System

Abstract

A system is provided.SOLUTION: This system is provided with a means for actively acquiring personal data from a user, a means for paying a price to the acquired personal data, a means for analyzing the collected personal data, and for selecting the optimal advertisement or service, and a means for displaying the selected advertisement or service on the terminal of the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] With traditional methods, it has become difficult to obtain user information due to the abolition of third-party cookies in browsers and the strengthening of personal information protection. Furthermore, users' distrust and discomfort over personal data collected without their consent has become a major issue, reducing the effectiveness of advertisements provided based on collected data. Furthermore, it is currently difficult to achieve both an improved user experience and optimized advertisements. [Means for solving the problem]

[0005] In order to solve the above problems, the present invention provides a system that provides a means for actively acquiring personal data from users, a means for paying for the acquired personal data, a means for analyzing the collected personal data and selecting optimal advertisements and services, and a means for displaying the selected advertisements and services on the user's terminal.

[0006] It also includes a method for having users periodically provide information in the form of a questionnaire, and by providing a framework in which users can provide information of their own volition, it reduces user distrust and discomfort. Furthermore, by incorporating a method for updating user profiles based on collected personal data using generative AI and ID linking, it is possible to constantly optimize the user experience and provide highly relevant advertisements.

[0007] "User" means an individual or organization that uses the system and actively provides personal data.

[0008] "Personal data" refers to information related to an individual, such as a user's interests, concerns, purchasing history, lifestyle, etc.

[0009] "Compensation" refers to benefits such as rewards or points systems given to users in exchange for providing personal data.

[0010] "Data analysis" is the process of analyzing collected personal data to identify user preferences and behavioral patterns.

[0011] "Advertisements and Services" means promotions and products and services selected based on your Personal Data.

[0012] "Terminal" means the device or platform through which a User accesses the System and receives advertisements and services.

[0013] The "questionnaire format" is a method of presenting questions to users and actively collecting information from them.

[0014] "Generative AI" is an artificial intelligence technology that generates and updates user profiles based on collected personal data and assists in selecting optimal advertisements and services.

[0015] "ID federation" is a method of integrating data from multiple devices and platforms to manage a consistent user profile. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

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

[0026] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] The present invention relates to a system that actively collects personal data from users, analyzes the data, and provides optimal advertisements and services to the users. This system is implemented in the following manner.

[0038] Acquisition of user information and payment

[0039] First, a user creates an account on the system and logs in. The device sends this login information to the server. The server authenticates the user's login and presents a questionnaire-style question to the user who has successfully logged in. When the user answers the question and submits it, the information is stored on the server.

[0040] The server processes the response data and rewards the user with points, which can be used to purchase products or services later.

[0041] Examples:

[0042] Suppose a user logs into the application and answers "Action" to the question "What is your favorite movie genre?" The device sends the answer to the server, which stores the information in a database and then credits the user's account with 10 points.

[0043] Analyze data and provide personalized advertising

[0044] The server analyzes the collected user data to identify the user's preferences and behavioral patterns. Based on the analyzed data, the server selects the most suitable advertisements and services and displays them on the user's device.

[0045] Specifically, an analytics algorithm uses data like "I like action movies" to select relevant ads that are then displayed while the user is browsing a webpage.

[0046] Deepening personalization and ID integration

[0047] The system uses generative AI and ID federation to enhance the user's personalized experience. The server integrates data from different devices and platforms and manages it as a single profile.

[0048] This allows users to have a consistent advertising and service experience whether they are using the same system on a smartphone or PC, and also allows for quick response to changes in user behavior or preferences, which can be reflected in the next ad display.

[0049] Examples:

[0050] If a user begins to show interest in "documentary films" on a particular device, the server will immediately update that information in the user's profile, ensuring that the next time the user logs in on another device, they will see advertisements related to documentary films.

[0051] System action

[0052] This system is implemented by a program. The process flow is explained below using a specific example.

[0053] First, the user answers a questionnaire, and the data is sent to a server and stored in a database. The server then analyzes the data and selects advertisements that match the user's preferences. The selected advertisements are then displayed on the user's device.

[0054] Furthermore, generative AI is used to constantly update data as users use the system, providing a more accurate and personalized experience.ID linking enables consistent data management across multiple devices, improving the advertising experience.

[0055] This system allows users to provide information of their own volition and receive benefits in return, while the system performs highly accurate data analysis to provide optimal advertisements and services, creating a valuable experience for both users and advertisers.

[0056] The processing flow will be explained below.

[0057] Program processing flow

[0058] Step 1:

[0059] The user launches the application and enters the required information (name, email address, password, etc.) on the account creation page.

[0060] Step 2:

[0061] The terminal transmits the input user information to the server.

[0062] Step 3:

[0063] The server stores the received user information in a database and sends a confirmation message to the terminal confirming that the account has been created.

[0064] Step 4:

[0065] The terminal receives a confirmation message and displays it to the user.

[0066] Step 5:

[0067] The user is directed to the login screen and enters their account information to log in.

[0068] Step 6:

[0069] The terminal sends the login information to the server.

[0070] Step 7:

[0071] The server authenticates the user information and initiates a login session.

[0072] Step 8:

[0073] The server sends a login completion message to the terminal and simultaneously presents a questionnaire-style question.

[0074] Step 9:

[0075] The terminal will display a survey screen along with a login completion message.

[0076] Step 10:

[0077] The user enters answers to the survey questions and presses the send button.

[0078] Step 11:

[0079] The terminal transmits the user's answer to the server.

[0080] Step 12:

[0081] The server receives the user's answers and stores the data in a database.

[0082] Step 13:

[0083] The server will reward the user with points in return for the answer.

[0084] Step 14:

[0085] The terminal displays a message to the user indicating that points have been awarded.

[0086] Step 15:

[0087] The server inputs the collected user data into an analytical algorithm to identify user preferences and behavioral patterns.

[0088] Step 16:

[0089] The server selects the most appropriate advertisements and services based on the analysis results.

[0090] Step 17:

[0091] The server transmits the selected advertisement data to the advertisement server, and prepares it to be embedded in the page viewed by the user.

[0092] Step 18:

[0093] The device detects user activity and displays personalized ads if advertising space is found on the page being viewed.

[0094] Step 19:

[0095] The user views the displayed advertisement and, if desired, clicks or checks for more information.

[0096] Step 20:

[0097] The server monitors the display status of advertisements in real time and collects and analyzes click and viewing data.

[0098] Step 21:

[0099] The server uses generative AI and ID federation to update user profiles based on the collected data.

[0100] Step 22:

[0101] The server will reflect the updated profile information in subsequent advertisement selections.

[0102] Step 23:

[0103] The device periodically presents new surveys to the user and continues to collect more personal data.

[0104] This series of steps allows users to provide information of their own volition and receive the optimal advertising experience, while the server performs highly accurate data analysis and can provide advertisers with valuable promotions.

[0105] Example 1

[0106] 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."

[0107] In conventional systems, when actively collecting personal data from users and analyzing that data to provide optimal advertisements and services, it was difficult to manage data consistently across devices and personalize it, which tended to fragment the user experience. There were also issues with the accuracy of data analysis and timely responses.

[0108] 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.

[0109] In this invention, the server includes means for actively acquiring personal data from users, means for paying for the acquired personal data, means for analyzing the collected personal data and selecting optimal advertisements and services, means for displaying the selected advertisements and services on the user's terminal, means for performing analysis using a generative AI model, and means for integrating data from different devices through ID federation, thereby providing a consistent personalized experience across devices and improving the accuracy of data analysis and the speed of response.

[0110] "User" refers to an individual or corporation that uses the system.

[0111] "Personal data" refers to personal information such as a user's preferences, behavioral patterns, and survey responses.

[0112] "Compensation" refers to the reward given by the system in exchange for the user providing personal data, specifically points or credits.

[0113] "Points" refer to rewards that users can earn by providing personal data, and are units that can be used when purchasing products or using services.

[0114] "Analysis" refers to the process of processing collected personal data to identify user preferences and behavioral patterns.

[0115] "Advertisement" refers to any message or content that informs users about a particular product or service.

[0116] "Service" refers to all products, functions, support, etc. provided to users.

[0117] "Terminal" refers to a hardware device used by a user, such as a computer, smartphone, or tablet.

[0118] "Server" refers to a central computer system that receives, processes, and stores information submitted by users.

[0119] "Generative AI model" refers to an artificial intelligence model used for data analysis and ad selection.

[0120] "ID linking" refers to a technology that integrates user data from different devices and manages it as a single profile.

[0121] A "profile" refers to a comprehensive collection of data such as a user's preferences and behavioral patterns.

[0122] The present invention is a system that actively collects personal data from users, analyzes the data, and provides optimal advertisements and services to the users. Specific embodiments of this system will be described below.

[0123] Acquisition of user information and payment

[0124] First, a user creates an account on the system and logs in. The device sends this login information to the server. The server authenticates the user's login and presents a questionnaire-style question to the successful user. When the user answers the questions and submits them, the information is stored on the server. The server processes the answer data and adds points to the user's account in return. These points can be used later to purchase products or use services.

[0125] A concrete example is when a user logs into an application and answers "action" to the question "What is your favorite movie genre?" The device sends the answer to the server, which stores the information in a database and then credits the user's account with 10 points.

[0126] Analyze data and provide personalized advertising

[0127] The server analyzes the collected user data using a generative AI model to identify the user's preferences and behavioral patterns. Based on the analyzed data, the server selects the most appropriate advertisements and services and displays them on the user's device. Specifically, the analysis algorithm uses the data, such as "I like action movies," to select relevant advertisements. These advertisements are then displayed while the user is browsing a web page.

[0128] Deepening personalization and ID integration

[0129] The system uses generative AI models and ID federation to deepen the user's personalized experience. The server integrates data from different devices and platforms and manages it as a single profile. This allows users to have a consistent advertising and service experience even when using the same system on both smartphones and PCs. Furthermore, if a user's behavior or preferences change, it can quickly respond and reflect that in the next ad display.

[0130] For example, if a user begins to show interest in "documentary films" on a particular device, the server can instantly update that information in the user's profile, so that the next time the user logs in on another device, they will see advertisements related to documentary films.

[0131] Prompt Sentence Examples

[0132] Below are some example prompts that can be used with generative AI models:

[0133] Based on the data "I like action movies," select and display relevant ads.

[0134] Hardware and software used

[0135] The system uses the following hardware and software:

[0136] Hardware: User devices (computers, smartphones, tablets, etc.), servers

[0137] Software: Database management system, generative AI model, ID linking system, survey management software

[0138] This allows users to provide information of their own volition and receive benefits in return, while the system performs highly accurate data analysis and provides optimal advertisements and services, creating a valuable experience for both users and advertisers.

[0139] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0140] Step 1: Create an account and log in

[0141] The user enters account information (username, password, etc.) and clicks the "Login" button. The terminal sends this information to the server. The server receives this information and authenticates the user by referencing a database. It receives the username and password as input, compares them with the database, and outputs the authentication result.

[0142] Step 2: Present the survey

[0143] If the authentication is successful, the server generates a questionnaire and sends it to the terminal. The terminal displays this questionnaire to the user. The server receives the user's login status as input, generates the questionnaire content, and sends it to the terminal to present the questions to the user.

[0144] Step 3: Collect survey responses

[0145] The user answers the questionnaire and clicks the "Submit" button. The device sends the response data to the server. The server receives this data and stores it in a database. The user's response is received as input and the response data is stored by recording it in a database.

[0146] Step 4: Points awarded

[0147] After the survey responses are saved, the server processes the response data and assigns points to the user's account. The terminal displays a notification to the user that points have been assigned. The point assignment process is completed by receiving the survey response data as input, calculating the required points, and assigning them to the user.

[0148] Step 5: Analyze the data

[0149] The server extracts user data collected from the database and analyzes it using a generative AI model, thereby identifying user preferences and behavioral patterns. It receives user data as input, analyzes it using a generative AI model, and outputs user preference data.

[0150] Step 6: Ad selection

[0151] Based on the user's preference data obtained through analysis, the server selects the most suitable advertisements and services. The selected advertisements and services are sent to the device. The server receives the analysis data as input, selects the appropriate advertisements, and sends them to the device, where they are displayed.

[0152] Step 7: Unify profiles through identity federation

[0153] The server aggregates user data from different devices and generates a consistent profile. It takes data from different devices as input and generates a unified profile, providing a consistent user experience.

[0154] At each step, the input data provided by the user is sent to the server, where it is processed and analyzed to provide the optimal advertisements and services to the user.By utilizing generative AI models and ID linking, advanced data analysis and a consistent advertising experience are realized.

[0155] (Application example 1)

[0156] 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."

[0157] Conventional ad delivery systems have had difficulty effectively delivering ads based on users' preferences and behavioral patterns. Furthermore, they lacked a method for fully utilizing personal data voluntarily provided by users to directly benefit them. This has led to a demand for ad delivery that provides value to users while also benefiting advertisers.

[0158] 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.

[0159] In this invention, the server includes means for actively acquiring personal data from users, means for paying for the acquired personal data, means for analyzing the collected personal data and selecting optimal advertisements and services, means for generating advertisements based on the user's preferences, and means for displaying the selected advertisements and services on the user's terminal, thereby making it possible to effectively provide advertisements and services that match the user's preferences and bring direct benefits to the user.

[0160] "Means for actively obtaining personal data from users" are mechanisms for collecting personal information that users voluntarily provide.

[0161] "Means of paying for acquired personal data" refers to a method of rewarding users for the personal information they provide.

[0162] "Means of analyzing collected personal data and selecting optimal advertisements and services" refers to the process of analyzing the acquired data and selecting optimal advertisements and services based on the user's preferences and behavioral patterns.

[0163] "Means for displaying selected advertisements and services on the user's device" refers to a mechanism for displaying advertisements and services selected based on the analysis on the user's device.

[0164] The "means for generating advertisements based on user preferences" is a method for creating relevant advertisements based on genres and product categories that users prefer.

[0165] The present invention relates to a system that actively collects personal data from users, analyzes that data, and provides optimal advertisements and services to users. This system can be realized via a server, a user terminal, and an internet connection.

[0166] System Configuration

[0167] This system mainly consists of the following hardware and software:

[0168] server

[0169] Smartphone

[0170] Database management systems (e.g., SQLite)

[0171] Programming language (e.g. Python)

[0172] Web frameworks (e.g., Flask)

[0173] Data analysis libraries (e.g., Scikit-learn)

[0174] Obtaining user information

[0175] First, users create an account using a smartphone application and log in. After logging in, they are presented with a survey-style question, and the user voluntarily provides information about their preferences and lifestyle. This information is sent from the device to a server and stored in a database.

[0176] Payment of consideration

[0177] The server then awards points for the received personal data, allowing users to receive rewards for the information they provide, and these points can be used to purchase products or use services.

[0178] Data analysis

[0179] The server analyzes the data collected from users to identify their preferences and behavioral patterns. The analysis is performed using the data analysis library Scikit-learn. Based on the results of this analysis, the server selects the most suitable advertisements and services for the user.

[0180] Ad generation and display

[0181] The advertisements selected by the server are generated based on the user's preferences. For example, if the user likes "action movies," advertisements for related action movies are generated. These advertisements are displayed on the user's smartphone, allowing the user to view advertisements that match their preferences.

[0182] Use of generative AI and ID linking

[0183] The server uses generative AI to constantly update user profiles to provide a more accurate personalized experience. By linking IDs, information from different devices is integrated to manage consistent user data. This allows users to see ads based on their preferences even when they log in on different devices.

[0184] Specific examples

[0185] For example, if a user responds that they are interested in action movies, the server analyzes that data and delivers ads for the latest action movies to the user's smartphone.Furthermore, using generative AI, the system can quickly respond if the user's preferences change and display ads that match their new preferences.

[0186] Example prompts to input to a generative AI model:

[0187] "What is the user's favorite movie genre?" If the user answers "action," what kind of ad would be best?

[0188] This allows users to view advertisements based on their preferences, and advertisers can effectively deliver advertisements to target users.

[0189] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0190] Step 1:

[0191] A user logs in to a smartphone app and creates an account. The user's login information (user ID and password) is required as input, and this information is sent from the device to the server. The server receives this information and stores it in a database. This authenticates the user's login.

[0192] Step 2:

[0193] The server presents the user with questionnaire-style questions. As input, the user's profile information is read from a database. The server generates questions and sends them to the user's device. These questions are about the user's preferences and lifestyle.

[0194] Step 3:

[0195] The user answers the survey questions. As input, the user's answer data is saved on the device and then sent to the server. As output, the answer data received by the server is saved in the database. The server confirms that the saving to the database was successful.

[0196] Step 4:

[0197] (Server) awards points to the user. As input, the user's answer data and user ID are required. Based on that data, the server calculates the points and saves them in the database. As output, the points are added to the user's account.

[0198] Step 5:

[0199] The server analyzes the collected personal data. As input, the user's personal data is extracted from the database. The server uses an analysis algorithm (such as Scikit-learn) to identify the user's preferences and behavioral patterns. As output, the analysis results are obtained.

[0200] Step 6:

[0201] The server selects the most suitable advertisements and services based on the analysis results. The analyzed data is used as input. The server uses a generative AI model to generate personalized advertisements for the user. The selected advertisement data is obtained as output.

[0202] Step 7:

[0203] The server sends the selected advertisement to the user's smartphone. The selected advertisement data and the user's device information are required as input. The advertisement data is displayed on the user's device as output.

[0204] Step 8:

[0205] The server uses generative AI to update the user profile. As input, it requires user data from different devices and platforms. The server integrates this information and generates a single user profile. As output, the updated profile data is stored in a database.

[0206] Through these steps, advertisements and services based on the user's preferences are effectively provided to the user.

[0207] 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.

[0208] The present invention relates to a system that actively collects personal data from users, analyzes the data to recognize the user's emotions, and provides optimal advertisements and services. This system is implemented in the following way.

[0209] Acquisition of user information and payment

[0210] A user first creates an account on the system and logs in. The device then sends this login information to the server. The server then authenticates the user's login and presents a questionnaire to the user who has successfully logged in. When the user answers the questions, the information is stored on the server. At this time, the emotion engine recognizes the user's facial expressions and tone of voice to determine the user's emotional state.

[0211] The server processes the response data and emotion data and rewards the user with points, which can be used to purchase products or services later.

[0212] Examples:

[0213] When a user logs into the application and answers "action" to the question "What is your favorite movie genre?", the emotion engine detects the user's facial expression and tone of voice and determines that the user is having fun. The device sends the answer and emotion data to the server, which stores the information in a database and then awards 10 points to the user's account.

[0214] Analyze data and provide personalized advertising

[0215] The server analyzes the collected user data and emotional data to identify the user's preferences and behavioral patterns. Based on the analyzed data, the server selects the most appropriate advertisements and services and displays them on the user's device.

[0216] Specifically, the analysis algorithm uses data such as "I like action movies and have fun emotions" to select relevant ads, which are then displayed while the user is browsing a web page.

[0217] Deepening personalization and ID integration

[0218] The system uses generative AI and ID federation to enhance the user's personalized experience. The server integrates data from different devices and platforms and manages it as a single profile.

[0219] This allows users to have a consistent advertising and service experience whether they are using the same system on a smartphone or a PC, and also allows for quick adaptation to changes in user behavior, preferences, and emotions, which can be reflected in the next ad display.

[0220] Examples:

[0221] If a user begins to show interest in "documentary films" on a specific device, and the emotion engine determines that the user's facial expressions indicate interest, the server will immediately update the user profile, ensuring that advertisements related to documentary films are displayed the next time the user logs in on another device.

[0222] System action

[0223] This system is implemented by a program. The process flow is explained below using a specific example.

[0224] First, the user answers a questionnaire, and the data and emotion data are sent to the server and stored in a database. The server then analyzes the data and selects the most appropriate advertisement based on the user's preferences and emotions. The selected advertisement is then displayed on the user's device.

[0225] Furthermore, generative AI is used to constantly update data and emotional state as users use the system, providing a more accurate and personalized experience.ID linking enables consistent data management across multiple devices, improving the advertising experience.

[0226] This system allows users to provide information of their own volition and receive benefits in return, while the system performs highly accurate data and sentiment analysis, enabling it to provide valuable promotions to advertisers.

[0227] The processing flow will be explained below.

[0228] Program processing flow

[0229] Step 1:

[0230] The user launches the application and enters the required information (name, email address, password, etc.) on the account creation page.

[0231] Step 2:

[0232] The terminal transmits the input user information to the server.

[0233] Step 3:

[0234] The server stores the received user information in a database and sends a confirmation message to the terminal confirming that the account has been created.

[0235] Step 4:

[0236] The terminal receives a confirmation message and displays it to the user.

[0237] Step 5:

[0238] The user is directed to the login screen and enters their account information to log in.

[0239] Step 6:

[0240] The terminal sends the login information to the server.

[0241] Step 7:

[0242] The server authenticates the user information and initiates a login session.

[0243] Step 8:

[0244] The server sends a login completion message to the terminal and simultaneously presents a questionnaire-style question.

[0245] Step 9:

[0246] The terminal will display a survey screen along with a login completion message.

[0247] Step 10:

[0248] The user enters answers to the survey questions and presses the submit button. At the same time, sensor data is collected in order for the emotion engine to recognize the user's facial expressions and tone of voice.

[0249] Step 11:

[0250] The terminal transmits the user's response and emotion data to the server.

[0251] Step 12:

[0252] The server receives the user's answers and emotion data and stores the data in a database.

[0253] Step 13:

[0254] The server analyzes the response data and emotion data and grants points to the user's account as compensation, which may be dynamically adjusted based on the emotion data.

[0255] Step 14:

[0256] The terminal displays a message to the user indicating that points have been awarded.

[0257] Step 15:

[0258] The server inputs the collected user data and emotional data into an analytical algorithm to identify the user's preferences, behavioral patterns, and emotional state.

[0259] Step 16:

[0260] The server selects the most suitable advertisements and services based on the analysis results. Based on the profile including emotional data, it selects the advertisements that are predicted to be of most interest to the user.

[0261] Step 17:

[0262] The server transmits the selected advertisement data to the advertisement server, and prepares it to be embedded in the page viewed by the user.

[0263] Step 18:

[0264] The device detects user activity, checks the page being viewed for ad space, and if there is ad space, displays personalized ads.

[0265] Step 19:

[0266] The user views the displayed ad and optionally clicks or checks for details. If the user clicks on the ad, that data is also collected along with emotional data.

[0267] Step 20:

[0268] The server monitors the display status of advertisements in real time and collects and analyzes click and viewing data.

[0269] Step 21:

[0270] The server uses generative AI and ID federation to update the user profile based on collected data and emotional state, and also works across different devices to maintain a consistent user profile.

[0271] Step 22:

[0272] The server will then reflect the updated profile information in subsequent ad selections, ensuring that users receive a consistently optimized ad experience.

[0273] Step 23:

[0274] The device periodically presents new surveys to the user and continues to collect additional personal and emotional data.

[0275] This series of steps allows users to provide information of their own volition and receive the optimal advertising experience, while the system performs highly accurate data and sentiment analysis to provide advertisers with valuable promotions.

[0276] Example 2

[0277] 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."

[0278] Conventional advertising systems typically display ads based on users' preferences and behavioral patterns, but this makes it difficult to provide optimal ads and services that respond to the user's momentary emotional state. Providing a consistent advertising experience across different devices is also a challenge. Furthermore, there is a lack of compensation for the collection of personal data, and a lack of mechanisms to encourage active user participation.

[0279] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0280] In this invention, the server includes means for actively acquiring personal data from users, means for paying for the acquired personal data, means for adding emotional data to the collected personal data and analyzing both to select optimal advertisements and services, means for displaying the selected advertisements and services on the user's terminal, and means for integrating data from different devices and managing it as a single profile. This makes it possible to provide optimal advertisements and services based on the user's momentary emotional state, allowing the user to enjoy a consistent advertising experience even when using different devices. Furthermore, paying users a fee can encourage active data provision.

[0281] "User" means an individual who uses the System and provides Personal Data.

[0282] "Personal Data" refers to information about your personal preferences, behavior, interests, etc. that you provide.

[0283] "Compensation" refers to the reward, such as points or money, that the system pays to users in exchange for providing their personal data.

[0284] "Emotion data" refers to information about the user's emotional state obtained by the emotion engine analyzing the user's facial expressions and tone of voice.

[0285] "Advertisements and Services" refers to promotions, products, and various services that the system selects and presents to users based on their user profile.

[0286] "Terminal" refers to the device (smartphone, PC, etc.) that a user uses to access the system.

[0287] "Server" refers to a central system that receives and analyzes data sent by users, and selects and delivers advertisements and services.

[0288] A "profile" refers to information that indicates a user's preferences and behavioral patterns, created by the server by integrating the user's personal data and emotional data.

[0289] "Generative AI model" refers to the artificial intelligence algorithm used by the server to analyze user data and select the most appropriate advertisements and services.

[0290] "ID federation" refers to a technology that integrates data collected from different devices and platforms into a single user profile.

[0291] The present invention is a system that actively collects personal data from users, analyzes the data to recognize the user's emotions, and provides optimal advertisements and services. This system is implemented using the following hardware and software.

[0292] Hardware and software used

[0293] Hardware: Smartphones, PCs, servers

[0294] Software: applications, database management software (e.g., MySQL), emotion engines (e.g., Affectiva SDK), and analytics algorithms (e.g., the Python library Scikit-learn)

[0295] Acquisition of user information and payment

[0296] A user creates an account on the system and logs in. The terminal sends this login information to the server, which then authenticates the user's login. After successful login, the server presents the user with questionnaire-style questions. When the user answers the questions, the terminal sends the answer data to the server. The server stores the answer data and the emotion data obtained by the emotion engine in a database and assigns points to the user's account.

[0297] Examples:

[0298] When a user logs into the application and answers "action" to the question "What is your favorite movie genre?", the emotion engine analyzes the user's facial expression and tone of voice to obtain data on their enjoyable emotional state. The device sends this response data and emotion data to the server, which stores it in a database and awards 10 points to the user's account.

[0299] Analyze data and provide personalized advertising

[0300] The server analyzes the collected user data and emotional data to identify the user's preferences and behavioral patterns. Based on the analysis results, the server selects the most appropriate advertisements and services and displays them on the user's device.

[0301] Examples:

[0302] The server analyzes the user's likes of action movies and has a feeling of fun, and selects a relevant advertisement. The advertisement is then displayed while the user is browsing a web page.

[0303] Deepening personalization and ID integration

[0304] The system uses generative AI and ID federation to deepen the user's personalized experience. The server integrates data from different devices and platforms and manages it as a single profile, providing a consistent advertising and service experience even when the user uses different devices.

[0305] Examples:

[0306] If a user shows interest in "documentary films" on a specific device and the emotion engine determines that the user's facial expressions are interesting, the server will immediately update the user profile with that information, so that the next time the user logs in from another device, advertisements related to documentary films will be displayed.

[0307] Example prompts for generative AI models

[0308] "Please create an algorithm that integrates and analyzes user behavioral and emotional data to deliver optimal ads in real time so that users can enjoy a consistent advertising experience even when they log in on different devices."

[0309] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0310] Step 1:

[0311] A user launches an application on the system, creates an account, and logs in.

[0312] Input: User's name, email address, and password

[0313] Specific operation: After launching the application, the user clicks the "New Registration" button, enters the required information to create an account, then enters an email address and password in the login form and presses the "Login" button.

[0314] Output: User login information

[0315] Step 2:

[0316] The device sends the login information to the server.

[0317] Input: User login information (email address and password)

[0318] Specific operation: The terminal application sends the login information entered by the user to the server via the HTTPS protocol.

[0319] Output: Login information sent to the server

[0320] Step 3:

[0321] The server authenticates the user's login information.

[0322] Input: Submitted login information

[0323] Specific operation: The server checks the registered information in the database and performs authentication, checking that the email address and password match.

[0324] Output: Authentication success or failure information

[0325] Step 4:

[0326] The server presents a questionnaire-style question to users who have successfully logged in.

[0327] Input: Authentication success information

[0328] Specific operation: The server generates the questionnaire form data and sends it to the terminal.

[0329] Output: Survey form data

[0330] Step 5:

[0331] The user answers the survey questions.

[0332] Input: Survey form question

[0333] Specific operation: The user enters answers to survey-style questions displayed on the device screen. For example, the user answers "action" to the question "What is your favorite movie genre?"

[0334] Output: Survey response data

[0335] Step 6:

[0336] The terminal transmits the response data to the server.

[0337] Input: Survey response data

[0338] Specific operation: When the user presses the survey send button, the device sends the response data to the server via HTTPS protocol.

[0339] Output: Survey response data sent to the server

[0340] Step 7:

[0341] The server stores the response data and emotion data and gives points in return.

[0342] Input: Submitted survey response data

[0343] Specific operation: The server saves the answer data in a database, analyzes the user's facial expressions and tone of voice using an emotion engine to generate emotion data, saves this emotion data in the database, and awards points to the user's account in return.

[0344] Output: Updated user account data (points awarded)

[0345] Step 8:

[0346] The server analyzes the collected data to identify user preferences and behavioral patterns.

[0347] Input: User data and emotion data in the database

[0348] Specific operation: Analyze the data using an analysis algorithm on the server (e.g., Python's Scikit-learn library) and generate a user profile.

[0349] Output: Parsed user profile

[0350] Step 9:

[0351] The server selects the most suitable advertisements and services and displays them on the device.

[0352] Input: Parsed user profile

[0353] How it works: The server selects the most suitable advertisements and services based on the user profile and sends the advertisement data to the device, which then displays it on the screen as an advertisement banner or pop-up.

[0354] Output: Ad displayed on device

[0355] Step 10:

[0356] The server integrates data from different devices and manages it as a single profile.

[0357] Input: User data collected from different devices

[0358] Specific operation: The server uses the user ID as a key to integrate data sent from multiple devices and update the user profile.

[0359] Output: Updated Unified User Profile

[0360] Step 11:

[0361] The server constantly updates the user profile using the generated AI model and ID federation.

[0362] Input: Latest user and sentiment data

[0363] What it does: It uses generative AI models to adapt to changes in a user's behavior and emotions, updating their profile to reflect them in the next ad they see.

[0364] Output: Real-time updated user profile

[0365] (Application example 2)

[0366] 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."

[0367] Current ad serving systems struggle to reflect user preferences and emotional data in real time, resulting in ads that don't match the user's interests or emotional state. They also lack a mechanism for quickly responding to changes in a user's emotions, potentially reducing the effectiveness of ads and the user experience. Furthermore, providing a consistent personalized experience across devices using emotion recognition technology based on a user's visual data is also a challenging task.

[0368] The specification processing by the specification 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 actively acquiring personal data from the user, means for paying for the acquired personal data, means for analyzing the collected personal data and selecting optimal advertisements and services, means for displaying the selected advertisements and services on the user's device, and means for recognizing the user's emotions from visual data acquired by the device and optimizing advertisements in real time based on the emotions. This makes it possible to display advertisements that quickly correspond to the user's emotional state, improving the user experience and maximizing the effectiveness of advertisements.

[0369] "Means of actively obtaining personal data from users" refers to methods of collecting personal information and behavioral data that users voluntarily provide.

[0370] "Means of paying for acquired personal data" refers to a method of awarding points or rewards for the personal information and behavioral data provided by the user.

[0371] "Means of analyzing collected personal data and selecting optimal advertisements and services" refers to a method of analyzing collected data to find advertisements and services that best suit the user's preferences and emotions.

[0372] The "means for displaying the selected advertisement or service on the user's device" refers to a method for displaying the selected advertisement or service on the terminal used by the user.

[0373] "Means for recognizing a user's emotions from visual data acquired by a device and optimizing advertisements in real time based on those emotions" refers to a method for analyzing emotions based on a user's visual data and instantly adjusting advertisement content according to that emotional state.

[0374] This invention relates to a system that actively collects personal data from users, analyzes the data to recognize the user's emotions, and provides optimal advertisements and services. The system of the present invention is implemented by the following means.

[0375] Acquisition of user information and payment

[0376] Users create an account on the system and log in, mainly via smart glasses. The device (smart glasses) sends this login information to the server. The server authenticates the user's login and presents questionnaire-style questions to users who have successfully logged in. When the user answers the questions, the information is saved on the server. At this time, an emotion engine recognizes the user's facial expressions and tone of voice to determine the user's emotional state. The server processes the answer data and emotion data and adds points to the user's account in return. These points can be used later to purchase products or use services.

[0377] For example, when a user answers "action" to the question "What is your favorite movie genre?" through smart glasses, the emotion engine detects the user's facial expression and tone of voice and determines that the user is having fun. The device sends the answer and emotion data to the server, which stores the information in a database and then awards 10 points to the user's account.

[0378] Analyze data and provide personalized advertising

[0379] The server analyzes the collected user data and emotional data to identify the user's preferences and behavioral patterns. Based on the analyzed data, the server selects the most appropriate advertisements and services and displays them on the user's device. Specifically, the analysis algorithm uses data such as "I like action movies and have happy emotions" to select relevant advertisements. When the user views a web page or product through the smart glasses, the advertisements are displayed.

[0380] Deepening personalization and ID integration

[0381] The system uses generative AI and ID federation to deepen the user's personalized experience. The server integrates data from different devices and platforms and manages it as a single profile. This allows for a consistent advertising and service experience even when the user uses the same system on both smart glasses and other devices (such as a smartphone or PC). Furthermore, if the user's behavior, preferences, and emotions change, the system can quickly respond and reflect them in the next ad display.

[0382] For example, if a user shows interest in "documentary films" on a specific device and the emotion engine determines that the user's facial expression is interesting, the server will immediately update the user profile with this information, so that the next time the user logs in on another device, advertisements related to documentary films will be displayed.

[0383] System action

[0384] This system is implemented using the following hardware and software.

[0385] Hardware used: Smart glasses (built-in camera, microphone)

[0386] Software used: OpenCV (face recognition), EmotionRecognition library (emotion recognition), AdSelector (ad selection)

[0387] Program processing procedure

[0388] The camera captures the user's face and obtains real-time video frames.

[0389] The visual data is analyzed using the EmotionRecognition library to extract emotion data (e.g., joy, interest).

[0390] The extracted emotion data is updated in the user profile.

[0391] AdSelector selects the best ads based on the latest user profiles and sentiment data.

[0392] Selected advertisements are overlaid on the smart glasses display.

[0393] Prompt Sentence Examples

[0394] "When a user expresses interest in a new canned drink, create a prompt that generates the most appropriate ad. For example, based on the user's interests and emotional state, you might display an ad that says, 'Buy this canned drink and get 10% off your next purchase.'"

[0395] By combining these methods, it becomes possible to display advertisements that quickly respond to the user's emotional state, improving the user experience and maximizing the effectiveness of advertisements.

[0396] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0397] Step 1:

[0398] The user puts on the smart glasses and logs into the system.

[0399] Input: User authentication information (user ID, password)

[0400] Output: Authentication token

[0401] Specific operation: The user enters their user ID and password into the login screen of the smart glasses, and the device sends this to the server. The server performs authentication processing, and if authentication is successful, generates an authentication token and sends it back to the device.

[0402] Step 2:

[0403] The server presents the user with survey-style questions.

[0404] Input: Authentication token

[0405] Output: Survey questions

[0406] Specific operation: After receiving the authentication token, the device requests survey data from the server, and the server sends a question about the user's preferences to the device. The question is displayed on the smart glasses. For example, "What is your favorite movie genre?"

[0407] Step 3:

[0408] The user fills out a questionnaire and the smart glasses capture the user's facial expressions and tone of voice.

[0409] Input: Survey responses, camera footage, audio data

[0410] Output: Answer data, emotion data

[0411] How it works: When a user responds with "action," the smart glasses' camera and microphone capture their facial expressions and tone of voice, which are then instantly stored on the device.

[0412] Step 4:

[0413] The device transmits the response data and emotion data to the server.

[0414] Input: Answer data, emotion data

[0415] Output: Notification of completion of data transmission to the server

[0416] Specific operation: The smart glasses send the captured data to the server and store it in the database. Once the server has finished storing the data, it will send a notification to the device.

[0417] Step 5:

[0418] The server analyzes the response data and emotion data, updates the user profile, and awards points.

[0419] Input: Answer data, emotion data

[0420] Output: Updated user profile, points awarded notification

[0421] Specific operation: The server analyzes the received data and determines that the user likes "action movies" and is showing signs of enjoyment. Based on this, the server updates the user profile and awards points.

[0422] Step 6:

[0423] The server selects the most suitable advertisement based on the user profile.

[0424] Input: Updated user profile

[0425] Output: Optimized ad information

[0426] How it works: Based on the user profile, the analytics algorithm selects ads related to "action movies." For example, ads for new action movies are selected.

[0427] Step 7:

[0428] The terminal displays the selected advertisement to the user in real time.

[0429] Input: Optimized ad information

[0430] Output: Ad display end notification

[0431] Specific operation: The smart glasses display the advertisement received from the server. The user sees an advertisement for a new action movie on the smart glasses display.

[0432] Step 8:

[0433] Consistent ads are served even when users change devices.

[0434] Input: Login details from different devices

[0435] Output: Consistent ad display

[0436] How it works: When a user logs in on their smartphone, the server uses the unified user profile to display appropriate ads. For example, ads displayed on smart glasses will also be displayed on their smartphone.

[0437] 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.

[0438] 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.

[0439] 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.

[0440] [Second embodiment]

[0441] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0442] 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.

[0443] 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).

[0444] 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.

[0445] 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.

[0446] 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).

[0447] 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.

[0448] 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.

[0449] 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.

[0450] 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.

[0451] 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.

[0452] 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."

[0453] The present invention relates to a system that actively collects personal data from users, analyzes the data, and provides optimal advertisements and services to the users. This system is implemented in the following manner.

[0454] Acquisition of user information and payment

[0455] First, a user creates an account on the system and logs in. The device sends this login information to the server. The server authenticates the user's login and presents a questionnaire-style question to the user who has successfully logged in. When the user answers the question and submits it, the information is stored on the server.

[0456] The server processes the response data and rewards the user with points, which can be used to purchase products or services later.

[0457] Examples:

[0458] Suppose a user logs into the application and answers "Action" to the question "What is your favorite movie genre?" The device sends the answer to the server, which stores the information in a database and then credits the user's account with 10 points.

[0459] Analyze data and provide personalized advertising

[0460] The server analyzes the collected user data to identify the user's preferences and behavioral patterns. Based on the analyzed data, the server selects the most suitable advertisements and services and displays them on the user's device.

[0461] Specifically, an analytics algorithm uses data like "I like action movies" to select relevant ads that are then displayed while the user is browsing a webpage.

[0462] Deepening personalization and ID integration

[0463] The system uses generative AI and ID federation to enhance the user's personalized experience. The server integrates data from different devices and platforms and manages it as a single profile.

[0464] This allows users to have a consistent advertising and service experience whether they are using the same system on a smartphone or PC, and also allows for quick response to changes in user behavior or preferences, which can be reflected in the next ad display.

[0465] Examples:

[0466] If a user begins to show interest in "documentary films" on a particular device, the server will immediately update that information in the user's profile, ensuring that the next time the user logs in on another device, they will see advertisements related to documentary films.

[0467] System action

[0468] This system is implemented by a program. The process flow is explained below using a specific example.

[0469] First, the user answers a questionnaire, and the data is sent to a server and stored in a database. The server then analyzes the data and selects advertisements that match the user's preferences. The selected advertisements are then displayed on the user's device.

[0470] Furthermore, generative AI is used to constantly update data as users use the system, providing a more accurate and personalized experience.ID linking enables consistent data management across multiple devices, improving the advertising experience.

[0471] This system allows users to provide information of their own volition and receive benefits in return, while the system performs highly accurate data analysis to provide optimal advertisements and services, creating a valuable experience for both users and advertisers.

[0472] The processing flow will be explained below.

[0473] Program processing flow

[0474] Step 1:

[0475] The user launches the application and enters the required information (name, email address, password, etc.) on the account creation page.

[0476] Step 2:

[0477] The terminal transmits the input user information to the server.

[0478] Step 3:

[0479] The server stores the received user information in a database and sends a confirmation message to the terminal confirming that the account has been created.

[0480] Step 4:

[0481] The terminal receives a confirmation message and displays it to the user.

[0482] Step 5:

[0483] The user is directed to the login screen and enters their account information to log in.

[0484] Step 6:

[0485] The terminal sends the login information to the server.

[0486] Step 7:

[0487] The server authenticates the user information and initiates a login session.

[0488] Step 8:

[0489] The server sends a login completion message to the terminal and simultaneously presents a questionnaire-style question.

[0490] Step 9:

[0491] The terminal will display a survey screen along with a login completion message.

[0492] Step 10:

[0493] The user enters answers to the survey questions and presses the send button.

[0494] Step 11:

[0495] The terminal transmits the user's answer to the server.

[0496] Step 12:

[0497] The server receives the user's answers and stores the data in a database.

[0498] Step 13:

[0499] The server will reward the user with points in return for the answer.

[0500] Step 14:

[0501] The terminal displays a message to the user indicating that points have been awarded.

[0502] Step 15:

[0503] The server inputs the collected user data into an analytical algorithm to identify user preferences and behavioral patterns.

[0504] Step 16:

[0505] The server selects the most appropriate advertisements and services based on the analysis results.

[0506] Step 17:

[0507] The server transmits the selected advertisement data to the advertisement server, and prepares it to be embedded in the page viewed by the user.

[0508] Step 18:

[0509] The device detects user activity and displays personalized ads if advertising space is found on the page being viewed.

[0510] Step 19:

[0511] The user views the displayed advertisement and, if desired, clicks or checks for more information.

[0512] Step 20:

[0513] The server monitors the display status of advertisements in real time and collects and analyzes click and viewing data.

[0514] Step 21:

[0515] The server uses generative AI and ID federation to update user profiles based on the collected data.

[0516] Step 22:

[0517] The server will reflect the updated profile information in subsequent advertisement selections.

[0518] Step 23:

[0519] The device periodically presents new surveys to the user and continues to collect more personal data.

[0520] This series of steps allows users to provide information of their own volition and receive the optimal advertising experience, while the server performs highly accurate data analysis and can provide advertisers with valuable promotions.

[0521] Example 1

[0522] 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."

[0523] In conventional systems, when actively collecting personal data from users and analyzing that data to provide optimal advertisements and services, it was difficult to manage data consistently across devices and personalize it, which tended to fragment the user experience. There were also issues with the accuracy of data analysis and timely responses.

[0524] 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.

[0525] In this invention, the server includes means for actively acquiring personal data from users, means for paying for the acquired personal data, means for analyzing the collected personal data and selecting optimal advertisements and services, means for displaying the selected advertisements and services on the user's terminal, means for performing analysis using a generative AI model, and means for integrating data from different devices through ID federation, thereby providing a consistent personalized experience across devices and improving the accuracy of data analysis and the speed of response.

[0526] "User" refers to an individual or corporation that uses the system.

[0527] "Personal data" refers to personal information such as a user's preferences, behavioral patterns, and survey responses.

[0528] "Compensation" refers to the reward given by the system in exchange for the user providing personal data, specifically points or credits.

[0529] "Points" refer to rewards that users can earn by providing personal data, and are units that can be used when purchasing products or using services.

[0530] "Analysis" refers to the process of processing collected personal data to identify user preferences and behavioral patterns.

[0531] "Advertisement" refers to any message or content that informs users about a particular product or service.

[0532] "Service" refers to all products, functions, support, etc. provided to users.

[0533] "Terminal" refers to a hardware device used by a user, such as a computer, smartphone, or tablet.

[0534] "Server" refers to a central computer system that receives, processes, and stores information submitted by users.

[0535] "Generative AI model" refers to an artificial intelligence model used for data analysis and ad selection.

[0536] "ID linking" refers to a technology that integrates user data from different devices and manages it as a single profile.

[0537] A "profile" refers to a comprehensive collection of data such as a user's preferences and behavioral patterns.

[0538] The present invention is a system that actively collects personal data from users, analyzes the data, and provides optimal advertisements and services to the users. Specific embodiments of this system will be described below.

[0539] Acquisition of user information and payment

[0540] First, a user creates an account on the system and logs in. The device sends this login information to the server. The server authenticates the user's login and presents a questionnaire-style question to the successful user. When the user answers the questions and submits them, the information is stored on the server. The server processes the answer data and adds points to the user's account in return. These points can be used later to purchase products or use services.

[0541] A concrete example is when a user logs into an application and answers "action" to the question "What is your favorite movie genre?" The device sends the answer to the server, which stores the information in a database and then credits the user's account with 10 points.

[0542] Analyze data and provide personalized advertising

[0543] The server analyzes the collected user data using a generative AI model to identify the user's preferences and behavioral patterns. Based on the analyzed data, the server selects the most appropriate advertisements and services and displays them on the user's device. Specifically, the analysis algorithm uses the data, such as "I like action movies," to select relevant advertisements. These advertisements are then displayed while the user is browsing a web page.

[0544] Deepening personalization and ID integration

[0545] The system uses generative AI models and ID federation to deepen the user's personalized experience. The server integrates data from different devices and platforms and manages it as a single profile. This allows users to have a consistent advertising and service experience even when using the same system on both smartphones and PCs. Furthermore, if a user's behavior or preferences change, it can quickly respond and reflect that in the next ad display.

[0546] For example, if a user begins to show interest in "documentary films" on a particular device, the server can instantly update that information in the user's profile, so that the next time the user logs in on another device, they will see advertisements related to documentary films.

[0547] Prompt Sentence Examples

[0548] Below are some example prompts that can be used with generative AI models:

[0549] Based on the data "I like action movies," select and display relevant ads.

[0550] Hardware and software used

[0551] The system uses the following hardware and software:

[0552] Hardware: User devices (computers, smartphones, tablets, etc.), servers

[0553] Software: Database management system, generative AI model, ID linking system, survey management software

[0554] This allows users to provide information of their own volition and receive benefits in return, while the system performs highly accurate data analysis and provides optimal advertisements and services, creating a valuable experience for both users and advertisers.

[0555] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0556] Step 1: Create an account and log in

[0557] The user enters account information (username, password, etc.) and clicks the "Login" button. The terminal sends this information to the server. The server receives this information and authenticates the user by referencing a database. It receives the username and password as input, compares them with the database, and outputs the authentication result.

[0558] Step 2: Present the survey

[0559] If the authentication is successful, the server generates a questionnaire and sends it to the terminal. The terminal displays this questionnaire to the user. The server receives the user's login status as input, generates the questionnaire content, and sends it to the terminal to present the questions to the user.

[0560] Step 3: Collect survey responses

[0561] The user answers the questionnaire and clicks the "Submit" button. The device sends the response data to the server. The server receives this data and stores it in a database. The user's response is received as input and the response data is stored by recording it in a database.

[0562] Step 4: Points awarded

[0563] After the survey responses are saved, the server processes the response data and assigns points to the user's account. The terminal displays a notification to the user that points have been assigned. The point assignment process is completed by receiving the survey response data as input, calculating the required points, and assigning them to the user.

[0564] Step 5: Analyze the data

[0565] The server extracts user data collected from the database and analyzes it using a generative AI model, thereby identifying user preferences and behavioral patterns. It receives user data as input, analyzes it using a generative AI model, and outputs user preference data.

[0566] Step 6: Ad selection

[0567] Based on the user's preference data obtained through analysis, the server selects the most suitable advertisements and services. The selected advertisements and services are sent to the device. The server receives the analysis data as input, selects the appropriate advertisements, and sends them to the device, where they are displayed.

[0568] Step 7: Unify profiles through identity federation

[0569] The server aggregates user data from different devices and generates a consistent profile. It takes data from different devices as input and generates a unified profile, providing a consistent user experience.

[0570] At each step, the input data provided by the user is sent to the server, where it is processed and analyzed to provide the optimal advertisements and services to the user.By utilizing generative AI models and ID linking, advanced data analysis and a consistent advertising experience are realized.

[0571] (Application example 1)

[0572] 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."

[0573] Conventional ad delivery systems have had difficulty effectively delivering ads based on users' preferences and behavioral patterns. Furthermore, they lacked a method for fully utilizing personal data voluntarily provided by users to directly benefit them. This has led to a demand for ad delivery that provides value to users while also benefiting advertisers.

[0574] 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.

[0575] In this invention, the server includes means for actively acquiring personal data from users, means for paying for the acquired personal data, means for analyzing the collected personal data and selecting optimal advertisements and services, means for generating advertisements based on the user's preferences, and means for displaying the selected advertisements and services on the user's terminal, thereby making it possible to effectively provide advertisements and services that match the user's preferences and bring direct benefits to the user.

[0576] "Means for actively obtaining personal data from users" are mechanisms for collecting personal information that users voluntarily provide.

[0577] "Means of paying for acquired personal data" refers to a method of rewarding users for the personal information they provide.

[0578] "Means of analyzing collected personal data and selecting optimal advertisements and services" refers to the process of analyzing the acquired data and selecting optimal advertisements and services based on the user's preferences and behavioral patterns.

[0579] "Means for displaying selected advertisements and services on the user's device" refers to a mechanism for displaying advertisements and services selected based on the analysis on the user's device.

[0580] The "means for generating advertisements based on user preferences" is a method for creating relevant advertisements based on genres and product categories that users prefer.

[0581] The present invention relates to a system that actively collects personal data from users, analyzes that data, and provides optimal advertisements and services to users. This system can be realized via a server, a user terminal, and an internet connection.

[0582] System Configuration

[0583] This system mainly consists of the following hardware and software:

[0584] server

[0585] Smartphone

[0586] Database management systems (e.g., SQLite)

[0587] Programming language (e.g. Python)

[0588] Web frameworks (e.g., Flask)

[0589] Data analysis libraries (e.g., Scikit-learn)

[0590] Obtaining user information

[0591] First, users create an account using a smartphone application and log in. After logging in, they are presented with a survey-style question, and the user voluntarily provides information about their preferences and lifestyle. This information is sent from the device to a server and stored in a database.

[0592] Payment of consideration

[0593] The server then awards points for the received personal data, allowing users to receive rewards for the information they provide, and these points can be used to purchase products or use services.

[0594] Data analysis

[0595] The server analyzes the data collected from users to identify their preferences and behavioral patterns. The analysis is performed using the data analysis library Scikit-learn. Based on the results of this analysis, the server selects the most suitable advertisements and services for the user.

[0596] Ad generation and display

[0597] The advertisements selected by the server are generated based on the user's preferences. For example, if the user likes "action movies," advertisements for related action movies are generated. These advertisements are displayed on the user's smartphone, allowing the user to view advertisements that match their preferences.

[0598] Use of generative AI and ID linking

[0599] The server uses generative AI to constantly update user profiles to provide a more accurate personalized experience. By linking IDs, information from different devices is integrated to manage consistent user data. This allows users to see ads based on their preferences even when they log in on different devices.

[0600] Specific examples

[0601] For example, if a user responds that they are interested in action movies, the server analyzes that data and delivers ads for the latest action movies to the user's smartphone.Furthermore, using generative AI, the system can quickly respond if the user's preferences change and display ads that match their new preferences.

[0602] Example prompts to input to a generative AI model:

[0603] "What is the user's favorite movie genre?" If the user answers "action," what kind of ad would be best?

[0604] This allows users to view advertisements based on their preferences, and advertisers can effectively deliver advertisements to target users.

[0605] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0606] Step 1:

[0607] A user logs in to a smartphone app and creates an account. The user's login information (user ID and password) is required as input, and this information is sent from the device to the server. The server receives this information and stores it in a database. This authenticates the user's login.

[0608] Step 2:

[0609] The server presents the user with questionnaire-style questions. As input, the user's profile information is read from a database. The server generates questions and sends them to the user's device. These questions are about the user's preferences and lifestyle.

[0610] Step 3:

[0611] The user answers the survey questions. As input, the user's answer data is saved on the device and then sent to the server. As output, the answer data received by the server is saved in the database. The server confirms that the saving to the database was successful.

[0612] Step 4:

[0613] (Server) awards points to the user. As input, the user's answer data and user ID are required. Based on that data, the server calculates the points and saves them in the database. As output, the points are added to the user's account.

[0614] Step 5:

[0615] The server analyzes the collected personal data. As input, the user's personal data is extracted from the database. The server uses an analysis algorithm (such as Scikit-learn) to identify the user's preferences and behavioral patterns. As output, the analysis results are obtained.

[0616] Step 6:

[0617] The server selects the most suitable advertisements and services based on the analysis results. The analyzed data is used as input. The server uses a generative AI model to generate personalized advertisements for the user. The selected advertisement data is obtained as output.

[0618] Step 7:

[0619] The server sends the selected advertisement to the user's smartphone. The selected advertisement data and the user's device information are required as input. The advertisement data is displayed on the user's device as output.

[0620] Step 8:

[0621] The server uses generative AI to update the user profile. As input, it requires user data from different devices and platforms. The server integrates this information and generates a single user profile. As output, the updated profile data is stored in a database.

[0622] Through these steps, advertisements and services based on the user's preferences are effectively provided to the user.

[0623] 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.

[0624] The present invention relates to a system that actively collects personal data from users, analyzes the data to recognize the user's emotions, and provides optimal advertisements and services. This system is implemented in the following way.

[0625] Acquisition of user information and payment

[0626] A user first creates an account on the system and logs in. The device then sends this login information to the server. The server then authenticates the user's login and presents a questionnaire to the user who has successfully logged in. When the user answers the questions, the information is stored on the server. At this time, the emotion engine recognizes the user's facial expressions and tone of voice to determine the user's emotional state.

[0627] The server processes the response data and emotion data and rewards the user with points, which can be used to purchase products or services later.

[0628] Examples:

[0629] When a user logs into the application and answers "action" to the question "What is your favorite movie genre?", the emotion engine detects the user's facial expression and tone of voice and determines that the user is having fun. The device sends the answer and emotion data to the server, which stores the information in a database and then awards 10 points to the user's account.

[0630] Analyze data and provide personalized advertising

[0631] The server analyzes the collected user data and emotional data to identify the user's preferences and behavioral patterns. Based on the analyzed data, the server selects the most appropriate advertisements and services and displays them on the user's device.

[0632] Specifically, the analysis algorithm uses data such as "I like action movies and have fun emotions" to select relevant ads, which are then displayed while the user is browsing a web page.

[0633] Deepening personalization and ID integration

[0634] The system uses generative AI and ID federation to enhance the user's personalized experience. The server integrates data from different devices and platforms and manages it as a single profile.

[0635] This allows users to have a consistent advertising and service experience whether they are using the same system on a smartphone or a PC, and also allows for quick adaptation to changes in user behavior, preferences, and emotions, which can be reflected in the next ad display.

[0636] Examples:

[0637] If a user begins to show interest in "documentary films" on a specific device, and the emotion engine determines that the user's facial expressions indicate interest, the server will immediately update the user profile, ensuring that advertisements related to documentary films are displayed the next time the user logs in on another device.

[0638] System action

[0639] This system is implemented by a program. The process flow is explained below using a specific example.

[0640] First, the user answers a questionnaire, and the data and emotion data are sent to the server and stored in a database. The server then analyzes the data and selects the most appropriate advertisement based on the user's preferences and emotions. The selected advertisement is then displayed on the user's device.

[0641] Furthermore, generative AI is used to constantly update data and emotional state as users use the system, providing a more accurate and personalized experience.ID linking enables consistent data management across multiple devices, improving the advertising experience.

[0642] This system allows users to provide information of their own volition and receive benefits in return, while the system performs highly accurate data and sentiment analysis, enabling it to provide valuable promotions to advertisers.

[0643] The processing flow will be explained below.

[0644] Program processing flow

[0645] Step 1:

[0646] The user launches the application and enters the required information (name, email address, password, etc.) on the account creation page.

[0647] Step 2:

[0648] The terminal transmits the input user information to the server.

[0649] Step 3:

[0650] The server stores the received user information in a database and sends a confirmation message to the terminal confirming that the account has been created.

[0651] Step 4:

[0652] The terminal receives a confirmation message and displays it to the user.

[0653] Step 5:

[0654] The user is directed to the login screen and enters their account information to log in.

[0655] Step 6:

[0656] The terminal sends the login information to the server.

[0657] Step 7:

[0658] The server authenticates the user information and initiates a login session.

[0659] Step 8:

[0660] The server sends a login completion message to the terminal and simultaneously presents a questionnaire-style question.

[0661] Step 9:

[0662] The terminal will display a survey screen along with a login completion message.

[0663] Step 10:

[0664] The user enters answers to the survey questions and presses the submit button. At the same time, sensor data is collected in order for the emotion engine to recognize the user's facial expressions and tone of voice.

[0665] Step 11:

[0666] The terminal transmits the user's response and emotion data to the server.

[0667] Step 12:

[0668] The server receives the user's answers and emotion data and stores the data in a database.

[0669] Step 13:

[0670] The server analyzes the response data and emotion data and grants points to the user's account as compensation, which may be dynamically adjusted based on the emotion data.

[0671] Step 14:

[0672] The terminal displays a message to the user indicating that points have been awarded.

[0673] Step 15:

[0674] The server inputs the collected user data and emotional data into an analytical algorithm to identify the user's preferences, behavioral patterns, and emotional state.

[0675] Step 16:

[0676] The server selects the most suitable advertisements and services based on the analysis results. Based on the profile including emotional data, it selects the advertisements that are predicted to be of most interest to the user.

[0677] Step 17:

[0678] The server transmits the selected advertisement data to the advertisement server, and prepares it to be embedded in the page viewed by the user.

[0679] Step 18:

[0680] The device detects user activity, checks the page being viewed for ad space, and if there is ad space, displays personalized ads.

[0681] Step 19:

[0682] The user views the displayed ad and optionally clicks or checks for details. If the user clicks on the ad, that data is also collected along with emotional data.

[0683] Step 20:

[0684] The server monitors the display status of advertisements in real time and collects and analyzes click and viewing data.

[0685] Step 21:

[0686] The server uses generative AI and ID federation to update the user profile based on collected data and emotional state, and also works across different devices to maintain a consistent user profile.

[0687] Step 22:

[0688] The server will then reflect the updated profile information in subsequent ad selections, ensuring that users receive a consistently optimized ad experience.

[0689] Step 23:

[0690] The device periodically presents new surveys to the user and continues to collect additional personal and emotional data.

[0691] This series of steps allows users to provide information of their own volition and receive the optimal advertising experience, while the system performs highly accurate data and sentiment analysis to provide advertisers with valuable promotions.

[0692] Example 2

[0693] 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."

[0694] Conventional advertising systems typically display ads based on users' preferences and behavioral patterns, but this makes it difficult to provide optimal ads and services that respond to the user's momentary emotional state. Providing a consistent advertising experience across different devices is also a challenge. Furthermore, there is a lack of compensation for the collection of personal data, and a lack of mechanisms to encourage active user participation.

[0695] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0696] In this invention, the server includes means for actively acquiring personal data from users, means for paying for the acquired personal data, means for adding emotional data to the collected personal data and analyzing both to select optimal advertisements and services, means for displaying the selected advertisements and services on the user's terminal, and means for integrating data from different devices and managing it as a single profile. This makes it possible to provide optimal advertisements and services based on the user's momentary emotional state, allowing the user to enjoy a consistent advertising experience even when using different devices. Furthermore, paying users a fee can encourage active data provision.

[0697] "User" means an individual who uses the System and provides Personal Data.

[0698] "Personal Data" refers to information about your personal preferences, behavior, interests, etc. that you provide.

[0699] "Compensation" refers to the reward, such as points or money, that the system pays to users in exchange for providing their personal data.

[0700] "Emotion data" refers to information about the user's emotional state obtained by the emotion engine analyzing the user's facial expressions and tone of voice.

[0701] "Advertisements and Services" refers to promotions, products, and various services that the system selects and presents to users based on their user profile.

[0702] "Terminal" refers to the device (smartphone, PC, etc.) that a user uses to access the system.

[0703] "Server" refers to a central system that receives and analyzes data sent by users, and selects and delivers advertisements and services.

[0704] A "profile" refers to information that indicates a user's preferences and behavioral patterns, created by the server by integrating the user's personal data and emotional data.

[0705] "Generative AI model" refers to the artificial intelligence algorithm used by the server to analyze user data and select the most appropriate advertisements and services.

[0706] "ID federation" refers to a technology that integrates data collected from different devices and platforms into a single user profile.

[0707] The present invention is a system that actively collects personal data from users, analyzes the data to recognize the user's emotions, and provides optimal advertisements and services. This system is implemented using the following hardware and software.

[0708] Hardware and software used

[0709] Hardware: Smartphones, PCs, servers

[0710] Software: applications, database management software (e.g., MySQL), emotion engines (e.g., Affectiva SDK), and analytics algorithms (e.g., the Python library Scikit-learn)

[0711] Acquisition of user information and payment

[0712] A user creates an account on the system and logs in. The terminal sends this login information to the server, which then authenticates the user's login. After successful login, the server presents the user with questionnaire-style questions. When the user answers the questions, the terminal sends the answer data to the server. The server stores the answer data and the emotion data obtained by the emotion engine in a database and assigns points to the user's account.

[0713] Examples:

[0714] When a user logs into the application and answers "action" to the question "What is your favorite movie genre?", the emotion engine analyzes the user's facial expression and tone of voice to obtain data on their enjoyable emotional state. The device sends this response data and emotion data to the server, which stores it in a database and awards 10 points to the user's account.

[0715] Analyze data and provide personalized advertising

[0716] The server analyzes the collected user data and emotional data to identify the user's preferences and behavioral patterns. Based on the analysis results, the server selects the most appropriate advertisements and services and displays them on the user's device.

[0717] Examples:

[0718] The server analyzes the user's likes of action movies and has a feeling of fun, and selects a relevant advertisement. The advertisement is then displayed while the user is browsing a web page.

[0719] Deepening personalization and ID integration

[0720] The system uses generative AI and ID federation to deepen the user's personalized experience. The server integrates data from different devices and platforms and manages it as a single profile, providing a consistent advertising and service experience even when the user uses different devices.

[0721] Examples:

[0722] If a user shows interest in "documentary films" on a specific device and the emotion engine determines that the user's facial expressions are interesting, the server will immediately update the user profile with that information, so that the next time the user logs in from another device, advertisements related to documentary films will be displayed.

[0723] Example prompts for generative AI models

[0724] "Please create an algorithm that integrates and analyzes user behavioral and emotional data to deliver optimal ads in real time so that users can enjoy a consistent advertising experience even when they log in on different devices."

[0725] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0726] Step 1:

[0727] A user launches an application on the system, creates an account, and logs in.

[0728] Input: User's name, email address, and password

[0729] Specific operation: After launching the application, the user clicks the "New Registration" button, enters the required information to create an account, then enters an email address and password in the login form and presses the "Login" button.

[0730] Output: User login information

[0731] Step 2:

[0732] The device sends the login information to the server.

[0733] Input: User login information (email address and password)

[0734] Specific operation: The terminal application sends the login information entered by the user to the server via the HTTPS protocol.

[0735] Output: Login information sent to the server

[0736] Step 3:

[0737] The server authenticates the user's login information.

[0738] Input: Submitted login information

[0739] Specific operation: The server checks the registered information in the database and performs authentication, checking that the email address and password match.

[0740] Output: Authentication success or failure information

[0741] Step 4:

[0742] The server presents a questionnaire-style question to users who have successfully logged in.

[0743] Input: Authentication success information

[0744] Specific operation: The server generates the questionnaire form data and sends it to the terminal.

[0745] Output: Survey form data

[0746] Step 5:

[0747] The user answers the survey questions.

[0748] Input: Survey form question

[0749] Specific operation: The user enters answers to survey-style questions displayed on the device screen. For example, the user answers "action" to the question "What is your favorite movie genre?"

[0750] Output: Survey response data

[0751] Step 6:

[0752] The terminal transmits the response data to the server.

[0753] Input: Survey response data

[0754] Specific operation: When the user presses the survey send button, the device sends the response data to the server via HTTPS protocol.

[0755] Output: Survey response data sent to the server

[0756] Step 7:

[0757] The server stores the response data and emotion data and gives points in return.

[0758] Input: Submitted survey response data

[0759] Specific operation: The server saves the answer data in a database, analyzes the user's facial expressions and tone of voice using an emotion engine to generate emotion data, saves this emotion data in the database, and awards points to the user's account in return.

[0760] Output: Updated user account data (points awarded)

[0761] Step 8:

[0762] The server analyzes the collected data to identify user preferences and behavioral patterns.

[0763] Input: User data and emotion data in the database

[0764] Specific operation: Analyze the data using an analysis algorithm on the server (e.g., Python's Scikit-learn library) and generate a user profile.

[0765] Output: Parsed user profile

[0766] Step 9:

[0767] The server selects the most suitable advertisements and services and displays them on the device.

[0768] Input: Parsed user profile

[0769] How it works: The server selects the most suitable advertisements and services based on the user profile and sends the advertisement data to the device, which then displays it on the screen as an advertisement banner or pop-up.

[0770] Output: Ad displayed on device

[0771] Step 10:

[0772] The server integrates data from different devices and manages it as a single profile.

[0773] Input: User data collected from different devices

[0774] Specific operation: The server uses the user ID as a key to integrate data sent from multiple devices and update the user profile.

[0775] Output: Updated Unified User Profile

[0776] Step 11:

[0777] The server constantly updates the user profile using the generated AI model and ID federation.

[0778] Input: Latest user and sentiment data

[0779] What it does: It uses generative AI models to adapt to changes in a user's behavior and emotions, updating their profile to reflect them in the next ad they see.

[0780] Output: Real-time updated user profile

[0781] (Application example 2)

[0782] 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."

[0783] Current ad serving systems struggle to reflect user preferences and emotional data in real time, resulting in ads that don't match the user's interests or emotional state. They also lack a mechanism for quickly responding to changes in a user's emotions, potentially reducing the effectiveness of ads and the user experience. Furthermore, providing a consistent personalized experience across devices using emotion recognition technology based on a user's visual data is also a challenging task.

[0784] The specification processing by the specification 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 actively acquiring personal data from the user, means for paying for the acquired personal data, means for analyzing the collected personal data and selecting optimal advertisements and services, means for displaying the selected advertisements and services on the user's device, and means for recognizing the user's emotions from visual data acquired by the device and optimizing advertisements in real time based on the emotions. This makes it possible to display advertisements that quickly correspond to the user's emotional state, improving the user experience and maximizing the effectiveness of advertisements.

[0785] "Means of actively obtaining personal data from users" refers to methods of collecting personal information and behavioral data that users voluntarily provide.

[0786] "Means of paying for acquired personal data" refers to a method of awarding points or rewards for the personal information and behavioral data provided by the user.

[0787] "Means of analyzing collected personal data and selecting optimal advertisements and services" refers to a method of analyzing collected data to find advertisements and services that best suit the user's preferences and emotions.

[0788] The "means for displaying the selected advertisement or service on the user's device" refers to a method for displaying the selected advertisement or service on the terminal used by the user.

[0789] "Means for recognizing a user's emotions from visual data acquired by a device and optimizing advertisements in real time based on those emotions" refers to a method for analyzing emotions based on a user's visual data and instantly adjusting advertisement content according to that emotional state.

[0790] This invention relates to a system that actively collects personal data from users, analyzes the data to recognize the user's emotions, and provides optimal advertisements and services. The system of the present invention is implemented by the following means.

[0791] Acquisition of user information and payment

[0792] Users create an account on the system and log in, mainly via smart glasses. The device (smart glasses) sends this login information to the server. The server authenticates the user's login and presents questionnaire-style questions to users who have successfully logged in. When the user answers the questions, the information is saved on the server. At this time, an emotion engine recognizes the user's facial expressions and tone of voice to determine the user's emotional state. The server processes the answer data and emotion data and adds points to the user's account in return. These points can be used later to purchase products or use services.

[0793] For example, when a user answers "action" to the question "What is your favorite movie genre?" through smart glasses, the emotion engine detects the user's facial expression and tone of voice and determines that the user is having fun. The device sends the answer and emotion data to the server, which stores the information in a database and then awards 10 points to the user's account.

[0794] Analyze data and provide personalized advertising

[0795] The server analyzes the collected user data and emotional data to identify the user's preferences and behavioral patterns. Based on the analyzed data, the server selects the most appropriate advertisements and services and displays them on the user's device. Specifically, the analysis algorithm uses data such as "I like action movies and have happy emotions" to select relevant advertisements. When the user views a web page or product through the smart glasses, the advertisements are displayed.

[0796] Deepening personalization and ID integration

[0797] The system uses generative AI and ID federation to deepen the user's personalized experience. The server integrates data from different devices and platforms and manages it as a single profile. This allows for a consistent advertising and service experience even when the user uses the same system on both smart glasses and other devices (such as a smartphone or PC). Furthermore, if the user's behavior, preferences, and emotions change, the system can quickly respond and reflect them in the next ad display.

[0798] For example, if a user shows interest in "documentary films" on a specific device and the emotion engine determines that the user's facial expression is interesting, the server will immediately update the user profile with this information, so that the next time the user logs in on another device, advertisements related to documentary films will be displayed.

[0799] System action

[0800] This system is implemented using the following hardware and software.

[0801] Hardware used: Smart glasses (built-in camera, microphone)

[0802] Software used: OpenCV (face recognition), EmotionRecognition library (emotion recognition), AdSelector (ad selection)

[0803] Program processing procedure

[0804] The camera captures the user's face and obtains real-time video frames.

[0805] The visual data is analyzed using the EmotionRecognition library to extract emotion data (e.g., joy, interest).

[0806] The extracted emotion data is updated in the user profile.

[0807] AdSelector selects the best ads based on the latest user profiles and sentiment data.

[0808] Selected advertisements are overlaid on the smart glasses display.

[0809] Prompt Sentence Examples

[0810] "When a user expresses interest in a new canned drink, create a prompt that generates the most appropriate ad. For example, based on the user's interests and emotional state, you might display an ad that says, 'Buy this canned drink and get 10% off your next purchase.'"

[0811] By combining these methods, it becomes possible to display advertisements that quickly respond to the user's emotional state, improving the user experience and maximizing the effectiveness of advertisements.

[0812] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0813] Step 1:

[0814] The user puts on the smart glasses and logs into the system.

[0815] Input: User authentication information (user ID, password)

[0816] Output: Authentication token

[0817] Specific operation: The user enters their user ID and password into the login screen of the smart glasses, and the device sends this to the server. The server performs authentication processing, and if authentication is successful, generates an authentication token and sends it back to the device.

[0818] Step 2:

[0819] The server presents the user with survey-style questions.

[0820] Input: Authentication token

[0821] Output: Survey questions

[0822] Specific operation: After receiving the authentication token, the device requests survey data from the server, and the server sends a question about the user's preferences to the device. The question is displayed on the smart glasses. For example, "What is your favorite movie genre?"

[0823] Step 3:

[0824] The user fills out a questionnaire and the smart glasses capture the user's facial expressions and tone of voice.

[0825] Input: Survey responses, camera footage, audio data

[0826] Output: Answer data, emotion data

[0827] How it works: When a user responds with "action," the smart glasses' camera and microphone capture their facial expressions and tone of voice, which are then instantly stored on the device.

[0828] Step 4:

[0829] The device transmits the response data and emotion data to the server.

[0830] Input: Answer data, emotion data

[0831] Output: Notification of completion of data transmission to the server

[0832] Specific operation: The smart glasses send the captured data to the server and store it in the database. Once the server has finished storing the data, it will send a notification to the device.

[0833] Step 5:

[0834] The server analyzes the response data and emotion data, updates the user profile, and awards points.

[0835] Input: Answer data, emotion data

[0836] Output: Updated user profile, points awarded notification

[0837] Specific operation: The server analyzes the received data and determines that the user likes "action movies" and is showing signs of enjoyment. Based on this, the server updates the user profile and awards points.

[0838] Step 6:

[0839] The server selects the most suitable advertisement based on the user profile.

[0840] Input: Updated user profile

[0841] Output: Optimized ad information

[0842] How it works: Based on the user profile, the analytics algorithm selects ads related to "action movies." For example, ads for new action movies are selected.

[0843] Step 7:

[0844] The terminal displays the selected advertisement to the user in real time.

[0845] Input: Optimized ad information

[0846] Output: Ad display end notification

[0847] Specific operation: The smart glasses display the advertisement received from the server. The user sees an advertisement for a new action movie on the smart glasses display.

[0848] Step 8:

[0849] Consistent ads are served even when users change devices.

[0850] Input: Login details from different devices

[0851] Output: Consistent ad display

[0852] How it works: When a user logs in on their smartphone, the server uses the unified user profile to display appropriate ads. For example, ads displayed on smart glasses will also be displayed on their smartphone.

[0853] 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.

[0854] 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.

[0855] 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.

[0856] [Third embodiment]

[0857] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0858] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0859] 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).

[0860] 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.

[0861] 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.

[0862] 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).

[0863] 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.

[0864] 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.

[0865] 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.

[0866] 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.

[0867] 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.

[0868] 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."

[0869] The present invention relates to a system that actively collects personal data from users, analyzes the data, and provides optimal advertisements and services to the users. This system is implemented in the following manner.

[0870] Acquisition of user information and payment

[0871] First, a user creates an account on the system and logs in. The device sends this login information to the server. The server authenticates the user's login and presents a questionnaire-style question to the user who has successfully logged in. When the user answers the question and submits it, the information is stored on the server.

[0872] The server processes the response data and rewards the user with points, which can be used to purchase products or services later.

[0873] Examples:

[0874] Suppose a user logs into the application and answers "Action" to the question "What is your favorite movie genre?" The device sends the answer to the server, which stores the information in a database and then credits the user's account with 10 points.

[0875] Analyze data and provide personalized advertising

[0876] The server analyzes the collected user data to identify the user's preferences and behavioral patterns. Based on the analyzed data, the server selects the most suitable advertisements and services and displays them on the user's device.

[0877] Specifically, an analytics algorithm uses data like "I like action movies" to select relevant ads that are then displayed while the user is browsing a webpage.

[0878] Deepening personalization and ID integration

[0879] The system uses generative AI and ID federation to enhance the user's personalized experience. The server integrates data from different devices and platforms and manages it as a single profile.

[0880] This allows users to have a consistent advertising and service experience whether they are using the same system on a smartphone or PC, and also allows for quick response to changes in user behavior or preferences, which can be reflected in the next ad display.

[0881] Examples:

[0882] If a user begins to show interest in "documentary films" on a particular device, the server will immediately update that information in the user's profile, ensuring that the next time the user logs in on another device, they will see advertisements related to documentary films.

[0883] System action

[0884] This system is implemented by a program. The process flow is explained below using a specific example.

[0885] First, the user answers a questionnaire, and the data is sent to a server and stored in a database. The server then analyzes the data and selects advertisements that match the user's preferences. The selected advertisements are then displayed on the user's device.

[0886] Furthermore, generative AI is used to constantly update data as users use the system, providing a more accurate and personalized experience.ID linking enables consistent data management across multiple devices, improving the advertising experience.

[0887] This system allows users to provide information of their own volition and receive benefits in return, while the system performs highly accurate data analysis to provide optimal advertisements and services, creating a valuable experience for both users and advertisers.

[0888] The processing flow will be explained below.

[0889] Program processing flow

[0890] Step 1:

[0891] The user launches the application and enters the required information (name, email address, password, etc.) on the account creation page.

[0892] Step 2:

[0893] The terminal transmits the input user information to the server.

[0894] Step 3:

[0895] The server stores the received user information in a database and sends a confirmation message to the terminal confirming that the account has been created.

[0896] Step 4:

[0897] The terminal receives a confirmation message and displays it to the user.

[0898] Step 5:

[0899] The user is directed to the login screen and enters their account information to log in.

[0900] Step 6:

[0901] The terminal sends the login information to the server.

[0902] Step 7:

[0903] The server authenticates the user information and initiates a login session.

[0904] Step 8:

[0905] The server sends a login completion message to the terminal and simultaneously presents a questionnaire-style question.

[0906] Step 9:

[0907] The terminal will display a survey screen along with a login completion message.

[0908] Step 10:

[0909] The user enters answers to the survey questions and presses the send button.

[0910] Step 11:

[0911] The terminal transmits the user's answer to the server.

[0912] Step 12:

[0913] The server receives the user's answers and stores the data in a database.

[0914] Step 13:

[0915] The server will reward the user with points in return for the answer.

[0916] Step 14:

[0917] The terminal displays a message to the user indicating that points have been awarded.

[0918] Step 15:

[0919] The server inputs the collected user data into an analytical algorithm to identify user preferences and behavioral patterns.

[0920] Step 16:

[0921] The server selects the most appropriate advertisements and services based on the analysis results.

[0922] Step 17:

[0923] The server transmits the selected advertisement data to the advertisement server, and prepares it to be embedded in the page viewed by the user.

[0924] Step 18:

[0925] The device detects user activity and displays personalized ads if advertising space is found on the page being viewed.

[0926] Step 19:

[0927] The user views the displayed advertisement and, if desired, clicks or checks for more information.

[0928] Step 20:

[0929] The server monitors the display status of advertisements in real time and collects and analyzes click and viewing data.

[0930] Step 21:

[0931] The server uses generative AI and ID federation to update user profiles based on the collected data.

[0932] Step 22:

[0933] The server will reflect the updated profile information in subsequent advertisement selections.

[0934] Step 23:

[0935] The device periodically presents new surveys to the user and continues to collect more personal data.

[0936] This series of steps allows users to provide information of their own volition and receive the optimal advertising experience, while the server performs highly accurate data analysis and can provide advertisers with valuable promotions.

[0937] Example 1

[0938] 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."

[0939] In conventional systems, when actively collecting personal data from users and analyzing that data to provide optimal advertisements and services, it was difficult to manage data consistently across devices and personalize it, which tended to fragment the user experience. There were also issues with the accuracy of data analysis and timely responses.

[0940] 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.

[0941] In this invention, the server includes means for actively acquiring personal data from users, means for paying for the acquired personal data, means for analyzing the collected personal data and selecting optimal advertisements and services, means for displaying the selected advertisements and services on the user's terminal, means for performing analysis using a generative AI model, and means for integrating data from different devices through ID federation, thereby providing a consistent personalized experience across devices and improving the accuracy of data analysis and the speed of response.

[0942] "User" refers to an individual or corporation that uses the system.

[0943] "Personal data" refers to personal information such as a user's preferences, behavioral patterns, and survey responses.

[0944] "Compensation" refers to the reward given by the system in exchange for the user providing personal data, specifically points or credits.

[0945] "Points" refer to rewards that users can earn by providing personal data, and are units that can be used when purchasing products or using services.

[0946] "Analysis" refers to the process of processing collected personal data to identify user preferences and behavioral patterns.

[0947] "Advertisement" refers to any message or content that informs users about a particular product or service.

[0948] "Service" refers to all products, functions, support, etc. provided to users.

[0949] "Terminal" refers to a hardware device used by a user, such as a computer, smartphone, or tablet.

[0950] "Server" refers to a central computer system that receives, processes, and stores information submitted by users.

[0951] "Generative AI model" refers to an artificial intelligence model used for data analysis and ad selection.

[0952] "ID linking" refers to a technology that integrates user data from different devices and manages it as a single profile.

[0953] A "profile" refers to a comprehensive collection of data such as a user's preferences and behavioral patterns.

[0954] The present invention is a system that actively collects personal data from users, analyzes the data, and provides optimal advertisements and services to the users. Specific embodiments of this system will be described below.

[0955] Acquisition of user information and payment

[0956] First, a user creates an account on the system and logs in. The device sends this login information to the server. The server authenticates the user's login and presents a questionnaire-style question to the successful user. When the user answers the questions and submits them, the information is stored on the server. The server processes the answer data and adds points to the user's account in return. These points can be used later to purchase products or use services.

[0957] A concrete example is when a user logs into an application and answers "action" to the question "What is your favorite movie genre?" The device sends the answer to the server, which stores the information in a database and then credits the user's account with 10 points.

[0958] Analyze data and provide personalized advertising

[0959] The server analyzes the collected user data using a generative AI model to identify the user's preferences and behavioral patterns. Based on the analyzed data, the server selects the most appropriate advertisements and services and displays them on the user's device. Specifically, the analysis algorithm uses the data, such as "I like action movies," to select relevant advertisements. These advertisements are then displayed while the user is browsing a web page.

[0960] Deepening personalization and ID integration

[0961] The system uses generative AI models and ID federation to deepen the user's personalized experience. The server integrates data from different devices and platforms and manages it as a single profile. This allows users to have a consistent advertising and service experience even when using the same system on both smartphones and PCs. Furthermore, if a user's behavior or preferences change, it can quickly respond and reflect that in the next ad display.

[0962] For example, if a user begins to show interest in "documentary films" on a particular device, the server can instantly update that information in the user's profile, so that the next time the user logs in on another device, they will see advertisements related to documentary films.

[0963] Prompt Sentence Examples

[0964] Below are some example prompts that can be used with generative AI models:

[0965] Based on the data "I like action movies," select and display relevant ads.

[0966] Hardware and software used

[0967] The system uses the following hardware and software:

[0968] Hardware: User devices (computers, smartphones, tablets, etc.), servers

[0969] Software: Database management system, generative AI model, ID linking system, survey management software

[0970] This allows users to provide information of their own volition and receive benefits in return, while the system performs highly accurate data analysis and provides optimal advertisements and services, creating a valuable experience for both users and advertisers.

[0971] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0972] Step 1: Create an account and log in

[0973] The user enters account information (username, password, etc.) and clicks the "Login" button. The terminal sends this information to the server. The server receives this information and authenticates the user by referencing a database. It receives the username and password as input, compares them with the database, and outputs the authentication result.

[0974] Step 2: Present the survey

[0975] If the authentication is successful, the server generates a questionnaire and sends it to the terminal. The terminal displays this questionnaire to the user. The server receives the user's login status as input, generates the questionnaire content, and sends it to the terminal to present the questions to the user.

[0976] Step 3: Collect survey responses

[0977] The user answers the questionnaire and clicks the "Submit" button. The device sends the response data to the server. The server receives this data and stores it in a database. The user's response is received as input and the response data is stored by recording it in a database.

[0978] Step 4: Points awarded

[0979] After the survey responses are saved, the server processes the response data and assigns points to the user's account. The terminal displays a notification to the user that points have been assigned. The point assignment process is completed by receiving the survey response data as input, calculating the required points, and assigning them to the user.

[0980] Step 5: Analyze the data

[0981] The server extracts user data collected from the database and analyzes it using a generative AI model, thereby identifying user preferences and behavioral patterns. It receives user data as input, analyzes it using a generative AI model, and outputs user preference data.

[0982] Step 6: Ad selection

[0983] Based on the user's preference data obtained through analysis, the server selects the most suitable advertisements and services. The selected advertisements and services are sent to the device. The server receives the analysis data as input, selects the appropriate advertisements, and sends them to the device, where they are displayed.

[0984] Step 7: Unify profiles through identity federation

[0985] The server aggregates user data from different devices and generates a consistent profile. It takes data from different devices as input and generates a unified profile, providing a consistent user experience.

[0986] At each step, the input data provided by the user is sent to the server, where it is processed and analyzed to provide the optimal advertisements and services to the user.By utilizing generative AI models and ID linking, advanced data analysis and a consistent advertising experience are realized.

[0987] (Application example 1)

[0988] 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."

[0989] Conventional ad delivery systems have had difficulty effectively delivering ads based on users' preferences and behavioral patterns. Furthermore, they lacked a method for fully utilizing personal data voluntarily provided by users to directly benefit them. This has led to a demand for ad delivery that provides value to users while also benefiting advertisers.

[0990] 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.

[0991] In this invention, the server includes means for actively acquiring personal data from users, means for paying for the acquired personal data, means for analyzing the collected personal data and selecting optimal advertisements and services, means for generating advertisements based on the user's preferences, and means for displaying the selected advertisements and services on the user's terminal, thereby making it possible to effectively provide advertisements and services that match the user's preferences and bring direct benefits to the user.

[0992] "Means for actively obtaining personal data from users" are mechanisms for collecting personal information that users voluntarily provide.

[0993] "Means of paying for acquired personal data" refers to a method of rewarding users for the personal information they provide.

[0994] "Means of analyzing collected personal data and selecting optimal advertisements and services" refers to the process of analyzing the acquired data and selecting optimal advertisements and services based on the user's preferences and behavioral patterns.

[0995] "Means for displaying selected advertisements and services on the user's device" refers to a mechanism for displaying advertisements and services selected based on the analysis on the user's device.

[0996] The "means for generating advertisements based on user preferences" is a method for creating relevant advertisements based on genres and product categories that users prefer.

[0997] The present invention relates to a system that actively collects personal data from users, analyzes that data, and provides optimal advertisements and services to users. This system can be realized via a server, a user terminal, and an internet connection.

[0998] System Configuration

[0999] This system mainly consists of the following hardware and software:

[1000] server

[1001] Smartphone

[1002] Database management systems (e.g., SQLite)

[1003] Programming language (e.g. Python)

[1004] Web frameworks (e.g., Flask)

[1005] Data analysis libraries (e.g., Scikit-learn)

[1006] Obtaining user information

[1007] First, users create an account using a smartphone application and log in. After logging in, they are presented with a survey-style question, and the user voluntarily provides information about their preferences and lifestyle. This information is sent from the device to a server and stored in a database.

[1008] Payment of consideration

[1009] The server then awards points for the received personal data, allowing users to receive rewards for the information they provide, and these points can be used to purchase products or use services.

[1010] Data analysis

[1011] The server analyzes the data collected from users to identify their preferences and behavioral patterns. The analysis is performed using the data analysis library Scikit-learn. Based on the results of this analysis, the server selects the most suitable advertisements and services for the user.

[1012] Ad generation and display

[1013] The advertisements selected by the server are generated based on the user's preferences. For example, if the user likes "action movies," advertisements for related action movies are generated. These advertisements are displayed on the user's smartphone, allowing the user to view advertisements that match their preferences.

[1014] Use of generative AI and ID linking

[1015] The server uses generative AI to constantly update user profiles to provide a more accurate personalized experience. By linking IDs, information from different devices is integrated to manage consistent user data. This allows users to see ads based on their preferences even when they log in on different devices.

[1016] Specific examples

[1017] For example, if a user responds that they are interested in action movies, the server analyzes that data and delivers ads for the latest action movies to the user's smartphone.Furthermore, using generative AI, the system can quickly respond if the user's preferences change and display ads that match their new preferences.

[1018] Example prompts to input to a generative AI model:

[1019] "What is the user's favorite movie genre?" If the user answers "action," what kind of ad would be best?

[1020] This allows users to view advertisements based on their preferences, and advertisers can effectively deliver advertisements to target users.

[1021] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1022] Step 1:

[1023] A user logs in to a smartphone app and creates an account. The user's login information (user ID and password) is required as input, and this information is sent from the device to the server. The server receives this information and stores it in a database. This authenticates the user's login.

[1024] Step 2:

[1025] The server presents the user with questionnaire-style questions. As input, the user's profile information is read from a database. The server generates questions and sends them to the user's device. These questions are about the user's preferences and lifestyle.

[1026] Step 3:

[1027] The user answers the survey questions. As input, the user's answer data is saved on the device and then sent to the server. As output, the answer data received by the server is saved in the database. The server confirms that the saving to the database was successful.

[1028] Step 4:

[1029] (Server) awards points to the user. As input, the user's answer data and user ID are required. Based on that data, the server calculates the points and saves them in the database. As output, the points are added to the user's account.

[1030] Step 5:

[1031] The server analyzes the collected personal data. As input, the user's personal data is extracted from the database. The server uses an analysis algorithm (such as Scikit-learn) to identify the user's preferences and behavioral patterns. As output, the analysis results are obtained.

[1032] Step 6:

[1033] The server selects the most suitable advertisements and services based on the analysis results. The analyzed data is used as input. The server uses a generative AI model to generate personalized advertisements for the user. The selected advertisement data is obtained as output.

[1034] Step 7:

[1035] The server sends the selected advertisement to the user's smartphone. The selected advertisement data and the user's device information are required as input. The advertisement data is displayed on the user's device as output.

[1036] Step 8:

[1037] The server uses generative AI to update the user profile. As input, it requires user data from different devices and platforms. The server integrates this information and generates a single user profile. As output, the updated profile data is stored in a database.

[1038] Through these steps, advertisements and services based on the user's preferences are effectively provided to the user.

[1039] 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.

[1040] The present invention relates to a system that actively collects personal data from users, analyzes the data to recognize the user's emotions, and provides optimal advertisements and services. This system is implemented in the following way.

[1041] Acquisition of user information and payment

[1042] A user first creates an account on the system and logs in. The device then sends this login information to the server. The server then authenticates the user's login and presents a questionnaire to the user who has successfully logged in. When the user answers the questions, the information is stored on the server. At this time, the emotion engine recognizes the user's facial expressions and tone of voice to determine the user's emotional state.

[1043] The server processes the response data and emotion data and rewards the user with points, which can be used to purchase products or services later.

[1044] Examples:

[1045] When a user logs into the application and answers "action" to the question "What is your favorite movie genre?", the emotion engine detects the user's facial expression and tone of voice and determines that the user is having fun. The device sends the answer and emotion data to the server, which stores the information in a database and then awards 10 points to the user's account.

[1046] Analyze data and provide personalized advertising

[1047] The server analyzes the collected user data and emotional data to identify the user's preferences and behavioral patterns. Based on the analyzed data, the server selects the most appropriate advertisements and services and displays them on the user's device.

[1048] Specifically, the analysis algorithm uses data such as "I like action movies and have fun emotions" to select relevant ads, which are then displayed while the user is browsing a web page.

[1049] Deepening personalization and ID integration

[1050] The system uses generative AI and ID federation to enhance the user's personalized experience. The server integrates data from different devices and platforms and manages it as a single profile.

[1051] This allows users to have a consistent advertising and service experience whether they are using the same system on a smartphone or a PC, and also allows for quick adaptation to changes in user behavior, preferences, and emotions, which can be reflected in the next ad display.

[1052] Examples:

[1053] If a user begins to show interest in "documentary films" on a specific device, and the emotion engine determines that the user's facial expressions indicate interest, the server will immediately update the user profile, ensuring that advertisements related to documentary films are displayed the next time the user logs in on another device.

[1054] System action

[1055] This system is implemented by a program. The process flow is explained below using a specific example.

[1056] First, the user answers a questionnaire, and the data and emotion data are sent to the server and stored in a database. The server then analyzes the data and selects the most appropriate advertisement based on the user's preferences and emotions. The selected advertisement is then displayed on the user's device.

[1057] Furthermore, generative AI is used to constantly update data and emotional state as users use the system, providing a more accurate and personalized experience.ID linking enables consistent data management across multiple devices, improving the advertising experience.

[1058] This system allows users to provide information of their own volition and receive benefits in return, while the system performs highly accurate data and sentiment analysis, enabling it to provide valuable promotions to advertisers.

[1059] The processing flow will be explained below.

[1060] Program processing flow

[1061] Step 1:

[1062] The user launches the application and enters the required information (name, email address, password, etc.) on the account creation page.

[1063] Step 2:

[1064] The terminal transmits the input user information to the server.

[1065] Step 3:

[1066] The server stores the received user information in a database and sends a confirmation message to the terminal confirming that the account has been created.

[1067] Step 4:

[1068] The terminal receives a confirmation message and displays it to the user.

[1069] Step 5:

[1070] The user is directed to the login screen and enters their account information to log in.

[1071] Step 6:

[1072] The terminal sends the login information to the server.

[1073] Step 7:

[1074] The server authenticates the user information and initiates a login session.

[1075] Step 8:

[1076] The server sends a login completion message to the terminal and simultaneously presents a questionnaire-style question.

[1077] Step 9:

[1078] The terminal will display a survey screen along with a login completion message.

[1079] Step 10:

[1080] The user enters answers to the survey questions and presses the submit button. At the same time, sensor data is collected in order for the emotion engine to recognize the user's facial expressions and tone of voice.

[1081] Step 11:

[1082] The terminal transmits the user's response and emotion data to the server.

[1083] Step 12:

[1084] The server receives the user's answers and emotion data and stores the data in a database.

[1085] Step 13:

[1086] The server analyzes the response data and emotion data and grants points to the user's account as compensation, which may be dynamically adjusted based on the emotion data.

[1087] Step 14:

[1088] The terminal displays a message to the user indicating that points have been awarded.

[1089] Step 15:

[1090] The server inputs the collected user data and emotional data into an analytical algorithm to identify the user's preferences, behavioral patterns, and emotional state.

[1091] Step 16:

[1092] The server selects the most suitable advertisements and services based on the analysis results. Based on the profile including emotional data, it selects the advertisements that are predicted to be of most interest to the user.

[1093] Step 17:

[1094] The server transmits the selected advertisement data to the advertisement server, and prepares it to be embedded in the page viewed by the user.

[1095] Step 18:

[1096] The device detects user activity, checks the page being viewed for ad space, and if there is ad space, displays personalized ads.

[1097] Step 19:

[1098] The user views the displayed ad and optionally clicks or checks for details. If the user clicks on the ad, that data is also collected along with emotional data.

[1099] Step 20:

[1100] The server monitors the display status of advertisements in real time and collects and analyzes click and viewing data.

[1101] Step 21:

[1102] The server uses generative AI and ID federation to update the user profile based on collected data and emotional state, and also works across different devices to maintain a consistent user profile.

[1103] Step 22:

[1104] The server will then reflect the updated profile information in subsequent ad selections, ensuring that users receive a consistently optimized ad experience.

[1105] Step 23:

[1106] The device periodically presents new surveys to the user and continues to collect additional personal and emotional data.

[1107] This series of steps allows users to provide information of their own volition and receive the optimal advertising experience, while the system performs highly accurate data and sentiment analysis to provide advertisers with valuable promotions.

[1108] Example 2

[1109] 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."

[1110] Conventional advertising systems typically display ads based on users' preferences and behavioral patterns, but this makes it difficult to provide optimal ads and services that respond to the user's momentary emotional state. Providing a consistent advertising experience across different devices is also a challenge. Furthermore, there is a lack of compensation for the collection of personal data, and a lack of mechanisms to encourage active user participation.

[1111] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1112] In this invention, the server includes means for actively acquiring personal data from users, means for paying for the acquired personal data, means for adding emotional data to the collected personal data and analyzing both to select optimal advertisements and services, means for displaying the selected advertisements and services on the user's terminal, and means for integrating data from different devices and managing it as a single profile. This makes it possible to provide optimal advertisements and services based on the user's momentary emotional state, allowing the user to enjoy a consistent advertising experience even when using different devices. Furthermore, paying users a fee can encourage active data provision.

[1113] "User" means an individual who uses the System and provides Personal Data.

[1114] "Personal Data" refers to information about your personal preferences, behavior, interests, etc. that you provide.

[1115] "Compensation" refers to the reward, such as points or money, that the system pays to users in exchange for providing their personal data.

[1116] "Emotion data" refers to information about the user's emotional state obtained by the emotion engine analyzing the user's facial expressions and tone of voice.

[1117] "Advertisements and Services" refers to promotions, products, and various services that the system selects and presents to users based on their user profile.

[1118] "Terminal" refers to the device (smartphone, PC, etc.) that a user uses to access the system.

[1119] "Server" refers to a central system that receives and analyzes data sent by users, and selects and delivers advertisements and services.

[1120] A "profile" refers to information that indicates a user's preferences and behavioral patterns, created by the server by integrating the user's personal data and emotional data.

[1121] "Generative AI model" refers to the artificial intelligence algorithm used by the server to analyze user data and select the most appropriate advertisements and services.

[1122] "ID federation" refers to a technology that integrates data collected from different devices and platforms into a single user profile.

[1123] The present invention is a system that actively collects personal data from users, analyzes the data to recognize the user's emotions, and provides optimal advertisements and services. This system is implemented using the following hardware and software.

[1124] Hardware and software used

[1125] Hardware: Smartphones, PCs, servers

[1126] Software: applications, database management software (e.g., MySQL), emotion engines (e.g., Affectiva SDK), and analytics algorithms (e.g., the Python library Scikit-learn)

[1127] Acquisition of user information and payment

[1128] A user creates an account on the system and logs in. The terminal sends this login information to the server, which then authenticates the user's login. After successful login, the server presents the user with questionnaire-style questions. When the user answers the questions, the terminal sends the answer data to the server. The server stores the answer data and the emotion data obtained by the emotion engine in a database and assigns points to the user's account.

[1129] Examples:

[1130] When a user logs into the application and answers "action" to the question "What is your favorite movie genre?", the emotion engine analyzes the user's facial expression and tone of voice to obtain data on their enjoyable emotional state. The device sends this response data and emotion data to the server, which stores it in a database and awards 10 points to the user's account.

[1131] Analyze data and provide personalized advertising

[1132] The server analyzes the collected user data and emotional data to identify the user's preferences and behavioral patterns. Based on the analysis results, the server selects the most appropriate advertisements and services and displays them on the user's device.

[1133] Examples:

[1134] The server analyzes the user's likes of action movies and has a feeling of fun, and selects a relevant advertisement. The advertisement is then displayed while the user is browsing a web page.

[1135] Deepening personalization and ID integration

[1136] The system uses generative AI and ID federation to deepen the user's personalized experience. The server integrates data from different devices and platforms and manages it as a single profile, providing a consistent advertising and service experience even when the user uses different devices.

[1137] Examples:

[1138] If a user shows interest in "documentary films" on a specific device and the emotion engine determines that the user's facial expressions are interesting, the server will immediately update the user profile with that information, so that the next time the user logs in from another device, advertisements related to documentary films will be displayed.

[1139] Example prompts for generative AI models

[1140] "Please create an algorithm that integrates and analyzes user behavioral and emotional data to deliver optimal ads in real time so that users can enjoy a consistent advertising experience even when they log in on different devices."

[1141] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1142] Step 1:

[1143] A user launches an application on the system, creates an account, and logs in.

[1144] Input: User's name, email address, and password

[1145] Specific operation: After launching the application, the user clicks the "New Registration" button, enters the required information to create an account, then enters an email address and password in the login form and presses the "Login" button.

[1146] Output: User login information

[1147] Step 2:

[1148] The device sends the login information to the server.

[1149] Input: User login information (email address and password)

[1150] Specific operation: The terminal application sends the login information entered by the user to the server via the HTTPS protocol.

[1151] Output: Login information sent to the server

[1152] Step 3:

[1153] The server authenticates the user's login information.

[1154] Input: Submitted login information

[1155] Specific operation: The server checks the registered information in the database and performs authentication, checking that the email address and password match.

[1156] Output: Authentication success or failure information

[1157] Step 4:

[1158] The server presents a questionnaire-style question to users who have successfully logged in.

[1159] Input: Authentication success information

[1160] Specific operation: The server generates the questionnaire form data and sends it to the terminal.

[1161] Output: Survey form data

[1162] Step 5:

[1163] The user answers the survey questions.

[1164] Input: Survey form question

[1165] Specific operation: The user enters answers to survey-style questions displayed on the device screen. For example, the user answers "action" to the question "What is your favorite movie genre?"

[1166] Output: Survey response data

[1167] Step 6:

[1168] The terminal transmits the response data to the server.

[1169] Input: Survey response data

[1170] Specific operation: When the user presses the survey send button, the device sends the response data to the server via HTTPS protocol.

[1171] Output: Survey response data sent to the server

[1172] Step 7:

[1173] The server stores the response data and emotion data and gives points in return.

[1174] Input: Submitted survey response data

[1175] Specific operation: The server saves the answer data in a database, analyzes the user's facial expressions and tone of voice using an emotion engine to generate emotion data, saves this emotion data in the database, and awards points to the user's account in return.

[1176] Output: Updated user account data (points awarded)

[1177] Step 8:

[1178] The server analyzes the collected data to identify user preferences and behavioral patterns.

[1179] Input: User data and emotion data in the database

[1180] Specific operation: Analyze the data using an analysis algorithm on the server (e.g., Python's Scikit-learn library) and generate a user profile.

[1181] Output: Parsed user profile

[1182] Step 9:

[1183] The server selects the most suitable advertisements and services and displays them on the device.

[1184] Input: Parsed user profile

[1185] How it works: The server selects the most suitable advertisements and services based on the user profile and sends the advertisement data to the device, which then displays it on the screen as an advertisement banner or pop-up.

[1186] Output: Ad displayed on device

[1187] Step 10:

[1188] The server integrates data from different devices and manages it as a single profile.

[1189] Input: User data collected from different devices

[1190] Specific operation: The server uses the user ID as a key to integrate data sent from multiple devices and update the user profile.

[1191] Output: Updated Unified User Profile

[1192] Step 11:

[1193] The server constantly updates the user profile using the generated AI model and ID federation.

[1194] Input: Latest user and sentiment data

[1195] What it does: It uses generative AI models to adapt to changes in a user's behavior and emotions, updating their profile to reflect them in the next ad they see.

[1196] Output: Real-time updated user profile

[1197] (Application example 2)

[1198] 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."

[1199] Current ad serving systems struggle to reflect user preferences and emotional data in real time, resulting in ads that don't match the user's interests or emotional state. They also lack a mechanism for quickly responding to changes in a user's emotions, potentially reducing the effectiveness of ads and the user experience. Furthermore, providing a consistent personalized experience across devices using emotion recognition technology based on a user's visual data is also a challenging task.

[1200] The specification processing by the specification 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 actively acquiring personal data from the user, means for paying for the acquired personal data, means for analyzing the collected personal data and selecting optimal advertisements and services, means for displaying the selected advertisements and services on the user's device, and means for recognizing the user's emotions from visual data acquired by the device and optimizing advertisements in real time based on the emotions. This makes it possible to display advertisements that quickly correspond to the user's emotional state, improving the user experience and maximizing the effectiveness of advertisements.

[1201] "Means of actively obtaining personal data from users" refers to methods of collecting personal information and behavioral data that users voluntarily provide.

[1202] "Means of paying for acquired personal data" refers to a method of awarding points or rewards for the personal information and behavioral data provided by the user.

[1203] "Means of analyzing collected personal data and selecting optimal advertisements and services" refers to a method of analyzing collected data to find advertisements and services that best suit the user's preferences and emotions.

[1204] The "means for displaying the selected advertisement or service on the user's device" refers to a method for displaying the selected advertisement or service on the terminal used by the user.

[1205] "Means for recognizing a user's emotions from visual data acquired by a device and optimizing advertisements in real time based on those emotions" refers to a method for analyzing emotions based on a user's visual data and instantly adjusting advertisement content according to that emotional state.

[1206] This invention relates to a system that actively collects personal data from users, analyzes the data to recognize the user's emotions, and provides optimal advertisements and services. The system of the present invention is implemented by the following means.

[1207] Acquisition of user information and payment

[1208] Users create an account on the system and log in, mainly via smart glasses. The device (smart glasses) sends this login information to the server. The server authenticates the user's login and presents questionnaire-style questions to users who have successfully logged in. When the user answers the questions, the information is saved on the server. At this time, an emotion engine recognizes the user's facial expressions and tone of voice to determine the user's emotional state. The server processes the answer data and emotion data and adds points to the user's account in return. These points can be used later to purchase products or use services.

[1209] For example, when a user answers "action" to the question "What is your favorite movie genre?" through smart glasses, the emotion engine detects the user's facial expression and tone of voice and determines that the user is having fun. The device sends the answer and emotion data to the server, which stores the information in a database and then awards 10 points to the user's account.

[1210] Analyze data and provide personalized advertising

[1211] The server analyzes the collected user data and emotional data to identify the user's preferences and behavioral patterns. Based on the analyzed data, the server selects the most appropriate advertisements and services and displays them on the user's device. Specifically, the analysis algorithm uses data such as "I like action movies and have happy emotions" to select relevant advertisements. When the user views a web page or product through the smart glasses, the advertisements are displayed.

[1212] Deepening personalization and ID integration

[1213] The system uses generative AI and ID federation to deepen the user's personalized experience. The server integrates data from different devices and platforms and manages it as a single profile. This allows for a consistent advertising and service experience even when the user uses the same system on both smart glasses and other devices (such as a smartphone or PC). Furthermore, if the user's behavior, preferences, and emotions change, the system can quickly respond and reflect them in the next ad display.

[1214] For example, if a user shows interest in "documentary films" on a specific device and the emotion engine determines that the user's facial expression is interesting, the server will immediately update the user profile with this information, so that the next time the user logs in on another device, advertisements related to documentary films will be displayed.

[1215] System action

[1216] This system is implemented using the following hardware and software.

[1217] Hardware used: Smart glasses (built-in camera, microphone)

[1218] Software used: OpenCV (face recognition), EmotionRecognition library (emotion recognition), AdSelector (ad selection)

[1219] Program processing procedure

[1220] The camera captures the user's face and obtains real-time video frames.

[1221] The visual data is analyzed using the EmotionRecognition library to extract emotion data (e.g., joy, interest).

[1222] The extracted emotion data is updated in the user profile.

[1223] AdSelector selects the best ads based on the latest user profiles and sentiment data.

[1224] Selected advertisements are overlaid on the smart glasses display.

[1225] Prompt Sentence Examples

[1226] "When a user expresses interest in a new canned drink, create a prompt that generates the most appropriate ad. For example, based on the user's interests and emotional state, you might display an ad that says, 'Buy this canned drink and get 10% off your next purchase.'"

[1227] By combining these methods, it becomes possible to display advertisements that quickly respond to the user's emotional state, improving the user experience and maximizing the effectiveness of advertisements.

[1228] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1229] Step 1:

[1230] The user puts on the smart glasses and logs into the system.

[1231] Input: User authentication information (user ID, password)

[1232] Output: Authentication token

[1233] Specific operation: The user enters their user ID and password into the login screen of the smart glasses, and the device sends this to the server. The server performs authentication processing, and if authentication is successful, generates an authentication token and sends it back to the device.

[1234] Step 2:

[1235] The server presents the user with survey-style questions.

[1236] Input: Authentication token

[1237] Output: Survey questions

[1238] Specific operation: After receiving the authentication token, the device requests survey data from the server, and the server sends a question about the user's preferences to the device. The question is displayed on the smart glasses. For example, "What is your favorite movie genre?"

[1239] Step 3:

[1240] The user fills out a questionnaire and the smart glasses capture the user's facial expressions and tone of voice.

[1241] Input: Survey responses, camera footage, audio data

[1242] Output: Answer data, emotion data

[1243] How it works: When a user responds with "action," the smart glasses' camera and microphone capture their facial expressions and tone of voice, which are then instantly stored on the device.

[1244] Step 4:

[1245] The device transmits the response data and emotion data to the server.

[1246] Input: Answer data, emotion data

[1247] Output: Notification of completion of data transmission to the server

[1248] Specific operation: The smart glasses send the captured data to the server and store it in the database. Once the server has finished storing the data, it will send a notification to the device.

[1249] Step 5:

[1250] The server analyzes the response data and emotion data, updates the user profile, and awards points.

[1251] Input: Answer data, emotion data

[1252] Output: Updated user profile, points awarded notification

[1253] Specific operation: The server analyzes the received data and determines that the user likes "action movies" and is showing signs of enjoyment. Based on this, the server updates the user profile and awards points.

[1254] Step 6:

[1255] The server selects the most suitable advertisement based on the user profile.

[1256] Input: Updated user profile

[1257] Output: Optimized ad information

[1258] How it works: Based on the user profile, the analytics algorithm selects ads related to "action movies." For example, ads for new action movies are selected.

[1259] Step 7:

[1260] The terminal displays the selected advertisement to the user in real time.

[1261] Input: Optimized ad information

[1262] Output: Ad display end notification

[1263] Specific operation: The smart glasses display the advertisement received from the server. The user sees an advertisement for a new action movie on the smart glasses display.

[1264] Step 8:

[1265] Consistent ads are served even when users change devices.

[1266] Input: Login details from different devices

[1267] Output: Consistent ad display

[1268] How it works: When a user logs in on their smartphone, the server uses the unified user profile to display appropriate ads. For example, ads displayed on smart glasses will also be displayed on their smartphone.

[1269] 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.

[1270] 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.

[1271] 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.

[1272] [Fourth embodiment]

[1273] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1274] 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.

[1275] 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).

[1276] 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.

[1277] 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.

[1278] 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).

[1279] 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.

[1280] 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.

[1281] 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.

[1282] 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.

[1283] 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.

[1284] 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.

[1285] 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."

[1286] The present invention relates to a system that actively collects personal data from users, analyzes the data, and provides optimal advertisements and services to the users. This system is implemented in the following manner.

[1287] Acquisition of user information and payment

[1288] First, a user creates an account on the system and logs in. The device sends this login information to the server. The server authenticates the user's login and presents a questionnaire-style question to the user who has successfully logged in. When the user answers the question and submits it, the information is stored on the server.

[1289] The server processes the response data and rewards the user with points, which can be used to purchase products or services later.

[1290] Examples:

[1291] Suppose a user logs into the application and answers "Action" to the question "What is your favorite movie genre?" The device sends the answer to the server, which stores the information in a database and then credits the user's account with 10 points.

[1292] Analyze data and provide personalized advertising

[1293] The server analyzes the collected user data to identify the user's preferences and behavioral patterns. Based on the analyzed data, the server selects the most suitable advertisements and services and displays them on the user's device.

[1294] Specifically, an analytics algorithm uses data like "I like action movies" to select relevant ads that are then displayed while the user is browsing a webpage.

[1295] Deepening personalization and ID integration

[1296] The system uses generative AI and ID federation to enhance the user's personalized experience. The server integrates data from different devices and platforms and manages it as a single profile.

[1297] This allows users to have a consistent advertising and service experience whether they are using the same system on a smartphone or PC, and also allows for quick response to changes in user behavior or preferences, which can be reflected in the next ad display.

[1298] Examples:

[1299] If a user begins to show interest in "documentary films" on a particular device, the server will immediately update that information in the user's profile, ensuring that the next time the user logs in on another device, they will see advertisements related to documentary films.

[1300] System action

[1301] This system is implemented by a program. The process flow is explained below using a specific example.

[1302] First, the user answers a questionnaire, and the data is sent to a server and stored in a database. The server then analyzes the data and selects advertisements that match the user's preferences. The selected advertisements are then displayed on the user's device.

[1303] Furthermore, generative AI is used to constantly update data as users use the system, providing a more accurate and personalized experience.ID linking enables consistent data management across multiple devices, improving the advertising experience.

[1304] This system allows users to provide information of their own volition and receive benefits in return, while the system performs highly accurate data analysis to provide optimal advertisements and services, creating a valuable experience for both users and advertisers.

[1305] The processing flow will be explained below.

[1306] Program processing flow

[1307] Step 1:

[1308] The user launches the application and enters the required information (name, email address, password, etc.) on the account creation page.

[1309] Step 2:

[1310] The terminal transmits the input user information to the server.

[1311] Step 3:

[1312] The server stores the received user information in a database and sends a confirmation message to the terminal confirming that the account has been created.

[1313] Step 4:

[1314] The terminal receives a confirmation message and displays it to the user.

[1315] Step 5:

[1316] The user is directed to the login screen and enters their account information to log in.

[1317] Step 6:

[1318] The terminal sends the login information to the server.

[1319] Step 7:

[1320] The server authenticates the user information and initiates a login session.

[1321] Step 8:

[1322] The server sends a login completion message to the terminal and simultaneously presents a questionnaire-style question.

[1323] Step 9:

[1324] The terminal will display a survey screen along with a login completion message.

[1325] Step 10:

[1326] The user enters answers to the survey questions and presses the send button.

[1327] Step 11:

[1328] The terminal transmits the user's answer to the server.

[1329] Step 12:

[1330] The server receives the user's answers and stores the data in a database.

[1331] Step 13:

[1332] The server will reward the user with points in return for the answer.

[1333] Step 14:

[1334] The terminal displays a message to the user indicating that points have been awarded.

[1335] Step 15:

[1336] The server inputs the collected user data into an analytical algorithm to identify user preferences and behavioral patterns.

[1337] Step 16:

[1338] The server selects the most appropriate advertisements and services based on the analysis results.

[1339] Step 17:

[1340] The server transmits the selected advertisement data to the advertisement server, and prepares it to be embedded in the page viewed by the user.

[1341] Step 18:

[1342] The device detects user activity and displays personalized ads if advertising space is found on the page being viewed.

[1343] Step 19:

[1344] The user views the displayed advertisement and, if desired, clicks or checks for more information.

[1345] Step 20:

[1346] The server monitors the display status of advertisements in real time and collects and analyzes click and viewing data.

[1347] Step 21:

[1348] The server uses generative AI and ID federation to update user profiles based on the collected data.

[1349] Step 22:

[1350] The server will reflect the updated profile information in subsequent advertisement selections.

[1351] Step 23:

[1352] The device periodically presents new surveys to the user and continues to collect more personal data.

[1353] This series of steps allows users to provide information of their own volition and receive the optimal advertising experience, while the server performs highly accurate data analysis and can provide advertisers with valuable promotions.

[1354] Example 1

[1355] 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."

[1356] In conventional systems, when actively collecting personal data from users and analyzing that data to provide optimal advertisements and services, it was difficult to manage data consistently across devices and personalize it, which tended to fragment the user experience. There were also issues with the accuracy of data analysis and timely responses.

[1357] 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.

[1358] In this invention, the server includes means for actively acquiring personal data from users, means for paying for the acquired personal data, means for analyzing the collected personal data and selecting optimal advertisements and services, means for displaying the selected advertisements and services on the user's terminal, means for performing analysis using a generative AI model, and means for integrating data from different devices through ID federation, thereby providing a consistent personalized experience across devices and improving the accuracy of data analysis and the speed of response.

[1359] "User" refers to an individual or corporation that uses the system.

[1360] "Personal data" refers to personal information such as a user's preferences, behavioral patterns, and survey responses.

[1361] "Compensation" refers to the reward given by the system in exchange for the user providing personal data, specifically points or credits.

[1362] "Points" refer to rewards that users can earn by providing personal data, and are units that can be used when purchasing products or using services.

[1363] "Analysis" refers to the process of processing collected personal data to identify user preferences and behavioral patterns.

[1364] "Advertisement" refers to any message or content that informs users about a particular product or service.

[1365] "Service" refers to all products, functions, support, etc. provided to users.

[1366] "Terminal" refers to a hardware device used by a user, such as a computer, smartphone, or tablet.

[1367] "Server" refers to a central computer system that receives, processes, and stores information submitted by users.

[1368] "Generative AI model" refers to an artificial intelligence model used for data analysis and ad selection.

[1369] "ID linking" refers to a technology that integrates user data from different devices and manages it as a single profile.

[1370] A "profile" refers to a comprehensive collection of data such as a user's preferences and behavioral patterns.

[1371] The present invention is a system that actively collects personal data from users, analyzes the data, and provides optimal advertisements and services to the users. Specific embodiments of this system will be described below.

[1372] Acquisition of user information and payment

[1373] First, a user creates an account on the system and logs in. The device sends this login information to the server. The server authenticates the user's login and presents a questionnaire-style question to the successful user. When the user answers the questions and submits them, the information is stored on the server. The server processes the answer data and adds points to the user's account in return. These points can be used later to purchase products or use services.

[1374] A concrete example is when a user logs into an application and answers "action" to the question "What is your favorite movie genre?" The device sends the answer to the server, which stores the information in a database and then credits the user's account with 10 points.

[1375] Analyze data and provide personalized advertising

[1376] The server analyzes the collected user data using a generative AI model to identify the user's preferences and behavioral patterns. Based on the analyzed data, the server selects the most appropriate advertisements and services and displays them on the user's device. Specifically, the analysis algorithm uses the data, such as "I like action movies," to select relevant advertisements. These advertisements are then displayed while the user is browsing a web page.

[1377] Deepening personalization and ID integration

[1378] The system uses generative AI models and ID federation to deepen the user's personalized experience. The server integrates data from different devices and platforms and manages it as a single profile. This allows users to have a consistent advertising and service experience even when using the same system on both smartphones and PCs. Furthermore, if a user's behavior or preferences change, it can quickly respond and reflect that in the next ad display.

[1379] For example, if a user begins to show interest in "documentary films" on a particular device, the server can instantly update that information in the user's profile, so that the next time the user logs in on another device, they will see advertisements related to documentary films.

[1380] Prompt Sentence Examples

[1381] Below are some example prompts that can be used with generative AI models:

[1382] Based on the data "I like action movies," select and display relevant ads.

[1383] Hardware and software used

[1384] The system uses the following hardware and software:

[1385] Hardware: User devices (computers, smartphones, tablets, etc.), servers

[1386] Software: Database management system, generative AI model, ID linking system, survey management software

[1387] This allows users to provide information of their own volition and receive benefits in return, while the system performs highly accurate data analysis and provides optimal advertisements and services, creating a valuable experience for both users and advertisers.

[1388] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1389] Step 1: Create an account and log in

[1390] The user enters account information (username, password, etc.) and clicks the "Login" button. The terminal sends this information to the server. The server receives this information and authenticates the user by referencing a database. It receives the username and password as input, compares them with the database, and outputs the authentication result.

[1391] Step 2: Present the survey

[1392] If the authentication is successful, the server generates a questionnaire and sends it to the terminal. The terminal displays this questionnaire to the user. The server receives the user's login status as input, generates the questionnaire content, and sends it to the terminal to present the questions to the user.

[1393] Step 3: Collect survey responses

[1394] The user answers the questionnaire and clicks the "Submit" button. The device sends the response data to the server. The server receives this data and stores it in a database. The user's response is received as input and the response data is stored by recording it in a database.

[1395] Step 4: Points awarded

[1396] After the survey responses are saved, the server processes the response data and assigns points to the user's account. The terminal displays a notification to the user that points have been assigned. The point assignment process is completed by receiving the survey response data as input, calculating the required points, and assigning them to the user.

[1397] Step 5: Analyze the data

[1398] The server extracts user data collected from the database and analyzes it using a generative AI model, thereby identifying user preferences and behavioral patterns. It receives user data as input, analyzes it using a generative AI model, and outputs user preference data.

[1399] Step 6: Ad selection

[1400] Based on the user's preference data obtained through analysis, the server selects the most suitable advertisements and services. The selected advertisements and services are sent to the device. The server receives the analysis data as input, selects the appropriate advertisements, and sends them to the device, where they are displayed.

[1401] Step 7: Unify profiles through identity federation

[1402] The server aggregates user data from different devices and generates a consistent profile. It takes data from different devices as input and generates a unified profile, providing a consistent user experience.

[1403] At each step, the input data provided by the user is sent to the server, where it is processed and analyzed to provide the optimal advertisements and services to the user.By utilizing generative AI models and ID linking, advanced data analysis and a consistent advertising experience are realized.

[1404] (Application example 1)

[1405] 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."

[1406] Conventional ad delivery systems have had difficulty effectively delivering ads based on users' preferences and behavioral patterns. Furthermore, they lacked a method for fully utilizing personal data voluntarily provided by users to directly benefit them. This has led to a demand for ad delivery that provides value to users while also benefiting advertisers.

[1407] 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.

[1408] In this invention, the server includes means for actively acquiring personal data from users, means for paying for the acquired personal data, means for analyzing the collected personal data and selecting optimal advertisements and services, means for generating advertisements based on the user's preferences, and means for displaying the selected advertisements and services on the user's terminal, thereby making it possible to effectively provide advertisements and services that match the user's preferences and bring direct benefits to the user.

[1409] "Means for actively obtaining personal data from users" are mechanisms for collecting personal information that users voluntarily provide.

[1410] "Means of paying for acquired personal data" refers to a method of rewarding users for the personal information they provide.

[1411] "Means of analyzing collected personal data and selecting optimal advertisements and services" refers to the process of analyzing the acquired data and selecting optimal advertisements and services based on the user's preferences and behavioral patterns.

[1412] "Means for displaying selected advertisements and services on the user's device" refers to a mechanism for displaying advertisements and services selected based on the analysis on the user's device.

[1413] The "means for generating advertisements based on user preferences" is a method for creating relevant advertisements based on genres and product categories that users prefer.

[1414] The present invention relates to a system that actively collects personal data from users, analyzes that data, and provides optimal advertisements and services to users. This system can be realized via a server, a user terminal, and an internet connection.

[1415] System Configuration

[1416] This system mainly consists of the following hardware and software:

[1417] server

[1418] Smartphone

[1419] Database management systems (e.g., SQLite)

[1420] Programming language (e.g. Python)

[1421] Web frameworks (e.g., Flask)

[1422] Data analysis libraries (e.g., Scikit-learn)

[1423] Obtaining user information

[1424] First, users create an account using a smartphone application and log in. After logging in, they are presented with a survey-style question, and the user voluntarily provides information about their preferences and lifestyle. This information is sent from the device to a server and stored in a database.

[1425] Payment of consideration

[1426] The server then awards points for the received personal data, allowing users to receive rewards for the information they provide, and these points can be used to purchase products or use services.

[1427] Data analysis

[1428] The server analyzes the data collected from users to identify their preferences and behavioral patterns. The analysis is performed using the data analysis library Scikit-learn. Based on the results of this analysis, the server selects the most suitable advertisements and services for the user.

[1429] Ad generation and display

[1430] The advertisements selected by the server are generated based on the user's preferences. For example, if the user likes "action movies," advertisements for related action movies are generated. These advertisements are displayed on the user's smartphone, allowing the user to view advertisements that match their preferences.

[1431] Use of generative AI and ID linking

[1432] The server uses generative AI to constantly update user profiles to provide a more accurate personalized experience. By linking IDs, information from different devices is integrated to manage consistent user data. This allows users to see ads based on their preferences even when they log in on different devices.

[1433] Specific examples

[1434] For example, if a user responds that they are interested in action movies, the server analyzes that data and delivers ads for the latest action movies to the user's smartphone.Furthermore, using generative AI, the system can quickly respond if the user's preferences change and display ads that match their new preferences.

[1435] Example prompts to input to a generative AI model:

[1436] "What is the user's favorite movie genre?" If the user answers "action," what kind of ad would be best?

[1437] This allows users to view advertisements based on their preferences, and advertisers can effectively deliver advertisements to target users.

[1438] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1439] Step 1:

[1440] A user logs in to a smartphone app and creates an account. The user's login information (user ID and password) is required as input, and this information is sent from the device to the server. The server receives this information and stores it in a database. This authenticates the user's login.

[1441] Step 2:

[1442] The server presents the user with questionnaire-style questions. As input, the user's profile information is read from a database. The server generates questions and sends them to the user's device. These questions are about the user's preferences and lifestyle.

[1443] Step 3:

[1444] The user answers the survey questions. As input, the user's answer data is saved on the device and then sent to the server. As output, the answer data received by the server is saved in the database. The server confirms that the saving to the database was successful.

[1445] Step 4:

[1446] (Server) awards points to the user. As input, the user's answer data and user ID are required. Based on that data, the server calculates the points and saves them in the database. As output, the points are added to the user's account.

[1447] Step 5:

[1448] The server analyzes the collected personal data. As input, the user's personal data is extracted from the database. The server uses an analysis algorithm (such as Scikit-learn) to identify the user's preferences and behavioral patterns. As output, the analysis results are obtained.

[1449] Step 6:

[1450] The server selects the most suitable advertisements and services based on the analysis results. The analyzed data is used as input. The server uses a generative AI model to generate personalized advertisements for the user. The selected advertisement data is obtained as output.

[1451] Step 7:

[1452] The server sends the selected advertisement to the user's smartphone. The selected advertisement data and the user's device information are required as input. The advertisement data is displayed on the user's device as output.

[1453] Step 8:

[1454] The server uses generative AI to update the user profile. As input, it requires user data from different devices and platforms. The server integrates this information and generates a single user profile. As output, the updated profile data is stored in a database.

[1455] Through these steps, advertisements and services based on the user's preferences are effectively provided to the user.

[1456] 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.

[1457] The present invention relates to a system that actively collects personal data from users, analyzes the data to recognize the user's emotions, and provides optimal advertisements and services. This system is implemented in the following way.

[1458] Acquisition of user information and payment

[1459] A user first creates an account on the system and logs in. The device then sends this login information to the server. The server then authenticates the user's login and presents a questionnaire to the user who has successfully logged in. When the user answers the questions, the information is stored on the server. At this time, the emotion engine recognizes the user's facial expressions and tone of voice to determine the user's emotional state.

[1460] The server processes the response data and emotion data and rewards the user with points, which can be used to purchase products or services later.

[1461] Examples:

[1462] When a user logs into the application and answers "action" to the question "What is your favorite movie genre?", the emotion engine detects the user's facial expression and tone of voice and determines that the user is having fun. The device sends the answer and emotion data to the server, which stores the information in a database and then awards 10 points to the user's account.

[1463] Analyze data and provide personalized advertising

[1464] The server analyzes the collected user data and emotional data to identify the user's preferences and behavioral patterns. Based on the analyzed data, the server selects the most appropriate advertisements and services and displays them on the user's device.

[1465] Specifically, the analysis algorithm uses data such as "I like action movies and have fun emotions" to select relevant ads, which are then displayed while the user is browsing a web page.

[1466] Deepening personalization and ID integration

[1467] The system uses generative AI and ID federation to enhance the user's personalized experience. The server integrates data from different devices and platforms and manages it as a single profile.

[1468] This allows users to have a consistent advertising and service experience whether they are using the same system on a smartphone or a PC, and also allows for quick adaptation to changes in user behavior, preferences, and emotions, which can be reflected in the next ad display.

[1469] Examples:

[1470] If a user begins to show interest in "documentary films" on a specific device, and the emotion engine determines that the user's facial expressions indicate interest, the server will immediately update the user profile, ensuring that advertisements related to documentary films are displayed the next time the user logs in on another device.

[1471] System action

[1472] This system is implemented by a program. The process flow is explained below using a specific example.

[1473] First, the user answers a questionnaire, and the data and emotion data are sent to the server and stored in a database. The server then analyzes the data and selects the most appropriate advertisement based on the user's preferences and emotions. The selected advertisement is then displayed on the user's device.

[1474] Furthermore, generative AI is used to constantly update data and emotional state as users use the system, providing a more accurate and personalized experience.ID linking enables consistent data management across multiple devices, improving the advertising experience.

[1475] This system allows users to provide information of their own volition and receive benefits in return, while the system performs highly accurate data and sentiment analysis, enabling it to provide valuable promotions to advertisers.

[1476] The processing flow will be explained below.

[1477] Program processing flow

[1478] Step 1:

[1479] The user launches the application and enters the required information (name, email address, password, etc.) on the account creation page.

[1480] Step 2:

[1481] The terminal transmits the input user information to the server.

[1482] Step 3:

[1483] The server stores the received user information in a database and sends a confirmation message to the terminal confirming that the account has been created.

[1484] Step 4:

[1485] The terminal receives a confirmation message and displays it to the user.

[1486] Step 5:

[1487] The user is directed to the login screen and enters their account information to log in.

[1488] Step 6:

[1489] The terminal sends the login information to the server.

[1490] Step 7:

[1491] The server authenticates the user information and initiates a login session.

[1492] Step 8:

[1493] The server sends a login completion message to the terminal and simultaneously presents a questionnaire-style question.

[1494] Step 9:

[1495] The terminal will display a survey screen along with a login completion message.

[1496] Step 10:

[1497] The user enters answers to the survey questions and presses the submit button. At the same time, sensor data is collected in order for the emotion engine to recognize the user's facial expressions and tone of voice.

[1498] Step 11:

[1499] The terminal transmits the user's response and emotion data to the server.

[1500] Step 12:

[1501] The server receives the user's answers and emotion data and stores the data in a database.

[1502] Step 13:

[1503] The server analyzes the response data and emotion data and grants points to the user's account as compensation, which may be dynamically adjusted based on the emotion data.

[1504] Step 14:

[1505] The terminal displays a message to the user indicating that points have been awarded.

[1506] Step 15:

[1507] The server inputs the collected user data and emotional data into an analytical algorithm to identify the user's preferences, behavioral patterns, and emotional state.

[1508] Step 16:

[1509] The server selects the most suitable advertisements and services based on the analysis results. Based on the profile including emotional data, it selects the advertisements that are predicted to be of most interest to the user.

[1510] Step 17:

[1511] The server transmits the selected advertisement data to the advertisement server, and prepares it to be embedded in the page viewed by the user.

[1512] Step 18:

[1513] The device detects user activity, checks the page being viewed for ad space, and if there is ad space, displays personalized ads.

[1514] Step 19:

[1515] The user views the displayed ad and optionally clicks or checks for details. If the user clicks on the ad, that data is also collected along with emotional data.

[1516] Step 20:

[1517] The server monitors the display status of advertisements in real time and collects and analyzes click and viewing data.

[1518] Step 21:

[1519] The server uses generative AI and ID federation to update the user profile based on collected data and emotional state, and also works across different devices to maintain a consistent user profile.

[1520] Step 22:

[1521] The server will then reflect the updated profile information in subsequent ad selections, ensuring that users receive a consistently optimized ad experience.

[1522] Step 23:

[1523] The device periodically presents new surveys to the user and continues to collect additional personal and emotional data.

[1524] This series of steps allows users to provide information of their own volition and receive the optimal advertising experience, while the system performs highly accurate data and sentiment analysis to provide advertisers with valuable promotions.

[1525] Example 2

[1526] 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."

[1527] Conventional advertising systems typically display ads based on users' preferences and behavioral patterns, but this makes it difficult to provide optimal ads and services that respond to the user's momentary emotional state. Providing a consistent advertising experience across different devices is also a challenge. Furthermore, there is a lack of compensation for the collection of personal data, and a lack of mechanisms to encourage active user participation.

[1528] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1529] In this invention, the server includes means for actively acquiring personal data from users, means for paying for the acquired personal data, means for adding emotional data to the collected personal data and analyzing both to select optimal advertisements and services, means for displaying the selected advertisements and services on the user's terminal, and means for integrating data from different devices and managing it as a single profile. This makes it possible to provide optimal advertisements and services based on the user's momentary emotional state, allowing the user to enjoy a consistent advertising experience even when using different devices. Furthermore, paying users a fee can encourage active data provision.

[1530] "User" means an individual who uses the System and provides Personal Data.

[1531] "Personal Data" refers to information about your personal preferences, behavior, interests, etc. that you provide.

[1532] "Compensation" refers to the reward, such as points or money, that the system pays to users in exchange for providing their personal data.

[1533] "Emotion data" refers to information about the user's emotional state obtained by the emotion engine analyzing the user's facial expressions and tone of voice.

[1534] "Advertisements and Services" refers to promotions, products, and various services that the system selects and presents to users based on their user profile.

[1535] "Terminal" refers to the device (smartphone, PC, etc.) that a user uses to access the system.

[1536] "Server" refers to a central system that receives and analyzes data sent by users, and selects and delivers advertisements and services.

[1537] A "profile" refers to information that indicates a user's preferences and behavioral patterns, created by the server by integrating the user's personal data and emotional data.

[1538] "Generative AI model" refers to the artificial intelligence algorithm used by the server to analyze user data and select the most appropriate advertisements and services.

[1539] "ID federation" refers to a technology that integrates data collected from different devices and platforms into a single user profile.

[1540] The present invention is a system that actively collects personal data from users, analyzes the data to recognize the user's emotions, and provides optimal advertisements and services. This system is implemented using the following hardware and software.

[1541] Hardware and software used

[1542] Hardware: Smartphones, PCs, servers

[1543] Software: applications, database management software (e.g., MySQL), emotion engines (e.g., Affectiva SDK), and analytics algorithms (e.g., the Python library Scikit-learn)

[1544] Acquisition of user information and payment

[1545] A user creates an account on the system and logs in. The terminal sends this login information to the server, which then authenticates the user's login. After successful login, the server presents the user with questionnaire-style questions. When the user answers the questions, the terminal sends the answer data to the server. The server stores the answer data and the emotion data obtained by the emotion engine in a database and assigns points to the user's account.

[1546] Examples:

[1547] When a user logs into the application and answers "action" to the question "What is your favorite movie genre?", the emotion engine analyzes the user's facial expression and tone of voice to obtain data on their enjoyable emotional state. The device sends this response data and emotion data to the server, which stores it in a database and awards 10 points to the user's account.

[1548] Analyze data and provide personalized advertising

[1549] The server analyzes the collected user data and emotional data to identify the user's preferences and behavioral patterns. Based on the analysis results, the server selects the most appropriate advertisements and services and displays them on the user's device.

[1550] Examples:

[1551] The server analyzes the user's likes of action movies and has a feeling of fun, and selects a relevant advertisement. The advertisement is then displayed while the user is browsing a web page.

[1552] Deepening personalization and ID integration

[1553] The system uses generative AI and ID federation to deepen the user's personalized experience. The server integrates data from different devices and platforms and manages it as a single profile, providing a consistent advertising and service experience even when the user uses different devices.

[1554] Examples:

[1555] If a user shows interest in "documentary films" on a specific device and the emotion engine determines that the user's facial expressions are interesting, the server will immediately update the user profile with that information, so that the next time the user logs in from another device, advertisements related to documentary films will be displayed.

[1556] Example prompts for generative AI models

[1557] "Please create an algorithm that integrates and analyzes user behavioral and emotional data to deliver optimal ads in real time so that users can enjoy a consistent advertising experience even when they log in on different devices."

[1558] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1559] Step 1:

[1560] A user launches an application on the system, creates an account, and logs in.

[1561] Input: User's name, email address, and password

[1562] Specific operation: After launching the application, the user clicks the "New Registration" button, enters the required information to create an account, then enters an email address and password in the login form and presses the "Login" button.

[1563] Output: User login information

[1564] Step 2:

[1565] The device sends the login information to the server.

[1566] Input: User login information (email address and password)

[1567] Specific operation: The terminal application sends the login information entered by the user to the server via the HTTPS protocol.

[1568] Output: Login information sent to the server

[1569] Step 3:

[1570] The server authenticates the user's login information.

[1571] Input: Submitted login information

[1572] Specific operation: The server checks the registered information in the database and performs authentication, checking that the email address and password match.

[1573] Output: Authentication success or failure information

[1574] Step 4:

[1575] The server presents a questionnaire-style question to users who have successfully logged in.

[1576] Input: Authentication success information

[1577] Specific operation: The server generates the questionnaire form data and sends it to the terminal.

[1578] Output: Survey form data

[1579] Step 5:

[1580] The user answers the survey questions.

[1581] Input: Survey form question

[1582] Specific operation: The user enters answers to survey-style questions displayed on the device screen. For example, the user answers "action" to the question "What is your favorite movie genre?"

[1583] Output: Survey response data

[1584] Step 6:

[1585] The terminal transmits the response data to the server.

[1586] Input: Survey response data

[1587] Specific operation: When the user presses the survey send button, the device sends the response data to the server via HTTPS protocol.

[1588] Output: Survey response data sent to the server

[1589] Step 7:

[1590] The server stores the response data and emotion data and gives points in return.

[1591] Input: Submitted survey response data

[1592] Specific operation: The server saves the answer data in a database, analyzes the user's facial expressions and tone of voice using an emotion engine to generate emotion data, saves this emotion data in the database, and awards points to the user's account in return.

[1593] Output: Updated user account data (points awarded)

[1594] Step 8:

[1595] The server analyzes the collected data to identify user preferences and behavioral patterns.

[1596] Input: User data and emotion data in the database

[1597] Specific operation: Analyze the data using an analysis algorithm on the server (e.g., Python's Scikit-learn library) and generate a user profile.

[1598] Output: Parsed user profile

[1599] Step 9:

[1600] The server selects the most suitable advertisements and services and displays them on the device.

[1601] Input: Parsed user profile

[1602] How it works: The server selects the most suitable advertisements and services based on the user profile and sends the advertisement data to the device, which then displays it on the screen as an advertisement banner or pop-up.

[1603] Output: Ad displayed on device

[1604] Step 10:

[1605] The server integrates data from different devices and manages it as a single profile.

[1606] Input: User data collected from different devices

[1607] Specific operation: The server uses the user ID as a key to integrate data sent from multiple devices and update the user profile.

[1608] Output: Updated Unified User Profile

[1609] Step 11:

[1610] The server constantly updates the user profile using the generated AI model and ID federation.

[1611] Input: Latest user and sentiment data

[1612] What it does: It uses generative AI models to adapt to changes in a user's behavior and emotions, updating their profile to reflect them in the next ad they see.

[1613] Output: Real-time updated user profile

[1614] (Application example 2)

[1615] 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."

[1616] Current ad serving systems struggle to reflect user preferences and emotional data in real time, resulting in ads that don't match the user's interests or emotional state. They also lack a mechanism for quickly responding to changes in a user's emotions, potentially reducing the effectiveness of ads and the user experience. Furthermore, providing a consistent personalized experience across devices using emotion recognition technology based on a user's visual data is also a challenging task.

[1617] The specification processing by the specification 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 actively acquiring personal data from the user, means for paying for the acquired personal data, means for analyzing the collected personal data and selecting optimal advertisements and services, means for displaying the selected advertisements and services on the user's device, and means for recognizing the user's emotions from visual data acquired by the device and optimizing advertisements in real time based on the emotions. This makes it possible to display advertisements that quickly correspond to the user's emotional state, improving the user experience and maximizing the effectiveness of advertisements.

[1618] "Means of actively obtaining personal data from users" refers to methods of collecting personal information and behavioral data that users voluntarily provide.

[1619] "Means of paying for acquired personal data" refers to a method of awarding points or rewards for the personal information and behavioral data provided by the user.

[1620] "Means of analyzing collected personal data and selecting optimal advertisements and services" refers to a method of analyzing collected data to find advertisements and services that best suit the user's preferences and emotions.

[1621] The "means for displaying the selected advertisement or service on the user's device" refers to a method for displaying the selected advertisement or service on the terminal used by the user.

[1622] "Means for recognizing a user's emotions from visual data acquired by a device and optimizing advertisements in real time based on those emotions" refers to a method for analyzing emotions based on a user's visual data and instantly adjusting advertisement content according to that emotional state.

[1623] This invention relates to a system that actively collects personal data from users, analyzes the data to recognize the user's emotions, and provides optimal advertisements and services. The system of the present invention is implemented by the following means.

[1624] Acquisition of user information and payment

[1625] Users create an account on the system and log in, mainly via smart glasses. The device (smart glasses) sends this login information to the server. The server authenticates the user's login and presents questionnaire-style questions to users who have successfully logged in. When the user answers the questions, the information is saved on the server. At this time, an emotion engine recognizes the user's facial expressions and tone of voice to determine the user's emotional state. The server processes the answer data and emotion data and adds points to the user's account in return. These points can be used later to purchase products or use services.

[1626] For example, when a user answers "action" to the question "What is your favorite movie genre?" through smart glasses, the emotion engine detects the user's facial expression and tone of voice and determines that the user is having fun. The device sends the answer and emotion data to the server, which stores the information in a database and then awards 10 points to the user's account.

[1627] Analyze data and provide personalized advertising

[1628] The server analyzes the collected user data and emotional data to identify the user's preferences and behavioral patterns. Based on the analyzed data, the server selects the most appropriate advertisements and services and displays them on the user's device. Specifically, the analysis algorithm uses data such as "I like action movies and have happy emotions" to select relevant advertisements. When the user views a web page or product through the smart glasses, the advertisements are displayed.

[1629] Deepening personalization and ID integration

[1630] The system uses generative AI and ID federation to deepen the user's personalized experience. The server integrates data from different devices and platforms and manages it as a single profile. This allows for a consistent advertising and service experience even when the user uses the same system on both smart glasses and other devices (such as a smartphone or PC). Furthermore, if the user's behavior, preferences, and emotions change, the system can quickly respond and reflect them in the next ad display.

[1631] For example, if a user shows interest in "documentary films" on a specific device and the emotion engine determines that the user's facial expression is interesting, the server will immediately update the user profile with this information, so that the next time the user logs in on another device, advertisements related to documentary films will be displayed.

[1632] System action

[1633] This system is implemented using the following hardware and software.

[1634] Hardware used: Smart glasses (built-in camera, microphone)

[1635] Software used: OpenCV (face recognition), EmotionRecognition library (emotion recognition), AdSelector (ad selection)

[1636] Program processing procedure

[1637] The camera captures the user's face and obtains real-time video frames.

[1638] The visual data is analyzed using the EmotionRecognition library to extract emotion data (e.g., joy, interest).

[1639] The extracted emotion data is updated in the user profile.

[1640] AdSelector selects the best ads based on the latest user profiles and sentiment data.

[1641] Selected advertisements are overlaid on the smart glasses display.

[1642] Prompt Sentence Examples

[1643] "When a user expresses interest in a new canned drink, create a prompt that generates the most appropriate ad. For example, based on the user's interests and emotional state, you might display an ad that says, 'Buy this canned drink and get 10% off your next purchase.'"

[1644] By combining these methods, it becomes possible to display advertisements that quickly respond to the user's emotional state, improving the user experience and maximizing the effectiveness of advertisements.

[1645] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1646] Step 1:

[1647] The user puts on the smart glasses and logs into the system.

[1648] Input: User authentication information (user ID, password)

[1649] Output: Authentication token

[1650] Specific operation: The user enters their user ID and password into the login screen of the smart glasses, and the device sends this to the server. The server performs authentication processing, and if authentication is successful, generates an authentication token and sends it back to the device.

[1651] Step 2:

[1652] The server presents the user with survey-style questions.

[1653] Input: Authentication token

[1654] Output: Survey questions

[1655] Specific operation: After receiving the authentication token, the device requests survey data from the server, and the server sends a question about the user's preferences to the device. The question is displayed on the smart glasses. For example, "What is your favorite movie genre?"

[1656] Step 3:

[1657] The user fills out a questionnaire and the smart glasses capture the user's facial expressions and tone of voice.

[1658] Input: Survey responses, camera footage, audio data

[1659] Output: Answer data, emotion data

[1660] How it works: When a user responds with "action," the smart glasses' camera and microphone capture their facial expressions and tone of voice, which are then instantly stored on the device.

[1661] Step 4:

[1662] The device transmits the response data and emotion data to the server.

[1663] Input: Answer data, emotion data

[1664] Output: Notification of completion of data transmission to the server

[1665] Specific operation: The smart glasses send the captured data to the server and store it in the database. Once the server has finished storing the data, it will send a notification to the device.

[1666] Step 5:

[1667] The server analyzes the response data and emotion data, updates the user profile, and awards points.

[1668] Input: Answer data, emotion data

[1669] Output: Updated user profile, points awarded notification

[1670] Specific operation: The server analyzes the received data and determines that the user likes "action movies" and is showing signs of enjoyment. Based on this, the server updates the user profile and awards points.

[1671] Step 6:

[1672] The server selects the most suitable advertisement based on the user profile.

[1673] Input: Updated user profile

[1674] Output: Optimized ad information

[1675] How it works: Based on the user profile, the analytics algorithm selects ads related to "action movies." For example, ads for new action movies are selected.

[1676] Step 7:

[1677] The terminal displays the selected advertisement to the user in real time.

[1678] Input: Optimized ad information

[1679] Output: Ad display end notification

[1680] Specific operation: The smart glasses display the advertisement received from the server. The user sees an advertisement for a new action movie on the smart glasses display.

[1681] Step 8:

[1682] Consistent ads are served even when users change devices.

[1683] Input: Login details from different devices

[1684] Output: Consistent ad display

[1685] How it works: When a user logs in on their smartphone, the server uses the unified user profile to display appropriate ads. For example, ads displayed on smart glasses will also be displayed on their smartphone.

[1686] 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.

[1687] 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.

[1688] 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.

[1689] 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.

[1690] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1691] 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.

[1692] 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).

[1693] 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.

[1694] 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."

[1695] 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.

[1696] 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).

[1697] 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.

[1698] 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.

[1699] 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.

[1700] 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.

[1701] 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.

[1702] 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.

[1703] 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.

[1704] 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.

[1705] 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.

[1706] 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.

[1707] The following is further disclosed regarding the above embodiment.

[1708] (Claim 1)

[1709] A means for actively acquiring personal data from a user;

[1710] A means of paying for the personal data obtained;

[1711] A means of analyzing collected personal data and selecting optimal advertisements and services,

[1712] a means for displaying the selected advertisements and services on the user's device;

[1713] A system including:

[1714] (Claim 2)

[1715] 2. The system according to claim 1, further comprising means for periodically having the user provide information in the form of a questionnaire.

[1716] (Claim 3)

[1717] 10. The system of claim 1, further comprising means for updating a user profile based on collected personal data using generation AI and ID federation.

[1718] "Example 1"

[1719] (Claim 1)

[1720] A means for actively acquiring personal data from a user;

[1721] A means of paying for the personal data obtained;

[1722] A means of analyzing collected personal data and selecting optimal advertisements and services,

[1723] a means for displaying the selected advertisements and services on the user's device;

[1724] A means for performing analytical analysis using a generative AI model;

[1725] A means to integrate data from different devices through ID linking,

[1726] A system including:

[1727] (Claim 2)

[1728] 2. The system according to claim 1, further comprising means for periodically having the user provide information in the form of a questionnaire.

[1729] (Claim 3)

[1730] 10. The system of claim 1, further comprising means for updating a user profile based on the collected personal data.

[1731] "Application Example 1"

[1732] (Claim 1)

[1733] A means for actively acquiring personal data from a user;

[1734] A means of paying for the personal data obtained;

[1735] A means of analyzing collected personal data and selecting optimal advertisements and services,

[1736] a means for displaying the selected advertisements and services on the user's device;

[1737] means for generating advertisements based on user preferences;

[1738] A system including:

[1739] (Claim 2)

[1740] 2. The system according to claim 1, further comprising means for periodically having the user provide information in the form of a questionnaire.

[1741] (Claim 3)

[1742] 10. The system of claim 1, further comprising means for updating a user profile based on collected personal data using generation AI and ID federation.

[1743] "Example 2: Combining Emotion Engines"

[1744] (Claim 1)

[1745] A means for actively acquiring personal data from a user;

[1746] A means of paying for the personal data obtained;

[1747] A method to add emotional data to collected personal data and analyze both to select optimal advertisements and services.

[1748] a means for displaying the selected advertisements and services on the user's device;

[1749] A means to integrate data from different devices and manage it as a single profile,

[1750] A system including:

[1751] (Claim 2)

[1752] 2. The system according to claim 1, further comprising means for periodically having the user provide information in the form of a questionnaire.

[1753] (Claim 3)

[1754] 10. The system of claim 1, further comprising means for updating a user profile based on the collected personal data and emotion data using a generative AI model and ID federation.

[1755] "Application example 2 when combining emotion engines"

[1756] (Claim 1)

[1757] A means for actively acquiring personal data from a user;

[1758] A means of paying for the personal data obtained;

[1759] A means of analyzing collected personal data and selecting optimal advertisements and services,

[1760] a means for displaying the selected advertisements and services on the user's device;

[1761] A means for recognizing a user's emotions from visual data acquired by the device and optimizing advertisements in real time based on the emotions;

[1762] A system including:

[1763] (Claim 2)

[1764] 2. The system according to claim 1, further comprising means for periodically having the user provide information in the form of a questionnaire.

[1765] (Claim 3)

[1766] 10. The system of claim 1, further comprising means for updating a user profile based on collected personal data using generation AI and ID federation. [Explanation of symbols]

[1767] 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 actively acquiring personal data from a user; A means of paying for the personal data obtained; A means of analyzing collected personal data and selecting optimal advertisements and services, a means for displaying the selected advertisements and services on the user's device; A system including:

2. 2. The system according to claim 1, further comprising means for periodically having the user provide information in the form of a questionnaire.

3. The system of claim 1 , further comprising means for updating a user profile based on collected personal data using generative AI and ID federation.

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