System

Abstract

To provide a system that enables users to efficiently search for goods and to purchase the goods.SOLUTION: A system includes the means of: mutually connecting a plurality of electronic commerce transaction platforms; providing a conversation type interface; using a natural language processing technology to analyze requests from users; generating a prompt sentence instructing retrieval of goods in accordance with the request from the user; using the generated prompt sentence, and a generative AI model to retrieve the good in accordance with the request from the user from the plurality of electronic commerce transaction platforms; recommending a plurality of goods to the user on the basis of a retrieval result; coordinating settlement solutions to be provided in each country; selecting a corresponding settlement solution on the basis of country information on the user; suggesting a settlement method to the user through a selected settlement module; and verifying settlement information the user inputs, and performing settlement processing.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] With conventional e-commerce services, it was difficult to search and compare products across multiple e-commerce malls, and they lacked the functionality to efficiently recommend products that users wanted.Furthermore, it was difficult to unify the payment solutions that differ from country to country, making global expansion a challenge. [Means for solving the problem]

[0005] This invention provides a system that interconnects multiple e-commerce malls and recommends multiple products based on user requests through a conversational interface. It also has a structure that can be deployed globally by linking payment solutions provided in each country, allowing users to efficiently search, compare, and purchase products. [Brief explanation of the drawings]

[0006] [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. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1 when an emotion engine is combined. [Figure 19] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. [Figure 20] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. [Figure 22] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] 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.

[0008] First, the terms used in the following description will be explained.

[0009] 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, the 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), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] 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.

[0011] 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.

[0012] 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.

[0013] 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."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 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.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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.

[0022] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] One embodiment of the present invention is a system that interconnects multiple e-commerce malls. This system accesses the product databases of each e-commerce mall and retrieves product information in response to a user's request. For example, when a user searches for "sneakers," the system retrieves sneaker product information from multiple e-commerce malls and presents it to the user.

[0029] "Example 2"

[0030] One embodiment of the present invention is a system that provides a conversational interface. The system uses natural language processing technology to enable dialogue with a user. The user uses natural language to search for or purchase a product, and the system generates an appropriate response accordingly. For example, if the user says, "I'm looking for red sneakers," the system searches for "red sneakers" and presents the results to the user.

[0031] "Example 3"

[0032] Furthermore, one embodiment of the present invention is a system that links payment solutions offered in various countries. This system has a payment module that supports the payment solutions of each country, allowing users to purchase products using the payment method of their own country. For example, users in Japan can purchase products using methods such as credit cards, bank transfers, and convenience store payments.

[0033] The processing flow of each embodiment will be described below.

[0034] "Example 1"

[0035] Step 1: The user makes a product search request. For example, a request to search for "sneakers."

[0036] Step 2: The system accesses the product databases of each e-commerce mall and retrieves product information according to the user's request. At this time, it retrieves "sneaker" product information from multiple e-commerce malls.

[0037] Step 3: The acquired product information is presented to the user. The user can select a product from the presented product information and proceed with the purchase.

[0038] "Example 2"

[0039] Step 1: The user makes a product search or purchase request in natural language, for example, "I'm looking for red sneakers."

[0040] Step 2: The system uses natural language processing techniques to analyze the user's request and generate an appropriate response, in this case, a search for "red sneakers."

[0041] Step 3: The generated response is presented to the user, who can then select a product from the presented response and proceed with the purchase.

[0042] "Example 3"

[0043] Step 1: The user selects a product and proceeds with the purchase. At this time, the user selects the payment method for their country. For example, Japanese users can select methods such as credit card, bank transfer, or convenience store payment.

[0044] Step 2: The system calls the payment module corresponding to the selected payment method and processes the payment.

[0045] Step 3: Once the payment is complete, the user is notified of the payment completion, allowing them to purchase the product using their own payment method.

[0046] Example 1

[0047] Next, a description will be given of Example 1 of Form 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."

[0048] In conventional e-commerce systems, users had to search multiple e-commerce platforms individually and compare product information. This required a lot of time and effort from users, making it difficult to conduct efficient product searches. In addition, because the product information provided by each platform differed, sorting and comparing overlapping product information was cumbersome. This reduced user convenience and made it difficult to select the optimal product.

[0049] 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.

[0050] In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for acquiring product information based on a user request, means for aggregating the acquired product information and eliminating duplication, and means for presenting the aggregated product information to the user, thereby enabling the user to check product information aggregated from multiple e-commerce platforms with a single search, enabling them to efficiently and quickly select the most suitable product.

[0051] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[0052] "Interconnection" refers to the state in which multiple systems or networks can communicate with each other and exchange data.

[0053] "User request" refers to a search or request made by a user to the system.

[0054] "Product Information" refers to detailed data about a product, such as the product name, price, availability, images, and description.

[0055] "Acquisition" refers to the system gathering the necessary information from external databases or APIs.

[0056] "Aggregation" refers to combining data obtained from multiple sources into one.

[0057] "Deduplication" refers to combining identical or similar information into one and removing redundant data.

[0058] "Presenting" means displaying or providing information to a user.

[0059] An "application program interface (API)" refers to an interface that allows different software systems to communicate with each other and utilize their functionality.

[0060] The present invention is a system that interconnects multiple e-commerce platforms, acquires product information based on user requests, and aggregates and presents it. Specific embodiments of this system are described below.

[0061] System Overview

[0062] This system consists of three main components: a server, a terminal, and a user. The server interconnects multiple e-commerce platforms and retrieves, aggregates, and presents product information based on user requests. The terminal is a device through which users input search keywords and display product information. Users use the terminal to search for products and obtain information.

[0063] Hardware and software used

[0064] The server is a computer system equipped with a high-performance processor and a large amount of memory. The server obtains product information using the APIs (Application Program Interfaces) of multiple e-commerce platforms. Specifically, the server uses the following APIs:

[0065] E-commerce platform A's API

[0066] E-commerce platform B's API

[0067] API for e-commerce platform C

[0068] The terminal is a device used by the user, such as a smartphone, tablet, or PC. The terminal communicates with the server through a browser or a dedicated application.

[0069] Data processing and calculation

[0070] The server receives search keywords from users and calls the APIs of each e-commerce platform to obtain product information. The obtained product information is aggregated within the server, and duplicate information is eliminated. The aggregated product information is then presented to the user.

[0071] The specific data processing and calculation procedures are as follows:

[0072] 1. The user enters a keyword into the device's search bar.

[0073] 2. The device sends the search keywords to the server.

[0074] 3. The server calls the API of each e-commerce platform to obtain product information.

[0075] 4. The server aggregates the product information it has obtained and eliminates duplicates.

[0076] 5. The server sends the aggregated product information to the terminal.

[0077] 6. The device displays product information to the user.

[0078] Specific examples

[0079] For example, consider a user searching for "sneakers." When the user types "sneakers" into the device and presses the search button, the following prompt is input to the generative AI model:

[0080] Example prompt sentence:

[0081] A user searches for "sneakers." You want to retrieve sneaker product information from multiple e-commerce platforms and present it to the user. The APIs used are the API of e-commerce platform A, the API of e-commerce platform B, and the API of e-commerce platform C.

[0082] Based on this prompt, the server will do the following:

[0083] 1. Call the API of e-commerce platform A to obtain sneaker product information.

[0084] 2. Call the API of e-commerce platform B to retrieve sneaker product information.

[0085] 3. Call the API of e-commerce platform C to get sneaker product information.

[0086] 4. Aggregate the acquired product information and eliminate duplicates.

[0087] 5. Present aggregated product information to users.

[0088] In this way, users can view sneaker product information aggregated from multiple e-commerce platforms at once.

[0089] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0090] Step 1:

[0091] The user enters a search keyword.

[0092] A user enters a keyword, such as "sneakers," into the device's search bar and presses the search button. The input is the search keyword entered by the user. The output is the search keyword sent to the device.

[0093] Step 2:

[0094] The device sends the search keywords to the server.

[0095] The device sends the search keywords entered by the user to the server. Specifically, the device generates JSON format data including the search keywords and sends it to the server as an HTTP POST request. The input is the search keywords entered by the user. The output is the search keywords sent to the server.

[0096] Step 3:

[0097] The server calls the API of each e-commerce platform.

[0098] Based on the received search keywords, the server calls the APIs of multiple e-commerce platforms to obtain product information. Specifically, the server sends a request including the search keywords to each API and obtains the corresponding product information. The input is the search keywords. The output is the product information obtained from each e-commerce platform.

[0099] Step 4:

[0100] The product information acquired by the server is aggregated.

[0101] The server aggregates the product information obtained from each e-commerce platform and eliminates duplicates. Specifically, it consolidates the obtained product information into a single list and eliminates duplicates. The input is the product information obtained from each e-commerce platform. The output is the aggregated product information with duplicates eliminated.

[0102] Step 5:

[0103] The server transmits the aggregated product information to the terminal.

[0104] The server sends the aggregated product information to the terminal in JSON format. Specifically, it returns data including the product information to the terminal as an HTTP response. The input is the aggregated product information. The output is the product information sent to the terminal.

[0105] Step 6:

[0106] The device displays product information to the user.

[0107] The terminal displays the received product information to the user. Specifically, it displays a product list on the screen and allows the user to check detailed information about each product (price, stock status, product image, etc.). The input is the product information sent from the server. The output is the product information displayed to the user.

[0108] (Application example 1)

[0109] Next, a description will be given of Application Example 1 of Embodiment 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."

[0110] Traditional e-commerce platforms require users to search multiple platforms individually and compare product information, which takes time and effort. Furthermore, the payment solutions and product information formats offered by each platform are different, making it difficult for users to use. Furthermore, the lack of features to filter products based on users' desired criteria and manage purchase history and favorite lists also creates a poor user experience.

[0111] 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.

[0112] In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on user requests, means for linking payment solutions offered in various countries, means for obtaining product information from multiple e-commerce platforms and comparing and displaying information such as price, availability, and reviews, means for providing a filtering function that allows users to set desired conditions, means for managing product purchase history and favorite lists, and means for notifying users of sales information and price fluctuations via push notifications. This allows users to obtain and compare product information from multiple platforms using a single interface, saving time and effort. Furthermore, the unified payment solution and product information format improves usability and enhances the user experience.

[0113] An "e-commerce platform" is an online system for selling and purchasing goods and services over the Internet.

[0114] "Interconnection" refers to the state in which multiple systems or networks can communicate with each other and exchange data.

[0115] A "conversational interface" is a user interface that allows a user to interact with a system using natural language.

[0116] "Natural language processing technology" is a technology that allows computers to understand and process human language.

[0117] "Product recommendation" is a function that suggests appropriate products based on the user's requests and preferences.

[0118] "Payment solutions" are systems and services that enable safe and efficient online payments.

[0119] "Product Information" refers to detailed information necessary for purchasing a product, such as product price, availability, and reviews.

[0120] The "filtering function" is a function that narrows down search results based on the user's desired conditions.

[0121] "Purchase history" is a record of products a user has purchased in the past.

[0122] A "favorites list" is a list for saving products that a user finds interesting.

[0123] "Push notifications" are a feature that allows an application to send information to a user's device in real time.

[0124] "Sale information" is information about product discounts and special prices.

[0125] "Price fluctuation" refers to the change in the price of a product over time.

[0126] The system for implementing this invention interconnects multiple e-commerce platforms to provide users with a consistent shopping experience. The system includes the following major components:

[0127] 1. Means of interconnecting multiple e-commerce platforms:

[0128] The server accesses the APIs of each e-commerce platform to retrieve product information, allowing users to search for product information from multiple platforms through a single interface.

[0129] 2. Means of providing a conversational interface:

[0130] The server uses natural language processing technology to enable interaction with users, who can search for products and ask questions in natural language via their smartphones or other devices.

[0131] 3. A method for recommending multiple products based on user requirements:

[0132] The server analyzes product information obtained from multiple e-commerce platforms based on the user's search query and recommends the most suitable products.

[0133] 4. Means of integrating payment solutions offered in each country:

[0134] The server will integrate payment solutions from each country, allowing users to seamlessly purchase the products they select.

[0135] 5. A way to retrieve product information from multiple e-commerce platforms and compare prices, availability, reviews, etc.:

[0136] The server integrates the acquired product information and displays a comparison of prices, availability, reviews, etc. to the user, allowing the user to select the most suitable product.

[0137] 6. Means of providing filtering functionality that allows users to set desired criteria:

[0138] The server provides the ability for users to filter search results by setting criteria such as price range, brand, size, etc.

[0139] 7. How to manage your purchase history and wish list:

[0140] The server manages the user's purchase history and favorites list, allowing the user to easily check products they have purchased in the past or products they are interested in.

[0141] 8. Push notifications for sales and price changes:

[0142] The server sends push notifications to users' devices to inform them of sales and price changes in real time.

[0143] Hardware and software used

[0144] Hardware: Smartphones, servers

[0145] Software: Python, Flask (web framework), requests (HTTP request library), natural language processing technology (e.g., Google (registered trademark) Cloud Natural Language API)

[0146] Data processing and calculation

[0147] The server receives a search query from the user and sends an HTTP request to the API of each e-commerce platform. The retrieved product information is consolidated within the server, and information such as price, availability, and reviews is displayed for comparison. Search results are narrowed down based on the filtering conditions set by the user. Purchase history and favorites lists are stored in a database, and push notifications are sent to the user's device in real time.

[0148] Specific examples

[0149] When a user searches for "sneakers," the server retrieves product information from multiple e-commerce platforms and displays it as follows:

[0150] Platform 1: Nike Air Max - ¥12,000 - In Stock - 4.5 Review

[0151] Platform 2: Adidas Ultraboost - ¥15,000 - Out of Stock - 4.7 Review

[0152] Platform 3: Puma RS-X - ¥10,000 - In Stock - 4.3 Review

[0153] Prompt Sentence Examples

[0154] "Develop an application that retrieves product information from multiple e-commerce platforms for a user-searched product and displays a comparison of prices, availability, reviews, etc."

[0155] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0156] Step 1:

[0157] A user launches an application on their smartphone and enters a search query (e.g., "sneakers"). The entered search query is sent from the application to a server. The input data is the keyword for the product the user wants to search for. The output data is the search query sent to the server.

[0158] Step 2:

[0159] The server analyzes the received search query and sends HTTP requests to the APIs of multiple e-commerce platforms. The input data is the search query received from the user. The output data is the HTTP requests sent to each e-commerce platform.

[0160] Step 3:

[0161] Each e-commerce platform receives an HTTP request from a server and returns the relevant product information (price, availability, reviews, etc.). The input data is the HTTP request from the server. The output data is the HTTP response containing the product information.

[0162] Step 4:

[0163] The server integrates the product information received from each e-commerce platform and processes the data to compare and display prices, availability, reviews, etc. The input data is the product information received from each e-commerce platform. The output data is the integrated product information.

[0164] Step 5:

[0165] The server returns the integrated product information to the user's smartphone, which the application displays. The input data is the integrated product information sent from the server. The output data is the product information displayed on the user's smartphone.

[0166] Step 6:

[0167] The user sets the desired conditions (price range, brand, size, etc.) based on the displayed product information and performs filtering. The input data are the filtering conditions set by the user. The output data is the filtered product information.

[0168] Step 7:

[0169] The server reprocesses the product information based on the user's filtering conditions and returns the filtered results to the user's smartphone. The input data are the filtering conditions set by the user. The output data is the filtered product information.

[0170] Step 8:

[0171] The user selects the product they wish to purchase and completes the purchase procedure. The server connects with payment solutions provided in each country, enabling the user to smoothly purchase the selected product. The input data is the product selected by the user and payment information. The output data is confirmation that the purchase has been completed.

[0172] Step 9:

[0173] The server stores and manages the user's purchase history and favorites list in a database. The input data is the user's purchase history and favorites list. The output data is the history information stored in the database.

[0174] Step 10:

[0175] The server sends push notifications to users' smartphones when sales information or price fluctuations occur. The input data is sales information or price fluctuation information. The output data is the push notification sent to the user's smartphone.

[0176] Example 2

[0177] Next, a description will be given of Example 2 of Form 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."

[0178] Conventional e-commerce systems require a lot of effort when users search for products, making it difficult to search and purchase efficiently. It is also difficult to integrate multiple e-commerce platforms and provide users with a consistent experience. Furthermore, linking payment solutions offered in each country is complex, making global expansion difficult.

[0179] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions offered in various countries, means for analyzing user input using natural language processing technology, means for inputting prompt sentences to the generative AI model based on the analysis results, and means for presenting responses from the generative AI model to the user. This enables users to search for products in natural language and purchase them efficiently. Furthermore, integrating multiple e-commerce platforms and linking payment solutions from various countries facilitates global expansion.

[0180] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[0181] A "conversational interface" is a user interface that allows a user to interact with a system using natural language.

[0182] A "user request" is a specific request such as a search or purchase that a user makes to the system.

[0183] "Payment Solutions" means payment instruments or systems used to purchase goods and services.

[0184] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language.

[0185] A "generative AI model" is an artificial intelligence model that generates appropriate responses or content based on input data.

[0186] A "prompt sentence" is an instruction sentence input to a generative AI model, and is the sentence that serves as the basis for the model to generate a response.

[0187] "Analysis results" are data obtained after analyzing a user's input using natural language processing techniques.

[0188] A "response" is a reply or result that a generative AI model generates based on a prompt.

[0189] This invention is a system that allows users to search for and purchase products efficiently in natural language. The system interconnects multiple e-commerce platforms, provides a conversational interface, recommends multiple products based on user requests, and integrates payment solutions offered in various countries.

[0190] Hardware and software used

[0191] Hardware:

[0192] High-performance servers (e.g., servers with Intel Xeon processors)

[0193] software:

[0194] Natural language processing libraries (e.g., spaCy, NLTK)

[0195] Database management system (e.g., MySQL®)

[0196] Generative AI models (e.g., GPT-3 (registered trademark))

[0197] Program processing

[0198] When the server receives input from a user, it analyzes the input using a natural language processing library. The analyzed data is input as a prompt sentence to the generative AI model. The generative AI model generates an appropriate response according to the user's request. For example, if a user inputs "I'm looking for red sneakers," the server searches the database using "red sneakers" as a keyword and presents the search results to the user.

[0199] Specific examples

[0200] A specific example is shown below where the user says, "I'm looking for red sneakers."

[0201] User input: "I'm looking for red sneakers"

[0202] Example prompt: "The user is looking for red sneakers. Retrieve a list of red sneakers from the database and generate an appropriate response."

[0203] The server inputs the above prompt sentence into the generative AI model and receives a response from the model. The server then presents the response to the user. For example, it displays the results in the form of "The following red sneakers were found: [Product List]."

[0204] In this way, a system is realized in which the server, terminals, and users work together to support product searches and purchases.

[0205] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0206] Step 1:

[0207] The user inputs in natural language. The user inputs product search and purchase requests in natural language through the terminal interface. For example, the user inputs "I'm looking for red sneakers." The input data is in text format.

[0208] Step 2:

[0209] The terminal sends the user's input to the server. The terminal sends the user's input to the server in real time. The HTTPS protocol is used for transmission to ensure data security. The input is the user's text data, and the output is the data sent to the server.

[0210] Step 3:

[0211] The server parses the input using a natural language processing library. The server parses the received user input using a natural language processing library (e.g., spaCy, NLTK). Parsing includes tokenization, part-of-speech tagging, dependency analysis, etc. The input is the user's text data, and the output is the parsed data.

[0212] Step 4:

[0213] The server generates a prompt sentence based on the analysis results. The server generates a prompt sentence to input to the generative AI model based on the analysis results. For example, a prompt sentence such as "The user is looking for red sneakers. Please retrieve a list of red sneakers from the database and generate an appropriate response" is created. The input is the analysis result data, and the output is the prompt sentence.

[0214] Step 5:

[0215] The server inputs a prompt sentence into the generative AI model. The server inputs the generated prompt sentence into the generative AI model (e.g., GPT-3). The model generates a response based on the prompt sentence. The input is the prompt sentence, and the output is the generated response.

[0216] Step 6:

[0217] The generative AI model generates a response. The generative AI model generates an appropriate response based on the prompt sentence according to the user's request. For example, it generates the response "The following red sneakers were found: [product list]". The input is the prompt sentence, and the output is the generated response.

[0218] Step 7:

[0219] The server receives the generated response and returns it to the user in an appropriate format. The server receives the response from the generative AI model and converts it into an appropriate format to return to the user, for example, formatting the response in HTML. The input is the generated response and the output is the formatted response.

[0220] Step 8:

[0221] The terminal displays the response from the server to the user. The terminal displays the response received from the server to the user. The user checks the displayed results and decides on the next action. The input is the formatted response, and the output is what is displayed to the user.

[0222] (Application example 2)

[0223] Next, a description will be given of Application Example 2 of Form 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."

[0224] Conventional e-commerce platforms require users to go through multiple steps when searching for and purchasing products, making operation cumbersome. Furthermore, the inability to use voice input for searches or purchases resulted in low user convenience. Furthermore, it was difficult to integrate payment solutions offered in each country, making global expansion difficult.

[0225] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0226] In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions offered in various countries, means for receiving voice input and converting the voice to text, means for analyzing the user's intent using natural language processing technology, means for searching a product database based on the analysis results, means for generating a response based on the search results and converting the text to speech, and means for playing the generated speech to the user. This allows users to search for and purchase products through natural conversation, simplifying operation and improving convenience. It also enables the integration of global payment solutions, facilitating international expansion.

[0227] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[0228] A "conversational interface" is a user interface that allows a user to interact with a system using natural language.

[0229] "User requests" are specific instructions or requests, such as searches or purchases, that a user makes to the system.

[0230] "Means for recommending products" is a function for selecting and presenting appropriate products based on the user's requests.

[0231] "Payment solutions" are systems and services used to process payments for the purchase of goods and services.

[0232] "Voice input" refers to voice data uttered by the user through a microphone.

[0233] "Speech-to-text" is the process of analyzing and converting speech data into corresponding text data.

[0234] "Natural language processing technology" is a technology that allows computers to understand and analyze human language.

[0235] "User intent" refers to the goals and desires that users have for the system.

[0236] A "product database" is a database that stores information about products.

[0237] The "means for generating a response" is a function for creating an appropriate reply to a user request.

[0238] "Text-to-speech" is the process of analyzing text data and converting it into corresponding audio data.

[0239] "Generated speech" refers to speech data created by text-to-speech conversion.

[0240] A system for implementing the present invention has the following configuration: a server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions offered in various countries, means for receiving voice input and converting the voice to text, means for analyzing the user's intent using natural language processing technology, means for searching a product database based on the analysis results, means for generating a response based on the search results and converting the text to voice, and means for playing the generated voice to the user.

[0241] Hardware and software used

[0242] Hardware: Smartphone (iOS or ANDROID (registered trademark))

[0243] software:

[0244] Natural language processing libraries (e.g., Google Cloud Natural Language API, spaCy)

[0245] Databases (e.g., Firebase, MongoDB)

[0246] Front-end frameworks (e.g., React Native)

[0247] Backend frameworks (e.g., Node.js, Express)

[0248] Speech recognition API (e.g., Google Cloud Speech-to-Text API)

[0249] Text-to-speech API (e.g., Google Cloud Text-to-Speech API)

[0250] Data processing and calculation

[0251] 1. Acquiring voice input: The user inputs voice using the smartphone microphone. The voice data is sent to the server in real time.

[0252] 2. Speech-to-text conversion: The server converts the speech data into text data using the Google Cloud Speech-to-Text API.

[0253] 3. Natural Language Processing: Text data is parsed using Google Cloud Natural Language API or spaCy to extract user intent.

[0254] 4. Product search: Based on the analysis results, search the product database stored in Firebase or MongoDB.

[0255] 5. Response generation: Based on the search results, a response is generated to present appropriate product information to the user.

[0256] 6. Text-to-Speech Conversion: The generated response is converted into audio data using the Google Cloud Text-to-Speech API.

[0257] 7. Audio playback: The generated audio data is played back to the user through the smartphone speaker.

[0258] Specific examples

[0259] When a user says, "I'm looking for red sneakers," the system processes them as follows:

[0260] 1. Take voice input and convert it to text.

[0261] 2. Analyze the text and extract "red sneakers" as a search keyword.

[0262] 3. Search the database for products that match "red sneakers."

[0263] 4. Based on the search results, generate a response such as "Here are the search results for red sneakers."

[0264] 5. Convert the response into speech and play it back to the user.

[0265] Prompt Sentence Examples

[0266] User: "I'm looking for red sneakers."

[0267] System: "Searching for red sneakers. Please wait."

[0268] System: "Here are the search results for red sneakers. There are Model A from XXXX, Model B from XXX, and so on. Which one would you like?"

[0269] In this way, users can search for and purchase products through natural conversation.

[0270] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0271] Step 1:

[0272] The user inputs voice using the microphone on their smartphone, and the voice data is sent to the server in real time.

[0273] Input: User's voice

[0274] Output: Audio data

[0275] Specific action: The user says, "I'm looking for red sneakers."

[0276] Step 2:

[0277] The server converts the audio data into text data using the Google Cloud Speech-to-Text API.

[0278] Input: Audio data

[0279] Output: Text data

[0280] Specific operation: The server receives the voice data and converts it into text: "I'm looking for red sneakers."

[0281] Step 3:

[0282] The server uses Google Cloud Natural Language API or spaCy to parse the text data and extract the user's intent.

[0283] Input: Text data

[0284] Output: Analysis result (user intent)

[0285] Specific operation: The server analyzes the text data and extracts "red sneakers" as a search keyword.

[0286] Step 4:

[0287] Based on the analysis results, the server searches the product database stored in Firebase or MongoDB.

[0288] Input: Analysis results (search keywords)

[0289] Output: Search results (product information)

[0290] Specific operation: The server searches the database for products that match "red sneakers."

[0291] Step 5:

[0292] The server generates a response based on the search results to present appropriate product information to the user.

[0293] Input: Search results (product information)

[0294] Output: Response text

[0295] What happens: The server generates a response like, "Here are the search results for red sneakers."

[0296] Step 6:

[0297] The server converts the response text into audio data using the Google Cloud Text-to-Speech API.

[0298] Input: Response text

[0299] Output: Audio data

[0300] Specific operation: The server receives the response text and converts it into voice data.

[0301] Step 7:

[0302] The server transmits the generated audio data to the smartphone and plays it back to the user through the smartphone's speaker.

[0303] Input: Audio data

[0304] Output: Audio output

[0305] Specific operation: The smartphone receives the audio data and plays it back to the user.

[0306] Example 3

[0307] Next, a description will be given of a third embodiment of the third embodiment. 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] With conventional e-commerce systems, when users purchase products using their own local payment methods, it is difficult to accommodate the different payment solutions in each country. Furthermore, there is a lack of an interface that allows users to select their preferred payment method and complete the payment smoothly. This leads to a poor user experience and complicated purchasing procedures.

[0309] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0310] In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions offered in each country, means for selecting a corresponding payment module based on the user's country information, means for presenting payment methods to the user through the selected payment module, means for verifying the payment information entered by the user and performing payment processing, and means for sending a payment completion notification to the user, thereby enabling the user to smoothly purchase products using the payment method of their own country.

[0311] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[0312] A "conversational interface" is an interface that allows users to interact with a system using natural language to perform operations and obtain information.

[0313] "Payment Solutions" is a collective term for technologies and services used to process online payments.

[0314] A "payment module" is a software component that implements a particular payment method.

[0315] "User country information" refers to information that identifies the country from which the user is accessing the site, including IP address and user account information.

[0316] "Payment method" refers to the means a user chooses to pay for goods or services, and includes credit cards, bank transfers, electronic money, etc.

[0317] "Payment Information" refers to payment information entered by the user based on the payment method selected, including credit card number and bank account information.

[0318] "Payment processing" refers to a series of operations required to actually complete a payment based on the payment information entered by the user.

[0319] The "payment completion notification" is a message to inform the user that the payment has been successfully completed.

[0320] This invention is a system that allows users to purchase products using their own country's payment method. The system interconnects multiple e-commerce platforms, provides a conversational interface, and recommends multiple products based on the user's request. It also connects payment solutions offered in each country, selects a corresponding payment module based on the user's country information, and presents payment methods to the user through the selected payment module. It also verifies the payment information entered by the user, processes the payment, and notifies the user that the payment has been completed.

[0321] Hardware and software used

[0322] This system uses the following hardware and software:

[0323] Servers: Database servers, web servers, payment gateway servers, etc.

[0324] Devices: PCs, smartphones, tablets, etc. used by users

[0325] Software: Conversational interfaces using natural language processing technology, payment modules, database management systems, middleware for processing API requests, etc.

[0326] Specific examples

[0327] For example, consider a case where a Japanese user purchases a product from an online shop. The user accesses the online shop's website or application and selects the product they wish to purchase. The terminal sends the product information selected by the user and the user's country information to the server. The server analyzes the received country information and selects the payment module corresponding to that country. For a Japanese user, the server selects the credit card, bank transfer, or convenience store payment module.

[0328] The server uses the selected payment module to present the user with available payment methods. The user selects the desired method from the presented payment methods and enters the required information (credit card number, bank account information, etc.). The server verifies the entered payment information and processes the payment. If the payment is successful, the server sends a purchase completion notification to the user. The terminal receives the purchase completion notification from the server and displays it to the user.

[0329] Prompt Sentence Examples

[0330] Please explain the process of the system that allows Japanese users to choose between credit card, bank transfer, and convenience store payment when purchasing products from an online shop.

[0331] In this way, the system allows users to smoothly purchase products using the payment method of their own country. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0332] Step 1:

[0333] The user selects an item and begins the checkout process.

[0334] Input: A user visits an online shopping website or application and selects the product they want to purchase.

[0335] What happens: The user clicks the "Add to Cart" button, then clicks the "Proceed to Checkout" button to begin the purchase process.

[0336] Output: The selected product information (product ID, quantity, price, etc.) is saved to the device.

[0337] Step 2:

[0338] The device sends the product information selected by the user and the user's country information to the server.

[0339] Input: Product information selected by the user and user country information (obtained from IP address and user account information)

[0340] Specific operation: The device uses an HTTP request to send data including product information and country information to the server.

[0341] Output: The server receives the product information and country information.

[0342] Step 3:

[0343] The server selects a corresponding payment module based on the received country information.

[0344] Input: User's country information received by the server

[0345] Specific operation: The server retrieves payment options for the relevant country (credit card, bank transfer, convenience store payment, etc.) from the database.

[0346] Output: The selected payment module information is saved on the server.

[0347] Step 4:

[0348] The server presents the payment method to the user through the selected payment module.

[0349] Input: Information about the payment module selected by the server

[0350] Specific operation: The server generates an HTML form and displays a screen for the user to enter credit card information and instructions for bank transfer.

[0351] Output: The user is presented with the available payment methods.

[0352] Step 5:

[0353] The user selects the desired payment method from the options presented and enters the required information.

[0354] Input: The payment method selected by the user and any required information (credit card number, bank account information, etc.)

[0355] Specific behavior: The user enters their credit card information and clicks the "Pay" button.

[0356] Output: The entered payment information is saved on the device and sent to the server.

[0357] Step 6:

[0358] The server verifies the entered payment information and processes the payment.

[0359] Input: Payment information entered by the user

[0360] Specific behavior: The server sends an API request to the payment gateway (e.g., payment service provider) to receive authorization for the payment.

[0361] Output: The result of the payment (success or failure) is returned to the server.

[0362] Step 7:

[0363] The server sends a notification to the user that the purchase is complete.

[0364] Input: Payment result if payment is successful

[0365] Specific behavior: The server generates a response containing the message "Purchase completed" and sends it to the user's device.

[0366] Output: A notification of successful purchase is sent to the user's device.

[0367] Step 8:

[0368] The device receives a purchase completion notification from the server and displays it to the user.

[0369] Input: Purchase completion notification sent from the server

[0370] What happens: The device displays the message "Purchase complete" on the screen.

[0371] Output: The user sees a message confirming the purchase.

[0372] (Application example 3)

[0373] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0374] With conventional e-commerce systems, when users purchase products using their own country's payment method, it is difficult to support different payment solutions in each country. In addition, it is time-consuming for users to select the appropriate payment option when purchasing a product, and there are delays in confirmation notifications after payment is completed. This creates an issue that impairs the user experience.

[0375] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions offered in each country, means for displaying appropriate payment options based on the user's country information, means for processing payment using the selected payment option, and means for sending a confirmation notice after payment is completed. As a result, when a user purchases a product using the payment method of their home country, appropriate payment options are automatically displayed, enabling the user to complete payment quickly and reliably.

[0376] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[0377] A "conversational interface" is a user interface that allows a user to interact with a system using natural language.

[0378] "User requests" refer to operations or instructions that users give to the system, such as product searches or purchases.

[0379] "Product recommendation means" refers to algorithms or systems that present appropriate products based on the user's requests and past behavioral history.

[0380] "Payment Solution" means a method or system for making payments for the purchase of goods or services.

[0381] "Payment Options" means the payment methods that users can choose when purchasing goods or services.

[0382] "Payment processing" refers to the series of steps taken to actually complete a payment using the payment option selected by the user.

[0383] A "confirmation notice" is a message or notification that informs the user that a payment has been completed.

[0384] "Natural language processing technology" is a technology that enables computers to understand and generate human language.

[0385] A "globally deployable structure" refers to a system that is designed and structured so that it can be used in multiple countries and regions and can meet the different requirements of each country.

[0386] As an embodiment of the present invention, the following system is constructed.

[0387] First, the server interconnects multiple e-commerce platforms, allowing users to search and purchase products from multiple platforms through a single interface.

[0388] The server then provides a conversational interface that uses natural language processing technology to allow users to search for products and ask questions in natural language. For example, if a user types, "I'm looking for the latest smartphone," the system will recommend suitable products.

[0389] Furthermore, the server recommends multiple products based on the user's request, using an algorithm that analyzes the user's past purchase and search history, thereby recommending the most suitable products for the user.

[0390] To integrate payment solutions offered in each country, the server displays appropriate payment options based on the user's country information. For example, a user in Japan will see options such as credit card, bank transfer, and convenience store payment.

[0391] To process the payment using the user's selected payment option, our server uses a payment API (e.g., Stripe, PayPal API), ensuring that the payment is completed quickly and securely using the payment method of your choice.

[0392] After the payment is completed, the server will send a confirmation to the user, so that the user can be sure that the payment was successfully completed.

[0393] As a concrete example, consider a user in Japan purchasing a product using a "Global Payment Assistant" app. The user opens the app, searches for a product, and a conversational interface responds in natural language. After the user selects a product and proceeds with the purchase, the server automatically displays Japanese payment options. After the user selects a credit card and completes the payment, a confirmation notification is sent.

[0394] An example of a prompt to be input to the generative AI model is, "When a Japanese user purchases a product, please generate a Python program that displays the options of credit card, bank transfer, and convenience store payment, and makes the payment using the selected option."

[0395] The above is an embodiment of the present invention.

[0396] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0397] Step 1:

[0398] The server recognizes the e-commerce platform accessed by the user and interconnects multiple platforms. It receives the user's access information as input and generates a list of platforms available to the user as output. Specifically, the server calls the API of each platform to obtain product data.

[0399] Step 2:

[0400] The server provides a conversational interface, receiving as input the user's natural language questions and requests, and generating appropriate responses and product recommendations as output. Specifically, the server uses natural language processing techniques to analyze the user's input and retrieve relevant product information.

[0401] Step 3:

[0402] The server recommends multiple products based on the user's request. It receives the user's search history and purchase history as input and generates a list of recommended products as output. Specifically, the server uses a machine learning algorithm to analyze the user's preferences and select the most suitable products.

[0403] Step 4:

[0404] The server connects payment solutions offered in each country. It receives the user's country information as input and displays the payment options corresponding to that country as output. Specifically, the server obtains the country information from the user's IP address and account information and lists the corresponding payment options.

[0405] Step 5:

[0406] The server processes the payment using the payment option selected by the user. As input, it receives the payment option selected by the user and payment information, and as output, it generates a payment completion status. Specifically, the server calls a payment API (e.g., Stripe, PayPal API) and executes the payment process.

[0407] Step 6:

[0408] The server sends a confirmation notice to the user after the payment is completed. It receives the payment completion status as input, generates a confirmation notice as output, and sends it to the user. Specifically, the server sends the payment completion information to the user via email or push notification.

[0409] The above are the specific processing steps for carrying out the present invention.

[0410] 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.

[0411] "Example 1"

[0412] One embodiment of the present invention provides a system incorporating an emotion engine. This system analyzes emotions from a user's text or voice input and recommends products based on the results. Specifically, if a user inputs the text "I'm tired today," the emotion engine recognizes from this text that the user is tired and recommends products with a relaxation effect, such as aroma candles or bath salts.

[0413] "Example 2"

[0414] The emotion engine also has the ability to change the interface display according to the user's emotions. For example, if the user enters text that indicates joy, the interface will change to a brighter color scheme and a positive message will be displayed. Conversely, if the user enters text that indicates sadness, the interface will change to a calmer color scheme and a comforting message will be displayed. This allows the system to respond appropriately to the user's emotions.

[0415] "Example 3"

[0416] One embodiment of the present invention provides a system incorporating an emotion engine. This system analyzes emotions from a user's text or voice input and recommends products based on the results. Specifically, if a user inputs the text "I'm tired today," the emotion engine recognizes from this text that the user is tired and recommends products with a relaxation effect, such as aroma candles or bath salts.

[0417] The processing flow of each embodiment will be described below.

[0418] "Example 1"

[0419] Step 1: The user enters text or voice input into the system.

[0420] Step 2: The emotion engine analyzes the emotion from the user's input.

[0421] Step 3: The system recommends products based on the analysis results. For example, if a user enters the text "I'm tired today," the emotion engine will recognize that the user is tired and recommend products with a relaxation effect, such as aroma candles or bath salts.

[0422] "Example 2"

[0423] Step 1: The user enters text or voice input into the system.

[0424] Step 2: The emotion engine analyzes the emotion from the user's input.

[0425] Step 3: Based on the analysis results, the system changes the interface display. For example, if the user enters text that indicates the emotion of joy, the interface will change to a brighter color scheme and display a positive message. Conversely, if the user enters text that indicates the emotion of sadness, the interface will change to a calmer color scheme and display a comforting message.

[0426] Example 1

[0427] Next, a description will be given of Example 1 of Form 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."

[0428] Conventional e-commerce systems face the problem of integrating multiple e-commerce platforms to provide product information, resulting in the time-consuming task of users searching across multiple platforms. Furthermore, product recommendations are not based on user sentiment, meaning that product suggestions cannot be tailored to the user's needs. Furthermore, it is difficult to integrate the different payment solutions offered in each country, limiting global expansion.

[0429] 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.

[0430] In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on user requests, means for linking payment solutions offered in various countries, means for analyzing user sentiment, and means for recommending products based on the results of the sentiment analysis. This allows users to obtain product information from multiple platforms through a single interface and receive product recommendations based on their sentiment. Furthermore, integrating different payment solutions facilitates global expansion.

[0431] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[0432] "Means of interconnection" refers to technologies and methods that link multiple systems and platforms and enable data exchange.

[0433] A "conversational interface" is a user interface that allows a user to interact with a system using natural language.

[0434] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language.

[0435] A "user request" is an action such as a search or inquiry that a user takes on the system.

[0436] "Means for recommending products" refers to technologies and methods for selecting and presenting appropriate products based on the user's requests and preferences.

[0437] "Payment solutions" are systems and services that enable online payments.

[0438] "Means for analyzing emotions" refers to technologies and methods for reading and analyzing emotions from a user's text or voice.

[0439] "Emotion analysis results" are information about the user's emotional state obtained by emotion analysis means.

[0440] A "globally deployable structure" is a design and structure that allows the system to be applied and operated in different countries and regions.

[0441] MODE FOR CARRYING OUT THE INVENTION

[0442] The present invention is a system that interconnects multiple e-commerce platforms, acquires product information based on user requests, and recommends products based on sentiment analysis. This system is designed to improve user convenience and realize more personalized product recommendations.

[0443] System configuration

[0444] 1. Hardware and Software Configuration

[0445] The server has an interface for accessing the APIs of multiple e-commerce platforms (e.g., online marketplaces and shopping sites).

[0446] The device provides the interface through which the user enters search queries or text and can be a smartphone, tablet, PC, etc.

[0447] The emotion engine is software that analyzes emotions from user text and voice input. Specifically, it uses IBM Watson (registered trademark) or Google Cloud Natural Language API.

[0448] 2. Data processing and calculation

[0449] When the server receives a user's search query, it calls the APIs of multiple e-commerce platforms to obtain related product information, which is then sent to the terminal in JSON format.

[0450] The terminal parses the received JSON data and displays it as a product list on the user interface.

[0451] When the server receives the user's text input, it uses an emotion engine to analyze the user's emotions. Based on the analysis results, it selects products with a relaxation effect and sends recommended product information to the device.

[0452] The terminal analyzes the received recommended product information and displays it as recommended products on the user interface.

[0453] Specific examples

[0454] 1. Obtaining product information in response to a user's search request

[0455] A user types "sneakers" into the device's search bar.

[0456] The device sends the search query "sneakers" to the server.

[0457] The server accesses product databases of multiple e-commerce platforms to obtain product information about sneakers.

[0458] The server transmits the acquired product information to the terminal, and the terminal displays the product information to the user.

[0459] 2. Product Recommendation Based on Sentiment Analysis

[0460] The user types "I'm tired today" into the text input field.

[0461] The terminal sends the entered text to the server.

[0462] The server analyzes the emotions using an emotion engine.

[0463] The server recommends products with a relaxation effect based on the analysis results.

[0464] The server transmits the recommended product information to the terminal, and the terminal displays the recommended product information to the user.

[0465] Prompt Sentence Examples

[0466] "When a user searches for 'sneakers', generate a program that retrieves sneaker product information from multiple e-commerce platforms and presents it to the user."

[0467] "If a user types, 'I feel tired today,' use an emotion engine to analyze the user's emotions and generate a program that recommends products that have a relaxation effect."

[0468] This concludes the description of an embodiment of the present invention. This system allows users to access product information from multiple platforms through a single interface and receive emotion-based product recommendations. Furthermore, by integrating different payment solutions, global expansion becomes easier.

[0469] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0470] Program processing flow

[0471] Obtaining product information in response to a user's search request

[0472] Step 1:

[0473] A user types "sneakers" into the device's search bar.

[0474] Input: The user enters the search query "sneakers"

[0475] What happens: A user opens a browser on their smartphone or PC and types "sneakers" into the search bar.

[0476] Step 2:

[0477] The device sends the search query "sneakers" to the server.

[0478] Input: User entered search query "sneakers"

[0479] Output: HTTP request sent to the server

[0480] Specific operation: The device generates an HTTP request and sends it to the server.

[0481] Step 3:

[0482] The server accesses product databases of multiple e-commerce platforms to obtain product information about sneakers.

[0483] Input: Search query "sneakers" received from the device

[0484] Output: Product information obtained from each e-commerce platform

[0485] Specific operation: The server calls the API of each e-commerce platform to obtain product data.

[0486] Step 4:

[0487] The server transmits the acquired product information to the terminal.

[0488] Input: Product information obtained from each e-commerce platform

[0489] Output: JSON format data sent to the device

[0490] Specific operation: The server converts the acquired data into JSON format and sends it to the terminal.

[0491] Step 5:

[0492] The device displays product information to the user.

[0493] Input: JSON format data received from the server

[0494] Output: A list of products displayed in the user interface

[0495] Specific operation: The device parses the received JSON data and displays it as a product list in the user interface.

[0496] Product recommendation based on sentiment analysis

[0497] Step 1:

[0498] The user types "I'm tired today" into the text input field.

[0499] Input: User-entered text: "I'm tired today"

[0500] Specific action: The user types "I'm tired today" into the text input field on their smartphone or PC.

[0501] Step 2:

[0502] The terminal sends the entered text to the server.

[0503] Input: User-entered text: "I'm tired today"

[0504] Output: HTTP request sent to the server

[0505] Specific operation: The device generates an HTTP request and sends it to the server.

[0506] Step 3:

[0507] The server analyzes the emotions using an emotion engine.

[0508] Input: Text received from device: "I'm tired today"

[0509] Output: Sentiment analysis result (e.g., fatigue)

[0510] Specific operation: The server calls the emotion engine API and analyzes the text "I'm tired today."

[0511] Step 4:

[0512] The server recommends products with a relaxation effect based on the analysis results.

[0513] Input: Sentiment analysis result (e.g., fatigue)

[0514] Output: Recommended product information (e.g., aroma candles, bath salts)

[0515] Specific operation: Based on the analysis results, the server selects products with a relaxation effect.

[0516] Step 5:

[0517] The server transmits recommended product information to the terminal.

[0518] Input: Recommended product information (e.g., aroma candle, bath salt)

[0519] Output: JSON format data sent to the device

[0520] Specific operation: The server converts the recommended product information into JSON format and sends it to the terminal.

[0521] Step 6:

[0522] The device displays recommended product information to the user.

[0523] Input: JSON format data received from the server

[0524] Output: Recommendations displayed in the user interface

[0525] Specific operation: The device parses the received JSON data and displays it as recommended products in the user interface.

[0526] (Application example 1)

[0527] Next, a description will be given of Application Example 1 of Embodiment 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."

[0528] Conventional e-commerce systems are inefficient because users must search multiple e-commerce platforms individually. Furthermore, product recommendations do not take into account the user's emotional state, resulting in low user satisfaction. Furthermore, it is difficult to integrate payment solutions offered in each country, making global expansion difficult.

[0529] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions offered in various countries, means for analyzing the user's emotions, and means for recommending products based on the results of the emotion analysis. This allows users to obtain product information from multiple platforms through a single interface and receive product recommendations based on their emotional state. Furthermore, linking global payment solutions enables smooth international transactions.

[0530] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[0531] A "conversational interface" is a user interface that allows a user to interact with a system using natural language.

[0532] "User requests" refer to search keywords and desired product information that users input into the system.

[0533] "Means for recommending products" is a function for presenting appropriate products to users based on the results of user requests and sentiment analysis.

[0534] "Payment Solutions" means technologies and services that enable online payments.

[0535] "Means for analyzing emotions" refers to technology that analyzes emotions from a user's text or voice input and determines their emotional state.

[0536] "Results of emotion analysis" refers to the determination of an emotional state obtained from a user's input.

[0537] The system for implementing this invention interconnects multiple e-commerce platforms, obtains product information based on user requests, and recommends products based on sentiment analysis. A specific embodiment of this system is described below.

[0538] System Configuration

[0539] The server includes the following means:

[0540] 1. E-commerce platform interconnection means: Access the APIs of multiple e-commerce platforms to obtain product information.

[0541] 2. Conversational interface provision: Enables dialogue with users using natural language processing technology.

[0542] 3. Product recommendation means: Recommend multiple products based on user requirements.

[0543] 4. Payment solution integration: Integrate payment solutions offered in each country.

[0544] 5. Sentiment analysis means: Analyzes emotions from the user's text or voice input.

[0545] 6. Product recommendation method based on the results of sentiment analysis: Recommend products based on the results of sentiment analysis.

[0546] Hardware and software used

[0547] Hardware: Servers, smartphones

[0548] Software: Python, requests library, TextBlob library

[0549] Data processing and calculation

[0550] 1. Data Acquisition:

[0551] The server accesses the API endpoint of the e-commerce platform and retrieves product information based on the specified keywords.

[0552] The acquired product information is integrated in the server and provided to the user.

[0553] 2. Emotion analysis:

[0554] The server analyzes the user's input text and classifies the sentiment as positive, negative, or neutral.

[0555] This analysis uses the TextBlob library.

[0556] 3. Product recommendation:

[0557] The server recommends products based on the results of emotion analysis. If the emotion is negative, it will recommend additional products with a relaxation effect.

[0558] Specific examples

[0559] If a user types into their smartphone, "I'm tired today, I want some new sneakers," the server does the following:

[0560] 1. Obtain product information for "sneakers" from an e-commerce platform.

[0561] 2. Analyze the negative emotion "tired" from the user's input text.

[0562] 3. In addition to product information about sneakers, recommend products with a relaxation effect (e.g., aroma candles and bath salts).

[0563] Prompt Sentence Examples

[0564] If a user types, "I'm tired today, I want new sneakers," perform sentiment analysis and, if negative sentiment is detected, recommend products that have a relaxation effect.

[0565] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0566] Step 1:

[0567] A user inputs a product search request into a smartphone terminal. For example, the user inputs, "I'm tired today, I want new sneakers." This input is sent to the server in text format.

[0568] Step 2:

[0569] The server receives the user's input text and analyzes it using natural language processing techniques. Specifically, it segments the input text and extracts keywords (in this case, "sneakers") and emotional expressions (in this case, "tired"). The input is the user's text, and the output is keywords and emotional expressions.

[0570] Step 3:

[0571] The server accesses the APIs of multiple e-commerce platforms and retrieves product information based on the extracted keywords. For example, it retrieves product information related to "sneakers" from each platform. The input is the keywords, and the output is a list of product information.

[0572] Step 4:

[0573] The server analyzes the user's emotional expressions using an emotion analysis tool. Specifically, it uses the TextBlob library to classify emotions as positive, negative, or neutral. The input is the emotional expression, and the output is the emotional classification result.

[0574] Step 5:

[0575] The server recommends products based on the results of sentiment analysis. If negative sentiment is detected, it recommends additional products with a relaxation effect (e.g., aroma candles or bath salts). The input is the sentiment classification result and a list of product information, and the output is the final list of recommended products.

[0576] Step 6:

[0577] The server sends the final recommended product list to the user's smartphone. The user can then check the recommended products on their smartphone and consider purchasing them. The input is the recommended product list, and the output is the product information displayed on the user's smartphone.

[0578] Example 2

[0579] Next, a description will be given of Example 2 of Form 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."

[0580] With conventional e-commerce systems, it was difficult for users to quickly find the right product when searching for it in natural language. Furthermore, the interface display did not change based on the user's emotions, resulting in a uniform user experience that was unable to respond to individual user emotions. Furthermore, it was difficult to interconnect multiple e-commerce platforms and link payment solutions across countries, making global expansion difficult.

[0581] 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.

[0582] In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions offered in various countries, means for analyzing user input using natural language processing technology, means for searching for products based on the analysis results, means for analyzing user sentiment, and means for changing the interface display based on the analysis results. This makes it easier for users to search for products in natural language and enables the interface display to be changed according to sentiment. Furthermore, interconnecting multiple e-commerce platforms and linking payment solutions in various countries facilitates global expansion.

[0583] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[0584] A "conversational interface" is a user interface that allows a user to interact with a system using natural language.

[0585] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language.

[0586] "Sentiment analysis" is a technology that detects emotions from user input text and evaluates the type and intensity of those emotions.

[0587] "Payment Solutions" are systems and services for processing online payments.

[0588] "Interface display change" refers to dynamically changing the appearance and content of the user interface in response to the user's emotions and behavior.

[0589] "Product recommendation" is a function that suggests appropriate products based on the user's requests and behavior.

[0590] "Interconnection" refers to linking multiple systems and platforms so that they can share data and functions.

[0591] The present invention relates to an electronic commerce system that allows users to search for products in natural language and change the interface display according to their emotions. Specific embodiments of this system are described below.

[0592] Hardware and software used

[0593] Hardware: Servers, user devices (PCs, smartphones, etc.)

[0594] Software: Natural language processing libraries (e.g., spaCy, NLTK), sentiment analysis libraries (e.g., TextBlob, VADER), databases (e.g., MySQL, MongoDB)

[0595] System configuration

[0596] 1. User Input

[0597] Users use the terminal to input product search and purchase requests in natural language.

[0598] Example: A user types, "I'm looking for red sneakers."

[0599] 2. Natural Language Processing

[0600] The server uses a natural language processing library to parse the user's input.

[0601] The keyword "red sneakers" is extracted from the analysis results.

[0602] 3. Product Search

[0603] The server connects to a database and searches for products based on the extracted keywords.

[0604] Present search results to the user.

[0605] Example: A search for "red sneakers" results in a list of multiple red sneakers.

[0606] 4. Sentiment analysis

[0607] The server uses a sentiment analysis library to analyze the sentiment of the user's input text.

[0608] Example: Detecting the emotion of joy when a user types, "I love these sneakers!"

[0609] 5. Changes to the interface display

[0610] The server uses an emotion engine to change the interface display based on the analysis results.

[0611] Example: If the emotion of joy is detected, the interface changes to a brighter color scheme and displays a positive message such as "Great choice!" Conversely, if the emotion of sadness is detected, the interface changes to a more subdued color scheme and displays a comforting message such as "Cheer up!"

[0612] Specific examples

[0613] User input: "I'm looking for red sneakers"

[0614] System response: "Here are your search results for red sneakers." (Displays a list of search results)

[0615] Example of sentiment analysis: "I love these sneakers!" (detects the emotion of happiness)

[0616] Interface changes: Lighter colors and a "Great Choice!" message

[0617] Prompt Sentence Examples

[0618] "I'm looking for red sneakers."

[0619] "I love these sneakers!"

[0620] "I've been feeling depressed lately"

[0621] This will allow users to easily search for products in natural language, enable the interface to change based on emotions, and facilitate global expansion by interconnecting multiple e-commerce platforms and integrating payment solutions across countries.

[0622] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0623] Step 1:

[0624] User Input

[0625] How it works: A user uses a device to input a product search or purchase request in natural language.

[0626] Input: User types "I'm looking for red sneakers."

[0627] Output: The user's input text is sent to the server.

[0628] Step 2:

[0629] Natural Language Processing

[0630] How it works: The server uses a natural language processing library (e.g., spaCy, NLTK) to parse the user's input text.

[0631] Input: User input text "I'm looking for red sneakers"

[0632] Data processing: Perform text analysis to extract the keyword "red sneakers."

[0633] Output: Extracted keyword "red sneakers"

[0634] Step 3:

[0635] Product search

[0636] How it works: The server connects to a database (e.g. MySQL, MongoDB) and searches for products based on the extracted keywords.

[0637] Input: Extracted keyword "red sneakers"

[0638] Data operation: Execute the following query against the database: SELECT FROM products WHERE color='red' AND category='sneakers'.

[0639] Output: A list of matching products (e.g., multiple red sneakers)

[0640] Step 4:

[0641] Presenting search results

[0642] Action: The server presents the search results to the user.

[0643] Input: List of applicable products

[0644] Output: Search results are displayed on the user's device.

[0645] What happens: The user's device will display a list of red sneakers along with the message, "Here are your search results for red sneakers."

[0646] Step 5:

[0647] sentiment analysis

[0648] How it works: The server uses a sentiment analysis library (e.g. TextBlob, VADER) to analyze the sentiment of the user's input text.

[0649] Input: User input text: "I love these sneakers!"

[0650] Data calculation: Calculate sentiment scores and detect positive sentiment.

[0651] Output: Detected emotion (e.g., joy)

[0652] Step 6:

[0653] Interface display changes

[0654] How it works: The server uses the emotion engine to change the interface display based on the analysis results.

[0655] Input: Detected emotion (e.g., joy)

[0656] What it does: It modifies the interface CSS to set the background color to a lighter shade and displays a positive message: "Great choice!"

[0657] Output: The modified interface is displayed on the user's terminal.

[0658] The above is the specific processing flow of the program of this system.

[0659] (Application example 2)

[0660] Next, a description will be given of Application Example 2 of Form 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."

[0661] On conventional e-commerce platforms, it was difficult for users to use natural language when searching for products, and the interface did not change in response to user sentiment, resulting in a limited user experience. Furthermore, it was difficult to interconnect multiple e-commerce platforms and integrate payment solutions offered in each region. This created challenges that made it difficult for users to search for and purchase products comfortably and efficiently.

[0662] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0663] In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions provided in each region, means for changing the interface display in response to the user's emotions, means for enabling dialogue with the user using natural language processing technology, means for analyzing the user's emotions using emotion analysis technology, and means for changing the color tone and messages of the interface based on the analysis results. This not only enables users to search for and purchase products in natural language, but also enables a more comfortable and personalized user experience by changing the interface in response to emotions.

[0664] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[0665] A "conversational interface" is a user interface that allows a user to interact with a system using natural language.

[0666] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language.

[0667] "Sentiment analysis technology" is a technology that analyzes emotions from a user's text or voice and identifies their emotional state.

[0668] "Payment solutions" are systems and services that enable safe and efficient online payments.

[0669] "Means for changing the interface display" refers to a function that dynamically changes the color tone and messages of the user interface according to the user's emotions and behavior.

[0670] "Product recommendation means" is a function that presents appropriate products based on the user's requests and past behavior.

[0671] "Means of interconnection" refers to technology that connects multiple systems and platforms and allows them to share data and functions.

[0672] "Means for changing the color tone and messages of the interface based on the analysis results" refers to a function that dynamically changes the appearance and display content of the user interface based on the results of sentiment analysis.

[0673] A system for carrying out the present invention has the following configuration: the system includes means for interconnecting a plurality of e-commerce platforms, means for providing a conversational interface, means for recommending a plurality of products based on a user's request, means for linking payment solutions provided in each region, means for changing the display of the interface in accordance with the user's emotions, means for enabling dialogue with the user using natural language processing technology, means for analyzing the user's emotions using emotion analysis technology, and means for changing the color tone and messages of the interface based on the analysis results.

[0674] Hardware and software used

[0675] Hardware: Smartphone (iOS or Android)

[0676] software:

[0677] Natural language processing libraries (e.g., Google Cloud Natural Language API)

[0678] Sentiment analysis library (e.g. IBM Watson Tone Analyzer)

[0679] Front-end frameworks (e.g., React Native)

[0680] Backend server (e.g. Node.js)

[0681] Program processing explanation

[0682] 1. Getting user input:

[0683] Users input product search and purchase requests in natural language through a smartphone application.

[0684] Example: "I'm looking for red sneakers."

[0685] 2. Natural Language Processing:

[0686] The server analyzes the input text using the Google Cloud Natural Language API and extracts keywords.

[0687] Example: Keyword "red sneakers"

[0688] 3. Sentiment analysis:

[0689] The server uses IBM Watson Tone Analyzer to analyze emotions from the user's input text.

[0690] Example: Emotion "joy"

[0691] 4. Product Search:

[0692] The server uses the extracted keywords to search the product database on the backend server (Node.js).

[0693] Example: Get search results for red sneakers

[0694] 5. Interface changes:

[0695] The server uses React Native to change the interface color tone and messages based on the results of the sentiment analysis.

[0696] For example, for the emotion of joy, bright colors and positive messages are displayed.

[0697] 6. Displaying the results:

[0698] The server displays search results and an emotionally appropriate interface to the user.

[0699] Example: A list of red sneakers and a brightly colored interface

[0700] Specific examples

[0701] When a user types "I'm looking for red sneakers," the server uses the Google Cloud Natural Language API to extract the keyword "red sneakers," analyzes the user's emotion as "joy" using IBM Watson Tone Analyzer, searches for red sneakers on a Node.js server, and displays the search results in a brightly colored interface using React Native.

[0702] Prompt Sentence Examples

[0703] "I'm looking for red sneakers."

[0704] "I want a new smartphone"

[0705] "I'm not feeling very well today"

[0706] In this way, not only can users search and purchase products in natural language, but the interface changes according to emotions, enabling a more comfortable and personalized user experience.

[0707] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0708] Step 1:

[0709] Users input product search and purchase requests in natural language through a smartphone application.

[0710] Input: User's natural language text input (e.g., "I'm looking for red sneakers")

[0711] Output: User input text data

[0712] Step 2:

[0713] The server receives the user's input text data and analyzes it using the Google Cloud Natural Language API.

[0714] Input: User-entered text data

[0715] Data processing: Analyze text using natural language processing techniques and extract keywords (e.g., "red sneakers")

[0716] Output: Extracted keywords

[0717] Step 3:

[0718] The server uses the extracted keywords to search the product database.

[0719] Input: Extracted keywords (e.g. "red sneakers")

[0720] Data calculation: Perform keyword search on product database

[0721] Output: Product list as search results

[0722] Step 4:

[0723] The server performs sentiment analysis on the user's input text data using IBM Watson Tone Analyzer.

[0724] Input: User-entered text data

[0725] Data processing: Using sentiment analysis techniques to analyze emotions from text (e.g., "joy")

[0726] Output: Parsed emotion data

[0727] Step 5:

[0728] The server uses React Native to change the interface color tone and messages based on the results of the sentiment analysis.

[0729] Input: Parsed emotion data (e.g., "joy")

[0730] Data calculation: Determines the color tone and message of the interface according to emotions

[0731] Output: Changed interface configuration

[0732] Step 6:

[0733] The server sends the search results and the changed interface settings to the user's smartphone for display.

[0734] Input: Product list as search result, modified interface settings

[0735] Specific operation: Sends and displays the product list and interface settings to the user's smartphone.

[0736] Output: Product list and interface displayed on the user's smartphone

[0737] In this way, users can not only search and purchase products in natural language, but also enjoy a more comfortable and personalized user experience through interface changes based on emotions.

[0738] Example 3

[0739] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0740] Traditional e-commerce systems have had issues with users having to go through the hassle of using payment methods in different countries and not being able to recommend products based on user sentiment. Furthermore, integrating payment solutions from different countries is difficult when expanding globally, resulting in an inconsistent user experience.

[0741] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0742] In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions provided in each country, means for analyzing emotions from user input data, and means for recommending products based on the analysis results. This not only allows users to easily use payment methods in their own country, but also enables product recommendations based on user emotions, making it possible to provide a globally consistent user experience.

[0743] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[0744] A "conversational interface" is an interface that allows a user to interact with a system using natural language.

[0745] A "payment solution" is a method or system for making payments for the purchase of goods or services.

[0746] "Emotion analysis methods" are technologies and algorithms used to identify emotions from user input data (text or voice).

[0747] A "means for recommending products" is a system for selecting and presenting appropriate products based on the user's needs and emotions.

[0748] "Natural language processing technology" is a technology that allows computers to understand and process human language.

[0749] A "globally deployable structure" is a system design and structure that can be used consistently in different countries and regions.

[0750] MODE FOR CARRYING OUT THE INVENTION

[0751] This invention is a system that interconnects multiple e-commerce platforms, provides a conversational interface, recommends products based on user requests, and connects payment solutions offered in each country. It also includes a function to analyze emotions from user input data and recommend products based on the analysis results. The multiple e-commerce platforms are e-commerce platforms offered across different countries and regions.

[0752] Hardware and software used

[0753] The system uses the following hardware and software:

[0754] Server: Manages the entire system and processes data. A server with a high-performance processor and large memory capacity is recommended.

[0755] Device: The device from which the user accesses the site, including computers, smartphones, tablets, etc.

[0756] Natural language processing engine: Software used to analyze user text and voice input. For example, Google Cloud Natural Language API or IBM Watson Natural Language Understanding can be used.

[0757] Payment module: Software to support local payment solutions, such as PayPal, Stripe, and Square.

[0758] Sentiment analysis engine: Software for analyzing user sentiment. For example, Microsoft® Azure® Text Analytics or Amazon Comprehend can be used.

[0759] Specific operation of the system

[0760] 1. The user selects a product and begins the purchase process. The user selects a product on a website or application and clicks the "Buy" button.

[0761] 2. The server determines the user's country and displays the available payment methods. The server determines the user's country from their IP address and account information, and displays the payment methods available in that country (e.g., credit card, bank transfer, convenience store payment).

[0762] 3. The user selects the desired payment method. The user selects the desired payment method from the displayed payment methods and clicks the "Next" button.

[0763] 4. The server calls the payment module corresponding to the selected payment method. The server calls the payment module corresponding to the selected payment method (e.g., credit card payment module).

[0764] 5. The server sends the payment information to the payment module and processes the payment. The server sends the user's payment information (e.g., credit card number, amount) to the payment module and processes the payment.

[0765] 6. The server receives the payment result (success / failure) from the payment module and notifies the user. If successful, a message indicating purchase completion is displayed.

[0766] Specific operation of a system incorporating an emotion engine

[0767] 1. The user enters text or speaks into the app. The user enters text into the app or website, or speaks into the app using a microphone.

[0768] 2. The server receives the input data and sends it to the emotion engine. The server receives the user's input data (text or voice data) and sends it to the emotion engine.

[0769] 3. The emotion engine analyzes emotions from the input data. The emotion engine uses natural language processing technology to analyze the input data and identify the user's emotions (e.g., fatigue, joy, sadness).

[0770] 4. The server recommends products based on the analysis results. The server receives the analysis results from the emotion engine and selects products that suit the emotion (e.g., products with a relaxation effect). In other words, the server searches for products taking into account the recognized emotional state of the user.

[0771] 5. The server displays the recommended products to the user. The server displays the selected recommended products to the user and encourages them to purchase.

[0772] Prompt Sentence Examples

[0773] An example prompt for a generative AI model would be:

[0774] "Please explain the payment process when a Japanese user purchases a product with a credit card."

[0775] "If a user types, 'I'm tired today,' how would the emotion engine analyze that emotion and recommend products to them?"

[0776] By using these prompt sentences, the generative AI model can explain the specific processing content of the system in natural language. The flow of the specific processing in Example 3 will be explained with reference to FIG.

[0777] Processing steps for payment solution linked system

[0778] Step 1:

[0779] The user selects a product and begins the checkout process.

[0780] Input: A user selects an item on a website or application and clicks a "Buy" button.

[0781] Output: The information about the selected product is sent to the server.

[0782] Specific operation: The user selects the desired product from the product list page, proceeds to the product details page, and then clicks the "Purchase" button to begin the purchase process.

[0783] Step 2:

[0784] The server determines the user's country and displays the corresponding payment methods.

[0785] Input: User's IP address and account information.

[0786] Output: A list of payment methods for the user's country.

[0787] Specific operation: The server analyzes the user's IP address and account information to identify the user's country, and then displays the payment methods available in that country (e.g., credit card, bank transfer, convenience store payment).

[0788] Step 3:

[0789] The user selects the desired payment method.

[0790] Input: A list of displayed payment methods.

[0791] Output: The selected payment method information is sent to the server.

[0792] Specific operation: The user selects the desired payment method from the displayed options and clicks the "Next" button.

[0793] Step 4:

[0794] The server calls the payment module corresponding to the selected payment method.

[0795] Enter: the selected payment method information.

[0796] Output: Sending payment information to the payment module.

[0797] Specific operation: The server calls the payment module corresponding to the selected payment method (e.g., credit card payment module) and prepares payment information.

[0798] Step 5:

[0799] The server sends the payment information to the payment module and performs the payment process.

[0800] Input: User's payment information (e.g. credit card number, amount).

[0801] Output: Payment result (success / failure).

[0802] Specific operation: The server sends the user's payment information to the payment module and executes the payment process. The payment module processes the payment information and returns the result to the server.

[0803] Step 6:

[0804] The server receives the payment result and notifies the user.

[0805] Input: Payment result from payment module.

[0806] Output: User notification (success / failure).

[0807] Specific operation: The server receives the payment result from the payment module and notifies the user. If successful, it displays a message indicating the purchase is complete, and if unsuccessful, it displays an error message.

[0808] Processing steps of a system incorporating an emotion engine

[0809] Step 1:

[0810] The user inputs text or voice.

[0811] Input: User text and voice data.

[0812] Output: The input data is sent to the server.

[0813] What happens: A user types text on a website or application, or uses a microphone to input speech.

[0814] Step 2:

[0815] The server receives the input data and sends it to the emotion engine.

[0816] Input: User text and voice data.

[0817] Output: Sending data to the emotion engine.

[0818] Specific operation: The server receives the user's input data and sends it to the emotion engine.

[0819] Step 3:

[0820] The emotion engine analyzes emotions from input data.

[0821] Input: User text and voice data.

[0822] Output: Parsed emotion data.

[0823] Specific operation: The emotion engine uses natural language processing techniques to analyze input data and identify the user's emotions (e.g., fatigue, joy, sadness).

[0824] Step 4:

[0825] The server recommends products based on the analysis results.

[0826] Input: Parsed emotion data.

[0827] Output: Recommended product list.

[0828] Specific operation: The server receives the analysis results from the emotion engine and selects products that are appropriate for that emotion (e.g., products with a relaxation effect).

[0829] Step 5:

[0830] The server displays recommended products to the user.

[0831] Input: Recommended product list.

[0832] Output: Product display to user.

[0833] Specific operation: The server displays the selected recommended products to the user and encourages them to purchase.

[0834] (Application example 3)

[0835] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0836] Conventional e-commerce systems have limitations, such as difficulty in allowing users to purchase products using their local payment methods and a lack of emotionally-driven product recommendations, limiting the user experience. Furthermore, it is difficult to integrate payment solutions from different countries when expanding globally. There is a need to solve these issues and provide users with a more personalized purchasing experience.

[0837] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0838] In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions provided in each country, means for analyzing user emotions, and means for recommending products based on the results of the emotion analysis, thereby enabling users to not only purchase products using the payment method of their own country but also receive product recommendations based on their emotions.

[0839] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[0840] A "conversational interface" is an interface that allows a user to interact with a system using natural language.

[0841] "Product recommendation methods" are algorithms or systems that present appropriate products based on user requirements and behavior.

[0842] "Payment solutions" is a general term for technologies and services used to make payments when purchasing goods or services.

[0843] "Emotion analysis means" means any technology or algorithm used to identify and analyze emotions from a user's text or voice input.

[0844] "Means for recommending products based on the results of sentiment analysis" is a system for presenting products suitable for users based on the results of sentiment analysis.

[0845] A system for implementing the present invention includes means for interconnecting a plurality of e-commerce platforms, means for providing a conversational interface, means for recommending a plurality of products based on a user's request, means for linking payment solutions provided in each country, means for analyzing user sentiment, and means for recommending products based on the results of the sentiment analysis.

[0846] System configuration

[0847] The system consists of a server, user terminals, and a network infrastructure. The server includes a database, a natural language processing engine, a sentiment analysis engine, and a payment gateway. User terminals are devices such as smartphones and PCs that communicate with the server via the Internet.

[0848] Program processing

[0849] The server receives user input and analyzes the text using a natural language processing engine. The analyzed text is then sent to a sentiment analysis engine to identify the user's sentiment. Based on the results of the sentiment analysis, a product recommendation algorithm selects appropriate products and presents them to the user. After the user selects a product, the payment gateway connects with local payment solutions to complete the payment.

[0850] Hardware and software used

[0851] Hardware: Servers, smartphones, PCs

[0852] Software: Natural language processing engines (e.g., TextBlob), sentiment analysis engines, payment gateways (e.g., PaymentGateway)

[0853] Specific examples

[0854] When a user types "I'm tired today" using a smartphone, the system analyzes this text using a natural language processing engine and identifies the emotion "tired" using a sentiment analysis engine. The system then recommends products with a relaxation effect (e.g., aroma candles and bath salts). After the user selects a product and pays with their credit card, the payment is completed through a payment gateway.

[0855] Prompt Sentence Examples

[0856] User input: "I'm tired today"

[0857] User Country: "Japan"

[0858] Payment method: "Credit card"

[0859] Purchase price: 5,000 yen

[0860] In this way, users can not only purchase products using their local payment methods, but also receive emotion-based product recommendations.

[0861] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0862] Step 1:

[0863] The user uses the device to enter text.

[0864] Input: User text input (e.g. "I'm tired today")

[0865] Output: Text data

[0866] Specific action: The user enters text into the interface of their smartphone or computer and presses the send button.

[0867] Step 2:

[0868] The terminal transmits the text data to the server.

[0869] Input: Text data

[0870] Output: Text data sent to the server

[0871] Specific operation: The device sends text data to the server via the Internet.

[0872] Step 3:

[0873] The server analyzes the text data using a natural language processing engine.

[0874] Input: Text data

[0875] Output: Parsed text data (including sentiment)

[0876] What happens: The server uses a natural language processing engine, such as TextBlob, to parse the text data and identify sentiment.

[0877] Step 4:

[0878] The server uses a sentiment analysis engine to identify the user's sentiment.

[0879] Input: Parsed text data

[0880] Output: Emotion data (e.g. "Tired")

[0881] What happens: The server uses a sentiment analysis engine to identify the user's sentiment from the parsed text data.

[0882] Step 5:

[0883] The server recommends products based on the results of sentiment analysis.

[0884] Input: Emotion data

[0885] Output: Recommended product list (e.g., scented candles, bath salts)

[0886] Specific operation: Based on the emotion data, the server uses a product recommendation algorithm to select appropriate products and generate a recommended product list.

[0887] Step 6:

[0888] The server sends a list of recommended products to the terminal.

[0889] Input: Recommended Products List

[0890] Output: Recommended product list sent to the device

[0891] Specific operation: The server sends a list of recommended products to the terminal via the Internet.

[0892] Step 7:

[0893] The user uses the terminal to select an item and enter a payment method.

[0894] Input: Recommended product list, payment method (e.g. credit card)

[0895] Output: Selected products and payment methods

[0896] What happens: The user uses the device interface to select a product from the recommended product list and enter a payment method.

[0897] Step 8:

[0898] The terminal transmits the selected product and payment method to the server.

[0899] Input: Selected product and payment method

[0900] Output: Selected products and payment methods sent to the server

[0901] Specific operation: The terminal sends the selected product and payment method to the server via the Internet.

[0902] Step 9:

[0903] The server processes the payment through a payment gateway.

[0904] Input: Selected product and payment method

[0905] Output: Payment result (success or failure)

[0906] Specific behavior: The server uses the payment gateway to process the payment based on the selected product and payment method, and obtains the result.

[0907] Step 10:

[0908] The server sends the payment result to the terminal.

[0909] Input: Payment result

[0910] Output: Payment result sent to the terminal

[0911] Specific operation: The server sends the payment results to the terminal via the Internet.

[0912] Step 11:

[0913] The user checks the payment result on the terminal.

[0914] Input: Payment result

[0915] Output: Confirmed payment result

[0916] Specific operation: The user uses the terminal interface to check the payment result.

[0917] 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.

[0918] 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> ) 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.

[0919] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0920] 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.

[0921] [Second embodiment]

[0922] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0923] 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.

[0924] 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).

[0925] 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.

[0926] 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.

[0927] 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).

[0928] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0929] 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.

[0930] 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.

[0931] 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.

[0932] 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.

[0933] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0934] "Example 1"

[0935] One embodiment of the present invention is a system that interconnects multiple e-commerce malls. This system accesses the product databases of each e-commerce mall and retrieves product information in response to a user's request. For example, when a user searches for "sneakers," the system retrieves sneaker product information from multiple e-commerce malls and presents it to the user.

[0936] "Example 2"

[0937] One embodiment of the present invention is a system that provides a conversational interface. The system uses natural language processing technology to enable dialogue with a user. The user uses natural language to search for or purchase a product, and the system generates an appropriate response accordingly. For example, if the user says, "I'm looking for red sneakers," the system searches for "red sneakers" and presents the results to the user.

[0938] "Example 3"

[0939] Furthermore, one embodiment of the present invention is a system that links payment solutions offered in various countries. This system has a payment module that supports the payment solutions of each country, allowing users to purchase products using the payment method of their own country. For example, users in Japan can purchase products using methods such as credit cards, bank transfers, and convenience store payments.

[0940] The processing flow of each embodiment will be described below.

[0941] "Example 1"

[0942] Step 1: The user makes a product search request. For example, a request to search for "sneakers."

[0943] Step 2: The system accesses the product databases of each e-commerce mall and retrieves product information according to the user's request. At this time, it retrieves "sneaker" product information from multiple e-commerce malls.

[0944] Step 3: The acquired product information is presented to the user. The user can select a product from the presented product information and proceed with the purchase.

[0945] "Example 2"

[0946] Step 1: The user makes a product search or purchase request in natural language, for example, "I'm looking for red sneakers."

[0947] Step 2: The system uses natural language processing techniques to analyze the user's request and generate an appropriate response, in this case, a search for "red sneakers."

[0948] Step 3: The generated response is presented to the user, who can then select a product from the presented response and proceed with the purchase.

[0949] "Example 3"

[0950] Step 1: The user selects a product and proceeds with the purchase. At this time, the user selects the payment method for their country. For example, Japanese users can select methods such as credit card, bank transfer, or convenience store payment.

[0951] Step 2: The system calls the payment module corresponding to the selected payment method and processes the payment.

[0952] Step 3: Once the payment is complete, the user is notified of the payment completion, allowing them to purchase the product using their own payment method.

[0953] Example 1

[0954] Next, a description will be given of Example 1 of Form 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."

[0955] In conventional e-commerce systems, users had to search multiple e-commerce platforms individually and compare product information. This required a lot of time and effort from users, making it difficult to conduct efficient product searches. In addition, because the product information provided by each platform differed, sorting and comparing overlapping product information was cumbersome. This reduced user convenience and made it difficult to select the optimal product.

[0956] 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.

[0957] In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for acquiring product information based on a user request, means for aggregating the acquired product information and eliminating duplication, and means for presenting the aggregated product information to the user, thereby enabling the user to check product information aggregated from multiple e-commerce platforms with a single search, enabling them to efficiently and quickly select the most suitable product.

[0958] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[0959] "Interconnection" refers to the state in which multiple systems or networks can communicate with each other and exchange data.

[0960] "User request" refers to a search or request made by a user to the system.

[0961] "Product Information" refers to detailed data about a product, such as the product name, price, availability, images, and description.

[0962] "Acquisition" refers to the system gathering the necessary information from external databases or APIs.

[0963] "Aggregation" refers to combining data obtained from multiple sources into one.

[0964] "Deduplication" refers to combining identical or similar information into one and removing redundant data.

[0965] "Presenting" means displaying or providing information to a user.

[0966] An "application program interface (API)" refers to an interface that allows different software systems to communicate with each other and utilize their functionality.

[0967] The present invention is a system that interconnects multiple e-commerce platforms, acquires product information based on user requests, and aggregates and presents it. Specific embodiments of this system are described below.

[0968] System Overview

[0969] This system consists of three main components: a server, a terminal, and a user. The server interconnects multiple e-commerce platforms and retrieves, aggregates, and presents product information based on user requests. The terminal is a device through which users input search keywords and display product information. Users use the terminal to search for products and obtain information.

[0970] Hardware and software used

[0971] The server is a computer system equipped with a high-performance processor and a large amount of memory. The server obtains product information using the APIs (Application Program Interfaces) of multiple e-commerce platforms. Specifically, the server uses the following APIs:

[0972] E-commerce platform A's API

[0973] E-commerce platform B's API

[0974] API for e-commerce platform C

[0975] The terminal is a device used by the user, such as a smartphone, tablet, or PC. The terminal communicates with the server through a browser or a dedicated application.

[0976] Data processing and calculation

[0977] The server receives search keywords from users and calls the APIs of each e-commerce platform to obtain product information. The obtained product information is aggregated within the server, and duplicate information is eliminated. The aggregated product information is then presented to the user.

[0978] The specific data processing and calculation procedures are as follows:

[0979] 1. The user enters a keyword into the device's search bar.

[0980] 2. The device sends the search keywords to the server.

[0981] 3. The server calls the API of each e-commerce platform to obtain product information.

[0982] 4. The server aggregates the product information it has obtained and eliminates duplicates.

[0983] 5. The server sends the aggregated product information to the terminal.

[0984] 6. The device displays product information to the user.

[0985] Specific examples

[0986] For example, consider a user searching for "sneakers." When the user types "sneakers" into the device and presses the search button, the following prompt is input to the generative AI model:

[0987] Example prompt sentence:

[0988] A user searches for "sneakers." You want to retrieve sneaker product information from multiple e-commerce platforms and present it to the user. The APIs used are the API of e-commerce platform A, the API of e-commerce platform B, and the API of e-commerce platform C.

[0989] Based on this prompt, the server will do the following:

[0990] 1. Call the API of e-commerce platform A to obtain sneaker product information.

[0991] 2. Call the API of e-commerce platform B to retrieve sneaker product information.

[0992] 3. Call the API of e-commerce platform C to get sneaker product information.

[0993] 4. Aggregate the acquired product information and eliminate duplicates.

[0994] 5. Present aggregated product information to users.

[0995] In this way, users can view sneaker product information aggregated from multiple e-commerce platforms at once.

[0996] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0997] Step 1:

[0998] The user enters a search keyword.

[0999] A user enters a keyword, such as "sneakers," into the device's search bar and presses the search button. The input is the search keyword entered by the user. The output is the search keyword sent to the device.

[1000] Step 2:

[1001] The device sends the search keywords to the server.

[1002] The device sends the search keywords entered by the user to the server. Specifically, the device generates JSON format data including the search keywords and sends it to the server as an HTTP POST request. The input is the search keywords entered by the user. The output is the search keywords sent to the server.

[1003] Step 3:

[1004] The server calls the API of each e-commerce platform.

[1005] Based on the received search keywords, the server calls the APIs of multiple e-commerce platforms to obtain product information. Specifically, the server sends a request including the search keywords to each API and obtains the corresponding product information. The input is the search keywords. The output is the product information obtained from each e-commerce platform.

[1006] Step 4:

[1007] The product information acquired by the server is aggregated.

[1008] The server aggregates the product information obtained from each e-commerce platform and eliminates duplicates. Specifically, it consolidates the obtained product information into a single list and eliminates duplicates. The input is the product information obtained from each e-commerce platform. The output is the aggregated product information with duplicates eliminated.

[1009] Step 5:

[1010] The server transmits the aggregated product information to the terminal.

[1011] The server sends the aggregated product information to the terminal in JSON format. Specifically, it returns data including the product information to the terminal as an HTTP response. The input is the aggregated product information. The output is the product information sent to the terminal.

[1012] Step 6:

[1013] The device displays product information to the user.

[1014] The terminal displays the received product information to the user. Specifically, it displays a product list on the screen and allows the user to check detailed information about each product (price, stock status, product image, etc.). The input is the product information sent from the server. The output is the product information displayed to the user.

[1015] (Application example 1)

[1016] Next, a description will be given of Application Example 1 of Form 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."

[1017] Traditional e-commerce platforms require users to search multiple platforms individually and compare product information, which takes time and effort. Furthermore, the payment solutions and product information formats offered by each platform are different, making it difficult for users to use. Furthermore, the lack of features to filter products based on users' desired criteria and manage purchase history and favorite lists also creates a poor user experience.

[1018] 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.

[1019] In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on user requests, means for linking payment solutions offered in various countries, means for obtaining product information from multiple e-commerce platforms and comparing and displaying information such as price, availability, and reviews, means for providing a filtering function that allows users to set desired conditions, means for managing product purchase history and favorite lists, and means for notifying users of sales information and price fluctuations via push notifications. This allows users to obtain and compare product information from multiple platforms using a single interface, saving time and effort. Furthermore, the unified payment solution and product information format improves usability and enhances the user experience.

[1020] An "e-commerce platform" is an online system for selling and purchasing goods and services over the Internet.

[1021] "Interconnection" refers to the state in which multiple systems or networks can communicate with each other and exchange data.

[1022] A "conversational interface" is a user interface that allows a user to interact with a system using natural language.

[1023] "Natural language processing technology" is a technology that allows computers to understand and process human language.

[1024] "Product recommendation" is a function that suggests appropriate products based on the user's requests and preferences.

[1025] "Payment solutions" are systems and services that enable safe and efficient online payments.

[1026] "Product Information" refers to detailed information necessary for purchasing a product, such as product price, availability, and reviews.

[1027] The "filtering function" is a function that narrows down search results based on the user's desired conditions.

[1028] "Purchase history" is a record of products a user has purchased in the past.

[1029] A "favorites list" is a list for saving products that a user finds interesting.

[1030] "Push notifications" are a feature that allows an application to send information to a user's device in real time.

[1031] "Sale information" is information about product discounts and special prices.

[1032] "Price fluctuation" refers to the change in the price of a product over time.

[1033] The system for implementing this invention interconnects multiple e-commerce platforms to provide users with a consistent shopping experience. The system includes the following major components:

[1034] 1. Means of interconnecting multiple e-commerce platforms:

[1035] The server accesses the APIs of each e-commerce platform to retrieve product information, allowing users to search for product information from multiple platforms through a single interface.

[1036] 2. Means of providing a conversational interface:

[1037] The server uses natural language processing technology to enable interaction with users, who can search for products and ask questions in natural language via their smartphones or other devices.

[1038] 3. A method for recommending multiple products based on user requirements:

[1039] The server analyzes product information obtained from multiple e-commerce platforms based on the user's search query and recommends the most suitable products.

[1040] 4. Means of integrating payment solutions offered in each country:

[1041] The server will integrate payment solutions from each country, allowing users to seamlessly purchase the products they select.

[1042] 5. A way to retrieve product information from multiple e-commerce platforms and compare prices, availability, reviews, etc.:

[1043] The server integrates the acquired product information and displays a comparison of prices, availability, reviews, etc. to the user, allowing the user to select the most suitable product.

[1044] 6. Means of providing filtering functionality that allows users to set desired criteria:

[1045] The server provides the ability for users to filter search results by setting criteria such as price range, brand, size, etc.

[1046] 7. How to manage your purchase history and wish list:

[1047] The server manages the user's purchase history and favorites list, allowing the user to easily check products they have purchased in the past or products they are interested in.

[1048] 8. Push notifications for sales and price changes:

[1049] The server sends push notifications to users' devices to inform them of sales and price changes in real time.

[1050] Hardware and software used

[1051] Hardware: Smartphones, servers

[1052] Software: Python, Flask (web framework), requests (HTTP request library), natural language processing technology (e.g., Google Cloud Natural Language API)

[1053] Data processing and calculation

[1054] The server receives a search query from the user and sends an HTTP request to the API of each e-commerce platform. The retrieved product information is consolidated within the server, and information such as price, availability, and reviews is displayed for comparison. Search results are narrowed down based on the filtering conditions set by the user. Purchase history and favorites lists are stored in a database, and push notifications are sent to the user's device in real time.

[1055] Specific examples

[1056] When a user searches for "sneakers," the server retrieves product information from multiple e-commerce platforms and displays it as follows:

[1057] Platform 1: Nike Air Max - ¥12,000 - In Stock - 4.5 Review

[1058] Platform 2: Adidas Ultraboost - ¥15,000 - Out of Stock - 4.7 Review

[1059] Platform 3: Puma RS-X - ¥10,000 - In Stock - 4.3 Review

[1060] Prompt Sentence Examples

[1061] "Develop an application that retrieves product information from multiple e-commerce platforms for a user-searched product and displays a comparison of prices, availability, reviews, etc."

[1062] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1063] Step 1:

[1064] A user launches an application on their smartphone and enters a search query (e.g., "sneakers"). The entered search query is sent from the application to a server. The input data is the keyword for the product the user wants to search for. The output data is the search query sent to the server.

[1065] Step 2:

[1066] The server analyzes the received search query and sends HTTP requests to the APIs of multiple e-commerce platforms. The input data is the search query received from the user. The output data is the HTTP requests sent to each e-commerce platform.

[1067] Step 3:

[1068] Each e-commerce platform receives an HTTP request from a server and returns the relevant product information (price, availability, reviews, etc.). The input data is the HTTP request from the server. The output data is the HTTP response containing the product information.

[1069] Step 4:

[1070] The server integrates the product information received from each e-commerce platform and processes the data to compare and display prices, availability, reviews, etc. The input data is the product information received from each e-commerce platform. The output data is the integrated product information.

[1071] Step 5:

[1072] The server returns the integrated product information to the user's smartphone, which the application displays. The input data is the integrated product information sent from the server. The output data is the product information displayed on the user's smartphone.

[1073] Step 6:

[1074] The user sets the desired conditions (price range, brand, size, etc.) based on the displayed product information and performs filtering. The input data are the filtering conditions set by the user. The output data is the filtered product information.

[1075] Step 7:

[1076] The server reprocesses the product information based on the user's filtering conditions and returns the filtered results to the user's smartphone. The input data are the filtering conditions set by the user. The output data is the filtered product information.

[1077] Step 8:

[1078] The user selects the product they wish to purchase and completes the purchase procedure. The server connects with payment solutions provided in each country, enabling the user to smoothly purchase the selected product. The input data is the product selected by the user and payment information. The output data is confirmation that the purchase has been completed.

[1079] Step 9:

[1080] The server stores and manages the user's purchase history and favorites list in a database. The input data is the user's purchase history and favorites list. The output data is the history information stored in the database.

[1081] Step 10:

[1082] The server sends push notifications to users' smartphones when sales information or price fluctuations occur. The input data is sales information or price fluctuation information. The output data is the push notification sent to the user's smartphone.

[1083] Example 2

[1084] Next, a description will be given of Example 2 of Form 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."

[1085] Conventional e-commerce systems require a lot of effort when users search for products, making it difficult to search and purchase efficiently. It is also difficult to integrate multiple e-commerce platforms and provide users with a consistent experience. Furthermore, linking payment solutions offered in each country is complex, making global expansion difficult.

[1086] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions offered in various countries, means for analyzing user input using natural language processing technology, means for inputting prompt sentences to the generative AI model based on the analysis results, and means for presenting responses from the generative AI model to the user. This enables users to search for products in natural language and purchase them efficiently. Furthermore, integrating multiple e-commerce platforms and linking payment solutions from various countries facilitates global expansion.

[1087] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[1088] A "conversational interface" is a user interface that allows a user to interact with a system using natural language.

[1089] A "user request" is a specific request such as a search or purchase that a user makes to the system.

[1090] "Payment Solutions" means payment instruments or systems used to purchase goods and services.

[1091] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language.

[1092] A "generative AI model" is an artificial intelligence model that generates appropriate responses or content based on input data.

[1093] A "prompt sentence" is an instruction sentence input to a generative AI model, and is the sentence that serves as the basis for the model to generate a response.

[1094] "Analysis results" are data obtained after analyzing a user's input using natural language processing techniques.

[1095] A "response" is a reply or result that a generative AI model generates based on a prompt.

[1096] This invention is a system that allows users to search for and purchase products efficiently in natural language. The system interconnects multiple e-commerce platforms, provides a conversational interface, recommends multiple products based on user requests, and integrates payment solutions offered in various countries.

[1097] Hardware and software used

[1098] Hardware:

[1099] High-performance servers (e.g., servers with Intel Xeon processors)

[1100] software:

[1101] Natural language processing libraries (e.g., spaCy, NLTK)

[1102] Database management system (e.g. MySQL)

[1103] Generative AI models (e.g., GPT-3)

[1104] Program processing

[1105] When the server receives input from a user, it analyzes the input using a natural language processing library. The analyzed data is input as a prompt sentence to the generative AI model. The generative AI model generates an appropriate response according to the user's request. For example, if a user inputs "I'm looking for red sneakers," the server searches the database using "red sneakers" as a keyword and presents the search results to the user.

[1106] Specific examples

[1107] A specific example is shown below where the user says, "I'm looking for red sneakers."

[1108] User input: "I'm looking for red sneakers"

[1109] Example prompt: "The user is looking for red sneakers. Retrieve a list of red sneakers from the database and generate an appropriate response."

[1110] The server inputs the above prompt sentence into the generative AI model and receives a response from the model. The server then presents the response to the user. For example, it displays the results in the form of "The following red sneakers were found: [Product List]."

[1111] In this way, a system is realized in which the server, terminals, and users work together to support product searches and purchases.

[1112] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1113] Step 1:

[1114] The user inputs in natural language. The user inputs product search and purchase requests in natural language through the terminal interface. For example, the user inputs "I'm looking for red sneakers." The input data is in text format.

[1115] Step 2:

[1116] The terminal sends the user's input to the server. The terminal sends the user's input to the server in real time. The HTTPS protocol is used for transmission to ensure data security. The input is the user's text data, and the output is the data sent to the server.

[1117] Step 3:

[1118] The server parses the input using a natural language processing library. The server parses the received user input using a natural language processing library (e.g., spaCy, NLTK). Parsing includes tokenization, part-of-speech tagging, dependency analysis, etc. The input is the user's text data, and the output is the parsed data.

[1119] Step 4:

[1120] The server generates a prompt sentence based on the analysis results. The server generates a prompt sentence to input to the generative AI model based on the analysis results. For example, a prompt sentence such as "The user is looking for red sneakers. Please retrieve a list of red sneakers from the database and generate an appropriate response" is created. The input is the analysis result data, and the output is the prompt sentence.

[1121] Step 5:

[1122] The server inputs a prompt sentence into the generative AI model. The server inputs the generated prompt sentence into the generative AI model (e.g., GPT-3). The model generates a response based on the prompt sentence. The input is the prompt sentence, and the output is the generated response.

[1123] Step 6:

[1124] The generative AI model generates a response. The generative AI model generates an appropriate response based on the prompt sentence according to the user's request. For example, it generates the response "The following red sneakers were found: [product list]". The input is the prompt sentence, and the output is the generated response.

[1125] Step 7:

[1126] The server receives the generated response and returns it to the user in an appropriate format. The server receives the response from the generative AI model and converts it into an appropriate format to return to the user, for example, formatting the response in HTML. The input is the generated response and the output is the formatted response.

[1127] Step 8:

[1128] The terminal displays the response from the server to the user. The terminal displays the response received from the server to the user. The user checks the displayed results and decides on the next action. The input is the formatted response, and the output is what is displayed to the user.

[1129] (Application example 2)

[1130] Next, a description will be given of Application Example 2 of Form 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."

[1131] Conventional e-commerce platforms require users to go through multiple steps when searching for and purchasing products, making operation cumbersome. Furthermore, the inability to use voice input for searches or purchases resulted in low user convenience. Furthermore, it was difficult to integrate payment solutions offered in each country, making global expansion difficult.

[1132] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1133] In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions offered in various countries, means for receiving voice input and converting the voice to text, means for analyzing the user's intent using natural language processing technology, means for searching a product database based on the analysis results, means for generating a response based on the search results and converting the text to speech, and means for playing the generated speech to the user. This allows users to search for and purchase products through natural conversation, simplifying operation and improving convenience. It also enables the integration of global payment solutions, facilitating international expansion.

[1134] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[1135] A "conversational interface" is a user interface that allows a user to interact with a system using natural language.

[1136] "User requests" are specific instructions or requests, such as searches or purchases, that a user makes to the system.

[1137] "Means for recommending products" is a function for selecting and presenting appropriate products based on the user's requests.

[1138] "Payment solutions" are systems and services used to process payments for the purchase of goods and services.

[1139] "Voice input" refers to voice data uttered by the user through a microphone.

[1140] "Speech-to-text" is the process of analyzing and converting speech data into corresponding text data.

[1141] "Natural language processing technology" is a technology that allows computers to understand and analyze human language.

[1142] "User intent" refers to the goals and desires that users have for the system.

[1143] A "product database" is a database that stores information about products.

[1144] The "means for generating a response" is a function for creating an appropriate reply to a user request.

[1145] "Text-to-speech" is the process of analyzing text data and converting it into corresponding audio data.

[1146] "Generated speech" refers to speech data created by text-to-speech conversion.

[1147] A system for implementing the present invention has the following configuration: a server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions offered in various countries, means for receiving voice input and converting the voice to text, means for analyzing the user's intent using natural language processing technology, means for searching a product database based on the analysis results, means for generating a response based on the search results and converting the text to voice, and means for playing the generated voice to the user.

[1148] Hardware and software used

[1149] Hardware: Smartphone (iOS or Android)

[1150] software:

[1151] Natural language processing libraries (e.g., Google Cloud Natural Language API, spaCy)

[1152] Databases (e.g., Firebase, MongoDB)

[1153] Front-end frameworks (e.g., React Native)

[1154] Backend frameworks (e.g., Node.js, Express)

[1155] Speech recognition API (e.g., Google Cloud Speech-to-Text API)

[1156] Text-to-speech API (e.g., Google Cloud Text-to-Speech API)

[1157] Data processing and calculation

[1158] 1. Acquiring voice input: The user inputs voice using the smartphone microphone. The voice data is sent to the server in real time.

[1159] 2. Speech-to-text conversion: The server converts the speech data into text data using the Google Cloud Speech-to-Text API.

[1160] 3. Natural Language Processing: Text data is parsed using Google Cloud Natural Language API or spaCy to extract user intent.

[1161] 4. Product search: Based on the analysis results, search the product database stored in Firebase or MongoDB.

[1162] 5. Response generation: Based on the search results, a response is generated to present appropriate product information to the user.

[1163] 6. Text-to-Speech Conversion: The generated response is converted into audio data using the Google Cloud Text-to-Speech API.

[1164] 7. Audio playback: The generated audio data is played back to the user through the smartphone speaker.

[1165] Specific examples

[1166] When a user says, "I'm looking for red sneakers," the system processes them as follows:

[1167] 1. Take voice input and convert it to text.

[1168] 2. Analyze the text and extract "red sneakers" as a search keyword.

[1169] 3. Search the database for products that match "red sneakers."

[1170] 4. Based on the search results, generate a response such as "Here are the search results for red sneakers."

[1171] 5. Convert the response into speech and play it back to the user.

[1172] Prompt Sentence Examples

[1173] User: "I'm looking for red sneakers."

[1174] System: "Searching for red sneakers. Please wait."

[1175] System: "Here are the search results for red sneakers. There are Model A from XXXX, Model B from XXX, and so on. Which one would you like?"

[1176] In this way, users can search for and purchase products through natural conversation.

[1177] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1178] Step 1:

[1179] The user inputs voice using the microphone on their smartphone, and the voice data is sent to the server in real time.

[1180] Input: User's voice

[1181] Output: Audio data

[1182] Specific action: The user says, "I'm looking for red sneakers."

[1183] Step 2:

[1184] The server converts the audio data into text data using the Google Cloud Speech-to-Text API.

[1185] Input: Audio data

[1186] Output: Text data

[1187] Specific operation: The server receives the voice data and converts it into text: "I'm looking for red sneakers."

[1188] Step 3:

[1189] The server uses Google Cloud Natural Language API or spaCy to parse the text data and extract the user's intent.

[1190] Input: Text data

[1191] Output: Analysis result (user intent)

[1192] Specific operation: The server analyzes the text data and extracts "red sneakers" as a search keyword.

[1193] Step 4:

[1194] Based on the analysis results, the server searches the product database stored in Firebase or MongoDB.

[1195] Input: Analysis results (search keywords)

[1196] Output: Search results (product information)

[1197] Specific operation: The server searches the database for products that match "red sneakers."

[1198] Step 5:

[1199] The server generates a response based on the search results to present appropriate product information to the user.

[1200] Input: Search results (product information)

[1201] Output: Response text

[1202] What happens: The server generates a response like, "Here are the search results for red sneakers."

[1203] Step 6:

[1204] The server converts the response text into audio data using the Google Cloud Text-to-Speech API.

[1205] Input: Response text

[1206] Output: Audio data

[1207] Specific operation: The server receives the response text and converts it into voice data.

[1208] Step 7:

[1209] The server transmits the generated audio data to the smartphone and plays it back to the user through the smartphone's speaker.

[1210] Input: Audio data

[1211] Output: Audio output

[1212] Specific operation: The smartphone receives the audio data and plays it back to the user.

[1213] Example 3

[1214] Next, a description will be given of Example 3 of Form Example 3. 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."

[1215] With conventional e-commerce systems, when users purchase products using their own local payment methods, it is difficult to accommodate the different payment solutions in each country. Furthermore, there is a lack of an interface that allows users to select their preferred payment method and complete the payment smoothly. This leads to a poor user experience and complicated purchasing procedures.

[1216] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1217] In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions offered in each country, means for selecting a corresponding payment module based on the user's country information, means for presenting payment methods to the user through the selected payment module, means for verifying the payment information entered by the user and performing payment processing, and means for sending a payment completion notification to the user, thereby enabling the user to smoothly purchase products using the payment method of their own country.

[1218] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[1219] A "conversational interface" is an interface that allows users to interact with a system using natural language to perform operations and obtain information.

[1220] "Payment Solutions" is a collective term for technologies and services used to process online payments.

[1221] A "payment module" is a software component that implements a particular payment method.

[1222] "User country information" refers to information that identifies the country from which the user is accessing the site, including IP address and user account information.

[1223] "Payment method" refers to the means a user chooses to pay for goods or services, and includes credit cards, bank transfers, electronic money, etc.

[1224] "Payment Information" refers to payment information entered by the user based on the payment method selected, including credit card number and bank account information.

[1225] "Payment processing" refers to a series of operations required to actually complete a payment based on the payment information entered by the user.

[1226] The "payment completion notification" is a message to inform the user that the payment has been successfully completed.

[1227] This invention is a system that allows users to purchase products using their own country's payment method. The system interconnects multiple e-commerce platforms, provides a conversational interface, and recommends multiple products based on the user's request. It also connects payment solutions offered in each country, selects a corresponding payment module based on the user's country information, and presents payment methods to the user through the selected payment module. It also verifies the payment information entered by the user, processes the payment, and notifies the user that the payment has been completed.

[1228] Hardware and software used

[1229] This system uses the following hardware and software:

[1230] Servers: Database servers, web servers, payment gateway servers, etc.

[1231] Devices: PCs, smartphones, tablets, etc. used by users

[1232] Software: Conversational interfaces using natural language processing technology, payment modules, database management systems, middleware for processing API requests, etc.

[1233] Specific examples

[1234] For example, consider a case where a Japanese user purchases a product from an online shop. The user accesses the online shop's website or application and selects the product they wish to purchase. The terminal sends the product information selected by the user and the user's country information to the server. The server analyzes the received country information and selects the payment module corresponding to that country. For a Japanese user, the server selects the credit card, bank transfer, or convenience store payment module.

[1235] The server uses the selected payment module to present the user with available payment methods. The user selects the desired method from the presented payment methods and enters the required information (credit card number, bank account information, etc.). The server verifies the entered payment information and processes the payment. If the payment is successful, the server sends a purchase completion notification to the user. The terminal receives the purchase completion notification from the server and displays it to the user.

[1236] Prompt Sentence Examples

[1237] Please explain the process of the system that allows Japanese users to choose between credit card, bank transfer, and convenience store payment when purchasing products from an online shop.

[1238] In this way, the system allows users to smoothly purchase products using the payment method of their own country. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1239] Step 1:

[1240] The user selects an item and begins the checkout process.

[1241] Input: A user visits an online shopping website or application and selects the product they want to purchase.

[1242] What happens: The user clicks the "Add to Cart" button, then clicks the "Proceed to Checkout" button to begin the purchase process.

[1243] Output: The selected product information (product ID, quantity, price, etc.) is saved to the device.

[1244] Step 2:

[1245] The device sends the product information selected by the user and the user's country information to the server.

[1246] Input: Product information selected by the user and user country information (obtained from IP address and user account information)

[1247] Specific operation: The device uses an HTTP request to send data including product information and country information to the server.

[1248] Output: The server receives the product information and country information.

[1249] Step 3:

[1250] The server selects a corresponding payment module based on the received country information.

[1251] Input: User's country information received by the server

[1252] Specific operation: The server retrieves payment options for the relevant country (credit card, bank transfer, convenience store payment, etc.) from the database.

[1253] Output: The selected payment module information is saved on the server.

[1254] Step 4:

[1255] The server presents the payment method to the user through the selected payment module.

[1256] Input: Information about the payment module selected by the server

[1257] Specific operation: The server generates an HTML form and displays a screen for the user to enter credit card information and instructions for bank transfer.

[1258] Output: The user is presented with the available payment methods.

[1259] Step 5:

[1260] The user selects the desired payment method from the options presented and enters the required information.

[1261] Input: The payment method selected by the user and any required information (credit card number, bank account information, etc.)

[1262] Specific behavior: The user enters their credit card information and clicks the "Pay" button.

[1263] Output: The entered payment information is saved on the device and sent to the server.

[1264] Step 6:

[1265] The server verifies the entered payment information and processes the payment.

[1266] Input: Payment information entered by the user

[1267] Specific behavior: The server sends an API request to the payment gateway (e.g., payment service provider) to receive authorization for the payment.

[1268] Output: The result of the payment (success or failure) is returned to the server.

[1269] Step 7:

[1270] The server sends a notification to the user that the purchase is complete.

[1271] Input: Payment result if payment is successful

[1272] Specific behavior: The server generates a response containing the message "Purchase completed" and sends it to the user's device.

[1273] Output: A notification of successful purchase is sent to the user's device.

[1274] Step 8:

[1275] The device receives a purchase completion notification from the server and displays it to the user.

[1276] Input: Purchase completion notification sent from the server

[1277] What happens: The device displays the message "Purchase complete" on the screen.

[1278] Output: The user sees a message confirming the purchase.

[1279] (Application example 3)

[1280] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1281] With conventional e-commerce systems, when users purchase products using their own country's payment method, it is difficult to support different payment solutions in each country. In addition, it is time-consuming for users to select the appropriate payment option when purchasing a product, and there are delays in confirmation notifications after payment is completed. This creates an issue that impairs the user experience.

[1282] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions offered in each country, means for displaying appropriate payment options based on the user's country information, means for processing payment using the selected payment option, and means for sending a confirmation notice after payment is completed. As a result, when a user purchases a product using the payment method of their home country, appropriate payment options are automatically displayed, enabling the user to complete payment quickly and reliably.

[1283] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[1284] A "conversational interface" is a user interface that allows a user to interact with a system using natural language.

[1285] "User requests" refer to operations or instructions that users give to the system, such as product searches or purchases.

[1286] "Product recommendation means" refers to algorithms or systems that present appropriate products based on the user's requests and past behavioral history.

[1287] "Payment Solution" means a method or system for making payments for the purchase of goods or services.

[1288] "Payment Options" means the payment methods that users can choose when purchasing goods or services.

[1289] "Payment processing" refers to the series of steps taken to actually complete a payment using the payment option selected by the user.

[1290] A "confirmation notice" is a message or notification that informs the user that a payment has been completed.

[1291] "Natural language processing technology" is a technology that enables computers to understand and generate human language.

[1292] A "globally deployable structure" refers to a system that is designed and structured so that it can be used in multiple countries and regions and can meet the different requirements of each country.

[1293] As an embodiment of the present invention, the following system is constructed.

[1294] First, the server interconnects multiple e-commerce platforms, allowing users to search and purchase products from multiple platforms through a single interface.

[1295] The server then provides a conversational interface that uses natural language processing technology to allow users to search for products and ask questions in natural language. For example, if a user types, "I'm looking for the latest smartphone," the system will recommend suitable products.

[1296] Furthermore, the server recommends multiple products based on the user's request, using an algorithm that analyzes the user's past purchase and search history, thereby recommending the most suitable products for the user.

[1297] To integrate payment solutions offered in each country, the server displays appropriate payment options based on the user's country information. For example, a user in Japan will see options such as credit card, bank transfer, and convenience store payment.

[1298] To process the payment using the user's selected payment option, our server uses a payment API (e.g., Stripe, PayPal API), ensuring that the payment is completed quickly and securely using the payment method of your choice.

[1299] After the payment is completed, the server will send a confirmation to the user, so that the user can be sure that the payment was successfully completed.

[1300] As a concrete example, consider a user in Japan purchasing a product using a "Global Payment Assistant" app. The user opens the app, searches for a product, and a conversational interface responds in natural language. After the user selects a product and proceeds with the purchase, the server automatically displays Japanese payment options. After the user selects a credit card and completes the payment, a confirmation notification is sent.

[1301] An example of a prompt to be input to the generative AI model is, "When a Japanese user purchases a product, please generate a Python program that displays the options of credit card, bank transfer, and convenience store payment, and makes the payment using the selected option."

[1302] The above is an embodiment of the present invention.

[1303] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1304] Step 1:

[1305] The server recognizes the e-commerce platform accessed by the user and interconnects multiple platforms. It receives the user's access information as input and generates a list of platforms available to the user as output. Specifically, the server calls the API of each platform to obtain product data.

[1306] Step 2:

[1307] The server provides a conversational interface, receiving as input the user's natural language questions and requests, and generating appropriate responses and product recommendations as output. Specifically, the server uses natural language processing techniques to analyze the user's input and retrieve relevant product information.

[1308] Step 3:

[1309] The server recommends multiple products based on the user's request. It receives the user's search history and purchase history as input and generates a list of recommended products as output. Specifically, the server uses a machine learning algorithm to analyze the user's preferences and select the most suitable products.

[1310] Step 4:

[1311] The server connects payment solutions offered in each country. It receives the user's country information as input and displays the payment options corresponding to that country as output. Specifically, the server obtains the country information from the user's IP address and account information and lists the corresponding payment options.

[1312] Step 5:

[1313] The server processes the payment using the payment option selected by the user. As input, it receives the payment option selected by the user and payment information, and as output, it generates a payment completion status. Specifically, the server calls a payment API (e.g., Stripe, PayPal API) and executes the payment process.

[1314] Step 6:

[1315] The server sends a confirmation notice to the user after the payment is completed. It receives the payment completion status as input, generates a confirmation notice as output, and sends it to the user. Specifically, the server sends the payment completion information to the user via email or push notification.

[1316] The above are the specific processing steps for carrying out the present invention.

[1317] 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.

[1318] "Example 1"

[1319] One embodiment of the present invention provides a system incorporating an emotion engine. This system analyzes emotions from a user's text or voice input and recommends products based on the results. Specifically, if a user inputs the text "I'm tired today," the emotion engine recognizes from this text that the user is tired and recommends products with a relaxation effect, such as aroma candles or bath salts.

[1320] "Example 2"

[1321] The emotion engine also has the ability to change the interface display according to the user's emotions. For example, if the user enters text that indicates joy, the interface will change to a brighter color scheme and a positive message will be displayed. Conversely, if the user enters text that indicates sadness, the interface will change to a calmer color scheme and a comforting message will be displayed. This allows the system to respond appropriately to the user's emotions.

[1322] "Example 3"

[1323] One embodiment of the present invention provides a system incorporating an emotion engine. This system analyzes emotions from a user's text or voice input and recommends products based on the results. Specifically, if a user inputs the text "I'm tired today," the emotion engine recognizes from this text that the user is tired and recommends products with a relaxation effect, such as aroma candles or bath salts.

[1324] The processing flow of each embodiment will be described below.

[1325] "Example 1"

[1326] Step 1: The user enters text or voice input into the system.

[1327] Step 2: The emotion engine analyzes the emotion from the user's input.

[1328] Step 3: The system recommends products based on the analysis results. For example, if a user enters the text "I'm tired today," the emotion engine will recognize that the user is tired and recommend products with a relaxation effect, such as aroma candles or bath salts.

[1329] "Example 2"

[1330] Step 1: The user enters text or voice input into the system.

[1331] Step 2: The emotion engine analyzes the emotion from the user's input.

[1332] Step 3: Based on the analysis results, the system changes the interface display. For example, if the user enters text that indicates the emotion of joy, the interface will change to a brighter color scheme and display a positive message. Conversely, if the user enters text that indicates the emotion of sadness, the interface will change to a calmer color scheme and display a comforting message.

[1333] Example 1

[1334] Next, a description will be given of Example 1 of Form 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."

[1335] Conventional e-commerce systems face the problem of integrating multiple e-commerce platforms to provide product information, resulting in the time-consuming task of users searching across multiple platforms. Furthermore, product recommendations are not based on user sentiment, meaning that product suggestions cannot be tailored to the user's needs. Furthermore, it is difficult to integrate the different payment solutions offered in each country, limiting global expansion.

[1336] 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.

[1337] In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on user requests, means for linking payment solutions offered in various countries, means for analyzing user sentiment, and means for recommending products based on the results of the sentiment analysis. This allows users to obtain product information from multiple platforms through a single interface and receive product recommendations based on their sentiment. Furthermore, integrating different payment solutions facilitates global expansion.

[1338] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[1339] "Means of interconnection" refers to technologies and methods that link multiple systems and platforms and enable data exchange.

[1340] A "conversational interface" is a user interface that allows a user to interact with a system using natural language.

[1341] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language.

[1342] A "user request" is an action such as a search or inquiry that a user takes on the system.

[1343] "Means for recommending products" refers to technologies and methods for selecting and presenting appropriate products based on the user's requests and preferences.

[1344] "Payment solutions" are systems and services that enable online payments.

[1345] "Means for analyzing emotions" refers to technologies and methods for reading and analyzing emotions from a user's text or voice.

[1346] "Emotion analysis results" are information about the user's emotional state obtained by emotion analysis means.

[1347] A "globally deployable structure" is a design and structure that allows the system to be applied and operated in different countries and regions.

[1348] MODE FOR CARRYING OUT THE INVENTION

[1349] The present invention is a system that interconnects multiple e-commerce platforms, acquires product information based on user requests, and recommends products based on sentiment analysis. This system is designed to improve user convenience and realize more personalized product recommendations.

[1350] System configuration

[1351] 1. Hardware and Software Configuration

[1352] The server has an interface for accessing the APIs of multiple e-commerce platforms (e.g., online marketplaces and shopping sites).

[1353] The device provides the interface through which the user enters search queries or text and can be a smartphone, tablet, PC, etc.

[1354] An emotion engine is software that analyzes emotions from user text or voice input, specifically using IBM Watson or Google Cloud Natural Language API.

[1355] 2. Data processing and calculation

[1356] When the server receives a user's search query, it calls the APIs of multiple e-commerce platforms to obtain related product information, which is then sent to the terminal in JSON format.

[1357] The terminal parses the received JSON data and displays it as a product list on the user interface.

[1358] When the server receives the user's text input, it uses an emotion engine to analyze the user's emotions. Based on the analysis results, it selects products with a relaxation effect and sends recommended product information to the device.

[1359] The terminal analyzes the received recommended product information and displays it as recommended products on the user interface.

[1360] Specific examples

[1361] 1. Obtaining product information in response to a user's search request

[1362] A user types "sneakers" into the device's search bar.

[1363] The device sends the search query "sneakers" to the server.

[1364] The server accesses product databases of multiple e-commerce platforms to obtain product information about sneakers.

[1365] The server transmits the acquired product information to the terminal, and the terminal displays the product information to the user.

[1366] 2. Product Recommendation Based on Sentiment Analysis

[1367] The user types "I'm tired today" into the text input field.

[1368] The terminal sends the entered text to the server.

[1369] The server analyzes the emotions using an emotion engine.

[1370] The server recommends products with a relaxation effect based on the analysis results.

[1371] The server transmits the recommended product information to the terminal, and the terminal displays the recommended product information to the user.

[1372] Prompt Sentence Examples

[1373] "When a user searches for 'sneakers', generate a program that retrieves sneaker product information from multiple e-commerce platforms and presents it to the user."

[1374] "If a user types, 'I feel tired today,' use an emotion engine to analyze the user's emotions and generate a program that recommends products that have a relaxation effect."

[1375] This concludes the description of an embodiment of the present invention. This system allows users to access product information from multiple platforms through a single interface and receive emotion-based product recommendations. Furthermore, by integrating different payment solutions, global expansion becomes easier.

[1376] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1377] Program processing flow

[1378] Obtaining product information in response to a user's search request

[1379] Step 1:

[1380] A user types "sneakers" into the device's search bar.

[1381] Input: The user enters the search query "sneakers"

[1382] What happens: A user opens a browser on their smartphone or PC and types "sneakers" into the search bar.

[1383] Step 2:

[1384] The device sends the search query "sneakers" to the server.

[1385] Input: User entered search query "sneakers"

[1386] Output: HTTP request sent to the server

[1387] Specific operation: The device generates an HTTP request and sends it to the server.

[1388] Step 3:

[1389] The server accesses product databases of multiple e-commerce platforms to obtain product information about sneakers.

[1390] Input: Search query "sneakers" received from the device

[1391] Output: Product information obtained from each e-commerce platform

[1392] Specific operation: The server calls the API of each e-commerce platform to obtain product data.

[1393] Step 4:

[1394] The server transmits the acquired product information to the terminal.

[1395] Input: Product information obtained from each e-commerce platform

[1396] Output: JSON format data sent to the device

[1397] Specific operation: The server converts the acquired data into JSON format and sends it to the terminal.

[1398] Step 5:

[1399] The device displays product information to the user.

[1400] Input: JSON format data received from the server

[1401] Output: A list of products displayed in the user interface

[1402] Specific operation: The device parses the received JSON data and displays it as a product list in the user interface.

[1403] Product recommendation based on sentiment analysis

[1404] Step 1:

[1405] The user types "I'm tired today" into the text input field.

[1406] Input: User-entered text: "I'm tired today"

[1407] Specific action: The user types "I'm tired today" into the text input field on their smartphone or PC.

[1408] Step 2:

[1409] The terminal sends the entered text to the server.

[1410] Input: User-entered text: "I'm tired today"

[1411] Output: HTTP request sent to the server

[1412] Specific operation: The device generates an HTTP request and sends it to the server.

[1413] Step 3:

[1414] The server analyzes the emotions using an emotion engine.

[1415] Input: Text received from device: "I'm tired today"

[1416] Output: Sentiment analysis result (e.g., fatigue)

[1417] Specific operation: The server calls the emotion engine API and analyzes the text "I'm tired today."

[1418] Step 4:

[1419] The server recommends products with a relaxation effect based on the analysis results.

[1420] Input: Sentiment analysis result (e.g., fatigue)

[1421] Output: Recommended product information (e.g., aroma candles, bath salts)

[1422] Specific operation: Based on the analysis results, the server selects products with a relaxation effect.

[1423] Step 5:

[1424] The server transmits recommended product information to the terminal.

[1425] Input: Recommended product information (e.g., aroma candle, bath salt)

[1426] Output: JSON format data sent to the device

[1427] Specific operation: The server converts the recommended product information into JSON format and sends it to the terminal.

[1428] Step 6:

[1429] The device displays recommended product information to the user.

[1430] Input: JSON format data received from the server

[1431] Output: Recommendations displayed in the user interface

[1432] Specific operation: The device parses the received JSON data and displays it as recommended products in the user interface.

[1433] (Application example 1)

[1434] Next, a description will be given of Application Example 1 of Form 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."

[1435] Conventional e-commerce systems are inefficient because users must search multiple e-commerce platforms individually. Furthermore, product recommendations do not take into account the user's emotional state, resulting in low user satisfaction. Furthermore, it is difficult to integrate payment solutions offered in each country, making global expansion difficult.

[1436] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions offered in various countries, means for analyzing the user's emotions, and means for recommending products based on the results of the emotion analysis. This allows users to obtain product information from multiple platforms through a single interface and receive product recommendations based on their emotional state. Furthermore, linking global payment solutions enables smooth international transactions.

[1437] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[1438] A "conversational interface" is a user interface that allows a user to interact with a system using natural language.

[1439] "User requests" refer to search keywords and desired product information that users input into the system.

[1440] "Means for recommending products" is a function for presenting appropriate products to users based on the results of user requests and sentiment analysis.

[1441] "Payment Solutions" means technologies and services that enable online payments.

[1442] "Means for analyzing emotions" refers to technology that analyzes emotions from a user's text or voice input and determines their emotional state.

[1443] "Results of emotion analysis" refers to the determination of an emotional state obtained from a user's input.

[1444] The system for implementing this invention interconnects multiple e-commerce platforms, obtains product information based on user requests, and recommends products based on sentiment analysis. A specific embodiment of this system is described below.

[1445] System Configuration

[1446] The server includes the following means:

[1447] 1. E-commerce platform interconnection means: Access the APIs of multiple e-commerce platforms to obtain product information.

[1448] 2. Conversational interface provision: Enables dialogue with users using natural language processing technology.

[1449] 3. Product recommendation means: Recommend multiple products based on user requirements.

[1450] 4. Payment solution integration: Integrate payment solutions offered in each country.

[1451] 5. Sentiment analysis means: Analyzes emotions from the user's text or voice input.

[1452] 6. Product recommendation method based on the results of sentiment analysis: Recommend products based on the results of sentiment analysis.

[1453] Hardware and software used

[1454] Hardware: Servers, smartphones

[1455] Software: Python, requests library, TextBlob library

[1456] Data processing and calculation

[1457] 1. Data Acquisition:

[1458] The server accesses the API endpoint of the e-commerce platform and retrieves product information based on the specified keywords.

[1459] The acquired product information is integrated in the server and provided to the user.

[1460] 2. Emotion analysis:

[1461] The server analyzes the user's input text and classifies the sentiment as positive, negative, or neutral.

[1462] This analysis uses the TextBlob library.

[1463] 3. Product recommendation:

[1464] The server recommends products based on the results of emotion analysis. If the emotion is negative, it will recommend additional products with a relaxation effect.

[1465] Specific examples

[1466] If a user types into their smartphone, "I'm tired today, I want some new sneakers," the server does the following:

[1467] 1. Obtain product information for "sneakers" from an e-commerce platform.

[1468] 2. Analyze the negative emotion "tired" from the user's input text.

[1469] 3. In addition to product information about sneakers, recommend products with a relaxation effect (e.g., aroma candles and bath salts).

[1470] Prompt Sentence Examples

[1471] If a user types, "I'm tired today, I want new sneakers," perform sentiment analysis and, if negative sentiment is detected, recommend products that have a relaxation effect.

[1472] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1473] Step 1:

[1474] A user inputs a product search request into a smartphone terminal. For example, the user inputs, "I'm tired today, I want new sneakers." This input is sent to the server in text format.

[1475] Step 2:

[1476] The server receives the user's input text and analyzes it using natural language processing techniques. Specifically, it segments the input text and extracts keywords (in this case, "sneakers") and emotional expressions (in this case, "tired"). The input is the user's text, and the output is keywords and emotional expressions.

[1477] Step 3:

[1478] The server accesses the APIs of multiple e-commerce platforms and retrieves product information based on the extracted keywords. For example, it retrieves product information related to "sneakers" from each platform. The input is the keywords, and the output is a list of product information.

[1479] Step 4:

[1480] The server analyzes the user's emotional expressions using an emotion analysis tool. Specifically, it uses the TextBlob library to classify emotions as positive, negative, or neutral. The input is the emotional expression, and the output is the emotional classification result.

[1481] Step 5:

[1482] The server recommends products based on the results of sentiment analysis. If negative sentiment is detected, it recommends additional products with a relaxation effect (e.g., aroma candles or bath salts). The input is the sentiment classification result and a list of product information, and the output is the final list of recommended products.

[1483] Step 6:

[1484] The server sends the final recommended product list to the user's smartphone. The user can then check the recommended products on their smartphone and consider purchasing them. The input is the recommended product list, and the output is the product information displayed on the user's smartphone.

[1485] Example 2

[1486] Next, a description will be given of Example 2 of Form 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."

[1487] With conventional e-commerce systems, it was difficult for users to quickly find the right product when searching for it in natural language. Furthermore, the interface display did not change based on the user's emotions, resulting in a uniform user experience that was unable to respond to individual user emotions. Furthermore, it was difficult to interconnect multiple e-commerce platforms and link payment solutions across countries, making global expansion difficult.

[1488] 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.

[1489] In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions offered in various countries, means for analyzing user input using natural language processing technology, means for searching for products based on the analysis results, means for analyzing user sentiment, and means for changing the interface display based on the analysis results. This makes it easier for users to search for products in natural language and enables the interface display to be changed according to sentiment. Furthermore, interconnecting multiple e-commerce platforms and linking payment solutions in various countries facilitates global expansion.

[1490] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[1491] A "conversational interface" is a user interface that allows a user to interact with a system using natural language.

[1492] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language.

[1493] "Sentiment analysis" is a technology that detects emotions from user input text and evaluates the type and intensity of those emotions.

[1494] "Payment Solutions" are systems and services for processing online payments.

[1495] "Interface display change" refers to dynamically changing the appearance and content of the user interface in response to the user's emotions and behavior.

[1496] "Product recommendation" is a function that suggests appropriate products based on the user's requests and behavior.

[1497] "Interconnection" refers to linking multiple systems and platforms so that they can share data and functions.

[1498] The present invention relates to an electronic commerce system that allows users to search for products in natural language and change the interface display according to their emotions. Specific embodiments of this system are described below.

[1499] Hardware and software used

[1500] Hardware: Servers, user devices (PCs, smartphones, etc.)

[1501] Software: Natural language processing libraries (e.g., spaCy, NLTK), sentiment analysis libraries (e.g., TextBlob, VADER), databases (e.g., MySQL, MongoDB)

[1502] System configuration

[1503] 1. User Input

[1504] Users use the terminal to input product search and purchase requests in natural language.

[1505] Example: A user types, "I'm looking for red sneakers."

[1506] 2. Natural Language Processing

[1507] The server uses a natural language processing library to parse the user's input.

[1508] The keyword "red sneakers" is extracted from the analysis results.

[1509] 3. Product Search

[1510] The server connects to a database and searches for products based on the extracted keywords.

[1511] Present search results to the user.

[1512] Example: A search for "red sneakers" results in a list of multiple red sneakers.

[1513] 4. Sentiment analysis

[1514] The server uses a sentiment analysis library to analyze the sentiment of the user's input text.

[1515] Example: Detecting the emotion of joy when a user types, "I love these sneakers!"

[1516] 5. Changes to the interface display

[1517] The server uses an emotion engine to change the interface display based on the analysis results.

[1518] Example: If the emotion of joy is detected, the interface changes to a brighter color scheme and displays a positive message such as "Great choice!" Conversely, if the emotion of sadness is detected, the interface changes to a more subdued color scheme and displays a comforting message such as "Cheer up!"

[1519] Specific examples

[1520] User input: "I'm looking for red sneakers"

[1521] System response: "Here are your search results for red sneakers." (Displays a list of search results)

[1522] Example of sentiment analysis: "I love these sneakers!" (detects the emotion of happiness)

[1523] Interface changes: Lighter colors and a "Great Choice!" message

[1524] Prompt Sentence Examples

[1525] "I'm looking for red sneakers."

[1526] "I love these sneakers!"

[1527] "I've been feeling depressed lately"

[1528] This will allow users to easily search for products in natural language, enable the interface to change based on emotions, and facilitate global expansion by interconnecting multiple e-commerce platforms and integrating payment solutions across countries.

[1529] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1530] Step 1:

[1531] User Input

[1532] How it works: A user uses a device to input a product search or purchase request in natural language.

[1533] Input: User types "I'm looking for red sneakers."

[1534] Output: The user's input text is sent to the server.

[1535] Step 2:

[1536] Natural Language Processing

[1537] How it works: The server uses a natural language processing library (e.g., spaCy, NLTK) to parse the user's input text.

[1538] Input: User input text "I'm looking for red sneakers"

[1539] Data processing: Perform text analysis to extract the keyword "red sneakers."

[1540] Output: Extracted keyword "red sneakers"

[1541] Step 3:

[1542] Product search

[1543] How it works: The server connects to a database (e.g. MySQL, MongoDB) and searches for products based on the extracted keywords.

[1544] Input: Extracted keyword "red sneakers"

[1545] Data operation: Execute the following query against the database: SELECT FROM products WHERE color='red' AND category='sneakers'.

[1546] Output: A list of matching products (e.g., multiple red sneakers)

[1547] Step 4:

[1548] Presenting search results

[1549] Action: The server presents the search results to the user.

[1550] Input: List of applicable products

[1551] Output: Search results are displayed on the user's device.

[1552] What happens: The user's device will display a list of red sneakers along with the message, "Here are your search results for red sneakers."

[1553] Step 5:

[1554] sentiment analysis

[1555] How it works: The server uses a sentiment analysis library (e.g. TextBlob, VADER) to analyze the sentiment of the user's input text.

[1556] Input: User input text: "I love these sneakers!"

[1557] Data calculation: Calculate sentiment scores and detect positive sentiment.

[1558] Output: Detected emotion (e.g., joy)

[1559] Step 6:

[1560] Interface display changes

[1561] How it works: The server uses the emotion engine to change the interface display based on the analysis results.

[1562] Input: Detected emotion (e.g., joy)

[1563] What it does: It modifies the interface CSS to set the background color to a lighter shade and displays a positive message: "Great choice!"

[1564] Output: The modified interface is displayed on the user's terminal.

[1565] The above is the specific processing flow of the program of this system.

[1566] (Application example 2)

[1567] Next, a description will be given of Application Example 2 of Form 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."

[1568] On conventional e-commerce platforms, it was difficult for users to use natural language when searching for products, and the interface did not change in response to user sentiment, limiting the user experience. Furthermore, it was difficult to interconnect multiple e-commerce platforms and integrate payment solutions offered in each region. This created challenges that made it difficult for users to search for and purchase products comfortably and efficiently.

[1569] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1570] In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions provided in each region, means for changing the interface display in response to the user's emotions, means for enabling dialogue with the user using natural language processing technology, means for analyzing the user's emotions using emotion analysis technology, and means for changing the color tone and messages of the interface based on the analysis results. This not only enables users to search for and purchase products in natural language, but also enables a more comfortable and personalized user experience by changing the interface in response to emotions.

[1571] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[1572] A "conversational interface" is a user interface that allows a user to interact with a system using natural language.

[1573] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language.

[1574] "Sentiment analysis technology" is a technology that analyzes emotions from a user's text or voice and identifies their emotional state.

[1575] "Payment solutions" are systems and services that enable safe and efficient online payments.

[1576] "Means for changing the interface display" refers to a function that dynamically changes the color tone and messages of the user interface according to the user's emotions and behavior.

[1577] "Product recommendation means" is a function that presents appropriate products based on the user's requests and past behavior.

[1578] "Means of interconnection" refers to technology that connects multiple systems and platforms and allows them to share data and functions.

[1579] "Means for changing the color tone and messages of the interface based on the analysis results" refers to a function that dynamically changes the appearance and display content of the user interface based on the results of sentiment analysis.

[1580] A system for carrying out the present invention has the following configuration: the system includes means for interconnecting a plurality of e-commerce platforms, means for providing a conversational interface, means for recommending a plurality of products based on a user's request, means for linking payment solutions provided in each region, means for changing the display of the interface in accordance with the user's emotions, means for enabling dialogue with the user using natural language processing technology, means for analyzing the user's emotions using emotion analysis technology, and means for changing the color tone and messages of the interface based on the analysis results.

[1581] Hardware and software used

[1582] Hardware: Smartphone (iOS or Android)

[1583] software:

[1584] Natural language processing libraries (e.g., Google Cloud Natural Language API)

[1585] Sentiment analysis library (e.g. IBM Watson Tone Analyzer)

[1586] Front-end frameworks (e.g., React Native)

[1587] Backend server (e.g. Node.js)

[1588] Program processing explanation

[1589] 1. Getting user input:

[1590] Users input product search and purchase requests in natural language through a smartphone application.

[1591] Example: "I'm looking for red sneakers."

[1592] 2. Natural Language Processing:

[1593] The server analyzes the input text using the Google Cloud Natural Language API and extracts keywords.

[1594] Example: Keyword "red sneakers"

[1595] 3. Sentiment analysis:

[1596] The server uses IBM Watson Tone Analyzer to analyze emotions from the user's input text.

[1597] Example: Emotion "joy"

[1598] 4. Product Search:

[1599] The server uses the extracted keywords to search the product database on the backend server (Node.js).

[1600] Example: Get search results for red sneakers

[1601] 5. Interface changes:

[1602] The server uses React Native to change the interface color tone and messages based on the results of the sentiment analysis.

[1603] For example, for the emotion of joy, bright colors and positive messages are displayed.

[1604] 6. Displaying the results:

[1605] The server displays search results and an emotionally appropriate interface to the user.

[1606] Example: A list of red sneakers and a brightly colored interface

[1607] Specific examples

[1608] When a user types "I'm looking for red sneakers," the server uses the Google Cloud Natural Language API to extract the keyword "red sneakers," analyzes the user's emotion as "joy" using IBM Watson Tone Analyzer, searches for red sneakers on a Node.js server, and displays the search results in a brightly colored interface using React Native.

[1609] Prompt Sentence Examples

[1610] "I'm looking for red sneakers."

[1611] "I want a new smartphone"

[1612] "I'm not feeling very well today"

[1613] In this way, not only can users search and purchase products in natural language, but the interface changes according to emotions, enabling a more comfortable and personalized user experience.

[1614] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1615] Step 1:

[1616] Users input product search and purchase requests in natural language through a smartphone application.

[1617] Input: User's natural language text input (e.g., "I'm looking for red sneakers")

[1618] Output: User input text data

[1619] Step 2:

[1620] The server receives the user's input text data and analyzes it using the Google Cloud Natural Language API.

[1621] Input: User-entered text data

[1622] Data processing: Analyze text using natural language processing techniques and extract keywords (e.g., "red sneakers")

[1623] Output: Extracted keywords

[1624] Step 3:

[1625] The server uses the extracted keywords to search the product database.

[1626] Input: Extracted keywords (e.g. "red sneakers")

[1627] Data calculation: Perform keyword search on product database

[1628] Output: Product list as search results

[1629] Step 4:

[1630] The server performs sentiment analysis on the user's input text data using IBM Watson Tone Analyzer.

[1631] Input: User-entered text data

[1632] Data processing: Using sentiment analysis techniques to analyze emotions from text (e.g., "joy")

[1633] Output: Parsed emotion data

[1634] Step 5:

[1635] The server uses React Native to change the interface color tone and messages based on the results of the sentiment analysis.

[1636] Input: Parsed emotion data (e.g., "joy")

[1637] Data calculation: Determines the color tone and message of the interface according to emotions

[1638] Output: Changed interface configuration

[1639] Step 6:

[1640] The server sends the search results and the changed interface settings to the user's smartphone for display.

[1641] Input: Product list as search result, modified interface settings

[1642] Specific operation: Sends and displays the product list and interface settings to the user's smartphone.

[1643] Output: Product list and interface displayed on the user's smartphone

[1644] In this way, users can not only search and purchase products in natural language, but also enjoy a more comfortable and personalized user experience through interface changes based on emotions.

[1645] Example 3

[1646] Next, a description will be given of Example 3 of Form Example 3. 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."

[1647] Traditional e-commerce systems have had issues with users having to go through the hassle of using payment methods in different countries and not being able to recommend products based on user sentiment. Furthermore, integrating payment solutions from different countries is difficult when expanding globally, resulting in an inconsistent user experience.

[1648] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1649] In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions provided in each country, means for analyzing emotions from user input data, and means for recommending products based on the analysis results. This not only allows users to easily use payment methods in their own country, but also enables product recommendations based on user emotions, making it possible to provide a globally consistent user experience.

[1650] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[1651] A "conversational interface" is an interface that allows a user to interact with a system using natural language.

[1652] A "payment solution" is a method or system for making payments for the purchase of goods or services.

[1653] "Emotion analysis methods" are technologies and algorithms used to identify emotions from user input data (text or voice).

[1654] A "means for recommending products" is a system for selecting and presenting appropriate products based on the user's needs and emotions.

[1655] "Natural language processing technology" is a technology that allows computers to understand and process human language.

[1656] A "globally deployable structure" is a system design and structure that can be used consistently in different countries and regions.

[1657] MODE FOR CARRYING OUT THE INVENTION

[1658] This invention is a system that interconnects multiple e-commerce platforms, provides a conversational interface, recommends products based on user requests, and connects payment solutions offered in various countries. It also includes a function to analyze emotions from user input data and recommend products based on the analysis results.

[1659] Hardware and software used

[1660] The system uses the following hardware and software:

[1661] Server: Manages the entire system and processes data. A server with a high-performance processor and large memory capacity is recommended.

[1662] Device: The device from which the user accesses the site, including computers, smartphones, tablets, etc.

[1663] Natural language processing engine: Software used to analyze user text and voice input. For example, Google Cloud Natural Language API or IBM Watson Natural Language Understanding can be used.

[1664] Payment module: Software to support local payment solutions, such as PayPal, Stripe, and Square.

[1665] Sentiment analysis engine: Software for analyzing user sentiment. For example, Microsoft Azure Text Analytics or Amazon Comprehend can be used.

[1666] Specific operation of the system

[1667] 1. The user selects a product and begins the purchase process. The user selects a product on a website or application and clicks the "Buy" button.

[1668] 2. The server determines the user's country and displays the available payment methods. The server determines the user's country from their IP address and account information, and displays the payment methods available in that country (e.g., credit card, bank transfer, convenience store payment).

[1669] 3. The user selects the desired payment method. The user selects the desired payment method from the displayed payment methods and clicks the "Next" button.

[1670] 4. The server calls the payment module corresponding to the selected payment method. The server calls the payment module corresponding to the selected payment method (e.g., credit card payment module).

[1671] 5. The server sends the payment information to the payment module and processes the payment. The server sends the user's payment information (e.g., credit card number, amount) to the payment module and processes the payment.

[1672] 6. The server receives the payment result (success / failure) from the payment module and notifies the user. If successful, a message indicating purchase completion is displayed.

[1673] Specific operation of a system incorporating an emotion engine

[1674] 1. The user enters text or speaks into the app. The user enters text into the app or website, or speaks into the app using a microphone.

[1675] 2. The server receives the input data and sends it to the emotion engine. The server receives the user's input data (text or voice data) and sends it to the emotion engine.

[1676] 3. The emotion engine analyzes emotions from the input data. The emotion engine uses natural language processing technology to analyze the input data and identify the user's emotions (e.g., fatigue, joy, sadness).

[1677] 4. The server recommends products based on the analysis results. The server receives the analysis results from the emotion engine and selects products that suit the emotion (e.g., products with a relaxation effect).

[1678] 5. The server displays the recommended products to the user. The server displays the selected recommended products to the user and encourages them to purchase.

[1679] Prompt Sentence Examples

[1680] An example prompt for a generative AI model would be:

[1681] "Please explain the payment process when a Japanese user purchases a product with a credit card."

[1682] "If a user types, 'I'm tired today,' how would the emotion engine analyze that emotion and recommend products to them?"

[1683] By using these prompt sentences, the generative AI model can explain the specific processing content of the system in natural language. The flow of the specific processing in Example 3 will be explained with reference to FIG.

[1684] Processing steps for payment solution linked system

[1685] Step 1:

[1686] The user selects a product and begins the checkout process.

[1687] Input: A user selects an item on a website or application and clicks a "Buy" button.

[1688] Output: The information about the selected product is sent to the server.

[1689] Specific operation: The user selects the desired product from the product list page, proceeds to the product details page, and then clicks the "Purchase" button to begin the purchase process.

[1690] Step 2:

[1691] The server determines the user's country and displays the corresponding payment methods.

[1692] Input: User's IP address and account information.

[1693] Output: A list of payment methods for the user's country.

[1694] Specific operation: The server analyzes the user's IP address and account information to identify the user's country, and then displays the payment methods available in that country (e.g., credit card, bank transfer, convenience store payment).

[1695] Step 3:

[1696] The user selects the desired payment method.

[1697] Input: A list of displayed payment methods.

[1698] Output: The selected payment method information is sent to the server.

[1699] Specific operation: The user selects the desired payment method from the displayed options and clicks the "Next" button.

[1700] Step 4:

[1701] The server calls the payment module corresponding to the selected payment method.

[1702] Enter: the selected payment method information.

[1703] Output: Sending payment information to the payment module.

[1704] Specific operation: The server calls the payment module corresponding to the selected payment method (e.g., credit card payment module) and prepares payment information.

[1705] Step 5:

[1706] The server sends the payment information to the payment module and performs the payment process.

[1707] Input: User's payment information (e.g. credit card number, amount).

[1708] Output: Payment result (success / failure).

[1709] Specific operation: The server sends the user's payment information to the payment module and executes the payment process. The payment module processes the payment information and returns the result to the server.

[1710] Step 6:

[1711] The server receives the payment result and notifies the user.

[1712] Input: Payment result from payment module.

[1713] Output: User notification (success / failure).

[1714] Specific operation: The server receives the payment result from the payment module and notifies the user. If successful, it displays a message indicating the purchase is complete, and if unsuccessful, it displays an error message.

[1715] Processing steps of a system incorporating an emotion engine

[1716] Step 1:

[1717] The user inputs text or voice.

[1718] Input: User text and voice data.

[1719] Output: The input data is sent to the server.

[1720] What happens: A user types text on a website or application, or uses a microphone to input speech.

[1721] Step 2:

[1722] The server receives the input data and sends it to the emotion engine.

[1723] Input: User text and voice data.

[1724] Output: Sending data to the emotion engine.

[1725] Specific operation: The server receives the user's input data and sends it to the emotion engine.

[1726] Step 3:

[1727] The emotion engine analyzes emotions from input data.

[1728] Input: User text and voice data.

[1729] Output: Parsed emotion data.

[1730] Specific operation: The emotion engine uses natural language processing techniques to analyze input data and identify the user's emotions (e.g., fatigue, joy, sadness).

[1731] Step 4:

[1732] The server recommends products based on the analysis results.

[1733] Input: Parsed emotion data.

[1734] Output: Recommended product list.

[1735] Specific operation: The server receives the analysis results from the emotion engine and selects products that are appropriate for that emotion (e.g., products with a relaxation effect).

[1736] Step 5:

[1737] The server displays recommended products to the user.

[1738] Input: Recommended product list.

[1739] Output: Product display to user.

[1740] Specific operation: The server displays the selected recommended products to the user and encourages them to purchase.

[1741] (Application example 3)

[1742] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1743] Conventional e-commerce systems have limitations, such as difficulty in allowing users to purchase products using their local payment methods and a lack of emotionally-driven product recommendations, limiting the user experience. Furthermore, it is difficult to integrate payment solutions from different countries when expanding globally. There is a need to solve these issues and provide users with a more personalized purchasing experience.

[1744] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1745] In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions provided in each country, means for analyzing user emotions, and means for recommending products based on the results of the emotion analysis, thereby enabling users to not only purchase products using the payment method of their own country but also receive product recommendations based on their emotions.

[1746] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[1747] A "conversational interface" is an interface that allows a user to interact with a system using natural language.

[1748] "Product recommendation methods" are algorithms or systems that present appropriate products based on user requirements and behavior.

[1749] "Payment solutions" is a general term for technologies and services used to make payments when purchasing goods or services.

[1750] "Emotion analysis means" means any technology or algorithm used to identify and analyze emotions from a user's text or voice input.

[1751] "Means for recommending products based on the results of sentiment analysis" is a system for presenting products suitable for users based on the results of sentiment analysis.

[1752] A system for implementing the present invention includes means for interconnecting a plurality of e-commerce platforms, means for providing a conversational interface, means for recommending a plurality of products based on a user's request, means for linking payment solutions provided in each country, means for analyzing user sentiment, and means for recommending products based on the results of the sentiment analysis.

[1753] System configuration

[1754] The system consists of a server, user terminals, and a network infrastructure. The server includes a database, a natural language processing engine, a sentiment analysis engine, and a payment gateway. User terminals are devices such as smartphones and PCs that communicate with the server via the Internet.

[1755] Program processing

[1756] The server receives user input and analyzes the text using a natural language processing engine. The analyzed text is then sent to a sentiment analysis engine to identify the user's sentiment. Based on the results of the sentiment analysis, a product recommendation algorithm selects appropriate products and presents them to the user. After the user selects a product, the payment gateway connects with local payment solutions to complete the payment.

[1757] Hardware and software used

[1758] Hardware: Servers, smartphones, PCs

[1759] Software: Natural language processing engines (e.g., TextBlob), sentiment analysis engines, payment gateways (e.g., PaymentGateway)

[1760] Specific examples

[1761] When a user types "I'm tired today" using a smartphone, the system analyzes this text using a natural language processing engine and identifies the emotion "tired" using a sentiment analysis engine. The system then recommends products with a relaxation effect (e.g., aroma candles and bath salts). After the user selects a product and pays with their credit card, the payment is completed through a payment gateway.

[1762] Prompt Sentence Examples

[1763] User input: "I'm tired today"

[1764] User Country: "Japan"

[1765] Payment method: "Credit card"

[1766] Purchase price: 5,000 yen

[1767] In this way, users can not only purchase products using their local payment methods, but also receive emotion-based product recommendations.

[1768] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1769] Step 1:

[1770] The user uses the device to enter text.

[1771] Input: User text input (e.g. "I'm tired today")

[1772] Output: Text data

[1773] Specific action: The user enters text into the interface of their smartphone or computer and presses the send button.

[1774] Step 2:

[1775] The terminal transmits the text data to the server.

[1776] Input: Text data

[1777] Output: Text data sent to the server

[1778] Specific operation: The device sends text data to the server via the Internet.

[1779] Step 3:

[1780] The server analyzes the text data using a natural language processing engine.

[1781] Input: Text data

[1782] Output: Parsed text data (including sentiment)

[1783] What happens: The server uses a natural language processing engine, such as TextBlob, to parse the text data and identify sentiment.

[1784] Step 4:

[1785] The server uses a sentiment analysis engine to identify the user's sentiment.

[1786] Input: Parsed text data

[1787] Output: Emotion data (e.g. "Tired")

[1788] What happens: The server uses a sentiment analysis engine to identify the user's sentiment from the parsed text data.

[1789] Step 5:

[1790] The server recommends products based on the results of sentiment analysis.

[1791] Input: Emotion data

[1792] Output: Recommended product list (e.g., scented candles, bath salts)

[1793] Specific operation: Based on the emotion data, the server uses a product recommendation algorithm to select appropriate products and generate a recommended product list.

[1794] Step 6:

[1795] The server sends a list of recommended products to the terminal.

[1796] Input: Recommended Products List

[1797] Output: Recommended product list sent to the device

[1798] Specific operation: The server sends a list of recommended products to the terminal via the Internet.

[1799] Step 7:

[1800] The user uses the terminal to select an item and enter a payment method.

[1801] Input: Recommended product list, payment method (e.g. credit card)

[1802] Output: Selected products and payment methods

[1803] What happens: The user uses the device interface to select a product from the recommended product list and enter a payment method.

[1804] Step 8:

[1805] The terminal transmits the selected product and payment method to the server.

[1806] Input: Selected product and payment method

[1807] Output: Selected products and payment methods sent to the server

[1808] Specific operation: The terminal sends the selected product and payment method to the server via the Internet.

[1809] Step 9:

[1810] The server processes the payment through a payment gateway.

[1811] Input: Selected product and payment method

[1812] Output: Payment result (success or failure)

[1813] Specific behavior: The server uses the payment gateway to process the payment based on the selected product and payment method, and obtains the result.

[1814] Step 10:

[1815] The server sends the payment result to the terminal.

[1816] Input: Payment result

[1817] Output: Payment result sent to the terminal

[1818] Specific operation: The server sends the payment results to the terminal via the Internet.

[1819] Step 11:

[1820] The user checks the payment result on the terminal.

[1821] Input: Payment result

[1822] Output: Confirmed payment result

[1823] Specific operation: The user uses the terminal interface to check the payment result.

[1824] 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.

[1825] 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> ) 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.

[1826] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1827] 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.

[1828] [Third embodiment]

[1829] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1830] 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.

[1831] 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).

[1832] 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.

[1833] 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.

[1834] 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).

[1835] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1836] 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.

[1837] 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.

[1838] 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.

[1839] 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.

[1840] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1841] "Example 1"

[1842] One embodiment of the present invention is a system that interconnects multiple e-commerce malls. This system accesses the product databases of each e-commerce mall and retrieves product information in response to a user's request. For example, when a user searches for "sneakers," the system retrieves sneaker product information from multiple e-commerce malls and presents it to the user.

[1843] "Example 2"

[1844] One embodiment of the present invention is a system that provides a conversational interface. The system uses natural language processing technology to enable dialogue with a user. The user uses natural language to search for or purchase a product, and the system generates an appropriate response accordingly. For example, if the user says, "I'm looking for red sneakers," the system searches for "red sneakers" and presents the results to the user.

[1845] "Example 3"

[1846] Furthermore, one embodiment of the present invention is a system that links payment solutions offered in various countries. This system has a payment module that supports the payment solutions of each country, allowing users to purchase products using the payment method of their own country. For example, users in Japan can purchase products using methods such as credit cards, bank transfers, and convenience store payments.

[1847] The processing flow of each embodiment will be described below.

[1848] "Example 1"

[1849] Step 1: The user makes a product search request. For example, a request to search for "sneakers."

[1850] Step 2: The system accesses the product databases of each e-commerce mall and retrieves product information according to the user's request. At this time, it retrieves "sneaker" product information from multiple e-commerce malls.

[1851] Step 3: The acquired product information is presented to the user. The user can select a product from the presented product information and proceed with the purchase.

[1852] "Example 2"

[1853] Step 1: The user makes a product search or purchase request in natural language, for example, "I'm looking for red sneakers."

[1854] Step 2: The system uses natural language processing techniques to analyze the user's request and generate an appropriate response, in this case, a search for "red sneakers."

[1855] Step 3: The generated response is presented to the user, who can then select a product from the presented response and proceed with the purchase.

[1856] "Example 3"

[1857] Step 1: The user selects a product and proceeds with the purchase. At this time, the user selects the payment method for their country. For example, Japanese users can select methods such as credit card, bank transfer, or convenience store payment.

[1858] Step 2: The system calls the payment module corresponding to the selected payment method and processes the payment.

[1859] Step 3: Once the payment is complete, the user is notified of the payment completion, allowing them to purchase the product using their own payment method.

[1860] Example 1

[1861] Next, a description will be given of Example 1 of Form 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."

[1862] In conventional e-commerce systems, users had to search multiple e-commerce platforms individually and compare product information. This required a lot of time and effort from users, making it difficult to conduct efficient product searches. In addition, because the product information provided by each platform differed, sorting and comparing overlapping product information was cumbersome. This reduced user convenience and made it difficult to select the optimal product.

[1863] 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.

[1864] In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for acquiring product information based on a user request, means for aggregating the acquired product information and eliminating duplication, and means for presenting the aggregated product information to the user, thereby enabling the user to check product information aggregated from multiple e-commerce platforms with a single search, enabling them to efficiently and quickly select the most suitable product.

[1865] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[1866] "Interconnection" refers to the state in which multiple systems or networks can communicate with each other and exchange data.

[1867] "User request" refers to a search or request made by a user to the system.

[1868] "Product Information" refers to detailed data about a product, such as the product name, price, availability, images, and description.

[1869] "Acquisition" refers to the system gathering the necessary information from external databases or APIs.

[1870] "Aggregation" refers to combining data obtained from multiple sources into one.

[1871] "Deduplication" refers to combining identical or similar information into one and removing redundant data.

[1872] "Presenting" means displaying or providing information to a user.

[1873] An "application program interface (API)" refers to an interface that allows different software systems to communicate with each other and utilize their functionality.

[1874] The present invention is a system that interconnects multiple e-commerce platforms, acquires product information based on user requests, and aggregates and presents it. Specific embodiments of this system are described below.

[1875] System Overview

[1876] This system consists of three main components: a server, a terminal, and a user. The server interconnects multiple e-commerce platforms and retrieves, aggregates, and presents product information based on user requests. The terminal is a device through which users input search keywords and display product information. Users use the terminal to search for products and obtain information.

[1877] Hardware and software used

[1878] The server is a computer system equipped with a high-performance processor and a large amount of memory. The server obtains product information using the APIs (Application Program Interfaces) of multiple e-commerce platforms. Specifically, the server uses the following APIs:

[1879] E-commerce platform A's API

[1880] E-commerce platform B's API

[1881] API for e-commerce platform C

[1882] The terminal is a device used by the user, such as a smartphone, tablet, or PC. The terminal communicates with the server through a browser or a dedicated application.

[1883] Data processing and calculation

[1884] The server receives search keywords from users and calls the APIs of each e-commerce platform to obtain product information. The obtained product information is aggregated within the server, and duplicate information is eliminated. The aggregated product information is then presented to the user.

[1885] The specific data processing and calculation procedures are as follows:

[1886] 1. The user enters a keyword into the device's search bar.

[1887] 2. The device sends the search keywords to the server.

[1888] 3. The server calls the API of each e-commerce platform to obtain product information.

[1889] 4. The server aggregates the product information it has obtained and eliminates duplicates.

[1890] 5. The server sends the aggregated product information to the terminal.

[1891] 6. The device displays product information to the user.

[1892] Specific examples

[1893] For example, consider a user searching for "sneakers." When the user types "sneakers" into the device and presses the search button, the following prompt is input to the generative AI model:

[1894] Example prompt sentence:

[1895] A user searches for "sneakers." You want to retrieve sneaker product information from multiple e-commerce platforms and present it to the user. The APIs used are the API of e-commerce platform A, the API of e-commerce platform B, and the API of e-commerce platform C.

[1896] Based on this prompt, the server will do the following:

[1897] 1. Call the API of e-commerce platform A to obtain sneaker product information.

[1898] 2. Call the API of e-commerce platform B to retrieve sneaker product information.

[1899] 3. Call the API of e-commerce platform C to get sneaker product information.

[1900] 4. Aggregate the acquired product information and eliminate duplicates.

[1901] 5. Present aggregated product information to users.

[1902] In this way, users can view sneaker product information aggregated from multiple e-commerce platforms at once.

[1903] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1904] Step 1:

[1905] The user enters a search keyword.

[1906] A user enters a keyword, such as "sneakers," into the device's search bar and presses the search button. The input is the search keyword entered by the user. The output is the search keyword sent to the device.

[1907] Step 2:

[1908] The device sends the search keywords to the server.

[1909] The device sends the search keywords entered by the user to the server. Specifically, the device generates JSON format data including the search keywords and sends it to the server as an HTTP POST request. The input is the search keywords entered by the user. The output is the search keywords sent to the server.

[1910] Step 3:

[1911] The server calls the API of each e-commerce platform.

[1912] Based on the received search keywords, the server calls the APIs of multiple e-commerce platforms to obtain product information. Specifically, the server sends a request including the search keywords to each API and obtains the corresponding product information. The input is the search keywords. The output is the product information obtained from each e-commerce platform.

[1913] Step 4:

[1914] The product information acquired by the server is aggregated.

[1915] The server aggregates the product information obtained from each e-commerce platform and eliminates duplicates. Specifically, it consolidates the obtained product information into a single list and eliminates duplicates. The input is the product information obtained from each e-commerce platform. The output is the aggregated product information with duplicates eliminated.

[1916] Step 5:

[1917] The server transmits the aggregated product information to the terminal.

[1918] The server sends the aggregated product information to the terminal in JSON format. Specifically, it returns data including the product information to the terminal as an HTTP response. The input is the aggregated product information. The output is the product information sent to the terminal.

[1919] Step 6:

[1920] The device displays product information to the user.

[1921] The terminal displays the received product information to the user. Specifically, it displays a product list on the screen and allows the user to check detailed information about each product (price, stock status, product image, etc.). The input is the product information sent from the server. The output is the product information displayed to the user.

[1922] (Application example 1)

[1923] Next, a description will be given of Application Example 1 of Form 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."

[1924] Traditional e-commerce platforms require users to search multiple platforms individually and compare product information, which takes time and effort. Furthermore, the payment solutions and product information formats offered by each platform are different, making it difficult for users to use. Furthermore, the lack of features to filter products based on users' desired criteria and manage purchase history and favorite lists also creates a poor user experience.

[1925] 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.

[1926] In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on user requests, means for linking payment solutions offered in various countries, means for obtaining product information from multiple e-commerce platforms and comparing and displaying information such as price, availability, and reviews, means for providing a filtering function that allows users to set desired conditions, means for managing product purchase history and favorite lists, and means for notifying users of sales information and price fluctuations via push notifications. This allows users to obtain and compare product information from multiple platforms using a single interface, saving time and effort. Furthermore, the unified payment solution and product information format improves usability and enhances the user experience.

[1927] An "e-commerce platform" is an online system for selling and purchasing goods and services over the Internet.

[1928] "Interconnection" refers to the state in which multiple systems or networks can communicate with each other and exchange data.

[1929] A "conversational interface" is a user interface that allows a user to interact with a system using natural language.

[1930] "Natural language processing technology" is a technology that allows computers to understand and process human language.

[1931] "Product recommendation" is a function that suggests appropriate products based on the user's requests and preferences.

[1932] "Payment solutions" are systems and services that enable safe and efficient online payments.

[1933] "Product Information" refers to detailed information necessary for purchasing a product, such as product price, availability, and reviews.

[1934] The "filtering function" is a function that narrows down search results based on the user's desired conditions.

[1935] "Purchase history" is a record of products a user has purchased in the past.

[1936] A "favorites list" is a list for saving products that a user finds interesting.

[1937] "Push notifications" are a feature that allows an application to send information to a user's device in real time.

[1938] "Sale information" is information about product discounts and special prices.

[1939] "Price fluctuation" refers to the change in the price of a product over time.

[1940] The system for implementing this invention interconnects multiple e-commerce platforms to provide users with a consistent shopping experience. The system includes the following major components:

[1941] 1. Means of interconnecting multiple e-commerce platforms:

[1942] The server accesses the APIs of each e-commerce platform to retrieve product information, allowing users to search for product information from multiple platforms through a single interface.

[1943] 2. Means of providing a conversational interface:

[1944] The server uses natural language processing technology to enable interaction with users, who can search for products and ask questions in natural language via their smartphones or other devices.

[1945] 3. A method for recommending multiple products based on user requirements:

[1946] The server analyzes product information obtained from multiple e-commerce platforms based on the user's search query and recommends the most suitable products.

[1947] 4. Means of integrating payment solutions offered in each country:

[1948] The server will integrate payment solutions from each country, allowing users to seamlessly purchase the products they select.

[1949] 5. A way to retrieve product information from multiple e-commerce platforms and compare prices, availability, reviews, etc.:

[1950] The server integrates the acquired product information and displays a comparison of prices, availability, reviews, etc. to the user, allowing the user to select the most suitable product.

[1951] 6. Means of providing filtering functionality that allows users to set desired criteria:

[1952] The server provides the ability for users to filter search results by setting criteria such as price range, brand, size, etc.

[1953] 7. How to manage your purchase history and wish list:

[1954] The server manages the user's purchase history and favorites list, allowing the user to easily check products they have purchased in the past or products they are interested in.

[1955] 8. Push notifications for sales and price changes:

[1956] The server sends push notifications to users' devices to inform them of sales and price changes in real time.

[1957] Hardware and software used

[1958] Hardware: Smartphones, servers

[1959] Software: Python, Flask (web framework), requests (HTTP request library), natural language processing technology (e.g., Google Cloud Natural Language API)

[1960] Data processing and calculation

[1961] The server receives a search query from the user and sends an HTTP request to the API of each e-commerce platform. The retrieved product information is consolidated within the server, and information such as price, availability, and reviews is displayed for comparison. Search results are narrowed down based on the filtering conditions set by the user. Purchase history and favorites lists are stored in a database, and push notifications are sent to the user's device in real time.

[1962] Specific examples

[1963] When a user searches for "sneakers," the server retrieves product information from multiple e-commerce platforms and displays it as follows:

[1964] Platform 1: Nike Air Max - ¥12,000 - In Stock - 4.5 Review

[1965] Platform 2: Adidas Ultraboost - ¥15,000 - Out of Stock - 4.7 Review

[1966] Platform 3: Puma RS-X - ¥10,000 - In Stock - 4.3 Review

[1967] Prompt Sentence Examples

[1968] "Develop an application that retrieves product information from multiple e-commerce platforms for a user-searched product and displays a comparison of prices, availability, reviews, etc."

[1969] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1970] Step 1:

[1971] A user launches an application on their smartphone and enters a search query (e.g., "sneakers"). The entered search query is sent from the application to a server. The input data is the keyword for the product the user wants to search for. The output data is the search query sent to the server.

[1972] Step 2:

[1973] The server analyzes the received search query and sends HTTP requests to the APIs of multiple e-commerce platforms. The input data is the search query received from the user. The output data is the HTTP requests sent to each e-commerce platform.

[1974] Step 3:

[1975] Each e-commerce platform receives an HTTP request from a server and returns the relevant product information (price, availability, reviews, etc.). The input data is the HTTP request from the server. The output data is the HTTP response containing the product information.

[1976] Step 4:

[1977] The server integrates the product information received from each e-commerce platform and processes the data to compare and display prices, availability, reviews, etc. The input data is the product information received from each e-commerce platform. The output data is the integrated product information.

[1978] Step 5:

[1979] The server returns the integrated product information to the user's smartphone, which the application displays. The input data is the integrated product information sent from the server. The output data is the product information displayed on the user's smartphone.

[1980] Step 6:

[1981] The user sets the desired conditions (price range, brand, size, etc.) based on the displayed product information and performs filtering. The input data are the filtering conditions set by the user. The output data is the filtered product information.

[1982] Step 7:

[1983] The server reprocesses the product information based on the user's filtering conditions and returns the filtered results to the user's smartphone. The input data are the filtering conditions set by the user. The output data is the filtered product information.

[1984] Step 8:

[1985] The user selects the product they wish to purchase and completes the purchase procedure. The server connects with payment solutions provided in each country, enabling the user to smoothly purchase the selected product. The input data is the product selected by the user and payment information. The output data is confirmation that the purchase has been completed.

[1986] Step 9:

[1987] The server stores and manages the user's purchase history and favorites list in a database. The input data is the user's purchase history and favorites list. The output data is the history information stored in the database.

[1988] Step 10:

[1989] The server sends push notifications to users' smartphones when sales information or price fluctuations occur. The input data is sales information or price fluctuation information. The output data is the push notification sent to the user's smartphone.

[1990] Example 2

[1991] Next, a description will be given of Example 2 of Form 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."

[1992] Conventional e-commerce systems require a lot of effort when users search for products, making it difficult to search and purchase efficiently. It is also difficult to integrate multiple e-commerce platforms and provide users with a consistent experience. Furthermore, linking payment solutions offered in each country is complex, making global expansion difficult.

[1993] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions offered in various countries, means for analyzing user input using natural language processing technology, means for inputting prompt sentences to the generative AI model based on the analysis results, and means for presenting responses from the generative AI model to the user. This enables users to search for products in natural language and purchase them efficiently. Furthermore, integrating multiple e-commerce platforms and linking payment solutions from various countries facilitates global expansion.

[1994] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[1995] A "conversational interface" is a user interface that allows a user to interact with a system using natural language.

[1996] A "user request" is a specific request such as a search or purchase that a user makes to the system.

[1997] "Payment Solutions" means payment instruments or systems used to purchase goods and services.

[1998] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language.

[1999] A "generative AI model" is an artificial intelligence model that generates appropriate responses or content based on input data.

[2000] A "prompt sentence" is an instruction sentence input to a generative AI model, and is the sentence that serves as the basis for the model to generate a response.

[2001] "Analysis results" are data obtained after analyzing a user's input using natural language processing techniques.

[2002] A "response" is a reply or result that a generative AI model generates based on a prompt.

[2003] This invention is a system that allows users to search for and purchase products efficiently in natural language. The system interconnects multiple e-commerce platforms, provides a conversational interface, recommends multiple products based on user requests, and integrates payment solutions offered in various countries.

[2004] Hardware and software used

[2005] Hardware:

[2006] High-performance servers (e.g., servers with Intel Xeon processors)

[2007] software:

[2008] Natural language processing libraries (e.g., spaCy, NLTK)

[2009] Database management system (e.g. MySQL)

[2010] Generative AI models (e.g., GPT-3)

[2011] Program processing

[2012] When the server receives input from a user, it analyzes the input using a natural language processing library. The analyzed data is input as a prompt sentence to the generative AI model. The generative AI model generates an appropriate response according to the user's request. For example, if a user inputs "I'm looking for red sneakers," the server searches the database using "red sneakers" as a keyword and presents the search results to the user.

[2013] Specific examples

[2014] A specific example is shown below where the user says, "I'm looking for red sneakers."

[2015] User input: "I'm looking for red sneakers"

[2016] Example prompt: "The user is looking for red sneakers. Retrieve a list of red sneakers from the database and generate an appropriate response."

[2017] The server inputs the above prompt sentence into the generative AI model and receives a response from the model. The server then presents the response to the user. For example, it displays the results in the form of "The following red sneakers were found: [Product List]."

[2018] In this way, a system is realized in which the server, terminals, and users work together to support product searches and purchases.

[2019] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2020] Step 1:

[2021] The user inputs in natural language. The user inputs product search and purchase requests in natural language through the terminal interface. For example, the user inputs "I'm looking for red sneakers." The input data is in text format.

[2022] Step 2:

[2023] The terminal sends the user's input to the server. The terminal sends the user's input to the server in real time. The HTTPS protocol is used for transmission to ensure data security. The input is the user's text data, and the output is the data sent to the server.

[2024] Step 3:

[2025] The server parses the input using a natural language processing library. The server parses the received user input using a natural language processing library (e.g., spaCy, NLTK). Parsing includes tokenization, part-of-speech tagging, dependency analysis, etc. The input is the user's text data, and the output is the parsed data.

[2026] Step 4:

[2027] The server generates a prompt sentence based on the analysis results. The server generates a prompt sentence to input to the generative AI model based on the analysis results. For example, a prompt sentence such as "The user is looking for red sneakers. Please retrieve a list of red sneakers from the database and generate an appropriate response" is created. The input is the analysis result data, and the output is the prompt sentence.

[2028] Step 5:

[2029] The server inputs a prompt sentence into the generative AI model. The server inputs the generated prompt sentence into the generative AI model (e.g., GPT-3). The model generates a response based on the prompt sentence. The input is the prompt sentence, and the output is the generated response.

[2030] Step 6:

[2031] The generative AI model generates a response. The generative AI model generates an appropriate response based on the prompt sentence according to the user's request. For example, it generates the response "The following red sneakers were found: [product list]". The input is the prompt sentence, and the output is the generated response.

[2032] Step 7:

[2033] The server receives the generated response and returns it to the user in an appropriate format. The server receives the response from the generative AI model and converts it into an appropriate format to return to the user, for example, formatting the response in HTML. The input is the generated response and the output is the formatted response.

[2034] Step 8:

[2035] The terminal displays the response from the server to the user. The terminal displays the response received from the server to the user. The user checks the displayed results and decides on the next action. The input is the formatted response, and the output is what is displayed to the user.

[2036] (Application example 2)

[2037] Next, a description will be given of Application Example 2 of Form 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."

[2038] Conventional e-commerce platforms require users to go through multiple steps when searching for and purchasing products, making operation cumbersome. Furthermore, the inability to use voice input for searches or purchases resulted in low user convenience. Furthermore, it was difficult to integrate payment solutions offered in each country, making global expansion difficult.

[2039] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2040] In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions offered in various countries, means for receiving voice input and converting the voice to text, means for analyzing the user's intent using natural language processing technology, means for searching a product database based on the analysis results, means for generating a response based on the search results and converting the text to speech, and means for playing the generated speech to the user. This allows users to search for and purchase products through natural conversation, simplifying operation and improving convenience. It also enables the integration of global payment solutions, facilitating international expansion.

[2041] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[2042] A "conversational interface" is a user interface that allows a user to interact with a system using natural language.

[2043] "User requests" are specific instructions or requests, such as searches or purchases, that a user makes to the system.

[2044] "Means for recommending products" is a function for selecting and presenting appropriate products based on the user's requests.

[2045] "Payment solutions" are systems and services used to process payments for the purchase of goods and services.

[2046] "Voice input" refers to voice data uttered by the user through a microphone.

[2047] "Speech-to-text" is the process of analyzing and converting speech data into corresponding text data.

[2048] "Natural language processing technology" is a technology that allows computers to understand and analyze human language.

[2049] "User intent" refers to the goals and desires that users have for the system.

[2050] A "product database" is a database that stores information about products.

[2051] The "means for generating a response" is a function for creating an appropriate reply to a user request.

[2052] "Text-to-speech" is the process of analyzing text data and converting it into corresponding audio data.

[2053] "Generated speech" refers to speech data created by text-to-speech conversion.

[2054] A system for implementing the present invention has the following configuration: a server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions offered in various countries, means for receiving voice input and converting the voice to text, means for analyzing the user's intent using natural language processing technology, means for searching a product database based on the analysis results, means for generating a response based on the search results and converting the text to voice, and means for playing the generated voice to the user.

[2055] Hardware and software used

[2056] Hardware: Smartphone (iOS or Android)

[2057] software:

[2058] Natural language processing libraries (e.g., Google Cloud Natural Language API, spaCy)

[2059] Databases (e.g., Firebase, MongoDB)

[2060] Front-end frameworks (e.g., React Native)

[2061] Backend frameworks (e.g., Node.js, Express)

[2062] Speech recognition API (e.g., Google Cloud Speech-to-Text API)

[2063] Text-to-speech API (e.g., Google Cloud Text-to-Speech API)

[2064] Data processing and calculation

[2065] 1. Acquiring voice input: The user inputs voice using the smartphone microphone. The voice data is sent to the server in real time.

[2066] 2. Speech-to-text conversion: The server converts the speech data into text data using the Google Cloud Speech-to-Text API.

[2067] 3. Natural Language Processing: Text data is parsed using Google Cloud Natural Language API or spaCy to extract user intent.

[2068] 4. Product search: Based on the analysis results, search the product database stored in Firebase or MongoDB.

[2069] 5. Response generation: Based on the search results, a response is generated to present appropriate product information to the user.

[2070] 6. Text-to-Speech Conversion: The generated response is converted into audio data using the Google Cloud Text-to-Speech API.

[2071] 7. Audio playback: The generated audio data is played back to the user through the smartphone speaker.

[2072] Specific examples

[2073] When a user says, "I'm looking for red sneakers," the system processes them as follows:

[2074] 1. Take voice input and convert it to text.

[2075] 2. Analyze the text and extract "red sneakers" as a search keyword.

[2076] 3. Search the database for products that match "red sneakers."

[2077] 4. Based on the search results, generate a response such as "Here are the search results for red sneakers."

[2078] 5. Convert the response into speech and play it back to the user.

[2079] Prompt Sentence Examples

[2080] User: "I'm looking for red sneakers."

[2081] System: "Searching for red sneakers. Please wait."

[2082] System: "Here are the search results for red sneakers. There are Model A from XXXX, Model B from XXX, and so on. Which one would you like?"

[2083] In this way, users can search for and purchase products through natural conversation.

[2084] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2085] Step 1:

[2086] The user inputs voice using the microphone on their smartphone, and the voice data is sent to the server in real time.

[2087] Input: User's voice

[2088] Output: Audio data

[2089] Specific action: The user says, "I'm looking for red sneakers."

[2090] Step 2:

[2091] The server converts the audio data into text data using the Google Cloud Speech-to-Text API.

[2092] Input: Audio data

[2093] Output: Text data

[2094] Specific operation: The server receives the voice data and converts it into text: "I'm looking for red sneakers."

[2095] Step 3:

[2096] The server uses Google Cloud Natural Language API or spaCy to parse the text data and extract the user's intent.

[2097] Input: Text data

[2098] Output: Analysis result (user intent)

[2099] Specific operation: The server analyzes the text data and extracts "red sneakers" as a search keyword.

[2100] Step 4:

[2101] Based on the analysis results, the server searches the product database stored in Firebase or MongoDB.

[2102] Input: Analysis results (search keywords)

[2103] Output: Search results (product information)

[2104] Specific operation: The server searches the database for products that match "red sneakers."

[2105] Step 5:

[2106] The server generates a response based on the search results to present appropriate product information to the user.

[2107] Input: Search results (product information)

[2108] Output: Response text

[2109] What happens: The server generates a response like, "Here are the search results for red sneakers."

[2110] Step 6:

[2111] The server converts the response text into audio data using the Google Cloud Text-to-Speech API.

[2112] Input: Response text

[2113] Output: Audio data

[2114] Specific operation: The server receives the response text and converts it into voice data.

[2115] Step 7:

[2116] The server transmits the generated audio data to the smartphone and plays it back to the user through the smartphone's speaker.

[2117] Input: Audio data

[2118] Output: Audio output

[2119] Specific operation: The smartphone receives the audio data and plays it back to the user.

[2120] Example 3

[2121] Next, a third embodiment of the third embodiment will be described. 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."

[2122] With conventional e-commerce systems, when users purchase products using their own local payment methods, it is difficult to accommodate the different payment solutions in each country. Furthermore, there is a lack of an interface that allows users to select their preferred payment method and complete the payment smoothly. This leads to a poor user experience and complicated purchasing procedures.

[2123] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[2124] In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions offered in each country, means for selecting a corresponding payment module based on the user's country information, means for presenting payment methods to the user through the selected payment module, means for verifying the payment information entered by the user and performing payment processing, and means for sending a payment completion notification to the user, thereby enabling the user to smoothly purchase products using the payment method of their own country.

[2125] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[2126] A "conversational interface" is an interface that allows users to interact with a system using natural language to perform operations and obtain information.

[2127] "Payment Solutions" is a collective term for technologies and services used to process online payments.

[2128] A "payment module" is a software component that implements a particular payment method.

[2129] "User country information" refers to information that identifies the country from which the user is accessing the site, including IP address and user account information.

[2130] "Payment method" refers to the means a user chooses to pay for goods or services, and includes credit cards, bank transfers, electronic money, etc.

[2131] "Payment Information" refers to payment information entered by the user based on the payment method selected, including credit card number and bank account information.

[2132] "Payment processing" refers to a series of operations required to actually complete a payment based on the payment information entered by the user.

[2133] The "payment completion notification" is a message to inform the user that the payment has been successfully completed.

[2134] This invention is a system that allows users to purchase products using their own country's payment method. The system interconnects multiple e-commerce platforms, provides a conversational interface, and recommends multiple products based on the user's request. It also connects payment solutions offered in each country, selects a corresponding payment module based on the user's country information, and presents payment methods to the user through the selected payment module. It also verifies the payment information entered by the user, processes the payment, and notifies the user that the payment has been completed.

[2135] Hardware and software used

[2136] This system uses the following hardware and software:

[2137] Servers: Database servers, web servers, payment gateway servers, etc.

[2138] Devices: PCs, smartphones, tablets, etc. used by users

[2139] Software: Conversational interfaces using natural language processing technology, payment modules, database management systems, middleware for processing API requests, etc.

[2140] Specific examples

[2141] For example, consider a case where a Japanese user purchases a product from an online shop. The user accesses the online shop's website or application and selects the product they wish to purchase. The terminal sends the product information selected by the user and the user's country information to the server. The server analyzes the received country information and selects the payment module corresponding to that country. For a Japanese user, the server selects the credit card, bank transfer, or convenience store payment module.

[2142] The server uses the selected payment module to present the user with available payment methods. The user selects the desired method from the presented payment methods and enters the required information (credit card number, bank account information, etc.). The server verifies the entered payment information and processes the payment. If the payment is successful, the server sends a purchase completion notification to the user. The terminal receives the purchase completion notification from the server and displays it to the user.

[2143] Prompt Sentence Examples

[2144] Please explain the process of the system that allows Japanese users to choose between credit card, bank transfer, and convenience store payment when purchasing products from an online shop.

[2145] In this way, the system allows users to smoothly purchase products using the payment method of their own country. The flow of the identification process in the third embodiment will be described with reference to FIG.

[2146] Step 1:

[2147] The user selects an item and begins the checkout process.

[2148] Input: A user visits an online shopping website or application and selects the product they want to purchase.

[2149] What happens: The user clicks the "Add to Cart" button, then clicks the "Proceed to Checkout" button to begin the purchase process.

[2150] Output: The selected product information (product ID, quantity, price, etc.) is saved to the device.

[2151] Step 2:

[2152] The device sends the product information selected by the user and the user's country information to the server.

[2153] Input: Product information selected by the user and user country information (obtained from IP address and user account information)

[2154] Specific operation: The device uses an HTTP request to send data including product information and country information to the server.

[2155] Output: The server receives the product information and country information.

[2156] Step 3:

[2157] The server selects a corresponding payment module based on the received country information.

[2158] Input: User's country information received by the server

[2159] Specific operation: The server retrieves payment options for the relevant country (credit card, bank transfer, convenience store payment, etc.) from the database.

[2160] Output: The selected payment module information is saved on the server.

[2161] Step 4:

[2162] The server presents the payment method to the user through the selected payment module.

[2163] Input: Information about the payment module selected by the server

[2164] Specific operation: The server generates an HTML form and displays a screen for the user to enter credit card information and instructions for bank transfer.

[2165] Output: The user is presented with the available payment methods.

[2166] Step 5:

[2167] The user selects the desired payment method from the options presented and enters the required information.

[2168] Input: The payment method selected by the user and any required information (credit card number, bank account information, etc.)

[2169] Specific behavior: The user enters their credit card information and clicks the "Pay" button.

[2170] Output: The entered payment information is saved on the device and sent to the server.

[2171] Step 6:

[2172] The server verifies the entered payment information and processes the payment.

[2173] Input: Payment information entered by the user

[2174] Specific behavior: The server sends an API request to the payment gateway (e.g., payment service provider) to receive authorization for the payment.

[2175] Output: The result of the payment (success or failure) is returned to the server.

[2176] Step 7:

[2177] The server sends a notification to the user that the purchase is complete.

[2178] Input: Payment result if payment is successful

[2179] Specific behavior: The server generates a response containing the message "Purchase completed" and sends it to the user's device.

[2180] Output: A notification of successful purchase is sent to the user's device.

[2181] Step 8:

[2182] The device receives a purchase completion notification from the server and displays it to the user.

[2183] Input: Purchase completion notification sent from the server

[2184] What happens: The device displays the message "Purchase complete" on the screen.

[2185] Output: The user sees a message confirming the purchase.

[2186] (Application example 3)

[2187] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[2188] With conventional e-commerce systems, when users purchase products using their own country's payment method, it is difficult to support different payment solutions in each country. In addition, it is time-consuming for users to select the appropriate payment option when purchasing a product, and there are delays in confirmation notifications after payment is completed. This creates an issue that impairs the user experience.

[2189] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for interconnecting multiple e-commerce platforms, means for providing a conversational interface, means for recommending multiple products based on a user's request, means for linking payment solutions offered in each country, means for displaying appropriate payment options based on the user's country information, means for processing payment using the selected payment option, and means for sending a confirmation notice after payment is completed. As a result, when a user purchases a product using the payment method of their home country, appropriate payment options are automatically displayed, enabling the user to complete payment quickly and reliably.

[2190] An "e-commerce platform" is an online system for buying and selling goods and services over the Internet.

[2191] A "conversational interface" is a user interface that allows a user to interact with a system using natural language.

[2192] "User requests" refer to operations or instructions that users give to the system, such as product searches or purchases.

[2193] "Product recommendation means" refers to algorithms or systems that present appropriate products based on the user's requests and past behavioral history.

[2194] "Payment Solution" means a method or system for making payments for the purchase of goods or services.

[2195] "Payment Options" means the payment methods that users can choose when purchasing goods or services.

[2196] "Payment processing" refers to the series of steps taken to actually complete a payment using the payment option selected by the user.

[2197] A "confirmation notice" is a message or notification that informs the user that a payment has been completed.

[2198] ...

Claims

1. A means for interconnecting a plurality of electronic commerce platforms; a means for providing a conversational interface; A means for analyzing user requests using natural language processing technology; A means for generating a prompt sentence for instructing a search for a product in response to a user request; A search means for searching the plurality of electronic commerce platforms for a product requested by a user using the generated prompt sentence and the generated AI model; A means for recommending multiple products to a user based on the search results; and A means to link payment solutions provided in each country, A means for selecting a corresponding payment module based on the user's country information; a means for presenting payment options to the user through the selected payment module; means for verifying payment information entered by a user and processing the payment; A system including:

2. means for recognizing an emotional state of the user using an emotion engine; the search means searches for products taking into account the recognized emotional state of the user; The system of claim 1 .

3. The plurality of e-commerce platforms are e-commerce platforms provided across different countries or regions; The system of claim 1 .

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