system

Abstract

Provide a system. A means for identifying user interests using generative AI; a means of delivering online advertisements; a means for accepting applications for participation; and A means of notifying students of upcoming classes; A means of providing information to classroom participants; a means of gathering feedback from classroom participants; a means of tracking the use of the services described in the classroom; A system including:

Description

[Technical Field]

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

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

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

[0004] In recent years, interest in new savings systems has been growing, but their complex mechanisms mean that many users lack understanding and face barriers to starting to use them. Conventional methods lack the means to efficiently and effectively attract users' interest and provide accurate information. This poses a challenge, preventing users from fully utilizing the benefits of new savings systems. Furthermore, methods for promoting the use of related services and expanding the customer base are also inefficient. [Means for solving the problem]

[0005] This invention provides a system that uses generative AI to identify user interests and announces the holding of classes on new savings systems through online advertisements. It also includes means for accepting applications to participate, notifying participants of class events, and providing detailed information to participants during the classes. In this system, generative AI analyzes website access logs and social media posts to identify user interests and deliver targeted online advertisements. It also collects feedback from class participants and tracks their use of services explained in the classes, thereby deepening user understanding, promoting the use of related services, and expanding the customer base.

[0006] "Generative AI" is artificial intelligence that uses machine learning and data analysis techniques to identify user interests and behavioral patterns.

[0007] A "user" is an individual or group of people who view an online advertisement and are interested in information about new savings schemes.

[0008] "Online advertising" means advertising delivered over the Internet, including banners and text links displayed on certain web pages or within applications.

[0009] "Application for participation" means the act of a user conveying their intention to participate in a class through the provided form.

[0010] The "classroom" refers to seminars and workshops on the new savings system, where users are provided with detailed information and education.

[0011] "Notification" refers to sending messages or emails to users to inform them of the date, time and location of classes.

[0012] "Feedback" refers to evaluations and comments regarding the content of a class or proposed services collected from users who have participated in the class.

[0013] "Tracking" is the act of continuously monitoring the usage of a service that a user has actually started using and recording it in a database. [Brief explanation of the drawings]

[0014] [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

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] The system of the present invention uses generative AI to identify users interested in a new savings program and automates the process of announcing the class via online advertising. The system is configured as follows:

[0036] User identification using generative AI

[0037] server:

[0038] User data is collected from various data sources (website access logs, social media posts, etc.) and stored in a database.

[0039] Generative AI is used to analyze the collected data and create a list of users who are interested in the new savings scheme.

[0040] Delivering online advertisements

[0041] server:

[0042] Based on the user list identified by the AI ​​generation, online advertising campaign settings are made, including the ad content, target audience, and period.

[0043] Based on the floor settings, banner ads will be delivered to platforms such as Yahoo and PayPay.

[0044] Device:

[0045] Allows internet users to see targeted advertising in their browsers and applications.

[0046] When a user clicks on the ad, they are taken to a page detailing the class on the new savings program.

[0047] Application acceptance and notification

[0048] server:

[0049] The class details page contains an application form, and the application data entered by the user is received and stored in a database.

[0050] After confirming your application, we will notify you of the date, time and location of the class via email or message.

[0051] Device:

[0052] The user enters the required information on the details page and applies to participate.

[0053] Receive notification emails and messages and prepare to join the class.

[0054] Classes held

[0055] server:

[0056] It manages presentation materials and demonstration data used in the classroom and provides them to the instructor's device.

[0057] Provide the instructor with a list of participants and assist with classroom management.

[0058] Device (instructor's smartphone):

[0059] The instructor will use a smartphone to display a presentation and provide a detailed explanation of the new savings system.

[0060] Demonstrations will be held on smartphones, fixed services, and point management using PayPay.

[0061] user:

[0062] Attend classes and listen to the instructor's explanations to deepen your understanding of the new savings system.

[0063] The proposed services will be reviewed.

[0064] Feedback collection and tracking

[0065] server:

[0066] After the class, participants will be sent a feedback form, and the collected data will be analyzed to identify areas for improvement.

[0067] Track and record usage of services discussed in the classroom in a database.

[0068] To give a specific example, while User A is searching for information on the internet, he or she is included in a target list by the generation AI. Based on this list, a banner ad for a new savings system is displayed on the web page that User A is viewing. When User A clicks on the ad, he or she is taken to the class details page where he or she can apply to participate. When the application to participate is accepted, a notification email is sent to User A's device. On the day of the class, the instructor displays materials and gives an explanation. After the class, User A fills out a feedback form, and subsequent service usage is tracked.

[0069] In this way, systems that utilize generative AI can efficiently identify users and provide information through classrooms, thereby promoting the use of related services and expanding the customer base.

[0070] The processing flow will be explained below.

[0071] Step 1:

[0072] server:

[0073] User data is collected from various data sources (website access logs, social media posts, etc.) and stored in a database, including user browsing history, click history, and post content.

[0074] The collected data is input into a generative AI to analyze user interests and behavioral patterns.

[0075] Step 2:

[0076] server:

[0077] Based on the analysis results of the Generator AI, a list of users who are interested in the new savings scheme is created. The Generator AI uses a specific algorithm to determine the level of interest and similarity of behavioral patterns.

[0078] Save the listed user information in the database.

[0079] Step 3:

[0080] server:

[0081] Set up a targeted advertising campaign: define what ads to advertise, who to advertise to, and for how long.

[0082] Online advertisements will begin to be delivered based on the specific user list obtained from the generated AI.

[0083] Step 4:

[0084] Device:

[0085] While users are browsing the internet, they are shown banner ads, which are dynamically timed and placed based on a targeting list.

[0086] When a user clicks on the banner ad, they are taken to a page detailing the new savings program.

[0087] Step 5:

[0088] User:

[0089] Access the class details page and enter the required information (name, contact information, desired date and time of participation, etc.) in the provided participation application form and submit it.

[0090] Once submitted, your application will be complete.

[0091] Step 6:

[0092] server:

[0093] Receives the registration data and stores it in a database. Generates an email or message to notify the user that their registration is complete.

[0094] It reviews each application and sends users notifications with details of the class date, time and location.

[0095] Step 7:

[0096] Device:

[0097] Classroom presentation materials and demo data are downloaded to the instructor's smartphone, and preparations are complete.

[0098] Users who receive the notification email or message can prepare to join the class.

[0099] Step 8:

[0100] server:

[0101] We will provide the instructor with a list of participants on the day of the class to help ensure the class runs smoothly.

[0102] Step 9:

[0103] Device (instructor's smartphone):

[0104] The instructor uses a smartphone to display a presentation about the new savings system and give an explanation.

[0105] We will conduct demonstrations on smartphones, fixed services, and point management with PayPay, and explain the benefits of using them.

[0106] Step 10:

[0107] User:

[0108] Participants will deepen their knowledge of the new savings system through classroom explanations and demonstrations, as well as learn about smartphones, fixed-line services, and how to use PayPay points.

[0109] Step 11:

[0110] server:

[0111] After the class, a feedback form is sent to participants via email or message to collect their ratings and comments.

[0112] The collected feedback data will be analyzed to improve classroom content and services provided.

[0113] Step 12:

[0114] server:

[0115] The usage status of services (smartphone, fixed line, point management, etc.) that participants have actually started using will be tracked and stored in a database. The usage data for each service will be visualized and used in corporate strategy planning.

[0116] In this way, by performing specific actions at each processing step, it is possible to utilize generative AI to achieve efficient user identification and classroom management, thereby promoting the use of related services and expanding the customer base.

[0117] Example 1

[0118] 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."

[0119] Existing online advertising systems lack the means to identify user interests and deliver targeted advertisements effectively. They also lack the means to smoothly guide target users through the process of joining a class and track service usage. As a result, it is difficult to promote the use of related services and expand customer base.

[0120] 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.

[0121] In this invention, the server includes means for identifying user interests using generation AI, means for delivering online advertisements, means for accepting participation applications, means for notifying class schedules, means for providing information to class participants, means for collecting feedback from class participants, means for tracking usage of services explained in classes, means for collecting user data and storing it in a database, and means for setting up advertising campaigns on an advertising platform. This effectively identifies user interests and delivers targeted advertisements, promoting the use of related services and expanding customer base. It also allows users to smoothly participate in the class process and efficiently track feedback and usage.

[0122] "Generative AI" is an artificial intelligence technology used to analyze collected data to identify user interests and concerns.

[0123] "Online advertising" refers to advertising delivered via the Internet and displayed in the browsers and applications used by users.

[0124] "Application" is the process by which a user expresses their intention to participate in a particular event or class by filling out and submitting the required information in the provided form.

[0125] "Class Notification" means an email or message sent to a user to inform them of the date, time, and location of a class.

[0126] "Information provision" refers to the act of providing detailed information about new savings programs to class participants through presentations and demonstrations.

[0127] "Feedback collection" is a procedure for collecting evaluations and opinions on the content of the class from class participants.

[0128] "Tracking" refers to the act of continuously tracking the usage of the services explained in the classroom and recording it in a database.

[0129] "User Data" refers to information about a specific user, such as website access logs or social media posts.

[0130] A "database" is an information system for storing and efficiently managing collected user data and analysis results.

[0131] An "advertising campaign" is an advertising distribution plan established based on a specific purpose, and includes advertising content, distribution target, period, etc.

[0132] An "advertising platform" refers to an internet infrastructure that provides systems and services for delivering online advertisements.

[0133] The system of the present invention uses generative AI to identify users interested in a new savings program and automates the process of announcing the class via online advertising. Specific embodiments are described below.

[0134] User identification using generative AI

[0135] server:

[0136] The server collects user data from data sources such as website access logs and social media posts and stores it in a database such as PostgreSQL.

[0137] A generative AI model (e.g., GPT-3 (registered trademark) or BERT) is used to analyze the collected data and identify users who are interested in the new savings scheme. This process uses the prompt "Analyze website access logs and social media posting data to identify users who are interested in the new savings scheme."

[0138] Generate a list of identified users and store it in Amazon S3.

[0139] For example, the server collects information such as when User A visits a page called "savings tips" or posts about "savings" on social media. Based on this information, the generation AI creates a list of User A as an interested user and stores it in Amazon S3.

[0140] Delivering online advertisements

[0141] server:

[0142] The server uses the identified user list to configure the advertising campaign, including specifying the ad content, target audience, and duration.

[0143] This setting is sent to advertising platforms (e.g., Yahoo or other internet services).

[0144] Device:

[0145] Internet users can view targeted advertisements in their browsers and applications.

[0146] When users click on the ad, they are taken to a page with more details about the new savings scheme.

[0147] As a concrete example, the server identifies User A, imports the information into Yahoo's advertising campaign management system, and sets the content and distribution period of a banner ad for a "new savings plan." When User A is browsing a Yahoo page, the ad is displayed. When User A clicks on the ad, the page transitions to a detailed page.

[0148] Application acceptance and notification

[0149] server:

[0150] Place a registration form on the class details page. Receive the data entered by the user and store it in a database.

[0151] After confirming your application, we will send you an email or message informing you of the date, time and location of the class.

[0152] Device:

[0153] Users enter the necessary information on the details page and apply to participate.

[0154] Receive notification emails and messages and prepare to join the class.

[0155] For example, when User A enters his / her name and email address into the form on the details page and submits it, the server stores this data in the database. When the application is accepted, a notification email is sent to User A.

[0156] Classes held

[0157] server:

[0158] It manages presentation materials and demonstration data used in the classroom and provides them to the instructor's device.

[0159] Manage participant lists and provide them to instructors to assist with classroom management.

[0160] Device (instructor's smartphone):

[0161] The lecturer will use a smartphone to display a presentation and explain the new savings system.

[0162] A demonstration will be conducted to show specific operation methods.

[0163] As a concrete example, the lecturer will project presentation materials onto a smartphone and explain to the participants. There will also be a demonstration of the specific operation of savings points via smartphones and other fixed services.

[0164] Feedback collection and tracking

[0165] server:

[0166] After the class, participants will be sent a feedback form and the collected data will be analyzed to identify areas for improvement.

[0167] Track and record the use of services discussed in the classroom in a database.

[0168] For example, after the class ends, the server sends a feedback form to User A asking, "How was the class?" and receives and analyzes the responses. It also continuously tracks User A's usage of the savings plan.

[0169] This allows the system, which utilizes generative AI, to effectively identify users and provide them with appropriate information through targeted advertising, thereby promoting the use of related services and expanding the customer base.

[0170] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0171] Step 1: Data collection

[0172] server:

[0173] Input: Website access logs, social media posting data

[0174] The server collects user data from these data sources, using web scraping and APIs to obtain log information and posted data.

[0175] After data acquisition, the collected data is stored in a PostgreSQL database.

[0176] Output: User data stored in the database

[0177] Step 2: Data analysis

[0178] server:

[0179] Input: User data stored in the database

[0180] The server uses a generative AI model (e.g., GPT-3 or BERT) to analyze the collected data based on the prompt.

[0181] Prompt: "Analyze website traffic logs and social media posting data to identify users interested in a new savings program."

[0182] Based on the analysis results, the server generates a list of users interested in the new savings system and stores it in Amazon S3.

[0183] Output: User list stored in Amazon S3

[0184] Step 3: Campaign Settings

[0185] server:

[0186] Input: A user list stored in Amazon S3

[0187] The server uses the user list to set up online advertising campaigns, for example determining the content, targeting, and duration of banner ads.

[0188] Send your settings to advertising platforms (Yahoo, other internet services).

[0189] Output: Campaign data set in the advertising platform

[0190] Step 4: Ad serving

[0191] server:

[0192] Input: Campaign data set in the advertising platform

[0193] The server uses an advertising platform to deliver online advertisements to targeted users.

[0194] Output: Ad banner displayed in the user's browser or app

[0195] Device:

[0196] Input: An ad banner displayed in a user's browser or app.

[0197] When users click on the ad, they are redirected to a page with more details about the new savings scheme.

[0198] Output: User navigates to the classroom details page

[0199] Step 5: Accepting your application

[0200] server:

[0201] Input: Application data entered by the user on the details page

[0202] The server receives the participation application data from the form placed on the classroom details page and stores it in a database.

[0203] Output: Application data stored in a database

[0204] Device:

[0205] Input: Information the user enters on the detail page (such as name, email address, etc.)

[0206] The user enters the required information into the application form and submits it.

[0207] Output: Data sent to the server

[0208] Step 6: Sending notifications

[0209] server:

[0210] Input: Participation application data stored in the database

[0211] The server will confirm the registration and send a notification email or message to the user with the date, time and location of the class.

[0212] Output: Notification emails and messages sent to users

[0213] Device:

[0214] Input: Notification emails and messages sent from the server

[0215] Users will receive notification emails and messages and prepare to join the class.

[0216] Output: Classroom participation preparation information

[0217] Step 7: Prepare for the class

[0218] server:

[0219] Input: Managed presentation and demo data

[0220] The server provides prepared materials and data to the instructor's device (such as a smartphone), and also manages the participant list and provides it to the instructor.

[0221] Output: Materials provided to the instructor and a list of participants

[0222] Step 8: Hold a class

[0223] Device (instructor's smartphone):

[0224] Input: Presentation materials and participant list provided by the server

[0225] The instructor will use a smartphone to display a presentation and explain the new savings system, and will provide a demonstration with concrete examples using the smartphone and other services.

[0226] Output: Explanations and demo content for classroom participants

[0227] user:

[0228] Input: Explanation and demo content provided by the instructor

[0229] Users can attend classes and listen to explanations to deepen their understanding of the new savings system.

[0230] Output: User understanding and interest

[0231] Step 9: Gather feedback

[0232] server:

[0233] Input: Feedback form submitted after class

[0234] The server sends feedback forms to participants and analyzes the collected data.

[0235] Output: Analyzed feedback data

[0236] Step 10: Tracking

[0237] server:

[0238] Input: Usage data of services explained in the classroom

[0239] The server continuously tracks the usage of the services explained in the classroom and records it in a database.

[0240] Output: Updated database usage data

[0241] By taking specific actions at each step, the system can efficiently identify users' interests and promote information and service use through targeted advertising and classes.

[0242] (Application example 1)

[0243] 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."

[0244] The challenge is to efficiently identify users who are interested in specific products or services in physical stores, promptly notify them of campaigns or events, and automate the entire process from registration to the actual event management and feedback collection.Flaws in such systems can impair the timeliness and accuracy of information provided to users, and effective feedback collection and utilization is necessary to improve event participant satisfaction and promote service usage.

[0245] 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.

[0246] In this invention, the server includes means for identifying user interests using a generation AI, means for delivering online advertisements, means for accepting participation applications, means for notifying event participants, means for providing information to event participants, means for collecting feedback from event participants, means for tracking the usage of services explained at the event, means for managing applications for events held at physical stores, and means for notifying smartphones of event information held at physical stores. This makes it possible to accurately grasp user interests, provide campaign and event information at appropriate times, and consistently manage the process from participation applications to feedback collection.

[0247] "Generative AI" is a type of artificial intelligence that analyzes data and automatically generates insights based on specific requirements and conditions.

[0248] "Means for identifying user interests" refers to technology that analyzes collected data to extract user interests in specific products or services.

[0249] "Means for delivering online advertising" refers to a mechanism for delivering advertising content to specific users via the Internet.

[0250] "Means for accepting participation applications" refers to a function for accepting and managing applications from users to participate in events and campaigns.

[0251] "Means for notifying users of upcoming events" is a function that notifies users of upcoming events based on the set date, time, and content.

[0252] "Means for providing information to event participants" refers to a system for providing participants with the information they need before, during, and after the event.

[0253] "Means for collecting feedback from event participants" refers to techniques for collecting opinions and impressions from participants after the event and analyzing them as data.

[0254] "Means for tracking usage of services explained at the event" refers to a system for monitoring and recording subsequent usage of products or services introduced at the event.

[0255] The "means for managing applications for events held in physical stores" refers to a technology that comprehensively manages users' applications to participate in events held in physical stores.

[0256] "Means of notifying smartphones of event information held at physical stores" is a system that notifies users' smartphones of information about events scheduled at physical stores.

[0257] The system of the present invention uses a generative AI to identify users who are interested in a specific product and provide those users with campaign and event notifications for physical stores. Specifically, it includes the following processing steps.

[0258] User Specific

[0259] The server collects website access logs and social media posts and stores them in a database. The software used here includes a data collection API and a generative AI model (e.g., OpenAI® GPT-3). The generative AI analyzes the collected data and creates a list of users who are interested in a particular product or service.

[0260] Campaign Notifications

[0261] The server sets up an online advertising campaign based on the user list identified by the generation AI. This setting includes the ad content, target audience, and period. Campaign information is then sent to the user's smartphone. The hardware used includes the server and the user's smartphone, and the software includes an email sending API (e.g., SendGrid) and a notification API.

[0262] Event participation application

[0263] The device (user's smartphone) displays details of the notified campaign or event and allows the user to apply directly. The server receives the application data and stores it in a database. The software used includes a web server and a database management system.

[0264] Event Notification

[0265] When the event date approaches, the server will send a reminder message to help users remember the event. The software includes a notification API so that reminder notifications are sent to users' smartphones.

[0266] Feedback collection

[0267] After the event, the server sends a feedback form to users, analyzes the collected data, and identifies areas for improvement. This will help improve the quality of the next event. The software used includes a feedback form API and a data analysis tool.

[0268] Specific user examples

[0269] For example, when User A is searching for savings-related products, he or she is included in a target list by the generation AI. Based on this list, a campaign notification for a new savings scheme is sent to User A's smartphone. User A clicks on the notification to check the details of the event and apply to participate. Before the event, the server sends User A a reminder message, and after the event ends, a feedback form is sent. Through this series of processes, User A can efficiently obtain information and use new services through the event.

[0270] Prompt Sentence Examples

[0271] "We use generative AI to automate the process of identifying users who are interested in a particular product and sending them promotional notifications."

[0272] "We want to develop an application that allows users to register for seminars held in physical stores and collect feedback on campaigns that interest them."

[0273] Through this process, this application example builds a system that identifies users interested in a new savings scheme and encourages them to participate in events at physical stores.

[0274] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0275] Step 1:

[0276] The server uses a data collection API to obtain website access logs and social media posts and stores them in a database. The input is log data and post data from each data source, which is processed and stored in the database. The output is raw data stored in the database. Specifically, it executes API requests, collects JSON-formatted data, analyzes it, and inserts it into the database.

[0277] Step 2:

[0278] The server analyzes the collected data using a generative AI model (e.g., OpenAI GPT-3) to create a list of users who are interested in a particular product or service. The input is raw data stored in a database, which is analyzed by the generative AI model. The output is a list of users who are determined to be interested. Specifically, the server creates prompts for the generative AI model and performs an analysis process to identify user interests based on the prompts.

[0279] Step 3:

[0280] The server sets up an online advertising campaign based on the user list identified by the generation AI. The input is the identified user list and campaign content, and based on this, it generates ad delivery settings. The output is setting information for the online ad delivery platform. Specifically, it sets parameters such as ad content, delivery target, and period, and sends the data to the delivery platform via API.

[0281] Step 4:

[0282] The device (user's smartphone) receives the campaign notification sent from the server and displays it to the user. The input is the campaign notification data, which is displayed through the smartphone's notification function. The output is the notification display to the user. Specifically, the notification message is constructed using the notification API and displayed as a pop-up on the smartphone screen.

[0283] Step 5:

[0284] The user checks the details of the notified campaign or event on their smartphone and applies to participate. The input is the notification message and a link to the details page, which the user clicks to access the application form. The output is the data entered into the application form. Specifically, the user clicks the link, enters the required information into the web form, and submits it.

[0285] Step 6:

[0286] The server receives event participation application data from users and stores it in a database. The input is the application data sent from the web form, which is saved in the database. The output is the saved application data. Specifically, it receives the form data and inserts it into the database.

[0287] Step 7:

[0288] As the event date approaches, the server sends a reminder message. The input is the event date and time and a list of users, and the server generates a reminder message based on this. The output is a reminder message sent to the user's smartphone. Specifically, the server uses a notification API to send a message based on the reminder settings.

[0289] Step 8:

[0290] After the event ends, the server sends a feedback form to users and analyzes the collected data. The input is the event participant list and the feedback form, and feedback is collected based on this. The output is the feedback data and its analysis results. Specifically, the form link is sent using the feedback form API, and the collected data is evaluated using an analysis tool.

[0291] 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.

[0292] This invention provides a method for specifically implementing a system that uses generative AI and an emotion engine to identify users interested in a new savings program and announces the opening of classes through online advertising. Each element and its specific operation are described below.

[0293] User identification with generative AI and emotion engine

[0294] server:

[0295] User data is collected from various data sources (website access logs, social media posts, user text input, etc.) and stored in a database.

[0296] The generative AI analyzes the collected data, analyzes user interests and behavioral patterns, and based on the analysis results, creates a list of users who are interested in the new savings system.

[0297] The emotion engine uses a webcam and microphone to analyze emotions from the user's facial expressions and voice, and also recognizes emotions from the user's text input.

[0298] Delivery and dynamic adjustment of online advertisements

[0299] server:

[0300] Set up a targeted advertising campaign: define what ads to advertise, who to advertise to, and for how long.

[0301] Based on the analysis results of the generative AI and emotion engine, the content of online advertisements is dynamically adjusted and banner advertisements are delivered.

[0302] Device:

[0303] As users navigate the internet, they are shown tailored banner ads, whose timing and location change dynamically based on targeting lists and sentiment analysis.

[0304] When a user clicks on the banner ad, they are taken to a page detailing the new savings program.

[0305] Application acceptance and notification

[0306] server:

[0307] The class details page contains an application form, and the application data entered by the user is received and stored in a database.

[0308] After confirming your application, we will notify you of the date, time and location of the class via email or message.

[0309] Device:

[0310] The user enters the required information on the details page and applies to participate.

[0311] Receive notification emails and messages and prepare to join the class.

[0312] Classroom Management and Emotional Response

[0313] server:

[0314] It manages presentation materials and demonstration data used in the classroom and provides them to the instructor's device.

[0315] Provide the instructor with a list of participants and assist with classroom management.

[0316] Device (instructor's smartphone):

[0317] The lecturer uses a smartphone to display and explain a presentation about a new savings system, and the speaker's smartphone dynamically adjusts the content and tone of the presentation based on the user's emotional data obtained from the emotion engine.

[0318] Demonstrations will be held on smartphones, fixed-line services, and point management, and the benefits of using them will be explained.

[0319] user:

[0320] Participate in the class, listen to the instructor's explanations and demonstrations, and deepen your understanding of the new savings system. You will also learn about smartphones, fixed-line services, and point management.

[0321] Feedback collection and tracking

[0322] server:

[0323] After the class, a feedback form is sent to participants via email or message to collect their ratings and comments.

[0324] The collected feedback data will be analyzed to improve classroom content and services provided.

[0325] The usage status of services (smartphone, fixed line, point management, etc.) that participants have actually started using will be tracked and stored in a database. The usage data for each service will be visualized and used in corporate strategy planning.

[0326] To give a specific example, while User A is searching for information on the Internet, he or she is included in a target list by the generative AI and emotion engine. Based on this list, a dynamically adjusted banner ad is displayed on the web page that User A is viewing. When User A clicks on the ad, he or she is taken to the class details page where he or she can apply to participate. After the application is accepted, a notification email is sent to User A's device. On the day of the class, the instructor will give an explanation, adjusting the presentation based on the user's emotion data. After the class ends, User A fills in a feedback form, and their subsequent service usage is tracked.

[0327] In this way, the system, which utilizes generative AI and an emotion engine, can effectively identify users and provide them with information through classrooms, thereby promoting the use of related services and expanding the customer base.

[0328] The processing flow will be explained below.

[0329] Step 1:

[0330] server:

[0331] User data is collected from various data sources (website access logs, social media posts, user text input, etc.) and stored in a database. The collected data includes user browsing history, click history, and post content.

[0332] The generative AI analyzes the collected data to analyze user interests and behavioral patterns, and based on the analysis results, creates a list of users who are interested in the new savings system.

[0333] Step 2:

[0334] server:

[0335] The emotion engine is initialized and collects the user's facial and voice data via the webcam and microphone. The emotion engine analyzes this data in real time to determine the user's current emotional state.

[0336] Analyzes emotional data from user text input, extracting emotions and tones from text messages and other inputs.

[0337] Step 3:

[0338] server:

[0339] Set up targeted advertising campaigns, defining the content, audience, and duration of ads, using user lists identified by generative AI and sentiment analysis results from the sentiment engine.

[0340] Based on data from the emotion engine, the content of online ads is dynamically adjusted to best suit the user's emotional state before being delivered.

[0341] Step 4:

[0342] Device:

[0343] As users navigate the internet and browse websites and applications, they are shown tailored banner ads, whose timing and location change dynamically based on targeting lists and sentiment analysis.

[0344] When a user clicks on the banner ad, they are taken to a page detailing the new savings program.

[0345] Step 5:

[0346] User:

[0347] Access the class details page and enter the required information (name, contact information, desired date and time of participation, etc.) in the provided participation application form and submit it.

[0348] Once you have completed your registration, you will automatically receive a confirmation message.

[0349] Step 6:

[0350] server:

[0351] Receives application data and stores it in a database. Generates and sends notification emails and messages to users so that they can confirm their application details.

[0352] Send notifications to users with details about class times, dates, and locations.

[0353] Step 7:

[0354] Device:

[0355] Download and prepare classroom presentation materials and demo data onto the instructor's smartphone.

[0356] Users who receive the notification email or message can prepare to join the class.

[0357] Step 8:

[0358] server:

[0359] We will provide the instructor with a list of participants on the day of the class to help ensure the class runs smoothly. This list will also be used to support smooth reception at the entrance to the venue.

[0360] Step 9:

[0361] Device (instructor's smartphone):

[0362] The lecturer uses a smartphone to display and explain in detail a presentation about a new savings scheme, and the speaker's smartphone dynamically adjusts the content and tone of the presentation based on the user's emotional data obtained from the emotion engine.

[0363] Step 10:

[0364] Device (instructor's smartphone):

[0365] Demonstrations will be conducted on smartphones, fixed-line services, and point management, and the benefits of using them will be explained in detail. An emotion engine will be used to adjust the progress of the demonstration based on the emotional state of the participants.

[0366] Step 11:

[0367] User:

[0368] Participate in the class, understand the instructor's explanations and demonstrations, and learn about the structure and benefits of the new savings system. You will also learn in detail about the proposed smartphone and fixed-line services, and point management.

[0369] Step 12:

[0370] server:

[0371] After the class, participants are sent a feedback form via email or message to collect their ratings and comments. The feedback data is then stored in a database for later use in improving the service.

[0372] The usage of the services explained in the class will be tracked in real time and recorded in a database. Usage trends for each service will be analyzed and used to plan future strategies.

[0373] To give a specific example, while User A is searching for information on the Internet, he or she is included in a target list by the generative AI and emotion engine. Based on this list, a dynamically adjusted banner ad is displayed on the web page that User A is viewing. When User A clicks on the ad, he or she is taken to the class details page where he or she can apply to participate. After the application is accepted, a notification email is sent to User A's device. On the day of the class, the instructor will give an explanation, adjusting the presentation based on the user's emotion data. After the class ends, User A fills in a feedback form, and their subsequent service usage is tracked.

[0374] In this way, the system, which utilizes generative AI and an emotion engine, can effectively identify users and provide them with information through classrooms, thereby promoting the use of related services and expanding the customer base.

[0375] Example 2

[0376] 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."

[0377] Conventional online advertising systems only deliver ads based on users' interests, but are unable to deliver ads that take into account users' emotions. Furthermore, there was a lack of a mechanism for adequately collecting and analyzing feedback on how users who received ads behaved after attending classes. Furthermore, it was difficult to track the usage of services explained in classes, which meant that the data could not be fully utilized to improve services or develop marketing strategies.

[0378] 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.

[0379] In this invention, the server includes a means for identifying user interests using generative AI, a means for analyzing user emotions using an emotion engine, and a means for dynamically adjusting and delivering online advertisements using the analysis results. This enables the delivery of highly targeted advertisements based on the user's interests and emotions. The server also includes a means for accepting participation applications, a means for notifying class participants, a means for providing information to class participants, a means for collecting feedback from class participants, and a means for tracking the usage of services explained in the classes. This facilitates the collection and analysis of feedback and the tracking of service usage, which can be used to improve services and develop strategies.

[0380] "Generative AI" is a system that uses artificial intelligence technology to identify users' interests and concerns.

[0381] An "emotion engine" is a system for analyzing emotions from data such as a user's facial expressions, voice, and text input.

[0382] "Online advertising" refers to advertising banners and links distributed over the Internet, which are a means of providing information and promotions to users.

[0383] "Dynamic adjustment" refers to changing the content and timing of advertising in real time based on the analysis results of the generative AI and emotion engine.

[0384] "Registration" is the process by which a user indicates their intention to attend a class or event and provides the necessary information.

[0385] "Notifications" are a way to communicate important information to users, such as the date, time, and location of class events.

[0386] "Feedback" refers to information collected from users, such as ratings and comments, that is used to improve our services and events.

[0387] "Tracking" is the process of monitoring and collecting data on the use of the services described in the classroom.

[0388] This invention is a system that utilizes generative AI and an emotion engine to analyze users' interests and emotions, deliver appropriate online advertisements, provide class information, collect feedback, and track service usage. The system is composed of three main entities: a server, a device, and the user.

[0389] User Specific

[0390] The server collects user data from various data sources (e.g., website access logs, social media posts, user text input) and stores it in a database. The server uses generative AI to analyze the collected data and identify the user's interests. This analysis uses natural language processing (NLP) technology. The emotion engine analyzes emotions from the user's facial expressions and voice data obtained from the webcam and microphone, as well as text input.

[0391] As a specific example, a user's search history for keywords related to "new savings systems" is collected, and based on the collected data, the generation AI determines that the user is interested in a new financial product.

[0392] Delivery and dynamic adjustment of online advertisements

[0393] The server sets up a targeted advertising campaign and defines the ad content, distribution target, and distribution period. Based on the analysis results of the generative AI and emotion engine, the ad content is dynamically adjusted and delivered to users as banner ads on the Internet. The adjusted banner ad is displayed on the user's device (PC or smartphone). When the user clicks on the banner ad, they are taken to a class details page where they can apply to participate.

[0394] As a concrete example, when user A is browsing a news site, a dynamically adjusted banner ad appears, and when he clicks on the ad, he is taken to a detailed page about a class on savings programs.

[0395] Application acceptance and notification

[0396] The server places a participation application form on the class details page and stores the participation application data entered by the user in a database. The server then notifies the user of the class date, time, and location via email or message. The user receives the notification on their device and prepares to participate in the class.

[0397] As a specific example, a user accesses a class details page via a banner ad, applies to participate from there, and receives a notification email.

[0398] Classroom Management and Emotional Response

[0399] The server manages presentation materials and demo data and provides them to the instructor's device (e.g., a smartphone). In the classroom, the instructor uses their smartphone to give a presentation, dynamically adjusting the content and tone based on the user's emotional data obtained from the emotion engine. Participants attend the class and learn about the new savings system.

[0400] As a concrete example, the instructor can use a smartphone in the classroom to check emotional data in real time and adjust the content of the explanation as he or she goes along.

[0401] Feedback collection and tracking

[0402] After the class ends, the server sends a feedback form to the participants and collects their ratings and comments. This data is analyzed to improve the class content and services. The server also tracks the usage of services that participants have actually started using and stores the data in a database. This data can be used to develop corporate strategies.

[0403] For example, after the class ends, users are sent a feedback form, and the results are reflected in improving the content of the next class.

[0404] Prompt Sentence Examples

[0405] "Describe a system that detects user interests and delivers targeted advertising based on the data analyzed by an emotion engine."

[0406] This invention enables highly targeted advertising based on user interests and emotions, helping to promote new savings programs more effectively through classrooms, while collecting feedback and tracking usage allows for continuous improvement of the service.

[0407] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0408] Step 1:

[0409] Data collection

[0410] server:

[0411] The server collects user data from data sources such as website access logs, social media posts, and user text input, and stores it in a database. Various data sources are used as input, and the output is formatted user data. Specifically, the server calls the data source API, retrieves JSON-formatted data, and stores it in the database.

[0412] Step 2:

[0413] Interest identification using generative AI

[0414] server:

[0415] The server inputs the collected user data into the generation AI to identify the user's interests. In this case, the generation AI uses natural language processing (NLP) technology. The input is user data, and the output is the identified user interest data. Specifically, the generation AI model feeds user data and classifies the user's interests by comparing it with the educational database.

[0416] Step 3:

[0417] Emotion analysis

[0418] server:

[0419] The server uses an emotion engine to analyze emotions from the user's facial expressions, voice, and text input obtained from the webcam and microphone. The input is real-time data, and the output is analyzed emotion data. Specifically, the webcam footage is analyzed frame by frame, the voice data is subjected to phonetic pattern analysis, and emotion keywords are extracted from the text.

[0420] Step 4:

[0421] Ad delivery settings and adjustments

[0422] server:

[0423] The server sets up targeted advertising campaigns and dynamically adjusts ad content based on the analysis results of the generative AI and emotion engine. The input is interest data and emotion data, and the output is adjusted ad data. Specifically, it inserts messages and images into ad templates that match the user's interests and emotions.

[0424] Step 5:

[0425] Advertisement display

[0426] Device:

[0427] The tailored banner ad is displayed on the user's device (PC or smartphone). The input is the tailored ad data, and the output is the displayed ad. Specifically, when the user browses a web page, the dynamically tailored banner ad is rendered in the ad display area.

[0428] Step 6:

[0429] Participation application acceptance

[0430] server:

[0431] The server places an application form on the class details page, receives the application data entered by the user, and stores it in a database. The input is the user's application data, and the output is the stored application data. Specifically, the server receives input from the user in an HTML form and saves it in a database on the backend.

[0432] Step 7:

[0433] Send notifications

[0434] server:

[0435] After the server confirms the participation application, it notifies the user of the class date, time, and location via email or message. The input is the participation confirmation data, and the output is the notification email or message sent. Specifically, it uses an email sending API to send individual notification emails to participants.

[0436] Step 8:

[0437] Presentation materials provided

[0438] server:

[0439] The server manages the presentation materials and demo data used in the classroom and provides them to the instructor's terminal. The input is the presentation materials and demo data, and the output is the materials provided to the instructor's terminal. Specifically, the server makes the materials available for download from a cloud storage service and sends a link to the instructor's terminal.

[0440] Step 9:

[0441] Classroom Management and Emotional Response

[0442] Device (instructor's smartphone):

[0443] The lecturer uses a device to give a presentation and dynamically adjusts the content and tone based on data from the emotion engine. The input is emotion data, and the output is an adjusted presentation. Specifically, the emotion data is received in real time and the content and tone of the slides are changed accordingly.

[0444] Step 10:

[0445] Feedback collection

[0446] server:

[0447] After the class ends, the server sends a feedback form to the participants and collects their ratings and comments. The input is the feedback data, and the output is the collected feedback. Specifically, a form submission API is used to send a link to the participants, and their responses are saved in a database.

[0448] Step 11:

[0449] Usage Tracking

[0450] server:

[0451] The server tracks the status of services actually used by class participants and stores the data in a database. The input is usage data, and the output is the stored tracking data. Specifically, usage logs are collected periodically and stored in a database for analysis.

[0452] Through these steps, the system can effectively deliver advertisements according to users' interests and emotions, manage classrooms, collect feedback, and track usage.

[0453] (Application example 2)

[0454] 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."

[0455] Today's consumers are bombarded with a vast amount of information, making it difficult to find information and products that are relevant to them. Furthermore, to maximize the effectiveness of online advertisements and campaigns, targeting based on individual users' emotions and interests is necessary. Furthermore, virtual stores require mechanisms that allow users to enjoy individually customized shopping experiences. Given this background, there is a need for systems that can provide advertisements and information based on users' interests and emotions, and measure and improve their effectiveness.

[0456] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0457] In this invention, the server includes means for identifying user interests using generative AI, means for delivering online advertisements, means for accepting participation applications, means for notifying class schedules, means for providing information to class participants, means for collecting feedback from class participants, means for tracking the usage of services explained in the class, means for using an emotion engine that analyzes the user's emotional state based on their facial expressions and voice, and means for providing a customized shopping experience through smart glasses in a virtual store. This makes it possible to provide advertisements and information optimized for each individual user and measure and improve their effectiveness in real time.

[0458] "Generative AI" is a technology that uses artificial intelligence to automatically analyze and identify users' interests and concerns.

[0459] "Online advertising" refers to advertising content delivered to users via the Internet.

[0460] "Registration" is the process by which a user indicates their intention to participate in a particular event or class and completes the necessary procedures.

[0461] "Classroom Notification" is a means of communicating information to users about details such as the date and location of an event or class.

[0462] "Feedback" refers to reactions and comments such as evaluations and opinions obtained from users.

[0463] "Tracking" means the continuous tracking and recording of the usage of a particular service or product.

[0464] The "emotion engine" is a technology that analyzes the user's facial expressions and voice to recognize and evaluate their emotional state.

[0465] A "virtual store" is not an actual physical store, but a virtual store that operates online or in the digital space.

[0466] "Smart glasses" are advanced eyeglass-type devices equipped with a display, camera, sensors, etc., and capable of providing information to users.

[0467] "Shopping experience" is a general term for the experiences and services that consumers receive in the process of selecting and purchasing a product.

[0468] This invention is a system that utilizes generative AI and an emotion engine to provide users with optimal advertisements and information, thereby improving their shopping experience in virtual stores. A specific embodiment of the present invention is described below.

[0469] System Configuration

[0470] This system mainly consists of three elements: a server, a terminal (smart glasses, smartphone, etc.), and a user. The role and operation of each element are explained below.

[0471] server

[0472] The server consists of multiple components, including a generative AI model, an emotion engine, and a database. Specifically, it uses the following software and hardware:

[0473] Hardware and Software

[0474] Hardware: High-performance server

[0475] Software: Python, TENSORFLOW (registered trademark), OpenCV

[0476] Data collection

[0477] The server collects user data from each data source (website access logs, social media posts, user text input, etc.) and stores it in a database.

[0478] Analysis by generative AI

[0479] The generative AI model analyzes the collected data and analyzes user interests and behavioral patterns. This generates a list of users who are interested in the new savings scheme. An example prompt is shown below:

[0480] "We are collecting text information to identify users who are interested in investing and saving. Analyze their interests and create a list of users who are most likely to be interested in a new savings scheme."

[0481] Analysis by emotion engine

[0482] The emotion engine uses a webcam and microphone to analyze emotions from the user's facial expressions and voice. The emotion engine also recognizes emotions from the user's text input.

[0483] Ad delivery and dynamic adjustment

[0484] The server sets up targeted advertising campaigns, defining the ad content, target audience, and distribution period. Based on the analysis results of the generative AI and emotion engine, the content of online ads is dynamically adjusted and banner ads are distributed.

[0485] Terminal

[0486] Smart Glasses

[0487] Users use smart glasses to shop in virtual stores. The smart glasses have the following features:

[0488] Advertisement display: Displaying customized banner ads at the right time based on the user's emotional state.

[0489] Providing detailed information: Clicking on an ad displays detailed information about the product or event and takes you to a page to register for participation.

[0490] Smartphone

[0491] Smartphones will be used for classroom presentations and registration.

[0492] Presentation display: The instructor uses a smartphone to display a presentation about a new savings scheme.

[0493] Dynamic adjustment based on emotional data: The instructor's smartphone dynamically adjusts the content and tone of the presentation based on the user's emotional data obtained from the emotion engine.

[0494] user

[0495] The user uses this system to perform the following process:

[0496] Viewing ads and signing up: When users are browsing the internet, they will be shown dynamically adjusted banner ads that, when clicked, will take them to a class details page where they can sign up.

[0497] Providing feedback: After the class, participants fill out a feedback form and their subsequent use of the service is tracked.

[0498] In this way, the present invention can provide users with the most appropriate advertisements and information, allowing them to customize their shopping experience in a virtual store.

[0499] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0500] Step 1:

[0501] The server collects user data from data sources such as website access logs, social media posts, and user text input, and stores it in a database.

[0502] Input: Website access logs, social media posts, user text input

[0503] Data processing: Collected data is centrally managed and stored in a database

[0504] Output: A cleaned up user database

[0505] Step 2:

[0506] The server uses a generative AI model to analyze the collected data and analyze users' interests and behavioral patterns.

[0507] Input: User Database

[0508] Data Computation: Using generative AI models to calculate interest scores and identify target users

[0509] Output: List of highly interested users

[0510] Specific operation: The generative AI performs analysis based on the prompt: "We are collecting text information to identify users who are interested in investing and saving. Analyze user interests and create a list of users who are likely to be most interested in the new savings system."

[0511] Step 3:

[0512] The server uses an emotion engine to analyze the user's emotional state based on facial expressions, voice, and text input obtained from the webcam and microphone.

[0513] Input: Webcam video, audio data, text input

[0514] Data Computation: Emotion Analysis Using an Emotion Engine

[0515] Output: User's emotional state data

[0516] Specific operation: Obtain data in real time from a webcam and microphone to estimate emotional state.

[0517] Step 4:

[0518] Based on the analysis results of the generative AI and emotion engine, the server sets up advertising campaigns, generates and adjusts targeted ads, and delivers online ads.

[0519] Input: User list, emotional state data

[0520] Data processing: Ad content is customized for each user and displayed at the appropriate time

[0521] Output: Tailored banner ad

[0522] Specific operation: The advertising distribution system displays the most appropriate advertisement for the page viewed by the target user.

[0523] Step 5:

[0524] While using the Internet, users view tailored banner ads and click on them to be taken to a details page where they can apply to participate.

[0525] Input: Tailored banner ads

[0526] Output: Display of classroom details page, participation application data

[0527] Specific actions: The user clicks on the ad and fills in the required information on the application form.

[0528] Step 6:

[0529] The server places a participation application form on the classroom details page, receives the participation application data entered by the user, and stores it in a database.

[0530] Input: Participation application data

[0531] Data processing: Save the application data in a database and check for duplications and errors.

[0532] Output: Organized participant list

[0533] Step 7:

[0534] The server confirms the participation application and notifies the user of the date, time and location of the class via email or message.

[0535] Input: Participant list

[0536] Output: Notification email, message

[0537] Specific action: Execute a process to automatically send notifications to participants.

[0538] Step 8:

[0539] The device (the instructor's smartphone) displays presentation materials during the class and dynamically adjusts the content and tone based on data from the emotion engine.

[0540] Input: Presentation materials, participants' emotional state data

[0541] Data processing: Adjusting presentation content and changing tone

[0542] Output: Well-tuned presentation

[0543] Specific behavior: Check emotional state in real time and optimize content.

[0544] Step 9:

[0545] Users will attend classes, follow lectures and demonstrations from instructors, and gain a deeper understanding of the new savings system.

[0546] Input: Instructor presentation

[0547] Output: Improved user understanding

[0548] Specific actions: Listen to the instructor's explanation and watch the demonstration to learn.

[0549] Step 10:

[0550] After the class, the server sends a feedback form to participants and collects their evaluations and comments.

[0551] Input: Feedback Form

[0552] Data processing: Analysis of collected feedback data

[0553] Output: Feedback data analysis results

[0554] Specific actions: Automatically send feedback forms to participants and analyze the collected data.

[0555] This makes it possible for the present invention to provide users with optimal advertisements and information, improving their shopping experience in virtual stores.

[0556] 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.

[0557] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0558] 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.

[0559] [Second embodiment]

[0560] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0561] 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.

[0562] 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).

[0563] 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.

[0564] 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.

[0565] 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).

[0566] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0567] 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.

[0568] 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.

[0569] 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.

[0570] In the smart glasses 214, 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.

[0571] 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."

[0572] The system of the present invention uses generative AI to identify users interested in a new savings program and automates the process of announcing the class via online advertising. The system is configured as follows:

[0573] User identification using generative AI

[0574] server:

[0575] User data is collected from various data sources (website access logs, social media posts, etc.) and stored in a database.

[0576] Generative AI is used to analyze the collected data and create a list of users who are interested in the new savings scheme.

[0577] Delivering online advertisements

[0578] server:

[0579] Based on the user list identified by the AI ​​generation, online advertising campaign settings are made, including the ad content, target audience, and period.

[0580] Based on the floor settings, banner ads will be delivered to platforms such as Yahoo and PayPay.

[0581] Device:

[0582] Allows internet users to see targeted advertising in their browsers and applications.

[0583] When a user clicks on the ad, they are taken to a page detailing the class on the new savings program.

[0584] Application acceptance and notification

[0585] server:

[0586] The class details page contains an application form, and the application data entered by the user is received and stored in a database.

[0587] After confirming your application, we will notify you of the date, time and location of the class via email or message.

[0588] Device:

[0589] The user enters the required information on the details page and applies to participate.

[0590] Receive notification emails and messages and prepare to join the class.

[0591] Classes held

[0592] server:

[0593] It manages presentation materials and demonstration data used in the classroom and provides them to the instructor's device.

[0594] Provide the instructor with a list of participants and assist with classroom management.

[0595] Device (instructor's smartphone):

[0596] The instructor will use a smartphone to display a presentation and provide a detailed explanation of the new savings system.

[0597] Demonstrations will be held on smartphones, fixed services, and point management using PayPay.

[0598] user:

[0599] Attend classes and listen to the instructor's explanations to deepen your understanding of the new savings system.

[0600] The proposed services will be reviewed.

[0601] Feedback collection and tracking

[0602] server:

[0603] After the class, participants will be sent a feedback form, and the collected data will be analyzed to identify areas for improvement.

[0604] Track and record usage of services discussed in the classroom in a database.

[0605] To give a specific example, while User A is searching for information on the internet, he or she is included in a target list by the generation AI. Based on this list, a banner ad for a new savings system is displayed on the web page that User A is viewing. When User A clicks on the ad, he or she is taken to the class details page where he or she can apply to participate. When the application to participate is accepted, a notification email is sent to User A's device. On the day of the class, the instructor displays materials and gives an explanation. After the class, User A fills out a feedback form, and subsequent service usage is tracked.

[0606] In this way, systems that utilize generative AI can efficiently identify users and provide information through classrooms, thereby promoting the use of related services and expanding the customer base.

[0607] The processing flow will be explained below.

[0608] Step 1:

[0609] server:

[0610] User data is collected from various data sources (website access logs, social media posts, etc.) and stored in a database, including user browsing history, click history, and post content.

[0611] The collected data is input into a generative AI to analyze user interests and behavioral patterns.

[0612] Step 2:

[0613] server:

[0614] Based on the analysis results of the Generator AI, a list of users who are interested in the new savings scheme is created. The Generator AI uses a specific algorithm to determine the level of interest and similarity of behavioral patterns.

[0615] Save the listed user information in the database.

[0616] Step 3:

[0617] server:

[0618] Set up a targeted advertising campaign: define what ads to advertise, who to advertise to, and for how long.

[0619] Online advertisements will begin to be delivered based on the specific user list obtained from the generated AI.

[0620] Step 4:

[0621] Device:

[0622] While users are browsing the internet, they are shown banner ads, which are dynamically timed and placed based on a targeting list.

[0623] When a user clicks on the banner ad, they are taken to a page detailing the new savings program.

[0624] Step 5:

[0625] User:

[0626] Access the class details page and enter the required information (name, contact information, desired date and time of participation, etc.) in the provided participation application form and submit it.

[0627] Once submitted, your application will be complete.

[0628] Step 6:

[0629] server:

[0630] Receives the registration data and stores it in a database. Generates an email or message to notify the user that their registration is complete.

[0631] It reviews each application and sends users notifications with details of the class date, time and location.

[0632] Step 7:

[0633] Device:

[0634] Classroom presentation materials and demo data are downloaded to the instructor's smartphone, and preparations are complete.

[0635] Users who receive the notification email or message can prepare to join the class.

[0636] Step 8:

[0637] server:

[0638] We will provide the instructor with a list of participants on the day of the class to help ensure the class runs smoothly.

[0639] Step 9:

[0640] Device (instructor's smartphone):

[0641] The instructor uses a smartphone to display a presentation about the new savings system and give an explanation.

[0642] We will conduct demonstrations on smartphones, fixed services, and point management with PayPay, and explain the benefits of using them.

[0643] Step 10:

[0644] User:

[0645] Participants will deepen their knowledge of the new savings system through classroom explanations and demonstrations, as well as learn about smartphones, fixed-line services, and how to use PayPay points.

[0646] Step 11:

[0647] server:

[0648] After the class, a feedback form is sent to participants via email or message to collect their ratings and comments.

[0649] The collected feedback data will be analyzed to improve classroom content and services provided.

[0650] Step 12:

[0651] server:

[0652] The usage status of services (smartphone, fixed line, point management, etc.) that participants have actually started using will be tracked and stored in a database. The usage data for each service will be visualized and used in corporate strategy planning.

[0653] In this way, by performing specific actions at each processing step, it is possible to utilize generative AI to achieve efficient user identification and classroom management, thereby promoting the use of related services and expanding the customer base.

[0654] Example 1

[0655] 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."

[0656] Existing online advertising systems lack the means to identify user interests and deliver targeted advertisements effectively. They also lack the means to smoothly guide target users through the process of joining a class and track service usage. As a result, it is difficult to promote the use of related services and expand customer base.

[0657] 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.

[0658] In this invention, the server includes means for identifying user interests using generation AI, means for delivering online advertisements, means for accepting participation applications, means for notifying class schedules, means for providing information to class participants, means for collecting feedback from class participants, means for tracking usage of services explained in classes, means for collecting user data and storing it in a database, and means for setting up advertising campaigns on an advertising platform. This effectively identifies user interests and delivers targeted advertisements, promoting the use of related services and expanding customer base. It also allows users to smoothly participate in the class process and efficiently track feedback and usage.

[0659] "Generative AI" is an artificial intelligence technology used to analyze collected data to identify user interests and concerns.

[0660] "Online advertising" refers to advertising delivered via the Internet and displayed in the browsers and applications used by users.

[0661] "Application" is the process by which a user expresses their intention to participate in a particular event or class by filling out and submitting the required information in the provided form.

[0662] "Class Notification" means an email or message sent to a user to inform them of the date, time, and location of a class.

[0663] "Information provision" refers to the act of providing detailed information about new savings programs to class participants through presentations and demonstrations.

[0664] "Feedback collection" is a procedure for collecting evaluations and opinions on the content of the class from class participants.

[0665] "Tracking" refers to the act of continuously tracking the usage of the services explained in the classroom and recording it in a database.

[0666] "User Data" refers to information about a specific user, such as website access logs or social media posts.

[0667] A "database" is an information system for storing and efficiently managing collected user data and analysis results.

[0668] An "advertising campaign" is an advertising distribution plan established based on a specific purpose, and includes advertising content, distribution target, period, etc.

[0669] An "advertising platform" refers to an internet infrastructure that provides systems and services for delivering online advertisements.

[0670] The system of the present invention uses generative AI to identify users interested in a new savings program and automates the process of announcing the class via online advertising. Specific embodiments are described below.

[0671] User identification using generative AI

[0672] server:

[0673] The server collects user data from data sources such as website access logs and social media posts and stores it in a database such as PostgreSQL.

[0674] Analyze the collected data using a generative AI model (e.g., GPT-3 or BERT) to identify users who are interested in the new savings scheme. This process uses the prompt "Analyze website access logs and social media posting data to identify users who are interested in the new savings scheme."

[0675] Generate a list of identified users and store it in Amazon S3.

[0676] For example, the server collects information such as when User A visits a page called "savings tips" or posts about "savings" on social media. Based on this information, the generation AI creates a list of User A as an interested user and stores it in Amazon S3.

[0677] Delivering online advertisements

[0678] server:

[0679] The server uses the identified user list to configure the advertising campaign, including specifying the ad content, target audience, and duration.

[0680] This setting is sent to advertising platforms (e.g., Yahoo or other internet services).

[0681] Device:

[0682] Internet users can view targeted advertisements in their browsers and applications.

[0683] When users click on the ad, they are taken to a page with more details about the new savings scheme.

[0684] As a concrete example, the server identifies User A, imports the information into Yahoo's advertising campaign management system, and sets the content and distribution period of a banner ad for a "new savings plan." When User A is browsing a Yahoo page, the ad is displayed. When User A clicks on the ad, the page transitions to a detailed page.

[0685] Application acceptance and notification

[0686] server:

[0687] Place a registration form on the class details page. Receive the data entered by the user and store it in a database.

[0688] After confirming your application, we will send you an email or message informing you of the date, time and location of the class.

[0689] Device:

[0690] Users enter the necessary information on the details page and apply to participate.

[0691] Receive notification emails and messages and prepare to join the class.

[0692] For example, when User A enters his / her name and email address into the form on the details page and submits it, the server stores this data in the database. When the application is accepted, a notification email is sent to User A.

[0693] Classes held

[0694] server:

[0695] It manages presentation materials and demonstration data used in the classroom and provides them to the instructor's device.

[0696] Manage participant lists and provide them to instructors to assist with classroom management.

[0697] Device (instructor's smartphone):

[0698] The lecturer will use a smartphone to display a presentation and explain the new savings system.

[0699] A demonstration will be conducted to show specific operation methods.

[0700] As a concrete example, the lecturer will project presentation materials onto a smartphone and explain to the participants. There will also be a demonstration of the specific operation of savings points via smartphones and other fixed services.

[0701] Feedback collection and tracking

[0702] server:

[0703] After the class, participants will be sent a feedback form and the collected data will be analyzed to identify areas for improvement.

[0704] Track and record the use of services discussed in the classroom in a database.

[0705] For example, after the class ends, the server sends a feedback form to User A asking, "How was the class?" and receives and analyzes the responses. It also continuously tracks User A's usage of the savings plan.

[0706] This allows the system, which utilizes generative AI, to effectively identify users and provide them with appropriate information through targeted advertising, thereby promoting the use of related services and expanding the customer base.

[0707] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0708] Step 1: Data collection

[0709] server:

[0710] Input: Website access logs, social media posting data

[0711] The server collects user data from these data sources, using web scraping and APIs to obtain log information and posted data.

[0712] After data acquisition, the collected data is stored in a PostgreSQL database.

[0713] Output: User data stored in the database

[0714] Step 2: Data analysis

[0715] server:

[0716] Input: User data stored in the database

[0717] The server uses a generative AI model (e.g., GPT-3 or BERT) to analyze the collected data based on the prompt.

[0718] Prompt: "Analyze website traffic logs and social media posting data to identify users interested in a new savings program."

[0719] Based on the analysis results, the server generates a list of users interested in the new savings system and stores it in Amazon S3.

[0720] Output: User list stored in Amazon S3

[0721] Step 3: Campaign Settings

[0722] server:

[0723] Input: A user list stored in Amazon S3

[0724] The server uses the user list to set up online advertising campaigns, for example determining the content, targeting, and duration of banner ads.

[0725] Send your settings to advertising platforms (Yahoo, other internet services).

[0726] Output: Campaign data set in the advertising platform

[0727] Step 4: Ad serving

[0728] server:

[0729] Input: Campaign data set in the advertising platform

[0730] The server uses an advertising platform to deliver online advertisements to targeted users.

[0731] Output: Ad banner displayed in the user's browser or app

[0732] Device:

[0733] Input: An ad banner displayed in a user's browser or app.

[0734] When users click on the ad, they are redirected to a page with more details about the new savings scheme.

[0735] Output: User navigates to the classroom details page

[0736] Step 5: Accepting your application

[0737] server:

[0738] Input: Application data entered by the user on the details page

[0739] The server receives the participation application data from the form placed on the classroom details page and stores it in a database.

[0740] Output: Application data stored in a database

[0741] Device:

[0742] Input: Information the user enters on the detail page (such as name, email address, etc.)

[0743] The user enters the required information into the application form and submits it.

[0744] Output: Data sent to the server

[0745] Step 6: Sending notifications

[0746] server:

[0747] Input: Participation application data stored in the database

[0748] The server will confirm the registration and send a notification email or message to the user with the date, time and location of the class.

[0749] Output: Notification emails and messages sent to users

[0750] Device:

[0751] Input: Notification emails and messages sent from the server

[0752] Users will receive notification emails and messages and prepare to join the class.

[0753] Output: Classroom participation preparation information

[0754] Step 7: Prepare for the class

[0755] server:

[0756] Input: Managed presentation and demo data

[0757] The server provides prepared materials and data to the instructor's device (such as a smartphone), and also manages the participant list and provides it to the instructor.

[0758] Output: Materials provided to the instructor and a list of participants

[0759] Step 8: Hold a class

[0760] Device (instructor's smartphone):

[0761] Input: Presentation materials and participant list provided by the server

[0762] The instructor will use a smartphone to display a presentation and explain the new savings system, and will provide a demonstration with concrete examples using the smartphone and other services.

[0763] Output: Explanations and demo content for classroom participants

[0764] user:

[0765] Input: Explanation and demo content provided by the instructor

[0766] Users can attend classes and listen to explanations to deepen their understanding of the new savings system.

[0767] Output: User understanding and interest

[0768] Step 9: Gather feedback

[0769] server:

[0770] Input: Feedback form submitted after class

[0771] The server sends feedback forms to participants and analyzes the collected data.

[0772] Output: Analyzed feedback data

[0773] Step 10: Tracking

[0774] server:

[0775] Input: Usage data of services explained in the classroom

[0776] The server continuously tracks the usage of the services explained in the classroom and records it in a database.

[0777] Output: Updated database usage data

[0778] By taking specific actions at each step, the system can efficiently identify users' interests and promote information and service use through targeted advertising and classes.

[0779] (Application example 1)

[0780] 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."

[0781] The challenge is to efficiently identify users who are interested in specific products or services in physical stores, promptly notify them of campaigns or events, and automate the entire process from registration to the actual event management and feedback collection.Flaws in such systems can impair the timeliness and accuracy of information provided to users, and effective feedback collection and utilization is necessary to improve event participant satisfaction and promote service usage.

[0782] 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.

[0783] In this invention, the server includes means for identifying user interests using a generation AI, means for delivering online advertisements, means for accepting participation applications, means for notifying event participants, means for providing information to event participants, means for collecting feedback from event participants, means for tracking the usage of services explained at the event, means for managing applications for events held at physical stores, and means for notifying smartphones of event information held at physical stores. This makes it possible to accurately grasp user interests, provide campaign and event information at appropriate times, and consistently manage the process from participation applications to feedback collection.

[0784] "Generative AI" is a type of artificial intelligence that analyzes data and automatically generates insights based on specific requirements and conditions.

[0785] "Means for identifying user interests" refers to technology that analyzes collected data to extract user interests in specific products or services.

[0786] "Means for delivering online advertising" refers to a mechanism for delivering advertising content to specific users via the Internet.

[0787] "Means for accepting participation applications" refers to a function for accepting and managing applications from users to participate in events and campaigns.

[0788] "Means for notifying users of upcoming events" is a function that notifies users of upcoming events based on the set date, time, and content.

[0789] "Means for providing information to event participants" refers to a system for providing participants with the information they need before, during, and after the event.

[0790] "Means for collecting feedback from event participants" refers to techniques for collecting opinions and impressions from participants after the event and analyzing them as data.

[0791] "Means for tracking usage of services explained at the event" refers to a system for monitoring and recording subsequent usage of products or services introduced at the event.

[0792] The "means for managing applications for events held in physical stores" refers to a technology that comprehensively manages users' applications to participate in events held in physical stores.

[0793] "Means of notifying smartphones of event information held at physical stores" is a system that notifies users' smartphones of information about events scheduled at physical stores.

[0794] The system of the present invention uses a generative AI to identify users who are interested in a specific product and provide those users with campaign and event notifications for physical stores. Specifically, it includes the following processing steps.

[0795] User Specific

[0796] The server collects website access logs and social media posts and stores them in a database. The software used here includes a data collection API and a generative AI model (e.g., OpenAI GPT-3). The generative AI analyzes the collected data and creates a list of users who are interested in a particular product or service.

[0797] Campaign Notifications

[0798] The server sets up an online advertising campaign based on the user list identified by the generation AI. This setting includes the ad content, target audience, and period. Campaign information is then sent to the user's smartphone. The hardware used includes the server and the user's smartphone, and the software includes an email sending API (e.g., SendGrid) and a notification API.

[0799] Event participation application

[0800] The device (user's smartphone) displays details of the notified campaign or event and allows the user to apply directly. The server receives the application data and stores it in a database. The software used includes a web server and a database management system.

[0801] Event Notification

[0802] When the event date approaches, the server will send a reminder message to help users remember the event. The software includes a notification API so that reminder notifications are sent to users' smartphones.

[0803] Feedback collection

[0804] After the event, the server sends a feedback form to users, analyzes the collected data, and identifies areas for improvement. This will help improve the quality of the next event. The software used includes a feedback form API and a data analysis tool.

[0805] Specific user examples

[0806] For example, when User A is searching for savings-related products, he or she is included in a target list by the generation AI. Based on this list, a campaign notification for a new savings scheme is sent to User A's smartphone. User A clicks on the notification to check the details of the event and apply to participate. Before the event, the server sends User A a reminder message, and after the event ends, a feedback form is sent. Through this series of processes, User A can efficiently obtain information and use new services through the event.

[0807] Prompt Sentence Examples

[0808] "We use generative AI to automate the process of identifying users who are interested in a particular product and sending them promotional notifications."

[0809] "We want to develop an application that allows users to register for seminars held in physical stores and collect feedback on campaigns that interest them."

[0810] Through this process, this application example builds a system that identifies users interested in a new savings scheme and encourages them to participate in events at physical stores.

[0811] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0812] Step 1:

[0813] The server uses a data collection API to obtain website access logs and social media posts and stores them in a database. The input is log data and post data from each data source, which is processed and stored in the database. The output is raw data stored in the database. Specifically, it executes API requests, collects JSON-formatted data, analyzes it, and inserts it into the database.

[0814] Step 2:

[0815] The server analyzes the collected data using a generative AI model (e.g., OpenAI GPT-3) to create a list of users who are interested in a particular product or service. The input is raw data stored in a database, which is analyzed by the generative AI model. The output is a list of users who are determined to be interested. Specifically, the server creates prompts for the generative AI model and performs an analysis process to identify user interests based on the prompts.

[0816] Step 3:

[0817] The server sets up an online advertising campaign based on the user list identified by the generation AI. The input is the identified user list and campaign content, and based on this, it generates ad delivery settings. The output is setting information for the online ad delivery platform. Specifically, it sets parameters such as ad content, delivery target, and period, and sends the data to the delivery platform via API.

[0818] Step 4:

[0819] The device (user's smartphone) receives the campaign notification sent from the server and displays it to the user. The input is the campaign notification data, which is displayed through the smartphone's notification function. The output is the notification display to the user. Specifically, the notification message is constructed using the notification API and displayed as a pop-up on the smartphone screen.

[0820] Step 5:

[0821] The user checks the details of the notified campaign or event on their smartphone and applies to participate. The input is the notification message and a link to the details page, which the user clicks to access the application form. The output is the data entered into the application form. Specifically, the user clicks the link, enters the required information into the web form, and submits it.

[0822] Step 6:

[0823] The server receives event participation application data from users and stores it in a database. The input is the application data sent from the web form, which is saved in the database. The output is the saved application data. Specifically, it receives the form data and inserts it into the database.

[0824] Step 7:

[0825] As the event date approaches, the server sends a reminder message. The input is the event date and time and a list of users, and the server generates a reminder message based on this. The output is a reminder message sent to the user's smartphone. Specifically, the server uses a notification API to send a message based on the reminder settings.

[0826] Step 8:

[0827] After the event ends, the server sends a feedback form to users and analyzes the collected data. The input is the event participant list and the feedback form, and feedback is collected based on this. The output is the feedback data and its analysis results. Specifically, the form link is sent using the feedback form API, and the collected data is evaluated using an analysis tool.

[0828] 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.

[0829] This invention provides a method for specifically implementing a system that uses generative AI and an emotion engine to identify users interested in a new savings program and announces the opening of classes through online advertising. Each element and its specific operation are described below.

[0830] User identification with generative AI and emotion engine

[0831] server:

[0832] User data is collected from various data sources (website access logs, social media posts, user text input, etc.) and stored in a database.

[0833] The generative AI analyzes the collected data, analyzes user interests and behavioral patterns, and based on the analysis results, creates a list of users who are interested in the new savings system.

[0834] The emotion engine uses a webcam and microphone to analyze emotions from the user's facial expressions and voice, and also recognizes emotions from the user's text input.

[0835] Delivery and dynamic adjustment of online advertisements

[0836] server:

[0837] Set up a targeted advertising campaign: define what ads to advertise, who to advertise to, and for how long.

[0838] Based on the analysis results of the generative AI and emotion engine, the content of online advertisements is dynamically adjusted and banner advertisements are delivered.

[0839] Device:

[0840] As users navigate the internet, they are shown tailored banner ads, whose timing and location change dynamically based on targeting lists and sentiment analysis.

[0841] When a user clicks on the banner ad, they are taken to a page detailing the new savings program.

[0842] Application acceptance and notification

[0843] server:

[0844] The class details page contains an application form, and the application data entered by the user is received and stored in a database.

[0845] After confirming your application, we will notify you of the date, time and location of the class via email or message.

[0846] Device:

[0847] The user enters the required information on the details page and applies to participate.

[0848] Receive notification emails and messages and prepare to join the class.

[0849] Classroom Management and Emotional Response

[0850] server:

[0851] It manages presentation materials and demonstration data used in the classroom and provides them to the instructor's device.

[0852] Provide the instructor with a list of participants and assist with classroom management.

[0853] Device (instructor's smartphone):

[0854] The lecturer uses a smartphone to display and explain a presentation about a new savings system, and the speaker's smartphone dynamically adjusts the content and tone of the presentation based on the user's emotional data obtained from the emotion engine.

[0855] Demonstrations will be held on smartphones, fixed-line services, and point management, and the benefits of using them will be explained.

[0856] user:

[0857] Participate in the class, listen to the instructor's explanations and demonstrations, and deepen your understanding of the new savings system. You will also learn about smartphones, fixed-line services, and point management.

[0858] Feedback collection and tracking

[0859] server:

[0860] After the class, a feedback form is sent to participants via email or message to collect their ratings and comments.

[0861] The collected feedback data will be analyzed to improve classroom content and services provided.

[0862] The usage status of services (smartphone, fixed line, point management, etc.) that participants have actually started using will be tracked and stored in a database. The usage data for each service will be visualized and used in corporate strategy planning.

[0863] To give a specific example, while User A is searching for information on the Internet, he or she is included in a target list by the generative AI and emotion engine. Based on this list, a dynamically adjusted banner ad is displayed on the web page that User A is viewing. When User A clicks on the ad, he or she is taken to the class details page where he or she can apply to participate. After the application is accepted, a notification email is sent to User A's device. On the day of the class, the instructor will give an explanation, adjusting the presentation based on the user's emotion data. After the class ends, User A fills in a feedback form, and their subsequent service usage is tracked.

[0864] In this way, the system, which utilizes generative AI and an emotion engine, can effectively identify users and provide them with information through classrooms, thereby promoting the use of related services and expanding the customer base.

[0865] The processing flow will be explained below.

[0866] Step 1:

[0867] server:

[0868] User data is collected from various data sources (website access logs, social media posts, user text input, etc.) and stored in a database. The collected data includes user browsing history, click history, and post content.

[0869] The generative AI analyzes the collected data to analyze user interests and behavioral patterns, and based on the analysis results, creates a list of users who are interested in the new savings system.

[0870] Step 2:

[0871] server:

[0872] The emotion engine is initialized and collects the user's facial and voice data via the webcam and microphone. The emotion engine analyzes this data in real time to determine the user's current emotional state.

[0873] Analyzes emotional data from user text input, extracting emotions and tones from text messages and other inputs.

[0874] Step 3:

[0875] server:

[0876] Set up targeted advertising campaigns, defining the content, audience, and duration of ads, using user lists identified by generative AI and sentiment analysis results from the sentiment engine.

[0877] Based on data from the emotion engine, the content of online ads is dynamically adjusted to best suit the user's emotional state before being delivered.

[0878] Step 4:

[0879] Device:

[0880] As users navigate the internet and browse websites and applications, they are shown tailored banner ads, whose timing and location change dynamically based on targeting lists and sentiment analysis.

[0881] When a user clicks on the banner ad, they are taken to a page detailing the new savings program.

[0882] Step 5:

[0883] User:

[0884] Access the class details page and enter the required information (name, contact information, desired date and time of participation, etc.) in the provided participation application form and submit it.

[0885] Once you have completed your registration, you will automatically receive a confirmation message.

[0886] Step 6:

[0887] server:

[0888] Receives application data and stores it in a database. Generates and sends notification emails and messages to users so that they can confirm their application details.

[0889] Send notifications to users with details about class times, dates, and locations.

[0890] Step 7:

[0891] Device:

[0892] Download and prepare classroom presentation materials and demo data onto the instructor's smartphone.

[0893] Users who receive the notification email or message can prepare to join the class.

[0894] Step 8:

[0895] server:

[0896] We will provide the instructor with a list of participants on the day of the class to help ensure the class runs smoothly. This list will also be used to support smooth reception at the entrance to the venue.

[0897] Step 9:

[0898] Device (instructor's smartphone):

[0899] The lecturer uses a smartphone to display and explain in detail a presentation about a new savings scheme, and the speaker's smartphone dynamically adjusts the content and tone of the presentation based on the user's emotional data obtained from the emotion engine.

[0900] Step 10:

[0901] Device (instructor's smartphone):

[0902] Demonstrations will be conducted on smartphones, fixed-line services, and point management, and the benefits of using them will be explained in detail. An emotion engine will be used to adjust the progress of the demonstration based on the emotional state of the participants.

[0903] Step 11:

[0904] User:

[0905] Participate in the class, understand the instructor's explanations and demonstrations, and learn about the structure and benefits of the new savings system. You will also learn in detail about the proposed smartphone and fixed-line services, and point management.

[0906] Step 12:

[0907] server:

[0908] After the class, participants are sent a feedback form via email or message to collect their ratings and comments. The feedback data is then stored in a database for later use in improving the service.

[0909] The usage of the services explained in the class will be tracked in real time and recorded in a database. Usage trends for each service will be analyzed and used to plan future strategies.

[0910] To give a specific example, while User A is searching for information on the Internet, he or she is included in a target list by the generative AI and emotion engine. Based on this list, a dynamically adjusted banner ad is displayed on the web page that User A is viewing. When User A clicks on the ad, he or she is taken to the class details page where he or she can apply to participate. After the application is accepted, a notification email is sent to User A's device. On the day of the class, the instructor will give an explanation, adjusting the presentation based on the user's emotion data. After the class ends, User A fills in a feedback form, and their subsequent service usage is tracked.

[0911] In this way, the system, which utilizes generative AI and an emotion engine, can effectively identify users and provide them with information through classrooms, thereby promoting the use of related services and expanding the customer base.

[0912] Example 2

[0913] 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."

[0914] Conventional online advertising systems only deliver ads based on users' interests, but are unable to deliver ads that take into account users' emotions. Furthermore, there was a lack of a mechanism for adequately collecting and analyzing feedback on how users who received ads behaved after attending classes. Furthermore, it was difficult to track the usage of services explained in classes, which meant that the data could not be fully utilized to improve services or develop marketing strategies.

[0915] 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.

[0916] In this invention, the server includes a means for identifying user interests using generative AI, a means for analyzing user emotions using an emotion engine, and a means for dynamically adjusting and delivering online advertisements using the analysis results. This enables the delivery of highly targeted advertisements based on the user's interests and emotions. The server also includes a means for accepting participation applications, a means for notifying class participants, a means for providing information to class participants, a means for collecting feedback from class participants, and a means for tracking the usage of services explained in the classes. This facilitates the collection and analysis of feedback and the tracking of service usage, which can be used to improve services and develop strategies.

[0917] "Generative AI" is a system that uses artificial intelligence technology to identify users' interests and concerns.

[0918] An "emotion engine" is a system for analyzing emotions from data such as a user's facial expressions, voice, and text input.

[0919] "Online advertising" refers to advertising banners and links distributed over the Internet, which are a means of providing information and promotions to users.

[0920] "Dynamic adjustment" refers to changing the content and timing of advertising in real time based on the analysis results of the generative AI and emotion engine.

[0921] "Registration" is the process by which a user indicates their intention to attend a class or event and provides the necessary information.

[0922] "Notifications" are a way to communicate important information to users, such as the date, time, and location of class events.

[0923] "Feedback" refers to information collected from users, such as ratings and comments, that is used to improve our services and events.

[0924] "Tracking" is the process of monitoring and collecting data on the use of the services described in the classroom.

[0925] This invention is a system that utilizes generative AI and an emotion engine to analyze users' interests and emotions, deliver appropriate online advertisements, provide class information, collect feedback, and track service usage. The system is composed of three main entities: a server, a device, and the user.

[0926] User Specific

[0927] The server collects user data from various data sources (e.g., website access logs, social media posts, user text input) and stores it in a database. The server uses generative AI to analyze the collected data and identify the user's interests. This analysis uses natural language processing (NLP) technology. The emotion engine analyzes emotions from the user's facial expressions and voice data obtained from the webcam and microphone, as well as text input.

[0928] As a specific example, a user's search history for keywords related to "new savings systems" is collected, and based on the collected data, the generation AI determines that the user is interested in a new financial product.

[0929] Delivery and dynamic adjustment of online advertisements

[0930] The server sets up a targeted advertising campaign and defines the ad content, distribution target, and distribution period. Based on the analysis results of the generative AI and emotion engine, the ad content is dynamically adjusted and delivered to users as banner ads on the Internet. The adjusted banner ad is displayed on the user's device (PC or smartphone). When the user clicks on the banner ad, they are taken to a class details page where they can apply to participate.

[0931] As a concrete example, when user A is browsing a news site, a dynamically adjusted banner ad appears, and when he clicks on the ad, he is taken to a detailed page about a class on savings programs.

[0932] Application acceptance and notification

[0933] The server places a participation application form on the class details page and stores the participation application data entered by the user in a database. The server then notifies the user of the class date, time, and location via email or message. The user receives the notification on their device and prepares to participate in the class.

[0934] As a specific example, a user accesses a class details page via a banner ad, applies to participate from there, and receives a notification email.

[0935] Classroom Management and Emotional Response

[0936] The server manages presentation materials and demo data and provides them to the instructor's device (e.g., a smartphone). In the classroom, the instructor uses their smartphone to give a presentation, dynamically adjusting the content and tone based on the user's emotional data obtained from the emotion engine. Participants attend the class and learn about the new savings system.

[0937] As a concrete example, the instructor can use a smartphone in the classroom to check emotional data in real time and adjust the content of the explanation as he or she goes along.

[0938] Feedback collection and tracking

[0939] After the class ends, the server sends a feedback form to the participants and collects their ratings and comments. This data is analyzed to improve the class content and services. The server also tracks the usage of services that participants have actually started using and stores the data in a database. This data can be used to develop corporate strategies.

[0940] For example, after the class ends, users are sent a feedback form, and the results are reflected in improving the content of the next class.

[0941] Prompt Sentence Examples

[0942] "Describe a system that detects user interests and delivers targeted advertising based on the data analyzed by an emotion engine."

[0943] This invention enables highly targeted advertising based on user interests and emotions, helping to promote new savings programs more effectively through classrooms, while collecting feedback and tracking usage allows for continuous improvement of the service.

[0944] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0945] Step 1:

[0946] Data collection

[0947] server:

[0948] The server collects user data from data sources such as website access logs, social media posts, and user text input, and stores it in a database. Various data sources are used as input, and the output is formatted user data. Specifically, the server calls the data source API, retrieves JSON-formatted data, and stores it in the database.

[0949] Step 2:

[0950] Interest identification using generative AI

[0951] server:

[0952] The server inputs the collected user data into the generation AI to identify the user's interests. In this case, the generation AI uses natural language processing (NLP) technology. The input is user data, and the output is the identified user interest data. Specifically, the generation AI model feeds user data and classifies the user's interests by comparing it with the educational database.

[0953] Step 3:

[0954] Emotion analysis

[0955] server:

[0956] The server uses an emotion engine to analyze emotions from the user's facial expressions, voice, and text input obtained from the webcam and microphone. The input is real-time data, and the output is analyzed emotion data. Specifically, the webcam footage is analyzed frame by frame, the voice data is subjected to phonetic pattern analysis, and emotion keywords are extracted from the text.

[0957] Step 4:

[0958] Ad delivery settings and adjustments

[0959] server:

[0960] The server sets up targeted advertising campaigns and dynamically adjusts ad content based on the analysis results of the generative AI and emotion engine. The input is interest data and emotion data, and the output is adjusted ad data. Specifically, it inserts messages and images into ad templates that match the user's interests and emotions.

[0961] Step 5:

[0962] Advertisement display

[0963] Device:

[0964] The tailored banner ad is displayed on the user's device (PC or smartphone). The input is the tailored ad data, and the output is the displayed ad. Specifically, when the user browses a web page, the dynamically tailored banner ad is rendered in the ad display area.

[0965] Step 6:

[0966] Participation application acceptance

[0967] server:

[0968] The server places an application form on the class details page, receives the application data entered by the user, and stores it in a database. The input is the user's application data, and the output is the stored application data. Specifically, the server receives input from the user in an HTML form and saves it in a database on the backend.

[0969] Step 7:

[0970] Send notifications

[0971] server:

[0972] After the server confirms the participation application, it notifies the user of the class date, time, and location via email or message. The input is the participation confirmation data, and the output is the notification email or message sent. Specifically, it uses an email sending API to send individual notification emails to participants.

[0973] Step 8:

[0974] Presentation materials provided

[0975] server:

[0976] The server manages the presentation materials and demo data used in the classroom and provides them to the instructor's terminal. The input is the presentation materials and demo data, and the output is the materials provided to the instructor's terminal. Specifically, the server makes the materials available for download from a cloud storage service and sends a link to the instructor's terminal.

[0977] Step 9:

[0978] Classroom Management and Emotional Response

[0979] Device (instructor's smartphone):

[0980] The lecturer uses a device to give a presentation and dynamically adjusts the content and tone based on data from the emotion engine. The input is emotion data, and the output is an adjusted presentation. Specifically, the emotion data is received in real time and the content and tone of the slides are changed accordingly.

[0981] Step 10:

[0982] Feedback collection

[0983] server:

[0984] After the class ends, the server sends a feedback form to the participants and collects their ratings and comments. The input is the feedback data, and the output is the collected feedback. Specifically, a form submission API is used to send a link to the participants, and their responses are saved in a database.

[0985] Step 11:

[0986] Usage Tracking

[0987] server:

[0988] The server tracks the status of services actually used by class participants and stores the data in a database. The input is usage data, and the output is the stored tracking data. Specifically, usage logs are collected periodically and stored in a database for analysis.

[0989] Through these steps, the system can effectively deliver advertisements according to users' interests and emotions, manage classrooms, collect feedback, and track usage.

[0990] (Application example 2)

[0991] 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."

[0992] Today's consumers are bombarded with a vast amount of information, making it difficult to find information and products that are relevant to them. Furthermore, to maximize the effectiveness of online advertisements and campaigns, targeting based on individual users' emotions and interests is necessary. Furthermore, virtual stores require mechanisms that allow users to enjoy individually customized shopping experiences. Given this background, there is a need for systems that can provide advertisements and information based on users' interests and emotions, and measure and improve their effectiveness.

[0993] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0994] In this invention, the server includes means for identifying user interests using generative AI, means for delivering online advertisements, means for accepting participation applications, means for notifying class schedules, means for providing information to class participants, means for collecting feedback from class participants, means for tracking the usage of services explained in the class, means for using an emotion engine that analyzes the user's emotional state based on their facial expressions and voice, and means for providing a customized shopping experience through smart glasses in a virtual store. This makes it possible to provide advertisements and information optimized for each individual user and measure and improve their effectiveness in real time.

[0995] "Generative AI" is a technology that uses artificial intelligence to automatically analyze and identify users' interests and concerns.

[0996] "Online advertising" refers to advertising content delivered to users via the Internet.

[0997] "Registration" is the process by which a user indicates their intention to participate in a particular event or class and completes the necessary procedures.

[0998] "Classroom Notification" is a means of communicating information to users about details such as the date and location of an event or class.

[0999] "Feedback" refers to reactions and comments such as evaluations and opinions obtained from users.

[1000] "Tracking" means the continuous tracking and recording of the usage of a particular service or product.

[1001] The "emotion engine" is a technology that analyzes the user's facial expressions and voice to recognize and evaluate their emotional state.

[1002] A "virtual store" is not an actual physical store, but a virtual store that operates online or in the digital space.

[1003] "Smart glasses" are advanced eyeglass-type devices equipped with a display, camera, sensors, etc., and capable of providing information to users.

[1004] "Shopping experience" is a general term for the experiences and services that consumers receive in the process of selecting and purchasing a product.

[1005] This invention is a system that utilizes generative AI and an emotion engine to provide users with optimal advertisements and information, thereby improving their shopping experience in virtual stores. A specific embodiment of the present invention is described below.

[1006] System Configuration

[1007] This system mainly consists of three elements: a server, a terminal (smart glasses, smartphone, etc.), and a user. The role and operation of each element are explained below.

[1008] server

[1009] The server consists of multiple components, including a generative AI model, an emotion engine, and a database. Specifically, it uses the following software and hardware:

[1010] Hardware and Software

[1011] Hardware: High-performance server

[1012] Software: Python, TensorFlow, OpenCV

[1013] Data collection

[1014] The server collects user data from each data source (website access logs, social media posts, user text input, etc.) and stores it in a database.

[1015] Analysis by generative AI

[1016] The generative AI model analyzes the collected data and analyzes user interests and behavioral patterns. This generates a list of users who are interested in the new savings scheme. An example prompt is shown below:

[1017] "We are collecting text information to identify users who are interested in investing and saving. Analyze their interests and create a list of users who are most likely to be interested in a new savings scheme."

[1018] Analysis by emotion engine

[1019] The emotion engine uses a webcam and microphone to analyze emotions from the user's facial expressions and voice. The emotion engine also recognizes emotions from the user's text input.

[1020] Ad delivery and dynamic adjustment

[1021] The server sets up targeted advertising campaigns, defining the ad content, target audience, and distribution period. Based on the analysis results of the generative AI and emotion engine, the content of online ads is dynamically adjusted and banner ads are distributed.

[1022] Terminal

[1023] Smart Glasses

[1024] Users use smart glasses to shop in virtual stores. The smart glasses have the following features:

[1025] Advertisement display: Displaying customized banner ads at the right time based on the user's emotional state.

[1026] Providing detailed information: Clicking on an ad displays detailed information about the product or event and takes you to a page to register for participation.

[1027] Smartphone

[1028] Smartphones will be used for classroom presentations and registration.

[1029] Presentation display: The instructor uses a smartphone to display a presentation about a new savings scheme.

[1030] Dynamic adjustment based on emotional data: The instructor's smartphone dynamically adjusts the content and tone of the presentation based on the user's emotional data obtained from the emotion engine.

[1031] user

[1032] The user uses this system to perform the following process:

[1033] Viewing ads and signing up: When users are browsing the internet, they will be shown dynamically adjusted banner ads that, when clicked, will take them to a class details page where they can sign up.

[1034] Providing feedback: After the class, participants fill out a feedback form and their subsequent use of the service is tracked.

[1035] In this way, the present invention can provide users with the most appropriate advertisements and information, allowing them to customize their shopping experience in a virtual store.

[1036] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1037] Step 1:

[1038] The server collects user data from data sources such as website access logs, social media posts, and user text input, and stores it in a database.

[1039] Input: Website access logs, social media posts, user text input

[1040] Data processing: Collected data is centrally managed and stored in a database

[1041] Output: A cleaned up user database

[1042] Step 2:

[1043] The server uses a generative AI model to analyze the collected data and analyze users' interests and behavioral patterns.

[1044] Input: User Database

[1045] Data Computation: Using generative AI models to calculate interest scores and identify target users

[1046] Output: List of highly interested users

[1047] Specific operation: The generative AI performs analysis based on the prompt: "We are collecting text information to identify users who are interested in investing and saving. Analyze user interests and create a list of users who are likely to be most interested in the new savings system."

[1048] Step 3:

[1049] The server uses an emotion engine to analyze the user's emotional state based on facial expressions, voice, and text input obtained from the webcam and microphone.

[1050] Input: Webcam video, audio data, text input

[1051] Data Computation: Emotion Analysis Using an Emotion Engine

[1052] Output: User's emotional state data

[1053] Specific operation: Obtain data in real time from a webcam and microphone to estimate emotional state.

[1054] Step 4:

[1055] Based on the analysis results of the generative AI and emotion engine, the server sets up advertising campaigns, generates and adjusts targeted ads, and delivers online ads.

[1056] Input: User list, emotional state data

[1057] Data processing: Ad content is customized for each user and displayed at the appropriate time

[1058] Output: Tailored banner ad

[1059] Specific operation: The advertising distribution system displays the most appropriate advertisement for the page viewed by the target user.

[1060] Step 5:

[1061] While using the Internet, users view tailored banner ads and click on them to be taken to a details page where they can apply to participate.

[1062] Input: Tailored banner ads

[1063] Output: Display of classroom details page, participation application data

[1064] Specific actions: The user clicks on the ad and fills in the required information on the application form.

[1065] Step 6:

[1066] The server places a participation application form on the classroom details page, receives the participation application data entered by the user, and stores it in a database.

[1067] Input: Participation application data

[1068] Data processing: Save the application data in a database and check for duplications and errors.

[1069] Output: Organized participant list

[1070] Step 7:

[1071] The server confirms the participation application and notifies the user of the date, time and location of the class via email or message.

[1072] Input: Participant list

[1073] Output: Notification email, message

[1074] Specific action: Execute a process to automatically send notifications to participants.

[1075] Step 8:

[1076] The device (the instructor's smartphone) displays presentation materials during the class and dynamically adjusts the content and tone based on data from the emotion engine.

[1077] Input: Presentation materials, participants' emotional state data

[1078] Data processing: Adjusting presentation content and changing tone

[1079] Output: Well-tuned presentation

[1080] Specific behavior: Check emotional state in real time and optimize content.

[1081] Step 9:

[1082] Users will attend classes, follow lectures and demonstrations from instructors, and gain a deeper understanding of the new savings system.

[1083] Input: Instructor presentation

[1084] Output: Improved user understanding

[1085] Specific actions: Listen to the instructor's explanation and watch the demonstration to learn.

[1086] Step 10:

[1087] After the class, the server sends a feedback form to participants and collects their evaluations and comments.

[1088] Input: Feedback Form

[1089] Data processing: Analysis of collected feedback data

[1090] Output: Feedback data analysis results

[1091] Specific actions: Automatically send feedback forms to participants and analyze the collected data.

[1092] This makes it possible for the present invention to provide users with optimal advertisements and information, improving their shopping experience in virtual stores.

[1093] 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.

[1094] 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.

[1095] 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.

[1096] [Third embodiment]

[1097] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1098] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1099] 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).

[1100] 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.

[1101] 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.

[1102] 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).

[1103] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1104] 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.

[1105] 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.

[1106] 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.

[1107] 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.

[1108] 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."

[1109] The system of the present invention uses generative AI to identify users interested in a new savings program and automates the process of announcing the class via online advertising. The system is configured as follows:

[1110] User identification using generative AI

[1111] server:

[1112] User data is collected from various data sources (website access logs, social media posts, etc.) and stored in a database.

[1113] Generative AI is used to analyze the collected data and create a list of users who are interested in the new savings scheme.

[1114] Delivering online advertisements

[1115] server:

[1116] Based on the user list identified by the AI ​​generation, online advertising campaign settings are made, including the ad content, target audience, and period.

[1117] Based on the floor settings, banner ads will be delivered to platforms such as Yahoo and PayPay.

[1118] Device:

[1119] Allows internet users to see targeted advertising in their browsers and applications.

[1120] When a user clicks on the ad, they are taken to a page detailing the class on the new savings program.

[1121] Application acceptance and notification

[1122] server:

[1123] The class details page contains an application form, and the application data entered by the user is received and stored in a database.

[1124] After confirming your application, we will notify you of the date, time and location of the class via email or message.

[1125] Device:

[1126] The user enters the required information on the details page and applies to participate.

[1127] Receive notification emails and messages and prepare to join the class.

[1128] Classes held

[1129] server:

[1130] It manages presentation materials and demonstration data used in the classroom and provides them to the instructor's device.

[1131] Provide the instructor with a list of participants and assist with classroom management.

[1132] Device (instructor's smartphone):

[1133] The instructor will use a smartphone to display a presentation and provide a detailed explanation of the new savings system.

[1134] Demonstrations will be held on smartphones, fixed services, and point management using PayPay.

[1135] user:

[1136] Attend classes and listen to the instructor's explanations to deepen your understanding of the new savings system.

[1137] The proposed services will be reviewed.

[1138] Feedback collection and tracking

[1139] server:

[1140] After the class, participants will be sent a feedback form, and the collected data will be analyzed to identify areas for improvement.

[1141] Track and record usage of services discussed in the classroom in a database.

[1142] To give a specific example, while User A is searching for information on the internet, he or she is included in a target list by the generation AI. Based on this list, a banner ad for a new savings system is displayed on the web page that User A is viewing. When User A clicks on the ad, he or she is taken to the class details page where he or she can apply to participate. When the application to participate is accepted, a notification email is sent to User A's device. On the day of the class, the instructor displays materials and gives an explanation. After the class, User A fills out a feedback form, and subsequent service usage is tracked.

[1143] In this way, systems that utilize generative AI can efficiently identify users and provide information through classrooms, thereby promoting the use of related services and expanding the customer base.

[1144] The processing flow will be explained below.

[1145] Step 1:

[1146] server:

[1147] User data is collected from various data sources (website access logs, social media posts, etc.) and stored in a database, including user browsing history, click history, and post content.

[1148] The collected data is input into a generative AI to analyze user interests and behavioral patterns.

[1149] Step 2:

[1150] server:

[1151] Based on the analysis results of the Generator AI, a list of users who are interested in the new savings scheme is created. The Generator AI uses a specific algorithm to determine the level of interest and similarity of behavioral patterns.

[1152] Save the listed user information in the database.

[1153] Step 3:

[1154] server:

[1155] Set up a targeted advertising campaign: define what ads to advertise, who to advertise to, and for how long.

[1156] Online advertisements will begin to be delivered based on the specific user list obtained from the generated AI.

[1157] Step 4:

[1158] Device:

[1159] While users are browsing the internet, they are shown banner ads, which are dynamically timed and placed based on a targeting list.

[1160] When a user clicks on the banner ad, they are taken to a page detailing the new savings program.

[1161] Step 5:

[1162] User:

[1163] Access the class details page and enter the required information (name, contact information, desired date and time of participation, etc.) in the provided participation application form and submit it.

[1164] Once submitted, your application will be complete.

[1165] Step 6:

[1166] server:

[1167] Receives the registration data and stores it in a database. Generates an email or message to notify the user that their registration is complete.

[1168] It reviews each application and sends users notifications with details of the class date, time and location.

[1169] Step 7:

[1170] Device:

[1171] Classroom presentation materials and demo data are downloaded to the instructor's smartphone, and preparations are complete.

[1172] Users who receive the notification email or message can prepare to join the class.

[1173] Step 8:

[1174] server:

[1175] We will provide the instructor with a list of participants on the day of the class to help ensure the class runs smoothly.

[1176] Step 9:

[1177] Device (instructor's smartphone):

[1178] The instructor uses a smartphone to display a presentation about the new savings system and give an explanation.

[1179] We will conduct demonstrations on smartphones, fixed services, and point management with PayPay, and explain the benefits of using them.

[1180] Step 10:

[1181] User:

[1182] Participants will deepen their knowledge of the new savings system through classroom explanations and demonstrations, as well as learn about smartphones, fixed-line services, and how to use PayPay points.

[1183] Step 11:

[1184] server:

[1185] After the class, a feedback form is sent to participants via email or message to collect their ratings and comments.

[1186] The collected feedback data will be analyzed to improve classroom content and services provided.

[1187] Step 12:

[1188] server:

[1189] The usage status of services (smartphone, fixed line, point management, etc.) that participants have actually started using will be tracked and stored in a database. The usage data for each service will be visualized and used in corporate strategy planning.

[1190] In this way, by performing specific actions at each processing step, it is possible to utilize generative AI to achieve efficient user identification and classroom management, thereby promoting the use of related services and expanding the customer base.

[1191] Example 1

[1192] 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."

[1193] Existing online advertising systems lack the means to identify user interests and deliver targeted advertisements effectively. They also lack the means to smoothly guide target users through the process of joining a class and track service usage. As a result, it is difficult to promote the use of related services and expand customer base.

[1194] 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.

[1195] In this invention, the server includes means for identifying user interests using generation AI, means for delivering online advertisements, means for accepting participation applications, means for notifying class schedules, means for providing information to class participants, means for collecting feedback from class participants, means for tracking usage of services explained in classes, means for collecting user data and storing it in a database, and means for setting up advertising campaigns on an advertising platform. This effectively identifies user interests and delivers targeted advertisements, promoting the use of related services and expanding customer base. It also allows users to smoothly participate in the class process and efficiently track feedback and usage.

[1196] "Generative AI" is an artificial intelligence technology used to analyze collected data to identify user interests and concerns.

[1197] "Online advertising" refers to advertising delivered via the Internet and displayed in the browsers and applications used by users.

[1198] "Application" is the process by which a user expresses their intention to participate in a particular event or class by filling out and submitting the required information in the provided form.

[1199] "Class Notification" means an email or message sent to a user to inform them of the date, time, and location of a class.

[1200] "Information provision" refers to the act of providing detailed information about new savings programs to class participants through presentations and demonstrations.

[1201] "Feedback collection" is a procedure for collecting evaluations and opinions on the content of the class from class participants.

[1202] "Tracking" refers to the act of continuously tracking the usage of the services explained in the classroom and recording it in a database.

[1203] "User Data" refers to information about a specific user, such as website access logs or social media posts.

[1204] A "database" is an information system for storing and efficiently managing collected user data and analysis results.

[1205] An "advertising campaign" is an advertising distribution plan established based on a specific purpose, and includes advertising content, distribution target, period, etc.

[1206] An "advertising platform" refers to an internet infrastructure that provides systems and services for delivering online advertisements.

[1207] The system of the present invention uses generative AI to identify users interested in a new savings program and automates the process of announcing the class via online advertising. Specific embodiments are described below.

[1208] User identification using generative AI

[1209] server:

[1210] The server collects user data from data sources such as website access logs and social media posts and stores it in a database such as PostgreSQL.

[1211] Analyze the collected data using a generative AI model (e.g., GPT-3 or BERT) to identify users who are interested in the new savings scheme. This process uses the prompt "Analyze website access logs and social media posting data to identify users who are interested in the new savings scheme."

[1212] Generate a list of identified users and store it in Amazon S3.

[1213] For example, the server collects information such as when User A visits a page called "savings tips" or posts about "savings" on social media. Based on this information, the generation AI creates a list of User A as an interested user and stores it in Amazon S3.

[1214] Delivering online advertisements

[1215] server:

[1216] The server uses the identified user list to configure the advertising campaign, including specifying the ad content, target audience, and duration.

[1217] This setting is sent to advertising platforms (e.g., Yahoo or other internet services).

[1218] Device:

[1219] Internet users can view targeted advertisements in their browsers and applications.

[1220] When users click on the ad, they are taken to a page with more details about the new savings scheme.

[1221] As a concrete example, the server identifies User A, imports the information into Yahoo's advertising campaign management system, and sets the content and distribution period of a banner ad for a "new savings plan." When User A is browsing a Yahoo page, the ad is displayed. When User A clicks on the ad, the page transitions to a detailed page.

[1222] Application acceptance and notification

[1223] server:

[1224] Place a registration form on the class details page. Receive the data entered by the user and store it in a database.

[1225] After confirming your application, we will send you an email or message informing you of the date, time and location of the class.

[1226] Device:

[1227] Users enter the necessary information on the details page and apply to participate.

[1228] Receive notification emails and messages and prepare to join the class.

[1229] For example, when User A enters his / her name and email address into the form on the details page and submits it, the server stores this data in the database. When the application is accepted, a notification email is sent to User A.

[1230] Classes held

[1231] server:

[1232] It manages presentation materials and demonstration data used in the classroom and provides them to the instructor's device.

[1233] Manage participant lists and provide them to instructors to assist with classroom management.

[1234] Device (instructor's smartphone):

[1235] The lecturer will use a smartphone to display a presentation and explain the new savings system.

[1236] A demonstration will be conducted to show specific operation methods.

[1237] As a concrete example, the lecturer will project presentation materials onto a smartphone and explain to the participants. There will also be a demonstration of the specific operation of savings points via smartphones and other fixed services.

[1238] Feedback collection and tracking

[1239] server:

[1240] After the class, participants will be sent a feedback form and the collected data will be analyzed to identify areas for improvement.

[1241] Track and record the use of services discussed in the classroom in a database.

[1242] For example, after the class ends, the server sends a feedback form to User A asking, "How was the class?" and receives and analyzes the responses. It also continuously tracks User A's usage of the savings plan.

[1243] This allows the system, which utilizes generative AI, to effectively identify users and provide them with appropriate information through targeted advertising, thereby promoting the use of related services and expanding the customer base.

[1244] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1245] Step 1: Data collection

[1246] server:

[1247] Input: Website access logs, social media posting data

[1248] The server collects user data from these data sources, using web scraping and APIs to obtain log information and posted data.

[1249] After data acquisition, the collected data is stored in a PostgreSQL database.

[1250] Output: User data stored in the database

[1251] Step 2: Data analysis

[1252] server:

[1253] Input: User data stored in the database

[1254] The server uses a generative AI model (e.g., GPT-3 or BERT) to analyze the collected data based on the prompt.

[1255] Prompt: "Analyze website traffic logs and social media posting data to identify users interested in a new savings program."

[1256] Based on the analysis results, the server generates a list of users interested in the new savings system and stores it in Amazon S3.

[1257] Output: User list stored in Amazon S3

[1258] Step 3: Campaign Settings

[1259] server:

[1260] Input: A user list stored in Amazon S3

[1261] The server uses the user list to set up online advertising campaigns, for example determining the content, targeting, and duration of banner ads.

[1262] Send your settings to advertising platforms (Yahoo, other internet services).

[1263] Output: Campaign data set in the advertising platform

[1264] Step 4: Ad serving

[1265] server:

[1266] Input: Campaign data set in the advertising platform

[1267] The server uses an advertising platform to deliver online advertisements to targeted users.

[1268] Output: Ad banner displayed in the user's browser or app

[1269] Device:

[1270] Input: An ad banner displayed in a user's browser or app.

[1271] When users click on the ad, they are redirected to a page with more details about the new savings scheme.

[1272] Output: User navigates to the classroom details page

[1273] Step 5: Accepting your application

[1274] server:

[1275] Input: Application data entered by the user on the details page

[1276] The server receives the participation application data from the form placed on the classroom details page and stores it in a database.

[1277] Output: Application data stored in a database

[1278] Device:

[1279] Input: Information the user enters on the detail page (such as name, email address, etc.)

[1280] The user enters the required information into the application form and submits it.

[1281] Output: Data sent to the server

[1282] Step 6: Sending notifications

[1283] server:

[1284] Input: Participation application data stored in the database

[1285] The server will confirm the registration and send a notification email or message to the user with the date, time and location of the class.

[1286] Output: Notification emails and messages sent to users

[1287] Device:

[1288] Input: Notification emails and messages sent from the server

[1289] Users will receive notification emails and messages and prepare to join the class.

[1290] Output: Classroom participation preparation information

[1291] Step 7: Prepare for the class

[1292] server:

[1293] Input: Managed presentation and demo data

[1294] The server provides prepared materials and data to the instructor's device (such as a smartphone), and also manages the participant list and provides it to the instructor.

[1295] Output: Materials provided to the instructor and a list of participants

[1296] Step 8: Hold a class

[1297] Device (instructor's smartphone):

[1298] Input: Presentation materials and participant list provided by the server

[1299] The instructor will use a smartphone to display a presentation and explain the new savings system, and will provide a demonstration with concrete examples using the smartphone and other services.

[1300] Output: Explanations and demo content for classroom participants

[1301] user:

[1302] Input: Explanation and demo content provided by the instructor

[1303] Users can attend classes and listen to explanations to deepen their understanding of the new savings system.

[1304] Output: User understanding and interest

[1305] Step 9: Gather feedback

[1306] server:

[1307] Input: Feedback form submitted after class

[1308] The server sends feedback forms to participants and analyzes the collected data.

[1309] Output: Analyzed feedback data

[1310] Step 10: Tracking

[1311] server:

[1312] Input: Usage data of services explained in the classroom

[1313] The server continuously tracks the usage of the services explained in the classroom and records it in a database.

[1314] Output: Updated database usage data

[1315] By taking specific actions at each step, the system can efficiently identify users' interests and promote information and service use through targeted advertising and classes.

[1316] (Application example 1)

[1317] 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."

[1318] The challenge is to efficiently identify users who are interested in specific products or services in physical stores, promptly notify them of campaigns or events, and automate the entire process from registration to the actual event management and feedback collection.Flaws in such systems can impair the timeliness and accuracy of information provided to users, and effective feedback collection and utilization is necessary to improve event participant satisfaction and promote service usage.

[1319] 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.

[1320] In this invention, the server includes means for identifying user interests using a generation AI, means for delivering online advertisements, means for accepting participation applications, means for notifying event participants, means for providing information to event participants, means for collecting feedback from event participants, means for tracking the usage of services explained at the event, means for managing applications for events held at physical stores, and means for notifying smartphones of event information held at physical stores. This makes it possible to accurately grasp user interests, provide campaign and event information at appropriate times, and consistently manage the process from participation applications to feedback collection.

[1321] "Generative AI" is a type of artificial intelligence that analyzes data and automatically generates insights based on specific requirements and conditions.

[1322] "Means for identifying user interests" refers to technology that analyzes collected data to extract user interests in specific products or services.

[1323] "Means for delivering online advertising" refers to a mechanism for delivering advertising content to specific users via the Internet.

[1324] "Means for accepting participation applications" refers to a function for accepting and managing applications from users to participate in events and campaigns.

[1325] "Means for notifying users of upcoming events" is a function that notifies users of upcoming events based on the set date, time, and content.

[1326] "Means for providing information to event participants" refers to a system for providing participants with the information they need before, during, and after the event.

[1327] "Means for collecting feedback from event participants" refers to techniques for collecting opinions and impressions from participants after the event and analyzing them as data.

[1328] "Means for tracking usage of services explained at the event" refers to a system for monitoring and recording subsequent usage of products or services introduced at the event.

[1329] The "means for managing applications for events held in physical stores" refers to a technology that comprehensively manages users' applications to participate in events held in physical stores.

[1330] "Means of notifying smartphones of event information held at physical stores" is a system that notifies users' smartphones of information about events scheduled at physical stores.

[1331] The system of the present invention uses a generative AI to identify users who are interested in a specific product and provide those users with campaign and event notifications for physical stores. Specifically, it includes the following processing steps.

[1332] User Specific

[1333] The server collects website access logs and social media posts and stores them in a database. The software used here includes a data collection API and a generative AI model (e.g., OpenAI GPT-3). The generative AI analyzes the collected data and creates a list of users who are interested in a particular product or service.

[1334] Campaign Notifications

[1335] The server sets up an online advertising campaign based on the user list identified by the generation AI. This setting includes the ad content, target audience, and period. Campaign information is then sent to the user's smartphone. The hardware used includes the server and the user's smartphone, and the software includes an email sending API (e.g., SendGrid) and a notification API.

[1336] Event participation application

[1337] The device (user's smartphone) displays details of the notified campaign or event and allows the user to apply directly. The server receives the application data and stores it in a database. The software used includes a web server and a database management system.

[1338] Event Notification

[1339] When the event date approaches, the server will send a reminder message to help users remember the event. The software includes a notification API so that reminder notifications are sent to users' smartphones.

[1340] Feedback collection

[1341] After the event, the server sends a feedback form to users, analyzes the collected data, and identifies areas for improvement. This will help improve the quality of the next event. The software used includes a feedback form API and a data analysis tool.

[1342] Specific user examples

[1343] For example, when User A is searching for savings-related products, he or she is included in a target list by the generation AI. Based on this list, a campaign notification for a new savings scheme is sent to User A's smartphone. User A clicks on the notification to check the details of the event and apply to participate. Before the event, the server sends User A a reminder message, and after the event ends, a feedback form is sent. Through this series of processes, User A can efficiently obtain information and use new services through the event.

[1344] Prompt Sentence Examples

[1345] "We use generative AI to automate the process of identifying users who are interested in a particular product and sending them promotional notifications."

[1346] "We want to develop an application that allows users to register for seminars held in physical stores and collect feedback on campaigns that interest them."

[1347] Through this process, this application example builds a system that identifies users interested in a new savings scheme and encourages them to participate in events at physical stores.

[1348] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1349] Step 1:

[1350] The server uses a data collection API to obtain website access logs and social media posts and stores them in a database. The input is log data and post data from each data source, which is processed and stored in the database. The output is raw data stored in the database. Specifically, it executes API requests, collects JSON-formatted data, analyzes it, and inserts it into the database.

[1351] Step 2:

[1352] The server analyzes the collected data using a generative AI model (e.g., OpenAI GPT-3) to create a list of users who are interested in a particular product or service. The input is raw data stored in a database, which is analyzed by the generative AI model. The output is a list of users who are determined to be interested. Specifically, the server creates prompts for the generative AI model and performs an analysis process to identify user interests based on the prompts.

[1353] Step 3:

[1354] The server sets up an online advertising campaign based on the user list identified by the generation AI. The input is the identified user list and campaign content, and based on this, it generates ad delivery settings. The output is setting information for the online ad delivery platform. Specifically, it sets parameters such as ad content, delivery target, and period, and sends the data to the delivery platform via API.

[1355] Step 4:

[1356] The device (user's smartphone) receives the campaign notification sent from the server and displays it to the user. The input is the campaign notification data, which is displayed through the smartphone's notification function. The output is the notification display to the user. Specifically, the notification message is constructed using the notification API and displayed as a pop-up on the smartphone screen.

[1357] Step 5:

[1358] The user checks the details of the notified campaign or event on their smartphone and applies to participate. The input is the notification message and a link to the details page, which the user clicks to access the application form. The output is the data entered into the application form. Specifically, the user clicks the link, enters the required information into the web form, and submits it.

[1359] Step 6:

[1360] The server receives event participation application data from users and stores it in a database. The input is the application data sent from the web form, which is saved in the database. The output is the saved application data. Specifically, it receives the form data and inserts it into the database.

[1361] Step 7:

[1362] As the event date approaches, the server sends a reminder message. The input is the event date and time and a list of users, and the server generates a reminder message based on this. The output is a reminder message sent to the user's smartphone. Specifically, the server uses a notification API to send a message based on the reminder settings.

[1363] Step 8:

[1364] After the event ends, the server sends a feedback form to users and analyzes the collected data. The input is the event participant list and the feedback form, and feedback is collected based on this. The output is the feedback data and its analysis results. Specifically, the form link is sent using the feedback form API, and the collected data is evaluated using an analysis tool.

[1365] 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.

[1366] This invention provides a method for specifically implementing a system that uses generative AI and an emotion engine to identify users interested in a new savings program and announces the opening of classes through online advertising. Each element and its specific operation are described below.

[1367] User identification with generative AI and emotion engine

[1368] server:

[1369] User data is collected from various data sources (website access logs, social media posts, user text input, etc.) and stored in a database.

[1370] The generative AI analyzes the collected data, analyzes user interests and behavioral patterns, and based on the analysis results, creates a list of users who are interested in the new savings system.

[1371] The emotion engine uses a webcam and microphone to analyze emotions from the user's facial expressions and voice, and also recognizes emotions from the user's text input.

[1372] Delivery and dynamic adjustment of online advertisements

[1373] server:

[1374] Set up a targeted advertising campaign: define what ads to advertise, who to advertise to, and for how long.

[1375] Based on the analysis results of the generative AI and emotion engine, the content of online advertisements is dynamically adjusted and banner advertisements are delivered.

[1376] Device:

[1377] As users navigate the internet, they are shown tailored banner ads, whose timing and location change dynamically based on targeting lists and sentiment analysis.

[1378] When a user clicks on the banner ad, they are taken to a page detailing the new savings program.

[1379] Application acceptance and notification

[1380] server:

[1381] The class details page contains an application form, and the application data entered by the user is received and stored in a database.

[1382] After confirming your application, we will notify you of the date, time and location of the class via email or message.

[1383] Device:

[1384] The user enters the required information on the details page and applies to participate.

[1385] Receive notification emails and messages and prepare to join the class.

[1386] Classroom Management and Emotional Response

[1387] server:

[1388] It manages presentation materials and demonstration data used in the classroom and provides them to the instructor's device.

[1389] Provide the instructor with a list of participants and assist with classroom management.

[1390] Device (instructor's smartphone):

[1391] The lecturer uses a smartphone to display and explain a presentation about a new savings system, and the speaker's smartphone dynamically adjusts the content and tone of the presentation based on the user's emotional data obtained from the emotion engine.

[1392] Demonstrations will be held on smartphones, fixed-line services, and point management, and the benefits of using them will be explained.

[1393] user:

[1394] Participate in the class, listen to the instructor's explanations and demonstrations, and deepen your understanding of the new savings system. You will also learn about smartphones, fixed-line services, and point management.

[1395] Feedback collection and tracking

[1396] server:

[1397] After the class, a feedback form is sent to participants via email or message to collect their ratings and comments.

[1398] The collected feedback data will be analyzed to improve classroom content and services provided.

[1399] The usage status of services (smartphone, fixed line, point management, etc.) that participants have actually started using will be tracked and stored in a database. The usage data for each service will be visualized and used in corporate strategy planning.

[1400] To give a specific example, while User A is searching for information on the Internet, he or she is included in a target list by the generative AI and emotion engine. Based on this list, a dynamically adjusted banner ad is displayed on the web page that User A is viewing. When User A clicks on the ad, he or she is taken to the class details page where he or she can apply to participate. After the application is accepted, a notification email is sent to User A's device. On the day of the class, the instructor will give an explanation, adjusting the presentation based on the user's emotion data. After the class ends, User A fills in a feedback form, and their subsequent service usage is tracked.

[1401] In this way, the system, which utilizes generative AI and an emotion engine, can effectively identify users and provide them with information through classrooms, thereby promoting the use of related services and expanding the customer base.

[1402] The processing flow will be explained below.

[1403] Step 1:

[1404] server:

[1405] User data is collected from various data sources (website access logs, social media posts, user text input, etc.) and stored in a database. The collected data includes user browsing history, click history, and post content.

[1406] The generative AI analyzes the collected data to analyze user interests and behavioral patterns, and based on the analysis results, creates a list of users who are interested in the new savings system.

[1407] Step 2:

[1408] server:

[1409] The emotion engine is initialized and collects the user's facial and voice data via the webcam and microphone. The emotion engine analyzes this data in real time to determine the user's current emotional state.

[1410] Analyzes emotional data from user text input, extracting emotions and tones from text messages and other inputs.

[1411] Step 3:

[1412] server:

[1413] Set up targeted advertising campaigns, defining the content, audience, and duration of ads, using user lists identified by generative AI and sentiment analysis results from the sentiment engine.

[1414] Based on data from the emotion engine, the content of online ads is dynamically adjusted to best suit the user's emotional state before being delivered.

[1415] Step 4:

[1416] Device:

[1417] As users navigate the internet and browse websites and applications, they are shown tailored banner ads, whose timing and location change dynamically based on targeting lists and sentiment analysis.

[1418] When a user clicks on the banner ad, they are taken to a page detailing the new savings program.

[1419] Step 5:

[1420] User:

[1421] Access the class details page and enter the required information (name, contact information, desired date and time of participation, etc.) in the provided participation application form and submit it.

[1422] Once you have completed your registration, you will automatically receive a confirmation message.

[1423] Step 6:

[1424] server:

[1425] Receives application data and stores it in a database. Generates and sends notification emails and messages to users so that they can confirm their application details.

[1426] Send notifications to users with details about class times, dates, and locations.

[1427] Step 7:

[1428] Device:

[1429] Download and prepare classroom presentation materials and demo data onto the instructor's smartphone.

[1430] Users who receive the notification email or message can prepare to join the class.

[1431] Step 8:

[1432] server:

[1433] We will provide the instructor with a list of participants on the day of the class to help ensure the class runs smoothly. This list will also be used to support smooth reception at the entrance to the venue.

[1434] Step 9:

[1435] Device (instructor's smartphone):

[1436] The lecturer uses a smartphone to display and explain in detail a presentation about a new savings scheme, and the speaker's smartphone dynamically adjusts the content and tone of the presentation based on the user's emotional data obtained from the emotion engine.

[1437] Step 10:

[1438] Device (instructor's smartphone):

[1439] Demonstrations will be conducted on smartphones, fixed-line services, and point management, and the benefits of using them will be explained in detail. An emotion engine will be used to adjust the progress of the demonstration based on the emotional state of the participants.

[1440] Step 11:

[1441] User:

[1442] Participate in the class, understand the instructor's explanations and demonstrations, and learn about the structure and benefits of the new savings system. You will also learn in detail about the proposed smartphone and fixed-line services, and point management.

[1443] Step 12:

[1444] server:

[1445] After the class, participants are sent a feedback form via email or message to collect their ratings and comments. The feedback data is then stored in a database for later use in improving the service.

[1446] The usage of the services explained in the class will be tracked in real time and recorded in a database. Usage trends for each service will be analyzed and used to plan future strategies.

[1447] To give a specific example, while User A is searching for information on the Internet, he or she is included in a target list by the generative AI and emotion engine. Based on this list, a dynamically adjusted banner ad is displayed on the web page that User A is viewing. When User A clicks on the ad, he or she is taken to the class details page where he or she can apply to participate. After the application is accepted, a notification email is sent to User A's device. On the day of the class, the instructor will give an explanation, adjusting the presentation based on the user's emotion data. After the class ends, User A fills in a feedback form, and their subsequent service usage is tracked.

[1448] In this way, the system, which utilizes generative AI and an emotion engine, can effectively identify users and provide them with information through classrooms, thereby promoting the use of related services and expanding the customer base.

[1449] Example 2

[1450] 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."

[1451] Conventional online advertising systems only deliver ads based on users' interests, but are unable to deliver ads that take into account users' emotions. Furthermore, there was a lack of a mechanism for adequately collecting and analyzing feedback on how users who received ads behaved after attending classes. Furthermore, it was difficult to track the usage of services explained in classes, which meant that the data could not be fully utilized to improve services or develop marketing strategies.

[1452] 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.

[1453] In this invention, the server includes a means for identifying user interests using generative AI, a means for analyzing user emotions using an emotion engine, and a means for dynamically adjusting and delivering online advertisements using the analysis results. This enables the delivery of highly targeted advertisements based on the user's interests and emotions. The server also includes a means for accepting participation applications, a means for notifying class participants, a means for providing information to class participants, a means for collecting feedback from class participants, and a means for tracking the usage of services explained in the classes. This facilitates the collection and analysis of feedback and the tracking of service usage, which can be used to improve services and develop strategies.

[1454] "Generative AI" is a system that uses artificial intelligence technology to identify users' interests and concerns.

[1455] An "emotion engine" is a system for analyzing emotions from data such as a user's facial expressions, voice, and text input.

[1456] "Online advertising" refers to advertising banners and links distributed over the Internet, which are a means of providing information and promotions to users.

[1457] "Dynamic adjustment" refers to changing the content and timing of advertising in real time based on the analysis results of the generative AI and emotion engine.

[1458] "Registration" is the process by which a user indicates their intention to attend a class or event and provides the necessary information.

[1459] "Notifications" are a way to communicate important information to users, such as the date, time, and location of class events.

[1460] "Feedback" refers to information collected from users, such as ratings and comments, that is used to improve our services and events.

[1461] "Tracking" is the process of monitoring and collecting data on the use of the services described in the classroom.

[1462] This invention is a system that utilizes generative AI and an emotion engine to analyze users' interests and emotions, deliver appropriate online advertisements, provide class information, collect feedback, and track service usage. The system is composed of three main entities: a server, a device, and the user.

[1463] User Specific

[1464] The server collects user data from various data sources (e.g., website access logs, social media posts, user text input) and stores it in a database. The server uses generative AI to analyze the collected data and identify the user's interests. This analysis uses natural language processing (NLP) technology. The emotion engine analyzes emotions from the user's facial expressions and voice data obtained from the webcam and microphone, as well as text input.

[1465] As a specific example, a user's search history for keywords related to "new savings systems" is collected, and based on the collected data, the generation AI determines that the user is interested in a new financial product.

[1466] Delivery and dynamic adjustment of online advertisements

[1467] The server sets up a targeted advertising campaign and defines the ad content, distribution target, and distribution period. Based on the analysis results of the generative AI and emotion engine, the ad content is dynamically adjusted and delivered to users as banner ads on the Internet. The adjusted banner ad is displayed on the user's device (PC or smartphone). When the user clicks on the banner ad, they are taken to a class details page where they can apply to participate.

[1468] As a concrete example, when user A is browsing a news site, a dynamically adjusted banner ad appears, and when he clicks on the ad, he is taken to a detailed page about a class on savings programs.

[1469] Application acceptance and notification

[1470] The server places a participation application form on the class details page and stores the participation application data entered by the user in a database. The server then notifies the user of the class date, time, and location via email or message. The user receives the notification on their device and prepares to participate in the class.

[1471] As a specific example, a user accesses a class details page via a banner ad, applies to participate from there, and receives a notification email.

[1472] Classroom Management and Emotional Response

[1473] The server manages presentation materials and demo data and provides them to the instructor's device (e.g., a smartphone). In the classroom, the instructor uses their smartphone to give a presentation, dynamically adjusting the content and tone based on the user's emotional data obtained from the emotion engine. Participants attend the class and learn about the new savings system.

[1474] As a concrete example, the instructor can use a smartphone in the classroom to check emotional data in real time and adjust the content of the explanation as he or she goes along.

[1475] Feedback collection and tracking

[1476] After the class ends, the server sends a feedback form to the participants and collects their ratings and comments. This data is analyzed to improve the class content and services. The server also tracks the usage of services that participants have actually started using and stores the data in a database. This data can be used to develop corporate strategies.

[1477] For example, after the class ends, users are sent a feedback form, and the results are reflected in improving the content of the next class.

[1478] Prompt Sentence Examples

[1479] "Describe a system that detects user interests and delivers targeted advertising based on the data analyzed by an emotion engine."

[1480] This invention enables highly targeted advertising based on user interests and emotions, helping to promote new savings programs more effectively through classrooms, while collecting feedback and tracking usage allows for continuous improvement of the service.

[1481] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1482] Step 1:

[1483] Data collection

[1484] server:

[1485] The server collects user data from data sources such as website access logs, social media posts, and user text input, and stores it in a database. Various data sources are used as input, and the output is formatted user data. Specifically, the server calls the data source API, retrieves JSON-formatted data, and stores it in the database.

[1486] Step 2:

[1487] Interest identification using generative AI

[1488] server:

[1489] The server inputs the collected user data into the generation AI to identify the user's interests. In this case, the generation AI uses natural language processing (NLP) technology. The input is user data, and the output is the identified user interest data. Specifically, the generation AI model feeds user data and classifies the user's interests by comparing it with the educational database.

[1490] Step 3:

[1491] Emotion analysis

[1492] server:

[1493] The server uses an emotion engine to analyze emotions from the user's facial expressions, voice, and text input obtained from the webcam and microphone. The input is real-time data, and the output is analyzed emotion data. Specifically, the webcam footage is analyzed frame by frame, the voice data is subjected to phonetic pattern analysis, and emotion keywords are extracted from the text.

[1494] Step 4:

[1495] Ad delivery settings and adjustments

[1496] server:

[1497] The server sets up targeted advertising campaigns and dynamically adjusts ad content based on the analysis results of the generative AI and emotion engine. The input is interest data and emotion data, and the output is adjusted ad data. Specifically, it inserts messages and images into ad templates that match the user's interests and emotions.

[1498] Step 5:

[1499] Advertisement display

[1500] Device:

[1501] The tailored banner ad is displayed on the user's device (PC or smartphone). The input is the tailored ad data, and the output is the displayed ad. Specifically, when the user browses a web page, the dynamically tailored banner ad is rendered in the ad display area.

[1502] Step 6:

[1503] Participation application acceptance

[1504] server:

[1505] The server places an application form on the class details page, receives the application data entered by the user, and stores it in a database. The input is the user's application data, and the output is the stored application data. Specifically, the server receives input from the user in an HTML form and saves it in a database on the backend.

[1506] Step 7:

[1507] Send notifications

[1508] server:

[1509] After the server confirms the participation application, it notifies the user of the class date, time, and location via email or message. The input is the participation confirmation data, and the output is the notification email or message sent. Specifically, it uses an email sending API to send individual notification emails to participants.

[1510] Step 8:

[1511] Presentation materials provided

[1512] server:

[1513] The server manages the presentation materials and demo data used in the classroom and provides them to the instructor's terminal. The input is the presentation materials and demo data, and the output is the materials provided to the instructor's terminal. Specifically, the server makes the materials available for download from a cloud storage service and sends a link to the instructor's terminal.

[1514] Step 9:

[1515] Classroom Management and Emotional Response

[1516] Device (instructor's smartphone):

[1517] The lecturer uses a device to give a presentation and dynamically adjusts the content and tone based on data from the emotion engine. The input is emotion data, and the output is an adjusted presentation. Specifically, the emotion data is received in real time and the content and tone of the slides are changed accordingly.

[1518] Step 10:

[1519] Feedback collection

[1520] server:

[1521] After the class ends, the server sends a feedback form to the participants and collects their ratings and comments. The input is the feedback data, and the output is the collected feedback. Specifically, a form submission API is used to send a link to the participants, and their responses are saved in a database.

[1522] Step 11:

[1523] Usage Tracking

[1524] server:

[1525] The server tracks the status of services actually used by class participants and stores the data in a database. The input is usage data, and the output is the stored tracking data. Specifically, usage logs are collected periodically and stored in a database for analysis.

[1526] Through these steps, the system can effectively deliver advertisements according to users' interests and emotions, manage classrooms, collect feedback, and track usage.

[1527] (Application example 2)

[1528] 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."

[1529] Today's consumers are bombarded with a vast amount of information, making it difficult to find information and products that are relevant to them. Furthermore, to maximize the effectiveness of online advertisements and campaigns, targeting based on individual users' emotions and interests is necessary. Furthermore, virtual stores require mechanisms that allow users to enjoy individually customized shopping experiences. Given this background, there is a need for systems that can provide advertisements and information based on users' interests and emotions, and measure and improve their effectiveness.

[1530] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1531] In this invention, the server includes means for identifying user interests using generative AI, means for delivering online advertisements, means for accepting participation applications, means for notifying class schedules, means for providing information to class participants, means for collecting feedback from class participants, means for tracking the usage of services explained in the class, means for using an emotion engine that analyzes the user's emotional state based on their facial expressions and voice, and means for providing a customized shopping experience through smart glasses in a virtual store. This makes it possible to provide advertisements and information optimized for each individual user and measure and improve their effectiveness in real time.

[1532] "Generative AI" is a technology that uses artificial intelligence to automatically analyze and identify users' interests and concerns.

[1533] "Online advertising" refers to advertising content delivered to users via the Internet.

[1534] "Registration" is the process by which a user indicates their intention to participate in a particular event or class and completes the necessary procedures.

[1535] "Classroom Notification" is a means of communicating information to users about details such as the date and location of an event or class.

[1536] "Feedback" refers to reactions and comments such as evaluations and opinions obtained from users.

[1537] "Tracking" means the continuous tracking and recording of the usage of a particular service or product.

[1538] The "emotion engine" is a technology that analyzes the user's facial expressions and voice to recognize and evaluate their emotional state.

[1539] A "virtual store" is not an actual physical store, but a virtual store that operates online or in the digital space.

[1540] "Smart glasses" are advanced eyeglass-type devices equipped with a display, camera, sensors, etc., and capable of providing information to users.

[1541] "Shopping experience" is a general term for the experiences and services that consumers receive in the process of selecting and purchasing a product.

[1542] This invention is a system that utilizes generative AI and an emotion engine to provide users with optimal advertisements and information, thereby improving their shopping experience in virtual stores. A specific embodiment of the present invention is described below.

[1543] System Configuration

[1544] This system mainly consists of three elements: a server, a terminal (smart glasses, smartphone, etc.), and a user. The role and operation of each element are explained below.

[1545] server

[1546] The server consists of multiple components, including a generative AI model, an emotion engine, and a database. Specifically, it uses the following software and hardware:

[1547] Hardware and Software

[1548] Hardware: High-performance server

[1549] Software: Python, TensorFlow, OpenCV

[1550] Data collection

[1551] The server collects user data from each data source (website access logs, social media posts, user text input, etc.) and stores it in a database.

[1552] Analysis by generative AI

[1553] The generative AI model analyzes the collected data and analyzes user interests and behavioral patterns. This generates a list of users who are interested in the new savings scheme. An example prompt is shown below:

[1554] "We are collecting text information to identify users who are interested in investing and saving. Analyze their interests and create a list of users who are most likely to be interested in a new savings scheme."

[1555] Analysis by emotion engine

[1556] The emotion engine uses a webcam and microphone to analyze emotions from the user's facial expressions and voice. The emotion engine also recognizes emotions from the user's text input.

[1557] Ad delivery and dynamic adjustment

[1558] The server sets up targeted advertising campaigns, defining the ad content, target audience, and distribution period. Based on the analysis results of the generative AI and emotion engine, the content of online ads is dynamically adjusted and banner ads are distributed.

[1559] Terminal

[1560] Smart Glasses

[1561] Users use smart glasses to shop in virtual stores. The smart glasses have the following features:

[1562] Advertisement display: Displaying customized banner ads at the right time based on the user's emotional state.

[1563] Providing detailed information: Clicking on an ad displays detailed information about the product or event and takes you to a page to register for participation.

[1564] Smartphone

[1565] Smartphones will be used for classroom presentations and registration.

[1566] Presentation display: The instructor uses a smartphone to display a presentation about a new savings scheme.

[1567] Dynamic adjustment based on emotional data: The instructor's smartphone dynamically adjusts the content and tone of the presentation based on the user's emotional data obtained from the emotion engine.

[1568] user

[1569] The user uses this system to perform the following process:

[1570] Viewing ads and signing up: When users are browsing the internet, they will be shown dynamically adjusted banner ads that, when clicked, will take them to a class details page where they can sign up.

[1571] Providing feedback: After the class, participants fill out a feedback form and their subsequent use of the service is tracked.

[1572] In this way, the present invention can provide users with the most appropriate advertisements and information, allowing them to customize their shopping experience in a virtual store.

[1573] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1574] Step 1:

[1575] The server collects user data from data sources such as website access logs, social media posts, and user text input, and stores it in a database.

[1576] Input: Website access logs, social media posts, user text input

[1577] Data processing: Collected data is centrally managed and stored in a database

[1578] Output: A cleaned up user database

[1579] Step 2:

[1580] The server uses a generative AI model to analyze the collected data and analyze users' interests and behavioral patterns.

[1581] Input: User Database

[1582] Data Computation: Using generative AI models to calculate interest scores and identify target users

[1583] Output: List of highly interested users

[1584] Specific operation: The generative AI performs analysis based on the prompt: "We are collecting text information to identify users who are interested in investing and saving. Analyze user interests and create a list of users who are likely to be most interested in the new savings system."

[1585] Step 3:

[1586] The server uses an emotion engine to analyze the user's emotional state based on facial expressions, voice, and text input obtained from the webcam and microphone.

[1587] Input: Webcam video, audio data, text input

[1588] Data Computation: Emotion Analysis Using an Emotion Engine

[1589] Output: User's emotional state data

[1590] Specific operation: Obtain data in real time from a webcam and microphone to estimate emotional state.

[1591] Step 4:

[1592] Based on the analysis results of the generative AI and emotion engine, the server sets up advertising campaigns, generates and adjusts targeted ads, and delivers online ads.

[1593] Input: User list, emotional state data

[1594] Data processing: Ad content is customized for each user and displayed at the appropriate time

[1595] Output: Tailored banner ad

[1596] Specific operation: The advertising distribution system displays the most appropriate advertisement for the page viewed by the target user.

[1597] Step 5:

[1598] While using the Internet, users view tailored banner ads and click on them to be taken to a details page where they can apply to participate.

[1599] Input: Tailored banner ads

[1600] Output: Display of classroom details page, participation application data

[1601] Specific actions: The user clicks on the ad and fills in the required information on the application form.

[1602] Step 6:

[1603] The server places a participation application form on the classroom details page, receives the participation application data entered by the user, and stores it in a database.

[1604] Input: Participation application data

[1605] Data processing: Save the application data in a database and check for duplications and errors.

[1606] Output: Organized participant list

[1607] Step 7:

[1608] The server confirms the participation application and notifies the user of the date, time and location of the class via email or message.

[1609] Input: Participant list

[1610] Output: Notification email, message

[1611] Specific action: Execute a process to automatically send notifications to participants.

[1612] Step 8:

[1613] The device (the instructor's smartphone) displays presentation materials during the class and dynamically adjusts the content and tone based on data from the emotion engine.

[1614] Input: Presentation materials, participants' emotional state data

[1615] Data processing: Adjusting presentation content and changing tone

[1616] Output: Well-tuned presentation

[1617] Specific behavior: Check emotional state in real time and optimize content.

[1618] Step 9:

[1619] Users will attend classes, follow lectures and demonstrations from instructors, and gain a deeper understanding of the new savings system.

[1620] Input: Instructor presentation

[1621] Output: Improved user understanding

[1622] Specific actions: Listen to the instructor's explanation and watch the demonstration to learn.

[1623] Step 10:

[1624] After the class, the server sends a feedback form to participants and collects their evaluations and comments.

[1625] Input: Feedback Form

[1626] Data processing: Analysis of collected feedback data

[1627] Output: Feedback data analysis results

[1628] Specific actions: Automatically send feedback forms to participants and analyze the collected data.

[1629] This makes it possible for the present invention to provide users with optimal advertisements and information, improving their shopping experience in virtual stores.

[1630] 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.

[1631] 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.

[1632] 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.

[1633] [Fourth embodiment]

[1634] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1635] 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.

[1636] 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).

[1637] 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.

[1638] 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.

[1639] 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).

[1640] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1641] 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.

[1642] 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.

[1643] 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.

[1644] 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.

[1645] 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.

[1646] 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."

[1647] The system of the present invention uses generative AI to identify users interested in a new savings program and automates the process of announcing the class via online advertising. The system is configured as follows:

[1648] User identification using generative AI

[1649] server:

[1650] User data is collected from various data sources (website access logs, social media posts, etc.) and stored in a database.

[1651] Generative AI is used to analyze the collected data and create a list of users who are interested in the new savings scheme.

[1652] Delivering online advertisements

[1653] server:

[1654] Based on the user list identified by the AI ​​generation, online advertising campaign settings are made, including the ad content, target audience, and period.

[1655] Based on the floor settings, banner ads will be delivered to platforms such as Yahoo and PayPay.

[1656] Device:

[1657] Allows internet users to see targeted advertising in their browsers and applications.

[1658] When a user clicks on the ad, they are taken to a page detailing the class on the new savings program.

[1659] Application acceptance and notification

[1660] server:

[1661] The class details page contains an application form, and the application data entered by the user is received and stored in a database.

[1662] After confirming your application, we will notify you of the date, time and location of the class via email or message.

[1663] Device:

[1664] The user enters the required information on the details page and applies to participate.

[1665] Receive notification emails and messages and prepare to join the class.

[1666] Classes held

[1667] server:

[1668] It manages presentation materials and demonstration data used in the classroom and provides them to the instructor's device.

[1669] Provide the instructor with a list of participants and assist with classroom management.

[1670] Device (instructor's smartphone):

[1671] The instructor will use a smartphone to display a presentation and provide a detailed explanation of the new savings system.

[1672] Demonstrations will be held on smartphones, fixed services, and point management using PayPay.

[1673] user:

[1674] Attend classes and listen to the instructor's explanations to deepen your understanding of the new savings system.

[1675] The proposed services will be reviewed.

[1676] Feedback collection and tracking

[1677] server:

[1678] After the class, participants will be sent a feedback form, and the collected data will be analyzed to identify areas for improvement.

[1679] Track and record usage of services discussed in the classroom in a database.

[1680] To give a specific example, while User A is searching for information on the internet, he or she is included in a target list by the generation AI. Based on this list, a banner ad for a new savings system is displayed on the web page that User A is viewing. When User A clicks on the ad, he or she is taken to the class details page where he or she can apply to participate. When the application to participate is accepted, a notification email is sent to User A's device. On the day of the class, the instructor displays materials and gives an explanation. After the class, User A fills out a feedback form, and subsequent service usage is tracked.

[1681] In this way, systems that utilize generative AI can efficiently identify users and provide information through classrooms, thereby promoting the use of related services and expanding the customer base.

[1682] The processing flow will be explained below.

[1683] Step 1:

[1684] server:

[1685] User data is collected from various data sources (website access logs, social media posts, etc.) and stored in a database, including user browsing history, click history, and post content.

[1686] The collected data is input into a generative AI to analyze user interests and behavioral patterns.

[1687] Step 2:

[1688] server:

[1689] Based on the analysis results of the Generator AI, a list of users who are interested in the new savings scheme is created. The Generator AI uses a specific algorithm to determine the level of interest and similarity of behavioral patterns.

[1690] Save the listed user information in the database.

[1691] Step 3:

[1692] server:

[1693] Set up a targeted advertising campaign: define what ads to advertise, who to advertise to, and for how long.

[1694] Online advertisements will begin to be delivered based on the specific user list obtained from the generated AI.

[1695] Step 4:

[1696] Device:

[1697] While users are browsing the internet, they are shown banner ads, which are dynamically timed and placed based on a targeting list.

[1698] When a user clicks on the banner ad, they are taken to a page detailing the new savings program.

[1699] Step 5:

[1700] User:

[1701] Access the class details page and enter the required information (name, contact information, desired date and time of participation, etc.) in the provided participation application form and submit it.

[1702] Once submitted, your application will be complete.

[1703] Step 6:

[1704] server:

[1705] Receives the registration data and stores it in a database. Generates an email or message to notify the user that their registration is complete.

[1706] It reviews each application and sends users notifications with details of the class date, time and location.

[1707] Step 7:

[1708] Device:

[1709] Classroom presentation materials and demo data are downloaded to the instructor's smartphone, and preparations are complete.

[1710] Users who receive the notification email or message can prepare to join the class.

[1711] Step 8:

[1712] server:

[1713] We will provide the instructor with a list of participants on the day of the class to help ensure the class runs smoothly.

[1714] Step 9:

[1715] Device (instructor's smartphone):

[1716] The instructor uses a smartphone to display a presentation about the new savings system and give an explanation.

[1717] We will conduct demonstrations on smartphones, fixed services, and point management with PayPay, and explain the benefits of using them.

[1718] Step 10:

[1719] User:

[1720] Participants will deepen their knowledge of the new savings system through classroom explanations and demonstrations, as well as learn about smartphones, fixed-line services, and how to use PayPay points.

[1721] Step 11:

[1722] server:

[1723] After the class, a feedback form is sent to participants via email or message to collect their ratings and comments.

[1724] The collected feedback data will be analyzed to improve classroom content and services provided.

[1725] Step 12:

[1726] server:

[1727] The usage status of services (smartphone, fixed line, point management, etc.) that participants have actually started using will be tracked and stored in a database. The usage data for each service will be visualized and used in corporate strategy planning.

[1728] In this way, by performing specific actions at each processing step, it is possible to utilize generative AI to achieve efficient user identification and classroom management, thereby promoting the use of related services and expanding the customer base.

[1729] Example 1

[1730] 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."

[1731] Existing online advertising systems lack the means to identify user interests and deliver targeted advertisements effectively. They also lack the means to smoothly guide target users through the process of joining a class and track service usage. As a result, it is difficult to promote the use of related services and expand customer base.

[1732] 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.

[1733] In this invention, the server includes means for identifying user interests using generation AI, means for delivering online advertisements, means for accepting participation applications, means for notifying class schedules, means for providing information to class participants, means for collecting feedback from class participants, means for tracking usage of services explained in classes, means for collecting user data and storing it in a database, and means for setting up advertising campaigns on an advertising platform. This effectively identifies user interests and delivers targeted advertisements, promoting the use of related services and expanding customer base. It also allows users to smoothly participate in the class process and efficiently track feedback and usage.

[1734] "Generative AI" is an artificial intelligence technology used to analyze collected data to identify user interests and concerns.

[1735] "Online advertising" refers to advertising delivered via the Internet and displayed in the browsers and applications used by users.

[1736] "Application" is the process by which a user expresses their intention to participate in a particular event or class by filling out and submitting the required information in the provided form.

[1737] "Class Notification" means an email or message sent to a user to inform them of the date, time, and location of a class.

[1738] "Information provision" refers to the act of providing detailed information about new savings programs to class participants through presentations and demonstrations.

[1739] "Feedback collection" is a procedure for collecting evaluations and opinions on the content of the class from class participants.

[1740] "Tracking" refers to the act of continuously tracking the usage of the services explained in the classroom and recording it in a database.

[1741] "User Data" refers to information about a specific user, such as website access logs or social media posts.

[1742] A "database" is an information system for storing and efficiently managing collected user data and analysis results.

[1743] An "advertising campaign" is an advertising distribution plan established based on a specific purpose, and includes advertising content, distribution target, period, etc.

[1744] An "advertising platform" refers to an internet infrastructure that provides systems and services for delivering online advertisements.

[1745] The system of the present invention uses generative AI to identify users interested in a new savings program and automates the process of announcing the class via online advertising. Specific embodiments are described below.

[1746] User identification using generative AI

[1747] server:

[1748] The server collects user data from data sources such as website access logs and social media posts and stores it in a database such as PostgreSQL.

[1749] Analyze the collected data using a generative AI model (e.g., GPT-3 or BERT) to identify users who are interested in the new savings scheme. This process uses the prompt "Analyze website access logs and social media posting data to identify users who are interested in the new savings scheme."

[1750] Generate a list of identified users and store it in Amazon S3.

[1751] For example, the server collects information such as when User A visits a page called "savings tips" or posts about "savings" on social media. Based on this information, the generation AI creates a list of User A as an interested user and stores it in Amazon S3.

[1752] Delivering online advertisements

[1753] server:

[1754] The server uses the identified user list to configure the advertising campaign, including specifying the ad content, target audience, and duration.

[1755] This setting is sent to advertising platforms (e.g., Yahoo or other internet services).

[1756] Device:

[1757] Internet users can view targeted advertisements in their browsers and applications.

[1758] When users click on the ad, they are taken to a page with more details about the new savings scheme.

[1759] As a concrete example, the server identifies User A, imports the information into Yahoo's advertising campaign management system, and sets the content and distribution period of a banner ad for a "new savings plan." When User A is browsing a Yahoo page, the ad is displayed. When User A clicks on the ad, the page transitions to a detailed page.

[1760] Application acceptance and notification

[1761] server:

[1762] Place a registration form on the class details page. Receive the data entered by the user and store it in a database.

[1763] After confirming your application, we will send you an email or message informing you of the date, time and location of the class.

[1764] Device:

[1765] Users enter the necessary information on the details page and apply to participate.

[1766] Receive notification emails and messages and prepare to join the class.

[1767] For example, when User A enters his / her name and email address into the form on the details page and submits it, the server stores this data in the database. When the application is accepted, a notification email is sent to User A.

[1768] Classes held

[1769] server:

[1770] It manages presentation materials and demonstration data used in the classroom and provides them to the instructor's device.

[1771] Manage participant lists and provide them to instructors to assist with classroom management.

[1772] Device (instructor's smartphone):

[1773] The lecturer will use a smartphone to display a presentation and explain the new savings system.

[1774] A demonstration will be conducted to show specific operation methods.

[1775] As a concrete example, the lecturer will project presentation materials onto a smartphone and explain to the participants. There will also be a demonstration of the specific operation of savings points via smartphones and other fixed services.

[1776] Feedback collection and tracking

[1777] server:

[1778] After the class, participants will be sent a feedback form and the collected data will be analyzed to identify areas for improvement.

[1779] Track and record the use of services discussed in the classroom in a database.

[1780] For example, after the class ends, the server sends a feedback form to User A asking, "How was the class?" and receives and analyzes the responses. It also continuously tracks User A's usage of the savings plan.

[1781] This allows the system, which utilizes generative AI, to effectively identify users and provide them with appropriate information through targeted advertising, thereby promoting the use of related services and expanding the customer base.

[1782] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1783] Step 1: Data collection

[1784] server:

[1785] Input: Website access logs, social media posting data

[1786] The server collects user data from these data sources, using web scraping and APIs to obtain log information and posted data.

[1787] After data acquisition, the collected data is stored in a PostgreSQL database.

[1788] Output: User data stored in the database

[1789] Step 2: Data analysis

[1790] server:

[1791] Input: User data stored in the database

[1792] The server uses a generative AI model (e.g., GPT-3 or BERT) to analyze the collected data based on the prompt.

[1793] Prompt: "Analyze website traffic logs and social media posting data to identify users interested in a new savings program."

[1794] Based on the analysis results, the server generates a list of users interested in the new savings system and stores it in Amazon S3.

[1795] Output: User list stored in Amazon S3

[1796] Step 3: Campaign Settings

[1797] server:

[1798] Input: A user list stored in Amazon S3

[1799] The server uses the user list to set up online advertising campaigns, for example determining the content, targeting, and duration of banner ads.

[1800] Send your settings to advertising platforms (Yahoo, other internet services).

[1801] Output: Campaign data set in the advertising platform

[1802] Step 4: Ad serving

[1803] server:

[1804] Input: Campaign data set in the advertising platform

[1805] The server uses an advertising platform to deliver online advertisements to targeted users.

[1806] Output: Ad banner displayed in the user's browser or app

[1807] Device:

[1808] Input: An ad banner displayed in a user's browser or app.

[1809] When users click on the ad, they are redirected to a page with more details about the new savings scheme.

[1810] Output: User navigates to the classroom details page

[1811] Step 5: Accepting your application

[1812] server:

[1813] Input: Application data entered by the user on the details page

[1814] The server receives the participation application data from the form placed on the classroom details page and stores it in a database.

[1815] Output: Application data stored in a database

[1816] Device:

[1817] Input: Information the user enters on the detail page (such as name, email address, etc.)

[1818] The user enters the required information into the application form and submits it.

[1819] Output: Data sent to the server

[1820] Step 6: Sending notifications

[1821] server:

[1822] Input: Participation application data stored in the database

[1823] The server will confirm the registration and send a notification email or message to the user with the date, time and location of the class.

[1824] Output: Notification emails and messages sent to users

[1825] Device:

[1826] Input: Notification emails and messages sent from the server

[1827] Users will receive notification emails and messages and prepare to join the class.

[1828] Output: Classroom participation preparation information

[1829] Step 7: Prepare for the class

[1830] server:

[1831] Input: Managed presentation and demo data

[1832] The server provides prepared materials and data to the instructor's device (such as a smartphone), and also manages the participant list and provides it to the instructor.

[1833] Output: Materials provided to the instructor and a list of participants

[1834] Step 8: Hold a class

[1835] Device (instructor's smartphone):

[1836] Input: Presentation materials and participant list provided by the server

[1837] The instructor will use a smartphone to display a presentation and explain the new savings system, and will provide a demonstration with concrete examples using the smartphone and other services.

[1838] Output: Explanations and demo content for classroom participants

[1839] user:

[1840] Input: Explanation and demo content provided by the instructor

[1841] Users can attend classes and listen to explanations to deepen their understanding of the new savings system.

[1842] Output: User understanding and interest

[1843] Step 9: Gather feedback

[1844] server:

[1845] Input: Feedback form submitted after class

[1846] The server sends feedback forms to participants and analyzes the collected data.

[1847] Output: Analyzed feedback data

[1848] Step 10: Tracking

[1849] server:

[1850] Input: Usage data of services explained in the classroom

[1851] The server continuously tracks the usage of the services explained in the classroom and records it in a database.

[1852] Output: Updated database usage data

[1853] By taking specific actions at each step, the system can efficiently identify users' interests and promote information and service use through targeted advertising and classes.

[1854] (Application example 1)

[1855] 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."

[1856] The challenge is to efficiently identify users who are interested in specific products or services in physical stores, promptly notify them of campaigns or events, and automate the entire process from registration to the actual event management and feedback collection.Flaws in such systems can impair the timeliness and accuracy of information provided to users, and effective feedback collection and utilization is necessary to improve event participant satisfaction and promote service usage.

[1857] 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.

[1858] In this invention, the server includes means for identifying user interests using a generation AI, means for delivering online advertisements, means for accepting participation applications, means for notifying event participants, means for providing information to event participants, means for collecting feedback from event participants, means for tracking the usage of services explained at the event, means for managing applications for events held at physical stores, and means for notifying smartphones of event information held at physical stores. This makes it possible to accurately grasp user interests, provide campaign and event information at appropriate times, and consistently manage the process from participation applications to feedback collection.

[1859] "Generative AI" is a type of artificial intelligence that analyzes data and automatically generates insights based on specific requirements and conditions.

[1860] "Means for identifying user interests" refers to technology that analyzes collected data to extract user interests in specific products or services.

[1861] "Means for delivering online advertising" refers to a mechanism for delivering advertising content to specific users via the Internet.

[1862] "Means for accepting participation applications" refers to a function for accepting and managing applications from users to participate in events and campaigns.

[1863] "Means for notifying users of upcoming events" is a function that notifies users of upcoming events based on the set date, time, and content.

[1864] "Means for providing information to event participants" refers to a system for providing participants with the information they need before, during, and after the event.

[1865] "Means for collecting feedback from event participants" refers to techniques for collecting opinions and impressions from participants after the event and analyzing them as data.

[1866] "Means for tracking usage of services explained at the event" refers to a system for monitoring and recording subsequent usage of products or services introduced at the event.

[1867] The "means for managing applications for events held in physical stores" refers to a technology that comprehensively manages users' applications to participate in events held in physical stores.

[1868] "Means of notifying smartphones of event information held at physical stores" is a system that notifies users' smartphones of information about events scheduled at physical stores.

[1869] The system of the present invention uses a generative AI to identify users who are interested in a specific product and provide those users with campaign and event notifications for physical stores. Specifically, it includes the following processing steps.

[1870] User Specific

[1871] The server collects website access logs and social media posts and stores them in a database. The software used here includes a data collection API and a generative AI model (e.g., OpenAI GPT-3). The generative AI analyzes the collected data and creates a list of users who are interested in a particular product or service.

[1872] Campaign Notifications

[1873] The server sets up an online advertising campaign based on the user list identified by the generation AI. This setting includes the ad content, target audience, and period. Campaign information is then sent to the user's smartphone. The hardware used includes the server and the user's smartphone, and the software includes an email sending API (e.g., SendGrid) and a notification API.

[1874] Event participation application

[1875] The device (user's smartphone) displays details of the notified campaign or event and allows the user to apply directly. The server receives the application data and stores it in a database. The software used includes a web server and a database management system.

[1876] Event Notification

[1877] When the event date approaches, the server will send a reminder message to help users remember the event. The software includes a notification API so that reminder notifications are sent to users' smartphones.

[1878] Feedback collection

[1879] After the event, the server sends a feedback form to users, analyzes the collected data, and identifies areas for improvement. This will help improve the quality of the next event. The software used includes a feedback form API and a data analysis tool.

[1880] Specific user examples

[1881] For example, when User A is searching for savings-related products, he or she is included in a target list by the generation AI. Based on this list, a campaign notification for a new savings scheme is sent to User A's smartphone. User A clicks on the notification to check the details of the event and apply to participate. Before the event, the server sends User A a reminder message, and after the event ends, a feedback form is sent. Through this series of processes, User A can efficiently obtain information and use new services through the event.

[1882] Prompt Sentence Examples

[1883] "We use generative AI to automate the process of identifying users who are interested in a particular product and sending them promotional notifications."

[1884] "We want to develop an application that allows users to register for seminars held in physical stores and collect feedback on campaigns that interest them."

[1885] Through this process, this application example builds a system that identifies users interested in a new savings scheme and encourages them to participate in events at physical stores.

[1886] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1887] Step 1:

[1888] The server uses a data collection API to obtain website access logs and social media posts and stores them in a database. The input is log data and post data from each data source, which is processed and stored in the database. The output is raw data stored in the database. Specifically, it executes API requests, collects JSON-formatted data, analyzes it, and inserts it into the database.

[1889] Step 2:

[1890] The server analyzes the collected data using a generative AI model (e.g., OpenAI GPT-3) to create a list of users who are interested in a particular product or service. The input is raw data stored in a database, which is analyzed by the generative AI model. The output is a list of users who are determined to be interested. Specifically, the server creates prompts for the generative AI model and performs an analysis process to identify user interests based on the prompts.

[1891] Step 3:

[1892] The server sets up an online advertising campaign based on the user list identified by the generation AI. The input is the identified user list and campaign content, and based on this, it generates ad delivery settings. The output is setting information for the online ad delivery platform. Specifically, it sets parameters such as ad content, delivery target, and period, and sends the data to the delivery platform via API.

[1893] Step 4:

[1894] The device (user's smartphone) receives the campaign notification sent from the server and displays it to the user. The input is the campaign notification data, which is displayed through the smartphone's notification function. The output is the notification display to the user. Specifically, the notification message is constructed using the notification API and displayed as a pop-up on the smartphone screen.

[1895] Step 5:

[1896] The user checks the details of the notified campaign or event on their smartphone and applies to participate. The input is the notification message and a link to the details page, which the user clicks to access the application form. The output is the data entered into the application form. Specifically, the user clicks the link, enters the required information into the web form, and submits it.

[1897] Step 6:

[1898] The server receives event participation application data from users and stores it in a database. The input is the application data sent from the web form, which is saved in the database. The output is the saved application data. Specifically, it receives the form data and inserts it into the database.

[1899] Step 7:

[1900] As the event date approaches, the server sends a reminder message. The input is the event date and time and a list of users, and the server generates a reminder message based on this. The output is a reminder message sent to the user's smartphone. Specifically, the server uses a notification API to send a message based on the reminder settings.

[1901] Step 8:

[1902] After the event ends, the server sends a feedback form to users and analyzes the collected data. The input is the event participant list and the feedback form, and feedback is collected based on this. The output is the feedback data and its analysis results. Specifically, the form link is sent using the feedback form API, and the collected data is evaluated using an analysis tool.

[1903] 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.

[1904] This invention provides a method for specifically implementing a system that uses generative AI and an emotion engine to identify users interested in a new savings program and announces the opening of classes through online advertising. Each element and its specific operation are described below.

[1905] User identification with generative AI and emotion engine

[1906] server:

[1907] User data is collected from various data sources (website access logs, social media posts, user text input, etc.) and stored in a database.

[1908] The generative AI analyzes the collected data, analyzes user interests and behavioral patterns, and based on the analysis results, creates a list of users who are interested in the new savings system.

[1909] The emotion engine uses a webcam and microphone to analyze emotions from the user's facial expressions and voice, and also recognizes emotions from the user's text input.

[1910] Delivery and dynamic adjustment of online advertisements

[1911] server:

[1912] Set up a targeted advertising campaign: define what ads to advertise, who to advertise to, and for how long.

[1913] Based on the analysis results of the generative AI and emotion engine, the content of online advertisements is dynamically adjusted and banner advertisements are delivered.

[1914] Device:

[1915] As users navigate the internet, they are shown tailored banner ads, whose timing and location change dynamically based on targeting lists and sentiment analysis.

[1916] When a user clicks on the banner ad, they are taken to a page detailing the new savings program.

[1917] Application acceptance and notification

[1918] server:

[1919] The class details page contains an application form, and the application data entered by the user is received and stored in a database.

[1920] After confirming your application, we will notify you of the date, time and location of the class via email or message.

[1921] Device:

[1922] The user enters the required information on the details page and applies to participate.

[1923] Receive notification emails and messages and prepare to join the class.

[1924] Classroom Management and Emotional Response

[1925] server:

[1926] It manages presentation materials and demonstration data used in the classroom and provides them to the instructor's device.

[1927] Provide the instructor with a list of participants and assist with classroom management.

[1928] Device (instructor's smartphone):

[1929] The lecturer uses a smartphone to display and explain a presentation about a new savings system, and the speaker's smartphone dynamically adjusts the content and tone of the presentation based on the user's emotional data obtained from the emotion engine.

[1930] Demonstrations will be held on smartphones, fixed-line services, and point management, and the benefits of using them will be explained.

[1931] user:

[1932] Participate in the class, listen to the instructor's explanations and demonstrations, and deepen your understanding of the new savings system. You will also learn about smartphones, fixed-line services, and point management.

[1933] Feedback collection and tracking

[1934] server:

[1935] After the class, a feedback form is sent to participants via email or message to collect their ratings and comments.

[1936] The collected feedback data will be analyzed to improve classroom content and services provided.

[1937] The usage status of services (smartphone, fixed line, point management, etc.) that participants have actually started using will be tracked and stored in a database. The usage data for each service will be visualized and used in corporate strategy planning.

[1938] To give a specific example, while User A is searching for information on the Internet, he or she is included in a target list by the generative AI and emotion engine. Based on this list, a dynamically adjusted banner ad is displayed on the web page that User A is viewing. When User A clicks on the ad, he or she is taken to the class details page where he or she can apply to participate. After the application is accepted, a notification email is sent to User A's device. On the day of the class, the instructor will give an explanation, adjusting the presentation based on the user's emotion data. After the class ends, User A fills in a feedback form, and their subsequent service usage is tracked.

[1939] In this way, the system, which utilizes generative AI and an emotion engine, can effectively identify users and provide them with information through classrooms, thereby promoting the use of related services and expanding the customer base.

[1940] The processing flow will be explained below.

[1941] Step 1:

[1942] server:

[1943] User data is collected from various data sources (website access logs, social media posts, user text input, etc.) and stored in a database. The collected data includes user browsing history, click history, and post content.

[1944] The generative AI analyzes the collected data to analyze user interests and behavioral patterns, and based on the analysis results, creates a list of users who are interested in the new savings system.

[1945] Step 2:

[1946] server:

[1947] The emotion engine is initialized and collects the user's facial and voice data via the webcam and microphone. The emotion engine analyzes this data in real time to determine the user's current emotional state.

[1948] Analyzes emotional data from user text input, extracting emotions and tones from text messages and other inputs.

[1949] Step 3:

[1950] server:

[1951] Set up targeted advertising campaigns, defining the content, audience, and duration of ads, using user lists identified by generative AI and sentiment analysis results from the sentiment engine.

[1952] Based on data from the emotion engine, the content of online ads is dynamically adjusted to best suit the user's emotional state before being delivered.

[1953] Step 4:

[1954] Device:

[1955] As users navigate the internet and browse websites and applications, they are shown tailored banner ads, whose timing and location change dynamically based on targeting lists and sentiment analysis.

[1956] When a user clicks on the banner ad, they are taken to a page detailing the new savings program.

[1957] Step 5:

[1958] User:

[1959] Access the class details page and enter the required information (name, contact information, desired date and time of participation, etc.) in the provided participation application form and submit it.

[1960] Once you have completed your registration, you will automatically receive a confirmation message.

[1961] Step 6:

[1962] server:

[1963] Receives application data and stores it in a database. Generates and sends notification emails and messages to users so that they can confirm their application details.

[1964] Send notifications to users with details about class times, dates, and locations.

[1965] Step 7:

[1966] Device:

[1967] Download and prepare classroom presentation materials and demo data onto the instructor's smartphone.

[1968] Users who receive the notification email or message can prepare to join the class.

[1969] Step 8:

[1970] server:

[1971] We will provide the instructor with a list of participants on the day of the class to help ensure the class runs smoothly. This list will also be used to support smooth reception at the entrance to the venue.

[1972] Step 9:

[1973] Device (instructor's smartphone):

[1974] The lecturer uses a smartphone to display and explain in detail a presentation about a new savings scheme, and the speaker's smartphone dynamically adjusts the content and tone of the presentation based on the user's emotional data obtained from the emotion engine.

[1975] Step 10:

[1976] Device (instructor's smartphone):

[1977] Demonstrations will be conducted on smartphones, fixed-line services, and point management, and the benefits of using them will be explained in detail. An emotion engine will be used to adjust the progress of the demonstration based on the emotional state of the participants.

[1978] Step 11:

[1979] User:

[1980] Participate in the class, understand the instructor's explanations and demonstrations, and learn about the structure and benefits of the new savings system. You will also learn in detail about the proposed smartphone and fixed-line services, and point management.

[1981] Step 12:

[1982] server:

[1983] After the class, participants are sent a feedback form via email or message to collect their ratings and comments. The feedback data is then stored in a database for later use in improving the service.

[1984] The usage of the services explained in the class will be tracked in real time and recorded in a database. Usage trends for each service will be analyzed and used to plan future strategies.

[1985] To give a specific example, while User A is searching for information on the Internet, he or she is included in a target list by the generative AI and emotion engine. Based on this list, a dynamically adjusted banner ad is displayed on the web page that User A is viewing. When User A clicks on the ad, he or she is taken to the class details page where he or she can apply to participate. After the application is accepted, a notification email is sent to User A's device. On the day of the class, the instructor will give an explanation, adjusting the presentation based on the user's emotion data. After the class ends, User A fills in a feedback form, and their subsequent service usage is tracked.

[1986] In this way, the system, which utilizes generative AI and an emotion engine, can effectively identify users and provide them with information through classrooms, thereby promoting the use of related services and expanding the customer base.

[1987] Example 2

[1988] 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."

[1989] Conventional online advertising systems only deliver ads based on users' interests, but are unable to deliver ads that take into account users' emotions. Furthermore, there was a lack of a mechanism for adequately collecting and analyzing feedback on how users who received ads behaved after attending classes. Furthermore, it was difficult to track the usage of services explained in classes, which meant that the data could not be fully utilized to improve services or develop marketing strategies.

[1990] 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.

[1991] In this invention, the server includes a means for identifying user interests using generative AI, a means for analyzing user emotions using an emotion engine, and a means for dynamically adjusting and delivering online advertisements using the analysis results. This enables the delivery of highly targeted advertisements based on the user's interests and emotions. The server also includes a means for accepting participation applications, a means for notifying class participants, a means for providing information to class participants, a means for collecting feedback from class participants, and a means for tracking the usage of services explained in the classes. This facilitates the collection and analysis of feedback and the tracking of service usage, which can be used to improve services and develop strategies.

[1992] "Generative AI" is a system that uses artificial intelligence technology to identify users' interests and concerns.

[1993] An "emotion engine" is a system for analyzing emotions from data such as a user's facial expressions, voice, and text input.

[1994] "Online advertising" refers to advertising banners and links distributed over the Internet, which are a means of providing information and promotions to users.

[1995] "Dynamic adjustment" refers to changing the content and timing of advertising in real time based on the analysis results of the generative AI and emotion engine.

[1996] "Registration" is the process by which a user indicates their intention to attend a class or event and provides the necessary information.

[1997] "Notifications" are a way to communicate important information to users, such as the date, time, and location of class events.

[1998] "Feedback" refers to information collected from users, such as ratings and comments, that is used to improve our services and events.

[1999] "Tracking" is the process of monitoring and collecting data on the use of the services described in the classroom.

[2000] This invention is a system that utilizes generative AI and an emotion engine to analyze users' interests and emotions, deliver appropriate online advertisements, provide class information, collect feedback, and track service usage. The system is composed of three main entities: a server, a device, and the user.

[2001] User Specific

[2002] The server collects user data from various data sources (e.g., website access logs, social media posts, user text input) and stores it in a database. The server uses generative AI to analyze the collected data and identify the user's interests. This analysis uses natural language processing (NLP) technology. The emotion engine analyzes emotions from the user's facial expressions and voice data obtained from the webcam and microphone, as well as text input.

[2003] As a specific example, a user's search history for keywords related to "new savings systems" is collected, and based on the collected data, the generation AI determines that the user is interested in a new financial product.

[2004] Delivery and dynamic adjustment of online advertisements

[2005] The server sets up a targeted advertising campaign and defines the ad content, distribution target, and distribution period. Based on the analysis results of the generative AI and emotion engine, the ad content is dynamically adjusted and delivered to users as banner ads on the Internet. The adjusted banner ad is displayed on the user's device (PC or smartphone). When the user clicks on the banner ad, they are taken to a class details page where they can apply to participate.

[2006] As a concrete example, when user A is browsing a news site, a dynamically adjusted banner ad appears, and when he clicks on the ad, he is taken to a detailed page about a class on savings programs.

[2007] Application acceptance and notification

[2008] The server places a participation application form on the class details page and stores the participation application data entered by the user in a database. The server then notifies the user of the class date, time, and location via email or message. The user receives the notification on their device and prepares to participate in the class.

[2009] As a specific example, a user accesses a class details page via a banner ad, applies to participate from there, and receives a notification email.

[2010] Classroom Management and Emotional Response

[2011] The server manages presentation materials and demo data and provides them to the instructor's device (e.g., a smartphone). In the classroom, the instructor uses their smartphone to give a presentation, dynamically adjusting the content and tone based on the user's emotional data obtained from the emotion engine. Participants attend the class and learn about the new savings system.

[2012] As a concrete example, the instructor can use a smartphone in the classroom to check emotional data in real time and adjust the content of the explanation as he or she goes along.

[2013] Feedback collection and tracking

[2014] After the class ends, the server sends a feedback form to the participants and collects their ratings and comments. This data is analyzed to improve the class content and services. The server also tracks the usage of services that participants have actually started using and stores the data in a database. This data can be used to develop corporate strategies.

[2015] For example, after the class ends, users are sent a feedback form, and the results are reflected in improving the content of the next class.

[2016] Prompt Sentence Examples

[2017] "Describe a system that detects user interests and delivers targeted advertising based on the data analyzed by an emotion engine."

[2018] This invention enables highly targeted advertising based on user interests and emotions, helping to promote new savings programs more effectively through classrooms, while collecting feedback and tracking usage allows for continuous improvement of the service.

[2019] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2020] Step 1:

[2021] Data collection

[2022] server:

[2023] The server collects user data from data sources such as website access logs, social media posts, and user text input, and stores it in a database. Various data sources are used as input, and the output is formatted user data. Specifically, the server calls the data source API, retrieves JSON-formatted data, and stores it in the database.

[2024] Step 2:

[2025] Interest identification using generative AI

[2026] server:

[2027] The server inputs the collected user data into the generation AI to identify the user's interests. In this case, the generation AI uses natural language processing (NLP) technology. The input is user data, and the output is the identified user interest data. Specifically, the generation AI model feeds user data and classifies the user's interests by comparing it with the educational database.

[2028] Step 3:

[2029] Emotion analysis

[2030] server:

[2031] The server uses an emotion engine to analyze emotions from the user's facial expressions, voice, and text input obtained from the webcam and microphone. The input is real-time data, and the output is analyzed emotion data. Specifically, the webcam footage is analyzed frame by frame, the voice data is subjected to phonetic pattern analysis, and emotion keywords are extracted from the text.

[2032] Step 4:

[2033] Ad delivery settings and adjustments

[2034] server:

[2035] The server sets up targeted advertising campaigns and dynamically adjusts ad content based on the analysis results of the generative AI and emotion engine. The input is interest data and emotion data, and the output is adjusted ad data. Specifically, it inserts messages and images into ad templates that match the user's interests and emotions.

[2036] Step 5:

[2037] Advertisement display

[2038] Device:

[2039] The tailored banner ad is displayed on the user's device (PC or smartphone). The input is the tailored ad data, and the output is the displayed ad. Specifically, when the user browses a web page, the dynamically tailored banner ad is rendered in the ad display area.

[2040] Step 6:

[2041] Participation application acceptance

[2042] server:

[2043] The server places an application form on the class details page, receives the application data entered by the user, and stores it in a database. The input is the user's application data, and the output is the stored application data. Specifically, the server receives input from the user in an HTML form and saves it in a database on the backend.

[2044] Step 7:

[2045] Send notifications

[2046] server:

[2047] After the server confirms the participation application, it notifies the user of the class date, time, and location via email or message. The input is the participation confirmation data, and the output is the notification email or message sent. Specifically, it uses an email sending API to send individual notification emails to participants.

[2048] Step 8:

[2049] Presentation materials provided

[2050] server:

[2051] The server manages the presentation materials and demo data used in the classroom and provides them to the instructor's terminal. The input is the presentation materials and demo data, and the output is the materials provided to the instructor's terminal. Specifically, the server makes the materials available for download from a cloud storage service and sends a link to the instructor's terminal.

[2052] Step 9:

[2053] Classroom Management and Emotional Response

[2054] Device (instructor's smartphone):

[2055] The lecturer uses a device to give a presentation and dynamically adjusts the content and tone based on data from the emotion engine. The input is emotion data, and the output is an adjusted presentation. Specifically, the emotion data is received in real time and the content and tone of the slides are changed accordingly.

[2056] Step 10:

[2057] Feedback collection

[2058] server:

[2059] After the class ends, the server sends a feedback form to the participants and collects their ratings and comments. The input is the feedback data, and the output is the collected feedback. Specifically, a form submission API is used to send a link to the participants, and their responses are saved in a database.

[2060] Step 11:

[2061] Usage Tracking

[2062] server:

[2063] The server tracks the status of services actually used by class participants and stores the data in a database. The input is usage data, and the output is the stored tracking data. Specifically, usage logs are collected periodically and stored in a database for analysis.

[2064] Through these steps, the system can effectively deliver advertisements according to users' interests and emotions, manage classrooms, collect feedback, and track usage.

[2065] (Application example 2)

[2066] 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."

[2067] Today's consumers are bombarded with a vast amount of information, making it difficult to find information and products that are relevant to them. Furthermore, to maximize the effectiveness of online advertisements and campaigns, targeting based on individual users' emotions and interests is necessary. Furthermore, virtual stores require mechanisms that allow users to enjoy individually customized shopping experiences. Given this background, there is a need for systems that can provide advertisements and information based on users' interests and emotions, and measure and improve their effectiveness.

[2068] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2069] In this invention, the server includes means for identifying user interests using generative AI, means for delivering online advertisements, means for accepting participation applications, means for notifying class schedules, means for providing information to class participants, means for collecting feedback from class participants, means for tracking the usage of services explained in the class, means for using an emotion engine that analyzes the user's emotional state based on their facial expressions and voice, and means for providing a customized shopping experience through smart glasses in a virtual store. This makes it possible to provide advertisements and information optimized for each individual user and measure and improve their effectiveness in real time.

[2070] "Generative AI" is a technology that uses artificial intelligence to automatically analyze and identify users' interests and concerns.

[2071] "Online advertising" refers to advertising content delivered to users via the Internet.

[2072] "Registration" is the process by which a user indicates their intention to participate in a particular event or class and completes the necessary procedures.

[2073] "Classroom Notification" is a means of communicating information to users about details such as the date and location of an event or class.

[2074] "Feedback" refers to reactions and comments such as evaluations and opinions obtained from users.

[2075] "Tracking" means the continuous tracking and recording of the usage of a particular service or product.

[2076] The "emotion engine" is a technology that analyzes the user's facial expressions and voice to recognize and evaluate their emotional state.

[2077] A "virtual store" is not an actual physical store, but a virtual store that operates online or in the digital space.

[2078] "Smart glasses" are advanced eyeglass-type devices equipped with a display, camera, sensors, etc., and capable of providing information to users.

[2079] "Shopping experience" is a general term for the experiences and services that consumers receive in the process of selecting and purchasing a product.

[2080] This invention is a system that utilizes generative AI and an emotion engine to provide users with optimal advertisements and information, thereby improving their shopping experience in virtual stores. A specific embodiment of the present invention is described below.

[2081] System Configuration

[2082] This system mainly consists of three elements: a server, a terminal (smart glasses, smartphone, etc.), and a user. The role and operation of each element are explained below.

[2083] server

[2084] The server consists of multiple components, including a generative AI model, an emotion engine, and a database. Specifically, it uses the following software and hardware:

[2085] Hardware and Software

[2086] Hardware: High-performance server

[2087] Software: Python, TensorFlow, OpenCV

[2088] Data collection

[2089] The server collects user data from each data source (website access logs, social media posts, user text input, etc.) and stores it in a database.

[2090] Analysis by generative AI

[2091] The generative AI model analyzes the collected data and analyzes user interests and behavioral patterns. This generates a list of users who are interested in the new savings scheme. An example prompt is shown below:

[2092] "We are collecting text information to identify users who are interested in investing and saving. Analyze their interests and create a list of users who are most likely to be interested in a new savings scheme."

[2093] Analysis by emotion engine

[2094] The emotion engine uses a webcam and microphone to analyze emotions from the user's facial expressions and voice. The emotion engine also recognizes emotions from the user's text input.

[2095] Ad delivery and dynamic adjustment

[2096] The server sets up targeted advertising campaigns, defining the ad content, target audience, and distribution period. Based on the analysis results of the generative AI and emotion engine, the content of online ads is dynamically adjusted and banner ads are distributed.

[2097] Terminal

[2098] Smart Glasses

[2099] Users use smart glasses to shop in virtual stores. The smart glasses have the following features:

[2100] Advertisement display: Displaying customized banner ads at the right time based on the user's emotional state.

[2101] Providing detailed information: Clicking on an ad displays detailed information about the product or event and takes you to a page to register for participation.

[2102] Smartphone

[2103] Smartphones will be used for classroom presentations and registration.

[2104] Presentation display: The instructor uses a smartphone to display a presentation about a new savings scheme.

[2105] Dynamic adjustment based on emotional data: The instructor's smartphone dynamically adjusts the content and tone of the presentation based on the user's emotional data obtained from the emotion engine.

[2106] user

[2107] The user uses this system to perform the following process:

[2108] Viewing ads and signing up: When users are browsing the internet, they will be shown dynamically adjusted banner ads that, when clicked, will take them to a class details page where they can sign up.

[2109] Providing feedback: After the class, participants fill out a feedback form and their subsequent use of the service is tracked.

[2110] In this way, the present invention can provide users with the most appropriate advertisements and information, allowing them to customize their shopping experience in a virtual store.

[2111] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2112] Step 1:

[2113] The server collects user data from data sources such as website access logs, social media posts, and user text input, and stores it in a database.

[2114] Input: Website access logs, social media posts, user text input

[2115] Data processing: Collected data is centrally managed and stored in a database

[2116] Output: A cleaned up user database

[2117] Step 2:

[2118] The server uses a generative AI model to analyze the collected data and analyze users' interests and behavioral patterns.

[2119] Input: User Database

[2120] Data Computation: Using generative AI models to calculate interest scores and identify target users

[2121] Output: List of highly interested users

[2122] Specific operation: The generative AI performs analysis based on the prompt: "We are collecting text information to identify users who are interested in investing and saving. Analyze user interests and create a list of users who are likely to be most interested in the new savings system."

[2123] Step 3:

[2124] The server uses an emotion engine to analyze the user's emotional state based on facial expressions, voice, and text input obtained from the webcam and microphone.

[2125] Input: Webcam video, audio data, text input

[2126] Data Computation: Emotion Analysis Using an Emotion Engine

[2127] Output: User's emotional state data

[2128] Specific operation: Obtain data in real time from a webcam and microphone to estimate emotional state.

[2129] Step 4:

[2130] Based on the analysis results of the generative AI and emotion engine, the server sets up advertising campaigns, generates and adjusts targeted ads, and delivers online ads.

[2131] Input: User list, emotional state data

[2132] Data processing: Ad content is customized for each user and displayed at the appropriate time

[2133] Output: Tailored banner ad

[2134] Specific operation: The advertising distribution system displays the most appropriate advertisement for the page viewed by the target user.

[2135] Step 5:

[2136] While using the Internet, users view tailored banner ads and click on them to be taken to a details page where they can apply to participate.

[2137] Input: Tailored banner ads

[2138] Output: Display of classroom details page, participation application data

[2139] Specific actions: The user clicks on the ad and fills in the required information on the application form.

[2140] Step 6:

[2141] The server places a participation application form on the classroom details page, receives the participation application data entered by the user, and stores it in a database.

[2142] Input: Participation application data

[2143] Data processing: Save the application data in a database and check for duplications and errors.

[2144] Output: Organized participant list

[2145] Step 7:

[2146] The server confirms the participation application and notifies the user of the date, time and location of the class via email or message.

[2147] Input: Participant list

[2148] Output: Notification email, message

[2149] Specific action: Execute a process to automatically send notifications to participants.

[2150] Step 8:

[2151] The device (the instructor's smartphone) displays presentation materials during the class and dynamically adjusts the content and tone based on data from the emotion engine.

[2152] Input: Presentation materials, participants' emotional state data

[2153] Data processing: Adjusting presentation content and changing tone

[2154] Output: Well-tuned presentation

[2155] Specific behavior: Check emotional state in real time and optimize content.

[2156] Step 9:

[2157] Users will attend classes, follow lectures and demonstrations from instructors, and gain a deeper understanding of the new savings system.

[2158] Input: Instructor presentation

[2159] Output: Improved user understanding

[2160] Specific actions: Listen to the instructor's explanation and watch the demonstration to learn.

[2161] Step 10:

[2162] After the class, the server sends a feedback form to participants and collects their evaluations and comments.

[2163] Input: Feedback Form

[2164] Data processing: Analysis of collected feedback data

[2165] Output: Feedback data analysis results

[2166] Specific actions: Automatically send feedback forms to participants and analyze the collected data.

[2167] This makes it possible for the present invention to provide users with optimal advertisements and information, improving their shopping experience in virtual stores.

[2168] 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.

[2169] 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.

[2170] 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.

[2171] 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.

[2172] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2173] 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.

[2174] 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).

[2175] 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.

[2176] 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."

[2177] 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.

[2178] 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 impleme...

Claims

1. A means of identifying user interests through generative AI; a means of delivering online advertisements; a means for accepting applications for participation; and A means of notifying students of upcoming classes; A means of providing information to classroom participants; a means of gathering feedback from classroom participants; a means of tracking the use of the services described in the classroom; A system including:

2. The system of claim 1 , wherein the generating AI analyzes website access logs and social media posts to identify user interests.

3. 10. The system of claim 1, wherein the delivered online advertisement includes a link to a page detailing a class on a new savings program.

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