System

Abstract

A system is provided.SOLUTION: A system comprising: means for collecting personal data of a user; means for storing the personal data in a database; means for receiving and storing an original image advertisement from an advertiser; means for generating an advertisement optimized for each user based on the personal data and the original image advertisement; means for delivering the generated advertisement to a terminal of a user; and means for displaying the generated advertisement on the terminal.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional ad delivery technologies are limited to targeting groups based on user attributes, and lack personalization at the individual level. As a result, ads often do not perfectly match users' interests, limiting improvements in click-through rates and conversion rates. Furthermore, conventional systems have difficulty incorporating user behavioral data as feedback during the ad delivery process, making it difficult to continuously optimize advertising effectiveness. The present invention aims to solve these problems by providing a system for generating and delivering highly accurate ads based on individuals' personal data. [Means for solving the problem]

[0005] The present invention solves the above problems by the following means. Specifically, it provides a system including means for collecting and storing personal data of users in a database, means for receiving and storing original image advertisements from advertisers, and means for generating advertisements optimized for each user based on this data. Furthermore, the system includes means for delivering the generated advertisements to the user's terminal and displaying the advertisements on the terminal. Furthermore, by providing means for collecting user response data and providing feedback to the advertisement generation means, the effectiveness of the advertisements can be continuously optimized. Furthermore, by allowing the generated advertisements to include customization elements based on the user's name and preferences, it is possible to gain greater user empathy.

[0006] "Personal data" refers to specific attribute information about an individual, such as the user's age, gender, occupation, hobbies, browsing history, and purchase history.

[0007] A "database" is a storage device or software that efficiently stores and manages collected personal data and advertising data and allows quick access when needed.

[0008] The "original image advertisement" is a basic advertisement image provided by an advertiser, and is the basic data from which a personalized advertisement is generated based on this image.

[0009] "Advertising generation AI" is an artificial intelligence system that automatically generates optimal advertisements for specific users based on the user's personal data and the original image advertisement.

[0010] A "terminal" is a device used by a user (such as a smartphone, tablet, or PC), and is the hardware that receives and displays advertisements.

[0011] "Advertisement delivery" is the process of transmitting the generated personalized advertisement to the user's terminal.

[0012] "Feedback" refers to information collected about users' reactions to advertisements (clicks, purchases, viewing time, etc.) and used to optimize advertisement generation and distribution.

[0013] "Customization elements" are elements of advertisements that are individually set for each user (such as name, content based on interests and preferences), and are information used to optimize the content of advertisements for specific users. [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] This invention relates to a system that generates and delivers personalized advertisements based on a user's personal data. This system includes AI that generates advertisements optimized for each user, and can improve advertisement click rates and conversion rates. Below, the program processing of this system is explained in natural language with specific examples.

[0036] 1. Collection and storage of personal data

[0037] The server collects personal data provided by the user (such as age, gender, occupation, and hobbies), including information entered by the user at the time of registration, subsequent website browsing history, and purchase history.

[0038] Examples:

[0039] When registering, the user (Tanaka) enters his / her age, gender, occupation, and hobbies. Tanaka's browsing history and purchase history of the websites he / she uses are also periodically sent to the server.

[0040] The server stores this data in a database, which is updated as needed to keep the data up to date.

[0041] 2. Management of original image ads

[0042] The server receives and stores original image advertisements provided by advertisers, which serve as the basis for generating personalized advertisements.

[0043] Examples:

[0044] Advertiser A sends the original image advertisement for the music player to the server, which stores it in the advertisement database and records related metadata (such as the target age group).

[0045] 3. Generating personalized ads

[0046] The server runs an ad generation AI to generate the optimal ad for each user based on the collected personal data and the original image ad. This AI considers the user's individual data and automatically generates the ad that best suits the specific user.

[0047] Examples:

[0048] The server generates an advertisement for a music player that is best suited to Tanaka, who is interested in music, based on Tanaka's age, gender, occupation, and hobbies. The advertisement includes content customized to Tanaka's name and preferences.

[0049] 4. Delivery of advertisements

[0050] The generated personalized advertisement is delivered from the server to the user's terminal, which receives and displays the advertisement.

[0051] Examples:

[0052] The server sends a personalized music player advertisement to Tanaka's smartphone, which displays the advertisement on his home screen and browser.

[0053] 5. Feedback collection and analysis

[0054] Information on users' reactions to ads (clicks, purchases, viewing time, etc.) is sent from the device to the server, which analyzes this feedback data and adjusts the parameters of the ad generation AI to continuously optimize the effectiveness of the ads.

[0055] Examples:

[0056] When Tanaka clicks on the displayed ad, the information is sent from his smartphone to the server, which analyzes Tanaka's click information and reflects it in the generation of the next ad.

[0057] summary

[0058] This system maximizes the effectiveness of advertising by generating personalized advertisements based on users' personal data and delivering them to their devices. The collection and analysis of feedback data also enables continuous optimization of the advertisement generation process.

[0059] The processing flow will be explained below.

[0060] Step 1:

[0061] The server collects personal data provided by the user, including basic information (age, gender, occupation, hobbies, etc.) entered by the user when registering an account. The server also collects the user's website browsing history and purchase history for analysis.

[0062] Step 2:

[0063] Terminals are devices (smartphones, tablets, PCs, etc.) that users use on a daily basis, and these devices periodically send user behavior data to a server. This data includes browsing history, purchase history, click information, etc.

[0064] Step 3:

[0065] The server stores the collected data in a database, including basic information about the user and their behavioral data, and updates the database accordingly to keep the user's profile information up to date.

[0066] Step 4:

[0067] The server receives and stores original image advertisements from advertisers. These images are stored in an advertisement database and managed as basic data for generating personalized advertisements.

[0068] Step 5:

[0069] The server runs an ad generation AI based on personal data and the original image ad. The AI ​​analyzes personal data such as the user's age, gender, occupation, and hobbies, and automatically generates the most suitable ad for each user based on that data.

[0070] Step 6:

[0071] The server then delivers the generated personalized advertisement to the user's device, either in real time or at a specific time.

[0072] Step 7:

[0073] The device then displays the received personalized advertisements to the user, primarily on the home screen or in a web browser or other interface, providing the advertisements in a format that is easy for the user to access.

[0074] Step 8:

[0075] Users respond to the displayed advertisements by clicking, purchasing, etc. These responses are recorded as feedback data.

[0076] Step 9:

[0077] The device sends user response data to the server, including whether or not the ad was clicked, the viewing time, and information about purchases made through the ad.

[0078] Step 10:

[0079] The server analyzes the received feedback data. The results of this analysis are used to adjust the ad generation AI algorithm and are used for subsequent ad generation. This makes it possible to continuously optimize the effectiveness of ads.

[0080] summary

[0081] Through these steps, the server generates personalized advertisements based on the user's personal data and delivers them to the user's device. The device displays the advertisements and sends back user response data to the server, realizing a system that continuously improves the effectiveness of advertisements.

[0082] Example 1

[0083] 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."

[0084] Conventional ad delivery systems have had difficulty effectively generating and delivering ads tailored to individual users' needs and preferences. As a result, ad click-through rates and conversion rates have fallen, resulting in insufficient advertising effectiveness. Furthermore, the inability to effectively analyze user feedback and reflect it in ad generation has also led to delays in ad optimization.

[0085] 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.

[0086] In this invention, the server includes means for collecting personal information of users, means for storing the personal information in a database, means for receiving and storing original image advertisements from advertisement providers, means for generating advertisements optimized for individual users based on the personal information and original image advertisements, means for delivering the generated advertisements to the users' display devices, means for displaying the generated advertisements on the display devices, and means for collecting and storing the users' website browsing history and purchase history in a database. This makes it possible to effectively generate and deliver advertisements tailored to the individual needs and preferences of users. Furthermore, by collecting user response data and feeding it back to the advertisement generation means, continuous optimization of advertisements can be achieved, thereby improving advertising effectiveness.

[0087] "User" means an individual or organization that receives advertisements and provides personal data.

[0088] "Personal Information" refers to personal data provided by the User, such as age, gender, occupation, and hobbies.

[0089] The term "database" refers to an electronic storage device for storing personal information, website browsing history, purchase history, and original image advertisements collected by the server.

[0090] An "advertising provider" is a company or organization that provides advertisements and is responsible for transmitting original image advertisements to the server.

[0091] "Original image advertisement" refers to the basic advertisement image sent by the advertisement provider and stored on the server.

[0092] "Optimized advertising" refers to advertising that is customized based on a user's personal information, website browsing history, and purchase history, and is tailored to best suit the user.

[0093] A "display device" is an electronic device used by a user, such as a computer, smartphone, or tablet, that is used to display the generated advertisement.

[0094] "Website browsing history" refers to the URLs of websites visited by a user and information about the pages viewed.

[0095] "Purchase History" refers to a record of purchase transactions made by a User online or offline.

[0096] "Response data" refers to information about actions taken by users in response to advertisements, such as clicking, viewing, or purchasing.

[0097] "Advertising generation means" refers to the algorithms and software used to generate optimized advertisements based on collected personal information and original image advertisements.

[0098] This invention relates to a system that generates and delivers personalized advertisements based on a user's personal information. This system includes an advertisement generation AI for generating advertisements optimized for each user, and can improve advertisement click rates and conversion rates. Below, we will explain how this system is specifically implemented.

[0099] First, the server collects personal information provided by the user and stores it in a database. This includes personal data such as the user's age, gender, occupation, and hobbies. The user's website browsing history and purchase history are also periodically collected and stored in a database. This personal data is used to understand the user's behavioral patterns and interests.

[0100] The server then receives and stores the original image advertisements sent by the advertisement providers. These original image advertisements contain metadata such as target age groups. The server stores the original image advertisements in an advertisement database and uses them in combination with the user's personal data.

[0101] The server runs an ad generation AI to generate optimal ads for each user based on the collected personal data and original image ads. This AI considers the user's individual data and automatically generates ads that are best suited to the specific user. For example, for a user who is interested in music, it generates music-related ads and generates ads with content customized to the user's name and preferences.

[0102] The generated personalized advertisements are delivered from the server to the user's device. The device receives the advertisements and displays them on a display device (smartphone, tablet, computer, etc.). The user can view these advertisements on their home screen or browser.

[0103] Furthermore, information on users' reactions to ads (clicks, purchases, viewing time, etc.) is sent from the device to the server. The server analyzes this feedback data and adjusts the parameters of the ad generation AI, thereby continuously optimizing the effectiveness of ads.

[0104] Examples:

[0105] A user (Tanaka) sees an advertisement for a new music player. Based on the age (29), gender (male), occupation (engineer), and hobby (listening to music) provided by Tanaka when he registered, the server generates an advertisement for the music player that best suits him. The server also takes into account Tanaka's website browsing history and purchase history to generate a customized advertisement. The advertisement includes Tanaka's name and content tailored to his preferences.

[0106] Example prompt sentence:

[0107] "Generate the best music player ad for Mr. Tanaka, a 29-year-old engineer who is interested in music."

[0108] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0109] Step 1:

[0110] The server collects the user's personal information and stores it in a database.

[0111] input:

[0112] Personal data provided by the user (age, gender, occupation, hobbies)

[0113] Specific behavior:

[0114] The user enters personal information into a registration form. The device sends this data to the server, which receives it and stores it in a database.

[0115] output:

[0116] User personal information stored in a database

[0117] Step 2:

[0118] The server collects the user's website browsing history and purchase history and stores it in a database.

[0119] input:

[0120] User browsing history and purchase history

[0121] Specific behavior:

[0122] When a user browses a website or makes a purchase, the device sends this history data to the server, which stores it in a database.

[0123] output:

[0124] Browsing and purchasing history stored in a database

[0125] Step 3:

[0126] The server receives and stores original image advertisements from advertisement providers.

[0127] input:

[0128] Original image ads and metadata (such as target demographics) sent by ad providers

[0129] Specific behavior:

[0130] Advertisers send original image ads to the server, which receives the ads and metadata and stores them in an ad database.

[0131] output:

[0132] Original image ads and metadata stored in the ad database

[0133] Step 4:

[0134] The server runs an ad generation AI to generate optimal ads for each user based on the collected personal data and original image ads.

[0135] input:

[0136] Personal information, website browsing history, purchase history, and original image ads

[0137] Specific behavior:

[0138] The server inputs personal information and original image ads into the ad generation AI, which then generates the most suitable ad for the user based on this data. This process involves customization based on names and preferences.

[0139] output:

[0140] Customized advertising for each user

[0141] Step 5:

[0142] The server delivers the generated personalized advertisement to the user's terminal.

[0143] input:

[0144] Generated personalized ads

[0145] Specific behavior:

[0146] The server transmits the generated advertisement to the user's terminal, and the terminal displays the received advertisement on a display device.

[0147] output:

[0148] Personalized advertisements displayed on a user's display device

[0149] Step 6:

[0150] The server collects data on users' responses to advertisements and analyzes it as feedback data.

[0151] input:

[0152] User response data to ads (clicks, purchases, viewing time, etc.)

[0153] Specific behavior:

[0154] When a user clicks on an ad or makes a purchase, the device sends the response data to the server, which analyzes the received feedback data and adjusts the parameters of the ad generation AI.

[0155] output:

[0156] Analyzed feedback data and adjusted ad generation AI parameters

[0157] (Application example 1)

[0158] 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."

[0159] Conventional advertising distribution systems can generate advertisements based on users' personal data, but they face the challenge of measuring the effectiveness of advertisements in real time and reflecting this in the next advertisement generation process. Another problem is that advertisements are not optimized sufficiently because user response data is not fully utilized. The present invention aims to solve this problem by providing a system that collects and analyzes user action data in real time and optimizes the advertisement generation process.

[0160] 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.

[0161] In this invention, the server includes: means for collecting user personal data; means for storing the personal data in a database; means for receiving and storing original image advertisements from advertisers; means for generating advertisements optimized for each user based on the personal data and the original image advertisements; means for delivering the generated advertisements to user terminals; means for displaying the generated advertisements on the terminals; means for collecting user action data (clicks, purchases, etc.) based on the generated advertisements; and means for analyzing the collected user action data using an advertisement generation AI and optimizing the advertisement generation process. This makes it possible to collect and analyze user response data in real time and reflect it in the next advertisement generation process, thereby continuously optimizing the effectiveness of advertisements.

[0162] "Personal data" refers to data that indicates a user's individual characteristics and behavior, such as age, gender, occupation, hobbies, browsing history, and purchase history.

[0163] A "database" is a system for efficiently storing, managing, and searching collected personal data and advertising data.

[0164] "Original image advertisement" refers to advertising material provided by an advertiser and serving as the basis for generating personalized advertisements.

[0165] "Advertising generation AI" is an artificial intelligence system that generates optimal advertisements for each user based on the user's personal data and the original image advertisement.

[0166] "Action data" is data that indicates the user's response to an advertisement (click, purchase, etc.).

[0167] The "advertising generation process" is a series of steps that generate and deliver individually optimized advertisements based on personal data and original image advertisements.

[0168] "Optimization" refers to adjusting the parameters of the ad generation AI based on collected data to maximize ad click-through rates and conversion rates.

[0169] A "terminal" is a device, such as a smartphone, tablet, or PC, that a user uses to receive and display advertisements.

[0170] "Server" means a central computer system that collects, stores, analyzes data, and generates advertisements.

[0171] "Delivery" refers to sending the generated advertisement to the user's terminal.

[0172] The present invention relates to a system for generating and distributing personalized advertisements based on personal data of users. Specific embodiments of the present invention will be described below.

[0173] Collection and storage of personal data

[0174] The server collects personal data provided by users (age, gender, occupation, hobbies, browsing history, purchase history, etc.) and stores it in a database. This data is updated periodically based on user behavior to keep it up to date. The main hardware used is a server computer and user devices (smartphones, tablets, etc.). Software includes Flask (web framework), SQLite (database management system), and Pandas (data processing library). For example, when a user enters their age, gender, occupation, and hobbies during registration, this information is sent to the server and stored in the database.

[0175] Management of original image ads

[0176] The server receives raw image advertisements provided by advertisers and stores them in an advertisement database. This includes data about the image itself and associated metadata (such as the target demographic). The primary hardware used is a server computer, and the software includes Flask and SQLite. For example, an advertiser may send an advertisement image for a new music player to the server, and this data is stored in the advertisement database.

[0177] Generating personalized ads

[0178] The server uses an ad generation AI to generate optimal ads for each user based on the collected personal data and the original image ads. This ad generation AI is built using machine learning libraries such as TENSORFLOW (registered trademark) and Keras. As a preprocessing step, the data is scaled using Scikit-learn's StandardScaler. For example, the server generates a customized ad based on a specific user's age, gender, occupation, and hobbies. This ad is input to the AI ​​model as a prompt: "User's age: 35, gender: male, occupation: engineer, hobbies: music. Please generate an ad for a music player that is optimal for this user."

[0179] Ad delivery and display

[0180] The generated personalized ads are delivered in real time from the server to the user's device, where they are displayed. The main hardware used is a server computer and the user's device, and the ads are delivered via Flask. The ads are displayed in the browser or app on the user's smartphone or tablet.

[0181] Collecting and analyzing user action data

[0182] Data on users' responses to ads (clicks, purchases, etc.) is sent from the device to the server. The server analyzes this feedback data and adjusts the parameters of the ad generation AI to optimize the next ad generation process. This process uses Flask, SQLite, and machine learning libraries such as TensorFlow and Keras. For example, when a user clicks on a displayed ad, that information is sent from the device to the server and analyzed.

[0183] Through these steps, it becomes possible to generate and deliver ads optimized for each user in real time, and to continuously optimize their effectiveness. This system not only improves ad click rates and conversion rates, but also provides advertisers with an efficient marketing method.

[0184] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0185] Step 1:

[0186] The server collects personal data from users. When users register, they enter information such as age, gender, occupation, and hobbies, and send it to the server. The server receives this data and stores it in a database. In this process, the information entered by the user is the input, and the organized personal data is stored in the database as the output.

[0187] Step 2:

[0188] The server continuously collects additional data, such as the user's website browsing history and purchase history, thereby improving the accuracy of the personal data. This data is sent from the user's device to the server at regular intervals. The server updates the database by adding this new data to the existing personal data. The input is the user's behavioral data, and the output is the updated personal data stored in the database.

[0189] Step 3:

[0190] The server receives original image advertisements from advertisers and stores them in the advertisement database. The advertiser sends the original image advertisements and their targeting metadata (e.g., target age group and interest categories) to the server. The server organizes the received data and stores it in the advertisement database. The advertisement database has the data provided by the advertiser as input and the saved original image advertisement as output.

[0191] Step 4:

[0192] The server generates personalized advertisements. This is done by running an advertisement generation AI using the collected personal data and original image advertisements. To generate advertisements optimized for each user, the server first scales the personal data, then combines it with the original image advertisements and inputs it into the AI ​​model. The generated advertisements are digital advertisements that include customized elements. The scaled personal data and original image advertisements are input, and the generated personalized advertisements are obtained as output.

[0193] Step 5:

[0194] The server delivers the generated personalized advertisement to the user's device. The generated advertisement is sent directly from the server to the user's smartphone or tablet and displayed in the device's display area. The generated advertisement data is the input, and the advertisement displayed on the user's device is the output.

[0195] Step 6:

[0196] The device collects user action data (clicks, viewing time, purchases, etc.). When a user responds to an advertisement, the response data is recorded on the device and sent to the server at regular intervals. User operations are input, and the collected action data is sent to the server as output.

[0197] Step 7:

[0198] The server analyzes the collected action data. The server receives this data and stores it in a database. Then, it uses ad generation AI to analyze this data and adjust the parameters of the ad generation process. The input is user action data, and the output is optimized ad generation parameters.

[0199] Step 8:

[0200] The server then uses the optimized parameters to execute the ad generation process from the next time onward, which makes the next ad more effective. By repeating all steps, the effectiveness of the ad is continuously improved. The optimized parameters are the input, and an effective ad generation process is executed as the output.

[0201] 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.

[0202] This invention combines an emotion engine with a system that generates and delivers personalized advertisements based on a user's personal data. The emotion engine recognizes the user's emotions and can further optimize advertisements based on that information.

[0203] 1. Collection of personal data and personal emotional data

[0204] The server collects personal data provided by the user (such as age, gender, occupation, and hobbies). This data includes not only the information the user enters when registering an account, but also subsequent website browsing and purchase history.

[0205] Furthermore, the device is equipped with an emotion engine that recognizes emotions by analyzing the user's facial expressions, voice, behavior, etc. The emotion engine captures the user's reactions while viewing advertisements and generates emotion data in real time.

[0206] Examples:

[0207] When registering, the user (Tanaka) enters his age, gender, occupation, and hobbies. When Tanaka watches a video advertisement while using his smartphone, the device's camera and microphone are used to analyze his facial expressions and voice, and an emotion engine recognizes his emotions, such as "interest" or "discomfort."

[0208] 2. Data storage and management

[0209] This data is stored in a database. The server updates the collected personal data and emotional data as needed to keep them up to date. This allows the user's profile to always reflect the most up-to-date information.

[0210] 3. Management of original image ads

[0211] The server receives and stores original image advertisements provided by advertisers, which are the basis for generating advertisements and are used to generate personalized advertisements.

[0212] Examples:

[0213] Advertiser A sends the original image advertisement for the music player to the server, which stores it in the advertisement database and records related metadata (such as the target age group).

[0214] 4. Generating personalized ads

[0215] The server runs an ad generation AI based on the collected personal data and original image ads. This AI analyzes the user's age, gender, occupation, hobbies, and even emotional data, and automatically generates the most suitable ad for each user based on that data.

[0216] Examples:

[0217] The server analyzes Tanaka's age, gender, occupation, and hobbies to determine his interest in music equipment. It then takes his emotional data (facial expressions and voice indicating interest) into account to customize ads for the music player. The ads include Tanaka's name and emotionally relevant copy.

[0218] 5. Delivery of advertisements

[0219] The generated personalized advertisements are delivered from the server to the user's device, either in real time or at a specific time.

[0220] Examples:

[0221] The server sends a personalized music player advertisement to Tanaka's smartphone, which displays the advertisement on his home screen and browser.

[0222] 6. Feedback Collection and Analysis

[0223] When a user responds to an ad (clicks, purchases, viewing time, etc.), that data is sent from the device to the server. The server analyzes this feedback data and adjusts the parameters of the ad generation AI to reflect this in future ad generation.

[0224] Examples:

[0225] When Tanaka clicks on the ad, that information is sent from his smartphone to the server. The emotion engine also records how Tanaka felt about the ad. The server uses this information to optimize the AI ​​algorithm for the next ad generation.

[0226] summary

[0227] This system maximizes the effectiveness of advertising by generating and delivering personalized advertisements based on the user's personal and emotional data. The collection and analysis of feedback data and emotional data enables continuous optimization of the advertisement generation process.

[0228] The processing flow will be explained below.

[0229] Step 1:

[0230] The server collects personal data provided by the user, specifically basic information such as age, gender, occupation, and hobbies that the user enters when registering an account.

[0231] Step 2:

[0232] The device collects and transmits data about the user's daily activities, including website browsing history, purchase history, and click information, to a server.

[0233] Step 3:

[0234] The server stores the collected personal and behavioral data in a database that is regularly updated to keep this data up to date.

[0235] Step 4:

[0236] The device uses an emotion engine to collect user emotion data, which is recognized in real time based on the user's facial expressions, voice, and behavior.

[0237] Step 5:

[0238] The device sends the collected emotional data to a server, including the user's reactions while watching the advertisement.

[0239] Step 6:

[0240] The server receives original image advertisements from advertisers and stores them in an advertisement database, along with metadata about the target demographic and advertisement content.

[0241] Step 7:

[0242] The server runs an ad generation AI based on the collected personal data, behavioral data, and emotional data, and the AI ​​generates ads optimized for each user.

[0243] Examples:

[0244] The server analyzes Tanaka's age, gender, occupation, and hobbies to determine his interest in music. It also uses emotional data to detect facial expressions that indicate Tanaka's interest in music player ads. It then generates a music player ad tailored to him, adding text that reflects Tanaka's name and emotions.

[0245] Step 8:

[0246] The server then delivers the generated personalized advertisement to Tanaka's device. The advertisement may be delivered in real time or at a specific time.

[0247] Step 9:

[0248] The device then displays the received personalized advertisements, which can appear on the home screen or in a web browser for easy user access.

[0249] Step 10:

[0250] Users respond to the displayed advertisements by clicking or purchasing, etc., which generates feedback data.

[0251] Step 11:

[0252] The terminal transmits user feedback data to the server, including whether or not an ad was clicked, viewing time, purchase information, and so on.

[0253] Step 12:

[0254] The server analyzes the received feedback data. The analysis results are used to optimize the parameters of the ad generation AI. This is reflected in subsequent ad generation, enabling continuous optimization of ad effectiveness.

[0255] By executing the above steps in order, a system is realized that generates and delivers personalized advertisements based on the user's personal data and emotional data.

[0256] Example 2

[0257] 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."

[0258] Conventional advertising delivery systems typically personalize advertisements based on users' personal data, but these systems do not take into account users' emotions or real-time responses, limiting the effectiveness of the advertisements. Furthermore, advertisement generation is often insufficient for individual users, failing to reflect users' preferences and interests. The present invention aims to improve advertising effectiveness and user experience by collecting and analyzing users' emotional data and generating and delivering optimized advertisements based on that data.

[0259] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting personal data and emotional data of users, means for storing the personal data and emotional data in a database, means for receiving and storing original image advertisements from advertisement providers, means for generating advertisements optimized for each user using a generative AI model based on the personal data, emotional data, and original image advertisements, means for delivering the generated advertisements to the user's information processing device, and means for displaying the generated advertisements on the information processing device. This makes it possible to generate and deliver highly optimized personalized advertisements that take into account the user's emotions and real-time reactions.

[0260] "User" means any person or legal entity that accesses the System and provides Personal Data or other information.

[0261] "Personal Data" refers to personal information about a user, such as age, gender, occupation, and hobbies.

[0262] "Emotional data" refers to data on the emotional state analyzed based on the user's facial expressions, voice, behavior, etc.

[0263] A "database" is a system for storing, managing, and searching collected data.

[0264] "Advertiser" means an individual or corporation that provides advertisements to promote its products or services.

[0265] "Original image advertisement" refers to the image or video file that serves as the basic data for the advertisement provided by the advertisement provider.

[0266] A "generative AI model" is an artificial intelligence algorithm that analyzes a user's personal and emotional data to generate optimized advertisements.

[0267] "Information processing device" refers to electronic devices such as computers, smartphones, and tablets that are the target of advertisement delivery.

[0268] "Optimized advertising" refers to advertising that is customized and delivered effectively based on the user's personal and emotional data.

[0269] "Response data" refers to behavioral data such as clicks, purchases, and viewing time shown by users in response to advertisements.

[0270] "Personalization" refers to the inclusion of a user's name, preferences, or other personally unique elements within an advertisement.

[0271] The present invention relates to a system for generating and distributing personalized advertisements based on personal data and emotional data of users. Specific embodiments of the invention using various hardware and software are described below.

[0272] Data collection

[0273] The server has the function of collecting personal data provided by users (such as age, gender, occupation, and hobbies). Users access the system and input their personal data, which is then stored in a database by the server. The server also records website browsing history and purchase history.

[0274] Examples:

[0275] When a user enters their age, gender, occupation, and hobbies on the registration page and clicks the submit button, this information is sent to the server and stored in a database. The server manages this data using MySQL (registered trademark).

[0276] Collecting Emotional Data

[0277] The device is equipped with an emotion engine that analyzes the user's facial expressions, voice, and behavior. This emotion engine recognizes the user's emotions in real time and generates data. The emotion data is sent to a server and stored in a database along with personal data.

[0278] Examples:

[0279] When a user watches an advertisement on their smartphone, the device's camera and microphone capture their facial expressions and voice, allowing emotions such as "interest" or "discomfort" to be recognized in real time and sent to a server.

[0280] Managing advertising data

[0281] The server receives the original image advertisements provided by the advertisement providers and stores them in the advertisement database. In addition, the target attributes of the advertisements (such as age group and region) are also recorded as metadata.

[0282] Examples:

[0283] When an advertisement provider sends an original image advertisement for a music player through an upload interface, the server receives it and stores it in a database.

[0284] Generating personalized ads

[0285] The server runs a generative AI model based on the collected personal and emotional data to generate optimized advertisements for each user. This process involves analyzing the collected data and customizing advertisements according to the user's preferences and emotions.

[0286] Example prompt sentence:

[0287] "Create an ad for a music player targeted to a user who is 30 years old, male, an engineer by profession, and whose hobby is listening to music, and who has shown interest in the product."

[0288] Ad serving

[0289] The generated personalized advertisement is delivered from the server to the information processing device. The advertisement may be delivered in real time or at a specific timing, and displayed on the user's terminal.

[0290] Examples:

[0291] The server sends personalized music player advertisements to the user's smartphone, which displays the advertisements on the home screen or browser.

[0292] Collecting and analyzing feedback

[0293] The user's response to the ad (clicks, purchases, viewing time, etc.) is sent from the device to the server, which analyzes the feedback data and optimizes the AI ​​model to reflect this in future ad generation.

[0294] Examples:

[0295] When a user clicks on an ad, the information is sent to the server in real time, and emotional data is also recorded, allowing the analysis system to update the parameters of the AI ​​model.

[0296] This system utilizes users' personal data and real-time emotional data to generate and deliver more effective and personalized advertisements, thereby maximizing the effectiveness of advertisements and improving the user experience.

[0297] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0298] Step 1: Collecting your personal data

[0299] A user accesses the system and inputs personal data such as age, gender, occupation, and hobbies. The server receives this input data and stores it in a database. Specific operations include the user entering data into a registration form and pressing the submit button. Based on the input data, the server prepares the data format to be saved in the database and stores it in the database.

[0300] Input: Data entered by the user, such as age, gender, occupation, hobbies, etc.

[0301] Output: User's personal data stored on the server

[0302] Step 2: Collecting website browsing and purchase history

[0303] The server records information about the pages viewed and the products purchased each time a user visits a website. Specifically, the server records the information in a log when a user's browsing actions occur, thereby collecting website action data in real time.

[0304] Input: User browsing and purchase history

[0305] Output: Browsing and purchase history data stored on the server

[0306] Step 3: Collecting emotion data

[0307] The emotion engine built into the device analyzes the user's facial expressions, voice, and behavior in real time to generate emotional data. The camera and microphone capture the user's reactions while viewing advertisements, and the data is analyzed to identify emotions such as "interest" or "discomfort." The analyzed emotional data is then sent to a server.

[0308] Input: User's facial expressions, voice, and actions captured by the device

[0309] Output: User emotion data sent to the server

[0310] Step 4: Store and manage your data

[0311] The server stores and manages the collected personal data, browsing history, purchase history, and emotional data in a database. The data is stored while maintaining consistency to prevent duplication or loss of data. The data is updated regularly to reflect the latest information.

[0312] Input: Collected personal data, browsing history, purchase history, emotional data

[0313] Output: The latest data stored in the database

[0314] Step 5: Receive and save the original image ad

[0315] The server receives original image advertisements provided by advertisement providers and stores them in an advertisement database. It also records the received advertisements along with related metadata (such as target age group). Specific operations include uploading advertisement files and inputting their metadata.

[0316] Input: Original image ad and metadata uploaded by the ad provider

[0317] Output: Original image ads and metadata stored in the ads database

[0318] Step 6: Generate personalized ads

[0319] The server runs a generative AI model based on the collected personal data, emotional data, and original image advertisements. The generative AI model receives a prompt sentence for the user's data as input, and generates an advertisement optimized for each user based on that data. Specifically, the AI ​​model inputs the prompt sentence, "Please create an advertisement for a music player for a user who is 30 years old, male, an engineer by profession, whose hobby is listening to music, and who has shown an interest in the advertisement."

[0320] Input: Personal data, emotion data, original image advertisement, prompt sentence

[0321] Output: Generated personalized ad

[0322] Step 7: Serving Ads

[0323] The generated personalized advertisement is delivered from the server to the user's information processing device. Delivery can be in real time or at a specific timing, and the advertisement is displayed on the terminal. Specific operations include the server sending the advertisement to the terminal, and the terminal displaying the advertisement on the home screen or browser.

[0324] Input: Generated personalized ads

[0325] Output: Advertisement delivered to and displayed on the user's device

[0326] Step 8: Collect and analyze feedback

[0327] The device records the user's response to the ad (clicks, purchases, viewing time, etc.) and sends it to the server. The server analyzes this feedback data and adjusts the parameters of the AI ​​model to reflect this in future ad generation.

[0328] Input: User response data to advertisements

[0329] Output: Optimized ad generation parameters from the updated generative AI model

[0330] (Application example 2)

[0331] 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."

[0332] While existing personalized advertising systems have made progress in generating ads based on basic user personal data (such as age, gender, and hobbies), they lack the technology to utilize emotional data to optimize ads in real time. This has resulted in the inability to display ads that respond immediately to user emotions, limiting the effectiveness of ads. Furthermore, while existing ad delivery systems can collect user responses as feedback, they are also problematic in that they do not quickly adjust ad generation based on that feedback.

[0333] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting personal data of users, means for saving the personal data in a database, means for receiving and saving original image advertisements from advertisers, means for generating advertisements optimized for each user based on the personal data and the original image advertisements, means for collecting user emotion data in real time, means for further optimizing advertisements based on the personal data and the emotion data, means for delivering the generated advertisements to the user's terminal, and means for displaying the generated advertisements on the terminal. This makes it possible to optimize advertisements based on the user's real-time emotions, thereby maximizing the effectiveness of advertisements.

[0334] "User" means an individual or organization that uses the system.

[0335] "Personal Data" refers to personal information about the user (age, gender, occupation, hobbies, etc.).

[0336] "Database" means a digital storage system for storing collected personal data and other information.

[0337] An "advertiser" is a company or organization that distributes advertisements and promotes specific products or services.

[0338] "Original image advertisement" refers to basic image data of an advertisement provided by an advertiser, and is the basis for generating a personalized advertisement.

[0339] "Optimized ads" are ads that are customized based on the user's personal and emotional data.

[0340] "Emotion data" is information about emotions acquired from the user's facial expressions, voice, etc.

[0341] "Real-time" means that data is collected immediately and processed on the spot.

[0342] "Terminal" refers to a device (e.g., smartphone, smart glasses, etc.) used to display advertisements.

[0343] "Display means" refers to a method or device for displaying the generated advertisement to a user.

[0344] The present invention provides a system for generating and distributing personalized advertisements using personal data and emotional data of users. Specific embodiments are described below.

[0345] 1. Collection of Personal Data

[0346] The server collects personal data provided by the user (such as age, gender, occupation, hobbies, etc.) This data collection includes not only the information the user enters when registering an account, but also subsequent website browsing history and purchase history.

[0347] 2. Real-time collection of emotional data

[0348] The device (e.g., smart glasses) analyzes the user's facial expressions and voice to collect emotional data in real time. This emotional data is captured using the device's camera and microphone and sent to a server.

[0349] 3. Data storage and management

[0350] The server stores the collected personal data and emotion data in a database, which is kept up to date. The database also stores original image advertisements provided by advertisers.

[0351] 4. Generating personalized ads

[0352] The server uses a generative AI model to generate ads based on the user's personal and emotional data. This process takes into account the user's age, gender, occupation, hobbies, and even real-time emotional data. The generated ads contain content optimized for the user.

[0353] 5. Delivery and display of advertisements

[0354] The generated advertisements are delivered from the server to the device and displayed on the device. In the case of smart glasses, the advertisements are displayed directly in the user's field of vision, while in the case of smartphones, the advertisements are displayed on the home screen or browser.

[0355] 6. Feedback Collection and Analysis

[0356] The user's reactions to the ad (clicks, viewing time, etc.) are collected along with emotional data and sent to the server, which analyzes this feedback data and adjusts the parameters of the generative AI model to reflect this in the next ad generation.

[0357] Hardware and software used

[0358] Hardware: Smart glasses (with camera, microphone, and display), smartphone

[0359] Software: Python, EmotionRecognition library, OpenCV, generative AI model (e.g., GPT-3 (registered trademark))

[0360] Specific examples

[0361] For example, if a user is a 30-year-old male engineer who is interested in music players, and the camera in the smart glasses recognizes that his facial expression looks happy, the server will send the following prompt sentence to the generative AI model to generate an advertisement:

[0362] Prompt Sentence Examples

[0363] "A 30-year-old male engineer is interested in music players. He currently has a happy expression. Please generate personalized ads for the best music equipment for this user."

[0364] This system maximizes the effectiveness of advertising by displaying the most suitable and interesting advertisements to users in real time.

[0365] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0366] Step 1:

[0367] The user inputs personal data. The user inputs personal data such as age, gender, occupation, and hobbies using smart glasses or a smartphone. This data is sent from the device to the server, which then stores the data in a database. Input data (e.g., age, gender) → Data stored in the database

[0368] Step 2:

[0369] The device collects emotion data. If the user is wearing smart glasses, the camera and microphone are used to collect facial expressions and voice in real time. This data is analyzed using the EmotionRecognition library to generate emotion data. Input data (e.g., video, audio) → Output data (e.g., emotion data)

[0370] Step 3:

[0371] The server manages the database. Collected personal data and emotional data are stored in the database and updated as needed. The server manages this database and always keeps the latest information. Input data (e.g., personal data, emotional data) → Latest database

[0372] Step 4:

[0373] Receive original image ads from advertisers. The server receives original image ads provided by advertisers and stores them in a database. During this process, the ad metadata is also stored. Input data (e.g. original image ads) → Stored ad data

[0374] Step 5:

[0375] The server generates personalized ads. Using a generative AI model (e.g., GPT-3), the server generates customized ads based on the collected personal data and emotional data. When generating ads, a prompt sentence is input into the generative AI model. Prompt sentence (e.g., "A 30-year-old male engineer is interested in music players. He currently has a happy expression. Please generate a personalized ad for music equipment that is best suited to this user.") → Personalized ads

[0376] Step 6:

[0377] The server delivers the generated personalized advertisement to the user's device (smart glasses or smartphone). Input data (e.g., personalized advertisement) → Delivered advertisement

[0378] Step 7:

[0379] The advertisement is displayed on the device. The user's device displays the received personalized advertisement. In the case of smart glasses, the advertisement is displayed directly in the user's field of vision. Input data (e.g., delivered advertisement) → Displayed advertisement

[0380] Step 8:

[0381] The user responds to the ad. The user clicks on the ad and the viewing time is measured. The feedback data collected during this process is sent from the device to the server. Input data (e.g., user's ad response) → Feedback data

[0382] Step 9:

[0383] The server analyzes the feedback data. The collected feedback data is analyzed by the server, and the parameters of the generative AI model are adjusted and reflected in the next ad generation. Input data (e.g., feedback data) → Adjusted generative AI model

[0384] As a result, advertisements are optimized based on the user's real-time emotions, making it possible to maximize the effectiveness of the advertisements.

[0385] 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.

[0386] 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.

[0387] 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.

[0388] [Second embodiment]

[0389] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0390] 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.

[0391] 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).

[0392] 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.

[0393] 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.

[0394] 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).

[0395] 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.

[0396] 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.

[0397] 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.

[0398] 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.

[0399] 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.

[0400] 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."

[0401] This invention relates to a system that generates and delivers personalized advertisements based on a user's personal data. This system includes AI that generates advertisements optimized for each user, and can improve advertisement click rates and conversion rates. Below, the program processing of this system is explained in natural language with specific examples.

[0402] 1. Collection and storage of personal data

[0403] The server collects personal data provided by the user (such as age, gender, occupation, and hobbies), including information entered by the user at the time of registration, subsequent website browsing history, and purchase history.

[0404] Examples:

[0405] When registering, the user (Tanaka) enters his / her age, gender, occupation, and hobbies. Tanaka's browsing history and purchase history of the websites he / she uses are also periodically sent to the server.

[0406] The server stores this data in a database, which is updated as needed to keep the data up to date.

[0407] 2. Management of original image ads

[0408] The server receives and stores original image advertisements provided by advertisers, which serve as the basis for generating personalized advertisements.

[0409] Examples:

[0410] Advertiser A sends the original image advertisement for the music player to the server, which stores it in the advertisement database and records related metadata (such as the target age group).

[0411] 3. Generating personalized ads

[0412] The server runs an ad generation AI to generate the optimal ad for each user based on the collected personal data and the original image ad. This AI considers the user's individual data and automatically generates the ad that best suits the specific user.

[0413] Examples:

[0414] The server generates an advertisement for a music player that is best suited to Tanaka, who is interested in music, based on Tanaka's age, gender, occupation, and hobbies. The advertisement includes content customized to Tanaka's name and preferences.

[0415] 4. Delivery of advertisements

[0416] The generated personalized advertisement is delivered from the server to the user's terminal, which receives and displays the advertisement.

[0417] Examples:

[0418] The server sends a personalized music player advertisement to Tanaka's smartphone, which displays the advertisement on his home screen and browser.

[0419] 5. Feedback collection and analysis

[0420] Information on users' reactions to ads (clicks, purchases, viewing time, etc.) is sent from the device to the server, which analyzes this feedback data and adjusts the parameters of the ad generation AI to continuously optimize the effectiveness of the ads.

[0421] Examples:

[0422] When Tanaka clicks on the displayed ad, the information is sent from his smartphone to the server, which analyzes Tanaka's click information and reflects it in the generation of the next ad.

[0423] summary

[0424] This system maximizes the effectiveness of advertising by generating personalized advertisements based on users' personal data and delivering them to their devices. The collection and analysis of feedback data also enables continuous optimization of the advertisement generation process.

[0425] The processing flow will be explained below.

[0426] Step 1:

[0427] The server collects personal data provided by the user, including basic information (age, gender, occupation, hobbies, etc.) entered by the user when registering an account. The server also collects the user's website browsing history and purchase history for analysis.

[0428] Step 2:

[0429] Terminals are devices (smartphones, tablets, PCs, etc.) that users use on a daily basis, and these devices periodically send user behavior data to a server. This data includes browsing history, purchase history, click information, etc.

[0430] Step 3:

[0431] The server stores the collected data in a database, including basic information about the user and their behavioral data, and updates the database accordingly to keep the user's profile information up to date.

[0432] Step 4:

[0433] The server receives and stores original image advertisements from advertisers. These images are stored in an advertisement database and managed as basic data for generating personalized advertisements.

[0434] Step 5:

[0435] The server runs an ad generation AI based on personal data and the original image ad. The AI ​​analyzes personal data such as the user's age, gender, occupation, and hobbies, and automatically generates the most suitable ad for each user based on that data.

[0436] Step 6:

[0437] The server then delivers the generated personalized advertisement to the user's device, either in real time or at a specific time.

[0438] Step 7:

[0439] The device then displays the received personalized advertisements to the user, primarily on the home screen or in a web browser or other interface, providing the advertisements in a format that is easy for the user to access.

[0440] Step 8:

[0441] Users respond to the displayed advertisements by clicking, purchasing, etc. These responses are recorded as feedback data.

[0442] Step 9:

[0443] The device sends user response data to the server, including whether or not the ad was clicked, the viewing time, and information about purchases made through the ad.

[0444] Step 10:

[0445] The server analyzes the received feedback data. The results of this analysis are used to adjust the ad generation AI algorithm and are used for subsequent ad generation. This makes it possible to continuously optimize the effectiveness of ads.

[0446] summary

[0447] Through these steps, the server generates personalized advertisements based on the user's personal data and delivers them to the user's device. The device displays the advertisements and sends back user response data to the server, realizing a system that continuously improves the effectiveness of advertisements.

[0448] Example 1

[0449] 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."

[0450] Conventional ad delivery systems have had difficulty effectively generating and delivering ads tailored to individual users' needs and preferences. As a result, ad click-through rates and conversion rates have fallen, resulting in insufficient advertising effectiveness. Furthermore, the inability to effectively analyze user feedback and reflect it in ad generation has also led to delays in ad optimization.

[0451] 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.

[0452] In this invention, the server includes means for collecting personal information of users, means for storing the personal information in a database, means for receiving and storing original image advertisements from advertisement providers, means for generating advertisements optimized for individual users based on the personal information and original image advertisements, means for delivering the generated advertisements to the users' display devices, means for displaying the generated advertisements on the display devices, and means for collecting and storing the users' website browsing history and purchase history in a database. This makes it possible to effectively generate and deliver advertisements tailored to the individual needs and preferences of users. Furthermore, by collecting user response data and feeding it back to the advertisement generation means, continuous optimization of advertisements can be achieved, thereby improving advertising effectiveness.

[0453] "User" means an individual or organization that receives advertisements and provides personal data.

[0454] "Personal Information" refers to personal data provided by the User, such as age, gender, occupation, and hobbies.

[0455] The term "database" refers to an electronic storage device for storing personal information, website browsing history, purchase history, and original image advertisements collected by the server.

[0456] An "advertising provider" is a company or organization that provides advertisements and is responsible for transmitting original image advertisements to the server.

[0457] "Original image advertisement" refers to the basic advertisement image sent by the advertisement provider and stored on the server.

[0458] "Optimized advertising" refers to advertising that is customized based on a user's personal information, website browsing history, and purchase history, and is tailored to best suit the user.

[0459] A "display device" is an electronic device used by a user, such as a computer, smartphone, or tablet, that is used to display the generated advertisement.

[0460] "Website browsing history" refers to the URLs of websites visited by a user and information about the pages viewed.

[0461] "Purchase History" refers to a record of purchase transactions made by a User online or offline.

[0462] "Response data" refers to information about actions taken by users in response to advertisements, such as clicking, viewing, or purchasing.

[0463] "Advertising generation means" refers to the algorithms and software used to generate optimized advertisements based on collected personal information and original image advertisements.

[0464] This invention relates to a system that generates and delivers personalized advertisements based on a user's personal information. This system includes an advertisement generation AI for generating advertisements optimized for each user, and can improve advertisement click rates and conversion rates. Below, we will explain how this system is specifically implemented.

[0465] First, the server collects personal information provided by the user and stores it in a database. This includes personal data such as the user's age, gender, occupation, and hobbies. The user's website browsing history and purchase history are also periodically collected and stored in a database. This personal data is used to understand the user's behavioral patterns and interests.

[0466] The server then receives and stores the original image advertisements sent by the advertisement providers. These original image advertisements contain metadata such as target age groups. The server stores the original image advertisements in an advertisement database and uses them in combination with the user's personal data.

[0467] The server runs an ad generation AI to generate optimal ads for each user based on the collected personal data and original image ads. This AI considers the user's individual data and automatically generates ads that are best suited to the specific user. For example, for a user who is interested in music, it generates music-related ads and generates ads with content customized to the user's name and preferences.

[0468] The generated personalized advertisements are delivered from the server to the user's device. The device receives the advertisements and displays them on a display device (smartphone, tablet, computer, etc.). The user can view these advertisements on their home screen or browser.

[0469] Furthermore, information on users' reactions to ads (clicks, purchases, viewing time, etc.) is sent from the device to the server. The server analyzes this feedback data and adjusts the parameters of the ad generation AI, thereby continuously optimizing the effectiveness of ads.

[0470] Examples:

[0471] A user (Tanaka) sees an advertisement for a new music player. Based on the age (29), gender (male), occupation (engineer), and hobby (listening to music) provided by Tanaka when he registered, the server generates an advertisement for the music player that best suits him. The server also takes into account Tanaka's website browsing history and purchase history to generate a customized advertisement. The advertisement includes Tanaka's name and content tailored to his preferences.

[0472] Example prompt sentence:

[0473] "Generate the best music player ad for Mr. Tanaka, a 29-year-old engineer who is interested in music."

[0474] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0475] Step 1:

[0476] The server collects the user's personal information and stores it in a database.

[0477] input:

[0478] Personal data provided by the user (age, gender, occupation, hobbies)

[0479] Specific behavior:

[0480] The user enters personal information into a registration form. The device sends this data to the server, which receives it and stores it in a database.

[0481] output:

[0482] User personal information stored in a database

[0483] Step 2:

[0484] The server collects the user's website browsing history and purchase history and stores it in a database.

[0485] input:

[0486] User browsing history and purchase history

[0487] Specific behavior:

[0488] When a user browses a website or makes a purchase, the device sends this history data to the server, which stores it in a database.

[0489] output:

[0490] Browsing and purchasing history stored in a database

[0491] Step 3:

[0492] The server receives and stores original image advertisements from advertisement providers.

[0493] input:

[0494] Original image ads and metadata (such as target demographics) sent by ad providers

[0495] Specific behavior:

[0496] Advertisers send original image ads to the server, which receives the ads and metadata and stores them in an ad database.

[0497] output:

[0498] Original image ads and metadata stored in the ad database

[0499] Step 4:

[0500] The server runs an ad generation AI to generate optimal ads for each user based on the collected personal data and original image ads.

[0501] input:

[0502] Personal information, website browsing history, purchase history, and original image ads

[0503] Specific behavior:

[0504] The server inputs personal information and original image ads into the ad generation AI, which then generates the most suitable ad for the user based on this data. This process involves customization based on names and preferences.

[0505] output:

[0506] Customized advertising for each user

[0507] Step 5:

[0508] The server delivers the generated personalized advertisement to the user's terminal.

[0509] input:

[0510] Generated personalized ads

[0511] Specific behavior:

[0512] The server transmits the generated advertisement to the user's terminal, and the terminal displays the received advertisement on a display device.

[0513] output:

[0514] Personalized advertisements displayed on a user's display device

[0515] Step 6:

[0516] The server collects data on users' responses to advertisements and analyzes it as feedback data.

[0517] input:

[0518] User response data to ads (clicks, purchases, viewing time, etc.)

[0519] Specific behavior:

[0520] When a user clicks on an ad or makes a purchase, the device sends the response data to the server, which analyzes the received feedback data and adjusts the parameters of the ad generation AI.

[0521] output:

[0522] Analyzed feedback data and adjusted ad generation AI parameters

[0523] (Application example 1)

[0524] 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."

[0525] Conventional advertising distribution systems can generate advertisements based on users' personal data, but they face the challenge of measuring the effectiveness of advertisements in real time and reflecting this in the next advertisement generation process. Another problem is that advertisements are not optimized sufficiently because user response data is not fully utilized. The present invention aims to solve this problem by providing a system that collects and analyzes user action data in real time and optimizes the advertisement generation process.

[0526] 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.

[0527] In this invention, the server includes: means for collecting user personal data; means for storing the personal data in a database; means for receiving and storing original image advertisements from advertisers; means for generating advertisements optimized for each user based on the personal data and the original image advertisements; means for delivering the generated advertisements to user terminals; means for displaying the generated advertisements on the terminals; means for collecting user action data (clicks, purchases, etc.) based on the generated advertisements; and means for analyzing the collected user action data using an advertisement generation AI and optimizing the advertisement generation process. This makes it possible to collect and analyze user response data in real time and reflect it in the next advertisement generation process, thereby continuously optimizing the effectiveness of advertisements.

[0528] "Personal data" refers to data that indicates a user's individual characteristics and behavior, such as age, gender, occupation, hobbies, browsing history, and purchase history.

[0529] A "database" is a system for efficiently storing, managing, and searching collected personal data and advertising data.

[0530] "Original image advertisement" refers to advertising material provided by an advertiser and serving as the basis for generating personalized advertisements.

[0531] "Advertising generation AI" is an artificial intelligence system that generates optimal advertisements for each user based on the user's personal data and the original image advertisement.

[0532] "Action data" is data that indicates the user's response to an advertisement (click, purchase, etc.).

[0533] The "advertising generation process" is a series of steps that generate and deliver individually optimized advertisements based on personal data and original image advertisements.

[0534] "Optimization" refers to adjusting the parameters of the ad generation AI based on collected data to maximize ad click-through rates and conversion rates.

[0535] A "terminal" is a device, such as a smartphone, tablet, or PC, that a user uses to receive and display advertisements.

[0536] "Server" means a central computer system that collects, stores, analyzes data, and generates advertisements.

[0537] "Delivery" refers to sending the generated advertisement to the user's terminal.

[0538] The present invention relates to a system for generating and distributing personalized advertisements based on personal data of users. Specific embodiments of the present invention will be described below.

[0539] Collection and storage of personal data

[0540] The server collects personal data provided by users (age, gender, occupation, hobbies, browsing history, purchase history, etc.) and stores it in a database. This data is updated periodically based on user behavior to keep it up to date. The main hardware used is a server computer and user devices (smartphones, tablets, etc.). Software includes Flask (web framework), SQLite (database management system), and Pandas (data processing library). For example, when a user enters their age, gender, occupation, and hobbies during registration, this information is sent to the server and stored in the database.

[0541] Management of original image ads

[0542] The server receives raw image advertisements provided by advertisers and stores them in an advertisement database. This includes data about the image itself and associated metadata (such as the target demographic). The primary hardware used is a server computer, and the software includes Flask and SQLite. For example, an advertiser may send an advertisement image for a new music player to the server, and this data is stored in the advertisement database.

[0543] Generating personalized ads

[0544] The server uses an ad generation AI to generate optimal ads for each user based on the collected personal data and the original image ads. This ad generation AI is built using machine learning libraries such as TensorFlow and Keras. As a preprocessing step, the data is scaled using Scikit-learn's StandardScaler. For example, the server generates a customized ad based on a specific user's age, gender, occupation, and hobbies, and this ad is input to the AI ​​model in the prompt text: "User's age: 35, gender: male, occupation: engineer, hobbies: music. Please generate the optimal music player ad for this user."

[0545] Ad delivery and display

[0546] The generated personalized ads are delivered in real time from the server to the user's device, where they are displayed. The main hardware used is a server computer and the user's device, and the ads are delivered via Flask. The ads are displayed in the browser or app on the user's smartphone or tablet.

[0547] Collecting and analyzing user action data

[0548] Data on users' responses to ads (clicks, purchases, etc.) is sent from the device to the server. The server analyzes this feedback data and adjusts the parameters of the ad generation AI to optimize the next ad generation process. This process uses Flask, SQLite, and machine learning libraries such as TensorFlow and Keras. For example, when a user clicks on a displayed ad, that information is sent from the device to the server and analyzed.

[0549] Through these steps, it becomes possible to generate and deliver ads optimized for each user in real time, and to continuously optimize their effectiveness. This system not only improves ad click rates and conversion rates, but also provides advertisers with an efficient marketing method.

[0550] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0551] Step 1:

[0552] The server collects personal data from users. When users register, they enter information such as age, gender, occupation, and hobbies, and send it to the server. The server receives this data and stores it in a database. In this process, the information entered by the user is the input, and the organized personal data is stored in the database as the output.

[0553] Step 2:

[0554] The server continuously collects additional data, such as the user's website browsing history and purchase history, thereby improving the accuracy of the personal data. This data is sent from the user's device to the server at regular intervals. The server updates the database by adding this new data to the existing personal data. The input is the user's behavioral data, and the output is the updated personal data stored in the database.

[0555] Step 3:

[0556] The server receives original image advertisements from advertisers and stores them in the advertisement database. The advertiser sends the original image advertisements and their targeting metadata (e.g., target age group and interest categories) to the server. The server organizes the received data and stores it in the advertisement database. The advertisement database has the data provided by the advertiser as input and the saved original image advertisement as output.

[0557] Step 4:

[0558] The server generates personalized advertisements. This is done by running an advertisement generation AI using the collected personal data and original image advertisements. To generate advertisements optimized for each user, the server first scales the personal data, then combines it with the original image advertisements and inputs it into the AI ​​model. The generated advertisements are digital advertisements that include customized elements. The scaled personal data and original image advertisements are input, and the generated personalized advertisements are obtained as output.

[0559] Step 5:

[0560] The server delivers the generated personalized advertisement to the user's device. The generated advertisement is sent directly from the server to the user's smartphone or tablet and displayed in the device's display area. The generated advertisement data is the input, and the advertisement displayed on the user's device is the output.

[0561] Step 6:

[0562] The device collects user action data (clicks, viewing time, purchases, etc.). When a user responds to an advertisement, the response data is recorded on the device and sent to the server at regular intervals. User operations are input, and the collected action data is sent to the server as output.

[0563] Step 7:

[0564] The server analyzes the collected action data. The server receives this data and stores it in a database. Then, it uses ad generation AI to analyze this data and adjust the parameters of the ad generation process. The input is user action data, and the output is optimized ad generation parameters.

[0565] Step 8:

[0566] The server then uses the optimized parameters to execute the ad generation process from the next time onward, which makes the next ad more effective. By repeating all steps, the effectiveness of the ad is continuously improved. The optimized parameters are the input, and an effective ad generation process is executed as the output.

[0567] 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.

[0568] This invention combines an emotion engine with a system that generates and delivers personalized advertisements based on a user's personal data. The emotion engine recognizes the user's emotions and can further optimize advertisements based on that information.

[0569] 1. Collection of personal data and personal emotional data

[0570] The server collects personal data provided by the user (such as age, gender, occupation, and hobbies). This data includes not only the information the user enters when registering an account, but also subsequent website browsing and purchase history.

[0571] Furthermore, the device is equipped with an emotion engine that recognizes emotions by analyzing the user's facial expressions, voice, behavior, etc. The emotion engine captures the user's reactions while viewing advertisements and generates emotion data in real time.

[0572] Examples:

[0573] When registering, the user (Tanaka) enters his age, gender, occupation, and hobbies. When Tanaka watches a video advertisement while using his smartphone, the device's camera and microphone are used to analyze his facial expressions and voice, and an emotion engine recognizes his emotions, such as "interest" or "discomfort."

[0574] 2. Data storage and management

[0575] This data is stored in a database. The server updates the collected personal data and emotional data as needed to keep them up to date. This allows the user's profile to always reflect the most up-to-date information.

[0576] 3. Management of original image ads

[0577] The server receives and stores original image advertisements provided by advertisers, which are the basis for generating advertisements and are used to generate personalized advertisements.

[0578] Examples:

[0579] Advertiser A sends the original image advertisement for the music player to the server, which stores it in the advertisement database and records related metadata (such as the target age group).

[0580] 4. Generating personalized ads

[0581] The server runs an ad generation AI based on the collected personal data and original image ads. This AI analyzes the user's age, gender, occupation, hobbies, and even emotional data, and automatically generates the most suitable ad for each user based on that data.

[0582] Examples:

[0583] The server analyzes Tanaka's age, gender, occupation, and hobbies to determine his interest in music equipment. It then takes his emotional data (facial expressions and voice indicating interest) into account to customize ads for the music player. The ads include Tanaka's name and emotionally relevant copy.

[0584] 5. Delivery of advertisements

[0585] The generated personalized advertisements are delivered from the server to the user's device, either in real time or at a specific time.

[0586] Examples:

[0587] The server sends a personalized music player advertisement to Tanaka's smartphone, which displays the advertisement on his home screen and browser.

[0588] 6. Feedback Collection and Analysis

[0589] When a user responds to an ad (clicks, purchases, viewing time, etc.), that data is sent from the device to the server. The server analyzes this feedback data and adjusts the parameters of the ad generation AI to reflect this in future ad generation.

[0590] Examples:

[0591] When Tanaka clicks on the ad, that information is sent from his smartphone to the server. The emotion engine also records how Tanaka felt about the ad. The server uses this information to optimize the AI ​​algorithm for the next ad generation.

[0592] summary

[0593] This system maximizes the effectiveness of advertising by generating and delivering personalized advertisements based on the user's personal and emotional data. The collection and analysis of feedback data and emotional data enables continuous optimization of the advertisement generation process.

[0594] The processing flow will be explained below.

[0595] Step 1:

[0596] The server collects personal data provided by the user, specifically basic information such as age, gender, occupation, and hobbies that the user enters when registering an account.

[0597] Step 2:

[0598] The device collects and transmits data about the user's daily activities, including website browsing history, purchase history, and click information, to a server.

[0599] Step 3:

[0600] The server stores the collected personal and behavioral data in a database that is regularly updated to keep this data up to date.

[0601] Step 4:

[0602] The device uses an emotion engine to collect user emotion data, which is recognized in real time based on the user's facial expressions, voice, and behavior.

[0603] Step 5:

[0604] The device sends the collected emotional data to a server, including the user's reactions while watching the advertisement.

[0605] Step 6:

[0606] The server receives original image advertisements from advertisers and stores them in an advertisement database, along with metadata about the target demographic and advertisement content.

[0607] Step 7:

[0608] The server runs an ad generation AI based on the collected personal data, behavioral data, and emotional data, and the AI ​​generates ads optimized for each user.

[0609] Examples:

[0610] The server analyzes Tanaka's age, gender, occupation, and hobbies to determine his interest in music. It also uses emotional data to detect facial expressions that indicate Tanaka's interest in music player ads. It then generates a music player ad tailored to him, adding text that reflects Tanaka's name and emotions.

[0611] Step 8:

[0612] The server then delivers the generated personalized advertisement to Tanaka's device. The advertisement may be delivered in real time or at a specific time.

[0613] Step 9:

[0614] The device then displays the received personalized advertisements, which can appear on the home screen or in a web browser for easy user access.

[0615] Step 10:

[0616] Users respond to the displayed advertisements by clicking or purchasing, etc., which generates feedback data.

[0617] Step 11:

[0618] The terminal transmits user feedback data to the server, including whether or not an ad was clicked, viewing time, purchase information, and so on.

[0619] Step 12:

[0620] The server analyzes the received feedback data. The analysis results are used to optimize the parameters of the ad generation AI. This is reflected in subsequent ad generation, enabling continuous optimization of ad effectiveness.

[0621] By executing the above steps in order, a system is realized that generates and delivers personalized advertisements based on the user's personal data and emotional data.

[0622] Example 2

[0623] 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."

[0624] Conventional advertising delivery systems typically personalize advertisements based on users' personal data, but these systems do not take into account users' emotions or real-time responses, limiting the effectiveness of the advertisements. Furthermore, advertisement generation is often insufficient for individual users, failing to reflect users' preferences and interests. The present invention aims to improve advertising effectiveness and user experience by collecting and analyzing users' emotional data and generating and delivering optimized advertisements based on that data.

[0625] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting personal data and emotional data of users, means for storing the personal data and emotional data in a database, means for receiving and storing original image advertisements from advertisement providers, means for generating advertisements optimized for each user using a generative AI model based on the personal data, emotional data, and original image advertisements, means for delivering the generated advertisements to the user's information processing device, and means for displaying the generated advertisements on the information processing device. This makes it possible to generate and deliver highly optimized personalized advertisements that take into account the user's emotions and real-time reactions.

[0626] "User" means any person or legal entity that accesses the System and provides Personal Data or other information.

[0627] "Personal Data" refers to personal information about a user, such as age, gender, occupation, and hobbies.

[0628] "Emotional data" refers to data on the emotional state analyzed based on the user's facial expressions, voice, behavior, etc.

[0629] A "database" is a system for storing, managing, and searching collected data.

[0630] "Advertiser" means an individual or corporation that provides advertisements to promote its products or services.

[0631] "Original image advertisement" refers to the image or video file that serves as the basic data for the advertisement provided by the advertisement provider.

[0632] A "generative AI model" is an artificial intelligence algorithm that analyzes a user's personal and emotional data to generate optimized advertisements.

[0633] "Information processing device" refers to electronic devices such as computers, smartphones, and tablets that are the target of advertisement delivery.

[0634] "Optimized advertising" refers to advertising that is customized and delivered effectively based on the user's personal and emotional data.

[0635] "Response data" refers to behavioral data such as clicks, purchases, and viewing time shown by users in response to advertisements.

[0636] "Personalization" refers to the inclusion of a user's name, preferences, or other personally unique elements within an advertisement.

[0637] The present invention relates to a system for generating and distributing personalized advertisements based on personal data and emotional data of users. Specific embodiments of the invention using various hardware and software are described below.

[0638] Data collection

[0639] The server has the function of collecting personal data provided by users (such as age, gender, occupation, and hobbies). Users access the system and input their personal data, which is then stored in a database by the server. The server also records website browsing history and purchase history.

[0640] Examples:

[0641] When a user enters their age, gender, occupation, and hobbies on the registration page and clicks the submit button, this information is sent to the server and stored in a database, which uses MySQL to manage this data.

[0642] Collecting Emotional Data

[0643] The device is equipped with an emotion engine that analyzes the user's facial expressions, voice, and behavior. This emotion engine recognizes the user's emotions in real time and generates data. The emotion data is sent to a server and stored in a database along with personal data.

[0644] Examples:

[0645] When a user watches an advertisement on their smartphone, the device's camera and microphone capture their facial expressions and voice, allowing emotions such as "interest" or "discomfort" to be recognized in real time and sent to a server.

[0646] Managing advertising data

[0647] The server receives the original image advertisements provided by the advertisement providers and stores them in the advertisement database. In addition, the target attributes of the advertisements (such as age group and region) are also recorded as metadata.

[0648] Examples:

[0649] When an advertisement provider sends an original image advertisement for a music player through an upload interface, the server receives it and stores it in a database.

[0650] Generating personalized ads

[0651] The server runs a generative AI model based on the collected personal and emotional data to generate optimized advertisements for each user. This process involves analyzing the collected data and customizing advertisements according to the user's preferences and emotions.

[0652] Example prompt sentence:

[0653] "Create an ad for a music player targeted to a user who is 30 years old, male, an engineer by profession, and whose hobby is listening to music, and who has shown interest in the product."

[0654] Ad serving

[0655] The generated personalized advertisement is delivered from the server to the information processing device. The advertisement may be delivered in real time or at a specific timing, and displayed on the user's terminal.

[0656] Examples:

[0657] The server sends personalized music player advertisements to the user's smartphone, which displays the advertisements on the home screen or browser.

[0658] Collecting and analyzing feedback

[0659] The user's response to the ad (clicks, purchases, viewing time, etc.) is sent from the device to the server, which analyzes the feedback data and optimizes the AI ​​model to reflect this in future ad generation.

[0660] Examples:

[0661] When a user clicks on an ad, the information is sent to the server in real time, and emotional data is also recorded, allowing the analysis system to update the parameters of the AI ​​model.

[0662] This system utilizes users' personal data and real-time emotional data to generate and deliver more effective and personalized advertisements, thereby maximizing the effectiveness of advertisements and improving the user experience.

[0663] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0664] Step 1: Collecting your personal data

[0665] A user accesses the system and inputs personal data such as age, gender, occupation, and hobbies. The server receives this input data and stores it in a database. Specific operations include the user entering data into a registration form and pressing the submit button. Based on the input data, the server prepares the data format to be saved in the database and stores it in the database.

[0666] Input: Data entered by the user, such as age, gender, occupation, hobbies, etc.

[0667] Output: User's personal data stored on the server

[0668] Step 2: Collecting website browsing and purchase history

[0669] The server records information about the pages viewed and the products purchased each time a user visits a website. Specifically, the server records the information in a log when a user's browsing actions occur, thereby collecting website action data in real time.

[0670] Input: User browsing and purchase history

[0671] Output: Browsing and purchase history data stored on the server

[0672] Step 3: Collecting emotion data

[0673] The emotion engine built into the device analyzes the user's facial expressions, voice, and behavior in real time to generate emotional data. The camera and microphone capture the user's reactions while viewing advertisements, and the data is analyzed to identify emotions such as "interest" or "discomfort." The analyzed emotional data is then sent to a server.

[0674] Input: User's facial expressions, voice, and actions captured by the device

[0675] Output: User emotion data sent to the server

[0676] Step 4: Store and manage your data

[0677] The server stores and manages the collected personal data, browsing history, purchase history, and emotional data in a database. The data is stored while maintaining consistency to prevent duplication or loss of data. The data is updated regularly to reflect the latest information.

[0678] Input: Collected personal data, browsing history, purchase history, emotional data

[0679] Output: The latest data stored in the database

[0680] Step 5: Receive and save the original image ad

[0681] The server receives original image advertisements provided by advertisement providers and stores them in an advertisement database. It also records the received advertisements along with related metadata (such as target age group). Specific operations include uploading advertisement files and inputting their metadata.

[0682] Input: Original image ad and metadata uploaded by the ad provider

[0683] Output: Original image ads and metadata stored in the ads database

[0684] Step 6: Generate personalized ads

[0685] The server runs a generative AI model based on the collected personal data, emotional data, and original image advertisements. The generative AI model receives a prompt sentence for the user's data as input, and generates an advertisement optimized for each user based on that data. Specifically, the AI ​​model inputs the prompt sentence, "Please create an advertisement for a music player for a user who is 30 years old, male, an engineer by profession, whose hobby is listening to music, and who has shown an interest in the advertisement."

[0686] Input: Personal data, emotion data, original image advertisement, prompt sentence

[0687] Output: Generated personalized ad

[0688] Step 7: Serving Ads

[0689] The generated personalized advertisement is delivered from the server to the user's information processing device. Delivery can be in real time or at a specific timing, and the advertisement is displayed on the terminal. Specific operations include the server sending the advertisement to the terminal, and the terminal displaying the advertisement on the home screen or browser.

[0690] Input: Generated personalized ads

[0691] Output: Advertisement delivered to and displayed on the user's device

[0692] Step 8: Collect and analyze feedback

[0693] The device records the user's response to the ad (clicks, purchases, viewing time, etc.) and sends it to the server. The server analyzes this feedback data and adjusts the parameters of the AI ​​model to reflect this in future ad generation.

[0694] Input: User response data to advertisements

[0695] Output: Optimized ad generation parameters from the updated generative AI model

[0696] (Application example 2)

[0697] 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."

[0698] While existing personalized advertising systems have made progress in generating ads based on basic user personal data (such as age, gender, and hobbies), they lack the technology to utilize emotional data to optimize ads in real time. This has resulted in the inability to display ads that respond immediately to user emotions, limiting the effectiveness of ads. Furthermore, while existing ad delivery systems can collect user responses as feedback, they are also problematic in that they do not quickly adjust ad generation based on that feedback.

[0699] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting personal data of users, means for saving the personal data in a database, means for receiving and saving original image advertisements from advertisers, means for generating advertisements optimized for each user based on the personal data and the original image advertisements, means for collecting user emotion data in real time, means for further optimizing advertisements based on the personal data and the emotion data, means for delivering the generated advertisements to the user's terminal, and means for displaying the generated advertisements on the terminal. This makes it possible to optimize advertisements based on the user's real-time emotions, thereby maximizing the effectiveness of advertisements.

[0700] "User" means an individual or organization that uses the system.

[0701] "Personal Data" refers to personal information about the user (age, gender, occupation, hobbies, etc.).

[0702] "Database" means a digital storage system for storing collected personal data and other information.

[0703] An "advertiser" is a company or organization that distributes advertisements and promotes specific products or services.

[0704] "Original image advertisement" refers to basic image data of an advertisement provided by an advertiser, and is the basis for generating a personalized advertisement.

[0705] "Optimized ads" are ads that are customized based on the user's personal and emotional data.

[0706] "Emotion data" is information about emotions acquired from the user's facial expressions, voice, etc.

[0707] "Real-time" means that data is collected immediately and processed on the spot.

[0708] "Terminal" refers to a device (e.g., smartphone, smart glasses, etc.) used to display advertisements.

[0709] "Display means" refers to a method or device for displaying the generated advertisement to a user.

[0710] The present invention provides a system for generating and distributing personalized advertisements using personal data and emotional data of users. Specific embodiments are described below.

[0711] 1. Collection of Personal Data

[0712] The server collects personal data provided by the user (such as age, gender, occupation, hobbies, etc.) This data collection includes not only the information the user enters when registering an account, but also subsequent website browsing history and purchase history.

[0713] 2. Real-time collection of emotional data

[0714] The device (e.g., smart glasses) analyzes the user's facial expressions and voice to collect emotional data in real time. This emotional data is captured using the device's camera and microphone and sent to a server.

[0715] 3. Data storage and management

[0716] The server stores the collected personal data and emotion data in a database, which is kept up to date. The database also stores original image advertisements provided by advertisers.

[0717] 4. Generating personalized ads

[0718] The server uses a generative AI model to generate ads based on the user's personal and emotional data. This process takes into account the user's age, gender, occupation, hobbies, and even real-time emotional data. The generated ads contain content optimized for the user.

[0719] 5. Delivery and display of advertisements

[0720] The generated advertisements are delivered from the server to the device and displayed on the device. In the case of smart glasses, the advertisements are displayed directly in the user's field of vision, while in the case of smartphones, the advertisements are displayed on the home screen or browser.

[0721] 6. Feedback Collection and Analysis

[0722] The user's reactions to the ad (clicks, viewing time, etc.) are collected along with emotional data and sent to the server, which analyzes this feedback data and adjusts the parameters of the generative AI model to reflect this in the next ad generation.

[0723] Hardware and software used

[0724] Hardware: Smart glasses (with camera, microphone, and display), smartphone

[0725] Software: Python, EmotionRecognition library, OpenCV, generative AI model (e.g., GPT-3)

[0726] Specific examples

[0727] For example, if a user is a 30-year-old male engineer who is interested in music players, and the camera in the smart glasses recognizes that his facial expression looks happy, the server will send the following prompt sentence to the generative AI model to generate an advertisement:

[0728] Prompt Sentence Examples

[0729] "A 30-year-old male engineer is interested in music players. He currently has a happy expression. Please generate personalized ads for the best music equipment for this user."

[0730] This system maximizes the effectiveness of advertising by displaying the most suitable and interesting advertisements to users in real time.

[0731] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0732] Step 1:

[0733] The user inputs personal data. The user inputs personal data such as age, gender, occupation, and hobbies using smart glasses or a smartphone. This data is sent from the device to the server, which then stores the data in a database. Input data (e.g., age, gender) → Data stored in the database

[0734] Step 2:

[0735] The device collects emotion data. If the user is wearing smart glasses, the camera and microphone are used to collect facial expressions and voice in real time. This data is analyzed using the EmotionRecognition library to generate emotion data. Input data (e.g., video, audio) → Output data (e.g., emotion data)

[0736] Step 3:

[0737] The server manages the database. Collected personal data and emotional data are stored in the database and updated as needed. The server manages this database and always keeps the latest information. Input data (e.g., personal data, emotional data) → Latest database

[0738] Step 4:

[0739] Receive original image ads from advertisers. The server receives original image ads provided by advertisers and stores them in a database. During this process, the ad metadata is also stored. Input data (e.g. original image ads) → Stored ad data

[0740] Step 5:

[0741] The server generates personalized ads. Using a generative AI model (e.g., GPT-3), the server generates customized ads based on the collected personal data and emotional data. When generating ads, a prompt sentence is input into the generative AI model. Prompt sentence (e.g., "A 30-year-old male engineer is interested in music players. He currently has a happy expression. Please generate a personalized ad for music equipment that is best suited to this user.") → Personalized ads

[0742] Step 6:

[0743] The server delivers the generated personalized advertisement to the user's device (smart glasses or smartphone). Input data (e.g., personalized advertisement) → Delivered advertisement

[0744] Step 7:

[0745] The advertisement is displayed on the device. The user's device displays the received personalized advertisement. In the case of smart glasses, the advertisement is displayed directly in the user's field of vision. Input data (e.g., delivered advertisement) → Displayed advertisement

[0746] Step 8:

[0747] The user responds to the ad. The user clicks on the ad and the viewing time is measured. The feedback data collected during this process is sent from the device to the server. Input data (e.g., user's ad response) → Feedback data

[0748] Step 9:

[0749] The server analyzes the feedback data. The collected feedback data is analyzed by the server, and the parameters of the generative AI model are adjusted and reflected in the next ad generation. Input data (e.g., feedback data) → Adjusted generative AI model

[0750] As a result, advertisements are optimized based on the user's real-time emotions, making it possible to maximize the effectiveness of the advertisements.

[0751] 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.

[0752] 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.

[0753] 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.

[0754] [Third embodiment]

[0755] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0756] 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.

[0757] 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).

[0758] 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.

[0759] 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.

[0760] 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).

[0761] 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.

[0762] 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.

[0763] 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.

[0764] 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.

[0765] 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.

[0766] 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."

[0767] This invention relates to a system that generates and delivers personalized advertisements based on a user's personal data. This system includes AI that generates advertisements optimized for each user, and can improve advertisement click rates and conversion rates. Below, the program processing of this system is explained in natural language with specific examples.

[0768] 1. Collection and storage of personal data

[0769] The server collects personal data provided by the user (such as age, gender, occupation, and hobbies), including information entered by the user at the time of registration, subsequent website browsing history, and purchase history.

[0770] Examples:

[0771] When registering, the user (Tanaka) enters his / her age, gender, occupation, and hobbies. Tanaka's browsing history and purchase history of the websites he / she uses are also periodically sent to the server.

[0772] The server stores this data in a database, which is updated as needed to keep the data up to date.

[0773] 2. Management of original image ads

[0774] The server receives and stores original image advertisements provided by advertisers, which serve as the basis for generating personalized advertisements.

[0775] Examples:

[0776] Advertiser A sends the original image advertisement for the music player to the server, which stores it in the advertisement database and records related metadata (such as the target age group).

[0777] 3. Generating personalized ads

[0778] The server runs an ad generation AI to generate the optimal ad for each user based on the collected personal data and the original image ad. This AI considers the user's individual data and automatically generates the ad that best suits the specific user.

[0779] Examples:

[0780] The server generates an advertisement for a music player that is best suited to Tanaka, who is interested in music, based on Tanaka's age, gender, occupation, and hobbies. The advertisement includes content customized to Tanaka's name and preferences.

[0781] 4. Delivery of advertisements

[0782] The generated personalized advertisement is delivered from the server to the user's terminal, which receives and displays the advertisement.

[0783] Examples:

[0784] The server sends a personalized music player advertisement to Tanaka's smartphone, which displays the advertisement on his home screen and browser.

[0785] 5. Feedback collection and analysis

[0786] Information on users' reactions to ads (clicks, purchases, viewing time, etc.) is sent from the device to the server, which analyzes this feedback data and adjusts the parameters of the ad generation AI to continuously optimize the effectiveness of the ads.

[0787] Examples:

[0788] When Tanaka clicks on the displayed ad, the information is sent from his smartphone to the server, which analyzes Tanaka's click information and reflects it in the generation of the next ad.

[0789] summary

[0790] This system maximizes the effectiveness of advertising by generating personalized advertisements based on users' personal data and delivering them to their devices. The collection and analysis of feedback data also enables continuous optimization of the advertisement generation process.

[0791] The processing flow will be explained below.

[0792] Step 1:

[0793] The server collects personal data provided by the user, including basic information (age, gender, occupation, hobbies, etc.) entered by the user when registering an account. The server also collects the user's website browsing history and purchase history for analysis.

[0794] Step 2:

[0795] Terminals are devices (smartphones, tablets, PCs, etc.) that users use on a daily basis, and these devices periodically send user behavior data to a server. This data includes browsing history, purchase history, click information, etc.

[0796] Step 3:

[0797] The server stores the collected data in a database, including basic information about the user and their behavioral data, and updates the database accordingly to keep the user's profile information up to date.

[0798] Step 4:

[0799] The server receives and stores original image advertisements from advertisers. These images are stored in an advertisement database and managed as basic data for generating personalized advertisements.

[0800] Step 5:

[0801] The server runs an ad generation AI based on personal data and the original image ad. The AI ​​analyzes personal data such as the user's age, gender, occupation, and hobbies, and automatically generates the most suitable ad for each user based on that data.

[0802] Step 6:

[0803] The server then delivers the generated personalized advertisement to the user's device, either in real time or at a specific time.

[0804] Step 7:

[0805] The device then displays the received personalized advertisements to the user, primarily on the home screen or in a web browser or other interface, providing the advertisements in a format that is easy for the user to access.

[0806] Step 8:

[0807] Users respond to the displayed advertisements by clicking, purchasing, etc. These responses are recorded as feedback data.

[0808] Step 9:

[0809] The device sends user response data to the server, including whether or not the ad was clicked, the viewing time, and information about purchases made through the ad.

[0810] Step 10:

[0811] The server analyzes the received feedback data. The results of this analysis are used to adjust the ad generation AI algorithm and are used for subsequent ad generation. This makes it possible to continuously optimize the effectiveness of ads.

[0812] summary

[0813] Through these steps, the server generates personalized advertisements based on the user's personal data and delivers them to the user's device. The device displays the advertisements and sends back user response data to the server, realizing a system that continuously improves the effectiveness of advertisements.

[0814] Example 1

[0815] 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."

[0816] Conventional ad delivery systems have had difficulty effectively generating and delivering ads tailored to individual users' needs and preferences. As a result, ad click-through rates and conversion rates have fallen, resulting in insufficient advertising effectiveness. Furthermore, the inability to effectively analyze user feedback and reflect it in ad generation has also led to delays in ad optimization.

[0817] 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.

[0818] In this invention, the server includes means for collecting personal information of users, means for storing the personal information in a database, means for receiving and storing original image advertisements from advertisement providers, means for generating advertisements optimized for individual users based on the personal information and original image advertisements, means for delivering the generated advertisements to the users' display devices, means for displaying the generated advertisements on the display devices, and means for collecting and storing the users' website browsing history and purchase history in a database. This makes it possible to effectively generate and deliver advertisements tailored to the individual needs and preferences of users. Furthermore, by collecting user response data and feeding it back to the advertisement generation means, continuous optimization of advertisements can be achieved, thereby improving advertising effectiveness.

[0819] "User" means an individual or organization that receives advertisements and provides personal data.

[0820] "Personal Information" refers to personal data provided by the User, such as age, gender, occupation, and hobbies.

[0821] The term "database" refers to an electronic storage device for storing personal information, website browsing history, purchase history, and original image advertisements collected by the server.

[0822] An "advertising provider" is a company or organization that provides advertisements and is responsible for transmitting original image advertisements to the server.

[0823] "Original image advertisement" refers to the basic advertisement image sent by the advertisement provider and stored on the server.

[0824] "Optimized advertising" refers to advertising that is customized based on a user's personal information, website browsing history, and purchase history, and is tailored to best suit the user.

[0825] A "display device" is an electronic device used by a user, such as a computer, smartphone, or tablet, that is used to display the generated advertisement.

[0826] "Website browsing history" refers to the URLs of websites visited by a user and information about the pages viewed.

[0827] "Purchase History" refers to a record of purchase transactions made by a User online or offline.

[0828] "Response data" refers to information about actions taken by users in response to advertisements, such as clicking, viewing, or purchasing.

[0829] "Advertising generation means" refers to the algorithms and software used to generate optimized advertisements based on collected personal information and original image advertisements.

[0830] This invention relates to a system that generates and delivers personalized advertisements based on a user's personal information. This system includes an advertisement generation AI for generating advertisements optimized for each user, and can improve advertisement click rates and conversion rates. Below, we will explain how this system is specifically implemented.

[0831] First, the server collects personal information provided by the user and stores it in a database. This includes personal data such as the user's age, gender, occupation, and hobbies. The user's website browsing history and purchase history are also periodically collected and stored in a database. This personal data is used to understand the user's behavioral patterns and interests.

[0832] The server then receives and stores the original image advertisements sent by the advertisement providers. These original image advertisements contain metadata such as target age groups. The server stores the original image advertisements in an advertisement database and uses them in combination with the user's personal data.

[0833] The server runs an ad generation AI to generate optimal ads for each user based on the collected personal data and original image ads. This AI considers the user's individual data and automatically generates ads that are best suited to the specific user. For example, for a user who is interested in music, it generates music-related ads and generates ads with content customized to the user's name and preferences.

[0834] The generated personalized advertisements are delivered from the server to the user's device. The device receives the advertisements and displays them on a display device (smartphone, tablet, computer, etc.). The user can view these advertisements on their home screen or browser.

[0835] Furthermore, information on users' reactions to ads (clicks, purchases, viewing time, etc.) is sent from the device to the server. The server analyzes this feedback data and adjusts the parameters of the ad generation AI, thereby continuously optimizing the effectiveness of ads.

[0836] Examples:

[0837] A user (Tanaka) sees an advertisement for a new music player. Based on the age (29), gender (male), occupation (engineer), and hobby (listening to music) provided by Tanaka when he registered, the server generates an advertisement for the music player that best suits him. The server also takes into account Tanaka's website browsing history and purchase history to generate a customized advertisement. The advertisement includes Tanaka's name and content tailored to his preferences.

[0838] Example prompt sentence:

[0839] "Generate the best music player ad for Mr. Tanaka, a 29-year-old engineer who is interested in music."

[0840] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0841] Step 1:

[0842] The server collects the user's personal information and stores it in a database.

[0843] input:

[0844] Personal data provided by the user (age, gender, occupation, hobbies)

[0845] Specific behavior:

[0846] The user enters personal information into a registration form. The device sends this data to the server, which receives it and stores it in a database.

[0847] output:

[0848] User personal information stored in a database

[0849] Step 2:

[0850] The server collects the user's website browsing history and purchase history and stores it in a database.

[0851] input:

[0852] User browsing history and purchase history

[0853] Specific behavior:

[0854] When a user browses a website or makes a purchase, the device sends this history data to the server, which stores it in a database.

[0855] output:

[0856] Browsing and purchasing history stored in a database

[0857] Step 3:

[0858] The server receives and stores original image advertisements from advertisement providers.

[0859] input:

[0860] Original image ads and metadata (such as target demographics) sent by ad providers

[0861] Specific behavior:

[0862] Advertisers send original image ads to the server, which receives the ads and metadata and stores them in an ad database.

[0863] output:

[0864] Original image ads and metadata stored in the ad database

[0865] Step 4:

[0866] The server runs an ad generation AI to generate optimal ads for each user based on the collected personal data and original image ads.

[0867] input:

[0868] Personal information, website browsing history, purchase history, and original image ads

[0869] Specific behavior:

[0870] The server inputs personal information and original image ads into the ad generation AI, which then generates the most suitable ad for the user based on this data. This process involves customization based on names and preferences.

[0871] output:

[0872] Customized advertising for each user

[0873] Step 5:

[0874] The server delivers the generated personalized advertisement to the user's terminal.

[0875] input:

[0876] Generated personalized ads

[0877] Specific behavior:

[0878] The server transmits the generated advertisement to the user's terminal, and the terminal displays the received advertisement on a display device.

[0879] output:

[0880] Personalized advertisements displayed on a user's display device

[0881] Step 6:

[0882] The server collects data on users' responses to advertisements and analyzes it as feedback data.

[0883] input:

[0884] User response data to ads (clicks, purchases, viewing time, etc.)

[0885] Specific behavior:

[0886] When a user clicks on an ad or makes a purchase, the device sends the response data to the server, which analyzes the received feedback data and adjusts the parameters of the ad generation AI.

[0887] output:

[0888] Analyzed feedback data and adjusted ad generation AI parameters

[0889] (Application example 1)

[0890] 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."

[0891] Conventional advertising distribution systems can generate advertisements based on users' personal data, but they face the challenge of measuring the effectiveness of advertisements in real time and reflecting this in the next advertisement generation process. Another problem is that advertisements are not optimized sufficiently because user response data is not fully utilized. The present invention aims to solve this problem by providing a system that collects and analyzes user action data in real time and optimizes the advertisement generation process.

[0892] 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.

[0893] In this invention, the server includes: means for collecting user personal data; means for storing the personal data in a database; means for receiving and storing original image advertisements from advertisers; means for generating advertisements optimized for each user based on the personal data and the original image advertisements; means for delivering the generated advertisements to user terminals; means for displaying the generated advertisements on the terminals; means for collecting user action data (clicks, purchases, etc.) based on the generated advertisements; and means for analyzing the collected user action data using an advertisement generation AI and optimizing the advertisement generation process. This makes it possible to collect and analyze user response data in real time and reflect it in the next advertisement generation process, thereby continuously optimizing the effectiveness of advertisements.

[0894] "Personal data" refers to data that indicates a user's individual characteristics and behavior, such as age, gender, occupation, hobbies, browsing history, and purchase history.

[0895] A "database" is a system for efficiently storing, managing, and searching collected personal data and advertising data.

[0896] "Original image advertisement" refers to advertising material provided by an advertiser and serving as the basis for generating personalized advertisements.

[0897] "Advertising generation AI" is an artificial intelligence system that generates optimal advertisements for each user based on the user's personal data and the original image advertisement.

[0898] "Action data" is data that indicates the user's response to an advertisement (click, purchase, etc.).

[0899] The "advertising generation process" is a series of steps that generate and deliver individually optimized advertisements based on personal data and original image advertisements.

[0900] "Optimization" refers to adjusting the parameters of the ad generation AI based on collected data to maximize ad click-through rates and conversion rates.

[0901] A "terminal" is a device, such as a smartphone, tablet, or PC, that a user uses to receive and display advertisements.

[0902] "Server" means a central computer system that collects, stores, analyzes data, and generates advertisements.

[0903] "Delivery" refers to sending the generated advertisement to the user's terminal.

[0904] The present invention relates to a system for generating and distributing personalized advertisements based on personal data of users. Specific embodiments of the present invention will be described below.

[0905] Collection and storage of personal data

[0906] The server collects personal data provided by users (age, gender, occupation, hobbies, browsing history, purchase history, etc.) and stores it in a database. This data is updated periodically based on user behavior to keep it up to date. The main hardware used is a server computer and user devices (smartphones, tablets, etc.). Software includes Flask (web framework), SQLite (database management system), and Pandas (data processing library). For example, when a user enters their age, gender, occupation, and hobbies during registration, this information is sent to the server and stored in the database.

[0907] Management of original image ads

[0908] The server receives raw image advertisements provided by advertisers and stores them in an advertisement database. This includes data about the image itself and associated metadata (such as the target demographic). The primary hardware used is a server computer, and the software includes Flask and SQLite. For example, an advertiser may send an advertisement image for a new music player to the server, and this data is stored in the advertisement database.

[0909] Generating personalized ads

[0910] The server uses an ad generation AI to generate optimal ads for each user based on the collected personal data and the original image ads. This ad generation AI is built using machine learning libraries such as TensorFlow and Keras. As a preprocessing step, the data is scaled using Scikit-learn's StandardScaler. For example, the server generates a customized ad based on a specific user's age, gender, occupation, and hobbies, and this ad is input to the AI ​​model in the prompt text: "User's age: 35, gender: male, occupation: engineer, hobbies: music. Please generate the optimal music player ad for this user."

[0911] Ad delivery and display

[0912] The generated personalized ads are delivered in real time from the server to the user's device, where they are displayed. The main hardware used is a server computer and the user's device, and the ads are delivered via Flask. The ads are displayed in the browser or app on the user's smartphone or tablet.

[0913] Collecting and analyzing user action data

[0914] Data on users' responses to ads (clicks, purchases, etc.) is sent from the device to the server. The server analyzes this feedback data and adjusts the parameters of the ad generation AI to optimize the next ad generation process. This process uses Flask, SQLite, and machine learning libraries such as TensorFlow and Keras. For example, when a user clicks on a displayed ad, that information is sent from the device to the server and analyzed.

[0915] Through these steps, it becomes possible to generate and deliver ads optimized for each user in real time, and to continuously optimize their effectiveness. This system not only improves ad click rates and conversion rates, but also provides advertisers with an efficient marketing method.

[0916] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0917] Step 1:

[0918] The server collects personal data from users. When users register, they enter information such as age, gender, occupation, and hobbies, and send it to the server. The server receives this data and stores it in a database. In this process, the information entered by the user is the input, and the organized personal data is stored in the database as the output.

[0919] Step 2:

[0920] The server continuously collects additional data, such as the user's website browsing history and purchase history, thereby improving the accuracy of the personal data. This data is sent from the user's device to the server at regular intervals. The server updates the database by adding this new data to the existing personal data. The input is the user's behavioral data, and the output is the updated personal data stored in the database.

[0921] Step 3:

[0922] The server receives original image advertisements from advertisers and stores them in the advertisement database. The advertiser sends the original image advertisements and their targeting metadata (e.g., target age group and interest categories) to the server. The server organizes the received data and stores it in the advertisement database. The advertisement database has the data provided by the advertiser as input and the saved original image advertisement as output.

[0923] Step 4:

[0924] The server generates personalized advertisements. This is done by running an advertisement generation AI using the collected personal data and original image advertisements. To generate advertisements optimized for each user, the server first scales the personal data, then combines it with the original image advertisements and inputs it into the AI ​​model. The generated advertisements are digital advertisements that include customized elements. The scaled personal data and original image advertisements are input, and the generated personalized advertisements are obtained as output.

[0925] Step 5:

[0926] The server delivers the generated personalized advertisement to the user's device. The generated advertisement is sent directly from the server to the user's smartphone or tablet and displayed in the device's display area. The generated advertisement data is the input, and the advertisement displayed on the user's device is the output.

[0927] Step 6:

[0928] The device collects user action data (clicks, viewing time, purchases, etc.). When a user responds to an advertisement, the response data is recorded on the device and sent to the server at regular intervals. User operations are input, and the collected action data is sent to the server as output.

[0929] Step 7:

[0930] The server analyzes the collected action data. The server receives this data and stores it in a database. Then, it uses ad generation AI to analyze this data and adjust the parameters of the ad generation process. The input is user action data, and the output is optimized ad generation parameters.

[0931] Step 8:

[0932] The server then uses the optimized parameters to execute the ad generation process from the next time onward, which makes the next ad more effective. By repeating all steps, the effectiveness of the ad is continuously improved. The optimized parameters are the input, and an effective ad generation process is executed as the output.

[0933] 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.

[0934] This invention combines an emotion engine with a system that generates and delivers personalized advertisements based on a user's personal data. The emotion engine recognizes the user's emotions and can further optimize advertisements based on that information.

[0935] 1. Collection of personal data and personal emotional data

[0936] The server collects personal data provided by the user (such as age, gender, occupation, and hobbies). This data includes not only the information the user enters when registering an account, but also subsequent website browsing and purchase history.

[0937] Furthermore, the device is equipped with an emotion engine that recognizes emotions by analyzing the user's facial expressions, voice, behavior, etc. The emotion engine captures the user's reactions while viewing advertisements and generates emotion data in real time.

[0938] Examples:

[0939] When registering, the user (Tanaka) enters his age, gender, occupation, and hobbies. When Tanaka watches a video advertisement while using his smartphone, the device's camera and microphone are used to analyze his facial expressions and voice, and an emotion engine recognizes his emotions, such as "interest" or "discomfort."

[0940] 2. Data storage and management

[0941] This data is stored in a database. The server updates the collected personal data and emotional data as needed to keep them up to date. This allows the user's profile to always reflect the most up-to-date information.

[0942] 3. Management of original image ads

[0943] The server receives and stores original image advertisements provided by advertisers, which are the basis for generating advertisements and are used to generate personalized advertisements.

[0944] Examples:

[0945] Advertiser A sends the original image advertisement for the music player to the server, which stores it in the advertisement database and records related metadata (such as the target age group).

[0946] 4. Generating personalized ads

[0947] The server runs an ad generation AI based on the collected personal data and original image ads. This AI analyzes the user's age, gender, occupation, hobbies, and even emotional data, and automatically generates the most suitable ad for each user based on that data.

[0948] Examples:

[0949] The server analyzes Tanaka's age, gender, occupation, and hobbies to determine his interest in music equipment. It then takes his emotional data (facial expressions and voice indicating interest) into account to customize ads for the music player. The ads include Tanaka's name and emotionally relevant copy.

[0950] 5. Delivery of advertisements

[0951] The generated personalized advertisements are delivered from the server to the user's device, either in real time or at a specific time.

[0952] Examples:

[0953] The server sends a personalized music player advertisement to Tanaka's smartphone, which displays the advertisement on his home screen and browser.

[0954] 6. Feedback Collection and Analysis

[0955] When a user responds to an ad (clicks, purchases, viewing time, etc.), that data is sent from the device to the server. The server analyzes this feedback data and adjusts the parameters of the ad generation AI to reflect this in future ad generation.

[0956] Examples:

[0957] When Tanaka clicks on the ad, that information is sent from his smartphone to the server. The emotion engine also records how Tanaka felt about the ad. The server uses this information to optimize the AI ​​algorithm for the next ad generation.

[0958] summary

[0959] This system maximizes the effectiveness of advertising by generating and delivering personalized advertisements based on the user's personal and emotional data. The collection and analysis of feedback data and emotional data enables continuous optimization of the advertisement generation process.

[0960] The processing flow will be explained below.

[0961] Step 1:

[0962] The server collects personal data provided by the user, specifically basic information such as age, gender, occupation, and hobbies that the user enters when registering an account.

[0963] Step 2:

[0964] The device collects and transmits data about the user's daily activities, including website browsing history, purchase history, and click information, to a server.

[0965] Step 3:

[0966] The server stores the collected personal and behavioral data in a database that is regularly updated to keep this data up to date.

[0967] Step 4:

[0968] The device uses an emotion engine to collect user emotion data, which is recognized in real time based on the user's facial expressions, voice, and behavior.

[0969] Step 5:

[0970] The device sends the collected emotional data to a server, including the user's reactions while watching the advertisement.

[0971] Step 6:

[0972] The server receives original image advertisements from advertisers and stores them in an advertisement database, along with metadata about the target demographic and advertisement content.

[0973] Step 7:

[0974] The server runs an ad generation AI based on the collected personal data, behavioral data, and emotional data, and the AI ​​generates ads optimized for each user.

[0975] Examples:

[0976] The server analyzes Tanaka's age, gender, occupation, and hobbies to determine his interest in music. It also uses emotional data to detect facial expressions that indicate Tanaka's interest in music player ads. It then generates a music player ad tailored to him, adding text that reflects Tanaka's name and emotions.

[0977] Step 8:

[0978] The server then delivers the generated personalized advertisement to Tanaka's device. The advertisement may be delivered in real time or at a specific time.

[0979] Step 9:

[0980] The device then displays the received personalized advertisements, which can appear on the home screen or in a web browser for easy user access.

[0981] Step 10:

[0982] Users respond to the displayed advertisements by clicking or purchasing, etc., which generates feedback data.

[0983] Step 11:

[0984] The terminal transmits user feedback data to the server, including whether or not an ad was clicked, viewing time, purchase information, and so on.

[0985] Step 12:

[0986] The server analyzes the received feedback data. The analysis results are used to optimize the parameters of the ad generation AI. This is reflected in subsequent ad generation, enabling continuous optimization of ad effectiveness.

[0987] By executing the above steps in order, a system is realized that generates and delivers personalized advertisements based on the user's personal data and emotional data.

[0988] Example 2

[0989] 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."

[0990] Conventional advertising delivery systems typically personalize advertisements based on users' personal data, but these systems do not take into account users' emotions or real-time responses, limiting the effectiveness of the advertisements. Furthermore, advertisement generation is often insufficient for individual users, failing to reflect users' preferences and interests. The present invention aims to improve advertising effectiveness and user experience by collecting and analyzing users' emotional data and generating and delivering optimized advertisements based on that data.

[0991] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting personal data and emotional data of users, means for storing the personal data and emotional data in a database, means for receiving and storing original image advertisements from advertisement providers, means for generating advertisements optimized for each user using a generative AI model based on the personal data, emotional data, and original image advertisements, means for delivering the generated advertisements to the user's information processing device, and means for displaying the generated advertisements on the information processing device. This makes it possible to generate and deliver highly optimized personalized advertisements that take into account the user's emotions and real-time reactions.

[0992] "User" means any person or legal entity that accesses the System and provides Personal Data or other information.

[0993] "Personal Data" refers to personal information about a user, such as age, gender, occupation, and hobbies.

[0994] "Emotional data" refers to data on the emotional state analyzed based on the user's facial expressions, voice, behavior, etc.

[0995] A "database" is a system for storing, managing, and searching collected data.

[0996] "Advertiser" means an individual or corporation that provides advertisements to promote its products or services.

[0997] "Original image advertisement" refers to the image or video file that serves as the basic data for the advertisement provided by the advertisement provider.

[0998] A "generative AI model" is an artificial intelligence algorithm that analyzes a user's personal and emotional data to generate optimized advertisements.

[0999] "Information processing device" refers to electronic devices such as computers, smartphones, and tablets that are the target of advertisement delivery.

[1000] "Optimized advertising" refers to advertising that is customized and delivered effectively based on the user's personal and emotional data.

[1001] "Response data" refers to behavioral data such as clicks, purchases, and viewing time shown by users in response to advertisements.

[1002] "Personalization" refers to the inclusion of a user's name, preferences, or other personally unique elements within an advertisement.

[1003] The present invention relates to a system for generating and distributing personalized advertisements based on personal data and emotional data of users. Specific embodiments of the invention using various hardware and software are described below.

[1004] Data collection

[1005] The server has the function of collecting personal data provided by users (such as age, gender, occupation, and hobbies). Users access the system and input their personal data, which is then stored in a database by the server. The server also records website browsing history and purchase history.

[1006] Examples:

[1007] When a user enters their age, gender, occupation, and hobbies on the registration page and clicks the submit button, this information is sent to the server and stored in a database, which uses MySQL to manage this data.

[1008] Collecting Emotional Data

[1009] The device is equipped with an emotion engine that analyzes the user's facial expressions, voice, and behavior. This emotion engine recognizes the user's emotions in real time and generates data. The emotion data is sent to a server and stored in a database along with personal data.

[1010] Examples:

[1011] When a user watches an advertisement on their smartphone, the device's camera and microphone capture their facial expressions and voice, allowing emotions such as "interest" or "discomfort" to be recognized in real time and sent to a server.

[1012] Managing advertising data

[1013] The server receives the original image advertisements provided by the advertisement providers and stores them in the advertisement database. In addition, the target attributes of the advertisements (such as age group and region) are also recorded as metadata.

[1014] Examples:

[1015] When an advertisement provider sends an original image advertisement for a music player through an upload interface, the server receives it and stores it in a database.

[1016] Generating personalized ads

[1017] The server runs a generative AI model based on the collected personal and emotional data to generate optimized advertisements for each user. This process involves analyzing the collected data and customizing advertisements according to the user's preferences and emotions.

[1018] Example prompt sentence:

[1019] "Create an ad for a music player targeted to a user who is 30 years old, male, an engineer by profession, and whose hobby is listening to music, and who has shown interest in the product."

[1020] Ad serving

[1021] The generated personalized advertisement is delivered from the server to the information processing device. The advertisement may be delivered in real time or at a specific timing, and displayed on the user's terminal.

[1022] Examples:

[1023] The server sends personalized music player advertisements to the user's smartphone, which displays the advertisements on the home screen or browser.

[1024] Collecting and analyzing feedback

[1025] The user's response to the ad (clicks, purchases, viewing time, etc.) is sent from the device to the server, which analyzes the feedback data and optimizes the AI ​​model to reflect this in future ad generation.

[1026] Examples:

[1027] When a user clicks on an ad, the information is sent to the server in real time, and emotional data is also recorded, allowing the analysis system to update the parameters of the AI ​​model.

[1028] This system utilizes users' personal data and real-time emotional data to generate and deliver more effective and personalized advertisements, thereby maximizing the effectiveness of advertisements and improving the user experience.

[1029] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1030] Step 1: Collecting your personal data

[1031] A user accesses the system and inputs personal data such as age, gender, occupation, and hobbies. The server receives this input data and stores it in a database. Specific operations include the user entering data into a registration form and pressing the submit button. Based on the input data, the server prepares the data format to be saved in the database and stores it in the database.

[1032] Input: Data entered by the user, such as age, gender, occupation, hobbies, etc.

[1033] Output: User's personal data stored on the server

[1034] Step 2: Collecting website browsing and purchase history

[1035] The server records information about the pages viewed and the products purchased each time a user visits a website. Specifically, the server records the information in a log when a user's browsing actions occur, thereby collecting website action data in real time.

[1036] Input: User browsing and purchase history

[1037] Output: Browsing and purchase history data stored on the server

[1038] Step 3: Collecting emotion data

[1039] The emotion engine built into the device analyzes the user's facial expressions, voice, and behavior in real time to generate emotional data. The camera and microphone capture the user's reactions while viewing advertisements, and the data is analyzed to identify emotions such as "interest" or "discomfort." The analyzed emotional data is then sent to a server.

[1040] Input: User's facial expressions, voice, and actions captured by the device

[1041] Output: User emotion data sent to the server

[1042] Step 4: Store and manage your data

[1043] The server stores and manages the collected personal data, browsing history, purchase history, and emotional data in a database. The data is stored while maintaining consistency to prevent duplication or loss of data. The data is updated regularly to reflect the latest information.

[1044] Input: Collected personal data, browsing history, purchase history, emotional data

[1045] Output: The latest data stored in the database

[1046] Step 5: Receive and save the original image ad

[1047] The server receives original image advertisements provided by advertisement providers and stores them in an advertisement database. It also records the received advertisements along with related metadata (such as target age group). Specific operations include uploading advertisement files and inputting their metadata.

[1048] Input: Original image ad and metadata uploaded by the ad provider

[1049] Output: Original image ads and metadata stored in the ads database

[1050] Step 6: Generate personalized ads

[1051] The server runs a generative AI model based on the collected personal data, emotional data, and original image advertisements. The generative AI model receives a prompt sentence for the user's data as input, and generates an advertisement optimized for each user based on that data. Specifically, the AI ​​model inputs the prompt sentence, "Please create an advertisement for a music player for a user who is 30 years old, male, an engineer by profession, whose hobby is listening to music, and who has shown an interest in the advertisement."

[1052] Input: Personal data, emotion data, original image advertisement, prompt sentence

[1053] Output: Generated personalized ad

[1054] Step 7: Serving Ads

[1055] The generated personalized advertisement is delivered from the server to the user's information processing device. Delivery can be in real time or at a specific timing, and the advertisement is displayed on the terminal. Specific operations include the server sending the advertisement to the terminal, and the terminal displaying the advertisement on the home screen or browser.

[1056] Input: Generated personalized ads

[1057] Output: Advertisement delivered to and displayed on the user's device

[1058] Step 8: Collect and analyze feedback

[1059] The device records the user's response to the ad (clicks, purchases, viewing time, etc.) and sends it to the server. The server analyzes this feedback data and adjusts the parameters of the AI ​​model to reflect this in future ad generation.

[1060] Input: User response data to advertisements

[1061] Output: Optimized ad generation parameters from the updated generative AI model

[1062] (Application example 2)

[1063] 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."

[1064] While existing personalized advertising systems have made progress in generating ads based on basic user personal data (such as age, gender, and hobbies), they lack the technology to utilize emotional data to optimize ads in real time. This has resulted in the inability to display ads that respond immediately to user emotions, limiting the effectiveness of ads. Furthermore, while existing ad delivery systems can collect user responses as feedback, they are also problematic in that they do not quickly adjust ad generation based on that feedback.

[1065] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting personal data of users, means for saving the personal data in a database, means for receiving and saving original image advertisements from advertisers, means for generating advertisements optimized for each user based on the personal data and the original image advertisements, means for collecting user emotion data in real time, means for further optimizing advertisements based on the personal data and the emotion data, means for delivering the generated advertisements to the user's terminal, and means for displaying the generated advertisements on the terminal. This makes it possible to optimize advertisements based on the user's real-time emotions, thereby maximizing the effectiveness of advertisements.

[1066] "User" means an individual or organization that uses the system.

[1067] "Personal Data" refers to personal information about the user (age, gender, occupation, hobbies, etc.).

[1068] "Database" means a digital storage system for storing collected personal data and other information.

[1069] An "advertiser" is a company or organization that distributes advertisements and promotes specific products or services.

[1070] "Original image advertisement" refers to basic image data of an advertisement provided by an advertiser, and is the basis for generating a personalized advertisement.

[1071] "Optimized ads" are ads that are customized based on the user's personal and emotional data.

[1072] "Emotion data" is information about emotions acquired from the user's facial expressions, voice, etc.

[1073] "Real-time" means that data is collected immediately and processed on the spot.

[1074] "Terminal" refers to a device (e.g., smartphone, smart glasses, etc.) used to display advertisements.

[1075] "Display means" refers to a method or device for displaying the generated advertisement to a user.

[1076] The present invention provides a system for generating and distributing personalized advertisements using personal data and emotional data of users. Specific embodiments are described below.

[1077] 1. Collection of Personal Data

[1078] The server collects personal data provided by the user (such as age, gender, occupation, hobbies, etc.) This data collection includes not only the information the user enters when registering an account, but also subsequent website browsing history and purchase history.

[1079] 2. Real-time collection of emotional data

[1080] The device (e.g., smart glasses) analyzes the user's facial expressions and voice to collect emotional data in real time. This emotional data is captured using the device's camera and microphone and sent to a server.

[1081] 3. Data storage and management

[1082] The server stores the collected personal data and emotion data in a database, which is kept up to date. The database also stores original image advertisements provided by advertisers.

[1083] 4. Generating personalized ads

[1084] The server uses a generative AI model to generate ads based on the user's personal and emotional data. This process takes into account the user's age, gender, occupation, hobbies, and even real-time emotional data. The generated ads contain content optimized for the user.

[1085] 5. Delivery and display of advertisements

[1086] The generated advertisements are delivered from the server to the device and displayed on the device. In the case of smart glasses, the advertisements are displayed directly in the user's field of vision, while in the case of smartphones, the advertisements are displayed on the home screen or browser.

[1087] 6. Feedback Collection and Analysis

[1088] The user's reactions to the ad (clicks, viewing time, etc.) are collected along with emotional data and sent to the server, which analyzes this feedback data and adjusts the parameters of the generative AI model to reflect this in the next ad generation.

[1089] Hardware and software used

[1090] Hardware: Smart glasses (with camera, microphone, and display), smartphone

[1091] Software: Python, EmotionRecognition library, OpenCV, generative AI model (e.g., GPT-3)

[1092] Specific examples

[1093] For example, if a user is a 30-year-old male engineer who is interested in music players, and the camera in the smart glasses recognizes that his facial expression looks happy, the server will send the following prompt sentence to the generative AI model to generate an advertisement:

[1094] Prompt Sentence Examples

[1095] "A 30-year-old male engineer is interested in music players. He currently has a happy expression. Please generate personalized ads for the best music equipment for this user."

[1096] This system maximizes the effectiveness of advertising by displaying the most suitable and interesting advertisements to users in real time.

[1097] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1098] Step 1:

[1099] The user inputs personal data. The user inputs personal data such as age, gender, occupation, and hobbies using smart glasses or a smartphone. This data is sent from the device to the server, which then stores the data in a database. Input data (e.g., age, gender) → Data stored in the database

[1100] Step 2:

[1101] The device collects emotion data. If the user is wearing smart glasses, the camera and microphone are used to collect facial expressions and voice in real time. This data is analyzed using the EmotionRecognition library to generate emotion data. Input data (e.g., video, audio) → Output data (e.g., emotion data)

[1102] Step 3:

[1103] The server manages the database. Collected personal data and emotional data are stored in the database and updated as needed. The server manages this database and always keeps the latest information. Input data (e.g., personal data, emotional data) → Latest database

[1104] Step 4:

[1105] Receive original image ads from advertisers. The server receives original image ads provided by advertisers and stores them in a database. During this process, the ad metadata is also stored. Input data (e.g. original image ads) → Stored ad data

[1106] Step 5:

[1107] The server generates personalized ads. Using a generative AI model (e.g., GPT-3), the server generates customized ads based on the collected personal data and emotional data. When generating ads, a prompt sentence is input into the generative AI model. Prompt sentence (e.g., "A 30-year-old male engineer is interested in music players. He currently has a happy expression. Please generate a personalized ad for music equipment that is best suited to this user.") → Personalized ads

[1108] Step 6:

[1109] The server delivers the generated personalized advertisement to the user's device (smart glasses or smartphone). Input data (e.g., personalized advertisement) → Delivered advertisement

[1110] Step 7:

[1111] The advertisement is displayed on the device. The user's device displays the received personalized advertisement. In the case of smart glasses, the advertisement is displayed directly in the user's field of vision. Input data (e.g., delivered advertisement) → Displayed advertisement

[1112] Step 8:

[1113] The user responds to the ad. The user clicks on the ad and the viewing time is measured. The feedback data collected during this process is sent from the device to the server. Input data (e.g., user's ad response) → Feedback data

[1114] Step 9:

[1115] The server analyzes the feedback data. The collected feedback data is analyzed by the server, and the parameters of the generative AI model are adjusted and reflected in the next ad generation. Input data (e.g., feedback data) → Adjusted generative AI model

[1116] As a result, advertisements are optimized based on the user's real-time emotions, making it possible to maximize the effectiveness of the advertisements.

[1117] 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.

[1118] 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.

[1119] 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.

[1120] [Fourth embodiment]

[1121] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1122] 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.

[1123] 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).

[1124] 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.

[1125] 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.

[1126] 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).

[1127] 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.

[1128] 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.

[1129] 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.

[1130] 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.

[1131] 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.

[1132] 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.

[1133] 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."

[1134] This invention relates to a system that generates and delivers personalized advertisements based on a user's personal data. This system includes AI that generates advertisements optimized for each user, and can improve advertisement click rates and conversion rates. Below, the program processing of this system is explained in natural language with specific examples.

[1135] 1. Collection and storage of personal data

[1136] The server collects personal data provided by the user (such as age, gender, occupation, and hobbies), including information entered by the user at the time of registration, subsequent website browsing history, and purchase history.

[1137] Examples:

[1138] When registering, the user (Tanaka) enters his / her age, gender, occupation, and hobbies. Tanaka's browsing history and purchase history of the websites he / she uses are also periodically sent to the server.

[1139] The server stores this data in a database, which is updated as needed to keep the data up to date.

[1140] 2. Management of original image ads

[1141] The server receives and stores original image advertisements provided by advertisers, which serve as the basis for generating personalized advertisements.

[1142] Examples:

[1143] Advertiser A sends the original image advertisement for the music player to the server, which stores it in the advertisement database and records related metadata (such as the target age group).

[1144] 3. Generating personalized ads

[1145] The server runs an ad generation AI to generate the optimal ad for each user based on the collected personal data and the original image ad. This AI considers the user's individual data and automatically generates the ad that best suits the specific user.

[1146] Examples:

[1147] The server generates an advertisement for a music player that is best suited to Tanaka, who is interested in music, based on Tanaka's age, gender, occupation, and hobbies. The advertisement includes content customized to Tanaka's name and preferences.

[1148] 4. Delivery of advertisements

[1149] The generated personalized advertisement is delivered from the server to the user's terminal, which receives and displays the advertisement.

[1150] Examples:

[1151] The server sends a personalized music player advertisement to Tanaka's smartphone, which displays the advertisement on his home screen and browser.

[1152] 5. Feedback collection and analysis

[1153] Information on users' reactions to ads (clicks, purchases, viewing time, etc.) is sent from the device to the server, which analyzes this feedback data and adjusts the parameters of the ad generation AI to continuously optimize the effectiveness of the ads.

[1154] Examples:

[1155] When Tanaka clicks on the displayed ad, the information is sent from his smartphone to the server, which analyzes Tanaka's click information and reflects it in the generation of the next ad.

[1156] summary

[1157] This system maximizes the effectiveness of advertising by generating personalized advertisements based on users' personal data and delivering them to their devices. The collection and analysis of feedback data also enables continuous optimization of the advertisement generation process.

[1158] The processing flow will be explained below.

[1159] Step 1:

[1160] The server collects personal data provided by the user, including basic information (age, gender, occupation, hobbies, etc.) entered by the user when registering an account. The server also collects the user's website browsing history and purchase history for analysis.

[1161] Step 2:

[1162] Terminals are devices (smartphones, tablets, PCs, etc.) that users use on a daily basis, and these devices periodically send user behavior data to a server. This data includes browsing history, purchase history, click information, etc.

[1163] Step 3:

[1164] The server stores the collected data in a database, including basic information about the user and their behavioral data, and updates the database accordingly to keep the user's profile information up to date.

[1165] Step 4:

[1166] The server receives and stores original image advertisements from advertisers. These images are stored in an advertisement database and managed as basic data for generating personalized advertisements.

[1167] Step 5:

[1168] The server runs an ad generation AI based on personal data and the original image ad. The AI ​​analyzes personal data such as the user's age, gender, occupation, and hobbies, and automatically generates the most suitable ad for each user based on that data.

[1169] Step 6:

[1170] The server then delivers the generated personalized advertisement to the user's device, either in real time or at a specific time.

[1171] Step 7:

[1172] The device then displays the received personalized advertisements to the user, primarily on the home screen or in a web browser or other interface, providing the advertisements in a format that is easy for the user to access.

[1173] Step 8:

[1174] Users respond to the displayed advertisements by clicking, purchasing, etc. These responses are recorded as feedback data.

[1175] Step 9:

[1176] The device sends user response data to the server, including whether or not the ad was clicked, the viewing time, and information about purchases made through the ad.

[1177] Step 10:

[1178] The server analyzes the received feedback data. The results of this analysis are used to adjust the ad generation AI algorithm and are used for subsequent ad generation. This makes it possible to continuously optimize the effectiveness of ads.

[1179] summary

[1180] Through these steps, the server generates personalized advertisements based on the user's personal data and delivers them to the user's device. The device displays the advertisements and sends back user response data to the server, realizing a system that continuously improves the effectiveness of advertisements.

[1181] Example 1

[1182] 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."

[1183] Conventional ad delivery systems have had difficulty effectively generating and delivering ads tailored to individual users' needs and preferences. As a result, ad click-through rates and conversion rates have fallen, resulting in insufficient advertising effectiveness. Furthermore, the inability to effectively analyze user feedback and reflect it in ad generation has also led to delays in ad optimization.

[1184] 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.

[1185] In this invention, the server includes means for collecting personal information of users, means for storing the personal information in a database, means for receiving and storing original image advertisements from advertisement providers, means for generating advertisements optimized for individual users based on the personal information and original image advertisements, means for delivering the generated advertisements to the users' display devices, means for displaying the generated advertisements on the display devices, and means for collecting and storing the users' website browsing history and purchase history in a database. This makes it possible to effectively generate and deliver advertisements tailored to the individual needs and preferences of users. Furthermore, by collecting user response data and feeding it back to the advertisement generation means, continuous optimization of advertisements can be achieved, thereby improving advertising effectiveness.

[1186] "User" means an individual or organization that receives advertisements and provides personal data.

[1187] "Personal Information" refers to personal data provided by the User, such as age, gender, occupation, and hobbies.

[1188] The term "database" refers to an electronic storage device for storing personal information, website browsing history, purchase history, and original image advertisements collected by the server.

[1189] An "advertising provider" is a company or organization that provides advertisements and is responsible for transmitting original image advertisements to the server.

[1190] "Original image advertisement" refers to the basic advertisement image sent by the advertisement provider and stored on the server.

[1191] "Optimized advertising" refers to advertising that is customized based on a user's personal information, website browsing history, and purchase history, and is tailored to best suit the user.

[1192] A "display device" is an electronic device used by a user, such as a computer, smartphone, or tablet, that is used to display the generated advertisement.

[1193] "Website browsing history" refers to the URLs of websites visited by a user and information about the pages viewed.

[1194] "Purchase History" refers to a record of purchase transactions made by a User online or offline.

[1195] "Response data" refers to information about actions taken by users in response to advertisements, such as clicking, viewing, or purchasing.

[1196] "Advertising generation means" refers to the algorithms and software used to generate optimized advertisements based on collected personal information and original image advertisements.

[1197] This invention relates to a system that generates and delivers personalized advertisements based on a user's personal information. This system includes an advertisement generation AI for generating advertisements optimized for each user, and can improve advertisement click rates and conversion rates. Below, we will explain how this system is specifically implemented.

[1198] First, the server collects personal information provided by the user and stores it in a database. This includes personal data such as the user's age, gender, occupation, and hobbies. The user's website browsing history and purchase history are also periodically collected and stored in a database. This personal data is used to understand the user's behavioral patterns and interests.

[1199] The server then receives and stores the original image advertisements sent by the advertisement providers. These original image advertisements contain metadata such as target age groups. The server stores the original image advertisements in an advertisement database and uses them in combination with the user's personal data.

[1200] The server runs an ad generation AI to generate optimal ads for each user based on the collected personal data and original image ads. This AI considers the user's individual data and automatically generates ads that are best suited to the specific user. For example, for a user who is interested in music, it generates music-related ads and generates ads with content customized to the user's name and preferences.

[1201] The generated personalized advertisements are delivered from the server to the user's device. The device receives the advertisements and displays them on a display device (smartphone, tablet, computer, etc.). The user can view these advertisements on their home screen or browser.

[1202] Furthermore, information on users' reactions to ads (clicks, purchases, viewing time, etc.) is sent from the device to the server. The server analyzes this feedback data and adjusts the parameters of the ad generation AI, thereby continuously optimizing the effectiveness of ads.

[1203] Examples:

[1204] A user (Tanaka) sees an advertisement for a new music player. Based on the age (29), gender (male), occupation (engineer), and hobby (listening to music) provided by Tanaka when he registered, the server generates an advertisement for the music player that best suits him. The server also takes into account Tanaka's website browsing history and purchase history to generate a customized advertisement. The advertisement includes Tanaka's name and content tailored to his preferences.

[1205] Example prompt sentence:

[1206] "Generate the best music player ad for Mr. Tanaka, a 29-year-old engineer who is interested in music."

[1207] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1208] Step 1:

[1209] The server collects the user's personal information and stores it in a database.

[1210] input:

[1211] Personal data provided by the user (age, gender, occupation, hobbies)

[1212] Specific behavior:

[1213] The user enters personal information into a registration form. The device sends this data to the server, which receives it and stores it in a database.

[1214] output:

[1215] User personal information stored in a database

[1216] Step 2:

[1217] The server collects the user's website browsing history and purchase history and stores it in a database.

[1218] input:

[1219] User browsing history and purchase history

[1220] Specific behavior:

[1221] When a user browses a website or makes a purchase, the device sends this history data to the server, which stores it in a database.

[1222] output:

[1223] Browsing and purchasing history stored in a database

[1224] Step 3:

[1225] The server receives and stores original image advertisements from advertisement providers.

[1226] input:

[1227] Original image ads and metadata (such as target demographics) sent by ad providers

[1228] Specific behavior:

[1229] Advertisers send original image ads to the server, which receives the ads and metadata and stores them in an ad database.

[1230] output:

[1231] Original image ads and metadata stored in the ad database

[1232] Step 4:

[1233] The server runs an ad generation AI to generate optimal ads for each user based on the collected personal data and original image ads.

[1234] input:

[1235] Personal information, website browsing history, purchase history, and original image ads

[1236] Specific behavior:

[1237] The server inputs personal information and original image ads into the ad generation AI, which then generates the most suitable ad for the user based on this data. This process involves customization based on names and preferences.

[1238] output:

[1239] Customized advertising for each user

[1240] Step 5:

[1241] The server delivers the generated personalized advertisement to the user's terminal.

[1242] input:

[1243] Generated personalized ads

[1244] Specific behavior:

[1245] The server transmits the generated advertisement to the user's terminal, and the terminal displays the received advertisement on a display device.

[1246] output:

[1247] Personalized advertisements displayed on a user's display device

[1248] Step 6:

[1249] The server collects data on users' responses to advertisements and analyzes it as feedback data.

[1250] input:

[1251] User response data to ads (clicks, purchases, viewing time, etc.)

[1252] Specific behavior:

[1253] When a user clicks on an ad or makes a purchase, the device sends the response data to the server, which analyzes the received feedback data and adjusts the parameters of the ad generation AI.

[1254] output:

[1255] Analyzed feedback data and adjusted ad generation AI parameters

[1256] (Application example 1)

[1257] 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."

[1258] Conventional advertising distribution systems can generate advertisements based on users' personal data, but they face the challenge of measuring the effectiveness of advertisements in real time and reflecting this in the next advertisement generation process. Another problem is that advertisements are not optimized sufficiently because user response data is not fully utilized. The present invention aims to solve this problem by providing a system that collects and analyzes user action data in real time and optimizes the advertisement generation process.

[1259] 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.

[1260] In this invention, the server includes: means for collecting user personal data; means for storing the personal data in a database; means for receiving and storing original image advertisements from advertisers; means for generating advertisements optimized for each user based on the personal data and the original image advertisements; means for delivering the generated advertisements to user terminals; means for displaying the generated advertisements on the terminals; means for collecting user action data (clicks, purchases, etc.) based on the generated advertisements; and means for analyzing the collected user action data using an advertisement generation AI and optimizing the advertisement generation process. This makes it possible to collect and analyze user response data in real time and reflect it in the next advertisement generation process, thereby continuously optimizing the effectiveness of advertisements.

[1261] "Personal data" refers to data that indicates a user's individual characteristics and behavior, such as age, gender, occupation, hobbies, browsing history, and purchase history.

[1262] A "database" is a system for efficiently storing, managing, and searching collected personal data and advertising data.

[1263] "Original image advertisement" refers to advertising material provided by an advertiser and serving as the basis for generating personalized advertisements.

[1264] "Advertising generation AI" is an artificial intelligence system that generates optimal advertisements for each user based on the user's personal data and the original image advertisement.

[1265] "Action data" is data that indicates the user's response to an advertisement (click, purchase, etc.).

[1266] The "advertising generation process" is a series of steps that generate and deliver individually optimized advertisements based on personal data and original image advertisements.

[1267] "Optimization" refers to adjusting the parameters of the ad generation AI based on collected data to maximize ad click-through rates and conversion rates.

[1268] A "terminal" is a device, such as a smartphone, tablet, or PC, that a user uses to receive and display advertisements.

[1269] "Server" means a central computer system that collects, stores, analyzes data, and generates advertisements.

[1270] "Delivery" refers to sending the generated advertisement to the user's terminal.

[1271] The present invention relates to a system for generating and distributing personalized advertisements based on personal data of users. Specific embodiments of the present invention will be described below.

[1272] Collection and storage of personal data

[1273] The server collects personal data provided by users (age, gender, occupation, hobbies, browsing history, purchase history, etc.) and stores it in a database. This data is updated periodically based on user behavior to keep it up to date. The main hardware used is a server computer and user devices (smartphones, tablets, etc.). Software includes Flask (web framework), SQLite (database management system), and Pandas (data processing library). For example, when a user enters their age, gender, occupation, and hobbies during registration, this information is sent to the server and stored in the database.

[1274] Management of original image ads

[1275] The server receives raw image advertisements provided by advertisers and stores them in an advertisement database. This includes data about the image itself and associated metadata (such as the target demographic). The primary hardware used is a server computer, and the software includes Flask and SQLite. For example, an advertiser may send an advertisement image for a new music player to the server, and this data is stored in the advertisement database.

[1276] Generating personalized ads

[1277] The server uses an ad generation AI to generate optimal ads for each user based on the collected personal data and the original image ads. This ad generation AI is built using machine learning libraries such as TensorFlow and Keras. As a preprocessing step, the data is scaled using Scikit-learn's StandardScaler. For example, the server generates a customized ad based on a specific user's age, gender, occupation, and hobbies, and this ad is input to the AI ​​model in the prompt text: "User's age: 35, gender: male, occupation: engineer, hobbies: music. Please generate the optimal music player ad for this user."

[1278] Ad delivery and display

[1279] The generated personalized ads are delivered in real time from the server to the user's device, where they are displayed. The main hardware used is a server computer and the user's device, and the ads are delivered via Flask. The ads are displayed in the browser or app on the user's smartphone or tablet.

[1280] Collecting and analyzing user action data

[1281] Data on users' responses to ads (clicks, purchases, etc.) is sent from the device to the server. The server analyzes this feedback data and adjusts the parameters of the ad generation AI to optimize the next ad generation process. This process uses Flask, SQLite, and machine learning libraries such as TensorFlow and Keras. For example, when a user clicks on a displayed ad, that information is sent from the device to the server and analyzed.

[1282] Through these steps, it becomes possible to generate and deliver ads optimized for each user in real time, and to continuously optimize their effectiveness. This system not only improves ad click rates and conversion rates, but also provides advertisers with an efficient marketing method.

[1283] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1284] Step 1:

[1285] The server collects personal data from users. When users register, they enter information such as age, gender, occupation, and hobbies, and send it to the server. The server receives this data and stores it in a database. In this process, the information entered by the user is the input, and the organized personal data is stored in the database as the output.

[1286] Step 2:

[1287] The server continuously collects additional data, such as the user's website browsing history and purchase history, thereby improving the accuracy of the personal data. This data is sent from the user's device to the server at regular intervals. The server updates the database by adding this new data to the existing personal data. The input is the user's behavioral data, and the output is the updated personal data stored in the database.

[1288] Step 3:

[1289] The server receives original image advertisements from advertisers and stores them in the advertisement database. The advertiser sends the original image advertisements and their targeting metadata (e.g., target age group and interest categories) to the server. The server organizes the received data and stores it in the advertisement database. The advertisement database has the data provided by the advertiser as input and the saved original image advertisement as output.

[1290] Step 4:

[1291] The server generates personalized advertisements. This is done by running an advertisement generation AI using the collected personal data and original image advertisements. To generate advertisements optimized for each user, the server first scales the personal data, then combines it with the original image advertisements and inputs it into the AI ​​model. The generated advertisements are digital advertisements that include customized elements. The scaled personal data and original image advertisements are input, and the generated personalized advertisements are obtained as output.

[1292] Step 5:

[1293] The server delivers the generated personalized advertisement to the user's device. The generated advertisement is sent directly from the server to the user's smartphone or tablet and displayed in the device's display area. The generated advertisement data is the input, and the advertisement displayed on the user's device is the output.

[1294] Step 6:

[1295] The device collects user action data (clicks, viewing time, purchases, etc.). When a user responds to an advertisement, the response data is recorded on the device and sent to the server at regular intervals. User operations are input, and the collected action data is sent to the server as output.

[1296] Step 7:

[1297] The server analyzes the collected action data. The server receives this data and stores it in a database. Then, it uses ad generation AI to analyze this data and adjust the parameters of the ad generation process. The input is user action data, and the output is optimized ad generation parameters.

[1298] Step 8:

[1299] The server then uses the optimized parameters to execute the ad generation process from the next time onward, which makes the next ad more effective. By repeating all steps, the effectiveness of the ad is continuously improved. The optimized parameters are the input, and an effective ad generation process is executed as the output.

[1300] 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.

[1301] This invention combines an emotion engine with a system that generates and delivers personalized advertisements based on a user's personal data. The emotion engine recognizes the user's emotions and can further optimize advertisements based on that information.

[1302] 1. Collection of personal data and personal emotional data

[1303] The server collects personal data provided by the user (such as age, gender, occupation, and hobbies). This data includes not only the information the user enters when registering an account, but also subsequent website browsing and purchase history.

[1304] Furthermore, the device is equipped with an emotion engine that recognizes emotions by analyzing the user's facial expressions, voice, behavior, etc. The emotion engine captures the user's reactions while viewing advertisements and generates emotion data in real time.

[1305] Examples:

[1306] When registering, the user (Tanaka) enters his age, gender, occupation, and hobbies. When Tanaka watches a video advertisement while using his smartphone, the device's camera and microphone are used to analyze his facial expressions and voice, and an emotion engine recognizes his emotions, such as "interest" or "discomfort."

[1307] 2. Data storage and management

[1308] This data is stored in a database. The server updates the collected personal data and emotional data as needed to keep them up to date. This allows the user's profile to always reflect the most up-to-date information.

[1309] 3. Management of original image ads

[1310] The server receives and stores original image advertisements provided by advertisers, which are the basis for generating advertisements and are used to generate personalized advertisements.

[1311] Examples:

[1312] Advertiser A sends the original image advertisement for the music player to the server, which stores it in the advertisement database and records related metadata (such as the target age group).

[1313] 4. Generating personalized ads

[1314] The server runs an ad generation AI based on the collected personal data and original image ads. This AI analyzes the user's age, gender, occupation, hobbies, and even emotional data, and automatically generates the most suitable ad for each user based on that data.

[1315] Examples:

[1316] The server analyzes Tanaka's age, gender, occupation, and hobbies to determine his interest in music equipment. It then takes his emotional data (facial expressions and voice indicating interest) into account to customize ads for the music player. The ads include Tanaka's name and emotionally relevant copy.

[1317] 5. Delivery of advertisements

[1318] The generated personalized advertisements are delivered from the server to the user's device, either in real time or at a specific time.

[1319] Examples:

[1320] The server sends a personalized music player advertisement to Tanaka's smartphone, which displays the advertisement on his home screen and browser.

[1321] 6. Feedback Collection and Analysis

[1322] When a user responds to an ad (clicks, purchases, viewing time, etc.), that data is sent from the device to the server. The server analyzes this feedback data and adjusts the parameters of the ad generation AI to reflect this in future ad generation.

[1323] Examples:

[1324] When Tanaka clicks on the ad, that information is sent from his smartphone to the server. The emotion engine also records how Tanaka felt about the ad. The server uses this information to optimize the AI ​​algorithm for the next ad generation.

[1325] summary

[1326] This system maximizes the effectiveness of advertising by generating and delivering personalized advertisements based on the user's personal and emotional data. The collection and analysis of feedback data and emotional data enables continuous optimization of the advertisement generation process.

[1327] The processing flow will be explained below.

[1328] Step 1:

[1329] The server collects personal data provided by the user, specifically basic information such as age, gender, occupation, and hobbies that the user enters when registering an account.

[1330] Step 2:

[1331] The device collects and transmits data about the user's daily activities, including website browsing history, purchase history, and click information, to a server.

[1332] Step 3:

[1333] The server stores the collected personal and behavioral data in a database that is regularly updated to keep this data up to date.

[1334] Step 4:

[1335] The device uses an emotion engine to collect user emotion data, which is recognized in real time based on the user's facial expressions, voice, and behavior.

[1336] Step 5:

[1337] The device sends the collected emotional data to a server, including the user's reactions while watching the advertisement.

[1338] Step 6:

[1339] The server receives original image advertisements from advertisers and stores them in an advertisement database, along with metadata about the target demographic and advertisement content.

[1340] Step 7:

[1341] The server runs an ad generation AI based on the collected personal data, behavioral data, and emotional data, and the AI ​​generates ads optimized for each user.

[1342] Examples:

[1343] The server analyzes Tanaka's age, gender, occupation, and hobbies to determine his interest in music. It also uses emotional data to detect facial expressions that indicate Tanaka's interest in music player ads. It then generates a music player ad tailored to him, adding text that reflects Tanaka's name and emotions.

[1344] Step 8:

[1345] The server then delivers the generated personalized advertisement to Tanaka's device. The advertisement may be delivered in real time or at a specific time.

[1346] Step 9:

[1347] The device then displays the received personalized advertisements, which can appear on the home screen or in a web browser for easy user access.

[1348] Step 10:

[1349] Users respond to the displayed advertisements by clicking or purchasing, etc., which generates feedback data.

[1350] Step 11:

[1351] The terminal transmits user feedback data to the server, including whether or not an ad was clicked, viewing time, purchase information, and so on.

[1352] Step 12:

[1353] The server analyzes the received feedback data. The analysis results are used to optimize the parameters of the ad generation AI. This is reflected in subsequent ad generation, enabling continuous optimization of ad effectiveness.

[1354] By executing the above steps in order, a system is realized that generates and delivers personalized advertisements based on the user's personal data and emotional data.

[1355] Example 2

[1356] 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."

[1357] Conventional advertising delivery systems typically personalize advertisements based on users' personal data, but these systems do not take into account users' emotions or real-time responses, limiting the effectiveness of the advertisements. Furthermore, advertisement generation is often insufficient for individual users, failing to reflect users' preferences and interests. The present invention aims to improve advertising effectiveness and user experience by collecting and analyzing users' emotional data and generating and delivering optimized advertisements based on that data.

[1358] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting personal data and emotional data of users, means for storing the personal data and emotional data in a database, means for receiving and storing original image advertisements from advertisement providers, means for generating advertisements optimized for each user using a generative AI model based on the personal data, emotional data, and original image advertisements, means for delivering the generated advertisements to the user's information processing device, and means for displaying the generated advertisements on the information processing device. This makes it possible to generate and deliver highly optimized personalized advertisements that take into account the user's emotions and real-time reactions.

[1359] "User" means any person or legal entity that accesses the System and provides Personal Data or other information.

[1360] "Personal Data" refers to personal information about a user, such as age, gender, occupation, and hobbies.

[1361] "Emotional data" refers to data on the emotional state analyzed based on the user's facial expressions, voice, behavior, etc.

[1362] A "database" is a system for storing, managing, and searching collected data.

[1363] "Advertiser" means an individual or corporation that provides advertisements to promote its products or services.

[1364] "Original image advertisement" refers to the image or video file that serves as the basic data for the advertisement provided by the advertisement provider.

[1365] A "generative AI model" is an artificial intelligence algorithm that analyzes a user's personal and emotional data to generate optimized advertisements.

[1366] "Information processing device" refers to electronic devices such as computers, smartphones, and tablets that are the target of advertisement delivery.

[1367] "Optimized advertising" refers to advertising that is customized and delivered effectively based on the user's personal and emotional data.

[1368] "Response data" refers to behavioral data such as clicks, purchases, and viewing time shown by users in response to advertisements.

[1369] "Personalization" refers to the inclusion of a user's name, preferences, or other personally unique elements within an advertisement.

[1370] The present invention relates to a system for generating and distributing personalized advertisements based on personal data and emotional data of users. Specific embodiments of the invention using various hardware and software are described below.

[1371] Data collection

[1372] The server has the function of collecting personal data provided by users (such as age, gender, occupation, and hobbies). Users access the system and input their personal data, which is then stored in a database by the server. The server also records website browsing history and purchase history.

[1373] Examples:

[1374] When a user enters their age, gender, occupation, and hobbies on the registration page and clicks the submit button, this information is sent to the server and stored in a database, which uses MySQL to manage this data.

[1375] Collecting Emotional Data

[1376] The device is equipped with an emotion engine that analyzes the user's facial expressions, voice, and behavior. This emotion engine recognizes the user's emotions in real time and generates data. The emotion data is sent to a server and stored in a database along with personal data.

[1377] Examples:

[1378] When a user watches an advertisement on their smartphone, the device's camera and microphone capture their facial expressions and voice, allowing emotions such as "interest" or "discomfort" to be recognized in real time and sent to a server.

[1379] Managing advertising data

[1380] The server receives the original image advertisements provided by the advertisement providers and stores them in the advertisement database. In addition, the target attributes of the advertisements (such as age group and region) are also recorded as metadata.

[1381] Examples:

[1382] When an advertisement provider sends an original image advertisement for a music player through an upload interface, the server receives it and stores it in a database.

[1383] Generating personalized ads

[1384] The server runs a generative AI model based on the collected personal and emotional data to generate optimized advertisements for each user. This process involves analyzing the collected data and customizing advertisements according to the user's preferences and emotions.

[1385] Example prompt sentence:

[1386] "Create an ad for a music player targeted to a user who is 30 years old, male, an engineer by profession, and whose hobby is listening to music, and who has shown interest in the product."

[1387] Ad serving

[1388] The generated personalized advertisement is delivered from the server to the information processing device. The advertisement may be delivered in real time or at a specific timing, and displayed on the user's terminal.

[1389] Examples:

[1390] The server sends personalized music player advertisements to the user's smartphone, which displays the advertisements on the home screen or browser.

[1391] Collecting and analyzing feedback

[1392] The user's response to the ad (clicks, purchases, viewing time, etc.) is sent from the device to the server, which analyzes the feedback data and optimizes the AI ​​model to reflect this in future ad generation.

[1393] Examples:

[1394] When a user clicks on an ad, the information is sent to the server in real time, and emotional data is also recorded, allowing the analysis system to update the parameters of the AI ​​model.

[1395] This system utilizes users' personal data and real-time emotional data to generate and deliver more effective and personalized advertisements, thereby maximizing the effectiveness of advertisements and improving the user experience.

[1396] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1397] Step 1: Collecting your personal data

[1398] A user accesses the system and inputs personal data such as age, gender, occupation, and hobbies. The server receives this input data and stores it in a database. Specific operations include the user entering data into a registration form and pressing the submit button. Based on the input data, the server prepares the data format to be saved in the database and stores it in the database.

[1399] Input: Data entered by the user, such as age, gender, occupation, hobbies, etc.

[1400] Output: User's personal data stored on the server

[1401] Step 2: Collecting website browsing and purchase history

[1402] The server records information about the pages viewed and the products purchased each time a user visits a website. Specifically, the server records the information in a log when a user's browsing actions occur, thereby collecting website action data in real time.

[1403] Input: User browsing and purchase history

[1404] Output: Browsing and purchase history data stored on the server

[1405] Step 3: Collecting emotion data

[1406] The emotion engine built into the device analyzes the user's facial expressions, voice, and behavior in real time to generate emotional data. The camera and microphone capture the user's reactions while viewing advertisements, and the data is analyzed to identify emotions such as "interest" or "discomfort." The analyzed emotional data is then sent to a server.

[1407] Input: User's facial expressions, voice, and actions captured by the device

[1408] Output: User emotion data sent to the server

[1409] Step 4: Store and manage your data

[1410] The server stores and manages the collected personal data, browsing history, purchase history, and emotional data in a database. The data is stored while maintaining consistency to prevent duplication or loss of data. The data is updated regularly to reflect the latest information.

[1411] Input: Collected personal data, browsing history, purchase history, emotional data

[1412] Output: The latest data stored in the database

[1413] Step 5: Receive and save the original image ad

[1414] The server receives original image advertisements provided by advertisement providers and stores them in an advertisement database. It also records the received advertisements along with related metadata (such as target age group). Specific operations include uploading advertisement files and inputting their metadata.

[1415] Input: Original image ad and metadata uploaded by the ad provider

[1416] Output: Original image ads and metadata stored in the ads database

[1417] Step 6: Generate personalized ads

[1418] The server runs a generative AI model based on the collected personal data, emotional data, and original image advertisements. The generative AI model receives a prompt sentence for the user's data as input, and generates an advertisement optimized for each user based on that data. Specifically, the AI ​​model inputs the prompt sentence, "Please create an advertisement for a music player for a user who is 30 years old, male, an engineer by profession, whose hobby is listening to music, and who has shown an interest in the advertisement."

[1419] Input: Personal data, emotion data, original image advertisement, prompt sentence

[1420] Output: Generated personalized ad

[1421] Step 7: Serving Ads

[1422] The generated personalized advertisement is delivered from the server to the user's information processing device. Delivery can be in real time or at a specific timing, and the advertisement is displayed on the terminal. Specific operations include the server sending the advertisement to the terminal, and the terminal displaying the advertisement on the home screen or browser.

[1423] Input: Generated personalized ads

[1424] Output: Advertisement delivered to and displayed on the user's device

[1425] Step 8: Collect and analyze feedback

[1426] The device records the user's response to the ad (clicks, purchases, viewing time, etc.) and sends it to the server. The server analyzes this feedback data and adjusts the parameters of the AI ​​model to reflect this in future ad generation.

[1427] Input: User response data to advertisements

[1428] Output: Optimized ad generation parameters from the updated generative AI model

[1429] (Application example 2)

[1430] 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."

[1431] While existing personalized advertising systems have made progress in generating ads based on basic user personal data (such as age, gender, and hobbies), they lack the technology to utilize emotional data to optimize ads in real time. This has resulted in the inability to display ads that respond immediately to user emotions, limiting the effectiveness of ads. Furthermore, while existing ad delivery systems can collect user responses as feedback, they are also problematic in that they do not quickly adjust ad generation based on that feedback.

[1432] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting personal data of users, means for saving the personal data in a database, means for receiving and saving original image advertisements from advertisers, means for generating advertisements optimized for each user based on the personal data and the original image advertisements, means for collecting user emotion data in real time, means for further optimizing advertisements based on the personal data and the emotion data, means for delivering the generated advertisements to the user's terminal, and means for displaying the generated advertisements on the terminal. This makes it possible to optimize advertisements based on the user's real-time emotions, thereby maximizing the effectiveness of advertisements.

[1433] "User" means an individual or organization that uses the system.

[1434] "Personal Data" refers to personal information about the user (age, gender, occupation, hobbies, etc.).

[1435] "Database" means a digital storage system for storing collected personal data and other information.

[1436] An "advertiser" is a company or organization that distributes advertisements and promotes specific products or services.

[1437] "Original image advertisement" refers to basic image data of an advertisement provided by an advertiser, and is the basis for generating a personalized advertisement.

[1438] "Optimized ads" are ads that are customized based on the user's personal and emotional data.

[1439] "Emotion data" is information about emotions acquired from the user's facial expressions, voice, etc.

[1440] "Real-time" means that data is collected immediately and processed on the spot.

[1441] "Terminal" refers to a device (e.g., smartphone, smart glasses, etc.) used to display advertisements.

[1442] "Display means" refers to a method or device for displaying the generated advertisement to a user.

[1443] The present invention provides a system for generating and distributing personalized advertisements using personal data and emotional data of users. Specific embodiments are described below.

[1444] 1. Collection of Personal Data

[1445] The server collects personal data provided by the user (such as age, gender, occupation, hobbies, etc.) This data collection includes not only the information the user enters when registering an account, but also subsequent website browsing history and purchase history.

[1446] 2. Real-time collection of emotional data

[1447] The device (e.g., smart glasses) analyzes the user's facial expressions and voice to collect emotional data in real time. This emotional data is captured using the device's camera and microphone and sent to a server.

[1448] 3. Data storage and management

[1449] The server stores the collected personal data and emotion data in a database, which is kept up to date. The database also stores original image advertisements provided by advertisers.

[1450] 4. Generating personalized ads

[1451] The server uses a generative AI model to generate ads based on the user's personal and emotional data. This process takes into account the user's age, gender, occupation, hobbies, and even real-time emotional data. The generated ads contain content optimized for the user.

[1452] 5. Delivery and display of advertisements

[1453] The generated advertisements are delivered from the server to the device and displayed on the device. In the case of smart glasses, the advertisements are displayed directly in the user's field of vision, while in the case of smartphones, the advertisements are displayed on the home screen or browser.

[1454] 6. Feedback Collection and Analysis

[1455] The user's reactions to the ad (clicks, viewing time, etc.) are collected along with emotional data and sent to the server, which analyzes this feedback data and adjusts the parameters of the generative AI model to reflect this in the next ad generation.

[1456] Hardware and software used

[1457] Hardware: Smart glasses (with camera, microphone, and display), smartphone

[1458] Software: Python, EmotionRecognition library, OpenCV, generative AI model (e.g., GPT-3)

[1459] Specific examples

[1460] For example, if a user is a 30-year-old male engineer who is interested in music players, and the camera in the smart glasses recognizes that his facial expression looks happy, the server will send the following prompt sentence to the generative AI model to generate an advertisement:

[1461] Prompt Sentence Examples

[1462] "A 30-year-old male engineer is interested in music players. He currently has a happy expression. Please generate personalized ads for the best music equipment for this user."

[1463] This system maximizes the effectiveness of advertising by displaying the most suitable and interesting advertisements to users in real time.

[1464] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1465] Step 1:

[1466] The user inputs personal data. The user inputs personal data such as age, gender, occupation, and hobbies using smart glasses or a smartphone. This data is sent from the device to the server, which then stores the data in a database. Input data (e.g., age, gender) → Data stored in the database

[1467] Step 2:

[1468] The device collects emotion data. If the user is wearing smart glasses, the camera and microphone are used to collect facial expressions and voice in real time. This data is analyzed using the EmotionRecognition library to generate emotion data. Input data (e.g., video, audio) → Output data (e.g., emotion data)

[1469] Step 3:

[1470] The server manages the database. Collected personal data and emotional data are stored in the database and updated as needed. The server manages this database and always keeps the latest information. Input data (e.g., personal data, emotional data) → Latest database

[1471] Step 4:

[1472] Receive original image ads from advertisers. The server receives original image ads provided by advertisers and stores them in a database. During this process, the ad metadata is also stored. Input data (e.g. original image ads) → Stored ad data

[1473] Step 5:

[1474] The server generates personalized ads. Using a generative AI model (e.g., GPT-3), the server generates customized ads based on the collected personal data and emotional data. When generating ads, a prompt sentence is input into the generative AI model. Prompt sentence (e.g., "A 30-year-old male engineer is interested in music players. He currently has a happy expression. Please generate a personalized ad for music equipment that is best suited to this user.") → Personalized ads

[1475] Step 6:

[1476] The server delivers the generated personalized advertisement to the user's device (smart glasses or smartphone). Input data (e.g., personalized advertisement) → Delivered advertisement

[1477] Step 7:

[1478] The advertisement is displayed on the device. The user's device displays the received personalized advertisement. In the case of smart glasses, the advertisement is displayed directly in the user's field of vision. Input data (e.g., delivered advertisement) → Displayed advertisement

[1479] Step 8:

[1480] The user responds to the ad. The user clicks on the ad and the viewing time is measured. The feedback data collected during this process is sent from the device to the server. Input data (e.g., user's ad response) → Feedback data

[1481] Step 9:

[1482] The server analyzes the feedback data. The collected feedback data is analyzed by the server, and the parameters of the generative AI model are adjusted and reflected in the next ad generation. Input data (e.g., feedback data) → Adjusted generative AI model

[1483] As a result, advertisements are optimized based on the user's real-time emotions, making it possible to maximize the effectiveness of the advertisements.

[1484] 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.

[1485] 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.

[1486] 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.

[1487] 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.

[1488] 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.

[1489] 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.

[1490] 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).

[1491] 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.

[1492] 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."

[1493] 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.

[1494] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1495] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1496] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1497] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1498] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1499] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1500] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1501] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1502] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1503] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1504] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1505] The following is further disclosed regarding the above embodiment.

[1506] (Claim 1)

[1507] means for collecting personal data of users;

[1508] means for storing the personal data in a database;

[1509] means for receiving and storing original image advertisements from advertisers;

[1510] means for generating an advertisement optimized for each user based on the personal data and the original image advertisement;

[1511] means for delivering the generated advertisement to a user terminal;

[1512] means for displaying the generated advertisement on the terminal;

[1513] A system including:

[1514] (Claim 2)

[1515] 2. The system according to claim 1, further comprising means for collecting said user's reaction data and feeding it back to said advertisement generating means.

[1516] (Claim 3)

[1517] 10. The system of claim 1, wherein the generated advertisement includes customization elements based on a user's name and preferences.

[1518] "Example 1"

[1519] (Claim 1)

[1520] A means for collecting personal information of users;

[1521] means for storing the personal information in a database;

[1522] means for receiving and storing original image advertisements from advertisement providers;

[1523] means for generating an advertisement optimized for an individual user based on the personal information and the original image advertisement;

[1524] means for delivering the generated advertisement to a user's display device;

[1525] means for displaying the generated advertisement on the display device;

[1526] means for collecting and storing the user's website browsing history and purchase history in a database;

[1527] A system including:

[1528] (Claim 2)

[1529] 2. The system according to claim 1, further comprising means for collecting said user's reaction data and feeding it back to said advertisement generating means.

[1530] (Claim 3)

[1531] The system according to claim 1, characterized in that the advertisement generation means generates advertisements including customization elements specific to individual users based on the personal information, website browsing history, and purchase history.

[1532] "Application Example 1"

[1533] (Claim 1)

[1534] means for collecting personal data of users;

[1535] means for storing the personal data in a database;

[1536] means for receiving and storing original image advertisements from advertisers;

[1537] means for generating an advertisement optimized for each user based on the personal data and the original image advertisement;

[1538] means for delivering the generated advertisement to a user terminal;

[1539] means for displaying the generated advertisement on the terminal;

[1540] means for collecting user action data (clicks, purchases, etc.) based on the generated advertisements;

[1541] A means of analyzing collected user action data using ad generation AI and optimizing the ad generation process;

[1542] A system including:

[1543] (Claim 2)

[1544] 2. The system according to claim 1, further comprising means for collecting said user's reaction data and feeding it back to said advertisement generating means.

[1545] (Claim 3)

[1546] 10. The system of claim 1, wherein the generated advertisement includes customization elements based on a user's name and preferences.

[1547] "Example 2: Combining Emotion Engines"

[1548] (Claim 1)

[1549] means for collecting personal data and emotional data of a user;

[1550] means for storing the personal data and emotion data in a database;

[1551] means for receiving and storing original image advertisements from advertisement providers;

[1552] means for generating an advertisement optimized for each user using a generative AI model based on the personal data, emotion data, and the original image advertisement;

[1553] means for delivering the generated advertisement to a user's information processing device;

[1554] a means for displaying the generated advertisement in the information processing device;

[1555] A system including:

[1556] (Claim 2)

[1557] 10. The system of claim 1, further comprising means for collecting reaction data and emotion data of the user and feeding the collected data back to the advertisement generating means.

[1558] (Claim 3)

[1559] 10. The system of claim 1, wherein the generated advertisement includes customization elements based on a user's identity and preferences.

[1560] "Application example 2 when combining emotion engines"

[1561] (Claim 1)

[1562] means for collecting personal data of users;

[1563] means for storing the personal data in a database;

[1564] means for receiving and storing original image advertisements from advertisers;

[1565] means for generating an advertisement optimized for each user based on the personal data and the original image advertisement;

[1566] a means for collecting user emotion data in real time;

[1567] means for further optimizing advertisements based on the personal data and the emotional data;

[1568] means for delivering the generated advertisement to a user terminal;

[1569] means for displaying the generated advertisement on the terminal;

[1570] A system including:

[1571] (Claim 2)

[1572] 2. The system according to claim 1, further comprising means for performing facial expression analysis and voice analysis to acquire the emotion data of the user.

[1573] (Claim 3)

[1574] 10. The system of claim 1, wherein the generated advertisement includes customization elements responsive to a user's real-time emotions. [Explanation of symbols]

[1575] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for collecting personal data of users; means for storing the personal data in a database; means for receiving and storing original image advertisements from advertisers; means for generating an advertisement optimized for each user based on the personal data and the original image advertisement; means for delivering the generated advertisement to a user terminal; means for displaying the generated advertisement on the terminal; A system including:

2. The system according to claim 1 , further comprising means for collecting said user's reaction data and feeding it back to said advertisement generating means.

3. 10. The system of claim 1, wherein the generated advertisement includes customization elements based on a user's name and preferences.

Images