system

Abstract

Provide a system. A means for a user to input conditions relating to a desired product; means for receiving the conditions and storing them in a database; A means for calling APIs of a plurality of online marketplaces to collect product information that meets the conditions; A means for storing the collected product information in a database; means for analyzing products based on the collected information and calculating a score; A means for selecting multiple products with high scores and generating them as a list; a means for notifying a user of the generated list; A system that includes a means for proceeding with the purchase of a product selected by a user using an API of an online marketplace.

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 recent years, with the spread of online shopping, many users have begun to purchase products using multiple online marketplaces. However, the time and effort required to search for product information on each marketplace, compare products, and then make a purchase is extremely cumbersome and places a heavy burden on users. Furthermore, selecting the best product when shopping requires users to carefully examine a large amount of information, which also wastes time and effort. To solve these problems, a system is needed that allows users to easily search for and compare products and efficiently complete the purchasing process. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for a user to input conditions related to a desired product, a means for receiving the input conditions and saving the input conditions in a database, a means for calling the APIs of multiple online marketplaces to collect product information that matches the conditions, a means for saving the collected product information in a database, a means for analyzing the products based on the collected information and calculating a score, a means for selecting multiple products with high scores and generating a list, a means for notifying the user of the generated list, and a means for using the APIs of the online marketplaces to proceed with the purchase procedure for the products selected by the user. This enables a user to efficiently search and compare products that match the conditions, select the most suitable product, and automate the purchase procedure.

[0006] "User" refers to an individual or organization that uses the Service to search for, select, and purchase products.

[0007] The "conditions related to the desired product" refer to specific attributes and specifications related to the product desired by the user, such as requirements for price range, functionality, brand, etc.

[0008] "Database" refers to a system for storing and managing data such as collected product information, user conditions, and purchase history.

[0009] "Online Marketplace" refers to a website or platform for conducting e-commerce transactions, including, for example, general e-commerce sites.

[0010] "API" stands for Application Programming Interface, which allows you to access and use data and functionality from online marketplaces.

[0011] "Product Information" refers to data about a particular product, such as attributes, price, reviews, and availability.

[0012] The "score" is a product evaluation indicator that is analyzed based on collected product information, and refers to a score calculated taking into account factors such as price, user reviews, and reliability.

[0013] "List" refers to a collection of selected products that have been analyzed and evaluated and are presented to the User.

[0014] "Notification" refers to an action to inform the user of the generated list or the completion of the purchase.

[0015] "Purchase procedure" refers to a series of processes including ordering the product selected by the user, making payment, and completing the delivery procedure. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] The present invention provides a system that allows users to search for and compare products from multiple online marketplaces and automate the purchasing process. The system includes a terminal that includes an interface for users to input product-related requirements, a server that receives the requirements and processes the information, and an API for collecting product information.

[0038] First, the user uses a terminal to input product-related requirements. For example, specific requirements such as "laptop computer, price under 100,000 yen, memory 8GB or more, SSD installed" can be input. This input information is sent to the server.

[0039] The server stores the received user conditions in a database. The server then calls the APIs of multiple online marketplaces to collect product information that matches the conditions. For example, it retrieves product lists from online marketplaces such as Amazon, Rakuten, and Yahoo Shopping. The information retrieved from the API includes the product name, price, review rating, and stock status.

[0040] The server then analyzes each product based on the collected product information. The analysis includes factors such as price, review rating, and seller credibility, and calculates a score based on each factor. This score is used to select the best product. As a result, a list of the top N products (e.g., 10) is generated and stored in a database.

[0041] This list is sent from the server to the terminal and displayed to the user. The user can review the product list presented via the terminal and select the appropriate product. Once the user confirms the purchase, the server automatically completes the purchase process using the API of each online marketplace. At this time, the necessary information (shipping address, payment information, etc.) is obtained from the user's account information.

[0042] Finally, when the purchase is complete, the server sends the information to the terminal and notifies the user of the completion of the purchase. The purchase information is also saved in a database.

[0043] For example, if a user enters "laptop computer" as a search condition, the server will search for products on Amazon, Rakuten, Yahoo Shopping, etc., and collect the necessary information. It will then calculate a score based on price and review ratings to select the most suitable product. The user can then review the selected product list, choose the product that best suits their needs, and proceed with the purchase. This allows the user to enjoy a smooth shopping experience.

[0044] The processing flow will be explained below.

[0045] Step 1:

[0046] The user opens the device interface and enters product-related criteria. For example, if the user is looking for a laptop computer, they enter specific criteria such as a price of less than 100,000 yen, 8GB or more of memory, and an SSD.

[0047] Step 2:

[0048] The terminal sends the entered conditions to the server, which receives the conditions and stores them in its database.

[0049] Step 3:

[0050] The server calls the APIs of multiple online marketplaces to collect product information that matches the above conditions. The server then calls the APIs of Amazon, Rakuten, Yahoo Shopping, etc. in order, sets the necessary parameters, and sends the request.

[0051] Step 4:

[0052] The online marketplace receives the request and returns product information that matches the criteria in JSON format. The server parses the received JSON data and extracts product information (product name, price, review rating, stock status, etc.).

[0053] Step 5:

[0054] The server stores the collected product information in a database, centralizing data from different online marketplaces and storing it in a unified format.

[0055] Step 6:

[0056] The server analyzes each product based on the stored product information and calculates a score based on factors such as price, review rating, and seller reliability. The server then weights each of these factors to calculate an overall score.

[0057] Step 7:

[0058] The server selects the top N products (for example, 10) in descending order of score and generates a candidate list. This list is provided to the user and is temporarily stored in a database.

[0059] Step 8:

[0060] The server sends the generated candidate list to the terminal, which receives it and displays the product list to the user. The user reviews this list and selects the product that seems most suitable.

[0061] Step 9:

[0062] The user decides to purchase and presses the purchase button. The device sends the information to the server.

[0063] Step 10:

[0064] The server again calls the API of the online marketplace for the selected product and sends a request to proceed with the purchase. The server obtains the shipping address, payment information, etc. from the user's account information, sets the necessary parameters, and sends the request.

[0065] Step 11:

[0066] The online marketplace receives the purchase request and completes the order process, after which it sends a purchase completion response back to the server.

[0067] Step 12:

[0068] The server receives the response indicating the purchase is complete and sends that information to the terminal. The terminal notifies the user that the purchase is complete and displays the purchase information. At the same time, the server saves the purchase history in a database.

[0069] Example 1

[0070] 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."

[0071] In modern online shopping, it is common for users to individually visit multiple marketplaces to search for products, compare them, and complete the purchase process. However, this process is not only time-consuming and labor-intensive, but also requires manual input according to the specifications of each marketplace, placing a significant burden on users. Furthermore, comparing prices and reviews across different marketplaces is tedious, making it difficult to make the optimal choice. This makes it difficult for users to efficiently purchase the best products at the best prices.

[0072] 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.

[0073] In this invention, the server includes means for a user to input conditions related to a desired product, means for receiving the conditions and saving the conditions in a database, means for calling application programming interfaces of multiple online marketplaces to collect product information that matches the conditions, means for saving the collected product information in a database, means for analyzing the products based on the collected information and calculating a score, means for selecting multiple products with high scores and creating a list, means for notifying the user of the created list, means for proceeding with the purchase of the product selected by the user using the application programming interface of the online marketplace, means for acquiring shipping address and payment information related to the user, means for receiving and notifying the user of completion of the purchase, and means for saving the purchase completion information in a database. This enables a user to search for, compare, and select the optimal product by entering conditions once, without visiting multiple marketplaces, and to automate the purchase process, thereby efficiently and quickly completing the purchase.

[0074] A "user" is an entity that utilizes the system to input criteria for searching, comparing, and purchasing products.

[0075] "Conditions" are attributes or requirements (e.g., price, performance, brand, etc.) that a user specifies regarding a desired product.

[0076] A "terminal" is a computing device that a user uses to enter conditions and receive results.

[0077] A "server" is a central computer system that processes data based on requirements received from users.

[0078] A "database" is a data storage system for storing and managing data such as terms and conditions, product information, and purchase history.

[0079] An "application programming interface (API)" is a standardized interface that a server uses to retrieve product information from an online marketplace.

[0080] A "marketplace" is an online platform where multiple sellers offer products and users can purchase them.

[0081] "Product information" refers to detailed product information obtained from the marketplace (e.g., product name, price, review rating, stock status, etc.).

[0082] The "score" is an evaluation value calculated based on collected product information, taking into account factors such as price, review rating, and seller reliability.

[0083] A "list" refers to a set of products generated by selecting multiple products with high scores.

[0084] "Delivery address" is address information required for a user to receive the purchased product.

[0085] "Payment Information" refers to payment information such as credit card information and bank account information required to complete the purchase process.

[0086] A "purchase procedure" is a series of operations and processes required to complete the purchase of a product selected by a user.

[0087] "Completion information" is information used to confirm that the purchase procedure has been completed successfully.

[0088] The present invention is a system for automating the process of users searching, comparing, and purchasing products from multiple online marketplaces. The system includes a terminal that provides an interface for users to input product-related requirements, a server that receives the requirements and processes the information, and an application programming interface (API) for collecting product information.

[0089] Hardware and software used

[0090] Device: The device on which the user enters product conditions (PC, smartphone, tablet, etc.)

[0091] Servers: Web servers and database servers (e.g., Amazon Web Services, Microsoft® Azure®)

[0092] Database: Relational database such as MySQL (registered trademark), PostgreSQL, etc.

[0093] API: Application programming interface provided by each online marketplace (e.g., Amazon API, Rakuten API, Yahoo Shopping API)

[0094] Analysis tools: Python Pandas, Numpy, etc.

[0095] System details

[0096] 1. Enter and submit product conditions

[0097] The user uses the device interface to input the search criteria for the product they want to search for, for example, "laptop computer, price under 100,000 yen, memory 8GB or more, SSD installed."

[0098] These conditions are transmitted from the terminal to the server.

[0099] 2. Receipt and storage of terms and conditions

[0100] The server stores the received conditions in a database, a process that uses a relational database such as MySQL or PostgreSQL.

[0101] 3. Collection of information

[0102] The server uses the saved conditions to call the API of each marketplace to collect product information. For example, it uses the Amazon API or Rakuten API to obtain product information.

[0103] Information collected includes product name, price, review rating, and availability.

[0104] 4. Data Analysis

[0105] The server analyzes the collected product information using Python's Pandas and Numpy, and calculates a score based on price, review rating, seller reliability, etc.

[0106] 5. Creating and saving a list

[0107] The server selects the best products based on the calculated scores and generates a top N (e.g., 10) product list, which is then stored in the database again.

[0108] 6. List Notification

[0109] The server sends the generated list to the terminal, which receives it and displays it to the user.

[0110] 7. Purchase Procedure

[0111] Once the user selects a product and confirms the purchase, the server obtains the user's shipping address and payment information and automatically completes the purchase process via the marketplace's API.

[0112] 8. Purchase completion notification

[0113] Once the purchase procedure is complete, the server sends a notification of purchase completion to the terminal, which is displayed to the user. The purchase information is also saved in a database.

[0114] Specific examples

[0115] Example of user input: "Laptop, price under 100,000 yen, 8GB or more of memory, SSD installed"

[0116] Example prompt for a generative AI model: "Search for products that meet the criteria of 'laptops, priced under ¥100,000, with at least 8GB of memory and an SSD,' and calculate a score based on price and ratings to select the best product."

[0117] As described above, the system of the present invention allows users to search multiple online marketplaces at once and select and purchase the best products quickly and efficiently.

[0118] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0119] Step 1:

[0120] The user enters product conditions

[0121] Input: The user uses the device interface to input product requirements. For example, they might input "laptop computer, price under 100,000 yen, memory 8GB or more, SSD installed."

[0122] Action: The user enters search criteria into the device's input field and presses the "Search" button.

[0123] Output: The entered conditions are sent from the terminal to the server.

[0124] Step 2:

[0125] The server receives and stores the conditions.

[0126] Input: Product conditions sent from the terminal.

[0127] Behavior: The server checks the received conditions to ensure that the data is valid, then stores it in the database (MySQL or PostgreSQL).

[0128] Output: The valid product terms are saved to the database.

[0129] Step 3:

[0130] The server collects information from the marketplace.

[0131] Input: Product terms stored in the database.

[0132] Operation: The server calls the API of each online marketplace (e.g., Amazon API, Rakuten API, Yahoo Shopping API) and collects product information that matches the product conditions.

[0133] Output: Product information obtained from each marketplace (product name, price, review rating, availability, etc.).

[0134] Step 4:

[0135] The server saves the product information to a database

[0136] Input: Product information collected from each marketplace.

[0137] How it works: The server converts the collected product information into an appropriate format and stores it in a database.

[0138] Output: Product information is saved in the database.

[0139] Step 5:

[0140] The server analyzes the data and calculates the score

[0141] Input: Product information stored in the database.

[0142] How it works: The server analyzes product information and calculates a score based on factors such as price, review rating, seller reliability, etc. Calculations are performed using Python tools such as Pandas and Numpy.

[0143] Output: A score is calculated for each product.

[0144] Step 6:

[0145] The server generates and stores the top N product list

[0146] Input: Product information for which a score is calculated.

[0147] How it works: The server sorts the products based on the calculated score and generates a list of the top N (e.g., 10) products, which is then stored in a database.

[0148] Output: A list of the top N products is generated and stored in a database.

[0149] Step 7:

[0150] The server sends the product list to the terminal.

[0151] Input: A server-generated top-N product list.

[0152] How it works: The server encodes the product list in JSON format and sends it to the device via the REST API.

[0153] Output: The product list is sent to the terminal.

[0154] Step 8:

[0155] The user selects an item and confirms the purchase

[0156] Input: The top N product list sent to the device.

[0157] How it works: The user reviews the product list, selects the product they want, and confirms their purchase. They then enter the required information (shipping address, payment information, etc.) through the device interface.

[0158] Output: The user's selected products and purchase information are sent to the server.

[0159] Step 9:

[0160] The server automatically executes the purchase process

[0161] Input: Your purchase confirmation and account information (shipping address, payment information, etc.).

[0162] How it works: The server calls the purchasing API of each online marketplace and automatically completes the purchase process.

[0163] Output: The purchase is completed.

[0164] Step 10:

[0165] The server sends and saves a purchase completion notification

[0166] Input: Purchase completion information.

[0167] Operation: The server confirms that the purchase was completed successfully, sends a notification to the device, and saves the purchase completion information in the database.

[0168] Output: A purchase completion notice will be displayed on the terminal, and the purchase completion information will be saved in the database.

[0169] (Application example 1)

[0170] 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."

[0171] In modern society, users spend a great deal of time and effort searching, comparing, and purchasing products from multiple electronic markets. This has led to a growing need for systems that can efficiently select optimal products and automate the purchasing process. Furthermore, ambiguity that arises when entering search criteria and the difficulty of comparing different information across different markets are also issues. Furthermore, it is important to provide an environment where users can easily perform these operations using their smartphones.

[0172] 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.

[0173] In this invention, the server includes: a means for a user to input search criteria for a desired product; a means for receiving the search criteria and saving the search criteria in a database; a means for calling APIs of multiple online markets to collect product information that matches the search criteria; a means for saving the collected product information in a database; a means for analyzing the products based on the collected information and calculating a score; a means for selecting multiple products with high scores and generating a list; a means for notifying the user of the generated list; a means for completing the purchase process for the user-selected products using the online market API; a means implemented as a smartphone application for the above means; and a means for generating prompt sentences using a generative AI model when the user enters search criteria. This allows users to efficiently search, compare, and purchase appropriate products from multiple online markets at once. Furthermore, generating prompt sentences eliminates input ambiguity, facilitating operation from a smartphone.

[0174] "User" means any person or entity that uses the System to search for, compare, and purchase products.

[0175] "Product conditions" are specific standards and requirements (e.g., price, specifications, rating) regarding the product desired by the user.

[0176] A "database" is a system that stores and manages data such as product information and user conditions.

[0177] An "electronic marketplace" is an online marketplace that sells goods over the Internet.

[0178] "API" stands for Application Programming Interface, an interface that allows electronic market services to exchange data with the outside world.

[0179] "Product Information" means product details (e.g., price, reviews, availability) collected from each electronic marketplace.

[0180] "Product analysis" is the process of evaluating the value and suitability of a product based on collected product information and according to multiple evaluation criteria.

[0181] A "score" is a numerical evaluation of each product based on the results of product analysis.

[0182] The "list" is a compilation of the results of selecting products with high scores.

[0183] "Notification" is a means of informing the user of important information (e.g., product list, purchase completion).

[0184] A "purchase process" is a series of steps to purchase a product on an online marketplace.

[0185] A "smartphone application" is application software that runs on a smartphone.

[0186] A "generative AI model" is a model that uses artificial intelligence technology to generate prompts and other text based on user input.

[0187] "Prompt sentences" are guidelines or example sentences created using generative AI models when a user types something.

[0188] The present invention is a system that allows users to search for and compare products from multiple online markets and automate the purchasing process. The system includes a terminal with an interface through which users input product-related requirements, a server that receives the requirements and processes the information, and an API for collecting product information.

[0189] First, the user uses a smartphone to input product-related criteria. At this time, a generative AI model can be used to generate a prompt sentence, which can be presented to the user as an input guide. For example, a generated prompt sentence might read, "I'm looking for a laptop computer. Priced at under 100,000 yen, with at least 8GB of memory and an SSD." The user then inputs their criteria based on this prompt sentence.

[0190] The entered information is sent from the user's smartphone to a server. The server stores the received user conditions in a database. The server then calls the APIs of multiple online markets to collect product information that matches the conditions. Typical examples of online markets include Amazon, Rakuten, and Yahoo Shopping. Information obtained from the API includes product name, price, review rating, and stock status.

[0191] Next, the server analyzes each product based on the collected product information. The analysis includes factors such as price, review rating, and seller reliability, and calculates a score based on each factor. The server uses this score to select the best product. As a result, a list of the top N products (for example, 10) is generated and stored in a database. This list is then sent from the server to a smartphone and notified to the user.

[0192] Users can view the product list displayed on their smartphones and select the appropriate product. Once the user confirms the purchase, the server automatically completes the purchase process using the API of each online marketplace. At this time, necessary information (shipping address, payment information, etc.) is obtained from the user's account information.

[0193] Finally, once the purchase is complete, the server sends the information to the user's smartphone and notifies them of the purchase. The purchase information is also stored in a database, allowing users to efficiently search, compare, and purchase suitable products from multiple online markets all at once.

[0194] For example, if a user enters "laptop computer" as a search condition, the server will search for products on Amazon, Rakuten, Yahoo Shopping, etc., and collect the necessary information. It will then calculate a score based on price and review ratings to select the most suitable product. The user can then review the selected product list, choose the product that best suits their needs, and proceed with the purchase. This allows the user to enjoy a smooth shopping experience.

[0195] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0196] Step 1:

[0197] A user uses a smartphone to input product-related criteria. The user uses the generative AI model to display a prompt ("I'm looking for a laptop computer. It should cost less than 100,000 yen, have 8GB or more of memory, and have an SSD.") while inputting the criteria. The entered criteria (e.g., laptop computer, price less than 100,000 yen, 8GB or more of memory, and have an SSD) are sent from the smartphone to the server.

[0198] Step 2:

[0199] The server stores the received user requirements in a database, where separate data for each user is stored and indexed for later use.

[0200] Step 3:

[0201] The server calls the APIs of multiple online markets to collect product information that matches the above conditions. Specifically, it uses the APIs of Amazon, Rakuten, and Yahoo Shopping to collect information such as product name, price, review rating, and stock status. The collected product information is temporarily stored in a database.

[0202] Step 4:

[0203] The server analyzes each product based on the collected product information, taking into account factors such as price, review rating, and seller reliability. A score is calculated based on each factor, and a score is assigned to each product. The lower the price, the higher the score, and the higher the review rating, the higher the score.

[0204] Step 5:

[0205] The server selects the top 10 products and generates a list. This list is ranked to include the products that best match the criteria entered by the user. The list is stored in a database and sent to the user's smartphone.

[0206] Step 6:

[0207] The user's smartphone notifies the user of the product list received from the server and displays it. The user selects any product from the presented list. The product information selected by the user is sent from the smartphone to the server.

[0208] Step 7:

[0209] The server automatically uses the API of the online marketplace to process the purchase of the product selected by the user. Specifically, it obtains user information such as shipping address and payment information and completes the purchase through each online marketplace's API. Once the purchase is complete, the information is saved in a database and a purchase completion notification is sent to the smartphone.

[0210] Step 8:

[0211] The server saves the purchase history in a database for future recommendations and history inquiries. A notification is displayed on the user's smartphone indicating that the purchase has been completed, and all processing is complete.

[0212] 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.

[0213] The present invention combines a system that allows users to search for and compare products from multiple online marketplaces and automates the purchasing process with an emotion engine that recognizes user emotions. This system includes a terminal that includes an interface through which users input product-related conditions, a server that receives the conditions and processes the information, an API for collecting product information, and an emotion engine that recognizes user emotions.

[0214] First, the user opens the device interface and inputs the product requirements. For example, they can enter specific requirements such as "laptop computer, price under 100,000 yen, memory over 8GB, SSD installed." This input information is sent to the server.

[0215] The server stores the received user's requirements in a database. Next, the server calls the APIs of multiple online marketplaces to collect product information that matches the requirements. For example, it retrieves product lists from online marketplaces such as Amazon, Rakuten, and Yahoo Shopping. The information retrieved from the API includes the product name, price, review rating, and stock status.

[0216] The server then analyzes each product based on the collected product information. The analysis includes factors such as price, review rating, and seller credibility, and calculates a score based on each factor. This score is used to select the best product. As a result, a list of the top N products (e.g., 10) is generated and stored in a database.

[0217] This list is sent from the server to the terminal and displayed to the user. The user can check the product list presented via the terminal and select an appropriate product. Here, the emotion engine recognizes emotions from the user's facial expressions and voice and collects the user's emotional data.

[0218] The server analyzes the emotional data and adjusts the product list according to the user's emotions. For example, if the user is unsure, it will prioritize products with high reviews and display them at the top of the list. On the other hand, if the user is excited, it will recommend high-quality products with slightly higher prices.

[0219] Once the user confirms the purchase, the server automatically processes the purchase using the API of each online marketplace. At this time, the necessary information (shipping address, payment information, etc.) is obtained from the user's account information. Once the purchase is complete, the server sends the information to the terminal and notifies the user that the purchase has been completed. The purchase information is also saved in a database.

[0220] For example, if a user enters "laptop computer" as a search term, the server will search for products on Amazon, Rakuten, Yahoo Shopping, etc., and collect the necessary information. It will then calculate a score based on price and review ratings to select the most suitable product. It will use an emotion engine to detect the user's hesitation or excitement and recommend products accordingly. The user can then review the selected product list, choose the product that best suits their needs, and proceed with the purchase. This allows the user to enjoy a smooth shopping experience.

[0221] The processing flow will be explained below.

[0222] Step 1:

[0223] The user opens the device interface and enters product-related criteria. For example, if the user is looking for a laptop computer, they enter specific criteria such as a price of less than 100,000 yen, 8GB or more of memory, and an SSD.

[0224] Step 2:

[0225] The terminal sends the entered conditions to the server, which receives the conditions and stores them in its database.

[0226] Step 3:

[0227] The server starts the emotion engine and starts collecting the user's facial expressions and voice data in real time, which allows the user's emotional data to be continuously analyzed.

[0228] Step 4:

[0229] The server calls the APIs of multiple online marketplaces to collect product information that matches the above conditions. The server then calls the APIs of Amazon, Rakuten, Yahoo Shopping, etc. in order, sets the necessary parameters, and sends the request.

[0230] Step 5:

[0231] The online marketplace receives the request and returns product information that matches the criteria in JSON format. The server parses the received JSON data and extracts product information (product name, price, review rating, stock status, etc.).

[0232] Step 6:

[0233] The server stores the collected product information in a database, centralizing data from different online marketplaces and storing it in a unified format.

[0234] Step 7:

[0235] The server analyzes each product based on the stored product information and calculates a score based on factors such as price, review rating, and seller reliability. The server then weights each of these factors to calculate an overall score.

[0236] Step 8:

[0237] The server selects the top N products (for example, 10) in descending order of score and generates a candidate list. This list is provided to the user and is temporarily stored in a database.

[0238] Step 9:

[0239] The server sends the generated candidate list to the terminal, which receives it and displays the product list to the user. The user can check this list and select an appropriate product.

[0240] Step 10:

[0241] The emotion engine analyzes the user's emotion data in real time and provides feedback to the server according to the user's emotion. If the user is unsure, the emotion engine detects the user's uncertain emotion and notifies the server. If the user is excited, the emotion engine measures the level of excitement and notifies the server.

[0242] Step 11:

[0243] The server adjusts the product list based on feedback from the emotion engine. For example, if the user is unsure, it will prioritize products with high reviews. If the user is excited, it will recommend high-quality products with higher prices.

[0244] Step 12:

[0245] The user decides to purchase and presses the purchase button. The device sends the information to the server.

[0246] Step 13:

[0247] The server again calls the API of the online marketplace for the selected product and sends a request to proceed with the purchase. The server obtains the shipping address, payment information, etc. from the user's account information, sets the necessary parameters, and sends the request.

[0248] Step 14:

[0249] The online marketplace receives the purchase request and completes the order process, after which it sends a purchase completion response back to the server.

[0250] Step 15:

[0251] The server receives the response indicating the purchase is complete and sends that information to the terminal. The terminal notifies the user that the purchase is complete and displays the purchase information. At the same time, the server saves the purchase history in a database.

[0252] Example 2

[0253] 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."

[0254] In today's online shopping environment, users must simultaneously search multiple online marketplaces and compare information from each. This requires a lot of time and effort, potentially compromising the user experience. Another issue is that product selection is often based solely on impersonal data, without taking into account the user's emotions, preventing them from making the best choice.

[0255] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0256] In this invention, the server includes: means for a user to input conditions related to a desired product; means for receiving the conditions and storing the conditions in a database; means for calling APIs of multiple online marketplaces to collect product information that matches the conditions; means for storing the collected product information in a database; means for analyzing products based on the collected information and calculating a score; means for selecting multiple products with high scores and generating a list; means for notifying the user of the generated list; means for proceeding with the purchase of the products selected by the user using the APIs of the online marketplaces; means for recognizing the user's emotions and collecting emotion data; means for adjusting the product list based on the emotion data; and means for notifying the user of purchase completion information and storing the data in a database. This enables users to efficiently perform a series of operations from product search to comparison to purchase, and further enables product selection that takes emotion into consideration.

[0257] "User" refers to a user of the system who inputs product-related conditions and searches, compares, and purchases based on those conditions.

[0258] "Conditions" refer to specific requirements or filter items that a user inputs for a desired product, such as price, specifications, brand, etc.

[0259] A "database" is an information storage system for storing and managing collected and analyzed product information, user conditions, purchase history, and other data.

[0260] An "online marketplace" is a platform where products are bought and sold over the Internet, and refers to a marketplace where multiple sellers list their products.

[0261] "API" stands for Application Programming Interface, a technology that provides a means for different software applications to communicate with each other.

[0262] "Product Information" means detailed product data collected from online marketplaces, including product name, price, review rating, and availability.

[0263] A "score" is a numerical indicator calculated by analyzing collected product information and based on its conformance to conditions and evaluation.

[0264] The "list" is a collection of products selected in descending order of score, and is a list of products notified to the user.

[0265] An "emotion engine" is a technology that recognizes emotions from a user's facial expressions, voice, etc., and collects and analyzes that data.

[0266] The "purchase process" refers to a series of operations and processes that a user performs to actually purchase a selected product from an online marketplace.

[0267] "Proceeding with the purchase procedure" is an execution process that automatically advances the purchase process for the product selected by the user via the API of the online marketplace.

[0268] The "completion notification" is information that notifies the user that the purchase procedure has been completed.

[0269] "Emotional Data" refers to data about a user's emotions collected and analyzed by the emotion engine.

[0270] "Adjustment" refers to the operation or process of changing product listings or recommendations based on collected emotional data.

[0271] The present invention combines a system that allows users to search for and compare products from multiple online marketplaces and automates the purchasing process with an emotion engine that recognizes user emotions. This system includes a terminal that includes an interface through which users input product-related conditions, a server that receives the conditions and processes the information, an API for collecting product information, and an emotion engine that recognizes user emotions.

[0272] First, the user opens the device interface and inputs the product requirements. For example, they can enter specific requirements such as "laptop computer, price under 100,000 yen, memory over 8GB, SSD installed." This input information is sent to the server.

[0273] The server stores the received user conditions in a database, using a relational database such as MongoDB or MySQL. The server then calls the APIs of multiple online marketplaces to collect product information that matches the conditions from, for example, Amazon, Rakuten, and Yahoo Shopping. The information obtained from the API includes the product name, price, review rating, and stock status.

[0274] The server then analyzes each product based on the collected product information. The analysis includes factors such as price, review rating, and seller credibility, and calculates a score based on each factor. This score is used to select the best product. As a result, a list of the top N products (e.g., 10) is generated and stored in a database.

[0275] This list is sent from the server to the device and displayed to the user. The user checks the product list presented via the device. At this time, the emotion engine recognizes emotions from the user's facial expressions and voice and collects emotional data. The emotion engine uses Microsoft's facial recognition API and voice recognition SDK.

[0276] The server analyzes the emotional data and adjusts the product list according to the user's emotions. For example, if the user is unsure, it will prioritize products with high reviews and display them at the top of the list. On the other hand, if the user is excited, it will recommend high-quality products with slightly higher prices.

[0277] Once the user confirms the purchase, the server automatically processes the purchase using the API of each online marketplace. At this time, the necessary information (shipping address, payment information, etc.) is obtained from the user's account information. Once the purchase is complete, the server sends the information to the terminal and notifies the user that the purchase has been completed. The purchase information is also saved in a database.

[0278] For example, if a user enters "laptop computer" as a search condition, the server will search for products on Amazon, Rakuten, Yahoo Shopping, etc., and collect the necessary information. It will then calculate a score based on price and review ratings to select the most suitable product. It will use an emotion engine to detect the user's hesitation or excitement, and recommend products accordingly. The user can then review the selected product list, choose the product that best suits their needs, and proceed with the purchase.

[0279] To implement this system, the following example prompts are provided:

[0280] "I'm looking for a laptop computer, but I'd like one that costs under 100,000 yen, has 8GB or more of memory, and has an SSD."

[0281] As described above, the present invention enables users to quickly and efficiently search for and compare products from multiple online marketplaces, and further select and purchase the most suitable product taking their emotions into consideration.

[0282] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0283] Step 1:

[0284] The user opens the terminal interface and inputs product-related conditions. The input data includes the product type (e.g., "laptop computer"), upper price limit (e.g., "under 100,000 yen"), memory capacity (e.g., "8GB or more"), and storage type (e.g., "equipped with SSD"). These conditions become the basis for data processing in subsequent processes. The input information is sent to the server via the user interface.

[0285] Step 2:

[0286] The device receives the condition data entered by the user and sends it to the server via an HTTP request. Specifically, the request is formed in the format "Product: Laptop, Price: Under 100,000 yen, Memory: 8GB or more, Storage: SSD." The input is the user's condition data, and the output is an HTTP request to the server.

[0287] Step 3:

[0288] The server analyzes the received user condition data and stores it in a relational database (for example, MongoDB or MySQL). Specifically, various conditions are saved as fields and used for future data reference and linkage. The input is the condition data sent by the user, and the output is the condition information stored in the database.

[0289] Step 4:

[0290] The server sequentially calls the APIs of multiple online marketplaces (e.g., the APIs of Amazon, Rakuten, and Yahoo Shopping) based on the stored condition data. It then sends requests to collect product information that matches the conditions. The input is the condition data stored in the database, and the output is product information obtained from each marketplace.

[0291] Step 5:

[0292] The server analyzes the retrieved product information and calculates a score for each product based on multiple factors, such as price, review rating, and seller reliability. A scoring algorithm is used to identify the product that best meets the user's criteria. The input is product data retrieved from the API, and the output is the analyzed score for each product.

[0293] Step 6:

[0294] The server sorts the products in descending order of score based on the calculated score. It then generates a list of the top N (e.g., top 10) products and stores it in a database. Here, a method is applied to efficiently provide the analysis results to the user. The input is score information, and the output is the top N product list.

[0295] Step 7:

[0296] The server sends the generated product list to the terminal as an HTTP response and displays it to the user. The input is the top N product list, and the output is the product list displayed to the user.

[0297] Step 8:

[0298] While the user is browsing the product list, the device's emotion engine (for example, Microsoft's facial recognition API or voice recognition SDK) collects the user's facial expression and voice data in real time. For example, a webcam and microphone are used for facial recognition and voice analysis. The input is the user's real-time facial expression and voice, and the output is emotion data.

[0299] Step 9:

[0300] The server analyzes the collected emotional data and adjusts the product list according to the user's psychological state (e.g., indecision, excitement). For example, if the user is indecisive, products with high review ratings are prioritized and displayed at the top of the list. The input is emotional data, and the output is the adjusted product list.

[0301] Step 10:

[0302] When a user confirms a purchase, the server automatically initiates the purchase process using the API of each online marketplace. The input is the product selected by the user and account information, and the output is the execution and completion of the purchase process.

[0303] Step 11:

[0304] When the purchase is completed, the server notifies the user of the purchase completion and simultaneously saves the purchase history in a database. The input is the purchase completion information, and the output is the notification to the user and the history saved in the database.

[0305] The above processing steps enable users to efficiently search, compare, and purchase products, and realize a system that allows for recommendations that take emotions into consideration.

[0306] (Application example 2)

[0307] 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."

[0308] Existing online shopping systems require a lot of effort for users to select products, and they often feel lost or have difficulty in making purchasing decisions. In addition, they provide mechanical recommendations without considering the user's emotional state, which results in a poor user experience.

[0309] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input conditions related to a desired product; means for receiving the conditions and saving them in a database; means for calling application programming interfaces of multiple online marketplaces to collect product information that matches the conditions; means for saving the collected product information in a database; means for analyzing products based on the collected information and calculating a score; means for selecting multiple products with high scores and creating a list; means for notifying the user of the created list; means for recognizing emotions from the user's facial expressions and voice and adjusting the product list based on the collected user emotion data; and means for completing the purchase procedure for the products selected by the user using the application programming interface of the online marketplace. This reduces the confusion and difficulty that users may experience when selecting products and enables appropriate product recommendations based on the user's emotional state.

[0310] A "User" is a person or entity that intends to search for and purchase a product.

[0311] "Conditions" are attributes or requirements that a user specifies when searching for a particular product.

[0312] A "database" is a system for storing and managing product information, user requirements, and emotional data.

[0313] An "application programming interface (API)" is an interface for exchanging information between different systems.

[0314] "Product information" refers to data such as product name, price, review rating, and stock status obtained from online marketplaces.

[0315] "Emotion recognition" is a technology that analyzes a user's facial expressions and voice to determine their emotional state.

[0316] The "score" is an evaluation value calculated based on collected product information, taking into account factors such as price, review rating, and seller reliability.

[0317] A "list" is a format for displaying multiple products selected based on their scores in an ordered manner.

[0318] "Emotion data" refers to data relating to the emotional state of the user recognized from facial expressions and voice.

[0319] An "online marketplace" is a platform for selling products over the Internet.

[0320] The "purchase procedure" is the procedure for a user to purchase a product selected by the user on the online marketplace.

[0321] The system of the present invention allows users to efficiently search for desired products using a smartphone and improves product selection through an emotion recognition engine. A specific embodiment of this system is described below.

[0322] First, a user launches a dedicated application on their smartphone and inputs the desired product's conditions, such as the category (e.g., "laptop"), price limit, required memory capacity, and storage type.

[0323] The terminal sends the conditions received from the user to the server, which stores these conditions in a database and calls the application programming interfaces (APIs) of multiple online marketplaces to collect product information that matches the conditions. This includes price comparison sites, and the information obtained includes product name, price, review rating, and stock status.

[0324] The server then analyzes the collected product information based on factors such as price, reviews, and seller reliability, and calculates a score based on each.The best products are selected based on this score and generated as a list.The generated list is stored in a database and notified to the device.

[0325] Furthermore, while the user is browsing the product list, an emotion recognition engine analyzes the user's facial expressions and voice using the device's built-in camera and microphone to collect emotional data. This emotional data is sent to the server, which then adjusts the product list based on the user's emotional state. For example, if the user is confused, the server can prioritize products with high reviews, while if the user is excited, the server can prioritize higher-priced, high-performance products at the top of the list.

[0326] Once the user selects the product to purchase, the server automatically completes the purchase process using the API of each online marketplace. During this process, the user's account information (shipping address, payment information, etc.) is securely processed. Once the purchase is complete, the server sends a notification of purchase completion to the device, and the purchase history is saved in a database.

[0327] Here's a concrete example: Suppose the user enters the following conditions:

[0328] Example prompt sentence:

[0329] "Laptop, price under 100,000 yen, 8GB or more of memory, SSD installed"

[0330] The server collects product information from multiple online marketplaces, scores them based on reviews and prices, and then presents a list to the user. At the same time, it analyzes the user's facial and voice data to determine their emotional state and suggests products that fit that emotional state. This process allows the user to have an efficient and emotionally adaptive shopping experience.

[0331] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0332] Step 1:

[0333] The user launches a dedicated application on their smartphone and inputs the conditions for the desired product. The input data includes the category (e.g., "laptop"), the upper price limit, the required memory capacity, the type of storage, etc. The input conditions are sent from the device to the server.

[0334] Step 2:

[0335] The server stores the received conditions in a database, including the user-entered conditions such as category, price limit, memory capacity, and storage type.

[0336] Step 3:

[0337] The server calls the application programming interfaces (APIs) of multiple online marketplaces to collect product information that matches the criteria. Specifically, the APIs are used to obtain product information, and the obtained data includes product name, price, review rating, and stock status. This data is then sent to the server.

[0338] Step 4:

[0339] The server stores the collected product information in a database, including product names, prices, review ratings, and stock availability obtained from each online marketplace.

[0340] Step 5:

[0341] The server analyzes the products based on the collected information and calculates a score. Specifically, it analyzes factors such as price, reviews, and seller reliability, and scores the products based on each factor. Scoring includes data processing (normalization, weighted average, etc.) and data calculation.

[0342] Step 6:

[0343] The server selects multiple products with high scores and generates a list, which is then stored in a database.

[0344] Step 7:

[0345] The server notifies the user of the generated list, which includes the scored products and their detailed information (price, review rating, stock status, etc.).

[0346] Step 8:

[0347] While the user is browsing the product list, the device's built-in camera and microphone are used to collect the user's facial expressions and voice. The emotion recognition engine analyzes the collected data and generates the user's emotion data. The generated emotion data is then sent from the device to the server.

[0348] Step 9:

[0349] The server adjusts the product list based on the user's emotional data. Specifically, the server analyzes the emotional data and adjusts the product list so that, for example, if the user is confused, products with high reviews are prioritized, and if the user is excited, higher-priced, high-performance products are prioritized and displayed at the top of the list.

[0350] Step 10:

[0351] The server automatically completes the purchase process for the product selected by the user using the API of each online marketplace. The information required for the purchase (shipping address, payment information, etc.) is obtained from the user's account information, and the purchase process is completed.

[0352] Step 11:

[0353] When the purchase is complete, the server sends a notification of the purchase completion to the terminal and saves the purchase history in a database, which includes the name of the purchased product, the purchase date and time, the price, shipping information, etc.

[0354] 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.

[0355] 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.

[0356] 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.

[0357] [Second embodiment]

[0358] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0359] 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.

[0360] 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).

[0361] 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.

[0362] 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.

[0363] 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).

[0364] 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. 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.

[0365] 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.

[0366] 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.

[0367] 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.

[0368] 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.

[0369] 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."

[0370] The present invention provides a system that allows users to search for and compare products from multiple online marketplaces and automate the purchasing process. The system includes a terminal that includes an interface for users to input product-related requirements, a server that receives the requirements and processes the information, and an API for collecting product information.

[0371] First, the user uses a terminal to input product-related requirements. For example, specific requirements such as "laptop computer, price under 100,000 yen, memory 8GB or more, SSD installed" can be input. This input information is sent to the server.

[0372] The server stores the received user conditions in a database. The server then calls the APIs of multiple online marketplaces to collect product information that matches the conditions. For example, it retrieves product lists from online marketplaces such as Amazon, Rakuten, and Yahoo Shopping. The information retrieved from the API includes the product name, price, review rating, and stock status.

[0373] The server then analyzes each product based on the collected product information. The analysis includes factors such as price, review rating, and seller credibility, and calculates a score based on each factor. This score is used to select the best product. As a result, a list of the top N products (e.g., 10) is generated and stored in a database.

[0374] This list is sent from the server to the terminal and displayed to the user. The user can review the product list presented via the terminal and select the appropriate product. Once the user confirms the purchase, the server automatically completes the purchase process using the API of each online marketplace. At this time, the necessary information (shipping address, payment information, etc.) is obtained from the user's account information.

[0375] Finally, when the purchase is complete, the server sends the information to the terminal and notifies the user of the completion of the purchase. The purchase information is also saved in a database.

[0376] For example, if a user enters "laptop computer" as a search condition, the server will search for products on Amazon, Rakuten, Yahoo Shopping, etc., and collect the necessary information. It will then calculate a score based on price and review ratings to select the most suitable product. The user can then review the selected product list, choose the product that best suits their needs, and proceed with the purchase. This allows the user to enjoy a smooth shopping experience.

[0377] The processing flow will be explained below.

[0378] Step 1:

[0379] The user opens the device interface and enters product-related criteria. For example, if the user is looking for a laptop computer, they enter specific criteria such as a price of less than 100,000 yen, 8GB or more of memory, and an SSD.

[0380] Step 2:

[0381] The terminal sends the entered conditions to the server, which receives the conditions and stores them in its database.

[0382] Step 3:

[0383] The server calls the APIs of multiple online marketplaces to collect product information that matches the above conditions. The server then calls the APIs of Amazon, Rakuten, Yahoo Shopping, etc. in order, sets the necessary parameters, and sends the request.

[0384] Step 4:

[0385] The online marketplace receives the request and returns product information that matches the criteria in JSON format. The server parses the received JSON data and extracts product information (product name, price, review rating, stock status, etc.).

[0386] Step 5:

[0387] The server stores the collected product information in a database, centralizing data from different online marketplaces and storing it in a unified format.

[0388] Step 6:

[0389] The server analyzes each product based on the stored product information and calculates a score based on factors such as price, review rating, and seller reliability. The server then weights each of these factors to calculate an overall score.

[0390] Step 7:

[0391] The server selects the top N products (for example, 10) in descending order of score and generates a candidate list. This list is provided to the user and is temporarily stored in a database.

[0392] Step 8:

[0393] The server sends the generated candidate list to the terminal, which receives it and displays the product list to the user. The user reviews this list and selects the product that seems most suitable.

[0394] Step 9:

[0395] The user decides to purchase and presses the purchase button. The device sends the information to the server.

[0396] Step 10:

[0397] The server again calls the API of the online marketplace for the selected product and sends a request to proceed with the purchase. The server obtains the shipping address, payment information, etc. from the user's account information, sets the necessary parameters, and sends the request.

[0398] Step 11:

[0399] The online marketplace receives the purchase request and completes the order process, after which it sends a purchase completion response back to the server.

[0400] Step 12:

[0401] The server receives the response indicating the purchase is complete and sends that information to the terminal. The terminal notifies the user that the purchase is complete and displays the purchase information. At the same time, the server saves the purchase history in a database.

[0402] Example 1

[0403] 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."

[0404] In modern online shopping, it is common for users to individually visit multiple marketplaces to search for products, compare them, and complete the purchase process. However, this process is not only time-consuming and labor-intensive, but also requires manual input according to the specifications of each marketplace, placing a significant burden on users. Furthermore, comparing prices and reviews across different marketplaces is tedious, making it difficult to make the optimal choice. This makes it difficult for users to efficiently purchase the best products at the best prices.

[0405] 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.

[0406] In this invention, the server includes means for a user to input conditions related to a desired product, means for receiving the conditions and saving the conditions in a database, means for calling application programming interfaces of multiple online marketplaces to collect product information that matches the conditions, means for saving the collected product information in a database, means for analyzing the products based on the collected information and calculating a score, means for selecting multiple products with high scores and creating a list, means for notifying the user of the created list, means for proceeding with the purchase of the product selected by the user using the application programming interface of the online marketplace, means for acquiring shipping address and payment information related to the user, means for receiving and notifying the user of completion of the purchase, and means for saving the purchase completion information in a database. This enables a user to search for, compare, and select the optimal product by entering conditions once, without visiting multiple marketplaces, and to automate the purchase process, thereby efficiently and quickly completing the purchase.

[0407] A "user" is an entity that utilizes the system to input criteria for searching, comparing, and purchasing products.

[0408] "Conditions" are attributes or requirements (e.g., price, performance, brand, etc.) that a user specifies regarding a desired product.

[0409] A "terminal" is a computing device that a user uses to enter conditions and receive results.

[0410] A "server" is a central computer system that processes data based on requirements received from users.

[0411] A "database" is a data storage system for storing and managing data such as terms and conditions, product information, and purchase history.

[0412] An "application programming interface (API)" is a standardized interface that a server uses to retrieve product information from an online marketplace.

[0413] A "marketplace" is an online platform where multiple sellers offer products and users can purchase them.

[0414] "Product information" refers to detailed product information obtained from the marketplace (e.g., product name, price, review rating, stock status, etc.).

[0415] The "score" is an evaluation value calculated based on collected product information, taking into account factors such as price, review rating, and seller reliability.

[0416] A "list" refers to a set of products generated by selecting multiple products with high scores.

[0417] "Delivery address" is address information required for a user to receive the purchased product.

[0418] "Payment Information" refers to payment information such as credit card information and bank account information required to complete the purchase process.

[0419] A "purchase procedure" is a series of operations and processes required to complete the purchase of a product selected by a user.

[0420] "Completion information" is information used to confirm that the purchase procedure has been completed successfully.

[0421] The present invention is a system for automating the process of users searching, comparing, and purchasing products from multiple online marketplaces. The system includes a terminal that provides an interface for users to input product-related requirements, a server that receives the requirements and processes the information, and an application programming interface (API) for collecting product information.

[0422] Hardware and software used

[0423] Device: The device on which the user enters product conditions (PC, smartphone, tablet, etc.)

[0424] Servers: Web servers and database servers (e.g., Amazon Web Services, Microsoft Azure)

[0425] Database: Relational database such as MySQL or PostgreSQL

[0426] API: Application programming interface provided by each online marketplace (e.g., Amazon API, Rakuten API, Yahoo Shopping API)

[0427] Analysis tools: Python Pandas, Numpy, etc.

[0428] System details

[0429] 1. Enter and submit product conditions

[0430] The user uses the device interface to input the search criteria for the product they want to search for, for example, "laptop computer, price under 100,000 yen, memory 8GB or more, SSD installed."

[0431] These conditions are transmitted from the terminal to the server.

[0432] 2. Receipt and storage of terms and conditions

[0433] The server stores the received conditions in a database, a process that uses a relational database such as MySQL or PostgreSQL.

[0434] 3. Collection of information

[0435] The server uses the saved conditions to call the API of each marketplace to collect product information. For example, it uses the Amazon API or Rakuten API to obtain product information.

[0436] Information collected includes product name, price, review rating, and availability.

[0437] 4. Data Analysis

[0438] The server analyzes the collected product information using Python's Pandas and Numpy, and calculates a score based on price, review rating, seller reliability, etc.

[0439] 5. Creating and saving a list

[0440] The server selects the best products based on the calculated scores and generates a top N (e.g., 10) product list, which is then stored in the database again.

[0441] 6. List Notification

[0442] The server sends the generated list to the terminal, which receives it and displays it to the user.

[0443] 7. Purchase Procedure

[0444] Once the user selects a product and confirms the purchase, the server obtains the user's shipping address and payment information and automatically completes the purchase process via the marketplace's API.

[0445] 8. Purchase completion notification

[0446] Once the purchase procedure is complete, the server sends a notification of purchase completion to the terminal, which is displayed to the user. The purchase information is also saved in a database.

[0447] Specific examples

[0448] Example of user input: "Laptop, price under 100,000 yen, 8GB or more of memory, SSD installed"

[0449] Example prompt for a generative AI model: "Search for products that meet the criteria of 'laptops, priced under ¥100,000, with at least 8GB of memory and an SSD,' and calculate a score based on price and ratings to select the best product."

[0450] As described above, the system of the present invention allows users to search multiple online marketplaces at once and select and purchase the best products quickly and efficiently.

[0451] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0452] Step 1:

[0453] The user enters product conditions

[0454] Input: The user uses the device interface to input product requirements. For example, they might input "laptop computer, price under 100,000 yen, memory 8GB or more, SSD installed."

[0455] Action: The user enters search criteria into the device's input field and presses the "Search" button.

[0456] Output: The entered conditions are sent from the terminal to the server.

[0457] Step 2:

[0458] The server receives and stores the conditions.

[0459] Input: Product conditions sent from the terminal.

[0460] Behavior: The server checks the received conditions to ensure that the data is valid, then stores it in the database (MySQL or PostgreSQL).

[0461] Output: The valid product terms are saved to the database.

[0462] Step 3:

[0463] The server collects information from the marketplace.

[0464] Input: Product terms stored in the database.

[0465] Operation: The server calls the API of each online marketplace (e.g., Amazon API, Rakuten API, Yahoo Shopping API) and collects product information that matches the product conditions.

[0466] Output: Product information obtained from each marketplace (product name, price, review rating, availability, etc.).

[0467] Step 4:

[0468] The server saves the product information to a database

[0469] Input: Product information collected from each marketplace.

[0470] How it works: The server converts the collected product information into an appropriate format and stores it in a database.

[0471] Output: Product information is saved in the database.

[0472] Step 5:

[0473] The server analyzes the data and calculates the score

[0474] Input: Product information stored in the database.

[0475] How it works: The server analyzes product information and calculates a score based on factors such as price, review rating, seller reliability, etc. Calculations are performed using Python tools such as Pandas and Numpy.

[0476] Output: A score is calculated for each product.

[0477] Step 6:

[0478] The server generates and stores the top N product list

[0479] Input: Product information for which a score is calculated.

[0480] How it works: The server sorts the products based on the calculated score and generates a list of the top N (e.g., 10) products, which is then stored in a database.

[0481] Output: A list of the top N products is generated and stored in a database.

[0482] Step 7:

[0483] The server sends the product list to the terminal.

[0484] Input: A server-generated top-N product list.

[0485] How it works: The server encodes the product list in JSON format and sends it to the device via the REST API.

[0486] Output: The product list is sent to the terminal.

[0487] Step 8:

[0488] The user selects an item and confirms the purchase

[0489] Input: The top N product list sent to the device.

[0490] How it works: The user reviews the product list, selects the product they want, and confirms their purchase. They then enter the required information (shipping address, payment information, etc.) through the device interface.

[0491] Output: The user's selected products and purchase information are sent to the server.

[0492] Step 9:

[0493] The server automatically executes the purchase process

[0494] Input: Your purchase confirmation and account information (shipping address, payment information, etc.).

[0495] How it works: The server calls the purchasing API of each online marketplace and automatically completes the purchase process.

[0496] Output: The purchase is completed.

[0497] Step 10:

[0498] The server sends and saves a purchase completion notification

[0499] Input: Purchase completion information.

[0500] Operation: The server confirms that the purchase was completed successfully, sends a notification to the device, and saves the purchase completion information in the database.

[0501] Output: A purchase completion notice will be displayed on the terminal, and the purchase completion information will be saved in the database.

[0502] (Application example 1)

[0503] 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."

[0504] In modern society, users spend a great deal of time and effort searching, comparing, and purchasing products from multiple electronic markets. This has led to a growing need for systems that can efficiently select optimal products and automate the purchasing process. Furthermore, ambiguity that arises when entering search criteria and the difficulty of comparing different information across different markets are also issues. Furthermore, it is important to provide an environment where users can easily perform these operations using their smartphones.

[0505] 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.

[0506] In this invention, the server includes: a means for a user to input search criteria for a desired product; a means for receiving the search criteria and saving the search criteria in a database; a means for calling APIs of multiple online markets to collect product information that matches the search criteria; a means for saving the collected product information in a database; a means for analyzing the products based on the collected information and calculating a score; a means for selecting multiple products with high scores and generating a list; a means for notifying the user of the generated list; a means for completing the purchase process for the user-selected products using the online market API; a means implemented as a smartphone application for the above means; and a means for generating prompt sentences using a generative AI model when the user enters search criteria. This allows users to efficiently search, compare, and purchase appropriate products from multiple online markets at once. Furthermore, generating prompt sentences eliminates input ambiguity, facilitating operation from a smartphone.

[0507] "User" means any person or entity that uses the System to search for, compare, and purchase products.

[0508] "Product conditions" are specific standards and requirements (e.g., price, specifications, rating) regarding the product desired by the user.

[0509] A "database" is a system that stores and manages data such as product information and user conditions.

[0510] An "electronic marketplace" is an online marketplace that sells goods over the Internet.

[0511] "API" stands for Application Programming Interface, an interface that allows electronic market services to exchange data with the outside world.

[0512] "Product Information" means product details (e.g., price, reviews, availability) collected from each electronic marketplace.

[0513] "Product analysis" is the process of evaluating the value and suitability of a product based on collected product information and according to multiple evaluation criteria.

[0514] A "score" is a numerical evaluation of each product based on the results of product analysis.

[0515] The "list" is a compilation of the results of selecting products with high scores.

[0516] "Notification" is a means of informing the user of important information (e.g., product list, purchase completion).

[0517] A "purchase process" is a series of steps to purchase a product on an online marketplace.

[0518] A "smartphone application" is application software that runs on a smartphone.

[0519] A "generative AI model" is a model that uses artificial intelligence technology to generate prompts and other text based on user input.

[0520] "Prompt sentences" are guidelines or example sentences created using generative AI models when a user types something.

[0521] The present invention is a system that allows users to search for and compare products from multiple online markets and automate the purchasing process. The system includes a terminal with an interface through which users input product-related requirements, a server that receives the requirements and processes the information, and an API for collecting product information.

[0522] First, the user uses a smartphone to input product-related criteria. At this time, a generative AI model can be used to generate a prompt sentence, which can be presented to the user as an input guide. For example, a generated prompt sentence might read, "I'm looking for a laptop computer. Priced at under 100,000 yen, with at least 8GB of memory and an SSD." The user then inputs their criteria based on this prompt sentence.

[0523] The entered information is sent from the user's smartphone to a server. The server stores the received user conditions in a database. The server then calls the APIs of multiple online markets to collect product information that matches the conditions. Typical examples of online markets include Amazon, Rakuten, and Yahoo Shopping. Information obtained from the API includes product name, price, review rating, and stock status.

[0524] Next, the server analyzes each product based on the collected product information. The analysis includes factors such as price, review rating, and seller reliability, and calculates a score based on each factor. The server uses this score to select the best product. As a result, a list of the top N products (for example, 10) is generated and stored in a database. This list is then sent from the server to a smartphone and notified to the user.

[0525] Users can view the product list displayed on their smartphones and select the appropriate product. Once the user confirms the purchase, the server automatically completes the purchase process using the API of each online marketplace. At this time, necessary information (shipping address, payment information, etc.) is obtained from the user's account information.

[0526] Finally, once the purchase is complete, the server sends the information to the user's smartphone and notifies them of the purchase. The purchase information is also stored in a database, allowing users to efficiently search, compare, and purchase suitable products from multiple online markets all at once.

[0527] For example, if a user enters "laptop computer" as a search condition, the server will search for products on Amazon, Rakuten, Yahoo Shopping, etc., and collect the necessary information. It will then calculate a score based on price and review ratings to select the most suitable product. The user can then review the selected product list, choose the product that best suits their needs, and proceed with the purchase. This allows the user to enjoy a smooth shopping experience.

[0528] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0529] Step 1:

[0530] A user uses a smartphone to input product-related criteria. The user uses the generative AI model to display a prompt ("I'm looking for a laptop computer. It should cost less than 100,000 yen, have 8GB or more of memory, and have an SSD.") while inputting the criteria. The entered criteria (e.g., laptop computer, price less than 100,000 yen, 8GB or more of memory, and have an SSD) are sent from the smartphone to the server.

[0531] Step 2:

[0532] The server stores the received user requirements in a database, where separate data for each user is stored and indexed for later use.

[0533] Step 3:

[0534] The server calls the APIs of multiple online markets to collect product information that matches the above conditions. Specifically, it uses the APIs of Amazon, Rakuten, and Yahoo Shopping to collect information such as product name, price, review rating, and stock status. The collected product information is temporarily stored in a database.

[0535] Step 4:

[0536] The server analyzes each product based on the collected product information, taking into account factors such as price, review rating, and seller reliability. A score is calculated based on each factor, and a score is assigned to each product. The lower the price, the higher the score, and the higher the review rating, the higher the score.

[0537] Step 5:

[0538] The server selects the top 10 products and generates a list. This list is ranked to include the products that best match the criteria entered by the user. The list is stored in a database and sent to the user's smartphone.

[0539] Step 6:

[0540] The user's smartphone notifies the user of the product list received from the server and displays it. The user selects any product from the presented list. The product information selected by the user is sent from the smartphone to the server.

[0541] Step 7:

[0542] The server automatically uses the API of the online marketplace to process the purchase of the product selected by the user. Specifically, it obtains user information such as shipping address and payment information and completes the purchase through each online marketplace's API. Once the purchase is complete, the information is saved in a database and a purchase completion notification is sent to the smartphone.

[0543] Step 8:

[0544] The server saves the purchase history in a database for future recommendations and history inquiries. A notification is displayed on the user's smartphone indicating that the purchase has been completed, and all processing is complete.

[0545] 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.

[0546] The present invention combines a system that allows users to search for and compare products from multiple online marketplaces and automates the purchasing process with an emotion engine that recognizes user emotions. This system includes a terminal that includes an interface through which users input product-related conditions, a server that receives the conditions and processes the information, an API for collecting product information, and an emotion engine that recognizes user emotions.

[0547] First, the user opens the device interface and inputs the product requirements. For example, they can enter specific requirements such as "laptop computer, price under 100,000 yen, memory over 8GB, SSD installed." This input information is sent to the server.

[0548] The server stores the received user's requirements in a database. Next, the server calls the APIs of multiple online marketplaces to collect product information that matches the requirements. For example, it retrieves product lists from online marketplaces such as Amazon, Rakuten, and Yahoo Shopping. The information retrieved from the API includes the product name, price, review rating, and stock status.

[0549] The server then analyzes each product based on the collected product information. The analysis includes factors such as price, review rating, and seller credibility, and calculates a score based on each factor. This score is used to select the best product. As a result, a list of the top N products (e.g., 10) is generated and stored in a database.

[0550] This list is sent from the server to the terminal and displayed to the user. The user can check the product list presented via the terminal and select an appropriate product. Here, the emotion engine recognizes emotions from the user's facial expressions and voice and collects the user's emotional data.

[0551] The server analyzes the emotional data and adjusts the product list according to the user's emotions. For example, if the user is unsure, it will prioritize products with high reviews and display them at the top of the list. On the other hand, if the user is excited, it will recommend high-quality products with slightly higher prices.

[0552] Once the user confirms the purchase, the server automatically processes the purchase using the API of each online marketplace. At this time, the necessary information (shipping address, payment information, etc.) is obtained from the user's account information. Once the purchase is complete, the server sends the information to the terminal and notifies the user that the purchase has been completed. The purchase information is also saved in a database.

[0553] For example, if a user enters "laptop computer" as a search term, the server will search for products on Amazon, Rakuten, Yahoo Shopping, etc., and collect the necessary information. It will then calculate a score based on price and review ratings to select the most suitable product. It will use an emotion engine to detect the user's hesitation or excitement and recommend products accordingly. The user can then review the selected product list, choose the product that best suits their needs, and proceed with the purchase. This allows the user to enjoy a smooth shopping experience.

[0554] The processing flow will be explained below.

[0555] Step 1:

[0556] The user opens the device interface and enters product-related criteria. For example, if the user is looking for a laptop computer, they enter specific criteria such as a price of less than 100,000 yen, 8GB or more of memory, and an SSD.

[0557] Step 2:

[0558] The terminal sends the entered conditions to the server, which receives the conditions and stores them in its database.

[0559] Step 3:

[0560] The server starts the emotion engine and starts collecting the user's facial expressions and voice data in real time, which allows the user's emotional data to be continuously analyzed.

[0561] Step 4:

[0562] The server calls the APIs of multiple online marketplaces to collect product information that matches the above conditions. The server then calls the APIs of Amazon, Rakuten, Yahoo Shopping, etc. in order, sets the necessary parameters, and sends the request.

[0563] Step 5:

[0564] The online marketplace receives the request and returns product information that matches the criteria in JSON format. The server parses the received JSON data and extracts product information (product name, price, review rating, stock status, etc.).

[0565] Step 6:

[0566] The server stores the collected product information in a database, centralizing data from different online marketplaces and storing it in a unified format.

[0567] Step 7:

[0568] The server analyzes each product based on the stored product information and calculates a score based on factors such as price, review rating, and seller reliability. The server then weights each of these factors to calculate an overall score.

[0569] Step 8:

[0570] The server selects the top N products (for example, 10) in descending order of score and generates a candidate list. This list is provided to the user and is temporarily stored in a database.

[0571] Step 9:

[0572] The server sends the generated candidate list to the terminal, which receives it and displays the product list to the user. The user can check this list and select an appropriate product.

[0573] Step 10:

[0574] The emotion engine analyzes the user's emotion data in real time and provides feedback to the server according to the user's emotion. If the user is unsure, the emotion engine detects the user's uncertain emotion and notifies the server. If the user is excited, the emotion engine measures the level of excitement and notifies the server.

[0575] Step 11:

[0576] The server adjusts the product list based on feedback from the emotion engine. For example, if the user is unsure, it will prioritize products with high reviews. If the user is excited, it will recommend high-quality products with higher prices.

[0577] Step 12:

[0578] The user decides to purchase and presses the purchase button. The device sends the information to the server.

[0579] Step 13:

[0580] The server again calls the API of the online marketplace for the selected product and sends a request to proceed with the purchase. The server obtains the shipping address, payment information, etc. from the user's account information, sets the necessary parameters, and sends the request.

[0581] Step 14:

[0582] The online marketplace receives the purchase request and completes the order process, after which it sends a purchase completion response back to the server.

[0583] Step 15:

[0584] The server receives the response indicating the purchase is complete and sends that information to the terminal. The terminal notifies the user that the purchase is complete and displays the purchase information. At the same time, the server saves the purchase history in a database.

[0585] Example 2

[0586] 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."

[0587] In today's online shopping environment, users must simultaneously search multiple online marketplaces and compare information from each. This requires a lot of time and effort, potentially compromising the user experience. Another issue is that product selection is often based solely on impersonal data, without taking into account the user's emotions, preventing them from making the best choice.

[0588] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0589] In this invention, the server includes: means for a user to input conditions related to a desired product; means for receiving the conditions and storing the conditions in a database; means for calling APIs of multiple online marketplaces to collect product information that matches the conditions; means for storing the collected product information in a database; means for analyzing products based on the collected information and calculating a score; means for selecting multiple products with high scores and generating a list; means for notifying the user of the generated list; means for proceeding with the purchase of the products selected by the user using the APIs of the online marketplaces; means for recognizing the user's emotions and collecting emotion data; means for adjusting the product list based on the emotion data; and means for notifying the user of purchase completion information and storing the data in a database. This enables users to efficiently perform a series of operations from product search to comparison to purchase, and further enables product selection that takes emotion into consideration.

[0590] "User" refers to a user of the system who inputs product-related conditions and searches, compares, and purchases based on those conditions.

[0591] "Conditions" refer to specific requirements or filter items that a user inputs for a desired product, such as price, specifications, brand, etc.

[0592] A "database" is an information storage system for storing and managing collected and analyzed product information, user conditions, purchase history, and other data.

[0593] An "online marketplace" is a platform where products are bought and sold over the Internet, and refers to a marketplace where multiple sellers list their products.

[0594] "API" stands for Application Programming Interface, a technology that provides a means for different software applications to communicate with each other.

[0595] "Product Information" means detailed product data collected from online marketplaces, including product name, price, review rating, and availability.

[0596] A "score" is a numerical indicator calculated by analyzing collected product information and based on its conformance to conditions and evaluation.

[0597] The "list" is a collection of products selected in descending order of score, and is a list of products notified to the user.

[0598] An "emotion engine" is a technology that recognizes emotions from a user's facial expressions, voice, etc., and collects and analyzes that data.

[0599] The "purchase process" refers to a series of operations and processes that a user performs to actually purchase a selected product from an online marketplace.

[0600] "Proceeding with the purchase procedure" is an execution process that automatically advances the purchase process for the product selected by the user via the API of the online marketplace.

[0601] The "completion notification" is information that notifies the user that the purchase procedure has been completed.

[0602] "Emotional Data" refers to data about a user's emotions collected and analyzed by the emotion engine.

[0603] "Adjustment" refers to the operation or process of changing product listings or recommendations based on collected emotional data.

[0604] The present invention combines a system that allows users to search for and compare products from multiple online marketplaces and automates the purchasing process with an emotion engine that recognizes user emotions. This system includes a terminal that includes an interface through which users input product-related conditions, a server that receives the conditions and processes the information, an API for collecting product information, and an emotion engine that recognizes user emotions.

[0605] First, the user opens the device interface and inputs the product requirements. For example, they can enter specific requirements such as "laptop computer, price under 100,000 yen, memory over 8GB, SSD installed." This input information is sent to the server.

[0606] The server stores the received user conditions in a database, using a relational database such as MongoDB or MySQL. The server then calls the APIs of multiple online marketplaces to collect product information that matches the conditions from, for example, Amazon, Rakuten, and Yahoo Shopping. The information obtained from the API includes the product name, price, review rating, and stock status.

[0607] The server then analyzes each product based on the collected product information. The analysis includes factors such as price, review rating, and seller credibility, and calculates a score based on each factor. This score is used to select the best product. As a result, a list of the top N products (e.g., 10) is generated and stored in a database.

[0608] This list is sent from the server to the device and displayed to the user. The user checks the product list presented via the device. At this time, the emotion engine recognizes emotions from the user's facial expressions and voice and collects emotional data. The emotion engine uses Microsoft's facial recognition API and voice recognition SDK.

[0609] The server analyzes the emotional data and adjusts the product list according to the user's emotions. For example, if the user is unsure, it will prioritize products with high reviews and display them at the top of the list. On the other hand, if the user is excited, it will recommend high-quality products with slightly higher prices.

[0610] Once the user confirms the purchase, the server automatically processes the purchase using the API of each online marketplace. At this time, the necessary information (shipping address, payment information, etc.) is obtained from the user's account information. Once the purchase is complete, the server sends the information to the terminal and notifies the user that the purchase has been completed. The purchase information is also saved in a database.

[0611] For example, if a user enters "laptop computer" as a search condition, the server will search for products on Amazon, Rakuten, Yahoo Shopping, etc., and collect the necessary information. It will then calculate a score based on price and review ratings to select the most suitable product. It will use an emotion engine to detect the user's hesitation or excitement, and recommend products accordingly. The user can then review the selected product list, choose the product that best suits their needs, and proceed with the purchase.

[0612] To implement this system, the following example prompts are provided:

[0613] "I'm looking for a laptop computer, but I'd like one that costs under 100,000 yen, has 8GB or more of memory, and has an SSD."

[0614] As described above, the present invention enables users to quickly and efficiently search for and compare products from multiple online marketplaces, and further select and purchase the most suitable product taking their emotions into consideration.

[0615] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0616] Step 1:

[0617] The user opens the terminal interface and inputs product-related conditions. The input data includes the product type (e.g., "laptop computer"), upper price limit (e.g., "under 100,000 yen"), memory capacity (e.g., "8GB or more"), and storage type (e.g., "equipped with SSD"). These conditions become the basis for data processing in subsequent processes. The input information is sent to the server via the user interface.

[0618] Step 2:

[0619] The device receives the condition data entered by the user and sends it to the server via an HTTP request. Specifically, the request is formed in the format "Product: Laptop, Price: Under 100,000 yen, Memory: 8GB or more, Storage: SSD." The input is the user's condition data, and the output is an HTTP request to the server.

[0620] Step 3:

[0621] The server analyzes the received user condition data and stores it in a relational database (for example, MongoDB or MySQL). Specifically, various conditions are saved as fields and used for future data reference and linkage. The input is the condition data sent by the user, and the output is the condition information stored in the database.

[0622] Step 4:

[0623] The server sequentially calls the APIs of multiple online marketplaces (e.g., the APIs of Amazon, Rakuten, and Yahoo Shopping) based on the stored condition data. It then sends requests to collect product information that matches the conditions. The input is the condition data stored in the database, and the output is product information obtained from each marketplace.

[0624] Step 5:

[0625] The server analyzes the retrieved product information and calculates a score for each product based on multiple factors, such as price, review rating, and seller reliability. A scoring algorithm is used to identify the product that best meets the user's criteria. The input is product data retrieved from the API, and the output is the analyzed score for each product.

[0626] Step 6:

[0627] The server sorts the products in descending order of score based on the calculated score. It then generates a list of the top N (e.g., top 10) products and stores it in a database. Here, a method is applied to efficiently provide the analysis results to the user. The input is score information, and the output is the top N product list.

[0628] Step 7:

[0629] The server sends the generated product list to the terminal as an HTTP response and displays it to the user. The input is the top N product list, and the output is the product list displayed to the user.

[0630] Step 8:

[0631] While the user is browsing the product list, the device's emotion engine (for example, Microsoft's facial recognition API or voice recognition SDK) collects the user's facial expression and voice data in real time. For example, a webcam and microphone are used for facial recognition and voice analysis. The input is the user's real-time facial expression and voice, and the output is emotion data.

[0632] Step 9:

[0633] The server analyzes the collected emotional data and adjusts the product list according to the user's psychological state (e.g., indecision, excitement). For example, if the user is indecisive, products with high review ratings are prioritized and displayed at the top of the list. The input is emotional data, and the output is the adjusted product list.

[0634] Step 10:

[0635] When a user confirms a purchase, the server automatically initiates the purchase process using the API of each online marketplace. The input is the product selected by the user and account information, and the output is the execution and completion of the purchase process.

[0636] Step 11:

[0637] When the purchase is completed, the server notifies the user of the purchase completion and simultaneously saves the purchase history in a database. The input is the purchase completion information, and the output is the notification to the user and the history saved in the database.

[0638] The above processing steps enable users to efficiently search, compare, and purchase products, and realize a system that allows for recommendations that take emotions into consideration.

[0639] (Application example 2)

[0640] 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."

[0641] Existing online shopping systems require a lot of effort for users to select products, and they often feel lost or have difficulty in making purchasing decisions. In addition, they provide mechanical recommendations without considering the user's emotional state, which results in a poor user experience.

[0642] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input conditions related to a desired product; means for receiving the conditions and saving them in a database; means for calling application programming interfaces of multiple online marketplaces to collect product information that matches the conditions; means for saving the collected product information in a database; means for analyzing products based on the collected information and calculating a score; means for selecting multiple products with high scores and creating a list; means for notifying the user of the created list; means for recognizing emotions from the user's facial expressions and voice and adjusting the product list based on the collected user emotion data; and means for completing the purchase procedure for the products selected by the user using the application programming interface of the online marketplace. This reduces the confusion and difficulty that users may experience when selecting products and enables appropriate product recommendations based on the user's emotional state.

[0643] A "User" is a person or entity that intends to search for and purchase a product.

[0644] "Conditions" are attributes or requirements that a user specifies when searching for a particular product.

[0645] A "database" is a system for storing and managing product information, user requirements, and emotional data.

[0646] An "application programming interface (API)" is an interface for exchanging information between different systems.

[0647] "Product information" refers to data such as product name, price, review rating, and stock status obtained from online marketplaces.

[0648] "Emotion recognition" is a technology that analyzes a user's facial expressions and voice to determine their emotional state.

[0649] The "score" is an evaluation value calculated based on collected product information, taking into account factors such as price, review rating, and seller reliability.

[0650] A "list" is a format for displaying multiple products selected based on their scores in an ordered manner.

[0651] "Emotion data" refers to data relating to the emotional state of the user recognized from facial expressions and voice.

[0652] An "online marketplace" is a platform for selling products over the Internet.

[0653] The "purchase procedure" is the procedure for a user to purchase a product selected by the user on the online marketplace.

[0654] The system of the present invention allows users to efficiently search for desired products using a smartphone and improves product selection through an emotion recognition engine. A specific embodiment of this system is described below.

[0655] First, a user launches a dedicated application on their smartphone and inputs the desired product's conditions, such as the category (e.g., "laptop"), price limit, required memory capacity, and storage type.

[0656] The terminal sends the conditions received from the user to the server, which stores these conditions in a database and calls the application programming interfaces (APIs) of multiple online marketplaces to collect product information that matches the conditions. This includes price comparison sites, and the information obtained includes product name, price, review rating, and stock status.

[0657] The server then analyzes the collected product information based on factors such as price, reviews, and seller reliability, and calculates a score based on each.The best products are selected based on this score and generated as a list.The generated list is stored in a database and notified to the device.

[0658] Furthermore, while the user is browsing the product list, an emotion recognition engine analyzes the user's facial expressions and voice using the device's built-in camera and microphone to collect emotional data. This emotional data is sent to the server, which then adjusts the product list based on the user's emotional state. For example, if the user is confused, the server can prioritize products with high reviews, while if the user is excited, the server can prioritize higher-priced, high-performance products at the top of the list.

[0659] Once the user selects the product to purchase, the server automatically completes the purchase process using the API of each online marketplace. During this process, the user's account information (shipping address, payment information, etc.) is securely processed. Once the purchase is complete, the server sends a notification of purchase completion to the device, and the purchase history is saved in a database.

[0660] Here's a concrete example: Suppose the user enters the following conditions:

[0661] Example prompt sentence:

[0662] "Laptop, price under 100,000 yen, 8GB or more of memory, SSD installed"

[0663] The server collects product information from multiple online marketplaces, scores them based on reviews and prices, and then presents a list to the user. At the same time, it analyzes the user's facial and voice data to determine their emotional state and suggests products that fit that emotional state. This process allows the user to have an efficient and emotionally adaptive shopping experience.

[0664] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0665] Step 1:

[0666] The user launches a dedicated application on their smartphone and inputs the conditions for the desired product. The input data includes the category (e.g., "laptop"), the upper price limit, the required memory capacity, the type of storage, etc. The input conditions are sent from the device to the server.

[0667] Step 2:

[0668] The server stores the received conditions in a database, including the user-entered conditions such as category, price limit, memory capacity, and storage type.

[0669] Step 3:

[0670] The server calls the application programming interfaces (APIs) of multiple online marketplaces to collect product information that matches the criteria. Specifically, the APIs are used to obtain product information, and the obtained data includes product name, price, review rating, and stock status. This data is then sent to the server.

[0671] Step 4:

[0672] The server stores the collected product information in a database, including product names, prices, review ratings, and stock availability obtained from each online marketplace.

[0673] Step 5:

[0674] The server analyzes the products based on the collected information and calculates a score. Specifically, it analyzes factors such as price, reviews, and seller reliability, and scores the products based on each factor. Scoring includes data processing (normalization, weighted average, etc.) and data calculation.

[0675] Step 6:

[0676] The server selects multiple products with high scores and generates a list, which is then stored in a database.

[0677] Step 7:

[0678] The server notifies the user of the generated list, which includes the scored products and their detailed information (price, review rating, stock status, etc.).

[0679] Step 8:

[0680] While the user is browsing the product list, the device's built-in camera and microphone are used to collect the user's facial expressions and voice. The emotion recognition engine analyzes the collected data and generates the user's emotion data. The generated emotion data is then sent from the device to the server.

[0681] Step 9:

[0682] The server adjusts the product list based on the user's emotional data. Specifically, the server analyzes the emotional data and adjusts the product list so that, for example, if the user is confused, products with high reviews are prioritized, and if the user is excited, higher-priced, high-performance products are prioritized and displayed at the top of the list.

[0683] Step 10:

[0684] The server automatically completes the purchase process for the product selected by the user using the API of each online marketplace. The information required for the purchase (shipping address, payment information, etc.) is obtained from the user's account information, and the purchase process is completed.

[0685] Step 11:

[0686] When the purchase is complete, the server sends a notification of the purchase completion to the terminal and saves the purchase history in a database, which includes the name of the purchased product, the purchase date and time, the price, shipping information, etc.

[0687] 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.

[0688] 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.

[0689] 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.

[0690] [Third embodiment]

[0691] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0692] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0693] 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).

[0694] 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.

[0695] 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.

[0696] 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).

[0697] 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. 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.

[0698] 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.

[0699] 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.

[0700] 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.

[0701] 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.

[0702] 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."

[0703] The present invention provides a system that allows users to search for and compare products from multiple online marketplaces and automate the purchasing process. The system includes a terminal that includes an interface for users to input product-related requirements, a server that receives the requirements and processes the information, and an API for collecting product information.

[0704] First, the user uses a terminal to input product-related requirements. For example, specific requirements such as "laptop computer, price under 100,000 yen, memory 8GB or more, SSD installed" can be input. This input information is sent to the server.

[0705] The server stores the received user conditions in a database. The server then calls the APIs of multiple online marketplaces to collect product information that matches the conditions. For example, it retrieves product lists from online marketplaces such as Amazon, Rakuten, and Yahoo Shopping. The information retrieved from the API includes the product name, price, review rating, and stock status.

[0706] The server then analyzes each product based on the collected product information. The analysis includes factors such as price, review rating, and seller credibility, and calculates a score based on each factor. This score is used to select the best product. As a result, a list of the top N products (e.g., 10) is generated and stored in a database.

[0707] This list is sent from the server to the terminal and displayed to the user. The user can review the product list presented via the terminal and select the appropriate product. Once the user confirms the purchase, the server automatically completes the purchase process using the API of each online marketplace. At this time, the necessary information (shipping address, payment information, etc.) is obtained from the user's account information.

[0708] Finally, when the purchase is complete, the server sends the information to the terminal and notifies the user of the completion of the purchase. The purchase information is also saved in a database.

[0709] For example, if a user enters "laptop computer" as a search condition, the server will search for products on Amazon, Rakuten, Yahoo Shopping, etc., and collect the necessary information. It will then calculate a score based on price and review ratings to select the most suitable product. The user can then review the selected product list, choose the product that best suits their needs, and proceed with the purchase. This allows the user to enjoy a smooth shopping experience.

[0710] The processing flow will be explained below.

[0711] Step 1:

[0712] The user opens the device interface and enters product-related criteria. For example, if the user is looking for a laptop computer, they enter specific criteria such as a price of less than 100,000 yen, 8GB or more of memory, and an SSD.

[0713] Step 2:

[0714] The terminal sends the entered conditions to the server, which receives the conditions and stores them in its database.

[0715] Step 3:

[0716] The server calls the APIs of multiple online marketplaces to collect product information that matches the above conditions. The server then calls the APIs of Amazon, Rakuten, Yahoo Shopping, etc. in order, sets the necessary parameters, and sends the request.

[0717] Step 4:

[0718] The online marketplace receives the request and returns product information that matches the criteria in JSON format. The server parses the received JSON data and extracts product information (product name, price, review rating, stock status, etc.).

[0719] Step 5:

[0720] The server stores the collected product information in a database, centralizing data from different online marketplaces and storing it in a unified format.

[0721] Step 6:

[0722] The server analyzes each product based on the stored product information and calculates a score based on factors such as price, review rating, and seller reliability. The server then weights each of these factors to calculate an overall score.

[0723] Step 7:

[0724] The server selects the top N products (for example, 10) in descending order of score and generates a candidate list. This list is provided to the user and is temporarily stored in a database.

[0725] Step 8:

[0726] The server sends the generated candidate list to the terminal, which receives it and displays the product list to the user. The user reviews this list and selects the product that seems most suitable.

[0727] Step 9:

[0728] The user decides to purchase and presses the purchase button. The device sends the information to the server.

[0729] Step 10:

[0730] The server again calls the API of the online marketplace for the selected product and sends a request to proceed with the purchase. The server obtains the shipping address, payment information, etc. from the user's account information, sets the necessary parameters, and sends the request.

[0731] Step 11:

[0732] The online marketplace receives the purchase request and completes the order process, after which it sends a purchase completion response back to the server.

[0733] Step 12:

[0734] The server receives the response indicating the purchase is complete and sends that information to the terminal. The terminal notifies the user that the purchase is complete and displays the purchase information. At the same time, the server saves the purchase history in a database.

[0735] Example 1

[0736] 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."

[0737] In modern online shopping, it is common for users to individually visit multiple marketplaces to search for products, compare them, and complete the purchase process. However, this process is not only time-consuming and labor-intensive, but also requires manual input according to the specifications of each marketplace, placing a significant burden on users. Furthermore, comparing prices and reviews across different marketplaces is tedious, making it difficult to make the optimal choice. This makes it difficult for users to efficiently purchase the best products at the best prices.

[0738] 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.

[0739] In this invention, the server includes means for a user to input conditions related to a desired product, means for receiving the conditions and saving the conditions in a database, means for calling application programming interfaces of multiple online marketplaces to collect product information that matches the conditions, means for saving the collected product information in a database, means for analyzing the products based on the collected information and calculating a score, means for selecting multiple products with high scores and creating a list, means for notifying the user of the created list, means for proceeding with the purchase of the product selected by the user using the application programming interface of the online marketplace, means for acquiring shipping address and payment information related to the user, means for receiving and notifying the user of completion of the purchase, and means for saving the purchase completion information in a database. This enables a user to search for, compare, and select the optimal product by entering conditions once, without visiting multiple marketplaces, and to automate the purchase process, thereby efficiently and quickly completing the purchase.

[0740] A "user" is an entity that utilizes the system to input criteria for searching, comparing, and purchasing products.

[0741] "Conditions" are attributes or requirements (e.g., price, performance, brand, etc.) that a user specifies regarding a desired product.

[0742] A "terminal" is a computing device that a user uses to enter conditions and receive results.

[0743] A "server" is a central computer system that processes data based on requirements received from users.

[0744] A "database" is a data storage system for storing and managing data such as terms and conditions, product information, and purchase history.

[0745] An "application programming interface (API)" is a standardized interface that a server uses to retrieve product information from an online marketplace.

[0746] A "marketplace" is an online platform where multiple sellers offer products and users can purchase them.

[0747] "Product information" refers to detailed product information obtained from the marketplace (e.g., product name, price, review rating, stock status, etc.).

[0748] The "score" is an evaluation value calculated based on collected product information, taking into account factors such as price, review rating, and seller reliability.

[0749] A "list" refers to a set of products generated by selecting multiple products with high scores.

[0750] "Delivery address" is address information required for a user to receive the purchased product.

[0751] "Payment Information" refers to payment information such as credit card information and bank account information required to complete the purchase process.

[0752] A "purchase procedure" is a series of operations and processes required to complete the purchase of a product selected by a user.

[0753] "Completion information" is information used to confirm that the purchase procedure has been completed successfully.

[0754] The present invention is a system for automating the process of users searching, comparing, and purchasing products from multiple online marketplaces. The system includes a terminal that provides an interface for users to input product-related requirements, a server that receives the requirements and processes the information, and an application programming interface (API) for collecting product information.

[0755] Hardware and software used

[0756] Device: The device on which the user enters product conditions (PC, smartphone, tablet, etc.)

[0757] Servers: Web servers and database servers (e.g., Amazon Web Services, Microsoft Azure)

[0758] Database: Relational database such as MySQL or PostgreSQL

[0759] API: Application programming interface provided by each online marketplace (e.g., Amazon API, Rakuten API, Yahoo Shopping API)

[0760] Analysis tools: Python Pandas, Numpy, etc.

[0761] System details

[0762] 1. Enter and submit product conditions

[0763] The user uses the device interface to input the search criteria for the product they want to search for, for example, "laptop computer, price under 100,000 yen, memory 8GB or more, SSD installed."

[0764] These conditions are transmitted from the terminal to the server.

[0765] 2. Receipt and storage of terms and conditions

[0766] The server stores the received conditions in a database, a process that uses a relational database such as MySQL or PostgreSQL.

[0767] 3. Collection of information

[0768] The server uses the saved conditions to call the API of each marketplace to collect product information. For example, it uses the Amazon API or Rakuten API to obtain product information.

[0769] Information collected includes product name, price, review rating, and availability.

[0770] 4. Data Analysis

[0771] The server analyzes the collected product information using Python's Pandas and Numpy, and calculates a score based on price, review rating, seller reliability, etc.

[0772] 5. Creating and saving a list

[0773] The server selects the best products based on the calculated scores and generates a top N (e.g., 10) product list, which is then stored in the database again.

[0774] 6. List Notification

[0775] The server sends the generated list to the terminal, which receives it and displays it to the user.

[0776] 7. Purchase Procedure

[0777] Once the user selects a product and confirms the purchase, the server obtains the user's shipping address and payment information and automatically completes the purchase process via the marketplace's API.

[0778] 8. Purchase completion notification

[0779] Once the purchase procedure is complete, the server sends a notification of purchase completion to the terminal, which is displayed to the user. The purchase information is also saved in a database.

[0780] Specific examples

[0781] Example of user input: "Laptop, price under 100,000 yen, 8GB or more of memory, SSD installed"

[0782] Example prompt for a generative AI model: "Search for products that meet the criteria of 'laptops, priced under ¥100,000, with at least 8GB of memory and an SSD,' and calculate a score based on price and ratings to select the best product."

[0783] As described above, the system of the present invention allows users to search multiple online marketplaces at once and select and purchase the best products quickly and efficiently.

[0784] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0785] Step 1:

[0786] The user enters product conditions

[0787] Input: The user uses the device interface to input product requirements. For example, they might input "laptop computer, price under 100,000 yen, memory 8GB or more, SSD installed."

[0788] Action: The user enters search criteria into the device's input field and presses the "Search" button.

[0789] Output: The entered conditions are sent from the terminal to the server.

[0790] Step 2:

[0791] The server receives and stores the conditions.

[0792] Input: Product conditions sent from the terminal.

[0793] Behavior: The server checks the received conditions to ensure that the data is valid, then stores it in the database (MySQL or PostgreSQL).

[0794] Output: The valid product terms are saved to the database.

[0795] Step 3:

[0796] The server collects information from the marketplace.

[0797] Input: Product terms stored in the database.

[0798] Operation: The server calls the API of each online marketplace (e.g., Amazon API, Rakuten API, Yahoo Shopping API) and collects product information that matches the product conditions.

[0799] Output: Product information obtained from each marketplace (product name, price, review rating, availability, etc.).

[0800] Step 4:

[0801] The server saves the product information to a database

[0802] Input: Product information collected from each marketplace.

[0803] How it works: The server converts the collected product information into an appropriate format and stores it in a database.

[0804] Output: Product information is saved in the database.

[0805] Step 5:

[0806] The server analyzes the data and calculates the score

[0807] Input: Product information stored in the database.

[0808] How it works: The server analyzes product information and calculates a score based on factors such as price, review rating, seller reliability, etc. Calculations are performed using Python tools such as Pandas and Numpy.

[0809] Output: A score is calculated for each product.

[0810] Step 6:

[0811] The server generates and stores the top N product list

[0812] Input: Product information for which a score is calculated.

[0813] How it works: The server sorts the products based on the calculated score and generates a list of the top N (e.g., 10) products, which is then stored in a database.

[0814] Output: A list of the top N products is generated and stored in a database.

[0815] Step 7:

[0816] The server sends the product list to the terminal.

[0817] Input: A server-generated top-N product list.

[0818] How it works: The server encodes the product list in JSON format and sends it to the device via the REST API.

[0819] Output: The product list is sent to the terminal.

[0820] Step 8:

[0821] The user selects an item and confirms the purchase

[0822] Input: The top N product list sent to the device.

[0823] How it works: The user reviews the product list, selects the product they want, and confirms their purchase. They then enter the required information (shipping address, payment information, etc.) through the device interface.

[0824] Output: The user's selected products and purchase information are sent to the server.

[0825] Step 9:

[0826] The server automatically executes the purchase process

[0827] Input: Your purchase confirmation and account information (shipping address, payment information, etc.).

[0828] How it works: The server calls the purchasing API of each online marketplace and automatically completes the purchase process.

[0829] Output: The purchase is completed.

[0830] Step 10:

[0831] The server sends and saves a purchase completion notification

[0832] Input: Purchase completion information.

[0833] Operation: The server confirms that the purchase was completed successfully, sends a notification to the device, and saves the purchase completion information in the database.

[0834] Output: A purchase completion notice will be displayed on the terminal, and the purchase completion information will be saved in the database.

[0835] (Application example 1)

[0836] 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."

[0837] In modern society, users spend a great deal of time and effort searching, comparing, and purchasing products from multiple electronic markets. This has led to a growing need for systems that can efficiently select optimal products and automate the purchasing process. Furthermore, ambiguity that arises when entering search criteria and the difficulty of comparing different information across different markets are also issues. Furthermore, it is important to provide an environment where users can easily perform these operations using their smartphones.

[0838] 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.

[0839] In this invention, the server includes: a means for a user to input search criteria for a desired product; a means for receiving the search criteria and saving the search criteria in a database; a means for calling APIs of multiple online markets to collect product information that matches the search criteria; a means for saving the collected product information in a database; a means for analyzing the products based on the collected information and calculating a score; a means for selecting multiple products with high scores and generating a list; a means for notifying the user of the generated list; a means for completing the purchase process for the user-selected products using the online market API; a means implemented as a smartphone application for the above means; and a means for generating prompt sentences using a generative AI model when the user enters search criteria. This allows users to efficiently search, compare, and purchase appropriate products from multiple online markets at once. Furthermore, generating prompt sentences eliminates input ambiguity, facilitating operation from a smartphone.

[0840] "User" means any person or entity that uses the System to search for, compare, and purchase products.

[0841] "Product conditions" are specific standards and requirements (e.g., price, specifications, rating) regarding the product desired by the user.

[0842] A "database" is a system that stores and manages data such as product information and user conditions.

[0843] An "electronic marketplace" is an online marketplace that sells goods over the Internet.

[0844] "API" stands for Application Programming Interface, an interface that allows electronic market services to exchange data with the outside world.

[0845] "Product Information" means product details (e.g., price, reviews, availability) collected from each electronic marketplace.

[0846] "Product analysis" is the process of evaluating the value and suitability of a product based on collected product information and according to multiple evaluation criteria.

[0847] A "score" is a numerical evaluation of each product based on the results of product analysis.

[0848] The "list" is a compilation of the results of selecting products with high scores.

[0849] "Notification" is a means of informing the user of important information (e.g., product list, purchase completion).

[0850] A "purchase process" is a series of steps to purchase a product on an online marketplace.

[0851] A "smartphone application" is application software that runs on a smartphone.

[0852] A "generative AI model" is a model that uses artificial intelligence technology to generate prompts and other text based on user input.

[0853] "Prompt sentences" are guidelines or example sentences created using generative AI models when a user types something.

[0854] The present invention is a system that allows users to search for and compare products from multiple online markets and automate the purchasing process. The system includes a terminal with an interface through which users input product-related requirements, a server that receives the requirements and processes the information, and an API for collecting product information.

[0855] First, the user uses a smartphone to input product-related criteria. At this time, a generative AI model can be used to generate a prompt sentence, which can be presented to the user as an input guide. For example, a generated prompt sentence might read, "I'm looking for a laptop computer. Priced at under 100,000 yen, with at least 8GB of memory and an SSD." The user then inputs their criteria based on this prompt sentence.

[0856] The entered information is sent from the user's smartphone to a server. The server stores the received user conditions in a database. The server then calls the APIs of multiple online markets to collect product information that matches the conditions. Typical examples of online markets include Amazon, Rakuten, and Yahoo Shopping. Information obtained from the API includes product name, price, review rating, and stock status.

[0857] Next, the server analyzes each product based on the collected product information. The analysis includes factors such as price, review rating, and seller reliability, and calculates a score based on each factor. The server uses this score to select the best product. As a result, a list of the top N products (for example, 10) is generated and stored in a database. This list is then sent from the server to a smartphone and notified to the user.

[0858] Users can view the product list displayed on their smartphones and select the appropriate product. Once the user confirms the purchase, the server automatically completes the purchase process using the API of each online marketplace. At this time, necessary information (shipping address, payment information, etc.) is obtained from the user's account information.

[0859] Finally, once the purchase is complete, the server sends the information to the user's smartphone and notifies them of the purchase. The purchase information is also stored in a database, allowing users to efficiently search, compare, and purchase suitable products from multiple online markets all at once.

[0860] For example, if a user enters "laptop computer" as a search condition, the server will search for products on Amazon, Rakuten, Yahoo Shopping, etc., and collect the necessary information. It will then calculate a score based on price and review ratings to select the most suitable product. The user can then review the selected product list, choose the product that best suits their needs, and proceed with the purchase. This allows the user to enjoy a smooth shopping experience.

[0861] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0862] Step 1:

[0863] A user uses a smartphone to input product-related criteria. The user uses the generative AI model to display a prompt ("I'm looking for a laptop computer. It should cost less than 100,000 yen, have 8GB or more of memory, and have an SSD.") while inputting the criteria. The entered criteria (e.g., laptop computer, price less than 100,000 yen, 8GB or more of memory, and have an SSD) are sent from the smartphone to the server.

[0864] Step 2:

[0865] The server stores the received user requirements in a database, where separate data for each user is stored and indexed for later use.

[0866] Step 3:

[0867] The server calls the APIs of multiple online markets to collect product information that matches the above conditions. Specifically, it uses the APIs of Amazon, Rakuten, and Yahoo Shopping to collect information such as product name, price, review rating, and stock status. The collected product information is temporarily stored in a database.

[0868] Step 4:

[0869] The server analyzes each product based on the collected product information, taking into account factors such as price, review rating, and seller reliability. A score is calculated based on each factor, and a score is assigned to each product. The lower the price, the higher the score, and the higher the review rating, the higher the score.

[0870] Step 5:

[0871] The server selects the top 10 products and generates a list. This list is ranked to include the products that best match the criteria entered by the user. The list is stored in a database and sent to the user's smartphone.

[0872] Step 6:

[0873] The user's smartphone notifies the user of the product list received from the server and displays it. The user selects any product from the presented list. The product information selected by the user is sent from the smartphone to the server.

[0874] Step 7:

[0875] The server automatically uses the API of the online marketplace to process the purchase of the product selected by the user. Specifically, it obtains user information such as shipping address and payment information and completes the purchase through each online marketplace's API. Once the purchase is complete, the information is saved in a database and a purchase completion notification is sent to the smartphone.

[0876] Step 8:

[0877] The server saves the purchase history in a database for future recommendations and history inquiries. A notification is displayed on the user's smartphone indicating that the purchase has been completed, and all processing is complete.

[0878] 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.

[0879] The present invention combines a system that allows users to search for and compare products from multiple online marketplaces and automates the purchasing process with an emotion engine that recognizes user emotions. This system includes a terminal that includes an interface through which users input product-related conditions, a server that receives the conditions and processes the information, an API for collecting product information, and an emotion engine that recognizes user emotions.

[0880] First, the user opens the device interface and inputs the product requirements. For example, they can enter specific requirements such as "laptop computer, price under 100,000 yen, memory over 8GB, SSD installed." This input information is sent to the server.

[0881] The server stores the received user's requirements in a database. Next, the server calls the APIs of multiple online marketplaces to collect product information that matches the requirements. For example, it retrieves product lists from online marketplaces such as Amazon, Rakuten, and Yahoo Shopping. The information retrieved from the API includes the product name, price, review rating, and stock status.

[0882] The server then analyzes each product based on the collected product information. The analysis includes factors such as price, review rating, and seller credibility, and calculates a score based on each factor. This score is used to select the best product. As a result, a list of the top N products (e.g., 10) is generated and stored in a database.

[0883] This list is sent from the server to the terminal and displayed to the user. The user can check the product list presented via the terminal and select an appropriate product. Here, the emotion engine recognizes emotions from the user's facial expressions and voice and collects the user's emotional data.

[0884] The server analyzes the emotional data and adjusts the product list according to the user's emotions. For example, if the user is unsure, it will prioritize products with high reviews and display them at the top of the list. On the other hand, if the user is excited, it will recommend high-quality products with slightly higher prices.

[0885] Once the user confirms the purchase, the server automatically processes the purchase using the API of each online marketplace. At this time, the necessary information (shipping address, payment information, etc.) is obtained from the user's account information. Once the purchase is complete, the server sends the information to the terminal and notifies the user that the purchase has been completed. The purchase information is also saved in a database.

[0886] For example, if a user enters "laptop computer" as a search term, the server will search for products on Amazon, Rakuten, Yahoo Shopping, etc., and collect the necessary information. It will then calculate a score based on price and review ratings to select the most suitable product. It will use an emotion engine to detect the user's hesitation or excitement and recommend products accordingly. The user can then review the selected product list, choose the product that best suits their needs, and proceed with the purchase. This allows the user to enjoy a smooth shopping experience.

[0887] The processing flow will be explained below.

[0888] Step 1:

[0889] The user opens the device interface and enters product-related criteria. For example, if the user is looking for a laptop computer, they enter specific criteria such as a price of less than 100,000 yen, 8GB or more of memory, and an SSD.

[0890] Step 2:

[0891] The terminal sends the entered conditions to the server, which receives the conditions and stores them in its database.

[0892] Step 3:

[0893] The server starts the emotion engine and starts collecting the user's facial expressions and voice data in real time, which allows the user's emotional data to be continuously analyzed.

[0894] Step 4:

[0895] The server calls the APIs of multiple online marketplaces to collect product information that matches the above conditions. The server then calls the APIs of Amazon, Rakuten, Yahoo Shopping, etc. in order, sets the necessary parameters, and sends the request.

[0896] Step 5:

[0897] The online marketplace receives the request and returns product information that matches the criteria in JSON format. The server parses the received JSON data and extracts product information (product name, price, review rating, stock status, etc.).

[0898] Step 6:

[0899] The server stores the collected product information in a database, centralizing data from different online marketplaces and storing it in a unified format.

[0900] Step 7:

[0901] The server analyzes each product based on the stored product information and calculates a score based on factors such as price, review rating, and seller reliability. The server then weights each of these factors to calculate an overall score.

[0902] Step 8:

[0903] The server selects the top N products (for example, 10) in descending order of score and generates a candidate list. This list is provided to the user and is temporarily stored in a database.

[0904] Step 9:

[0905] The server sends the generated candidate list to the terminal, which receives it and displays the product list to the user. The user can check this list and select an appropriate product.

[0906] Step 10:

[0907] The emotion engine analyzes the user's emotion data in real time and provides feedback to the server according to the user's emotion. If the user is unsure, the emotion engine detects the user's uncertain emotion and notifies the server. If the user is excited, the emotion engine measures the level of excitement and notifies the server.

[0908] Step 11:

[0909] The server adjusts the product list based on feedback from the emotion engine. For example, if the user is unsure, it will prioritize products with high reviews. If the user is excited, it will recommend high-quality products with higher prices.

[0910] Step 12:

[0911] The user decides to purchase and presses the purchase button. The device sends the information to the server.

[0912] Step 13:

[0913] The server again calls the API of the online marketplace for the selected product and sends a request to proceed with the purchase. The server obtains the shipping address, payment information, etc. from the user's account information, sets the necessary parameters, and sends the request.

[0914] Step 14:

[0915] The online marketplace receives the purchase request and completes the order process, after which it sends a purchase completion response back to the server.

[0916] Step 15:

[0917] The server receives the response indicating the purchase is complete and sends that information to the terminal. The terminal notifies the user that the purchase is complete and displays the purchase information. At the same time, the server saves the purchase history in a database.

[0918] Example 2

[0919] 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."

[0920] In today's online shopping environment, users must simultaneously search multiple online marketplaces and compare information from each. This requires a lot of time and effort, potentially compromising the user experience. Another issue is that product selection is often based solely on impersonal data, without taking into account the user's emotions, preventing them from making the best choice.

[0921] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0922] In this invention, the server includes: means for a user to input conditions related to a desired product; means for receiving the conditions and storing the conditions in a database; means for calling APIs of multiple online marketplaces to collect product information that matches the conditions; means for storing the collected product information in a database; means for analyzing products based on the collected information and calculating a score; means for selecting multiple products with high scores and generating a list; means for notifying the user of the generated list; means for proceeding with the purchase of the products selected by the user using the APIs of the online marketplaces; means for recognizing the user's emotions and collecting emotion data; means for adjusting the product list based on the emotion data; and means for notifying the user of purchase completion information and storing the data in a database. This enables users to efficiently perform a series of operations from product search to comparison to purchase, and further enables product selection that takes emotion into consideration.

[0923] "User" refers to a user of the system who inputs product-related conditions and searches, compares, and purchases based on those conditions.

[0924] "Conditions" refer to specific requirements or filter items that a user inputs for a desired product, such as price, specifications, brand, etc.

[0925] A "database" is an information storage system for storing and managing collected and analyzed product information, user conditions, purchase history, and other data.

[0926] An "online marketplace" is a platform where products are bought and sold over the Internet, and refers to a marketplace where multiple sellers list their products.

[0927] "API" stands for Application Programming Interface, a technology that provides a means for different software applications to communicate with each other.

[0928] "Product Information" means detailed product data collected from online marketplaces, including product name, price, review rating, and availability.

[0929] A "score" is a numerical indicator calculated by analyzing collected product information and based on its conformance to conditions and evaluation.

[0930] The "list" is a collection of products selected in descending order of score, and is a list of products notified to the user.

[0931] An "emotion engine" is a technology that recognizes emotions from a user's facial expressions, voice, etc., and collects and analyzes that data.

[0932] The "purchase process" refers to a series of operations and processes that a user performs to actually purchase a selected product from an online marketplace.

[0933] "Proceeding with the purchase procedure" is an execution process that automatically advances the purchase process for the product selected by the user via the API of the online marketplace.

[0934] The "completion notification" is information that notifies the user that the purchase procedure has been completed.

[0935] "Emotional Data" refers to data about a user's emotions collected and analyzed by the emotion engine.

[0936] "Adjustment" refers to the operation or process of changing product listings or recommendations based on collected emotional data.

[0937] The present invention combines a system that allows users to search for and compare products from multiple online marketplaces and automates the purchasing process with an emotion engine that recognizes user emotions. This system includes a terminal that includes an interface through which users input product-related conditions, a server that receives the conditions and processes the information, an API for collecting product information, and an emotion engine that recognizes user emotions.

[0938] First, the user opens the device interface and inputs the product requirements. For example, they can enter specific requirements such as "laptop computer, price under 100,000 yen, memory over 8GB, SSD installed." This input information is sent to the server.

[0939] The server stores the received user conditions in a database, using a relational database such as MongoDB or MySQL. The server then calls the APIs of multiple online marketplaces to collect product information that matches the conditions from, for example, Amazon, Rakuten, and Yahoo Shopping. The information obtained from the API includes the product name, price, review rating, and stock status.

[0940] The server then analyzes each product based on the collected product information. The analysis includes factors such as price, review rating, and seller credibility, and calculates a score based on each factor. This score is used to select the best product. As a result, a list of the top N products (e.g., 10) is generated and stored in a database.

[0941] This list is sent from the server to the device and displayed to the user. The user checks the product list presented via the device. At this time, the emotion engine recognizes emotions from the user's facial expressions and voice and collects emotional data. The emotion engine uses Microsoft's facial recognition API and voice recognition SDK.

[0942] The server analyzes the emotional data and adjusts the product list according to the user's emotions. For example, if the user is unsure, it will prioritize products with high reviews and display them at the top of the list. On the other hand, if the user is excited, it will recommend high-quality products with slightly higher prices.

[0943] Once the user confirms the purchase, the server automatically processes the purchase using the API of each online marketplace. At this time, the necessary information (shipping address, payment information, etc.) is obtained from the user's account information. Once the purchase is complete, the server sends the information to the terminal and notifies the user that the purchase has been completed. The purchase information is also saved in a database.

[0944] For example, if a user enters "laptop computer" as a search condition, the server will search for products on Amazon, Rakuten, Yahoo Shopping, etc., and collect the necessary information. It will then calculate a score based on price and review ratings to select the most suitable product. It will use an emotion engine to detect the user's hesitation or excitement, and recommend products accordingly. The user can then review the selected product list, choose the product that best suits their needs, and proceed with the purchase.

[0945] To implement this system, the following example prompts are provided:

[0946] "I'm looking for a laptop computer, but I'd like one that costs under 100,000 yen, has 8GB or more of memory, and has an SSD."

[0947] As described above, the present invention enables users to quickly and efficiently search for and compare products from multiple online marketplaces, and further select and purchase the most suitable product taking their emotions into consideration.

[0948] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0949] Step 1:

[0950] The user opens the terminal interface and inputs product-related conditions. The input data includes the product type (e.g., "laptop computer"), upper price limit (e.g., "under 100,000 yen"), memory capacity (e.g., "8GB or more"), and storage type (e.g., "equipped with SSD"). These conditions become the basis for data processing in subsequent processes. The input information is sent to the server via the user interface.

[0951] Step 2:

[0952] The device receives the condition data entered by the user and sends it to the server via an HTTP request. Specifically, the request is formed in the format "Product: Laptop, Price: Under 100,000 yen, Memory: 8GB or more, Storage: SSD." The input is the user's condition data, and the output is an HTTP request to the server.

[0953] Step 3:

[0954] The server analyzes the received user condition data and stores it in a relational database (for example, MongoDB or MySQL). Specifically, various conditions are saved as fields and used for future data reference and linkage. The input is the condition data sent by the user, and the output is the condition information stored in the database.

[0955] Step 4:

[0956] The server sequentially calls the APIs of multiple online marketplaces (e.g., the APIs of Amazon, Rakuten, and Yahoo Shopping) based on the stored condition data. It then sends requests to collect product information that matches the conditions. The input is the condition data stored in the database, and the output is product information obtained from each marketplace.

[0957] Step 5:

[0958] The server analyzes the retrieved product information and calculates a score for each product based on multiple factors, such as price, review rating, and seller reliability. A scoring algorithm is used to identify the product that best meets the user's criteria. The input is product data retrieved from the API, and the output is the analyzed score for each product.

[0959] Step 6:

[0960] The server sorts the products in descending order of score based on the calculated score. It then generates a list of the top N (e.g., top 10) products and stores it in a database. Here, a method is applied to efficiently provide the analysis results to the user. The input is score information, and the output is the top N product list.

[0961] Step 7:

[0962] The server sends the generated product list to the terminal as an HTTP response and displays it to the user. The input is the top N product list, and the output is the product list displayed to the user.

[0963] Step 8:

[0964] While the user is browsing the product list, the device's emotion engine (for example, Microsoft's facial recognition API or voice recognition SDK) collects the user's facial expression and voice data in real time. For example, a webcam and microphone are used for facial recognition and voice analysis. The input is the user's real-time facial expression and voice, and the output is emotion data.

[0965] Step 9:

[0966] The server analyzes the collected emotional data and adjusts the product list according to the user's psychological state (e.g., indecision, excitement). For example, if the user is indecisive, products with high review ratings are prioritized and displayed at the top of the list. The input is emotional data, and the output is the adjusted product list.

[0967] Step 10:

[0968] When a user confirms a purchase, the server automatically initiates the purchase process using the API of each online marketplace. The input is the product selected by the user and account information, and the output is the execution and completion of the purchase process.

[0969] Step 11:

[0970] When the purchase is completed, the server notifies the user of the purchase completion and simultaneously saves the purchase history in a database. The input is the purchase completion information, and the output is the notification to the user and the history saved in the database.

[0971] The above processing steps enable users to efficiently search, compare, and purchase products, and realize a system that allows for recommendations that take emotions into consideration.

[0972] (Application example 2)

[0973] 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."

[0974] Existing online shopping systems require a lot of effort for users to select products, and they often feel lost or have difficulty in making purchasing decisions. In addition, they provide mechanical recommendations without considering the user's emotional state, which results in a poor user experience.

[0975] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input conditions related to a desired product; means for receiving the conditions and saving them in a database; means for calling application programming interfaces of multiple online marketplaces to collect product information that matches the conditions; means for saving the collected product information in a database; means for analyzing products based on the collected information and calculating a score; means for selecting multiple products with high scores and creating a list; means for notifying the user of the created list; means for recognizing emotions from the user's facial expressions and voice and adjusting the product list based on the collected user emotion data; and means for completing the purchase procedure for the products selected by the user using the application programming interface of the online marketplace. This reduces the confusion and difficulty that users may experience when selecting products and enables appropriate product recommendations based on the user's emotional state.

[0976] A "User" is a person or entity that intends to search for and purchase a product.

[0977] "Conditions" are attributes or requirements that a user specifies when searching for a particular product.

[0978] A "database" is a system for storing and managing product information, user requirements, and emotional data.

[0979] An "application programming interface (API)" is an interface for exchanging information between different systems.

[0980] "Product information" refers to data such as product name, price, review rating, and stock status obtained from online marketplaces.

[0981] "Emotion recognition" is a technology that analyzes a user's facial expressions and voice to determine their emotional state.

[0982] The "score" is an evaluation value calculated based on collected product information, taking into account factors such as price, review rating, and seller reliability.

[0983] A "list" is a format for displaying multiple products selected based on their scores in an ordered manner.

[0984] "Emotion data" refers to data relating to the emotional state of the user recognized from facial expressions and voice.

[0985] An "online marketplace" is a platform for selling products over the Internet.

[0986] The "purchase procedure" is the procedure for a user to purchase a product selected by the user on the online marketplace.

[0987] The system of the present invention allows users to efficiently search for desired products using a smartphone and improves product selection through an emotion recognition engine. A specific embodiment of this system is described below.

[0988] First, a user launches a dedicated application on their smartphone and inputs the desired product's conditions, such as the category (e.g., "laptop"), price limit, required memory capacity, and storage type.

[0989] The terminal sends the conditions received from the user to the server, which stores these conditions in a database and calls the application programming interfaces (APIs) of multiple online marketplaces to collect product information that matches the conditions. This includes price comparison sites, and the information obtained includes product name, price, review rating, and stock status.

[0990] The server then analyzes the collected product information based on factors such as price, reviews, and seller reliability, and calculates a score based on each.The best products are selected based on this score and generated as a list.The generated list is stored in a database and notified to the device.

[0991] Furthermore, while the user is browsing the product list, an emotion recognition engine analyzes the user's facial expressions and voice using the device's built-in camera and microphone to collect emotional data. This emotional data is sent to the server, which then adjusts the product list based on the user's emotional state. For example, if the user is confused, the server can prioritize products with high reviews, while if the user is excited, the server can prioritize higher-priced, high-performance products at the top of the list.

[0992] Once the user selects the product to purchase, the server automatically completes the purchase process using the API of each online marketplace. During this process, the user's account information (shipping address, payment information, etc.) is securely processed. Once the purchase is complete, the server sends a notification of purchase completion to the device, and the purchase history is saved in a database.

[0993] Here's a concrete example: Suppose the user enters the following conditions:

[0994] Example prompt sentence:

[0995] "Laptop, price under 100,000 yen, 8GB or more of memory, SSD installed"

[0996] The server collects product information from multiple online marketplaces, scores them based on reviews and prices, and then presents a list to the user. At the same time, it analyzes the user's facial and voice data to determine their emotional state and suggests products that fit that emotional state. This process allows the user to have an efficient and emotionally adaptive shopping experience.

[0997] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0998] Step 1:

[0999] The user launches a dedicated application on their smartphone and inputs the conditions for the desired product. The input data includes the category (e.g., "laptop"), the upper price limit, the required memory capacity, the type of storage, etc. The input conditions are sent from the device to the server.

[1000] Step 2:

[1001] The server stores the received conditions in a database, including the user-entered conditions such as category, price limit, memory capacity, and storage type.

[1002] Step 3:

[1003] The server calls the application programming interfaces (APIs) of multiple online marketplaces to collect product information that matches the criteria. Specifically, the APIs are used to obtain product information, and the obtained data includes product name, price, review rating, and stock status. This data is then sent to the server.

[1004] Step 4:

[1005] The server stores the collected product information in a database, including product names, prices, review ratings, and stock availability obtained from each online marketplace.

[1006] Step 5:

[1007] The server analyzes the products based on the collected information and calculates a score. Specifically, it analyzes factors such as price, reviews, and seller reliability, and scores the products based on each factor. Scoring includes data processing (normalization, weighted average, etc.) and data calculation.

[1008] Step 6:

[1009] The server selects multiple products with high scores and generates a list, which is then stored in a database.

[1010] Step 7:

[1011] The server notifies the user of the generated list, which includes the scored products and their detailed information (price, review rating, stock status, etc.).

[1012] Step 8:

[1013] While the user is browsing the product list, the device's built-in camera and microphone are used to collect the user's facial expressions and voice. The emotion recognition engine analyzes the collected data and generates the user's emotion data. The generated emotion data is then sent from the device to the server.

[1014] Step 9:

[1015] The server adjusts the product list based on the user's emotional data. Specifically, the server analyzes the emotional data and adjusts the product list so that, for example, if the user is confused, products with high reviews are prioritized, and if the user is excited, higher-priced, high-performance products are prioritized and displayed at the top of the list.

[1016] Step 10:

[1017] The server automatically completes the purchase process for the product selected by the user using the API of each online marketplace. The information required for the purchase (shipping address, payment information, etc.) is obtained from the user's account information, and the purchase process is completed.

[1018] Step 11:

[1019] When the purchase is complete, the server sends a notification of the purchase completion to the terminal and saves the purchase history in a database, which includes the name of the purchased product, the purchase date and time, the price, shipping information, etc.

[1020] 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.

[1021] 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.

[1022] 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.

[1023] [Fourth embodiment]

[1024] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1025] 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.

[1026] 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).

[1027] 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.

[1028] 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.

[1029] 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).

[1030] 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. 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.

[1031] 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.

[1032] 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.

[1033] 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.

[1034] 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.

[1035] 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.

[1036] 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."

[1037] The present invention provides a system that allows users to search for and compare products from multiple online marketplaces and automate the purchasing process. The system includes a terminal that includes an interface for users to input product-related requirements, a server that receives the requirements and processes the information, and an API for collecting product information.

[1038] First, the user uses a terminal to input product-related requirements. For example, specific requirements such as "laptop computer, price under 100,000 yen, memory 8GB or more, SSD installed" can be input. This input information is sent to the server.

[1039] The server stores the received user conditions in a database. The server then calls the APIs of multiple online marketplaces to collect product information that matches the conditions. For example, it retrieves product lists from online marketplaces such as Amazon, Rakuten, and Yahoo Shopping. The information retrieved from the API includes the product name, price, review rating, and stock status.

[1040] The server then analyzes each product based on the collected product information. The analysis includes factors such as price, review rating, and seller credibility, and calculates a score based on each factor. This score is used to select the best product. As a result, a list of the top N products (e.g., 10) is generated and stored in a database.

[1041] This list is sent from the server to the terminal and displayed to the user. The user can review the product list presented via the terminal and select the appropriate product. Once the user confirms the purchase, the server automatically completes the purchase process using the API of each online marketplace. At this time, the necessary information (shipping address, payment information, etc.) is obtained from the user's account information.

[1042] Finally, when the purchase is complete, the server sends the information to the terminal and notifies the user of the completion of the purchase. The purchase information is also saved in a database.

[1043] For example, if a user enters "laptop computer" as a search condition, the server will search for products on Amazon, Rakuten, Yahoo Shopping, etc., and collect the necessary information. It will then calculate a score based on price and review ratings to select the most suitable product. The user can then review the selected product list, choose the product that best suits their needs, and proceed with the purchase. This allows the user to enjoy a smooth shopping experience.

[1044] The processing flow will be explained below.

[1045] Step 1:

[1046] The user opens the device interface and enters product-related criteria. For example, if the user is looking for a laptop computer, they enter specific criteria such as a price of less than 100,000 yen, 8GB or more of memory, and an SSD.

[1047] Step 2:

[1048] The terminal sends the entered conditions to the server, which receives the conditions and stores them in its database.

[1049] Step 3:

[1050] The server calls the APIs of multiple online marketplaces to collect product information that matches the above conditions. The server then calls the APIs of Amazon, Rakuten, Yahoo Shopping, etc. in order, sets the necessary parameters, and sends the request.

[1051] Step 4:

[1052] The online marketplace receives the request and returns product information that matches the criteria in JSON format. The server parses the received JSON data and extracts product information (product name, price, review rating, stock status, etc.).

[1053] Step 5:

[1054] The server stores the collected product information in a database, centralizing data from different online marketplaces and storing it in a unified format.

[1055] Step 6:

[1056] The server analyzes each product based on the stored product information and calculates a score based on factors such as price, review rating, and seller reliability. The server then weights each of these factors to calculate an overall score.

[1057] Step 7:

[1058] The server selects the top N products (for example, 10) in descending order of score and generates a candidate list. This list is provided to the user and is temporarily stored in a database.

[1059] Step 8:

[1060] The server sends the generated candidate list to the terminal, which receives it and displays the product list to the user. The user reviews this list and selects the product that seems most suitable.

[1061] Step 9:

[1062] The user decides to purchase and presses the purchase button. The device sends the information to the server.

[1063] Step 10:

[1064] The server again calls the API of the online marketplace for the selected product and sends a request to proceed with the purchase. The server obtains the shipping address, payment information, etc. from the user's account information, sets the necessary parameters, and sends the request.

[1065] Step 11:

[1066] The online marketplace receives the purchase request and completes the order process, after which it sends a purchase completion response back to the server.

[1067] Step 12:

[1068] The server receives the response indicating the purchase is complete and sends that information to the terminal. The terminal notifies the user that the purchase is complete and displays the purchase information. At the same time, the server saves the purchase history in a database.

[1069] Example 1

[1070] 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."

[1071] In modern online shopping, it is common for users to individually visit multiple marketplaces to search for products, compare them, and complete the purchase process. However, this process is not only time-consuming and labor-intensive, but also requires manual input according to the specifications of each marketplace, placing a significant burden on users. Furthermore, comparing prices and reviews across different marketplaces is tedious, making it difficult to make the optimal choice. This makes it difficult for users to efficiently purchase the best products at the best prices.

[1072] 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.

[1073] In this invention, the server includes means for a user to input conditions related to a desired product, means for receiving the conditions and saving the conditions in a database, means for calling application programming interfaces of multiple online marketplaces to collect product information that matches the conditions, means for saving the collected product information in a database, means for analyzing the products based on the collected information and calculating a score, means for selecting multiple products with high scores and creating a list, means for notifying the user of the created list, means for proceeding with the purchase of the product selected by the user using the application programming interface of the online marketplace, means for acquiring shipping address and payment information related to the user, means for receiving and notifying the user of completion of the purchase, and means for saving the purchase completion information in a database. This enables a user to search for, compare, and select the optimal product by entering conditions once, without visiting multiple marketplaces, and to automate the purchase process, thereby efficiently and quickly completing the purchase.

[1074] A "user" is an entity that utilizes the system to input criteria for searching, comparing, and purchasing products.

[1075] "Conditions" are attributes or requirements (e.g., price, performance, brand, etc.) that a user specifies regarding a desired product.

[1076] A "terminal" is a computing device that a user uses to enter conditions and receive results.

[1077] A "server" is a central computer system that processes data based on requirements received from users.

[1078] A "database" is a data storage system for storing and managing data such as terms and conditions, product information, and purchase history.

[1079] An "application programming interface (API)" is a standardized interface that a server uses to retrieve product information from an online marketplace.

[1080] A "marketplace" is an online platform where multiple sellers offer products and users can purchase them.

[1081] "Product information" refers to detailed product information obtained from the marketplace (e.g., product name, price, review rating, stock status, etc.).

[1082] The "score" is an evaluation value calculated based on collected product information, taking into account factors such as price, review rating, and seller reliability.

[1083] A "list" refers to a set of products generated by selecting multiple products with high scores.

[1084] "Delivery address" is address information required for a user to receive the purchased product.

[1085] "Payment Information" refers to payment information such as credit card information and bank account information required to complete the purchase process.

[1086] A "purchase procedure" is a series of operations and processes required to complete the purchase of a product selected by a user.

[1087] "Completion information" is information used to confirm that the purchase procedure has been completed successfully.

[1088] The present invention is a system for automating the process of users searching, comparing, and purchasing products from multiple online marketplaces. The system includes a terminal that provides an interface for users to input product-related requirements, a server that receives the requirements and processes the information, and an application programming interface (API) for collecting product information.

[1089] Hardware and software used

[1090] Device: The device on which the user enters product conditions (PC, smartphone, tablet, etc.)

[1091] Servers: Web servers and database servers (e.g., Amazon Web Services, Microsoft Azure)

[1092] Database: Relational database such as MySQL or PostgreSQL

[1093] API: Application programming interface provided by each online marketplace (e.g., Amazon API, Rakuten API, Yahoo Shopping API)

[1094] Analysis tools: Python Pandas, Numpy, etc.

[1095] System details

[1096] 1. Enter and submit product conditions

[1097] The user uses the device interface to input the search criteria for the product they want to search for, for example, "laptop computer, price under 100,000 yen, memory 8GB or more, SSD installed."

[1098] These conditions are transmitted from the terminal to the server.

[1099] 2. Receipt and storage of terms and conditions

[1100] The server stores the received conditions in a database, a process that uses a relational database such as MySQL or PostgreSQL.

[1101] 3. Collection of information

[1102] The server uses the saved conditions to call the API of each marketplace to collect product information. For example, it uses the Amazon API or Rakuten API to obtain product information.

[1103] Information collected includes product name, price, review rating, and availability.

[1104] 4. Data Analysis

[1105] The server analyzes the collected product information using Python's Pandas and Numpy, and calculates a score based on price, review rating, seller reliability, etc.

[1106] 5. Creating and saving a list

[1107] The server selects the best products based on the calculated scores and generates a top N (e.g., 10) product list, which is then stored in the database again.

[1108] 6. List Notification

[1109] The server sends the generated list to the terminal, which receives it and displays it to the user.

[1110] 7. Purchase Procedure

[1111] Once the user selects a product and confirms the purchase, the server obtains the user's shipping address and payment information and automatically completes the purchase process via the marketplace's API.

[1112] 8. Purchase completion notification

[1113] Once the purchase procedure is complete, the server sends a notification of purchase completion to the terminal, which is displayed to the user. The purchase information is also saved in a database.

[1114] Specific examples

[1115] Example of user input: "Laptop, price under 100,000 yen, 8GB or more of memory, SSD installed"

[1116] Example prompt for a generative AI model: "Search for products that meet the criteria of 'laptops, priced under ¥100,000, with at least 8GB of memory and an SSD,' and calculate a score based on price and ratings to select the best product."

[1117] As described above, the system of the present invention allows users to search multiple online marketplaces at once and select and purchase the best products quickly and efficiently.

[1118] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1119] Step 1:

[1120] The user enters product conditions

[1121] Input: The user uses the device interface to input product requirements. For example, they might input "laptop computer, price under 100,000 yen, memory 8GB or more, SSD installed."

[1122] Action: The user enters search criteria into the device's input field and presses the "Search" button.

[1123] Output: The entered conditions are sent from the terminal to the server.

[1124] Step 2:

[1125] The server receives and stores the conditions.

[1126] Input: Product conditions sent from the terminal.

[1127] Behavior: The server checks the received conditions to ensure that the data is valid, then stores it in the database (MySQL or PostgreSQL).

[1128] Output: The valid product terms are saved to the database.

[1129] Step 3:

[1130] The server collects information from the marketplace.

[1131] Input: Product terms stored in the database.

[1132] Operation: The server calls the API of each online marketplace (e.g., Amazon API, Rakuten API, Yahoo Shopping API) and collects product information that matches the product conditions.

[1133] Output: Product information obtained from each marketplace (product name, price, review rating, availability, etc.).

[1134] Step 4:

[1135] The server saves the product information to a database

[1136] Input: Product information collected from each marketplace.

[1137] How it works: The server converts the collected product information into an appropriate format and stores it in a database.

[1138] Output: Product information is saved in the database.

[1139] Step 5:

[1140] The server analyzes the data and calculates the score

[1141] Input: Product information stored in the database.

[1142] How it works: The server analyzes product information and calculates a score based on factors such as price, review rating, seller reliability, etc. Calculations are performed using Python tools such as Pandas and Numpy.

[1143] Output: A score is calculated for each product.

[1144] Step 6:

[1145] The server generates and stores the top N product list

[1146] Input: Product information for which a score is calculated.

[1147] How it works: The server sorts the products based on the calculated score and generates a list of the top N (e.g., 10) products, which is then stored in a database.

[1148] Output: A list of the top N products is generated and stored in a database.

[1149] Step 7:

[1150] The server sends the product list to the terminal.

[1151] Input: A server-generated top-N product list.

[1152] How it works: The server encodes the product list in JSON format and sends it to the device via the REST API.

[1153] Output: The product list is sent to the terminal.

[1154] Step 8:

[1155] The user selects an item and confirms the purchase

[1156] Input: The top N product list sent to the device.

[1157] How it works: The user reviews the product list, selects the product they want, and confirms their purchase. They then enter the required information (shipping address, payment information, etc.) through the device interface.

[1158] Output: The user's selected products and purchase information are sent to the server.

[1159] Step 9:

[1160] The server automatically executes the purchase process

[1161] Input: Your purchase confirmation and account information (shipping address, payment information, etc.).

[1162] How it works: The server calls the purchasing API of each online marketplace and automatically completes the purchase process.

[1163] Output: The purchase is completed.

[1164] Step 10:

[1165] The server sends and saves a purchase completion notification

[1166] Input: Purchase completion information.

[1167] Operation: The server confirms that the purchase was completed successfully, sends a notification to the device, and saves the purchase completion information in the database.

[1168] Output: A purchase completion notice will be displayed on the terminal, and the purchase completion information will be saved in the database.

[1169] (Application example 1)

[1170] 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."

[1171] In modern society, users spend a great deal of time and effort searching, comparing, and purchasing products from multiple electronic markets. This has led to a growing need for systems that can efficiently select optimal products and automate the purchasing process. Furthermore, ambiguity that arises when entering search criteria and the difficulty of comparing different information across different markets are also issues. Furthermore, it is important to provide an environment where users can easily perform these operations using their smartphones.

[1172] 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.

[1173] In this invention, the server includes: a means for a user to input search criteria for a desired product; a means for receiving the search criteria and saving the search criteria in a database; a means for calling APIs of multiple online markets to collect product information that matches the search criteria; a means for saving the collected product information in a database; a means for analyzing the products based on the collected information and calculating a score; a means for selecting multiple products with high scores and generating a list; a means for notifying the user of the generated list; a means for completing the purchase process for the user-selected products using the online market API; a means implemented as a smartphone application for the above means; and a means for generating prompt sentences using a generative AI model when the user enters search criteria. This allows users to efficiently search, compare, and purchase appropriate products from multiple online markets at once. Furthermore, generating prompt sentences eliminates input ambiguity, facilitating operation from a smartphone.

[1174] "User" means any person or entity that uses the System to search for, compare, and purchase products.

[1175] "Product conditions" are specific standards and requirements (e.g., price, specifications, rating) regarding the product desired by the user.

[1176] A "database" is a system that stores and manages data such as product information and user conditions.

[1177] An "electronic marketplace" is an online marketplace that sells goods over the Internet.

[1178] "API" stands for Application Programming Interface, an interface that allows electronic market services to exchange data with the outside world.

[1179] "Product Information" means product details (e.g., price, reviews, availability) collected from each electronic marketplace.

[1180] "Product analysis" is the process of evaluating the value and suitability of a product based on collected product information and according to multiple evaluation criteria.

[1181] A "score" is a numerical evaluation of each product based on the results of product analysis.

[1182] The "list" is a compilation of the results of selecting products with high scores.

[1183] "Notification" is a means of informing the user of important information (e.g., product list, purchase completion).

[1184] A "purchase process" is a series of steps to purchase a product on an online marketplace.

[1185] A "smartphone application" is application software that runs on a smartphone.

[1186] A "generative AI model" is a model that uses artificial intelligence technology to generate prompts and other text based on user input.

[1187] "Prompt sentences" are guidelines or example sentences created using generative AI models when a user types something.

[1188] The present invention is a system that allows users to search for and compare products from multiple online markets and automate the purchasing process. The system includes a terminal with an interface through which users input product-related requirements, a server that receives the requirements and processes the information, and an API for collecting product information.

[1189] First, the user uses a smartphone to input product-related criteria. At this time, a generative AI model can be used to generate a prompt sentence, which can be presented to the user as an input guide. For example, a generated prompt sentence might read, "I'm looking for a laptop computer. Priced at under 100,000 yen, with at least 8GB of memory and an SSD." The user then inputs their criteria based on this prompt sentence.

[1190] The entered information is sent from the user's smartphone to a server. The server stores the received user conditions in a database. The server then calls the APIs of multiple online markets to collect product information that matches the conditions. Typical examples of online markets include Amazon, Rakuten, and Yahoo Shopping. Information obtained from the API includes product name, price, review rating, and stock status.

[1191] Next, the server analyzes each product based on the collected product information. The analysis includes factors such as price, review rating, and seller reliability, and calculates a score based on each factor. The server uses this score to select the best product. As a result, a list of the top N products (for example, 10) is generated and stored in a database. This list is then sent from the server to a smartphone and notified to the user.

[1192] Users can view the product list displayed on their smartphones and select the appropriate product. Once the user confirms the purchase, the server automatically completes the purchase process using the API of each online marketplace. At this time, necessary information (shipping address, payment information, etc.) is obtained from the user's account information.

[1193] Finally, once the purchase is complete, the server sends the information to the user's smartphone and notifies them of the purchase. The purchase information is also stored in a database, allowing users to efficiently search, compare, and purchase suitable products from multiple online markets all at once.

[1194] For example, if a user enters "laptop computer" as a search condition, the server will search for products on Amazon, Rakuten, Yahoo Shopping, etc., and collect the necessary information. It will then calculate a score based on price and review ratings to select the most suitable product. The user can then review the selected product list, choose the product that best suits their needs, and proceed with the purchase. This allows the user to enjoy a smooth shopping experience.

[1195] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1196] Step 1:

[1197] A user uses a smartphone to input product-related criteria. The user uses the generative AI model to display a prompt ("I'm looking for a laptop computer. It should cost less than 100,000 yen, have 8GB or more of memory, and have an SSD.") while inputting the criteria. The entered criteria (e.g., laptop computer, price less than 100,000 yen, 8GB or more of memory, and have an SSD) are sent from the smartphone to the server.

[1198] Step 2:

[1199] The server stores the received user requirements in a database, where separate data for each user is stored and indexed for later use.

[1200] Step 3:

[1201] The server calls the APIs of multiple online markets to collect product information that matches the above conditions. Specifically, it uses the APIs of Amazon, Rakuten, and Yahoo Shopping to collect information such as product name, price, review rating, and stock status. The collected product information is temporarily stored in a database.

[1202] Step 4:

[1203] The server analyzes each product based on the collected product information, taking into account factors such as price, review rating, and seller reliability. A score is calculated based on each factor, and a score is assigned to each product. The lower the price, the higher the score, and the higher the review rating, the higher the score.

[1204] Step 5:

[1205] The server selects the top 10 products and generates a list. This list is ranked to include the products that best match the criteria entered by the user. The list is stored in a database and sent to the user's smartphone.

[1206] Step 6:

[1207] The user's smartphone notifies the user of the product list received from the server and displays it. The user selects any product from the presented list. The product information selected by the user is sent from the smartphone to the server.

[1208] Step 7:

[1209] The server automatically uses the API of the online marketplace to process the purchase of the product selected by the user. Specifically, it obtains user information such as shipping address and payment information and completes the purchase through each online marketplace's API. Once the purchase is complete, the information is saved in a database and a purchase completion notification is sent to the smartphone.

[1210] Step 8:

[1211] The server saves the purchase history in a database for future recommendations and history inquiries. A notification is displayed on the user's smartphone indicating that the purchase has been completed, and all processing is complete.

[1212] 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.

[1213] The present invention combines a system that allows users to search for and compare products from multiple online marketplaces and automates the purchasing process with an emotion engine that recognizes user emotions. This system includes a terminal that includes an interface through which users input product-related conditions, a server that receives the conditions and processes the information, an API for collecting product information, and an emotion engine that recognizes user emotions.

[1214] First, the user opens the device interface and inputs the product requirements. For example, they can enter specific requirements such as "laptop computer, price under 100,000 yen, memory over 8GB, SSD installed." This input information is sent to the server.

[1215] The server stores the received user's requirements in a database. Next, the server calls the APIs of multiple online marketplaces to collect product information that matches the requirements. For example, it retrieves product lists from online marketplaces such as Amazon, Rakuten, and Yahoo Shopping. The information retrieved from the API includes the product name, price, review rating, and stock status.

[1216] The server then analyzes each product based on the collected product information. The analysis includes factors such as price, review rating, and seller credibility, and calculates a score based on each factor. This score is used to select the best product. As a result, a list of the top N products (e.g., 10) is generated and stored in a database.

[1217] This list is sent from the server to the terminal and displayed to the user. The user can check the product list presented via the terminal and select an appropriate product. Here, the emotion engine recognizes emotions from the user's facial expressions and voice and collects the user's emotional data.

[1218] The server analyzes the emotional data and adjusts the product list according to the user's emotions. For example, if the user is unsure, it will prioritize products with high reviews and display them at the top of the list. On the other hand, if the user is excited, it will recommend high-quality products with slightly higher prices.

[1219] Once the user confirms the purchase, the server automatically processes the purchase using the API of each online marketplace. At this time, the necessary information (shipping address, payment information, etc.) is obtained from the user's account information. Once the purchase is complete, the server sends the information to the terminal and notifies the user that the purchase has been completed. The purchase information is also saved in a database.

[1220] For example, if a user enters "laptop computer" as a search term, the server will search for products on Amazon, Rakuten, Yahoo Shopping, etc., and collect the necessary information. It will then calculate a score based on price and review ratings to select the most suitable product. It will use an emotion engine to detect the user's hesitation or excitement and recommend products accordingly. The user can then review the selected product list, choose the product that best suits their needs, and proceed with the purchase. This allows the user to enjoy a smooth shopping experience.

[1221] The processing flow will be explained below.

[1222] Step 1:

[1223] The user opens the device interface and enters product-related criteria. For example, if the user is looking for a laptop computer, they enter specific criteria such as a price of less than 100,000 yen, 8GB or more of memory, and an SSD.

[1224] Step 2:

[1225] The terminal sends the entered conditions to the server, which receives the conditions and stores them in its database.

[1226] Step 3:

[1227] The server starts the emotion engine and starts collecting the user's facial expressions and voice data in real time, which allows the user's emotional data to be continuously analyzed.

[1228] Step 4:

[1229] The server calls the APIs of multiple online marketplaces to collect product information that matches the above conditions. The server then calls the APIs of Amazon, Rakuten, Yahoo Shopping, etc. in order, sets the necessary parameters, and sends the request.

[1230] Step 5:

[1231] The online marketplace receives the request and returns product information that matches the criteria in JSON format. The server parses the received JSON data and extracts product information (product name, price, review rating, stock status, etc.).

[1232] Step 6:

[1233] The server stores the collected product information in a database, centralizing data from different online marketplaces and storing it in a unified format.

[1234] Step 7:

[1235] The server analyzes each product based on the stored product information and calculates a score based on factors such as price, review rating, and seller reliability. The server then weights each of these factors to calculate an overall score.

[1236] Step 8:

[1237] The server selects the top N products (for example, 10) in descending order of score and generates a candidate list. This list is provided to the user and is temporarily stored in a database.

[1238] Step 9:

[1239] The server sends the generated candidate list to the terminal, which receives it and displays the product list to the user. The user can check this list and select an appropriate product.

[1240] Step 10:

[1241] The emotion engine analyzes the user's emotion data in real time and provides feedback to the server according to the user's emotion. If the user is unsure, the emotion engine detects the user's uncertain emotion and notifies the server. If the user is excited, the emotion engine measures the level of excitement and notifies the server.

[1242] Step 11:

[1243] The server adjusts the product list based on feedback from the emotion engine. For example, if the user is unsure, it will prioritize products with high reviews. If the user is excited, it will recommend high-quality products with higher prices.

[1244] Step 12:

[1245] The user decides to purchase and presses the purchase button. The device sends the information to the server.

[1246] Step 13:

[1247] The server again calls the API of the online marketplace for the selected product and sends a request to proceed with the purchase. The server obtains the shipping address, payment information, etc. from the user's account information, sets the necessary parameters, and sends the request.

[1248] Step 14:

[1249] The online marketplace receives the purchase request and completes the order process, after which it sends a purchase completion response back to the server.

[1250] Step 15:

[1251] The server receives the response indicating the purchase is complete and sends that information to the terminal. The terminal notifies the user that the purchase is complete and displays the purchase information. At the same time, the server saves the purchase history in a database.

[1252] Example 2

[1253] 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."

[1254] In today's online shopping environment, users must simultaneously search multiple online marketplaces and compare information from each. This requires a lot of time and effort, potentially compromising the user experience. Another issue is that product selection is often based solely on impersonal data, without taking into account the user's emotions, preventing them from making the best choice.

[1255] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1256] In this invention, the server includes: means for a user to input conditions related to a desired product; means for receiving the conditions and storing the conditions in a database; means for calling APIs of multiple online marketplaces to collect product information that matches the conditions; means for storing the collected product information in a database; means for analyzing products based on the collected information and calculating a score; means for selecting multiple products with high scores and generating a list; means for notifying the user of the generated list; means for proceeding with the purchase of the products selected by the user using the APIs of the online marketplaces; means for recognizing the user's emotions and collecting emotion data; means for adjusting the product list based on the emotion data; and means for notifying the user of purchase completion information and storing the data in a database. This enables users to efficiently perform a series of operations from product search to comparison to purchase, and further enables product selection that takes emotion into consideration.

[1257] "User" refers to a user of the system who inputs product-related conditions and searches, compares, and purchases based on those conditions.

[1258] "Conditions" refer to specific requirements or filter items that a user inputs for a desired product, such as price, specifications, brand, etc.

[1259] A "database" is an information storage system for storing and managing collected and analyzed product information, user conditions, purchase history, and other data.

[1260] An "online marketplace" is a platform where products are bought and sold over the Internet, and refers to a marketplace where multiple sellers list their products.

[1261] "API" stands for Application Programming Interface, a technology that provides a means for different software applications to communicate with each other.

[1262] "Product Information" means detailed product data collected from online marketplaces, including product name, price, review rating, and availability.

[1263] A "score" is a numerical indicator calculated by analyzing collected product information and based on its conformance to conditions and evaluation.

[1264] The "list" is a collection of products selected in descending order of score, and is a list of products notified to the user.

[1265] An "emotion engine" is a technology that recognizes emotions from a user's facial expressions, voice, etc., and collects and analyzes that data.

[1266] The "purchase process" refers to a series of operations and processes that a user performs to actually purchase a selected product from an online marketplace.

[1267] "Proceeding with the purchase procedure" is an execution process that automatically advances the purchase process for the product selected by the user via the API of the online marketplace.

[1268] The "completion notification" is information that notifies the user that the purchase procedure has been completed.

[1269] "Emotional Data" refers to data about a user's emotions collected and analyzed by the emotion engine.

[1270] "Adjustment" refers to the operation or process of changing product listings or recommendations based on collected emotional data.

[1271] The present invention combines a system that allows users to search for and compare products from multiple online marketplaces and automates the purchasing process with an emotion engine that recognizes user emotions. This system includes a terminal that includes an interface through which users input product-related conditions, a server that receives the conditions and processes the information, an API for collecting product information, and an emotion engine that recognizes user emotions.

[1272] First, the user opens the device interface and inputs the product requirements. For example, they can enter specific requirements such as "laptop computer, price under 100,000 yen, memory over 8GB, SSD installed." This input information is sent to the server.

[1273] The server stores the received user conditions in a database, using a relational database such as MongoDB or MySQL. The server then calls the APIs of multiple online marketplaces to collect product information that matches the conditions from, for example, Amazon, Rakuten, and Yahoo Shopping. The information obtained from the API includes the product name, price, review rating, and stock status.

[1274] The server then analyzes each product based on the collected product information. The analysis includes factors such as price, review rating, and seller credibility, and calculates a score based on each factor. This score is used to select the best product. As a result, a list of the top N products (e.g., 10) is generated and stored in a database.

[1275] This list is sent from the server to the device and displayed to the user. The user checks the product list presented via the device. At this time, the emotion engine recognizes emotions from the user's facial expressions and voice and collects emotional data. The emotion engine uses Microsoft's facial recognition API and voice recognition SDK.

[1276] The server analyzes the emotional data and adjusts the product list according to the user's emotions. For example, if the user is unsure, it will prioritize products with high reviews and display them at the top of the list. On the other hand, if the user is excited, it will recommend high-quality products with slightly higher prices.

[1277] Once the user confirms the purchase, the server automatically processes the purchase using the API of each online marketplace. At this time, the necessary information (shipping address, payment information, etc.) is obtained from the user's account information. Once the purchase is complete, the server sends the information to the terminal and notifies the user that the purchase has been completed. The purchase information is also saved in a database.

[1278] For example, if a user enters "laptop computer" as a search condition, the server will search for products on Amazon, Rakuten, Yahoo Shopping, etc., and collect the necessary information. It will then calculate a score based on price and review ratings to select the most suitable product. It will use an emotion engine to detect the user's hesitation or excitement, and recommend products accordingly. The user can then review the selected product list, choose the product that best suits their needs, and proceed with the purchase.

[1279] To implement this system, the following example prompts are provided:

[1280] "I'm looking for a laptop computer, but I'd like one that costs under 100,000 yen, has 8GB or more of memory, and has an SSD."

[1281] As described above, the present invention enables users to quickly and efficiently search for and compare products from multiple online marketplaces, and further select and purchase the most suitable product taking their emotions into consideration.

[1282] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1283] Step 1:

[1284] The user opens the terminal interface and inputs product-related conditions. The input data includes the product type (e.g., "laptop computer"), upper price limit (e.g., "under 100,000 yen"), memory capacity (e.g., "8GB or more"), and storage type (e.g., "equipped with SSD"). These conditions become the basis for data processing in subsequent processes. The input information is sent to the server via the user interface.

[1285] Step 2:

[1286] The device receives the condition data entered by the user and sends it to the server via an HTTP request. Specifically, the request is formed in the format "Product: Laptop, Price: Under 100,000 yen, Memory: 8GB or more, Storage: SSD." The input is the user's condition data, and the output is an HTTP request to the server.

[1287] Step 3:

[1288] The server analyzes the received user condition data and stores it in a relational database (for example, MongoDB or MySQL). Specifically, various conditions are saved as fields and used for future data reference and linkage. The input is the condition data sent by the user, and the output is the condition information stored in the database.

[1289] Step 4:

[1290] The server sequentially calls the APIs of multiple online marketplaces (e.g., the APIs of Amazon, Rakuten, and Yahoo Shopping) based on the stored condition data. It then sends requests to collect product information that matches the conditions. The input is the condition data stored in the database, and the output is product information obtained from each marketplace.

[1291] Step 5:

[1292] The server analyzes the retrieved product information and calculates a score for each product based on multiple factors, such as price, review rating, and seller reliability. A scoring algorithm is used to identify the product that best meets the user's criteria. The input is product data retrieved from the API, and the output is the analyzed score for each product.

[1293] Step 6:

[1294] The server sorts the products in descending order of score based on the calculated score. It then generates a list of the top N (e.g., top 10) products and stores it in a database. Here, a method is applied to efficiently provide the analysis results to the user. The input is score information, and the output is the top N product list.

[1295] Step 7:

[1296] The server sends the generated product list to the terminal as an HTTP response and displays it to the user. The input is the top N product list, and the output is the product list displayed to the user.

[1297] Step 8:

[1298] While the user is browsing the product list, the device's emotion engine (for example, Microsoft's facial recognition API or voice recognition SDK) collects the user's facial expression and voice data in real time. For example, a webcam and microphone are used for facial recognition and voice analysis. The input is the user's real-time facial expression and voice, and the output is emotion data.

[1299] Step 9:

[1300] The server analyzes the collected emotional data and adjusts the product list according to the user's psychological state (e.g., indecision, excitement). For example, if the user is indecisive, products with high review ratings are prioritized and displayed at the top of the list. The input is emotional data, and the output is the adjusted product list.

[1301] Step 10:

[1302] When a user confirms a purchase, the server automatically initiates the purchase process using the API of each online marketplace. The input is the product selected by the user and account information, and the output is the execution and completion of the purchase process.

[1303] Step 11:

[1304] When the purchase is completed, the server notifies the user of the purchase completion and simultaneously saves the purchase history in a database. The input is the purchase completion information, and the output is the notification to the user and the history saved in the database.

[1305] The above processing steps enable users to efficiently search, compare, and purchase products, and realize a system that allows for recommendations that take emotions into consideration.

[1306] (Application example 2)

[1307] 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."

[1308] Existing online shopping systems require a lot of effort for users to select products, and they often feel lost or have difficulty in making purchasing decisions. In addition, they provide mechanical recommendations without considering the user's emotional state, which results in a poor user experience.

[1309] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input conditions related to a desired product; means for receiving the conditions and saving them in a database; means for calling application programming interfaces of multiple online marketplaces to collect product information that matches the conditions; means for saving the collected product information in a database; means for analyzing products based on the collected information and calculating a score; means for selecting multiple products with high scores and creating a list; means for notifying the user of the created list; means for recognizing emotions from the user's facial expressions and voice and adjusting the product list based on the collected user emotion data; and means for completing the purchase procedure for the products selected by the user using the application programming interface of the online marketplace. This reduces the confusion and difficulty that users may experience when selecting products and enables appropriate product recommendations based on the user's emotional state.

[1310] A "User" is a person or entity that intends to search for and purchase a product.

[1311] "Conditions" are attributes or requirements that a user specifies when searching for a particular product.

[1312] A "database" is a system for storing and managing product information, user requirements, and emotional data.

[1313] An "application programming interface (API)" is an interface for exchanging information between different systems.

[1314] "Product information" refers to data such as product name, price, review rating, and stock status obtained from online marketplaces.

[1315] "Emotion recognition" is a technology that analyzes a user's facial expressions and voice to determine their emotional state.

[1316] The "score" is an evaluation value calculated based on collected product information, taking into account factors such as price, review rating, and seller reliability.

[1317] A "list" is a format for displaying multiple products selected based on their scores in an ordered manner.

[1318] "Emotion data" refers to data relating to the emotional state of the user recognized from facial expressions and voice.

[1319] An "online marketplace" is a platform for selling products over the Internet.

[1320] The "purchase procedure" is the procedure for a user to purchase a product selected by the user on the online marketplace.

[1321] The system of the present invention allows users to efficiently search for desired products using a smartphone and improves product selection through an emotion recognition engine. A specific embodiment of this system is described below.

[1322] First, a user launches a dedicated application on their smartphone and inputs the desired product's conditions, such as the category (e.g., "laptop"), price limit, required memory capacity, and storage type.

[1323] The terminal sends the conditions received from the user to the server, which stores these conditions in a database and calls the application programming interfaces (APIs) of multiple online marketplaces to collect product information that matches the conditions. This includes price comparison sites, and the information obtained includes product name, price, review rating, and stock status.

[1324] The server then analyzes the collected product information based on factors such as price, reviews, and seller reliability, and calculates a score based on each.The best products are selected based on this score and generated as a list.The generated list is stored in a database and notified to the device.

[1325] Furthermore, while the user is browsing the product list, an emotion recognition engine analyzes the user's facial expressions and voice using the device's built-in camera and microphone to collect emotional data. This emotional data is sent to the server, which then adjusts the product list based on the user's emotional state. For example, if the user is confused, the server can prioritize products with high reviews, while if the user is excited, the server can prioritize higher-priced, high-performance products at the top of the list.

[1326] Once the user selects the product to purchase, the server automatically completes the purchase process using the API of each online marketplace. During this process, the user's account information (shipping address, payment information, etc.) is securely processed. Once the purchase is complete, the server sends a notification of purchase completion to the device, and the purchase history is saved in a database.

[1327] Here's a concrete example: Suppose the user enters the following conditions:

[1328] Example prompt sentence:

[1329] "Laptop, price under 100,000 yen, 8GB or more of memory, SSD installed"

[1330] The server collects product information from multiple online marketplaces, scores them based on reviews and prices, and then presents a list to the user. At the same time, it analyzes the user's facial and voice data to determine their emotional state and suggests products that fit that emotional state. This process allows the user to have an efficient and emotionally adaptive shopping experience.

[1331] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1332] Step 1:

[1333] The user launches a dedicated application on their smartphone and inputs the conditions for the desired product. The input data includes the category (e.g., "laptop"), the upper price limit, the required memory capacity, the type of storage, etc. The input conditions are sent from the device to the server.

[1334] Step 2:

[1335] The server stores the received conditions in a database, including the user-entered conditions such as category, price limit, memory capacity, and storage type.

[1336] Step 3:

[1337] The server calls the application programming interfaces (APIs) of multiple online marketplaces to collect product information that matches the criteria. Specifically, the APIs are used to obtain product information, and the obtained data includes product name, price, review rating, and stock status. This data is then sent to the server.

[1338] Step 4:

[1339] The server stores the collected product information in a database, including product names, prices, review ratings, and stock availability obtained from each online marketplace.

[1340] Step 5:

[1341] The server analyzes the products based on the collected information and calculates a score. Specifically, it analyzes factors such as price, reviews, and seller reliability, and scores the products based on each factor. Scoring includes data processing (normalization, weighted average, etc.) and data calculation.

[1342] Step 6:

[1343] The server selects multiple products with high scores and generates a list, which is then stored in a database.

[1344] Step 7:

[1345] The server notifies the user of the generated list, which includes the scored products and their detailed information (price, review rating, stock status, etc.).

[1346] Step 8:

[1347] While the user is browsing the product list, the device's built-in camera and microphone are used to collect the user's facial expressions and voice. The emotion recognition engine analyzes the collected data and generates the user's emotion data. The generated emotion data is then sent from the device to the server.

[1348] Step 9:

[1349] The server adjusts the product list based on the user's emotional data. Specifically, the server analyzes the emotional data and adjusts the product list so that, for example, if the user is confused, products with high reviews are prioritized, and if the user is excited, higher-priced, high-performance products are prioritized and displayed at the top of the list.

[1350] Step 10:

[1351] The server automatically completes the purchase process for the product selected by the user using the API of each online marketplace. The information required for the purchase (shipping address, payment information, etc.) is obtained from the user's account information, and the purchase process is completed.

[1352] Step 11:

[1353] When the purchase is complete, the server sends a notification of the purchase completion to the terminal and saves the purchase history in a database, which includes the name of the purchased product, the purchase date and time, the price, shipping information, etc.

[1354] 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.

[1355] 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.

[1356] 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.

[1357] 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.

[1358] FIG. 9 illustrates 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 behaviors 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 concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1359] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1360] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1361] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1362] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1363] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1364] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1365] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1366] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1367] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1368] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1369] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1370] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1371] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1372] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1373] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1374] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1375] The following is further disclosed regarding the above embodiment.

[1376] (Claim 1)

[1377] A means for a user to input conditions regarding a desired product;

[1378] means for receiving the conditions and storing them in a database;

[1379] A means for calling APIs of a plurality of online marketplaces to collect product information that meets the conditions;

[1380] A means for storing the collected product information in a database;

[1381] means for analyzing products based on the collected information and calculating a score;

[1382] A means for selecting multiple products with high scores and generating them as a list;

[1383] a means for notifying a user of the generated list;

[1384] A system that includes a means for proceeding with the purchase of a product selected by a user using an API of an online marketplace.

[1385] (Claim 2)

[1386] The system according to claim 1, further comprising means for analyzing products based on product information collected by calling the API of the online marketplace, taking into consideration price, user reviews, and reliability.

[1387] (Claim 3)

[1388] 2. The system according to claim 1, further comprising: means for sending a notification of completion of a purchase procedure to the user; and means for storing a purchase history in a database.

[1389] "Example 1"

[1390] (Claim 1)

[1391] A means for a user to input conditions regarding a desired product;

[1392] means for receiving the conditions and storing them in a database;

[1393] means for calling application programming interfaces of a plurality of online marketplaces to collect product information that meets the conditions;

[1394] A means for storing the collected product information in a database;

[1395] means for analyzing products based on the collected information and calculating a score;

[1396] A means for selecting multiple products with high scores and generating them as a list;

[1397] a means for notifying a user of the generated list;

[1398] means for completing a purchase of the product selected by the user using an application programming interface of the online marketplace;

[1399] means for obtaining shipping address and payment information for said user;

[1400] A means for receiving information on the completion of the purchase procedure and notifying the user;

[1401] a means for storing the completed purchase information in a database;

[1402] A system including:

[1403] (Claim 2)

[1404] The system according to claim 1, further comprising means for analyzing products based on product information collected by calling an application programming interface of the online marketplace, taking into account price, user reviews, and reliability.

[1405] (Claim 3)

[1406] 2. The system according to claim 1, further comprising: means for sending a notification of completion of a purchase procedure to the user; and means for storing a purchase history in a database.

[1407] "Application Example 1"

[1408] (Claim 1)

[1409] A means for a user to input conditions regarding a desired product;

[1410] means for receiving the conditions and storing them in a database;

[1411] A means for calling APIs of a plurality of online markets to collect product information that meets the conditions;

[1412] A means for storing the collected product information in a database;

[1413] means for analyzing products based on the collected information and calculating a score;

[1414] A means for selecting multiple products with high scores and generating them as a list;

[1415] a means for notifying a user of the generated list;

[1416] A means for carrying out a purchase procedure for the product selected by the user using an API of the online marketplace;

[1417] A means implemented as a smartphone application in the above means;

[1418] a means for generating prompt sentences using a generative AI model when a user inputs search criteria;

[1419] A system including:

[1420] (Claim 2)

[1421] The system according to claim 1, further comprising means for analyzing products based on product information collected by calling the API of the electronic marketplace, taking into consideration price, user reviews, and reliability.

[1422] (Claim 3)

[1423] The system according to claim 1, which is implemented as a smartphone application and includes means for sending a notification to the user that the purchase procedure has been completed and means for storing the purchase history in a database.

[1424] "Example 2: Combining Emotion Engines"

[1425] (Claim 1)

[1426] A means for a user to input conditions regarding a desired product;

[1427] means for receiving the conditions and storing them in a database;

[1428] A means for calling APIs of a plurality of online marketplaces to collect product information that meets the conditions;

[1429] A means for storing the collected product information in a database;

[1430] means for analyzing products based on the collected information and calculating a score;

[1431] A means for selecting multiple products with high scores and generating them as a list;

[1432] a means for notifying a user of the generated list;

[1433] A means for proceeding with the purchase of the product selected by the user using an API of the online marketplace;

[1434] means for recognizing a user's emotion and collecting emotion data;

[1435] means for adjusting a product list based on the emotion data;

[1436] The system includes a means for notifying the user of the purchase completion information and storing it in a database.

[1437] (Claim 2)

[1438] The system according to claim 1, further comprising means for analyzing products based on product information collected by calling an API of an online marketplace, taking into account price, user reviews, and reliability.

[1439] (Claim 3)

[1440] 2. The system according to claim 1, further comprising: means for sending a notification of completion of a purchase procedure to the user; and means for storing a purchase history in a database.

[1441] "Application example 2 when combining emotion engines"

[1442] (Claim 1)

[1443] A means for a user to input conditions regarding a desired product;

[1444] means for receiving the conditions and storing them in a database;

[1445] means for calling application programming interfaces of a plurality of online marketplaces to collect product information that meets the conditions;

[1446] A means for storing the collected product information in a database;

[1447] means for analyzing products based on the collected information and calculating a score;

[1448] A means for selecting multiple products with high scores and generating them as a list;

[1449] a means for notifying a user of the generated list;

[1450] means for recognizing emotions from the user's facial expressions and voice and adjusting the product list based on the collected user emotion data;

[1451] A system including means for proceeding with a purchase of a user-selected item using an application programming interface of an online marketplace.

[1452] (Claim 2)

[1453] The system according to claim 1, further comprising means for analyzing products based on product information collected by calling an application programming interface of the online marketplace, taking into account price, user reviews, and reliability.

[1454] (Claim 3)

[1455] 2. The system according to claim 1, further comprising: means for sending a notification of completion of a purchase procedure to the user; and means for storing a purchase history in a database. [Explanation of symbols]

[1456] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for a user to input conditions regarding a desired product; means for receiving the conditions and storing them in a database; A means for calling APIs of a plurality of online marketplaces to collect product information that meets the conditions; A means for storing the collected product information in a database; A means for analyzing products based on the collected information and calculating a score; A means for selecting multiple products with high scores and generating them as a list; a means for notifying a user of the generated list; A system that includes a means for proceeding with the purchase of a product selected by a user using an API of an online marketplace.

2. The system according to claim 1, further comprising means for analyzing products based on product information collected by calling the API of the online marketplace, taking into consideration price, user reviews, and reliability.

3. 2. The system according to claim 1, further comprising: means for sending a notification of completion of a purchase procedure to the user; and means for storing a purchase history in a database.

Images