System

Abstract

A system is provided.SOLUTION: This system includes a means for analyzing the action history of a user by using generation artificial intelligence, a means for selecting the optimal web service, a means for registering the selected web service in a portal based on the identification information of the user, a means for performing authentication by using the identification information of the user, and a means for providing the authenticated web service.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In recent years, when using web services, users are required to register an ID and password and undergo identity authentication procedures. These procedures are often cumbersome and time-consuming for users. Furthermore, there are cases where the services they have taken the trouble to register for are not useful to them, resulting in a lack of convenience. Given this background, there is a need for the development of a system that reduces the burden on users and enables them to efficiently use the most appropriate services. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides a system including a means for analyzing a user's behavioral history using generative artificial intelligence, a means for selecting an optimal web service, a means for registering the selected web service in a portal based on the user's identification information, a means for performing authentication using the user's identification information, and a means for providing the authenticated web service. The present invention also provides a system further including a means for collecting the user's behavioral history and a means for storing the collected behavioral history in a database, and a system including a means for using information from a personal identification number card as the user's identification information.

[0006] "Generative AI" refers to artificial intelligence technology used to analyze a user's behavioral history and select the most suitable web service.

[0007] "Behavioral history" refers to the operations and access records performed by a user on a web browser or application.

[0008] "Web services" refers to various online services provided over the Internet.

[0009] "Identification information" refers to information for uniquely identifying a user, and includes information on a personal identification number card, etc.

[0010] "Portal" refers to a platform for managing and providing services based on user identification information.

[0011] "Authentication" refers to the process of verifying a user's identity.

[0012] A "personal identification number card" refers to a card issued by a state or institution to uniquely identify an individual, including the My Number Card. [Brief explanation of the drawings]

[0013] [Figure 1]1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0014] 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.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0017] 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.

[0018] 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.

[0019] 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.

[0020] 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."

[0021] [First embodiment]

[0022] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0034] The present invention provides a system that collects a user's behavioral history, selects the most suitable web service based on that history, and allows the user to use the service quickly and easily using their personal identification number card.

[0035] The system mainly includes the following components:

[0036] 1. Behavioral history collection module

[0037] 2. Generative artificial intelligence (generative AI)

[0038] 3. Service Selection Module

[0039] 4. Portal Registration Module

[0040] 5. Authentication Module

[0041] 6. Service Provision Module

[0042] Behavioral history collection module

[0043] This module collects various operations and access records performed by users on web browsers and applications. This module records behavioral data such as the URL of the page viewed, the viewing time, and the links clicked, and sends this data to the server at regular intervals.

[0044] Generative artificial intelligence (generative AI)

[0045] The server stores the user's behavioral history data in a database, which is then analyzed by the Generative AI, which identifies the user's interests and needs and lists the optimal web services that match them.

[0046] Service Selection Module

[0047] The generative AI narrows down the list of web service candidates to the most suitable one, and the server then decides on the final service to offer to the user.

[0048] Portal Registration Module

[0049] The server registers the optimal web service in the portal based on the user's identification information. Specifically, it registers the selected service using information from the user's personal identification number card (e.g., My Number card).

[0050] Authentication Module

[0051] When a user connects a personal identification number card to a terminal, the terminal uses a card reader to read the card information and sends an authentication request to the server. The server performs authentication based on this information and notifies the terminal of the success or failure of the authentication.

[0052] Service Delivery Module

[0053] Once authentication is complete, the selected web service is provided to the user, allowing the user to quickly use the service without having to enter an ID or password.

[0054] Specific examples

[0055] Example 1: Using an e-commerce site

[0056] When a user browses fashion items, the behavioral history collection module collects access records and sends them to the server. The generation AI analyzes this data and determines that the user is interested in fashion items. The service selection module then selects the most suitable fashion e-commerce site, and the portal registration module registers this information in My Number Portal. The user is authenticated by connecting their My Number card to a terminal, and after authentication, they can start shopping on the e-commerce site without entering their ID / PW.

[0057] Example 2: Using SNS services

[0058] If a user browses multiple SNS sites, the behavioral history collection module collects access records and sends them to the server. The generation AI analyzes this data and determines that the user is interested in SNS platforms. The service selection module then selects the most suitable SNS site, and the portal registration module registers this information in My Number Portal. The user is authenticated by connecting their My Number card to their PC, and after authentication, they can use the SNS site without entering their ID / PW.

[0059] In this way, the present invention allows users to omit the complicated IDPW registration and authentication procedures and to use optimal web services quickly and easily.

[0060] The processing flow will be explained below.

[0061] Step 1:

[0062] A user browses a web page. The user's device records the user's behavioral data (URL of the page viewed, viewing time, links clicked, etc.).

[0063] Step 2:

[0064] The device transmits behavioral data to the server at a fixed frequency.

[0065] Step 3:

[0066] The server receives the user's behavior data sent from the terminal and stores it in a database.

[0067] Step 4:

[0068] The server runs the generation AI based on the behavioral data stored in the database. The generation AI analyzes the user's behavioral patterns and identifies the user's interests and needs.

[0069] Step 5:

[0070] The server generates a list of optimal web service candidates based on the results of the AI's analysis.

[0071] Step 6:

[0072] The server selects the most suitable web service for the user from among the candidate web services listed.

[0073] Step 7:

[0074] The server registers the selected web service with the portal based on the user's identification information, using the user's personal identification number card information for registration.

[0075] Step 8:

[0076] The user connects the personal identification number card to the terminal, which uses a card reader to read the card information and sends an authentication request to the server.

[0077] Step 9:

[0078] The server checks the received authentication information and compares it with the data in My Number Portal.

[0079] Step 10:

[0080] The server notifies the terminal of the success or failure of the authentication, and the terminal displays the authentication result to the user.

[0081] Step 11:

[0082] If authentication is successful, the user can use the selected web service. The user can use the service quickly and easily without entering an ID or password.

[0083] Example 1

[0084] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0085] Today's Internet users must manage multiple IDs and passwords to access a wide variety of web services, resulting in cumbersome operations and information security risks. Furthermore, there is no established method for selecting the most suitable service for a user and providing it quickly and easily. Therefore, there is a need for a system that automatically selects the most suitable web service based on a user's behavioral history and enables quick access using personal identification information.

[0086] 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.

[0087] In this invention, the server includes means for collecting user behavior history, means for transmitting the collected behavior history to the server, and means for storing the behavior history in a database. This makes it possible to identify the user's interests and needs through analysis based on the user's behavior history, and to select and quickly provide the most appropriate web service.

[0088] "User behavior history" refers to the operations and access records performed by users on web browsers and applications. Specifically, it includes information such as the URLs of pages viewed, the duration of viewing, and links clicked.

[0089] A "server" refers to a computer system that provides services such as data storage, management, and analysis on a network.

[0090] "Generative AI" refers to AI technology that analyzes data to identify user interests and needs, particularly in selecting the most appropriate web services based on a user's behavioral history.

[0091] A "database" refers to a system for organizing and storing information. It efficiently stores data such as behavioral history and makes it available for later analysis and reference.

[0092] "Web services" refers to various online services provided via the Internet, including e-commerce sites and social networking sites.

[0093] A "portal" is a web page or system that acts as a gateway for users to access, providing an interface for centrally managing multiple services.

[0094] "Authentication" refers to the process of verifying access rights using user identification information, such as a personal identification number card.

[0095] "Personal identification number card" refers to a card that uniquely identifies a specific individual. This includes My Number cards.

[0096] "Prompt sentences" are instructions used by the generative AI when analyzing data. They set conditions to list the most suitable web services based on the user's behavioral history.

[0097] The present invention provides a system that collects a user's behavioral history, selects the most suitable web service based on that history, and allows the user to use the service quickly and easily using their personal identification number card.

[0098] 1. Collecting behavioral history

[0099] It collects various operations and access records performed by users on web browsers and applications. Specifically, it records behavioral data such as the URLs of pages viewed, viewing times, and links clicked. This data is collected by the behavioral history collection module and sent to the server at regular intervals.

[0100] 2. Data storage

[0101] The server receives the data sent from the behavioral history collection module and stores it in a database. The database is a system for efficiently managing collected behavioral data such as URLs, click history, and viewing time.

[0102] 3. Data Analysis

[0103] A generative artificial intelligence (generative AI) on the server periodically analyzes the behavioral history data in the database. The generative AI identifies the user's interests and needs and lists the optimal web services that match them. The generative AI uses the following prompt: "Based on the web pages the user visited most frequently in the past week and the time spent viewing those pages, please list the optimal web services for this user."

[0104] 4. Service Selection

[0105] Based on the analysis results from the generative AI, the service selection module narrows down the optimal web services. For example, if multiple fashion-related web services are listed as candidates, the module will select the most suitable service from among them.

[0106] 5. Registering for the Service

[0107] The server registers the selected web service with the portal based on the user's identification information, specifically, the service is registered using the user's personal identification number card (e.g., personal identification number card), and this information is managed securely and efficiently.

[0108] 6. User Authentication

[0109] The user authenticates by connecting a personal identification number card to the terminal. The terminal reads the card information using a card reader and sends an authentication request to the server. The server performs authentication based on this information and notifies the terminal of the success or failure of the authentication.

[0110] 7. Provision of Services

[0111] The purpose of this service is to provide selected web services to users who have completed authentication, allowing them to quickly use the services without having to enter their ID or password.

[0112] Specific examples

[0113] Example 1: Using an e-commerce site

[0114] When a user browses fashion items, the behavioral history collection module collects the access record and sends it to the server. The generation AI analyzes this data and determines that the user is interested in fashion items. The service selection module then selects the most suitable fashion e-commerce site. The server uses the portal registration module to associate this information with the user's personal identification number card information and registers it in the portal. When the user connects their personal identification number card to their device, they are authenticated and can directly access the service.

[0115] Example 2: Using SNS services

[0116] If a user browses multiple social networking sites, the behavioral history collection module collects their access records and sends them to the server. The generation AI analyzes this data and determines whether the user is interested in social networking platforms. The service selection module then selects the most suitable social networking site. The server uses the portal registration module to associate this information with the user's personal identification number card information and register it in the portal. When the user connects their personal identification number card to their device, authentication is performed and they can directly access the service.

[0117] In this way, the system of the invention selects the most suitable web service based on the user's behavioral history and provides it quickly and easily, thereby greatly improving user convenience.

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

[0119] Step 1: User uses web browser or application

[0120] A user uses a web browser or application to browse fashion items or social networking sites. Specifically, the user clicks on an item on a fashion e-commerce site and views its details page. The input at this time is the user's clicks and browsing actions, and the output is the history of the pages the user viewed. The behavioral history collection module captures this in real time.

[0121] Step 2: Send behavioral data to the server

[0122] The device sends the collected behavioral history data to the server at a fixed interval. Specifically, every five minutes, the device sends the URLs of the pages the user viewed, the viewing time, and information about the links they clicked to the server. The data sent is structured in JSON format, etc. The input is the user's behavioral data, and the output is the data sent to the server.

[0123] Step 3: Save the behavioral data to the database

[0124] The server stores the behavioral data it receives in a database. Specifically, it creates a database entry and records the received URL, viewing time, and click history. The input is the behavioral data received by the server, and the output is the data stored in the database.

[0125] Step 4: Generate behavioral data and analyze it with AI

[0126] The generation AI on the server periodically analyzes the behavioral history data stored in the database. Specifically, the generation AI model is given a prompt: "Based on the web pages the user accessed most frequently in the past week and the amount of time spent viewing those pages, please list the most suitable web services for this user." The input is the behavioral history data stored in the database, and the output is a list of web services that meet the user's needs.

[0127] Step 5: Choose the best web service

[0128] The service selection module narrows down the optimal web services based on the analysis results of the generation AI. For example, from the three fashion sites listed by the generation AI, it ultimately selects the site that best suits the user's interests. The input is the analysis results of the generation AI, and the output is the selected web service.

[0129] Step 6: Register your service in the portal

[0130] The server registers the selected web service in the portal based on the user's identification information. Specifically, it associates a service ID with the user's identification information (e.g., information from a personal identification number card) and registers it in a database. The input is the selected web service and the user's identification information, and the output is the service information registered in the portal.

[0131] Step 7: Authenticate the user

[0132] A user connects a personal identification number card to a terminal, and the terminal uses a card reader to read the card information. The terminal then sends the read information to a server, which receives it at a specific endpoint and authenticates the user. The input is the personal identification number card information, and the output is the success or failure of the authentication.

[0133] Step 8: Provide the Service

[0134] The server provides the selected web service to the user after successful authentication. Specifically, the link or dashboard that the user can access after successful authentication is displayed. The input is the authentication success information, and the output is the web service that the user can use.

[0135] In this way, the system of the present invention goes through a series of processing steps to quickly and easily provide optimal web services to users.

[0136] (Application example 1)

[0137] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0138] In conventional virtual stores, it is difficult for users to quickly and easily find the products they are interested in, and the authentication process requires the input of IDs and passwords, making the user experience cumbersome.Furthermore, there is a lack of effective ways to provide personalized services.

[0139] 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.

[0140] In this invention, the server includes means for analyzing a user's behavioral history using generative artificial intelligence, means for selecting an optimal web service, means for registering the selected product information in a portal in a virtual store based on information from a personal identification number card, means for performing authentication using the personal identification number card, and means for providing the optimal product in the virtual store after authentication is complete. This allows users to quickly and easily find and purchase personalized products without having to enter an ID or password.

[0141] - "Generative AI" is AI that analyzes a user's behavioral history and identifies their interests and needs.

[0142] "Behavioral history" refers to the history of browsing and operations performed by a user on a web browser or application, and specifically includes data such as the URLs accessed and the duration of their stay.

[0143] "Web services" refers to various services provided via the Internet, and in this context refers specifically to personalized products and services based on the user's interests.

[0144] "Portal" means a website or application that aggregates certain information or services and allows users to access them in a single location.

[0145] A "personal identification number card" is a card that contains a unique identification number, typically a My Number card, and is used to authenticate a user.

[0146] "Authentication" is the process of verifying a user's identity using the user's personal identification number card.

[0147] A "virtual store" is a store operated on the Internet where users can browse and purchase products in a virtual space.

[0148] In this invention, we build a system that collects user behavior history, analyzes it using a generation AI, and provides optimal products in a virtual store. The specific form is shown below.

[0149] Collecting behavioral history

[0150] The device records the products viewed by the user in the virtual store and the time spent there. The collected data includes the URL of the product page, the viewing time, and the links clicked. This behavioral data is sent to the server at a fixed interval.

[0151] Analysis by generative AI

[0152] The server stores the collected behavioral history data in a database. The generative AI analyzes this data and identifies the user's interests and needs. The generative AI is implemented using machine learning libraries such as TensorFlow and PyTorch.

[0153] Selecting the best service

[0154] Based on the results of the analysis by the generation AI, the server lists the most suitable products for the user.Then, the service selection module narrows down the most suitable product candidates and registers them in the portal based on the user's identification information.

[0155] Portal Registration

[0156] The selected product information is registered in the portal along with the user's personal identification number card information. This process is handled by the portal registration module.

[0157] certification

[0158] When a user connects a personal identification number card to a terminal, the terminal reads the card information using a card reader, then sends an authentication request to the server, which uses an authentication module to authenticate the user and notifies the terminal of the result.

[0159] Service provision

[0160] If authentication is successful, the server provides the selected product information to the user, allowing the user to quickly and easily purchase products in the virtual store without having to enter an ID or password.

[0161] Specific examples

[0162] For example, you can use prompts like the following to feed data into a generative AI model:

[0163] In the past week, users have:

[0164] View the product page of URL1 for 30 seconds

[0165] View the product page of URL2 for 15 seconds

[0166] View the product page of URL3 for 10 seconds

[0167] Based on this data, the user's preferences are analyzed, the most suitable fashion items are selected, and the items are registered on My Number Portal. After the user completes authentication using their personal identification number card, the selected fashion items are suggested.

[0168] In this way, the embodiment of the present invention allows users to quickly and easily find and purchase the most suitable product based on their behavioral history, and also simplifies the authentication procedure, thereby significantly improving the user experience.

[0169] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0170] Step 1: Collecting behavioral history

[0171] The terminal collects various operations and browsing data (e.g., URL of product page and browsing time) performed by the user within the virtual store. The input is the user's operation data, which is temporarily stored in a local database. The output is the collected behavioral data. Specifically, it records the products the user clicked on and the viewing time.

[0172] Step 2: Sending Activity History

[0173] The device sends the collected behavioral data to the server at a fixed frequency. The input is the behavioral history stored in the local database. The output is the behavioral data sent to the server. Specifically, the data is sent using an HTTP POST request.

[0174] Step 3: Save your activity history

[0175] The server stores the received behavioral history data in a database. The input is the behavioral history data sent from the device. The output is the history data stored in the database. Specifically, it performs a write operation to the NoSQL database.

[0176] Step 4: Analyzing behavioral history

[0177] The server uses generative AI to analyze the behavioral history data. The input is the behavioral history data stored in the database. The output is the analysis results about the user's interests and needs. Specifically, a machine learning model (e.g., TensorFlow) is used to analyze the data and identify the user's preferences.

[0178] Step 5: Select the best service

[0179] The server generates a list of optimal products and services based on the analysis results of the generation AI. The input is the analysis results of the behavioral history. The output is a list of optimal products and services. Specifically, it generates a list of products that match the user's preferences and temporarily stores this.

[0180] Step 6: Portal Registration

[0181] The server registers the selected product information along with the personal identification number card information in the portal. The input is the optimal product list and the personal identification number card information. The output is the information registered in the portal. Specifically, the server uses the user's identification information to register product information in My Number Portal.

[0182] Step 7: Authentication

[0183] When a user connects a personal identification number card to a terminal, the terminal uses a card reader to read the card information and sends an authentication request to the server. The input is the personal identification number card information. The output is the authentication result. Specifically, an HTTP request is sent, and the server verifies it using the authentication module.

[0184] Step 8: Service Delivery

[0185] If authentication is successful, the server provides the selected product information to the user. The input is the authentication result and a list of optimal products. The output is the product information provided to the user. Specifically, based on the authentication result, the server performs an operation to display the optimal products on the user's screen.

[0186] The above processing steps realize a system that allows users to quickly and easily purchase individually personalized products without having to go through complicated authentication procedures.

[0187] 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.

[0188] The present invention provides a system that collects a user's behavioral history and emotional data, selects the most suitable web service based on that data, and allows the user to use the service quickly and easily using their personal identification number card.

[0189] The system mainly includes the following components:

[0190] 1. Behavioral history collection module

[0191] 2. Emotion Engine

[0192] 3. Generative artificial intelligence (generative AI)

[0193] 4. Service Selection Module

[0194] 5. Portal Registration Module

[0195] 6. Authentication Module

[0196] 7. Service Provision Module

[0197] Behavioral history collection module

[0198] This module collects various operations and access records performed by users on web browsers and applications. This module records behavioral data such as the URL of the page viewed, the viewing time, and the links clicked, and sends this data to the server at regular intervals.

[0199] Emotion Engine

[0200] The engine recognizes users' emotions in real time and collects emotional data. It analyzes emotions from users' facial expressions, tone of voice, input text, etc. and generates data.

[0201] Generative artificial intelligence (generative AI)

[0202] The server stores the user's behavioral and emotional data in a database, which is then analyzed by the Generative AI, which analyzes the user's behavioral patterns and emotional state to identify the user's interests and needs.

[0203] Service Selection Module

[0204] Based on the results of the analysis by the generative AI, it lists the most suitable web service candidates for the user and selects the service that is further optimized using emotional data.

[0205] Portal Registration Module

[0206] The server registers the most suitable web service to the portal based on the user's identification information. Specifically, it registers the selected service using information from the user's personal identification number card (e.g., My Number card).

[0207] Authentication Module

[0208] When a user connects a personal identification number card to a terminal, the terminal uses a card reader to read the card information and sends an authentication request to the server. The server performs authentication based on this information and notifies the terminal of the success or failure of the authentication.

[0209] Service Delivery Module

[0210] Once authentication is complete, the selected web service is provided to the user, allowing the user to quickly use the service without having to enter an ID or password.

[0211] Specific examples

[0212] Example 1: Using an e-commerce site

[0213] When a user browses fashion items, the behavioral history collection module collects access records and sends them to the server. The emotion engine analyzes the user's facial expressions and tone of voice via the webcam and microphone to collect emotional data such as joy and excitement. The generative AI analyzes this data and determines that the user is interested in fashion and has favorable feelings toward specific brands. The service selection module then selects the most suitable fashion e-commerce site, and the portal registration module registers this information in My Number Portal. The user is authenticated by connecting their My Number card to a terminal, after which they can start shopping on the e-commerce site without entering their ID / PW.

[0214] Example 2: Using SNS services

[0215] When a user browses multiple social networking sites and posts comments on posts, the behavioral history collection module collects access records and comments and sends them to the server. The emotion engine analyzes the user's emotions from the text and detects that the user has a strong interest in a particular topic. The generation AI analyzes this data and determines that the user has a strong interest in the social networking platform. The service selection module then selects the most suitable social networking site, and the portal registration module registers this information in My Number Portal. The user is authenticated by connecting their My Number card to their PC, and after authentication, they can use the social networking site without entering their ID / PW.

[0216] In this way, this invention allows users to omit the cumbersome IDPW registration and authentication procedures and quickly and easily use the most suitable web services. In addition, by taking into account the user's emotions, it becomes possible to provide more personalized services.

[0217] The processing flow will be explained below.

[0218] Step 1:

[0219] A user browses a web page. The user's device records the user's behavioral data (URL of the page viewed, viewing time, links clicked, etc.).

[0220] Step 2:

[0221] The emotion engine analyzes the user's facial expressions and tone of voice via a webcam and microphone to obtain the user's emotional data (happiness, excitement, sadness, etc.). The obtained emotional data is then recorded on the device.

[0222] Step 3:

[0223] The device transmits user behavioral data and emotion data to the server at a fixed frequency. The transmitted data includes behavioral history and emotion recognition results.

[0224] Step 4:

[0225] The server receives the user's behavioral and emotional data and stores this data in a database.

[0226] Step 5:

[0227] The server runs a generative AI based on the behavioral and emotional data stored in the database. The generative AI analyzes the user's behavioral patterns and emotional state to identify the user's interests and needs.

[0228] Step 6:

[0229] The server generates a list of optimal web service candidates based on the results of the AI's analysis.

[0230] Step 7:

[0231] The server considers the emotion data and selects the most suitable web service for the user from the listed web service candidates.

[0232] Step 8:

[0233] The server registers the selected web service with the portal based on the user's identification information, specifically, by using the user's personal identification number card to register the selected service.

[0234] Step 9:

[0235] The user connects the personal identification number card to the terminal, which uses a card reader to read the card information and sends an authentication request to the server.

[0236] Step 10:

[0237] The server checks the received authentication information and compares it with the data in My Number Portal.

[0238] Step 11:

[0239] The server notifies the terminal of the success or failure of the authentication, and the terminal displays the authentication result to the user.

[0240] Step 12:

[0241] If authentication is successful, the server provides the selected web service to the user, who can then use the service quickly and easily without having to enter an ID or password.

[0242] Example 2

[0243] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0244] When using current web services, users often need to authenticate using an ID and password, which is a cumbersome process. Furthermore, personalized services based on users' behavioral history and emotional data are insufficient, making it difficult for them to quickly access the optimal web service that meets their interests and needs. This leads to a poor user experience and impacts service usage rates.

[0245] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for collecting a user's behavioral history, means for recognizing the user's emotions and collecting emotional data, means for analyzing the user's behavioral history and emotional data using generative artificial intelligence, means for selecting an optimal web service, means for registering the selected web service in a portal based on the user's identification information, means for performing authentication using the user's identification information, and means for providing the authenticated web service. This allows the user to quickly and easily use the optimal web service without having to enter a complicated ID or password. Furthermore, providing services based on the behavioral history and emotional data can realize a personalized user experience.

[0246] "Behavioral history" refers to the various operations and access records performed by a user on a web browser or application.

[0247] "Emotional Data" refers to emotional information parsed from a user's facial expressions, tone of voice, and input text.

[0248] "Generative artificial intelligence (generative AI)" refers to artificial intelligence that analyzes a user's behavioral history and emotional data to identify their interests and needs.

[0249] "Portal" refers to an interface for registering the most suitable web services based on a user's identity.

[0250] "Authentication" refers to the process by which a user verifies their access rights using identifying information such as a personal identification number card.

[0251] "Web Services" refers to various online services provided to users via the Internet.

[0252] "Personal Identification Number Card" refers to a card that contains a number that uniquely identifies a user.

[0253] "Database" refers to a system for storing and analyzing collected behavioral history and emotional data.

[0254] The present invention relates to a system that collects user behavioral history and emotion data, selects the most suitable web service based on the collected data, and enables the user to quickly and easily use the service using their personal identification number card. This system mainly includes the following components:

[0255] 1. Behavioral history collection module

[0256] 2. Emotion Engine

[0257] 3. Generative artificial intelligence (generative AI)

[0258] 4. Service Selection Module

[0259] 5. Portal Registration Module

[0260] 6. Authentication Module

[0261] 7. Service Provision Module

[0262] Each module is described in detail below.

[0263] Behavioral history collection module

[0264] The device collects various operations and access records performed by the user on the web browser and applications. This module records behavioral data such as the URL of the page viewed, the viewing time, and the links clicked, and periodically sends this data to the server.

[0265] Emotion Engine

[0266] The device recognizes the user's emotions in real time and collects emotional data. The engine uses a webcam and microphone to analyze the user's facial expressions and tone of voice, and also analyzes emotions from input text to generate data.

[0267] Generative artificial intelligence (generative AI)

[0268] The server stores the user's behavioral and emotional data in a database. Based on this data, the generative AI analyzes the user's behavioral patterns and emotional state to identify the user's interests and needs. Specifically, the generative AI model performs analysis based on prompt sentences.

[0269] Service Selection Module

[0270] Based on the analysis results of the generative AI, the server lists candidate web services that are most suitable for the user, and selects services that are further optimized using emotional data.

[0271] Portal Registration Module

[0272] The server registers the optimal web service in the portal based on the user's identification information. Specifically, the server registers the selected service using information from the user's personal identification number card (e.g., My Number card).

[0273] Authentication Module

[0274] When a user connects a personal identification number card, the terminal reads the card information using a card reader, sends an authentication request to the server, which performs the authentication, and notifies the terminal of the success or failure of the authentication.

[0275] Service Delivery Module

[0276] The server provides the selected web service to the user after authentication is complete, allowing the user to quickly use the service without having to enter an ID or password.

[0277] Specific examples

[0278] Example 1: Using an e-commerce site

[0279] When a user browses fashion items, the device's behavioral history collection module collects access records and sends them to the server. The device's emotion engine analyzes the user's facial expressions and tone of voice via the webcam and microphone to collect emotional data such as joy and excitement. The server's generation AI analyzes this data and determines that the user is interested in fashion and has favorable feelings toward specific brands. The server's service selection module then selects the most suitable fashion e-commerce site, and the portal registration module registers this information in My Number Portal. The user connects their My Number card to the device for authentication, after which they can start shopping on the e-commerce site without entering their ID or password.

[0280] Example 2: Using SNS services

[0281] When a user browses multiple social networking sites and posts comments on posts, the device's behavioral history collection module collects access records and comments and sends them to the server. The device's emotion engine analyzes the user's emotions from the text and detects that the user has a strong interest in a particular topic. The server's generation AI analyzes this data and determines that the user has a strong interest in the social networking platform. The server's service selection module then selects the most suitable social networking site, and the portal registration module registers this information in My Number Portal. The user connects their My Number card to their PC for authentication, after which they can use the social networking site without entering an ID or password.

[0282] Prompt Sentence Examples

[0283] Examples of prompts for a generative AI model include:

[0284] "Based on the URLs of websites visited by the user in the past week, the time spent browsing, and the list of links clicked, identify the user's interests and needs, and recommend the most suitable web services based on the results. Also, take into account the user's emotional data (facial expressions, tone of voice, and input text)."

[0285] By inputting this prompt into the generation AI, the most suitable service can be selected and provided to the user.

[0286] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0287] Step 1: Collecting behavioral history

[0288] The device collects the operations and access records performed by the user on the web browser and applications. The input includes the URL of the page the user views, the time spent viewing, and the links clicked. This data is periodically recorded and processed for transmission to the server. The output is sent to the server as behavioral history data.

[0289] Specific behavior:

[0290] A user searches and browses for fashion items on an e-commerce site.

[0291] The device collects the URLs of pages viewed and records the time of viewing.

[0292] It also collects information about the links clicked and sends it all to the server.

[0293] Step 2: Collecting emotion data

[0294] The device recognizes the user's emotions in real time and collects emotional data. Input includes video data from the webcam, audio data from the microphone, and text entered by the user. This data is analyzed and output as emotional data. The output is emotional data analyzed from facial expressions, tone of voice, and text.

[0295] Specific behavior:

[0296] The user smiles into the webcam.

[0297] The device analyzes the video data and recognizes smiles as an emotion of joy.

[0298] The user speaks into the microphone in a happy tone.

[0299] It recognizes emotions of enjoyment from voice data and generates emotional data by analyzing text input.

[0300] Step 3: Data storage and analysis (generative AI)

[0301] The server stores behavioral history data and emotional data in a database. The input includes behavioral history data and emotional data sent from the device. The generative AI analyzes this data to identify the user's behavioral patterns and emotional state. The output is an analysis result that includes the user's interests and needs.

[0302] Specific behavior:

[0303] The server stores the behavior history data and emotion data in a database.

[0304] The server's generated AI reads data from the database and analyzes behavioral patterns.

[0305] Generative AI identifies the user's interests, such as fashion.

[0306] Step 4: Select a service

[0307] The server lists the best web service candidates for the user based on the analysis results of the generative AI. The input includes the analysis results from the generative AI. Based on this, the server selects the optimized web service and creates a list of the best web services as the output.

[0308] Specific behavior:

[0309] The generative AI determines that the user is interested in fashion.

[0310] The server will select and list the best fashion e-commerce sites.

[0311] Step 5: Register your service on the portal

[0312] The server registers the optimal web service in the portal based on the user's identity information. The input includes a list of optimal web services selected by the generation AI and personal identification number card information. The output is a mapping of the user's identity information and web services registered in the portal.

[0313] Specific behavior:

[0314] The server obtains information about selected fashion e-commerce sites.

[0315] This information is registered in the portal along with the user's personal identification number card information.

[0316] Step 6: Authentication

[0317] When a user connects a PIN card to the terminal, the terminal uses a card reader to read the card information. The input includes the data from the PIN card. The terminal sends an authentication request to the server, which performs the authentication. The output is a notification of success or failure as the authentication result.

[0318] Specific behavior:

[0319] The user connects their My Number card to the terminal.

[0320] The terminal reads the card information using a card reader.

[0321] The read information is sent to the server as an authentication request, and the server performs authentication.

[0322] The authentication result is notified to the terminal.

[0323] Step 7: Providing the service

[0324] The server provides the selected web service to the authenticated user. The input includes the authentication result and information about the selected web service. The output is the provision of a web service that the user can use quickly and easily.

[0325] Specific behavior:

[0326] After selecting a service, the server grants usage rights to the authenticated user.

[0327] Users can start shopping on selected fashion e-commerce sites without entering their ID or password.

[0328] (Application example 2)

[0329] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0330] Currently, when users use food delivery services, they must choose from a large number of delivery services, which requires complicated operations and authentication procedures. In addition, there is no system that provides optimal services by taking into account the user's emotions and past behavioral history. This results in low user convenience and makes it difficult to provide personalized services.

[0331] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing a user's behavioral history using generative artificial intelligence, means for selecting an optimal online service, means for recognizing and analyzing the user's emotional data in real time, means for registering the selected online service in a portal based on the user's identification information, means for performing authentication using the user's identification information, and means for providing the authenticated online service. This enables the selection of an optimal food delivery service based on the user's emotions and behavioral history and rapid authentication.

[0332] "Generative AI" refers to AI that analyzes a user's behavioral history and emotional data to identify their interests and needs.

[0333] "Behavioral history" refers to the records of operations and accesses performed by a user on a web browser or application.

[0334] "Emotional data" refers to data that indicates the user's emotional state as analyzed from their facial expressions, tone of voice, and input text.

[0335] "Online services" refer to various services provided via the Internet.

[0336] A "portal" is a platform for centrally managing multiple online services.

[0337] "Identification information" refers to data for identifying a user's personal information, and includes, for example, information on a personal identification number card.

[0338] "Authentication" is the process by which a user proves that they are who they say they are.

[0339] The present invention provides a system that collects a user's behavioral history and emotional data, selects the most suitable online service based on the collected data, and allows the user to quickly and easily use the service using their personal identification number card. The following describes in detail an embodiment of the system.

[0340] System configuration

[0341] The system mainly includes the following components:

[0342] 1. Behavioral history collection module

[0343] 2. Emotion Engine

[0344] 3. Generative artificial intelligence (generative AI)

[0345] 4. Service Selection Module

[0346] 5. Portal Registration Module

[0347] 6. Authentication Module

[0348] 7. Service Provision Module

[0349] Hardware and software used

[0350] Smartphone (iOS / Android)

[0351] Card reader (NFC-enabled smartphone)

[0352] Hardware: Webcam, microphone (built-in or external)

[0353] Software: TensorFlow (face recognition and voice emotion recognition), OpenCV (image processing), Python, Flask (server side)

[0354] Processing flow

[0355] 1. Behavioral history collection module:

[0356] It collects the operations and access records of users on their smartphones, including the URLs of pages viewed, the duration of viewing, and the links clicked.

[0357] The data is temporarily stored in the smartphone's local storage and sent to the server at regular intervals.

[0358] 2. Emotion Engine:

[0359] Collects user emotional data. The engine analyzes facial expressions captured through a webcam and tone of voice captured through a microphone.

[0360] TensorFlow is used to recognize emotions from facial expressions and tone of voice and generate data.

[0361] The data is sent to the server in real time.

[0362] 3. Generative artificial intelligence (generative AI):

[0363] The behavioral and emotional data received by the server is stored in a database using a Django-based server.

[0364] Based on this data, the generative AI performs analysis, analyzing the user's behavioral patterns and emotional state to identify their interests and needs.

[0365] 4. Service Selection Module:

[0366] Based on the analysis results of the generative AI, a list of the most suitable online services is created.

[0367] Select services that are further optimized based on user sentiment data.

[0368] 5. Portal Registration Module:

[0369] The selected online services are registered on the portal based on the user's identification information (personal identification number card information).

[0370] Registration is done using secure communication (SSL / TLS).

[0371] 6. Authentication Module:

[0372] The user touches their My Number card to an NFC-enabled smartphone to read the information.

[0373] The read data is sent to the server, where authentication processing is carried out.

[0374] 7. Service Delivery Module:

[0375] Selected online services are provided to users who have been successfully authenticated. After authentication, users can use the services without entering their ID or password.

[0376] Specific examples

[0377] 1. Examples of behavioral history collection:

[0378] It collects data on the dishes a user has ordered and the restaurants they have visited, including the date and time of the order, the food category, and the frequency of the order.

[0379] Example sentence: "User has ordered 10 times in the past month. The most frequent orders are pizza and sushi."

[0380] 2. Emotion data collection example:

[0381] Using TensorFlow, emotions are recognized using facial image data obtained from a webcam and audio data obtained from a microphone.

[0382] Example sentence: "The current emotion is happy."

[0383] 3. Analysis results by generative AI:

[0384] Generative AI analyzes this data to identify which food delivery services users are interested in.

[0385] Example prompt: "User has ordered 10 times in the past month. The most frequent orders are pizza and sushi. The current emotion is happy."

[0386] In this way, optimal online services can be provided based on the user's behavioral history and emotional data.

[0387] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0388] Step 1:

[0389] A user launches a food delivery application on their smartphone.

[0390] Step 2:

[0391] The terminal (smartphone) obtains the user's past order history and browsing history through the behavioral history collection module.

[0392] Input: User actions and access records (such as past orders and visited restaurants)

[0393] Data processing: This data is organized into categories such as order date and time, food category, and order frequency.

[0394] Output: Organized behavioral history data

[0395] Step 3:

[0396] The device activates an emotion engine and collects the user's facial expressions and voice in real time via the webcam and microphone.

[0397] Input: Facial image data from a webcam, audio data from a microphone

[0398] Data Computing: Use TensorFlow to perform facial and vocal emotion recognition.

[0399] Output: Parsed emotion data (e.g., happiness, stress, etc.)

[0400] Step 4:

[0401] The terminal transmits the behavioral history data and the emotion data to the server.

[0402] Input: behavioral history data, emotion data

[0403] Output: Data sent to the server

[0404] Step 5:

[0405] The server stores the received data in a database.

[0406] Input: Behavioral history data and emotional data sent from the device

[0407] Data processing: Converting data into a suitable format and storing it in a database.

[0408] Output: Behavioral history data and emotion data stored in a database

[0409] Step 6:

[0410] The server uses generative AI to analyze behavioral history and emotional data to select the most suitable food delivery service.

[0411] Input: Behavioral history data and emotion data stored in the database

[0412] Data Calculation: Generative AI analyzes data based on prompts and identifies user needs.

[0413] Output: A list of the best food delivery services

[0414] Step 7:

[0415] The server registers the selected food delivery service with the portal.

[0416] Input: List of best food delivery services, user identification information (personal identification number card information)

[0417] Data Computing: Registering selected services to the portal based on the user's identity.

[0418] Output: Service information registered in the portal

[0419] Step 8:

[0420] Users touch their My Number card to an NFC-enabled smartphone and are authenticated using the authentication module.

[0421] Input: My Number card information

[0422] Data calculation: The card information is read using a card reader, sent to the server, and authenticated.

[0423] Output: Authentication result (success or failure)

[0424] Step 9:

[0425] If the authentication is successful, the server allows the user to use the selected food delivery service.

[0426] Input: Authentication result

[0427] Data calculation: Once authenticated, users are granted access to selected food delivery services.

[0428] Output: Users can now use the food delivery service without entering their ID or password.

[0429] 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.

[0430] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0431] 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.

[0432] [Second embodiment]

[0433] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0434] 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.

[0435] 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).

[0436] 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.

[0437] 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.

[0438] 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).

[0439] 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.

[0440] 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.

[0441] 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.

[0442] 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.

[0443] 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.

[0444] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0445] The present invention provides a system that collects a user's behavioral history, selects the most suitable web service based on that history, and allows the user to use the service quickly and easily using their personal identification number card.

[0446] The system mainly includes the following components:

[0447] 1. Behavioral history collection module

[0448] 2. Generative artificial intelligence (generative AI)

[0449] 3. Service Selection Module

[0450] 4. Portal Registration Module

[0451] 5. Authentication Module

[0452] 6. Service Provision Module

[0453] Behavioral history collection module

[0454] This module collects various operations and access records performed by users on web browsers and applications. This module records behavioral data such as the URL of the page viewed, the viewing time, and the links clicked, and sends this data to the server at regular intervals.

[0455] Generative artificial intelligence (generative AI)

[0456] The server stores the user's behavioral history data in a database, which is then analyzed by the Generative AI, which identifies the user's interests and needs and lists the optimal web services that match them.

[0457] Service Selection Module

[0458] The generative AI narrows down the list of web service candidates to the most suitable one, and the server then decides on the final service to offer to the user.

[0459] Portal Registration Module

[0460] The server registers the optimal web service in the portal based on the user's identification information. Specifically, it registers the selected service using information from the user's personal identification number card (e.g., My Number card).

[0461] Authentication Module

[0462] When a user connects a personal identification number card to a terminal, the terminal uses a card reader to read the card information and sends an authentication request to the server. The server performs authentication based on this information and notifies the terminal of the success or failure of the authentication.

[0463] Service Delivery Module

[0464] Once authentication is complete, the selected web service is provided to the user, allowing the user to quickly use the service without having to enter an ID or password.

[0465] Specific examples

[0466] Example 1: Using an e-commerce site

[0467] When a user browses fashion items, the behavioral history collection module collects access records and sends them to the server. The generation AI analyzes this data and determines that the user is interested in fashion items. The service selection module then selects the most suitable fashion e-commerce site, and the portal registration module registers this information in My Number Portal. The user is authenticated by connecting their My Number card to a terminal, and after authentication, they can start shopping on the e-commerce site without entering their ID / PW.

[0468] Example 2: Using SNS services

[0469] If a user browses multiple SNS sites, the behavioral history collection module collects access records and sends them to the server. The generation AI analyzes this data and determines that the user is interested in SNS platforms. The service selection module then selects the most suitable SNS site, and the portal registration module registers this information in My Number Portal. The user is authenticated by connecting their My Number card to their PC, and after authentication, they can use the SNS site without entering their ID / PW.

[0470] In this way, the present invention allows users to omit the complicated IDPW registration and authentication procedures and to use optimal web services quickly and easily.

[0471] The processing flow will be explained below.

[0472] Step 1:

[0473] A user browses a web page. The user's device records the user's behavioral data (URL of the page viewed, viewing time, links clicked, etc.).

[0474] Step 2:

[0475] The device transmits behavioral data to the server at a fixed frequency.

[0476] Step 3:

[0477] The server receives the user's behavior data sent from the terminal and stores it in a database.

[0478] Step 4:

[0479] The server runs the generation AI based on the behavioral data stored in the database. The generation AI analyzes the user's behavioral patterns and identifies the user's interests and needs.

[0480] Step 5:

[0481] The server generates a list of optimal web service candidates based on the results of the AI's analysis.

[0482] Step 6:

[0483] The server selects the most suitable web service for the user from among the candidate web services listed.

[0484] Step 7:

[0485] The server registers the selected web service with the portal based on the user's identification information, using the user's personal identification number card information for registration.

[0486] Step 8:

[0487] The user connects the personal identification number card to the terminal, which uses a card reader to read the card information and sends an authentication request to the server.

[0488] Step 9:

[0489] The server checks the received authentication information and compares it with the data in My Number Portal.

[0490] Step 10:

[0491] The server notifies the terminal of the success or failure of the authentication, and the terminal displays the authentication result to the user.

[0492] Step 11:

[0493] If authentication is successful, the user can use the selected web service. The user can use the service quickly and easily without entering an ID or password.

[0494] Example 1

[0495] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0496] Today's Internet users must manage multiple IDs and passwords to access a wide variety of web services, resulting in cumbersome operations and information security risks. Furthermore, there is no established method for selecting the most suitable service for a user and providing it quickly and easily. Therefore, there is a need for a system that automatically selects the most suitable web service based on a user's behavioral history and enables quick access using personal identification information.

[0497] 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.

[0498] In this invention, the server includes means for collecting user behavior history, means for transmitting the collected behavior history to the server, and means for storing the behavior history in a database. This makes it possible to identify the user's interests and needs through analysis based on the user's behavior history, and to select and quickly provide the most appropriate web service.

[0499] "User behavior history" refers to the operations and access records performed by users on web browsers and applications. Specifically, it includes information such as the URLs of pages viewed, the duration of viewing, and links clicked.

[0500] A "server" refers to a computer system that provides services such as data storage, management, and analysis on a network.

[0501] "Generative AI" refers to AI technology that analyzes data to identify user interests and needs, particularly in selecting the most appropriate web services based on a user's behavioral history.

[0502] A "database" refers to a system for organizing and storing information. It efficiently stores data such as behavioral history and makes it available for later analysis and reference.

[0503] "Web services" refers to various online services provided via the Internet, including e-commerce sites and social networking sites.

[0504] A "portal" is a web page or system that acts as a gateway for users to access, providing an interface for centrally managing multiple services.

[0505] "Authentication" refers to the process of verifying access rights using user identification information, such as a personal identification number card.

[0506] "Personal identification number card" refers to a card that uniquely identifies a specific individual. This includes My Number cards.

[0507] "Prompt sentences" are instructions used by the generative AI when analyzing data. They set conditions to list the most suitable web services based on the user's behavioral history.

[0508] The present invention provides a system that collects a user's behavioral history, selects the most suitable web service based on that history, and allows the user to use the service quickly and easily using their personal identification number card.

[0509] 1. Collecting behavioral history

[0510] It collects various operations and access records performed by users on web browsers and applications. Specifically, it records behavioral data such as the URLs of pages viewed, viewing times, and links clicked. This data is collected by the behavioral history collection module and sent to the server at regular intervals.

[0511] 2. Data storage

[0512] The server receives the data sent from the behavioral history collection module and stores it in a database. The database is a system for efficiently managing collected behavioral data such as URLs, click history, and viewing time.

[0513] 3. Data Analysis

[0514] A generative artificial intelligence (generative AI) on the server periodically analyzes the behavioral history data in the database. The generative AI identifies the user's interests and needs and lists the optimal web services that match them. The generative AI uses the following prompt: "Based on the web pages the user visited most frequently in the past week and the time spent viewing those pages, please list the optimal web services for this user."

[0515] 4. Service Selection

[0516] Based on the analysis results from the generative AI, the service selection module narrows down the optimal web services. For example, if multiple fashion-related web services are listed as candidates, the module will select the most suitable service from among them.

[0517] 5. Registering for the Service

[0518] The server registers the selected web service with the portal based on the user's identification information, specifically, the service is registered using the user's personal identification number card (e.g., personal identification number card), and this information is managed securely and efficiently.

[0519] 6. User Authentication

[0520] The user authenticates by connecting a personal identification number card to the terminal. The terminal reads the card information using a card reader and sends an authentication request to the server. The server performs authentication based on this information and notifies the terminal of the success or failure of the authentication.

[0521] 7. Provision of Services

[0522] The purpose of this service is to provide selected web services to users who have completed authentication, allowing them to quickly use the services without having to enter their ID or password.

[0523] Specific examples

[0524] Example 1: Using an e-commerce site

[0525] When a user browses fashion items, the behavioral history collection module collects the access record and sends it to the server. The generation AI analyzes this data and determines that the user is interested in fashion items. The service selection module then selects the most suitable fashion e-commerce site. The server uses the portal registration module to associate this information with the user's personal identification number card information and registers it in the portal. When the user connects their personal identification number card to their device, they are authenticated and can directly access the service.

[0526] Example 2: Using SNS services

[0527] If a user browses multiple social networking sites, the behavioral history collection module collects their access records and sends them to the server. The generation AI analyzes this data and determines whether the user is interested in social networking platforms. The service selection module then selects the most suitable social networking site. The server uses the portal registration module to associate this information with the user's personal identification number card information and register it in the portal. When the user connects their personal identification number card to their device, authentication is performed and they can directly access the service.

[0528] In this way, the system of the invention selects the most suitable web service based on the user's behavioral history and provides it quickly and easily, thereby greatly improving user convenience.

[0529] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0530] Step 1: User uses web browser or application

[0531] A user uses a web browser or application to browse fashion items or social networking sites. Specifically, the user clicks on an item on a fashion e-commerce site and views its details page. The input at this time is the user's clicks and browsing actions, and the output is the history of the pages the user viewed. The behavioral history collection module captures this in real time.

[0532] Step 2: Send behavioral data to the server

[0533] The device sends the collected behavioral history data to the server at a fixed interval. Specifically, every five minutes, the device sends the URLs of the pages the user viewed, the viewing time, and information about the links they clicked to the server. The data sent is structured in JSON format, etc. The input is the user's behavioral data, and the output is the data sent to the server.

[0534] Step 3: Save the behavioral data to the database

[0535] The server stores the behavioral data it receives in a database. Specifically, it creates a database entry and records the received URL, viewing time, and click history. The input is the behavioral data received by the server, and the output is the data stored in the database.

[0536] Step 4: Generate behavioral data and analyze it with AI

[0537] The generation AI on the server periodically analyzes the behavioral history data stored in the database. Specifically, the generation AI model is given a prompt: "Based on the web pages the user accessed most frequently in the past week and the amount of time spent viewing those pages, please list the most suitable web services for this user." The input is the behavioral history data stored in the database, and the output is a list of web services that meet the user's needs.

[0538] Step 5: Choose the best web service

[0539] The service selection module narrows down the optimal web services based on the analysis results of the generation AI. For example, from the three fashion sites listed by the generation AI, it ultimately selects the site that best suits the user's interests. The input is the analysis results of the generation AI, and the output is the selected web service.

[0540] Step 6: Register your service in the portal

[0541] The server registers the selected web service in the portal based on the user's identification information. Specifically, it associates a service ID with the user's identification information (e.g., information from a personal identification number card) and registers it in a database. The input is the selected web service and the user's identification information, and the output is the service information registered in the portal.

[0542] Step 7: Authenticate the user

[0543] A user connects a personal identification number card to a terminal, and the terminal uses a card reader to read the card information. The terminal then sends the read information to a server, which receives it at a specific endpoint and authenticates the user. The input is the personal identification number card information, and the output is the success or failure of the authentication.

[0544] Step 8: Provide the Service

[0545] The server provides the selected web service to the user after successful authentication. Specifically, the link or dashboard that the user can access after successful authentication is displayed. The input is the authentication success information, and the output is the web service that the user can use.

[0546] In this way, the system of the present invention goes through a series of processing steps to quickly and easily provide optimal web services to users.

[0547] (Application example 1)

[0548] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0549] In conventional virtual stores, it is difficult for users to quickly and easily find the products they are interested in, and the authentication process requires the input of IDs and passwords, making the user experience cumbersome.Furthermore, there is a lack of effective ways to provide personalized services.

[0550] 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.

[0551] In this invention, the server includes means for analyzing a user's behavioral history using generative artificial intelligence, means for selecting an optimal web service, means for registering the selected product information in a portal in a virtual store based on information from a personal identification number card, means for performing authentication using the personal identification number card, and means for providing the optimal product in the virtual store after authentication is complete. This allows users to quickly and easily find and purchase personalized products without having to enter an ID or password.

[0552] - "Generative AI" is AI that analyzes a user's behavioral history and identifies their interests and needs.

[0553] "Behavioral history" refers to the history of browsing and operations performed by a user on a web browser or application, and specifically includes data such as the URLs accessed and the duration of their stay.

[0554] "Web services" refers to various services provided via the Internet, and in this context refers specifically to personalized products and services based on the user's interests.

[0555] "Portal" means a website or application that aggregates certain information or services and allows users to access them in a single location.

[0556] A "personal identification number card" is a card that contains a unique identification number, typically a My Number card, and is used to authenticate a user.

[0557] "Authentication" is the process of verifying a user's identity using the user's personal identification number card.

[0558] A "virtual store" is a store operated on the Internet where users can browse and purchase products in a virtual space.

[0559] In this invention, we build a system that collects user behavior history, analyzes it using a generation AI, and provides optimal products in a virtual store. The specific form is shown below.

[0560] Collecting behavioral history

[0561] The device records the products viewed by the user in the virtual store and the time spent there. The collected data includes the URL of the product page, the viewing time, and the links clicked. This behavioral data is sent to the server at a fixed interval.

[0562] Analysis by generative AI

[0563] The server stores the collected behavioral history data in a database. The generative AI analyzes this data and identifies the user's interests and needs. The generative AI is implemented using machine learning libraries such as TensorFlow and PyTorch.

[0564] Selecting the best service

[0565] Based on the results of the analysis by the generation AI, the server lists the most suitable products for the user.Then, the service selection module narrows down the most suitable product candidates and registers them in the portal based on the user's identification information.

[0566] Portal Registration

[0567] The selected product information is registered in the portal along with the user's personal identification number card information. This process is handled by the portal registration module.

[0568] certification

[0569] When a user connects a personal identification number card to a terminal, the terminal reads the card information using a card reader, then sends an authentication request to the server, which uses an authentication module to authenticate the user and notifies the terminal of the result.

[0570] Service provision

[0571] If authentication is successful, the server provides the selected product information to the user, allowing the user to quickly and easily purchase products in the virtual store without having to enter an ID or password.

[0572] Specific examples

[0573] For example, you can use prompts like the following to feed data into a generative AI model:

[0574] In the past week, users have:

[0575] View the product page of URL1 for 30 seconds

[0576] View the product page of URL2 for 15 seconds

[0577] View the product page of URL3 for 10 seconds

[0578] Based on this data, the user's preferences are analyzed, the most suitable fashion items are selected, and the items are registered on My Number Portal. After the user completes authentication using their personal identification number card, the selected fashion items are suggested.

[0579] In this way, the embodiment of the present invention allows users to quickly and easily find and purchase the most suitable product based on their behavioral history, and also simplifies the authentication procedure, thereby significantly improving the user experience.

[0580] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0581] Step 1: Collecting behavioral history

[0582] The terminal collects various operations and browsing data (e.g., URL of product page and browsing time) performed by the user within the virtual store. The input is the user's operation data, which is temporarily stored in a local database. The output is the collected behavioral data. Specifically, it records the products the user clicked on and the viewing time.

[0583] Step 2: Sending Activity History

[0584] The device sends the collected behavioral data to the server at a fixed frequency. The input is the behavioral history stored in the local database. The output is the behavioral data sent to the server. Specifically, the data is sent using an HTTP POST request.

[0585] Step 3: Save your activity history

[0586] The server stores the received behavioral history data in a database. The input is the behavioral history data sent from the device. The output is the history data stored in the database. Specifically, it performs a write operation to the NoSQL database.

[0587] Step 4: Analyzing behavioral history

[0588] The server uses generative AI to analyze the behavioral history data. The input is the behavioral history data stored in the database. The output is the analysis results about the user's interests and needs. Specifically, a machine learning model (e.g., TensorFlow) is used to analyze the data and identify the user's preferences.

[0589] Step 5: Select the best service

[0590] The server generates a list of optimal products and services based on the analysis results of the generation AI. The input is the analysis results of the behavioral history. The output is a list of optimal products and services. Specifically, it generates a list of products that match the user's preferences and temporarily stores this.

[0591] Step 6: Portal Registration

[0592] The server registers the selected product information along with the personal identification number card information in the portal. The input is the optimal product list and the personal identification number card information. The output is the information registered in the portal. Specifically, the server uses the user's identification information to register product information in My Number Portal.

[0593] Step 7: Authentication

[0594] When a user connects a personal identification number card to a terminal, the terminal uses a card reader to read the card information and sends an authentication request to the server. The input is the personal identification number card information. The output is the authentication result. Specifically, an HTTP request is sent, and the server verifies it using the authentication module.

[0595] Step 8: Service Delivery

[0596] If authentication is successful, the server provides the selected product information to the user. The input is the authentication result and a list of optimal products. The output is the product information provided to the user. Specifically, based on the authentication result, the server performs an operation to display the optimal products on the user's screen.

[0597] The above processing steps realize a system that allows users to quickly and easily purchase individually personalized products without having to go through complicated authentication procedures.

[0598] 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.

[0599] The present invention provides a system that collects a user's behavioral history and emotional data, selects the most suitable web service based on that data, and allows the user to use the service quickly and easily using their personal identification number card.

[0600] The system mainly includes the following components:

[0601] 1. Behavioral history collection module

[0602] 2. Emotion Engine

[0603] 3. Generative artificial intelligence (generative AI)

[0604] 4. Service Selection Module

[0605] 5. Portal Registration Module

[0606] 6. Authentication Module

[0607] 7. Service Provision Module

[0608] Behavioral history collection module

[0609] This module collects various operations and access records performed by users on web browsers and applications. This module records behavioral data such as the URL of the page viewed, the viewing time, and the links clicked, and sends this data to the server at regular intervals.

[0610] Emotion Engine

[0611] The engine recognizes users' emotions in real time and collects emotional data. It analyzes emotions from users' facial expressions, tone of voice, input text, etc. and generates data.

[0612] Generative artificial intelligence (generative AI)

[0613] The server stores the user's behavioral and emotional data in a database, which is then analyzed by the Generative AI, which analyzes the user's behavioral patterns and emotional state to identify the user's interests and needs.

[0614] Service Selection Module

[0615] Based on the results of the analysis by the generative AI, it lists the most suitable web service candidates for the user and selects the service that is further optimized using emotional data.

[0616] Portal Registration Module

[0617] The server registers the most suitable web service to the portal based on the user's identification information. Specifically, it registers the selected service using information from the user's personal identification number card (e.g., My Number card).

[0618] Authentication Module

[0619] When a user connects a personal identification number card to a terminal, the terminal uses a card reader to read the card information and sends an authentication request to the server. The server performs authentication based on this information and notifies the terminal of the success or failure of the authentication.

[0620] Service Delivery Module

[0621] Once authentication is complete, the selected web service is provided to the user, allowing the user to quickly use the service without having to enter an ID or password.

[0622] Specific examples

[0623] Example 1: Using an e-commerce site

[0624] When a user browses fashion items, the behavioral history collection module collects access records and sends them to the server. The emotion engine analyzes the user's facial expressions and tone of voice via the webcam and microphone to collect emotional data such as joy and excitement. The generative AI analyzes this data and determines that the user is interested in fashion and has favorable feelings toward specific brands. The service selection module then selects the most suitable fashion e-commerce site, and the portal registration module registers this information in My Number Portal. The user is authenticated by connecting their My Number card to a terminal, after which they can start shopping on the e-commerce site without entering their ID / PW.

[0625] Example 2: Using SNS services

[0626] When a user browses multiple social networking sites and posts comments on posts, the behavioral history collection module collects access records and comments and sends them to the server. The emotion engine analyzes the user's emotions from the text and detects that the user has a strong interest in a particular topic. The generation AI analyzes this data and determines that the user has a strong interest in the social networking platform. The service selection module then selects the most suitable social networking site, and the portal registration module registers this information in My Number Portal. The user is authenticated by connecting their My Number card to their PC, and after authentication, they can use the social networking site without entering their ID / PW.

[0627] In this way, this invention allows users to omit the cumbersome IDPW registration and authentication procedures and quickly and easily use the most suitable web services. In addition, by taking into account the user's emotions, it becomes possible to provide more personalized services.

[0628] The processing flow will be explained below.

[0629] Step 1:

[0630] A user browses a web page. The user's device records the user's behavioral data (URL of the page viewed, viewing time, links clicked, etc.).

[0631] Step 2:

[0632] The emotion engine analyzes the user's facial expressions and tone of voice via a webcam and microphone to obtain the user's emotional data (happiness, excitement, sadness, etc.). The obtained emotional data is then recorded on the device.

[0633] Step 3:

[0634] The device transmits user behavioral data and emotion data to the server at a fixed frequency. The transmitted data includes behavioral history and emotion recognition results.

[0635] Step 4:

[0636] The server receives the user's behavioral and emotional data and stores this data in a database.

[0637] Step 5:

[0638] The server runs a generative AI based on the behavioral and emotional data stored in the database. The generative AI analyzes the user's behavioral patterns and emotional state to identify the user's interests and needs.

[0639] Step 6:

[0640] The server generates a list of optimal web service candidates based on the results of the AI's analysis.

[0641] Step 7:

[0642] The server considers the emotion data and selects the most suitable web service for the user from the listed web service candidates.

[0643] Step 8:

[0644] The server registers the selected web service with the portal based on the user's identification information, specifically, by using the user's personal identification number card to register the selected service.

[0645] Step 9:

[0646] The user connects the personal identification number card to the terminal, which uses a card reader to read the card information and sends an authentication request to the server.

[0647] Step 10:

[0648] The server checks the received authentication information and compares it with the data in My Number Portal.

[0649] Step 11:

[0650] The server notifies the terminal of the success or failure of the authentication, and the terminal displays the authentication result to the user.

[0651] Step 12:

[0652] If authentication is successful, the server provides the selected web service to the user, who can then use the service quickly and easily without having to enter an ID or password.

[0653] Example 2

[0654] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0655] When using current web services, users often need to authenticate using an ID and password, which is a cumbersome process. Furthermore, personalized services based on users' behavioral history and emotional data are insufficient, making it difficult for them to quickly access the optimal web service that meets their interests and needs. This leads to a poor user experience and impacts service usage rates.

[0656] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for collecting a user's behavioral history, means for recognizing the user's emotions and collecting emotional data, means for analyzing the user's behavioral history and emotional data using generative artificial intelligence, means for selecting an optimal web service, means for registering the selected web service in a portal based on the user's identification information, means for performing authentication using the user's identification information, and means for providing the authenticated web service. This allows the user to quickly and easily use the optimal web service without having to enter a complicated ID or password. Furthermore, providing services based on the behavioral history and emotional data can realize a personalized user experience.

[0657] "Behavioral history" refers to the various operations and access records performed by a user on a web browser or application.

[0658] "Emotional Data" refers to emotional information parsed from a user's facial expressions, tone of voice, and input text.

[0659] "Generative artificial intelligence (generative AI)" refers to artificial intelligence that analyzes a user's behavioral history and emotional data to identify their interests and needs.

[0660] "Portal" refers to an interface for registering the most suitable web services based on a user's identity.

[0661] "Authentication" refers to the process by which a user verifies their access rights using identifying information such as a personal identification number card.

[0662] "Web Services" refers to various online services provided to users via the Internet.

[0663] "Personal Identification Number Card" refers to a card that contains a number that uniquely identifies a user.

[0664] "Database" refers to a system for storing and analyzing collected behavioral history and emotional data.

[0665] The present invention relates to a system that collects user behavioral history and emotion data, selects the most suitable web service based on the collected data, and enables the user to quickly and easily use the service using their personal identification number card. This system mainly includes the following components:

[0666] 1. Behavioral history collection module

[0667] 2. Emotion Engine

[0668] 3. Generative artificial intelligence (generative AI)

[0669] 4. Service Selection Module

[0670] 5. Portal Registration Module

[0671] 6. Authentication Module

[0672] 7. Service Provision Module

[0673] Each module is described in detail below.

[0674] Behavioral history collection module

[0675] The device collects various operations and access records performed by the user on the web browser and applications. This module records behavioral data such as the URL of the page viewed, the viewing time, and the links clicked, and periodically sends this data to the server.

[0676] Emotion Engine

[0677] The device recognizes the user's emotions in real time and collects emotional data. The engine uses a webcam and microphone to analyze the user's facial expressions and tone of voice, and also analyzes emotions from input text to generate data.

[0678] Generative artificial intelligence (generative AI)

[0679] The server stores the user's behavioral and emotional data in a database. Based on this data, the generative AI analyzes the user's behavioral patterns and emotional state to identify the user's interests and needs. Specifically, the generative AI model performs analysis based on prompt sentences.

[0680] Service Selection Module

[0681] Based on the analysis results of the generative AI, the server lists candidate web services that are most suitable for the user, and selects services that are further optimized using emotional data.

[0682] Portal Registration Module

[0683] The server registers the optimal web service in the portal based on the user's identification information. Specifically, the server registers the selected service using information from the user's personal identification number card (e.g., My Number card).

[0684] Authentication Module

[0685] When a user connects a personal identification number card, the terminal reads the card information using a card reader, sends an authentication request to the server, which performs the authentication, and notifies the terminal of the success or failure of the authentication.

[0686] Service Delivery Module

[0687] The server provides the selected web service to the user after authentication is complete, allowing the user to quickly use the service without having to enter an ID or password.

[0688] Specific examples

[0689] Example 1: Using an e-commerce site

[0690] When a user browses fashion items, the device's behavioral history collection module collects access records and sends them to the server. The device's emotion engine analyzes the user's facial expressions and tone of voice via the webcam and microphone to collect emotional data such as joy and excitement. The server's generation AI analyzes this data and determines that the user is interested in fashion and has favorable feelings toward specific brands. The server's service selection module then selects the most suitable fashion e-commerce site, and the portal registration module registers this information in My Number Portal. The user connects their My Number card to the device for authentication, after which they can start shopping on the e-commerce site without entering their ID or password.

[0691] Example 2: Using SNS services

[0692] When a user browses multiple social networking sites and posts comments on posts, the device's behavioral history collection module collects access records and comments and sends them to the server. The device's emotion engine analyzes the user's emotions from the text and detects that the user has a strong interest in a particular topic. The server's generation AI analyzes this data and determines that the user has a strong interest in the social networking platform. The server's service selection module then selects the most suitable social networking site, and the portal registration module registers this information in My Number Portal. The user connects their My Number card to their PC for authentication, after which they can use the social networking site without entering an ID or password.

[0693] Prompt Sentence Examples

[0694] Examples of prompts for a generative AI model include:

[0695] "Based on the URLs of websites visited by the user in the past week, the time spent browsing, and the list of links clicked, identify the user's interests and needs, and recommend the most suitable web services based on the results. Also, take into account the user's emotional data (facial expressions, tone of voice, and input text)."

[0696] By inputting this prompt into the generation AI, the most suitable service can be selected and provided to the user.

[0697] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0698] Step 1: Collecting behavioral history

[0699] The device collects the operations and access records performed by the user on the web browser and applications. The input includes the URL of the page the user views, the time spent viewing, and the links clicked. This data is periodically recorded and processed for transmission to the server. The output is sent to the server as behavioral history data.

[0700] Specific behavior:

[0701] A user searches and browses for fashion items on an e-commerce site.

[0702] The device collects the URLs of pages viewed and records the time of viewing.

[0703] It also collects information about the links clicked and sends it all to the server.

[0704] Step 2: Collecting emotion data

[0705] The device recognizes the user's emotions in real time and collects emotional data. Input includes video data from the webcam, audio data from the microphone, and text entered by the user. This data is analyzed and output as emotional data. The output is emotional data analyzed from facial expressions, tone of voice, and text.

[0706] Specific behavior:

[0707] The user smiles into the webcam.

[0708] The device analyzes the video data and recognizes smiles as an emotion of joy.

[0709] The user speaks into the microphone in a happy tone.

[0710] It recognizes emotions of enjoyment from voice data and generates emotional data by analyzing text input.

[0711] Step 3: Data storage and analysis (generative AI)

[0712] The server stores behavioral history data and emotional data in a database. The input includes behavioral history data and emotional data sent from the device. The generative AI analyzes this data to identify the user's behavioral patterns and emotional state. The output is an analysis result that includes the user's interests and needs.

[0713] Specific behavior:

[0714] The server stores the behavior history data and emotion data in a database.

[0715] The server's generated AI reads data from the database and analyzes behavioral patterns.

[0716] Generative AI identifies the user's interests, such as fashion.

[0717] Step 4: Select a service

[0718] The server lists the best web service candidates for the user based on the analysis results of the generative AI. The input includes the analysis results from the generative AI. Based on this, the server selects the optimized web service and creates a list of the best web services as the output.

[0719] Specific behavior:

[0720] The generative AI determines that the user is interested in fashion.

[0721] The server will select and list the best fashion e-commerce sites.

[0722] Step 5: Register your service on the portal

[0723] The server registers the optimal web service in the portal based on the user's identity information. The input includes a list of optimal web services selected by the generation AI and personal identification number card information. The output is a mapping of the user's identity information and web services registered in the portal.

[0724] Specific behavior:

[0725] The server obtains information about selected fashion e-commerce sites.

[0726] This information is registered in the portal along with the user's personal identification number card information.

[0727] Step 6: Authentication

[0728] When a user connects a PIN card to the terminal, the terminal uses a card reader to read the card information. The input includes the data from the PIN card. The terminal sends an authentication request to the server, which performs the authentication. The output is a notification of success or failure as the authentication result.

[0729] Specific behavior:

[0730] The user connects their My Number card to the terminal.

[0731] The terminal reads the card information using a card reader.

[0732] The read information is sent to the server as an authentication request, and the server performs authentication.

[0733] The authentication result is notified to the terminal.

[0734] Step 7: Providing the service

[0735] The server provides the selected web service to the authenticated user. The input includes the authentication result and information about the selected web service. The output is the provision of a web service that the user can use quickly and easily.

[0736] Specific behavior:

[0737] After selecting a service, the server grants usage rights to the authenticated user.

[0738] Users can start shopping on selected fashion e-commerce sites without entering their ID or password.

[0739] (Application example 2)

[0740] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0741] Currently, when users use food delivery services, they must choose from a large number of delivery services, which requires complicated operations and authentication procedures. In addition, there is no system that provides optimal services by taking into account the user's emotions and past behavioral history. This results in low user convenience and makes it difficult to provide personalized services.

[0742] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing a user's behavioral history using generative artificial intelligence, means for selecting an optimal online service, means for recognizing and analyzing the user's emotional data in real time, means for registering the selected online service in a portal based on the user's identification information, means for performing authentication using the user's identification information, and means for providing the authenticated online service. This enables the selection of an optimal food delivery service based on the user's emotions and behavioral history and rapid authentication.

[0743] "Generative AI" refers to AI that analyzes a user's behavioral history and emotional data to identify their interests and needs.

[0744] "Behavioral history" refers to the records of operations and accesses performed by a user on a web browser or application.

[0745] "Emotional data" refers to data that indicates the user's emotional state as analyzed from their facial expressions, tone of voice, and input text.

[0746] "Online services" refer to various services provided via the Internet.

[0747] A "portal" is a platform for centrally managing multiple online services.

[0748] "Identification information" refers to data for identifying a user's personal information, and includes, for example, information on a personal identification number card.

[0749] "Authentication" is the process by which a user proves that they are who they say they are.

[0750] The present invention provides a system that collects a user's behavioral history and emotional data, selects the most suitable online service based on the collected data, and allows the user to quickly and easily use the service using their personal identification number card. The following describes in detail an embodiment of the system.

[0751] System configuration

[0752] The system mainly includes the following components:

[0753] 1. Behavioral history collection module

[0754] 2. Emotion Engine

[0755] 3. Generative artificial intelligence (generative AI)

[0756] 4. Service Selection Module

[0757] 5. Portal Registration Module

[0758] 6. Authentication Module

[0759] 7. Service Provision Module

[0760] Hardware and software used

[0761] Smartphone (iOS / Android)

[0762] Card reader (NFC-enabled smartphone)

[0763] Hardware: Webcam, microphone (built-in or external)

[0764] Software: TensorFlow (face recognition and voice emotion recognition), OpenCV (image processing), Python, Flask (server side)

[0765] Processing flow

[0766] 1. Behavioral history collection module:

[0767] It collects the operations and access records of users on their smartphones, including the URLs of pages viewed, the duration of viewing, and the links clicked.

[0768] The data is temporarily stored in the smartphone's local storage and sent to the server at regular intervals.

[0769] 2. Emotion Engine:

[0770] Collects user emotional data. The engine analyzes facial expressions captured through a webcam and tone of voice captured through a microphone.

[0771] TensorFlow is used to recognize emotions from facial expressions and tone of voice and generate data.

[0772] The data is sent to the server in real time.

[0773] 3. Generative artificial intelligence (generative AI):

[0774] The behavioral and emotional data received by the server is stored in a database using a Django-based server.

[0775] Based on this data, the generative AI performs analysis, analyzing the user's behavioral patterns and emotional state to identify their interests and needs.

[0776] 4. Service Selection Module:

[0777] Based on the analysis results of the generative AI, a list of the most suitable online services is created.

[0778] Select services that are further optimized based on user sentiment data.

[0779] 5. Portal Registration Module:

[0780] The selected online services are registered on the portal based on the user's identification information (personal identification number card information).

[0781] Registration is done using secure communication (SSL / TLS).

[0782] 6. Authentication Module:

[0783] The user touches their My Number card to an NFC-enabled smartphone to read the information.

[0784] The read data is sent to the server, where authentication processing is carried out.

[0785] 7. Service Delivery Module:

[0786] Selected online services are provided to users who have been successfully authenticated. After authentication, users can use the services without entering their ID or password.

[0787] Specific examples

[0788] 1. Examples of behavioral history collection:

[0789] It collects data on the dishes a user has ordered and the restaurants they have visited, including the date and time of the order, the food category, and the frequency of the order.

[0790] Example sentence: "User has ordered 10 times in the past month. The most frequent orders are pizza and sushi."

[0791] 2. Emotion data collection example:

[0792] Using TensorFlow, emotions are recognized using facial image data obtained from a webcam and audio data obtained from a microphone.

[0793] Example sentence: "The current emotion is happy."

[0794] 3. Analysis results by generative AI:

[0795] Generative AI analyzes this data to identify which food delivery services users are interested in.

[0796] Example prompt: "User has ordered 10 times in the past month. The most frequent orders are pizza and sushi. The current emotion is happy."

[0797] In this way, optimal online services can be provided based on the user's behavioral history and emotional data.

[0798] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0799] Step 1:

[0800] A user launches a food delivery application on their smartphone.

[0801] Step 2:

[0802] The terminal (smartphone) obtains the user's past order history and browsing history through the behavioral history collection module.

[0803] Input: User actions and access records (such as past orders and visited restaurants)

[0804] Data processing: This data is organized into categories such as order date and time, food category, and order frequency.

[0805] Output: Organized behavioral history data

[0806] Step 3:

[0807] The device activates an emotion engine and collects the user's facial expressions and voice in real time via the webcam and microphone.

[0808] Input: Facial image data from a webcam, audio data from a microphone

[0809] Data Computing: Use TensorFlow to perform facial and vocal emotion recognition.

[0810] Output: Parsed emotion data (e.g., happiness, stress, etc.)

[0811] Step 4:

[0812] The terminal transmits the behavioral history data and the emotion data to the server.

[0813] Input: behavioral history data, emotion data

[0814] Output: Data sent to the server

[0815] Step 5:

[0816] The server stores the received data in a database.

[0817] Input: Behavioral history data and emotional data sent from the device

[0818] Data processing: Converting data into a suitable format and storing it in a database.

[0819] Output: Behavioral history data and emotion data stored in a database

[0820] Step 6:

[0821] The server uses generative AI to analyze behavioral history and emotional data to select the most suitable food delivery service.

[0822] Input: Behavioral history data and emotion data stored in the database

[0823] Data Calculation: Generative AI analyzes data based on prompts and identifies user needs.

[0824] Output: A list of the best food delivery services

[0825] Step 7:

[0826] The server registers the selected food delivery service with the portal.

[0827] Input: List of best food delivery services, user identification information (personal identification number card information)

[0828] Data Computing: Registering selected services to the portal based on the user's identity.

[0829] Output: Service information registered in the portal

[0830] Step 8:

[0831] Users touch their My Number card to an NFC-enabled smartphone and are authenticated using the authentication module.

[0832] Input: My Number card information

[0833] Data calculation: The card information is read using a card reader, sent to the server, and authenticated.

[0834] Output: Authentication result (success or failure)

[0835] Step 9:

[0836] If the authentication is successful, the server allows the user to use the selected food delivery service.

[0837] Input: Authentication result

[0838] Data calculation: Once authenticated, users are granted access to selected food delivery services.

[0839] Output: Users can now use the food delivery service without entering their ID or password.

[0840] 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.

[0841] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0842] 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.

[0843] [Third embodiment]

[0844] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0845] 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.

[0846] 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).

[0847] 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.

[0848] 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.

[0849] 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).

[0850] 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.

[0851] 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.

[0852] 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.

[0853] 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.

[0854] 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.

[0855] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0856] The present invention provides a system that collects a user's behavioral history, selects the most suitable web service based on that history, and allows the user to use the service quickly and easily using their personal identification number card.

[0857] The system mainly includes the following components:

[0858] 1. Behavioral history collection module

[0859] 2. Generative artificial intelligence (generative AI)

[0860] 3. Service Selection Module

[0861] 4. Portal Registration Module

[0862] 5. Authentication Module

[0863] 6. Service Provision Module

[0864] Behavioral history collection module

[0865] This module collects various operations and access records performed by users on web browsers and applications. This module records behavioral data such as the URL of the page viewed, the viewing time, and the links clicked, and sends this data to the server at regular intervals.

[0866] Generative artificial intelligence (generative AI)

[0867] The server stores the user's behavioral history data in a database, which is then analyzed by the Generative AI, which identifies the user's interests and needs and lists the optimal web services that match them.

[0868] Service Selection Module

[0869] The generative AI narrows down the list of web service candidates to the most suitable one, and the server then decides on the final service to offer to the user.

[0870] Portal Registration Module

[0871] The server registers the optimal web service in the portal based on the user's identification information. Specifically, it registers the selected service using information from the user's personal identification number card (e.g., My Number card).

[0872] Authentication Module

[0873] When a user connects a personal identification number card to a terminal, the terminal uses a card reader to read the card information and sends an authentication request to the server. The server performs authentication based on this information and notifies the terminal of the success or failure of the authentication.

[0874] Service Delivery Module

[0875] Once authentication is complete, the selected web service is provided to the user, allowing the user to quickly use the service without having to enter an ID or password.

[0876] Specific examples

[0877] Example 1: Using an e-commerce site

[0878] When a user browses fashion items, the behavioral history collection module collects access records and sends them to the server. The generation AI analyzes this data and determines that the user is interested in fashion items. The service selection module then selects the most suitable fashion e-commerce site, and the portal registration module registers this information in My Number Portal. The user is authenticated by connecting their My Number card to a terminal, and after authentication, they can start shopping on the e-commerce site without entering their ID / PW.

[0879] Example 2: Using SNS services

[0880] If a user browses multiple SNS sites, the behavioral history collection module collects access records and sends them to the server. The generation AI analyzes this data and determines that the user is interested in SNS platforms. The service selection module then selects the most suitable SNS site, and the portal registration module registers this information in My Number Portal. The user is authenticated by connecting their My Number card to their PC, and after authentication, they can use the SNS site without entering their ID / PW.

[0881] In this way, the present invention allows users to omit the complicated IDPW registration and authentication procedures and to use optimal web services quickly and easily.

[0882] The processing flow will be explained below.

[0883] Step 1:

[0884] A user browses a web page. The user's device records the user's behavioral data (URL of the page viewed, viewing time, links clicked, etc.).

[0885] Step 2:

[0886] The device transmits behavioral data to the server at a fixed frequency.

[0887] Step 3:

[0888] The server receives the user's behavior data sent from the terminal and stores it in a database.

[0889] Step 4:

[0890] The server runs the generation AI based on the behavioral data stored in the database. The generation AI analyzes the user's behavioral patterns and identifies the user's interests and needs.

[0891] Step 5:

[0892] The server generates a list of optimal web service candidates based on the results of the AI's analysis.

[0893] Step 6:

[0894] The server selects the most suitable web service for the user from among the candidate web services listed.

[0895] Step 7:

[0896] The server registers the selected web service with the portal based on the user's identification information, using the user's personal identification number card information for registration.

[0897] Step 8:

[0898] The user connects the personal identification number card to the terminal, which uses a card reader to read the card information and sends an authentication request to the server.

[0899] Step 9:

[0900] The server checks the received authentication information and compares it with the data in My Number Portal.

[0901] Step 10:

[0902] The server notifies the terminal of the success or failure of the authentication, and the terminal displays the authentication result to the user.

[0903] Step 11:

[0904] If authentication is successful, the user can use the selected web service. The user can use the service quickly and easily without entering an ID or password.

[0905] Example 1

[0906] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0907] Today's Internet users must manage multiple IDs and passwords to access a wide variety of web services, resulting in cumbersome operations and information security risks. Furthermore, there is no established method for selecting the most suitable service for a user and providing it quickly and easily. Therefore, there is a need for a system that automatically selects the most suitable web service based on a user's behavioral history and enables quick access using personal identification information.

[0908] 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.

[0909] In this invention, the server includes means for collecting user behavior history, means for transmitting the collected behavior history to the server, and means for storing the behavior history in a database. This makes it possible to identify the user's interests and needs through analysis based on the user's behavior history, and to select and quickly provide the most appropriate web service.

[0910] "User behavior history" refers to the operations and access records performed by users on web browsers and applications. Specifically, it includes information such as the URLs of pages viewed, the duration of viewing, and links clicked.

[0911] A "server" refers to a computer system that provides services such as data storage, management, and analysis on a network.

[0912] "Generative AI" refers to AI technology that analyzes data to identify user interests and needs, particularly in selecting the most appropriate web services based on a user's behavioral history.

[0913] A "database" refers to a system for organizing and storing information. It efficiently stores data such as behavioral history and makes it available for later analysis and reference.

[0914] "Web services" refers to various online services provided via the Internet, including e-commerce sites and social networking sites.

[0915] A "portal" is a web page or system that acts as a gateway for users to access, providing an interface for centrally managing multiple services.

[0916] "Authentication" refers to the process of verifying access rights using user identification information, such as a personal identification number card.

[0917] "Personal identification number card" refers to a card that uniquely identifies a specific individual. This includes My Number cards.

[0918] "Prompt sentences" are instructions used by the generative AI when analyzing data. They set conditions to list the most suitable web services based on the user's behavioral history.

[0919] The present invention provides a system that collects a user's behavioral history, selects the most suitable web service based on that history, and allows the user to use the service quickly and easily using their personal identification number card.

[0920] 1. Collecting behavioral history

[0921] It collects various operations and access records performed by users on web browsers and applications. Specifically, it records behavioral data such as the URLs of pages viewed, viewing times, and links clicked. This data is collected by the behavioral history collection module and sent to the server at regular intervals.

[0922] 2. Data storage

[0923] The server receives the data sent from the behavioral history collection module and stores it in a database. The database is a system for efficiently managing collected behavioral data such as URLs, click history, and viewing time.

[0924] 3. Data Analysis

[0925] A generative artificial intelligence (generative AI) on the server periodically analyzes the behavioral history data in the database. The generative AI identifies the user's interests and needs and lists the optimal web services that match them. The generative AI uses the following prompt: "Based on the web pages the user visited most frequently in the past week and the time spent viewing those pages, please list the optimal web services for this user."

[0926] 4. Service Selection

[0927] Based on the analysis results from the generative AI, the service selection module narrows down the optimal web services. For example, if multiple fashion-related web services are listed as candidates, the module will select the most suitable service from among them.

[0928] 5. Registering for the Service

[0929] The server registers the selected web service with the portal based on the user's identification information, specifically, the service is registered using the user's personal identification number card (e.g., personal identification number card), and this information is managed securely and efficiently.

[0930] 6. User Authentication

[0931] The user authenticates by connecting a personal identification number card to the terminal. The terminal reads the card information using a card reader and sends an authentication request to the server. The server performs authentication based on this information and notifies the terminal of the success or failure of the authentication.

[0932] 7. Provision of Services

[0933] The purpose of this service is to provide selected web services to users who have completed authentication, allowing them to quickly use the services without having to enter their ID or password.

[0934] Specific examples

[0935] Example 1: Using an e-commerce site

[0936] When a user browses fashion items, the behavioral history collection module collects the access record and sends it to the server. The generation AI analyzes this data and determines that the user is interested in fashion items. The service selection module then selects the most suitable fashion e-commerce site. The server uses the portal registration module to associate this information with the user's personal identification number card information and registers it in the portal. When the user connects their personal identification number card to their device, they are authenticated and can directly access the service.

[0937] Example 2: Using SNS services

[0938] If a user browses multiple social networking sites, the behavioral history collection module collects their access records and sends them to the server. The generation AI analyzes this data and determines whether the user is interested in social networking platforms. The service selection module then selects the most suitable social networking site. The server uses the portal registration module to associate this information with the user's personal identification number card information and register it in the portal. When the user connects their personal identification number card to their device, authentication is performed and they can directly access the service.

[0939] In this way, the system of the invention selects the most suitable web service based on the user's behavioral history and provides it quickly and easily, thereby greatly improving user convenience.

[0940] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0941] Step 1: User uses web browser or application

[0942] A user uses a web browser or application to browse fashion items or social networking sites. Specifically, the user clicks on an item on a fashion e-commerce site and views its details page. The input at this time is the user's clicks and browsing actions, and the output is the history of the pages the user viewed. The behavioral history collection module captures this in real time.

[0943] Step 2: Send behavioral data to the server

[0944] The device sends the collected behavioral history data to the server at a fixed interval. Specifically, every five minutes, the device sends the URLs of the pages the user viewed, the viewing time, and information about the links they clicked to the server. The data sent is structured in JSON format, etc. The input is the user's behavioral data, and the output is the data sent to the server.

[0945] Step 3: Save the behavioral data to the database

[0946] The server stores the behavioral data it receives in a database. Specifically, it creates a database entry and records the received URL, viewing time, and click history. The input is the behavioral data received by the server, and the output is the data stored in the database.

[0947] Step 4: Generate behavioral data and analyze it with AI

[0948] The generation AI on the server periodically analyzes the behavioral history data stored in the database. Specifically, the generation AI model is given a prompt: "Based on the web pages the user accessed most frequently in the past week and the amount of time spent viewing those pages, please list the most suitable web services for this user." The input is the behavioral history data stored in the database, and the output is a list of web services that meet the user's needs.

[0949] Step 5: Choose the best web service

[0950] The service selection module narrows down the optimal web services based on the analysis results of the generation AI. For example, from the three fashion sites listed by the generation AI, it ultimately selects the site that best suits the user's interests. The input is the analysis results of the generation AI, and the output is the selected web service.

[0951] Step 6: Register your service in the portal

[0952] The server registers the selected web service in the portal based on the user's identification information. Specifically, it associates a service ID with the user's identification information (e.g., information from a personal identification number card) and registers it in a database. The input is the selected web service and the user's identification information, and the output is the service information registered in the portal.

[0953] Step 7: Authenticate the user

[0954] A user connects a personal identification number card to a terminal, and the terminal uses a card reader to read the card information. The terminal then sends the read information to a server, which receives it at a specific endpoint and authenticates the user. The input is the personal identification number card information, and the output is the success or failure of the authentication.

[0955] Step 8: Provide the Service

[0956] The server provides the selected web service to the user after successful authentication. Specifically, the link or dashboard that the user can access after successful authentication is displayed. The input is the authentication success information, and the output is the web service that the user can use.

[0957] In this way, the system of the present invention goes through a series of processing steps to quickly and easily provide optimal web services to users.

[0958] (Application example 1)

[0959] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0960] In conventional virtual stores, it is difficult for users to quickly and easily find the products they are interested in, and the authentication process requires the input of IDs and passwords, making the user experience cumbersome.Furthermore, there is a lack of effective ways to provide personalized services.

[0961] 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.

[0962] In this invention, the server includes means for analyzing a user's behavioral history using generative artificial intelligence, means for selecting an optimal web service, means for registering the selected product information in a portal in a virtual store based on information from a personal identification number card, means for performing authentication using the personal identification number card, and means for providing the optimal product in the virtual store after authentication is complete. This allows users to quickly and easily find and purchase personalized products without having to enter an ID or password.

[0963] - "Generative AI" is AI that analyzes a user's behavioral history and identifies their interests and needs.

[0964] "Behavioral history" refers to the history of browsing and operations performed by a user on a web browser or application, and specifically includes data such as the URLs accessed and the duration of their stay.

[0965] "Web services" refers to various services provided via the Internet, and in this context refers specifically to personalized products and services based on the user's interests.

[0966] "Portal" means a website or application that aggregates certain information or services and allows users to access them in a single location.

[0967] A "personal identification number card" is a card that contains a unique identification number, typically a My Number card, and is used to authenticate a user.

[0968] "Authentication" is the process of verifying a user's identity using the user's personal identification number card.

[0969] A "virtual store" is a store operated on the Internet where users can browse and purchase products in a virtual space.

[0970] In this invention, we build a system that collects user behavior history, analyzes it using a generation AI, and provides optimal products in a virtual store. The specific form is shown below.

[0971] Collecting behavioral history

[0972] The device records the products viewed by the user in the virtual store and the time spent there. The collected data includes the URL of the product page, the viewing time, and the links clicked. This behavioral data is sent to the server at a fixed interval.

[0973] Analysis by generative AI

[0974] The server stores the collected behavioral history data in a database. The generative AI analyzes this data and identifies the user's interests and needs. The generative AI is implemented using machine learning libraries such as TensorFlow and PyTorch.

[0975] Selecting the best service

[0976] Based on the results of the analysis by the generation AI, the server lists the most suitable products for the user.Then, the service selection module narrows down the most suitable product candidates and registers them in the portal based on the user's identification information.

[0977] Portal Registration

[0978] The selected product information is registered in the portal along with the user's personal identification number card information. This process is handled by the portal registration module.

[0979] certification

[0980] When a user connects a personal identification number card to a terminal, the terminal reads the card information using a card reader, then sends an authentication request to the server, which uses an authentication module to authenticate the user and notifies the terminal of the result.

[0981] Service provision

[0982] If authentication is successful, the server provides the selected product information to the user, allowing the user to quickly and easily purchase products in the virtual store without having to enter an ID or password.

[0983] Specific examples

[0984] For example, you can use prompts like the following to feed data into a generative AI model:

[0985] In the past week, users have:

[0986] View the product page of URL1 for 30 seconds

[0987] View the product page of URL2 for 15 seconds

[0988] View the product page of URL3 for 10 seconds

[0989] Based on this data, the user's preferences are analyzed, the most suitable fashion items are selected, and the items are registered on My Number Portal. After the user completes authentication using their personal identification number card, the selected fashion items are suggested.

[0990] In this way, the embodiment of the present invention allows users to quickly and easily find and purchase the most suitable product based on their behavioral history, and also simplifies the authentication procedure, thereby significantly improving the user experience.

[0991] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0992] Step 1: Collecting behavioral history

[0993] The terminal collects various operations and browsing data (e.g., URL of product page and browsing time) performed by the user within the virtual store. The input is the user's operation data, which is temporarily stored in a local database. The output is the collected behavioral data. Specifically, it records the products the user clicked on and the viewing time.

[0994] Step 2: Sending Activity History

[0995] The device sends the collected behavioral data to the server at a fixed frequency. The input is the behavioral history stored in the local database. The output is the behavioral data sent to the server. Specifically, the data is sent using an HTTP POST request.

[0996] Step 3: Save your activity history

[0997] The server stores the received behavioral history data in a database. The input is the behavioral history data sent from the device. The output is the history data stored in the database. Specifically, it performs a write operation to the NoSQL database.

[0998] Step 4: Analyzing behavioral history

[0999] The server uses generative AI to analyze the behavioral history data. The input is the behavioral history data stored in the database. The output is the analysis results about the user's interests and needs. Specifically, a machine learning model (e.g., TensorFlow) is used to analyze the data and identify the user's preferences.

[1000] Step 5: Select the best service

[1001] The server generates a list of optimal products and services based on the analysis results of the generation AI. The input is the analysis results of the behavioral history. The output is a list of optimal products and services. Specifically, it generates a list of products that match the user's preferences and temporarily stores this.

[1002] Step 6: Portal Registration

[1003] The server registers the selected product information along with the personal identification number card information in the portal. The input is the optimal product list and the personal identification number card information. The output is the information registered in the portal. Specifically, the server uses the user's identification information to register product information in My Number Portal.

[1004] Step 7: Authentication

[1005] When a user connects a personal identification number card to a terminal, the terminal uses a card reader to read the card information and sends an authentication request to the server. The input is the personal identification number card information. The output is the authentication result. Specifically, an HTTP request is sent, and the server verifies it using the authentication module.

[1006] Step 8: Service Delivery

[1007] If authentication is successful, the server provides the selected product information to the user. The input is the authentication result and a list of optimal products. The output is the product information provided to the user. Specifically, based on the authentication result, the server performs an operation to display the optimal products on the user's screen.

[1008] The above processing steps realize a system that allows users to quickly and easily purchase individually personalized products without having to go through complicated authentication procedures.

[1009] 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.

[1010] The present invention provides a system that collects a user's behavioral history and emotional data, selects the most suitable web service based on that data, and allows the user to use the service quickly and easily using their personal identification number card.

[1011] The system mainly includes the following components:

[1012] 1. Behavioral history collection module

[1013] 2. Emotion Engine

[1014] 3. Generative artificial intelligence (generative AI)

[1015] 4. Service Selection Module

[1016] 5. Portal Registration Module

[1017] 6. Authentication Module

[1018] 7. Service Provision Module

[1019] Behavioral history collection module

[1020] This module collects various operations and access records performed by users on web browsers and applications. This module records behavioral data such as the URL of the page viewed, the viewing time, and the links clicked, and sends this data to the server at regular intervals.

[1021] Emotion Engine

[1022] The engine recognizes users' emotions in real time and collects emotional data. It analyzes emotions from users' facial expressions, tone of voice, input text, etc. and generates data.

[1023] Generative artificial intelligence (generative AI)

[1024] The server stores the user's behavioral and emotional data in a database, which is then analyzed by the Generative AI, which analyzes the user's behavioral patterns and emotional state to identify the user's interests and needs.

[1025] Service Selection Module

[1026] Based on the results of the analysis by the generative AI, it lists the most suitable web service candidates for the user and selects the service that is further optimized using emotional data.

[1027] Portal Registration Module

[1028] The server registers the most suitable web service to the portal based on the user's identification information. Specifically, it registers the selected service using information from the user's personal identification number card (e.g., My Number card).

[1029] Authentication Module

[1030] When a user connects a personal identification number card to a terminal, the terminal uses a card reader to read the card information and sends an authentication request to the server. The server performs authentication based on this information and notifies the terminal of the success or failure of the authentication.

[1031] Service Delivery Module

[1032] Once authentication is complete, the selected web service is provided to the user, allowing the user to quickly use the service without having to enter an ID or password.

[1033] Specific examples

[1034] Example 1: Using an e-commerce site

[1035] When a user browses fashion items, the behavioral history collection module collects access records and sends them to the server. The emotion engine analyzes the user's facial expressions and tone of voice via the webcam and microphone to collect emotional data such as joy and excitement. The generative AI analyzes this data and determines that the user is interested in fashion and has favorable feelings toward specific brands. The service selection module then selects the most suitable fashion e-commerce site, and the portal registration module registers this information in My Number Portal. The user is authenticated by connecting their My Number card to a terminal, after which they can start shopping on the e-commerce site without entering their ID / PW.

[1036] Example 2: Using SNS services

[1037] When a user browses multiple social networking sites and posts comments on posts, the behavioral history collection module collects access records and comments and sends them to the server. The emotion engine analyzes the user's emotions from the text and detects that the user has a strong interest in a particular topic. The generation AI analyzes this data and determines that the user has a strong interest in the social networking platform. The service selection module then selects the most suitable social networking site, and the portal registration module registers this information in My Number Portal. The user is authenticated by connecting their My Number card to their PC, and after authentication, they can use the social networking site without entering their ID / PW.

[1038] In this way, this invention allows users to omit the cumbersome IDPW registration and authentication procedures and quickly and easily use the most suitable web services. In addition, by taking into account the user's emotions, it becomes possible to provide more personalized services.

[1039] The processing flow will be explained below.

[1040] Step 1:

[1041] A user browses a web page. The user's device records the user's behavioral data (URL of the page viewed, viewing time, links clicked, etc.).

[1042] Step 2:

[1043] The emotion engine analyzes the user's facial expressions and tone of voice via a webcam and microphone to obtain the user's emotional data (happiness, excitement, sadness, etc.). The obtained emotional data is then recorded on the device.

[1044] Step 3:

[1045] The device transmits user behavioral data and emotion data to the server at a fixed frequency. The transmitted data includes behavioral history and emotion recognition results.

[1046] Step 4:

[1047] The server receives the user's behavioral and emotional data and stores this data in a database.

[1048] Step 5:

[1049] The server runs a generative AI based on the behavioral and emotional data stored in the database. The generative AI analyzes the user's behavioral patterns and emotional state to identify the user's interests and needs.

[1050] Step 6:

[1051] The server generates a list of optimal web service candidates based on the results of the AI's analysis.

[1052] Step 7:

[1053] The server considers the emotion data and selects the most suitable web service for the user from the listed web service candidates.

[1054] Step 8:

[1055] The server registers the selected web service with the portal based on the user's identification information, specifically, by using the user's personal identification number card to register the selected service.

[1056] Step 9:

[1057] The user connects the personal identification number card to the terminal, which uses a card reader to read the card information and sends an authentication request to the server.

[1058] Step 10:

[1059] The server checks the received authentication information and compares it with the data in My Number Portal.

[1060] Step 11:

[1061] The server notifies the terminal of the success or failure of the authentication, and the terminal displays the authentication result to the user.

[1062] Step 12:

[1063] If authentication is successful, the server provides the selected web service to the user, who can then use the service quickly and easily without having to enter an ID or password.

[1064] Example 2

[1065] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1066] When using current web services, users often need to authenticate using an ID and password, which is a cumbersome process. Furthermore, personalized services based on users' behavioral history and emotional data are insufficient, making it difficult for them to quickly access the optimal web service that meets their interests and needs. This leads to a poor user experience and impacts service usage rates.

[1067] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for collecting a user's behavioral history, means for recognizing the user's emotions and collecting emotional data, means for analyzing the user's behavioral history and emotional data using generative artificial intelligence, means for selecting an optimal web service, means for registering the selected web service in a portal based on the user's identification information, means for performing authentication using the user's identification information, and means for providing the authenticated web service. This allows the user to quickly and easily use the optimal web service without having to enter a complicated ID or password. Furthermore, providing services based on the behavioral history and emotional data can realize a personalized user experience.

[1068] "Behavioral history" refers to the various operations and access records performed by a user on a web browser or application.

[1069] "Emotional Data" refers to emotional information parsed from a user's facial expressions, tone of voice, and input text.

[1070] "Generative artificial intelligence (generative AI)" refers to artificial intelligence that analyzes a user's behavioral history and emotional data to identify their interests and needs.

[1071] "Portal" refers to an interface for registering the most suitable web services based on a user's identity.

[1072] "Authentication" refers to the process by which a user verifies their access rights using identifying information such as a personal identification number card.

[1073] "Web Services" refers to various online services provided to users via the Internet.

[1074] "Personal Identification Number Card" refers to a card that contains a number that uniquely identifies a user.

[1075] "Database" refers to a system for storing and analyzing collected behavioral history and emotional data.

[1076] The present invention relates to a system that collects user behavioral history and emotion data, selects the most suitable web service based on the collected data, and enables the user to quickly and easily use the service using their personal identification number card. This system mainly includes the following components:

[1077] 1. Behavioral history collection module

[1078] 2. Emotion Engine

[1079] 3. Generative artificial intelligence (generative AI)

[1080] 4. Service Selection Module

[1081] 5. Portal Registration Module

[1082] 6. Authentication Module

[1083] 7. Service Provision Module

[1084] Each module is described in detail below.

[1085] Behavioral history collection module

[1086] The device collects various operations and access records performed by the user on the web browser and applications. This module records behavioral data such as the URL of the page viewed, the viewing time, and the links clicked, and periodically sends this data to the server.

[1087] Emotion Engine

[1088] The device recognizes the user's emotions in real time and collects emotional data. The engine uses a webcam and microphone to analyze the user's facial expressions and tone of voice, and also analyzes emotions from input text to generate data.

[1089] Generative artificial intelligence (generative AI)

[1090] The server stores the user's behavioral and emotional data in a database. Based on this data, the generative AI analyzes the user's behavioral patterns and emotional state to identify the user's interests and needs. Specifically, the generative AI model performs analysis based on prompt sentences.

[1091] Service Selection Module

[1092] Based on the analysis results of the generative AI, the server lists candidate web services that are most suitable for the user, and selects services that are further optimized using emotional data.

[1093] Portal Registration Module

[1094] The server registers the optimal web service in the portal based on the user's identification information. Specifically, the server registers the selected service using information from the user's personal identification number card (e.g., My Number card).

[1095] Authentication Module

[1096] When a user connects a personal identification number card, the terminal reads the card information using a card reader, sends an authentication request to the server, which performs the authentication, and notifies the terminal of the success or failure of the authentication.

[1097] Service Delivery Module

[1098] The server provides the selected web service to the user after authentication is complete, allowing the user to quickly use the service without having to enter an ID or password.

[1099] Specific examples

[1100] Example 1: Using an e-commerce site

[1101] When a user browses fashion items, the device's behavioral history collection module collects access records and sends them to the server. The device's emotion engine analyzes the user's facial expressions and tone of voice via the webcam and microphone to collect emotional data such as joy and excitement. The server's generation AI analyzes this data and determines that the user is interested in fashion and has favorable feelings toward specific brands. The server's service selection module then selects the most suitable fashion e-commerce site, and the portal registration module registers this information in My Number Portal. The user connects their My Number card to the device for authentication, after which they can start shopping on the e-commerce site without entering their ID or password.

[1102] Example 2: Using SNS services

[1103] When a user browses multiple social networking sites and posts comments on posts, the device's behavioral history collection module collects access records and comments and sends them to the server. The device's emotion engine analyzes the user's emotions from the text and detects that the user has a strong interest in a particular topic. The server's generation AI analyzes this data and determines that the user has a strong interest in the social networking platform. The server's service selection module then selects the most suitable social networking site, and the portal registration module registers this information in My Number Portal. The user connects their My Number card to their PC for authentication, after which they can use the social networking site without entering an ID or password.

[1104] Prompt Sentence Examples

[1105] Examples of prompts for a generative AI model include:

[1106] "Based on the URLs of websites visited by the user in the past week, the time spent browsing, and the list of links clicked, identify the user's interests and needs, and recommend the most suitable web services based on the results. Also, take into account the user's emotional data (facial expressions, tone of voice, and input text)."

[1107] By inputting this prompt into the generation AI, the most suitable service can be selected and provided to the user.

[1108] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1109] Step 1: Collecting behavioral history

[1110] The device collects the operations and access records performed by the user on the web browser and applications. The input includes the URL of the page the user views, the time spent viewing, and the links clicked. This data is periodically recorded and processed for transmission to the server. The output is sent to the server as behavioral history data.

[1111] Specific behavior:

[1112] A user searches and browses for fashion items on an e-commerce site.

[1113] The device collects the URLs of pages viewed and records the time of viewing.

[1114] It also collects information about the links clicked and sends it all to the server.

[1115] Step 2: Collecting emotion data

[1116] The device recognizes the user's emotions in real time and collects emotional data. Input includes video data from the webcam, audio data from the microphone, and text entered by the user. This data is analyzed and output as emotional data. The output is emotional data analyzed from facial expressions, tone of voice, and text.

[1117] Specific behavior:

[1118] The user smiles into the webcam.

[1119] The device analyzes the video data and recognizes smiles as an emotion of joy.

[1120] The user speaks into the microphone in a happy tone.

[1121] It recognizes emotions of enjoyment from voice data and generates emotional data by analyzing text input.

[1122] Step 3: Data storage and analysis (generative AI)

[1123] The server stores behavioral history data and emotional data in a database. The input includes behavioral history data and emotional data sent from the device. The generative AI analyzes this data to identify the user's behavioral patterns and emotional state. The output is an analysis result that includes the user's interests and needs.

[1124] Specific behavior:

[1125] The server stores the behavior history data and emotion data in a database.

[1126] The server's generated AI reads data from the database and analyzes behavioral patterns.

[1127] Generative AI identifies the user's interests, such as fashion.

[1128] Step 4: Select a service

[1129] The server lists the best web service candidates for the user based on the analysis results of the generative AI. The input includes the analysis results from the generative AI. Based on this, the server selects the optimized web service and creates a list of the best web services as the output.

[1130] Specific behavior:

[1131] The generative AI determines that the user is interested in fashion.

[1132] The server will select and list the best fashion e-commerce sites.

[1133] Step 5: Register your service on the portal

[1134] The server registers the optimal web service in the portal based on the user's identity information. The input includes a list of optimal web services selected by the generation AI and personal identification number card information. The output is a mapping of the user's identity information and web services registered in the portal.

[1135] Specific behavior:

[1136] The server obtains information about selected fashion e-commerce sites.

[1137] This information is registered in the portal along with the user's personal identification number card information.

[1138] Step 6: Authentication

[1139] When a user connects a PIN card to the terminal, the terminal uses a card reader to read the card information. The input includes the data from the PIN card. The terminal sends an authentication request to the server, which performs the authentication. The output is a notification of success or failure as the authentication result.

[1140] Specific behavior:

[1141] The user connects their My Number card to the terminal.

[1142] The terminal reads the card information using a card reader.

[1143] The read information is sent to the server as an authentication request, and the server performs authentication.

[1144] The authentication result is notified to the terminal.

[1145] Step 7: Providing the service

[1146] The server provides the selected web service to the authenticated user. The input includes the authentication result and information about the selected web service. The output is the provision of a web service that the user can use quickly and easily.

[1147] Specific behavior:

[1148] After selecting a service, the server grants usage rights to the authenticated user.

[1149] Users can start shopping on selected fashion e-commerce sites without entering their ID or password.

[1150] (Application example 2)

[1151] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1152] Currently, when users use food delivery services, they must choose from a large number of delivery services, which requires complicated operations and authentication procedures. In addition, there is no system that provides optimal services by taking into account the user's emotions and past behavioral history. This results in low user convenience and makes it difficult to provide personalized services.

[1153] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing a user's behavioral history using generative artificial intelligence, means for selecting an optimal online service, means for recognizing and analyzing the user's emotional data in real time, means for registering the selected online service in a portal based on the user's identification information, means for performing authentication using the user's identification information, and means for providing the authenticated online service. This enables the selection of an optimal food delivery service based on the user's emotions and behavioral history and rapid authentication.

[1154] "Generative AI" refers to AI that analyzes a user's behavioral history and emotional data to identify their interests and needs.

[1155] "Behavioral history" refers to the records of operations and accesses performed by a user on a web browser or application.

[1156] "Emotional data" refers to data that indicates the user's emotional state as analyzed from their facial expressions, tone of voice, and input text.

[1157] "Online services" refer to various services provided via the Internet.

[1158] A "portal" is a platform for centrally managing multiple online services.

[1159] "Identification information" refers to data for identifying a user's personal information, and includes, for example, information on a personal identification number card.

[1160] "Authentication" is the process by which a user proves that they are who they say they are.

[1161] The present invention provides a system that collects a user's behavioral history and emotional data, selects the most suitable online service based on the collected data, and allows the user to quickly and easily use the service using their personal identification number card. The following describes in detail an embodiment of the system.

[1162] System configuration

[1163] The system mainly includes the following components:

[1164] 1. Behavioral history collection module

[1165] 2. Emotion Engine

[1166] 3. Generative artificial intelligence (generative AI)

[1167] 4. Service Selection Module

[1168] 5. Portal Registration Module

[1169] 6. Authentication Module

[1170] 7. Service Provision Module

[1171] Hardware and software used

[1172] Smartphone (iOS / Android)

[1173] Card reader (NFC-enabled smartphone)

[1174] Hardware: Webcam, microphone (built-in or external)

[1175] Software: TensorFlow (face recognition and voice emotion recognition), OpenCV (image processing), Python, Flask (server side)

[1176] Processing flow

[1177] 1. Behavioral history collection module:

[1178] It collects the operations and access records of users on their smartphones, including the URLs of pages viewed, the duration of viewing, and the links clicked.

[1179] The data is temporarily stored in the smartphone's local storage and sent to the server at regular intervals.

[1180] 2. Emotion Engine:

[1181] Collects user emotional data. The engine analyzes facial expressions captured through a webcam and tone of voice captured through a microphone.

[1182] TensorFlow is used to recognize emotions from facial expressions and tone of voice and generate data.

[1183] The data is sent to the server in real time.

[1184] 3. Generative artificial intelligence (generative AI):

[1185] The behavioral and emotional data received by the server is stored in a database using a Django-based server.

[1186] Based on this data, the generative AI performs analysis, analyzing the user's behavioral patterns and emotional state to identify their interests and needs.

[1187] 4. Service Selection Module:

[1188] Based on the analysis results of the generative AI, a list of the most suitable online services is created.

[1189] Select services that are further optimized based on user sentiment data.

[1190] 5. Portal Registration Module:

[1191] The selected online services are registered on the portal based on the user's identification information (personal identification number card information).

[1192] Registration is done using secure communication (SSL / TLS).

[1193] 6. Authentication Module:

[1194] The user touches their My Number card to an NFC-enabled smartphone to read the information.

[1195] The read data is sent to the server, where authentication processing is carried out.

[1196] 7. Service Delivery Module:

[1197] Selected online services are provided to users who have been successfully authenticated. After authentication, users can use the services without entering their ID or password.

[1198] Specific examples

[1199] 1. Examples of behavioral history collection:

[1200] It collects data on the dishes a user has ordered and the restaurants they have visited, including the date and time of the order, the food category, and the frequency of the order.

[1201] Example sentence: "User has ordered 10 times in the past month. The most frequent orders are pizza and sushi."

[1202] 2. Emotion data collection example:

[1203] Using TensorFlow, emotions are recognized using facial image data obtained from a webcam and audio data obtained from a microphone.

[1204] Example sentence: "The current emotion is happy."

[1205] 3. Analysis results by generative AI:

[1206] Generative AI analyzes this data to identify which food delivery services users are interested in.

[1207] Example prompt: "User has ordered 10 times in the past month. The most frequent orders are pizza and sushi. The current emotion is happy."

[1208] In this way, optimal online services can be provided based on the user's behavioral history and emotional data.

[1209] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1210] Step 1:

[1211] A user launches a food delivery application on their smartphone.

[1212] Step 2:

[1213] The terminal (smartphone) obtains the user's past order history and browsing history through the behavioral history collection module.

[1214] Input: User actions and access records (such as past orders and visited restaurants)

[1215] Data processing: This data is organized into categories such as order date and time, food category, and order frequency.

[1216] Output: Organized behavioral history data

[1217] Step 3:

[1218] The device activates an emotion engine and collects the user's facial expressions and voice in real time via the webcam and microphone.

[1219] Input: Facial image data from a webcam, audio data from a microphone

[1220] Data Computing: Use TensorFlow to perform facial and vocal emotion recognition.

[1221] Output: Parsed emotion data (e.g., happiness, stress, etc.)

[1222] Step 4:

[1223] The terminal transmits the behavioral history data and the emotion data to the server.

[1224] Input: behavioral history data, emotion data

[1225] Output: Data sent to the server

[1226] Step 5:

[1227] The server stores the received data in a database.

[1228] Input: Behavioral history data and emotional data sent from the device

[1229] Data processing: Converting data into a suitable format and storing it in a database.

[1230] Output: Behavioral history data and emotion data stored in a database

[1231] Step 6:

[1232] The server uses generative AI to analyze behavioral history and emotional data to select the most suitable food delivery service.

[1233] Input: Behavioral history data and emotion data stored in the database

[1234] Data Calculation: Generative AI analyzes data based on prompts and identifies user needs.

[1235] Output: A list of the best food delivery services

[1236] Step 7:

[1237] The server registers the selected food delivery service with the portal.

[1238] Input: List of best food delivery services, user identification information (personal identification number card information)

[1239] Data Computing: Registering selected services to the portal based on the user's identity.

[1240] Output: Service information registered in the portal

[1241] Step 8:

[1242] Users touch their My Number card to an NFC-enabled smartphone and are authenticated using the authentication module.

[1243] Input: My Number card information

[1244] Data calculation: The card information is read using a card reader, sent to the server, and authenticated.

[1245] Output: Authentication result (success or failure)

[1246] Step 9:

[1247] If the authentication is successful, the server allows the user to use the selected food delivery service.

[1248] Input: Authentication result

[1249] Data calculation: Once authenticated, users are granted access to selected food delivery services.

[1250] Output: Users can now use the food delivery service without entering their ID or password.

[1251] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1252] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1253] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1254] [Fourth embodiment]

[1255] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1256] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1257] 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).

[1258] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1259] 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.

[1260] 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).

[1261] 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.

[1262] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1263] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1264] 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.

[1265] 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.

[1266] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1267] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1268] The present invention provides a system that collects a user's behavioral history, selects the most suitable web service based on that history, and allows the user to use the service quickly and easily using their personal identification number card.

[1269] The system mainly includes the following components:

[1270] 1. Behavioral history collection module

[1271] 2. Generative artificial intelligence (generative AI)

[1272] 3. Service Selection Module

[1273] 4. Portal Registration Module

[1274] 5. Authentication Module

[1275] 6. Service Provision Module

[1276] Behavioral history collection module

[1277] This module collects various operations and access records performed by users on web browsers and applications. This module records behavioral data such as the URL of the page viewed, the viewing time, and the links clicked, and sends this data to the server at regular intervals.

[1278] Generative artificial intelligence (generative AI)

[1279] The server stores the user's behavioral history data in a database, which is then analyzed by the Generative AI, which identifies the user's interests and needs and lists the optimal web services that match them.

[1280] Service Selection Module

[1281] The generative AI narrows down the list of web service candidates to the most suitable one, and the server then decides on the final service to offer to the user.

[1282] Portal Registration Module

[1283] The server registers the optimal web service in the portal based on the user's identification information. Specifically, it registers the selected service using information from the user's personal identification number card (e.g., My Number card).

[1284] Authentication Module

[1285] When a user connects a personal identification number card to a terminal, the terminal uses a card reader to read the card information and sends an authentication request to the server. The server performs authentication based on this information and notifies the terminal of the success or failure of the authentication.

[1286] Service Delivery Module

[1287] Once authentication is complete, the selected web service is provided to the user, allowing the user to quickly use the service without having to enter an ID or password.

[1288] Specific examples

[1289] Example 1: Using an e-commerce site

[1290] When a user browses fashion items, the behavioral history collection module collects access records and sends them to the server. The generation AI analyzes this data and determines that the user is interested in fashion items. The service selection module then selects the most suitable fashion e-commerce site, and the portal registration module registers this information in My Number Portal. The user is authenticated by connecting their My Number card to a terminal, and after authentication, they can start shopping on the e-commerce site without entering their ID / PW.

[1291] Example 2: Using SNS services

[1292] If a user browses multiple SNS sites, the behavioral history collection module collects access records and sends them to the server. The generation AI analyzes this data and determines that the user is interested in SNS platforms. The service selection module then selects the most suitable SNS site, and the portal registration module registers this information in My Number Portal. The user is authenticated by connecting their My Number card to their PC, and after authentication, they can use the SNS site without entering their ID / PW.

[1293] In this way, the present invention allows users to omit the complicated IDPW registration and authentication procedures and to use optimal web services quickly and easily.

[1294] The processing flow will be explained below.

[1295] Step 1:

[1296] A user browses a web page. The user's device records the user's behavioral data (URL of the page viewed, viewing time, links clicked, etc.).

[1297] Step 2:

[1298] The device transmits behavioral data to the server at a fixed frequency.

[1299] Step 3:

[1300] The server receives the user's behavior data sent from the terminal and stores it in a database.

[1301] Step 4:

[1302] The server runs the generation AI based on the behavioral data stored in the database. The generation AI analyzes the user's behavioral patterns and identifies the user's interests and needs.

[1303] Step 5:

[1304] The server generates a list of optimal web service candidates based on the results of the AI's analysis.

[1305] Step 6:

[1306] The server selects the most suitable web service for the user from among the candidate web services listed.

[1307] Step 7:

[1308] The server registers the selected web service with the portal based on the user's identification information, using the user's personal identification number card information for registration.

[1309] Step 8:

[1310] The user connects the personal identification number card to the terminal, which uses a card reader to read the card information and sends an authentication request to the server.

[1311] Step 9:

[1312] The server checks the received authentication information and compares it with the data in My Number Portal.

[1313] Step 10:

[1314] The server notifies the terminal of the success or failure of the authentication, and the terminal displays the authentication result to the user.

[1315] Step 11:

[1316] If authentication is successful, the user can use the selected web service. The user can use the service quickly and easily without entering an ID or password.

[1317] Example 1

[1318] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1319] Today's Internet users must manage multiple IDs and passwords to access a wide variety of web services, resulting in cumbersome operations and information security risks. Furthermore, there is no established method for selecting the most suitable service for a user and providing it quickly and easily. Therefore, there is a need for a system that automatically selects the most suitable web service based on a user's behavioral history and enables quick access using personal identification information.

[1320] 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.

[1321] In this invention, the server includes means for collecting user behavior history, means for transmitting the collected behavior history to the server, and means for storing the behavior history in a database. This makes it possible to identify the user's interests and needs through analysis based on the user's behavior history, and to select and quickly provide the most appropriate web service.

[1322] "User behavior history" refers to the operations and access records performed by users on web browsers and applications. Specifically, it includes information such as the URLs of pages viewed, the duration of viewing, and links clicked.

[1323] A "server" refers to a computer system that provides services such as data storage, management, and analysis on a network.

[1324] "Generative AI" refers to AI technology that analyzes data to identify user interests and needs, particularly in selecting the most appropriate web services based on a user's behavioral history.

[1325] A "database" refers to a system for organizing and storing information. It efficiently stores data such as behavioral history and makes it available for later analysis and reference.

[1326] "Web services" refers to various online services provided via the Internet, including e-commerce sites and social networking sites.

[1327] A "portal" is a web page or system that acts as a gateway for users to access, providing an interface for centrally managing multiple services.

[1328] "Authentication" refers to the process of verifying access rights using user identification information, such as a personal identification number card.

[1329] "Personal identification number card" refers to a card that uniquely identifies a specific individual. This includes My Number cards.

[1330] "Prompt sentences" are instructions used by the generative AI when analyzing data. They set conditions to list the most suitable web services based on the user's behavioral history.

[1331] The present invention provides a system that collects a user's behavioral history, selects the most suitable web service based on that history, and allows the user to use the service quickly and easily using their personal identification number card.

[1332] 1. Collecting behavioral history

[1333] It collects various operations and access records performed by users on web browsers and applications. Specifically, it records behavioral data such as the URLs of pages viewed, viewing times, and links clicked. This data is collected by the behavioral history collection module and sent to the server at regular intervals.

[1334] 2. Data storage

[1335] The server receives the data sent from the behavioral history collection module and stores it in a database. The database is a system for efficiently managing collected behavioral data such as URLs, click history, and viewing time.

[1336] 3. Data Analysis

[1337] A generative artificial intelligence (generative AI) on the server periodically analyzes the behavioral history data in the database. The generative AI identifies the user's interests and needs and lists the optimal web services that match them. The generative AI uses the following prompt: "Based on the web pages the user visited most frequently in the past week and the time spent viewing those pages, please list the optimal web services for this user."

[1338] 4. Service Selection

[1339] Based on the analysis results from the generative AI, the service selection module narrows down the optimal web services. For example, if multiple fashion-related web services are listed as candidates, the module will select the most suitable service from among them.

[1340] 5. Registering for the Service

[1341] The server registers the selected web service with the portal based on the user's identification information, specifically, the service is registered using the user's personal identification number card (e.g., personal identification number card), and this information is managed securely and efficiently.

[1342] 6. User Authentication

[1343] The user authenticates by connecting a personal identification number card to the terminal. The terminal reads the card information using a card reader and sends an authentication request to the server. The server performs authentication based on this information and notifies the terminal of the success or failure of the authentication.

[1344] 7. Provision of Services

[1345] The purpose of this service is to provide selected web services to users who have completed authentication, allowing them to quickly use the services without having to enter their ID or password.

[1346] Specific examples

[1347] Example 1: Using an e-commerce site

[1348] When a user browses fashion items, the behavioral history collection module collects the access record and sends it to the server. The generation AI analyzes this data and determines that the user is interested in fashion items. The service selection module then selects the most suitable fashion e-commerce site. The server uses the portal registration module to associate this information with the user's personal identification number card information and registers it in the portal. When the user connects their personal identification number card to their device, they are authenticated and can directly access the service.

[1349] Example 2: Using SNS services

[1350] If a user browses multiple social networking sites, the behavioral history collection module collects their access records and sends them to the server. The generation AI analyzes this data and determines whether the user is interested in social networking platforms. The service selection module then selects the most suitable social networking site. The server uses the portal registration module to associate this information with the user's personal identification number card information and register it in the portal. When the user connects their personal identification number card to their device, authentication is performed and they can directly access the service.

[1351] In this way, the system of the invention selects the most suitable web service based on the user's behavioral history and provides it quickly and easily, thereby greatly improving user convenience.

[1352] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1353] Step 1: User uses web browser or application

[1354] A user uses a web browser or application to browse fashion items or social networking sites. Specifically, the user clicks on an item on a fashion e-commerce site and views its details page. The input at this time is the user's clicks and browsing actions, and the output is the history of the pages the user viewed. The behavioral history collection module captures this in real time.

[1355] Step 2: Send behavioral data to the server

[1356] The device sends the collected behavioral history data to the server at a fixed interval. Specifically, every five minutes, the device sends the URLs of the pages the user viewed, the viewing time, and information about the links they clicked to the server. The data sent is structured in JSON format, etc. The input is the user's behavioral data, and the output is the data sent to the server.

[1357] Step 3: Save the behavioral data to the database

[1358] The server stores the behavioral data it receives in a database. Specifically, it creates a database entry and records the received URL, viewing time, and click history. The input is the behavioral data received by the server, and the output is the data stored in the database.

[1359] Step 4: Generate behavioral data and analyze it with AI

[1360] The generation AI on the server periodically analyzes the behavioral history data stored in the database. Specifically, the generation AI model is given a prompt: "Based on the web pages the user accessed most frequently in the past week and the amount of time spent viewing those pages, please list the most suitable web services for this user." The input is the behavioral history data stored in the database, and the output is a list of web services that meet the user's needs.

[1361] Step 5: Choose the best web service

[1362] The service selection module narrows down the optimal web services based on the analysis results of the generation AI. For example, from the three fashion sites listed by the generation AI, it ultimately selects the site that best suits the user's interests. The input is the analysis results of the generation AI, and the output is the selected web service.

[1363] Step 6: Register your service in the portal

[1364] The server registers the selected web service in the portal based on the user's identification information. Specifically, it associates a service ID with the user's identification information (e.g., information from a personal identification number card) and registers it in a database. The input is the selected web service and the user's identification information, and the output is the service information registered in the portal.

[1365] Step 7: Authenticate the user

[1366] A user connects a personal identification number card to a terminal, and the terminal uses a card reader to read the card information. The terminal then sends the read information to a server, which receives it at a specific endpoint and authenticates the user. The input is the personal identification number card information, and the output is the success or failure of the authentication.

[1367] Step 8: Provide the Service

[1368] The server provides the selected web service to the user after successful authentication. Specifically, the link or dashboard that the user can access after successful authentication is displayed. The input is the authentication success information, and the output is the web service that the user can use.

[1369] In this way, the system of the present invention goes through a series of processing steps to quickly and easily provide optimal web services to users.

[1370] (Application example 1)

[1371] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1372] In conventional virtual stores, it is difficult for users to quickly and easily find the products they are interested in, and the authentication process requires the input of IDs and passwords, making the user experience cumbersome.Furthermore, there is a lack of effective ways to provide personalized services.

[1373] 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.

[1374] In this invention, the server includes means for analyzing a user's behavioral history using generative artificial intelligence, means for selecting an optimal web service, means for registering the selected product information in a portal in a virtual store based on information from a personal identification number card, means for performing authentication using the personal identification number card, and means for providing the optimal product in the virtual store after authentication is complete. This allows users to quickly and easily find and purchase personalized products without having to enter an ID or password.

[1375] - "Generative AI" is AI that analyzes a user's behavioral history and identifies their interests and needs.

[1376] "Behavioral history" refers to the history of browsing and operations performed by a user on a web browser or application, and specifically includes data such as the URLs accessed and the duration of their stay.

[1377] "Web services" refers to various services provided via the Internet, and in this context refers specifically to personalized products and services based on the user's interests.

[1378] "Portal" means a website or application that aggregates certain information or services and allows users to access them in a single location.

[1379] A "personal identification number card" is a card that contains a unique identification number, typically a My Number card, and is used to authenticate a user.

[1380] "Authentication" is the process of verifying a user's identity using the user's personal identification number card.

[1381] A "virtual store" is a store operated on the Internet where users can browse and purchase products in a virtual space.

[1382] In this invention, we build a system that collects user behavior history, analyzes it using a generation AI, and provides optimal products in a virtual store. The specific form is shown below.

[1383] Collecting behavioral history

[1384] The device records the products viewed by the user in the virtual store and the time spent there. The collected data includes the URL of the product page, the viewing time, and the links clicked. This behavioral data is sent to the server at a fixed interval.

[1385] Analysis by generative AI

[1386] The server stores the collected behavioral history data in a database. The generative AI analyzes this data and identifies the user's interests and needs. The generative AI is implemented using machine learning libraries such as TensorFlow and PyTorch.

[1387] Selecting the best service

[1388] Based on the results of the analysis by the generation AI, the server lists the most suitable products for the user.Then, the service selection module narrows down the most suitable product candidates and registers them in the portal based on the user's identification information.

[1389] Portal Registration

[1390] The selected product information is registered in the portal along with the user's personal identification number card information. This process is handled by the portal registration module.

[1391] certification

[1392] When a user connects a personal identification number card to a terminal, the terminal reads the card information using a card reader, then sends an authentication request to the server, which uses an authentication module to authenticate the user and notifies the terminal of the result.

[1393] Service provision

[1394] If authentication is successful, the server provides the selected product information to the user, allowing the user to quickly and easily purchase products in the virtual store without having to enter an ID or password.

[1395] Specific examples

[1396] For example, you can use prompts like the following to feed data into a generative AI model:

[1397] In the past week, users have:

[1398] View the product page of URL1 for 30 seconds

[1399] View the product page of URL2 for 15 seconds

[1400] View the product page of URL3 for 10 seconds

[1401] Based on this data, the user's preferences are analyzed, the most suitable fashion items are selected, and the items are registered on My Number Portal. After the user completes authentication using their personal identification number card, the selected fashion items are suggested.

[1402] In this way, the embodiment of the present invention allows users to quickly and easily find and purchase the most suitable product based on their behavioral history, and also simplifies the authentication procedure, thereby significantly improving the user experience.

[1403] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1404] Step 1: Collecting behavioral history

[1405] The terminal collects various operations and browsing data (e.g., URL of product page and browsing time) performed by the user within the virtual store. The input is the user's operation data, which is temporarily stored in a local database. The output is the collected behavioral data. Specifically, it records the products the user clicked on and the viewing time.

[1406] Step 2: Sending Activity History

[1407] The device sends the collected behavioral data to the server at a fixed frequency. The input is the behavioral history stored in the local database. The output is the behavioral data sent to the server. Specifically, the data is sent using an HTTP POST request.

[1408] Step 3: Save your activity history

[1409] The server stores the received behavioral history data in a database. The input is the behavioral history data sent from the device. The output is the history data stored in the database. Specifically, it performs a write operation to the NoSQL database.

[1410] Step 4: Analyzing behavioral history

[1411] The server uses generative AI to analyze the behavioral history data. The input is the behavioral history data stored in the database. The output is the analysis results about the user's interests and needs. Specifically, a machine learning model (e.g., TensorFlow) is used to analyze the data and identify the user's preferences.

[1412] Step 5: Select the best service

[1413] The server generates a list of optimal products and services based on the analysis results of the generation AI. The input is the analysis results of the behavioral history. The output is a list of optimal products and services. Specifically, it generates a list of products that match the user's preferences and temporarily stores this.

[1414] Step 6: Portal Registration

[1415] The server registers the selected product information along with the personal identification number card information in the portal. The input is the optimal product list and the personal identification number card information. The output is the information registered in the portal. Specifically, the server uses the user's identification information to register product information in My Number Portal.

[1416] Step 7: Authentication

[1417] When a user connects a personal identification number card to a terminal, the terminal uses a card reader to read the card information and sends an authentication request to the server. The input is the personal identification number card information. The output is the authentication result. Specifically, an HTTP request is sent, and the server verifies it using the authentication module.

[1418] Step 8: Service Delivery

[1419] If authentication is successful, the server provides the selected product information to the user. The input is the authentication result and a list of optimal products. The output is the product information provided to the user. Specifically, based on the authentication result, the server performs an operation to display the optimal products on the user's screen.

[1420] The above processing steps realize a system that allows users to quickly and easily purchase individually personalized products without having to go through complicated authentication procedures.

[1421] 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.

[1422] The present invention provides a system that collects a user's behavioral history and emotional data, selects the most suitable web service based on that data, and allows the user to use the service quickly and easily using their personal identification number card.

[1423] The system mainly includes the following components:

[1424] 1. Behavioral history collection module

[1425] 2. Emotion Engine

[1426] 3. Generative artificial intelligence (generative AI)

[1427] 4. Service Selection Module

[1428] 5. Portal Registration Module

[1429] 6. Authentication Module

[1430] 7. Service Provision Module

[1431] Behavioral history collection module

[1432] This module collects various operations and access records performed by users on web browsers and applications. This module records behavioral data such as the URL of the page viewed, the viewing time, and the links clicked, and sends this data to the server at regular intervals.

[1433] Emotion Engine

[1434] The engine recognizes users' emotions in real time and collects emotional data. It analyzes emotions from users' facial expressions, tone of voice, input text, etc. and generates data.

[1435] Generative artificial intelligence (generative AI)

[1436] The server stores the user's behavioral and emotional data in a database, which is then analyzed by the Generative AI, which analyzes the user's behavioral patterns and emotional state to identify the user's interests and needs.

[1437] Service Selection Module

[1438] Based on the results of the analysis by the generative AI, it lists the most suitable web service candidates for the user and selects the service that is further optimized using emotional data.

[1439] Portal Registration Module

[1440] The server registers the most suitable web service to the portal based on the user's identification information. Specifically, it registers the selected service using information from the user's personal identification number card (e.g., My Number card).

[1441] Authentication Module

[1442] When a user connects a personal identification number card to a terminal, the terminal uses a card reader to read the card information and sends an authentication request to the server. The server performs authentication based on this information and notifies the terminal of the success or failure of the authentication.

[1443] Service Delivery Module

[1444] Once authentication is complete, the selected web service is provided to the user, allowing the user to quickly use the service without having to enter an ID or password.

[1445] Specific examples

[1446] Example 1: Using an e-commerce site

[1447] When a user browses fashion items, the behavioral history collection module collects access records and sends them to the server. The emotion engine analyzes the user's facial expressions and tone of voice via the webcam and microphone to collect emotional data such as joy and excitement. The generative AI analyzes this data and determines that the user is interested in fashion and has favorable feelings toward specific brands. The service selection module then selects the most suitable fashion e-commerce site, and the portal registration module registers this information in My Number Portal. The user is authenticated by connecting their My Number card to a terminal, after which they can start shopping on the e-commerce site without entering their ID / PW.

[1448] Example 2: Using SNS services

[1449] When a user browses multiple social networking sites and posts comments on posts, the behavioral history collection module collects access records and comments and sends them to the server. The emotion engine analyzes the user's emotions from the text and detects that the user has a strong interest in a particular topic. The generation AI analyzes this data and determines that the user has a strong interest in the social networking platform. The service selection module then selects the most suitable social networking site, and the portal registration module registers this information in My Number Portal. The user is authenticated by connecting their My Number card to their PC, and after authentication, they can use the social networking site without entering their ID / PW.

[1450] In this way, this invention allows users to omit the cumbersome IDPW registration and authentication procedures and quickly and easily use the most suitable web services. In addition, by taking into account the user's emotions, it becomes possible to provide more personalized services.

[1451] The processing flow will be explained below.

[1452] Step 1:

[1453] A user browses a web page. The user's device records the user's behavioral data (URL of the page viewed, viewing time, links clicked, etc.).

[1454] Step 2:

[1455] The emotion engine analyzes the user's facial expressions and tone of voice via a webcam and microphone to obtain the user's emotional data (happiness, excitement, sadness, etc.). The obtained emotional data is then recorded on the device.

[1456] Step 3:

[1457] The device transmits user behavioral data and emotion data to the server at a fixed frequency. The transmitted data includes behavioral history and emotion recognition results.

[1458] Step 4:

[1459] The server receives the user's behavioral and emotional data and stores this data in a database.

[1460] Step 5:

[1461] The server runs a generative AI based on the behavioral and emotional data stored in the database. The generative AI analyzes the user's behavioral patterns and emotional state to identify the user's interests and needs.

[1462] Step 6:

[1463] The server generates a list of optimal web service candidates based on the results of the AI's analysis.

[1464] Step 7:

[1465] The server considers the emotion data and selects the most suitable web service for the user from the listed web service candidates.

[1466] Step 8:

[1467] The server registers the selected web service with the portal based on the user's identification information, specifically, by using the user's personal identification number card to register the selected service.

[1468] Step 9:

[1469] The user connects the personal identification number card to the terminal, which uses a card reader to read the card information and sends an authentication request to the server.

[1470] Step 10:

[1471] The server checks the received authentication information and compares it with the data in My Number Portal.

[1472] Step 11:

[1473] The server notifies the terminal of the success or failure of the authentication, and the terminal displays the authentication result to the user.

[1474] Step 12:

[1475] If authentication is successful, the server provides the selected web service to the user, who can then use the service quickly and easily without having to enter an ID or password.

[1476] Example 2

[1477] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1478] When using current web services, users often need to authenticate using an ID and password, which is a cumbersome process. Furthermore, personalized services based on users' behavioral history and emotional data are insufficient, making it difficult for them to quickly access the optimal web service that meets their interests and needs. This leads to a poor user experience and impacts service usage rates.

[1479] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for collecting a user's behavioral history, means for recognizing the user's emotions and collecting emotional data, means for analyzing the user's behavioral history and emotional data using generative artificial intelligence, means for selecting an optimal web service, means for registering the selected web service in a portal based on the user's identification information, means for performing authentication using the user's identification information, and means for providing the authenticated web service. This allows the user to quickly and easily use the optimal web service without having to enter a complicated ID or password. Furthermore, providing services based on the behavioral history and emotional data can realize a personalized user experience.

[1480] "Behavioral history" refers to the various operations and access records performed by a user on a web browser or application.

[1481] "Emotional Data" refers to emotional information parsed from a user's facial expressions, tone of voice, and input text.

[1482] "Generative artificial intelligence (generative AI)" refers to artificial intelligence that analyzes a user's behavioral history and emotional data to identify their interests and needs.

[1483] "Portal" refers to an interface for registering the most suitable web services based on a user's identity.

[1484] "Authentication" refers to the process by which a user verifies their access rights using identifying information such as a personal identification number card.

[1485] "Web Services" refers to various online services provided to users via the Internet.

[1486] "Personal Identification Number Card" refers to a card that contains a number that uniquely identifies a user.

[1487] "Database" refers to a system for storing and analyzing collected behavioral history and emotional data.

[1488] The present invention relates to a system that collects user behavioral history and emotion data, selects the most suitable web service based on the collected data, and enables the user to quickly and easily use the service using their personal identification number card. This system mainly includes the following components:

[1489] 1. Behavioral history collection module

[1490] 2. Emotion Engine

[1491] 3. Generative artificial intelligence (generative AI)

[1492] 4. Service Selection Module

[1493] 5. Portal Registration Module

[1494] 6. Authentication Module

[1495] 7. Service Provision Module

[1496] Each module is described in detail below.

[1497] Behavioral history collection module

[1498] The device collects various operations and access records performed by the user on the web browser and applications. This module records behavioral data such as the URL of the page viewed, the viewing time, and the links clicked, and periodically sends this data to the server.

[1499] Emotion Engine

[1500] The device recognizes the user's emotions in real time and collects emotional data. The engine uses a webcam and microphone to analyze the user's facial expressions and tone of voice, and also analyzes emotions from input text to generate data.

[1501] Generative artificial intelligence (generative AI)

[1502] The server stores the user's behavioral and emotional data in a database. Based on this data, the generative AI analyzes the user's behavioral patterns and emotional state to identify the user's interests and needs. Specifically, the generative AI model performs analysis based on prompt sentences.

[1503] Service Selection Module

[1504] Based on the analysis results of the generative AI, the server lists candidate web services that are most suitable for the user, and selects services that are further optimized using emotional data.

[1505] Portal Registration Module

[1506] The server registers the optimal web service in the portal based on the user's identification information. Specifically, the server registers the selected service using information from the user's personal identification number card (e.g., My Number card).

[1507] Authentication Module

[1508] When a user connects a personal identification number card, the terminal reads the card information using a card reader, sends an authentication request to the server, which performs the authentication, and notifies the terminal of the success or failure of the authentication.

[1509] Service Delivery Module

[1510] The server provides the selected web service to the user after authentication is complete, allowing the user to quickly use the service without having to enter an ID or password.

[1511] Specific examples

[1512] Example 1: Using an e-commerce site

[1513] When a user browses fashion items, the device's behavioral history collection module collects access records and sends them to the server. The device's emotion engine analyzes the user's facial expressions and tone of voice via the webcam and microphone to collect emotional data such as joy and excitement. The server's generation AI analyzes this data and determines that the user is interested in fashion and has favorable feelings toward specific brands. The server's service selection module then selects the most suitable fashion e-commerce site, and the portal registration module registers this information in My Number Portal. The user connects their My Number card to the device for authentication, after which they can start shopping on the e-commerce site without entering their ID or password.

[1514] Example 2: Using SNS services

[1515] When a user browses multiple social networking sites and posts comments on posts, the device's behavioral history collection module collects access records and comments and sends them to the server. The device's emotion engine analyzes the user's emotions from the text and detects that the user has a strong interest in a particular topic. The server's generation AI analyzes this data and determines that the user has a strong interest in the social networking platform. The server's service selection module then selects the most suitable social networking site, and the portal registration module registers this information in My Number Portal. The user connects their My Number card to their PC for authentication, after which they can use the social networking site without entering an ID or password.

[1516] Prompt Sentence Examples

[1517] Examples of prompts for a generative AI model include:

[1518] "Based on the URLs of websites visited by the user in the past week, the time spent browsing, and the list of links clicked, identify the user's interests and needs, and recommend the most suitable web services based on the results. Also, take into account the user's emotional data (facial expressions, tone of voice, and input text)."

[1519] By inputting this prompt into the generation AI, the most suitable service can be selected and provided to the user.

[1520] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1521] Step 1: Collecting behavioral history

[1522] The device collects the operations and access records performed by the user on the web browser and applications. The input includes the URL of the page the user views, the time spent viewing, and the links clicked. This data is periodically recorded and processed for transmission to the server. The output is sent to the server as behavioral history data.

[1523] Specific behavior:

[1524] A user searches and browses for fashion items on an e-commerce site.

[1525] The device collects the URLs of pages viewed and records the time of viewing.

[1526] It also collects information about the links clicked and sends it all to the server.

[1527] Step 2: Collecting emotion data

[1528] The device recognizes the user's emotions in real time and collects emotional data. Input includes video data from the webcam, audio data from the microphone, and text entered by the user. This data is analyzed and output as emotional data. The output is emotional data analyzed from facial expressions, tone of voice, and text.

[1529] Specific behavior:

[1530] The user smiles into the webcam.

[1531] The device analyzes the video data and recognizes smiles as an emotion of joy.

[1532] The user speaks into the microphone in a happy tone.

[1533] It recognizes emotions of enjoyment from voice data and generates emotional data by analyzing text input.

[1534] Step 3: Data storage and analysis (generative AI)

[1535] The server stores behavioral history data and emotional data in a database. The input includes behavioral history data and emotional data sent from the device. The generative AI analyzes this data to identify the user's behavioral patterns and emotional state. The output is an analysis result that includes the user's interests and needs.

[1536] Specific behavior:

[1537] The server stores the behavior history data and emotion data in a database.

[1538] The server's generated AI reads data from the database and analyzes behavioral patterns.

[1539] Generative AI identifies the user's interests, such as fashion.

[1540] Step 4: Select a service

[1541] The server lists the best web service candidates for the user based on the analysis results of the generative AI. The input includes the analysis results from the generative AI. Based on this, the server selects the optimized web service and creates a list of the best web services as the output.

[1542] Specific behavior:

[1543] The generative AI determines that the user is interested in fashion.

[1544] The server will select and list the best fashion e-commerce sites.

[1545] Step 5: Register your service on the portal

[1546] The server registers the optimal web service in the portal based on the user's identity information. The input includes a list of optimal web services selected by the generation AI and personal identification number card information. The output is a mapping of the user's identity information and web services registered in the portal.

[1547] Specific behavior:

[1548] The server obtains information about selected fashion e-commerce sites.

[1549] This information is registered in the portal along with the user's personal identification number card information.

[1550] Step 6: Authentication

[1551] When a user connects a PIN card to the terminal, the terminal uses a card reader to read the card information. The input includes the data from the PIN card. The terminal sends an authentication request to the server, which performs the authentication. The output is a notification of success or failure as the authentication result.

[1552] Specific behavior:

[1553] The user connects their My Number card to the terminal.

[1554] The terminal reads the card information using a card reader.

[1555] The read information is sent to the server as an authentication request, and the server performs authentication.

[1556] The authentication result is notified to the terminal.

[1557] Step 7: Providing the service

[1558] The server provides the selected web service to the authenticated user. The input includes the authentication result and information about the selected web service. The output is the provision of a web service that the user can use quickly and easily.

[1559] Specific behavior:

[1560] After selecting a service, the server grants usage rights to the authenticated user.

[1561] Users can start shopping on selected fashion e-commerce sites without entering their ID or password.

[1562] (Application example 2)

[1563] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1564] Currently, when users use food delivery services, they must choose from a large number of delivery services, which requires complicated operations and authentication procedures. In addition, there is no system that provides optimal services by taking into account the user's emotions and past behavioral history. This results in low user convenience and makes it difficult to provide personalized services.

[1565] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing a user's behavioral history using generative artificial intelligence, means for selecting an optimal online service, means for recognizing and analyzing the user's emotional data in real time, means for registering the selected online service in a portal based on the user's identification information, means for performing authentication using the user's identification information, and means for providing the authenticated online service. This enables the selection of an optimal food delivery service based on the user's emotions and behavioral history and rapid authentication.

[1566] "Generative AI" refers to AI that analyzes a user's behavioral history and emotional data to identify their interests and needs.

[1567] "Behavioral history" refers to the records of operations and accesses performed by a user on a web browser or application.

[1568] "Emotional data" refers to data that indicates the user's emotional state as analyzed from their facial expressions, tone of voice, and input text.

[1569] "Online services" refer to various services provided via the Internet.

[1570] A "portal" is a platform for centrally managing multiple online services.

[1571] "Identification information" refers to data for identifying a user's personal information, and includes, for example, information on a personal identification number card.

[1572] "Authentication" is the process by which a user proves that they are who they say they are.

[1573] The present invention provides a system that collects a user's behavioral history and emotional data, selects the most suitable online service based on the collected data, and allows the user to quickly and easily use the service using their personal identification number card. The following describes in detail an embodiment of the system.

[1574] System configuration

[1575] The system mainly includes the following components:

[1576] 1. Behavioral history collection module

[1577] 2. Emotion Engine

[1578] 3. Generative artificial intelligence (generative AI)

[1579] 4. Service Selection Module

[1580] 5. Portal Registration Module

[1581] 6. Authentication Module

[1582] 7. Service Provision Module

[1583] Hardware and software used

[1584] Smartphone (iOS / Android)

[1585] Card reader (NFC-enabled smartphone)

[1586] Hardware: Webcam, microphone (built-in or external)

[1587] Software: TensorFlow (face recognition and voice emotion recognition), OpenCV (image processing), Python, Flask (server side)

[1588] Processing flow

[1589] 1. Behavioral history collection module:

[1590] It collects the operations and access records of users on their smartphones, including the URLs of pages viewed, the duration of viewing, and the links clicked.

[1591] The data is temporarily stored in the smartphone's local storage and sent to the server at regular intervals.

[1592] 2. Emotion Engine:

[1593] Collects user emotional data. The engine analyzes facial expressions captured through a webcam and tone of voice captured through a microphone.

[1594] TensorFlow is used to recognize emotions from facial expressions and tone of voice and generate data.

[1595] The data is sent to the server in real time.

[1596] 3. Generative artificial intelligence (generative AI):

[1597] The behavioral and emotional data received by the server is stored in a database using a Django-based server.

[1598] Based on this data, the generative AI performs analysis, analyzing the user's behavioral patterns and emotional state to identify their interests and needs.

[1599] 4. Service Selection Module:

[1600] Based on the analysis results of the generative AI, a list of the most suitable online services is created.

[1601] Select services that are further optimized based on user sentiment data.

[1602] 5. Portal Registration Module:

[1603] The selected online services are registered on the portal based on the user's identification information (personal identification number card information).

[1604] Registration is done using secure communication (SSL / TLS).

[1605] 6. Authentication Module:

[1606] The user touches their My Number card to an NFC-enabled smartphone to read the information.

[1607] The read data is sent to the server, where authentication processing is carried out.

[1608] 7. Service Delivery Module:

[1609] Selected online services are provided to users who have been successfully authenticated. After authentication, users can use the services without entering their ID or password.

[1610] Specific examples

[1611] 1. Examples of behavioral history collection:

[1612] It collects data on the dishes a user has ordered and the restaurants they have visited, including the date and time of the order, the food category, and the frequency of the order.

[1613] Example sentence: "User has ordered 10 times in the past month. The most frequent orders are pizza and sushi."

[1614] 2. Emotion data collection example:

[1615] Using TensorFlow, emotions are recognized using facial image data obtained from a webcam and audio data obtained from a microphone.

[1616] Example sentence: "The current emotion is happy."

[1617] 3. Analysis results by generative AI:

[1618] Generative AI analyzes this data to identify which food delivery services users are interested in.

[1619] Example prompt: "User has ordered 10 times in the past month. The most frequent orders are pizza and sushi. The current emotion is happy."

[1620] In this way, optimal online services can be provided based on the user's behavioral history and emotional data.

[1621] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1622] Step 1:

[1623] A user launches a food delivery application on their smartphone.

[1624] Step 2:

[1625] The terminal (smartphone) obtains the user's past order history and browsing history through the behavioral history collection module.

[1626] Input: User actions and access records (such as past orders and visited restaurants)

[1627] Data processing: This data is organized into categories such as order date and time, food category, and order frequency.

[1628] Output: Organized behavioral history data

[1629] Step 3:

[1630] The device activates an emotion engine and collects the user's facial expressions and voice in real time via the webcam and microphone.

[1631] Input: Facial image data from a webcam, audio data from a microphone

[1632] Data Computing: Use TensorFlow to perform facial and vocal emotion recognition.

[1633] Output: Parsed emotion data (e.g., happiness, stress, etc.)

[1634] Step 4:

[1635] The terminal transmits the behavioral history data and the emotion data to the server.

[1636] Input: behavioral history data, emotion data

[1637] Output: Data sent to the server

[1638] Step 5:

[1639] The server stores the received data in a database.

[1640] Input: Behavioral history data and emotional data sent from the device

[1641] Data processing: Converting data into a suitable format and storing it in a database.

[1642] Output: Behavioral history data and emotion data stored in a database

[1643] Step 6:

[1644] The server uses generative AI to analyze behavioral history and emotional data to select the most suitable food delivery service.

[1645] Input: Behavioral history data and emotion data stored in the database

[1646] Data Calculation: Generative AI analyzes data based on prompts and identifies user needs.

[1647] Output: A list of the best food delivery services

[1648] Step 7:

[1649] The server registers the selected food delivery service with the portal.

[1650] Input: List of best food delivery services, user identification information (personal identification number card information)

[1651] Data Computing: Registering selected services to the portal based on the user's identity.

[1652] Output: Service information registered in the portal

[1653] Step 8:

[1654] Users touch their My Number card to an NFC-enabled smartphone and are authenticated using the authentication module.

[1655] Input: My Number card information

[1656] Data calculation: The card information is read using a card reader, sent to the server, and authenticated.

[1657] Output: Authentication result (success or failure)

[1658] Step 9:

[1659] If the authentication is successful, the server allows the user to use the selected food delivery service.

[1660] Input: Authentication result

[1661] Data calculation: Once authenticated, users are granted access to selected food delivery services.

[1662] Output: Users can now use the food delivery service without entering their ID or password.

[1663] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1664] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1665] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1666] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1667] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1668] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1669] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1670] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1671] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1672] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1673] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1674] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1675] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1676] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1677] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1678] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1679] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1680] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1681] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1682] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1683] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1684] The following is further disclosed regarding the above embodiment.

[1685] (Claim 1)

[1686] A means for analyzing user behavior history using generative artificial intelligence;

[1687] A means of selecting the most suitable web service;

[1688] means for registering the selected web services with the portal based on the user's identification information;

[1689] a means for authenticating the user using the user's identity;

[1690] a means for providing an authenticated web service;

[1691] A system including:

[1692] (Claim 2)

[1693] A means of collecting user behavior history;

[1694] Further comprising means for storing the collected behavioral history in a database;

[1695] 10. The system of claim 1.

[1696] (Claim 3)

[1697] including using personal identification number card information as user identification information,

[1698] 10. The system of claim 1.

[1699] "Example 1"

[1700] (Claim 1)

[1701] A means of collecting user behavior history;

[1702] A means for transmitting the collected behavioral history to a server;

[1703] A means for storing the behavioral history in a database;

[1704] A means for analyzing user behavior history using generative artificial intelligence;

[1705] A means of selecting the most suitable web service;

[1706] means for registering the selected web services with the portal based on the user's identification information;

[1707] a means for authenticating the user using the user's identity;

[1708] a means for providing an authenticated web service;

[1709] A system including:

[1710] (Claim 2)

[1711] 10. The system of claim 1, further comprising means for parsing the generative artificial intelligence model with prompt statements to list web services based on the user's interests and needs.

[1712] (Claim 3)

[1713] 10. The system of claim 1, further comprising means for utilizing information on a personal identification number card as the user's identification information.

[1714] "Application Example 1"

[1715] New Claims

[1716] (Claim 1)

[1717] A means for analyzing user behavior history using generative artificial intelligence;

[1718] A means of selecting the most suitable web service;

[1719] a means for registering selected product information in a portal based on information on a personal identification number card in the virtual store;

[1720] A means for performing authentication using a personal identification number card;

[1721] After authentication is complete, a virtual store will provide the best products for you.

[1722] A system including:

[1723] (Claim 2)

[1724] A means of collecting user behavior history;

[1725] Further comprising means for storing the collected behavioral history in a database;

[1726] 10. The system of claim 1.

[1727] (Claim 3)

[1728] including using personal identification number card information as user identification information,

[1729] 10. The system of claim 1.

[1730] "Example 2: Combining Emotion Engines"

[1731] (Claim 1)

[1732] A means of collecting user behavior history;

[1733] a means for recognizing a user's emotions and collecting emotion data;

[1734] A means for analyzing user behavioral history and emotional data using generative artificial intelligence;

[1735] A means of selecting the most suitable web service;

[1736] means for registering the selected web services with the portal based on the user's identification information;

[1737] a means for authenticating the user using the user's identity;

[1738] a means for providing an authenticated web service;

[1739] A system including:

[1740] (Claim 2)

[1741] and means for storing the collected behavioral history and emotion data in a database.

[1742] 10. The system of claim 1.

[1743] (Claim 3)

[1744] including using personal identification number card information as user identification information,

[1745] 10. The system of claim 1.

[1746] "Application example 2 when combining emotion engines"

[1747] (Claim 1)

[1748] A means for analyzing user behavior history using generative artificial intelligence;

[1749] How to select the best online service,

[1750] A means of recognizing and analyzing user emotional data in real time,

[1751] means for registering selected online services with the portal based on the user's identification information;

[1752] a means for authenticating the user using the user's identity;

[1753] a means for providing authenticated online services;

[1754] A system including:

[1755] (Claim 2)

[1756] A means of collecting user behavior history;

[1757] and means for storing the collected behavioral history and emotion data in a database.

[1758] 10. The system of claim 1.

[1759] (Claim 3)

[1760] including using personal identification number card information as user identification information,

[1761] 10. The system of claim 1. [Explanation of symbols]

[1762] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for analyzing user behavior history using generative artificial intelligence; A means of selecting the most suitable web service; means for registering the selected web services with the portal based on the user's identification information; a means for authenticating the user using the user's identity; a means for providing an authenticated web service; A system including:

2. A means of collecting user behavior history; Further comprising means for storing the collected behavioral history in a database; The system of claim 1 .

3. including using personal identification number card information as user identification information, The system of claim 1 .

Images