data processing means, their characteristics, and user preferences.

[1340] A "prompt generation means" is a means for generating and inputting a prompt sentence to a generative AI model.

[1341] An "AI-enabled means" is an artificial intelligence-enabled means for product search, comparison, and recommendation based on the prompt generation means.

[1342] The present invention relates to a system that enables a user to efficiently search for, compare, and purchase desired products. The present invention is specifically implemented as follows.

[1343] First, the user enters the type of product they are considering purchasing, their desired specifications and features, and their budget through a data input means. The data input means is realized as an input screen for a smartphone application. Once the user enters this information, the data is sent from the device to the server via an HTTP request.

[1344] The server uses the received data to search for relevant products from multiple e-commerce sites on the Internet and internal databases. At this stage, the server compares products based on price, specifications, and features. The data processing means includes product search algorithms and price comparison engines.

[1345] Once the comparison results are obtained, the server uses a report generation means to generate a report summarizing these results. The report includes product names, prices, and key features, allowing the user to evaluate and compare products. This report is sent to the terminal and displayed on the user's smartphone screen.

[1346] The user can then input additional preferences based on the displayed report, for example, specifying a particular brand or requesting more detailed specifications, and this information is retransmitted to the server via the additional preference input means.

[1347] The server searches for products again based on the newly received request and updates the results. The re-search data processing means performs a re-search taking into account the additional conditions for the initial search results. The updated comparison results are again compiled by the report generation means, sent to the terminal, and displayed to the user again.

[1348] Finally, when the user decides on the desired product, the server uses a purchasing agent to complete the purchasing process on the e-commerce site. At this stage, the server adds the product to the cart through the e-commerce site's API and completes the purchasing process. This process includes payment procedures and inputting shipping information.

[1349] Furthermore, the server recommends products using the generative AI model. A prompt generation means generates and inputs prompt sentences for the generative AI model, and the AI ​​support means performs product search, comparison, and recommendation based on the prompt sentences, thereby enabling users to efficiently find more suitable products.

[1350] Specific examples are shown below.

[1351] If a user searches for "smartphone, large screen, high resolution, 60000," the server searches multiple e-commerce sites for matching smartphones, generates results, and displays them to the user. If the user adds "long battery life," the server performs a second search and presents products that match the criteria. In this way, users can efficiently search, compare, and purchase the products they want.

[1352] An example of a prompt for the generative AI model is to search for "smartphone, large screen, high resolution, 60000" and then search again with the additional criteria "long battery life."

[1353] This system allows users to efficiently search for products based on their desired criteria and make optimal purchasing decisions. In addition, by utilizing a generative AI model, users can receive product recommendations in a format that is easy for them to input, improving the purchasing experience.

[1354] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1355] Step 1:

[1356] A user launches a smartphone application and enters the type of product they are considering purchasing, their desired specifications and features, and their budget into the data input means. An example of input is "smartphone, large screen, high resolution, 60000." Once this input is made, the device constructs the input data in JSON format and sends it to the server as an HTTP POST request using the data transmission means. The input data is sent to the server's API endpoint.

[1357] Step 2:

[1358] The server analyzes the data received via the data transmission means. Based on the analyzed data, the server searches for relevant products from multiple e-commerce sites on the Internet and from an internal database. The data processing means aggregates the prices, specifications, and features of the searched products. The server performs product comparison calculations based on this aggregated data. Comparison result data is generated as output.

[1359] Step 3:

[1360] The server uses the comparison results obtained by the data processing means to activate the report generation means and generate a report to be provided to the user. The report includes the product name, price, and main features. The generated report is packaged in JSON format and sent back to the terminal. The terminal receives this data and displays the report on the user's smartphone screen.

[1361] Step 4:

[1362] The user checks the displayed report and inputs additional preferences (e.g., "longer battery life"). This additional preference data is sent to the server again through the additional preference input means. The input data is again constructed in JSON format and sent to the server as an HTTP POST request.

[1363] Step 5:

[1364] The server receives the data again and uses the re-search data processing means to search for products again, taking into account the newly received conditions. The search results are again accumulated and comparison operations are performed. The server then generates an updated report again using the report generation means. The re-generated report is again sent to the terminal. As an output, the updated report is displayed on the user's smartphone screen.

[1365] Step 6:

[1366] Once the user has finally selected the desired product and instructed the purchase through the purchasing procedure proxy, the server will use the API of the e-commerce site to carry out the purchasing procedure on their behalf. Specifically, the server will add the product to the cart, and handle payment procedures and input delivery information. As an output, a notification of the completion of the purchasing procedure will be sent to the user's device.

[1367] Step 7:

[1368] The server uses the generative AI model to launch a product recommendation means based on the user's preferences and input data. It then launches a prompt generation means to generate a prompt sentence for the generative AI model. Using the generated prompt sentence, the AI-enabled means searches, compares, and recommends products. An example of a prompt sentence is to enter "smartphone, large screen, high resolution, 60000" and search again with "long battery life" as an additional condition. As an output, recommended product information is presented to the user.

[1369] This allows users to efficiently search and compare the products they want and make better purchasing decisions.

[1370] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1371] This invention improves the user experience by combining an emotion engine with a system that allows users to efficiently search, compare, and purchase the products they desire. The specific configuration and operation of the system are described below.

[1372] First, the user enters the type of product they are considering purchasing, their desired functions and features, and their budget through an interface. This is done using a web form or a mobile application input screen. For example, they enter information such as "tablet, large screen, high resolution, 50,000 yen." The entered data is then sent from the device to the server. The data is sent via a communication protocol such as an HTTP POST request over the Internet.

[1373] The server then analyzes the received data and uses data processing means to search for the relevant products from each shopping site or internal database. This process uses techniques such as API calls and web scraping to obtain a list of products that match the criteria. The server then compares prices, functions, and features based on the obtained product list. This comparison uses a specific evaluation algorithm to analyze product prices, features, user ratings, etc.

[1374] After obtaining the comparison results, the server generates a comparison report using a report generation means, which includes product names, prices, main features, user ratings, etc. This report is sent to the terminal, and the user can use it to consider purchasing.

[1375] This is where the emotion engine, a key feature of the present invention, comes into play. The emotion engine analyzes the user's reactions and inputs while the report is displayed and recognizes the user's emotions. For example, it determines whether the user is happy, troubled, or anxious. The emotion engine can analyze keystroke patterns and speed, the frequency and timing of screen operations, and even facial expressions and voice using a camera or microphone.

[1376] Once the user's emotions are recognized, the server can adjust the product recommendations based on the results. For example, if the user is in a difficult situation, the server can narrow down the recommendations to only those with particularly high ratings. The emotion engine can also adapt the interface display. If the user is tired, the interface can be simplified and only the most important recommended products can be highlighted.

[1377] After the emotion engine has completed its adjustments, another report is sent to the user. The user can review this new report and enter more specific requests. For example, the user can enter "long battery life" as an additional request. The server then searches for products again based on the newly received request and updates the results. Using the reprocessing means, the server performs a new search taking into account the additional conditions added to the initial search results, and provides the user with a revised report.

[1378] Finally, once the user has decided on the product they want, the server uses a purchasing procedure proxy to carry out the purchasing procedure on the online shopping site. The server uses the shopping site's API to add the product to the cart and completes the payment procedure and input of shipping information. Once the purchasing procedure is complete, confirmation information is sent to the terminal and the user is notified that the purchase has been completed.

[1379] As a concrete example, if a user wants to purchase a "tablet," the system works as follows.

[1380] 1. The user enters "tablet, large screen, high resolution, 50,000 yen."

[1381] 2. The device sends this information to the server.

[1382] 3. The server searches for the appropriate tablet on each shopping site and compares prices and features.

[1383] 4. The server sends the generated report to the terminal, and the user checks the report.

[1384] 5. While viewing the report, the emotion engine detects the user's "anxiety."

[1385] 6. The server tailors the report to recommend only highly rated products based on user sentiment and provides a simplified interface.

[1386] 7. The user specifies "longer battery life" as an additional requirement.

[1387] 8. The server searches again based on the new criteria, updates the results, and provides the report again.

[1388] 9. The user selects a specific tablet and requests a purchase.

[1389] 10. The server uses the shopping site's API to complete the purchase process on behalf of the customer.

[1390] In this way, the present invention is a system that significantly improves the user experience by recognizing the user's emotions and adjusting product recommendations, supporting efficient and satisfying product selection and purchasing procedures.

[1391] The processing flow will be explained below.

[1392] Step 1:

[1393] Through the interface, users input the type of product they are considering purchasing, the desired features and functionality, and their budget. For example, they input "tablet, large screen, high resolution, 50,000 yen." This data input method is realized through a web form or a mobile application input screen.

[1394] Step 2:

[1395] The terminal transmits the data input by the user to the server, which can be achieved by an HTTP POST request or other communication protocol via the Internet.

[1396] Step 3:

[1397] The server analyzes the received data and extracts search criteria, such as "tablet," "large screen," "high resolution," and "under 50,000 yen."

[1398] Step 4:

[1399] The server uses data processing means to search for relevant products from multiple shopping sites and databases on the Internet, and obtains a list of products that meet the criteria using API calls and web scraping technology.

[1400] Step 5:

[1401] The server compares products from the retrieved product list based on price, functionality, and features. It uses a specific evaluation algorithm to analyze data such as the price, features, and user ratings of each product.

[1402] Step 6:

[1403] The server generates a report based on the comparison results, including product name, price, key features, and user ratings. The report is generated in simple text or HTML format.

[1404] Step 7:

[1405] The server sends the generated report to the terminal, where the user can check the report. The user can view the report displayed through the interface and evaluate the product.

[1406] Step 8:

[1407] While viewing a report, the emotion engine recognizes the user's emotions. For example, it analyzes keystroke patterns and speed, the frequency and timing of screen operations, and even facial expressions and voice using a camera and microphone. This determines the user's emotions, such as "joy," "confusion," or "anxiety."

[1408] Step 9:

[1409] The server adjusts product recommendations based on the user's emotions recognized by the emotion engine. For example, if the user is "confused," the server modifies the report to prioritize highly rated products.

[1410] Step 10:

[1411] The emotion engine allows the interface display to adapt according to the user's emotions. For example, if the user is feeling "tired," the interface will be simplified by highlighting only the main recommended products.

[1412] Step 11:

[1413] The server sends the adjusted report back to the terminal and displays it to the user, who then reviews the updated report and makes further evaluations.

[1414] Step 12:

[1415] The user inputs additional requests based on the report. For example, a request such as "a device with a long battery life" is input through the interface. The additional requests are sent from the terminal to the server.

[1416] Step 13:

[1417] The server searches for the product again based on the additional request, and uses the data reprocessing means to search for the product again based on the additional request and update the result.

[1418] Step 14:

[1419] The server generates a new report based on the updated comparison results and sends it to the terminal, where the user can check the revised report.

[1420] Step 15:

[1421] The user finally decides which products to purchase. Based on the report, the user selects the products to purchase and sends a final confirmation instruction to the server via the terminal.

[1422] Step 16:

[1423] The server uses a purchasing agent to process purchases on an online shopping site, adding products to the cart using the shopping site's API and entering payment and delivery information.

[1424] Step 17:

[1425] Once the purchase procedure is complete, the server sends confirmation information to the terminal, and the user receives a notification that the purchase has been completed.

[1426] The above are the specific processing steps of the system that combines the emotion engine of the present invention. This flow enables efficient product recommendations and purchasing procedures that take into account the user's emotions.

[1427] Example 2

[1428] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1429] In conventional online shopping systems, users are required to input the type of product they are considering purchasing, their desired functions, features, and budget, and then compare the search results. Furthermore, because the system does not take into account the user's emotional state, selecting the optimal product takes time and effort. Furthermore, the system also leaves users with psychological burdens when checking reports and anxiety about the operations involved in the purchase process. There is a need to address these issues and improve the user experience.

[1430] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes emotion engine means that analyzes the user's reactions and inputs while the report is being displayed and recognizes their emotions, adjustment means that adjusts product recommendations based on the concern results analyzed by the emotion engine means to improve the user experience, and purchase procedure proxy means that performs the purchase procedure on the sales website on behalf of the user based on instructions from the user who has finally decided on the product to purchase. This makes it possible to adjust product recommendations according to the user's emotional state and perform the purchase procedure on behalf of the user.

[1431] The "data input means" is a means for a user to input the type of product they are considering purchasing, the functions and features they desire, and their budget.

[1432] The "data transmission means" is a means for transmitting data inputted from the data input means to the server.

[1433] "Data processing means" refers to a means for searching for relevant products from multiple sales websites and information bases on the Internet based on the data transmitted by the data transmission means, and for comparing prices, functions and features.

[1434] The "report generating means" is a means for providing the user with the comparison results obtained by the data processing means.

[1435] The "emotion engine means" is a means for analyzing the user's reactions and inputs while the report is being displayed, and recognizing emotions.

[1436] The "adjustment means" is a means for adjusting product recommendations based on the concern results analyzed by the emotion engine means, thereby improving the user experience.

[1437] The "additional request input means" is a means for the user to input additional requests for the report.

[1438] The "data reprocessing means" is a means for searching for and comparing products again based on the data input by the additional request input means.

[1439] The "purchase procedure proxy means" is a means for carrying out the purchase procedure on the sales website on behalf of the user who has finally decided on the product to purchase, based on the instructions of the user.

[1440] This invention improves the user experience by combining an emotion engine with a system that allows users to efficiently search, compare, and purchase the products they desire. The specific configuration and operation of the system are described below.

[1441] First, the user enters the type of product they are considering purchasing, their desired functions and features, and their budget through an interface. This interface uses a web form or a mobile application input screen. As a specific example, let's say the user enters "tablet, large screen, high resolution, 50,000 yen." The interface used could be a React-based web form or a mobile application using Swift. The entered data is sent from the device to the server. At this time, a communication protocol such as an HTTP POST request via the Internet is used as the data transmission method. The communication protocol assumes HTTPS.

[1442] The server then analyzes the received data and searches for relevant products on each sales website or internal information base. This process uses API calls and web scraping techniques, including the Amazon API, Rakuten API, and Python's BeautifulSoup library. Based on the analyzed data, the server retrieves a list of products and compares prices, functions, and features. For this comparison, Python's Pandas library is used to calculate a product score and create a ranking list.

[1443] Based on the comparison results of the acquired data, the server generates a report that includes product name, price, key features, user ratings, etc. This report is generated in Markdown format and can be converted to the required format such as HTML or PDF. The server then sends the report to the terminal as an HTTP response.

[1444] This is where the emotion engine, a key feature of the present invention, comes into play. While the user is viewing the report, the emotion engine analyzes the user's reactions and inputs to recognize their emotions. Specifically, it collects typing speed and click patterns, and uses the device's camera and microphone to analyze the user's facial expressions and voice using OpenCV and the Google Cloud Speech-to-Text API. This allows it to determine whether the user is happy, troubled, anxious, etc.

[1445] Once the user's emotions are recognized, the server adjusts the product recommendations based on the results. For example, if the user is in a difficult situation, the server will narrow down the recommendations to only highly rated products and provide a simplified interface. The user interface is dynamically changed using HTML / CSS and JavaScript.

[1446] After the emotion engine has completed its adjustments, another report is sent to the user. The user can review the new report and enter more specific requests. For example, they can enter "long battery life" as an additional request. The device again sends this information in JSON format to the server, and the server performs a new search. Using the reprocessing means, a new search is performed taking into account the additional conditions from the initial search results.

[1447] Finally, once the user has decided on the product they want, the server uses a purchasing procedure proxy to carry out the purchasing procedure on the online shopping site on their behalf. The server uses the shopping site's API to add the product to the cart and complete the payment procedure. Purchase confirmation information is then sent to the user as an email notification.

[1448] Below are some examples of prompt sentences to input to the generative AI model.

[1449] 1. I am looking for a tablet, so please tell me about products that meet the following criteria: large screen, high resolution, and under 50,000 yen.

[1450] 2. I would like to conduct a thorough sentiment analysis to find out how users react when they detect they are in a difficult situation.

[1451] 3. Generate new product search results that take into account the additional requirement "long battery life."

[1452] In this way, the present invention is a system that significantly improves the user experience by recognizing the user's emotions and adjusting product recommendations, supporting efficient and satisfying product selection and purchasing procedures.

[1453] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1454] Step 1:

[1455] Data Entry

[1456] Users enter the type of product they are considering purchasing, the features and functionality they are looking for, and their budget through an interface that can be a web form or a mobile application.

[1457] Input: User enters "tablet, large screen, high resolution, 50,000 yen."

[1458] Output: Input data ("Tablet, large screen, high resolution, 50,000 yen").

[1459] What happens: A user enters information into a React-based web form or a Swift-powered mobile application.

[1460] Step 2:

[1461] Data transmission

[1462] The device sends the entered data to the server using a communication protocol such as an HTTP POST request over the Internet.

[1463] Input: Input data ("Tablet, large screen, high resolution, 50,000 yen").

[1464] Output: The data sent to the server.

[1465] Specific operation: The terminal packs the user's input data into JSON format and sends it to the server using the HTTPS protocol.

[1466] Step 3:

[1467] Data analysis and product search

[1468] The server analyzes the received data and searches for relevant products on each sales website or internal information base, using API calls and web scraping techniques.

[1469] Input: Data sent to the server ("Tablet, large screen, high resolution, 50,000 yen").

[1470] Output: A list of matching products.

[1471] Specific operation: The server sends a search query to the Amazon API or Rakuten API based on the input data and retrieves a product list. Web scraping is performed using the Python BeautifulSoup library.

[1472] Step 4:

[1473] Product comparison

[1474] The server compares the prices, features, and characteristics of the products it receives, using a specific rating algorithm.

[1475] Input: A list of applicable products.

[1476] Output: Comparison results (including price, features, and characteristics).

[1477] Specific operation: The server generates a product comparison table using an algorithm (Python's Pandas library) that analyzes product prices, user ratings, and features, calculates a score for each product, and creates a ranked list.

[1478] Step 5:

[1479] Report Generation

[1480] The server generates a report based on the comparison results and sends it to the device, which includes product names, prices, key features, and user ratings.

[1481] Input: Comparison result.

[1482] Output: Report (including product name, price, key features, and user ratings).

[1483] Specific operation: The server generates a report in Markdown format, converts it to the required format such as HTML or PDF, and sends the generated report data to the terminal as an HTTP response.

[1484] Step 6:

[1485] Emotion analysis

[1486] The emotion engine analyzes the user's reactions and inputs while the report is displayed, and recognizes the user's emotions. It analyzes keystroke patterns and speed, frequency of screen operations, facial expressions and voice using a camera and microphone.

[1487] Input: User responses and input data (keystrokes, click patterns, facial expressions, voice, etc.).

[1488] Output: Sentiment analysis results (happiness, confusion, anxiety, etc.).

[1489] Specific operation: While the user is viewing the report, the system collects typing speed and click patterns. The system uses the device's camera and microphone to analyze the user's facial expressions and voice using OpenCV and the Google Cloud Speech-to-Text API.

[1490] Step 7:

[1491] Adjusted recommendations and adapted interface

[1492] The server adjusts product recommendations and adapts the interface based on the results of sentiment analysis.

[1493] Input: Sentiment analysis results.

[1494] Output: A tailored list of recommended products and an adapted interface.

[1495] Specific behavior: The server lists only highly rated products and switches to a simple UI. The user interface is dynamically changed using HTML / CSS and JavaScript.

[1496] Step 8:

[1497] Enter additional requests

[1498] The user inputs a new request, which is received by the server and the search is carried out again.

[1499] Input: User's additional requests (e.g. "something with a longer battery life").

[1500] Output: Updated product list and report.

[1501] Specific operation: The user enters additional requests, and the device again sends this information in JSON format to the server. The server then performs a new search based on the new conditions and updates the results.

[1502] Step 9:

[1503] Purchase procedure proxy

[1504] Once the user has decided on the product they want, the server will use the shopping site's API to carry out the purchase process on their behalf.

[1505] Input: The product decided by the user.

[1506] Output: Purchase confirmation information.

[1507] Specific operations: The server adds the selected product to the shopping cart on the sales website, completes the payment process, and sends the purchase confirmation information to the user via email.

[1508] In this way, by describing the processing flow at each step and the specific actions that correspond to them in detail, a system that improves the user experience is realized.

[1509] (Application example 2)

[1510] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1511] Conventional online shopping systems often fail to efficiently search for and compare products that users desire. Furthermore, product recommendations are not optimized based on user emotions and reactions, resulting in a lack of user experience. This can leave users feeling lost or confused when selecting or purchasing a product, resulting in no purchase at all. These issues need to be addressed.

[1512] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1513] In this invention, the server includes: data input means for a user to input the type of product the user is considering purchasing, the desired functions and features, and the user's budget; data transmission means for transmitting the data input from the data input means to the server; data processing means for searching for relevant products from multiple shopping sites and databases on the Internet based on the data transmitted by the data transmission means and comparing prices, functions, and features; report generation means for providing the user with the comparison results obtained by the data processing means; emotion recognition means for recognizing the user's emotions and dynamically adjusting product recommendations and interface display methods based on the results; additional request input means for the user to input additional requests for the report; data reprocessing means for searching for and comparing products again based on the data input by the additional request input means; and purchase procedure proxy means for carrying out the purchase procedure at the online shopping site on behalf of the user who has finally decided on the product to purchase. This enables the user to efficiently search for, compare, and purchase the product they desire, and the use of the emotion recognition means significantly improves the user experience, making it easier for the user to select an appropriate product without hesitation or confusion.

[1514] The "data input means" is a means for a user to input the type of product they are considering purchasing, the functions and features they desire, and their budget.

[1515] The "data transmission means" is a means for transmitting data inputted from the data input means to the server.

[1516] The "data processing means" is a means for searching for relevant products from multiple shopping sites and databases on the Internet based on the data transmitted by the data transmission means, and comparing prices, functions, and features.

[1517] The "report generating means" is a means for providing the user with the comparison results obtained by the data processing means.

[1518] The "emotion recognition means" is a means for recognizing the user's emotions and dynamically adjusting the product recommendations and interface display method based on the results.

[1519] The "additional request input means" is a means for the user to input additional requests for the report.

[1520] The "data reprocessing means" is a means for searching for and comparing products again based on the data input by the additional request input means.

[1521] The "purchase procedure proxy means" is a means for carrying out the purchase procedure on an online shopping site on behalf of the user who has finally decided on the product to purchase, based on instructions from the user.

[1522] This invention improves the user experience by combining emotion recognition means with a system that allows users to efficiently search, compare, and purchase desired products. The specific configuration and operation of the system are described below.

[1523] First, the user uses the data input means to input the type of product they are considering purchasing, their desired functions and features, and their budget. For example, they input information such as "tablet, large screen, high resolution, 50,000 yen." This data is then sent from the device to the server. The data transmission means is implemented via the Internet using a communication protocol such as an HTTP POST request.

[1524] Next, the server uses data processing means to search for relevant products from multiple shopping sites and internal databases based on the received data. This process uses techniques such as API calls and web scraping to obtain a list of products that match the criteria. The server then compares prices, functions, and features based on the obtained product list. This comparison process uses a specific evaluation algorithm to analyze product prices, features, user ratings, etc.

[1525] After obtaining the comparison results, the server generates a comparison report using a report generation means, which includes product names, prices, main features, user ratings, etc. This report is sent to the terminal, and the user can use it to consider purchasing.

[1526] This is where the emotion recognition means, a feature of the present invention, comes into play. The emotion recognition means analyzes the user's reactions and inputs while the report is displayed and recognizes the user's emotions. For example, it determines whether the user is happy, troubled, or anxious. The emotion recognition means can analyze key input patterns and speed, the frequency and timing of screen operations, and even facial expressions and voice using a camera or microphone. The hardware used includes the smartphone's camera and microphone. The software uses an emotion recognition API (e.g., OpenCV, DeepFace).

[1527] Once the user's emotions are recognized, the server can adjust the product recommendations based on the results. For example, if the user is in a difficult situation, the server can narrow down the recommendations to only highly rated products. The emotion recognition method can also adapt the interface display. If the user is tired, the interface can be simplified and only the most important recommended products can be highlighted.

[1528] After the emotion recognition process has completed its adjustments, another report is sent to the user. The user can review this new report and enter more specific requests. For example, they could enter "longer battery life" as an additional request. Examples of prompts include:

[1529] product_type = 'tablet'

[1530] features = ['large screen', 'high resolution', 'battery life']

[1531] budget = 50000

[1532] The server then searches for products again based on the newly received request, updates the results, and provides a new report.The server then uses the data reprocessing means to perform a new search that takes into account additional conditions added to the initial search results, and provides a revised report to the user.

[1533] Finally, once the user has decided on the product they want, the server uses a purchasing procedure proxy to carry out the purchasing procedure on the online shopping site. The server uses the shopping site's API to add the product to the cart and completes the payment procedure and input of shipping information. Once the purchasing procedure is complete, confirmation information is sent to the terminal and the user is notified that the purchase has been completed.

[1534] In this way, users can efficiently search, compare, and purchase desired products, and the use of emotion recognition means can significantly improve the user experience.

[1535] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1536] Step 1:

[1537] The user uses the data input means to input the type of product they are considering purchasing, their desired functions and features, and their budget. The input data includes information such as "tablet, large screen, high resolution, 50,000 yen." Based on this information, the device uses the data transmission means to send the data to the server via a communication protocol (e.g., HTTP POST request).

[1538] Step 2:

[1539] The server uses data processing means to search for relevant products from multiple shopping sites and databases based on the received user information. This search process utilizes API calls and web scraping technology.

[1540] Input: The user's desired product type, functions, features, and budget.

[1541] Output: A list of searched products.

[1542] Step 3:

[1543] The server uses a data processing means to compare prices, functions, and features based on the retrieved product list. In this comparison process, product prices, features, user ratings, etc. are analyzed and a specific rating algorithm is used.

[1544] Input: Searched product list.

[1545] Output: The comparison result.

[1546] Step 4:

[1547] The server uses the report generating means to generate a comparison report from the comparison results obtained by the data processing means, which includes product names, prices, main features, user ratings, etc.

[1548] Input: Comparison result.

[1549] Output: Comparison report.

[1550] Step 5:

[1551] The terminal receives the comparison report sent from the server and displays it to the user, who then considers purchasing based on the report.

[1552] Step 6:

[1553] While the report is being displayed, the emotion recognition means analyzes the pattern and speed of key input, the frequency and timing of screen operations, and even the user's facial expressions and voice using a camera and microphone to recognize the user's emotions.

[1554] Input: User input patterns, facial expressions, and voice.

[1555] Output: Emotion recognition result.

[1556] Step 7:

[1557] The server adjusts the product recommendations based on the user's emotions recognized by the emotion recognition means, such as prioritizing highly rated products and simplifying the interface.

[1558] Input: Emotion recognition results.

[1559] Output: Tailored recommendation results or interface.

[1560] Step 8:

[1561] The server regenerates a report based on the adjusted recommendations and the new interface and sends it to the terminal, where the user can review the report again and enter any additional requests using the data input means.

[1562] Input: Adjusted recommendation results.

[1563] Output: New comparison report or adjusted interface display.

[1564] Step 9:

[1565] The server searches for the relevant product again based on the additional request from the user, and performs a re-search using a data re-processing means that takes the additional conditions into consideration in the original search results.

[1566] Input: User's additional request.

[1567] Output: Updated product list and comparison results.

[1568] Step 10:

[1569] Once the user has finally decided on the product to purchase, the server uses the purchasing procedure proxy to add the product to the cart using the online shopping site's API, and completes the payment procedure and input of shipping information. Once the purchasing procedure is complete, confirmation information is sent to the terminal, and the user is notified that the purchase has been completed.

[1570] Input: The user's final selection.

[1571] Output: Purchase completion notification.

[1572] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1573] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1574] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1575] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1576] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the conc...

Claims

1. a data entry means for the user to input the type of product they are considering purchasing, their desired features and functionality, and their budget; data transmission means for transmitting data input from the data input means to a server; a data processing means for searching for the relevant product from a plurality of shopping sites and databases on the Internet based on the data transmitted by the data transmission means, and for comparing prices, functions, and features; a report generating means for providing a user with the comparison results obtained by the data processing means; an additional request input means for a user to input additional requests for the report; a data reprocessing means for searching and comparing products again based on the data input by the additional request input means; a purchasing procedure proxy means for carrying out a purchasing procedure on an online shopping site on behalf of the user who has finally decided on the product to purchase; A system including:

2. 10. The system of claim 1, further comprising means for the user to determine which product to ultimately purchase.

3. 2. The system according to claim 1, further comprising means for searching for products from a plurality of shopping sites and databases, generating a comparison report based on the results, and providing the report to the user.

Images