system

Abstract

Provide a system. 【Solution means】 In a system where a data processing device uses artificial intelligence to provide information based on the generated advertisement information, Means for receiving data input from a user to set advertisement information, Means for recording the input advertisement information in a database for storage, Means for the artificial intelligence to adjust the priority and recommend information for the user's reference query based on the stored advertisement information, Means for displaying the recommended information on the user terminal, Means for evaluating the results related to information provision and generating a report, Means for analyzing data and providing personalized advertisement information in real time based on the user's trend information and interests, A system including the above.

Description

Technical Field

[0005] , ,

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a conventional information providing system, in order for business operators such as restaurants and accommodation facilities to effectively deliver information to consumers, it was necessary to perform search engine optimization (SEO) and listing advertisements that involve a large amount of advertising costs. Such a cost burden has been a major economic burden on the business operator side, and particularly small and medium-sized business operators have had the problem of being unable to compete appropriately. Furthermore, it has been difficult to provide optimal information in real time according to specific needs and situations of users, and it has been necessary to improve the matching accuracy with consumers.

Means for Solving the Problems

[0005] This invention provides a system that accepts input from businesses to set advertising information and stores that information in a database. Furthermore, based on the stored advertising information, artificial intelligence adjusts the recommendation level of information based on the user's search queries, profile, and behavioral history, and provides priority information. This makes it possible to effectively reach consumers and improve the efficiency of advertising costs. In addition, by analyzing the results of information provision, it supports further optimization of marketing strategies and reduces the financial burden on businesses.

[0006] An "information processing device" is a computer device that receives input from a user and performs data storage, processing, retrieval, and analysis.

[0007] Artificial intelligence refers to algorithms and systems that perform pattern recognition and reasoning based on diverse data to support decision-making and information provision.

[0008] "Priority" refers to the criteria used to determine the display order and importance of information when it is provided to a user.

[0009] A "database" is a collection of digital information that is organized in a way that makes it easy to search, retrieve, and process.

[0010] A "user terminal" is a computer or portable device that a user uses to access an information processing device and input or receive information.

[0011] A "report" is a document that summarizes the results of a system analysis and is created to show the status of information provision and the success of advertising campaigns. [Brief explanation of the drawing]

[0012] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2]This is a conceptual diagram showing an example of the essential functions of the data processing device and smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, when an emotion engine is combined. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0013] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0014] First, the terms used in the following description will be explained.

[0015] In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0016] In the following embodiments, a RAM (Random Access Memory) with a reference numeral is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0017] In the following embodiments, a storage with a reference numeral is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0018] In the following embodiments, a communication I / F (Interface) with a reference numeral is an interface including a communication processor and 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), or Bluetooth (registered trademark), and the like.

[0019] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0020] [First Embodiment]

[0021] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0022] As shown in Figure 1, the 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.

[0023] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0024] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0025] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0026] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0027] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0030] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0031] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0032] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0033] This invention relates to an information processing system that optimizes a business's advertising costs by effectively providing advertising information using artificial intelligence. This system includes a mechanism in which the business user inputs advertising information, and based on that, the system prioritizes providing information to consumers.

[0034] The user (business) first accesses the system via their device and inputs the information they wish to offer as an advertising campaign. This information may include, for example, introductions to new products or limited-time offers. The device receives this information and sends it to the server.

[0035] The server stores information entered by users in a database. Based on the stored data, the server uses artificial intelligence algorithms to analyze each user's profile and past behavior history, and provides information recommendations tailored to each individual. In this recommendation process, the algorithm is adjusted to take into account the consumer user's search queries, prioritizing the presentation of the most relevant information.

[0036] As a concrete example, consider a restaurant that wants to launch a new lunch menu. The restaurant owner uses this system to register an advertisement for the new menu and create a campaign with a set budget. When a consumer searches for "delicious lunch in Tokyo," the AI ​​selects restaurants relevant to that search query based on priority and displays them on the consumer's device. In this way, the restaurant can efficiently reach customers and effectively attract more patrons.

[0037] This system also has the functionality to monitor the effectiveness of advertisements and generate performance reports periodically. The server analyzes daily data and compiles reports on ad impressions, click-through rates, customer inquiries, and other metrics, which are then presented to the business. By utilizing this information, the business can formulate its next marketing strategy.

[0038] This format allows businesses to use advertising budgets more effectively than traditional methods, and provides consumers with more relevant information. Therefore, it is possible to improve the overall quality of information provided and enhance convenience for both businesses and consumers.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] Users (businesses) access the platform using their devices and open the new campaign registration screen. Here, they enter information such as the content of the advertisement (details and images), the advertising period, the target audience, and the advertising budget.

[0042] Step 2:

[0043] The terminal checks the entered campaign information and sends it to the server. The server verifies the received information (for example, checking the correctness of the input format and whether there are any missing items), and then saves the campaign information to the database.

[0044] Step 3:

[0045] The server sends the stored campaign information to the artificial intelligence module. The artificial intelligence module calculates a recommendation score based on the user's attributes, using previously accumulated user data (profile, search history, etc.).

[0046] Step 4:

[0047] When a user (consumer) searches for information from their device, the device sends a search query to the server. The server receives this query and queries the database and the artificial intelligence module.

[0048] Step 5:

[0049] The server selects the most relevant advertising information according to a recommendation score calculated by artificial intelligence, prioritizing and generating search results. This ensures that results that match the user's needs are provided.

[0050] Step 6:

[0051] The terminal displays priority information received from the server to the consumer user. Based on this, the consumer user selects items of interest, views details, or makes inquiries.

[0052] Step 7:

[0053] The server tracks user behavior (number of clicks, frequency of inquiries, etc.) during the campaign and collects performance data. Based on this, it analyzes the effectiveness of the advertisements, generates performance reports periodically, and notifies the business users.

[0054] (Example 1)

[0055] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0056] In today's information-saturated world, it is becoming increasingly difficult for consumers to access the information they truly need. Similarly, advertisers face the challenge of efficiently using their advertising budgets and effectively reaching their target audience. Therefore, there is a need to build a system that provides information beneficial to both consumers and advertisers.

[0057] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0058] In this invention, the server includes means for transmitting advertising information entered by a user to an information processing device, means for storing the entered advertising information in a database, and means for using artificial intelligence to analyze consumer profile information and past behavioral history based on the stored data, and for personalizing and recommending information. This makes it possible to efficiently provide advertising information that is suitable for consumer needs and to improve the cost-effectiveness for advertisers.

[0059] A "user" is an entity that inputs advertising information into the system and provides that information.

[0060] "Advertising information" refers to data that includes details about products and services offered to consumers, campaign details, and other relevant information.

[0061] An "information processing device" is a computing system that receives, stores, and processes advertising information sent by users.

[0062] A "database" is a storage system used to systematically store and manage advertising information and consumer data.

[0063] "Artificial intelligence" is a program or algorithm that performs analysis and makes recommendations based on data provided by users.

[0064] "Consumer profile information" refers to data that includes consumers' personal attributes, purchase history, and interests.

[0065] "Past behavioral history" refers to the data history of actions and search queries that consumers have taken in the past.

[0066] A "receiving device" is a device used by consumers to receive information.

[0067] This invention relates to an information processing system for effectively managing and distributing advertising information. Specific embodiments for carrying out the invention are described below.

[0068] System Overview

[0069] The system is centered around the user, the device, and the server, each playing a specific role. The user inputs advertising information and sends it to the server via the device. The server receives this information and uses artificial intelligence to deliver optimized advertisements.

[0070] Hardware and software to be used

[0071] User terminal: Users use a personal computer, tablet, or smartphone to enter advertising information via an input interface.

[0072] Server: Uses high-performance server equipment and is responsible for storing and analyzing advertising information and running artificial intelligence models.

[0073] Artificial intelligence software: Equipped with machine learning algorithms and data analysis tools, and implemented in programming languages ​​such as Python or R.

[0074] Data processing and calculations

[0075] The server stores the advertising information provided by the user in a database. The artificial intelligence model analyzes the stored information along with the consumer's profile and behavioral history data to perform calculations for optimal ad delivery. This allows for the presentation of advertising information tailored to the individual needs of each consumer.

[0076] Specific example

[0077] For example, if a user wants to promote a new product, they would use their device to input advertising information. They would enter information such as "We will run a new product promotion with a budget of up to 10,000 yen" and send it to the server. The server would then analyze this information and use a generative AI model to recommend the most effective way to reach consumers.

[0078] Example of a prompt

[0079] An example of a prompt might be: "Generate suggestions using an AI algorithm that takes into account the target audience's profile and past behavioral data, in order to provide effective information regarding the advertising campaign for our new product."

[0080] In this way, by implementing the invention, users can efficiently deliver advertisements to the market, and consumers can receive information that aligns with their interests.

[0081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0082] Step 1:

[0083] Users input advertising information using their devices. Specifically, users enter details about new products or campaigns, budget, target regions, etc., on the input screen. The input data is temporarily processed on the device, formatted, and then sent to the server. The input data includes product name, campaign period, budget limit, etc.

[0084] Step 2:

[0085] The device sends advertising information to the server. During transmission, the data is encrypted and securely transferred via a security protocol. The server temporarily stores the received advertising information in its internal memory and prepares to store it in its database. Once the data has been received, the server verifies that the data format is correct.

[0086] Step 3:

[0087] The server stores the received advertising information in a database. This storage process includes checking for duplicates with existing data and verifying data integrity. In the database, information is managed by advertising campaign ID and indexed to allow for efficient access in subsequent processing.

[0088] Step 4:

[0089] The server uses artificial intelligence to analyze each consumer's profile information and past behavioral history based on advertising information stored in a database. The inputs used are stored advertising information, consumer demographic data, and behavioral logs. The AI ​​model processes this data to generate the most suitable advertising recommendations for each individual consumer. The output is a personalized advertising list.

[0090] Step 5:

[0091] The server sends the generated ad recommendations to the consumer's device. Specifically, it selects the most relevant ads based on the search query specified by the consumer and determines their display priority. The output is reflected in the ad display area on the consumer's device. Through this, users can be automatically provided with optimized ads.

[0092] Step 6:

[0093] The server monitors the results of ad impressions and generates performance reports. This process analyzes metrics such as impressions, click-through rates, and conversion rates, and compiles them into daily and monthly reports. The output is a report that visualizes the effectiveness of the ads and is provided to the user to help them plan their next campaign.

[0094] (Application Example 1)

[0095] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0096] Conventional advertising information systems sometimes fail to adequately provide information that accurately captures users' needs and interests. Therefore, there is a need to improve the efficiency and immediacy of advertising while optimizing advertising costs. General advertising systems lack sufficient real-time data analysis for ad display, and are unable to immediately provide information tailored to users' interests. A new system is needed to solve these problems.

[0097] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0098] In this invention, the server includes means for analyzing data based on user behavior information and interests and providing personalized advertising information in real time, means for receiving data input from users to set advertising information, and means for artificial intelligence to adjust the priority of information in response to the user's reference queries based on the accumulated advertising information. This improves the personalization and immediacy of advertising information for users and enables optimization of advertising costs.

[0099] A "data processing device" is a device that performs tasks such as inputting, analyzing, generating, and displaying information, and plays a central role in systems that utilize digital information.

[0100] "Artificial intelligence" is a technology in which computers imitate human intellectual activity and possess the ability to learn and reason based on data.

[0101] "Data entry" is the process of receiving information from users and converting it into a format that can be processed within the system.

[0102] A "database" is a structured collection of information used to systematically store, organize, and manage information.

[0103] A "reference query" is a request or inquiry made by a user to a system in order to obtain specific information.

[0104] "Priority" is a criterion used to determine which information or tasks are more important and should be provided more frequently compared to others.

[0105] A "report" is a document that compiles facts, analysis results, and other information related to specific data and outcomes, and presents them to users.

[0106] "Trend information" refers to data that shows how users' behavior and interests change over time.

[0107] "Real-time" is a term that refers to the operation of a system that processes information and provides results almost simultaneously.

[0108] "Personalization" refers to adjusting information and services to suit the specific needs and preferences of individual users.

[0109] In this embodiment of the invention, an advertising information provision system utilizing artificial intelligence is constructed. The server receives data input from users and manages advertising information via an information processing device. Specifically, the server records the input advertising information in a database and uses artificial intelligence to adjust the priority of information for reference queries based on that information. This adjustment is performed to personalize the information based on accumulated trend information and user interests.

[0110] The server analyzes data in real time using artificial intelligence frameworks such as TENSORFLOW®. The analyzed information is reflected as advertising information displayed on the user's device. The device used to display the advertising information is the user's mobile device, such as a smartphone or tablet.

[0111] By instantly reflecting user trends and interests, advertising information becomes more relevant to the user. For example, when a user planning a trip searches for a tourist destination, advertisements for hotels and restaurants in that area are displayed in real time.

[0112] A key feature of this system is its use of a generative AI model to personalize advertisements through prompt text. For example, a prompt text might instruct a user searching for "Tokyo travel" to suggest relevant travel packages and hotel advertisements. Based on this instruction, the system can quickly provide users with the most relevant advertising information.

[0113] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0114] Step 1:

[0115] The server receives advertising data input from the user's terminal. The terminal then transfers the advertising information entered by the user to the server. This input includes product name, campaign details, budget, etc. The server receives this data and stores it in a database. This data accumulation prepares the foundational data used in subsequent processing.

[0116] Step 2:

[0117] The server retrieves advertising information stored in the database and performs analysis using artificial intelligence. The analysis incorporates user reference queries, trend information, and past behavioral history. Specifically, it uses TensorFlow to analyze behavioral history and adjust the priority of advertising information. The input data consists of queries and historical data, and the output is prioritized advertising information.

[0118] Step 3:

[0119] The server personalizes information based on prioritized advertising data. It uses a generative AI model to execute the prompt "Present ads based on user interests." This generates advertising data optimized for each user. The input is prioritized advertising data, and the output is personalized advertising data.

[0120] Step 4:

[0121] The server returns personalized advertising information to the user's device for display. Based on the received information, the device displays advertisements on the user screen in real time. Specifically, this can be done by displaying advertising information in a notification format or by embedding it within the app. The input is personalized advertising information, and the output is advertisements delivered visually to the user.

[0122] Step 5:

[0123] The server collects data on information provision and generates reports. It analyzes data such as user click-through rates, page views, and conversion rates to evaluate the effectiveness of the advertisements. The analysis generates a performance report for the advertising campaign, which is provided to the advertiser as output. This report is then used to inform future advertising strategies.

[0124] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0125] This invention provides a system that uses artificial intelligence and an emotion engine to deliver advertising information to consumers more effectively. This system sets up advertising information based on user input and stores it in a database. The stored information is then prioritized and recommended by artificial intelligence based on the user's search queries and profile. Furthermore, by combining this with an emotion engine, it is possible to dynamically change the display of information based on the user's emotional state, thereby maximizing the effectiveness of advertising.

[0126] Users (businesses) log in to the system via their terminal and enter the necessary information on a screen for creating advertising campaigns. The terminal sends the entered information to the server, where it is stored in a database. The server analyzes the user input in real time and uses artificial intelligence to prioritize providing information deemed most useful to the customer.

[0127] A notable feature is that when a user (consumer) uses the system, the emotion engine analyzes the user's voice and facial expressions in real time and acquires emotional data. This emotional data is sent to a server, where artificial intelligence adjusts advertising information to match the user's emotional state. For example, if the system recognizes that the user is in a positive state, more vivid and emotionally stimulating content will be recommended.

[0128] As a concrete example, consider a situation where a restaurant wants to advertise a special weekend dinner menu. When a consumer uses this system to search for "weekend dinner," and the device recognizes the user's emotional state as "looking happy," the artificial intelligence will prioritize displaying images along with details of the special dinner menu to match that positive emotion.

[0129] As advertising campaigns progress, the server collects and analyzes a wealth of data, including user sentiment data, to evaluate the success of the ads in real time and provide detailed reports to the advertisers. Based on these reports, advertisers can more effectively adjust their advertising strategies.

[0130] Thus, by combining an emotion engine and artificial intelligence, the present invention makes it possible to provide a highly personalized advertising experience that benefits both businesses and consumers.

[0131] The following describes the processing flow.

[0132] Step 1:

[0133] Users (businesses) access the advertising campaign registration page via their device. There, they enter detailed information about the service or product they want to advertise, the campaign period, and their budget.

[0134] Step 2:

[0135] The device sends the user's input information to the server. After the server verifies the legitimacy of the received advertising information, it saves the information to its database.

[0136] Step 3:

[0137] The server sends the accumulated advertising information to the artificial intelligence module. The AI ​​module analyzes the user's profile information and past behavior history, and sets the optimal priority score for each query.

[0138] Step 4:

[0139] The user (consumer) uses a device to search for information on the target. The device collects data through the user's voice or image data for sentiment analysis by an emotion engine.

[0140] Step 5:

[0141] The emotion engine recognizes the user's emotional state in real time based on collected audio and image data, and sends that information to the server.

[0142] Step 6:

[0143] The server uses an artificial intelligence module to analyze a combination of user search queries and sentiment data, and dynamically adjusts the priority of the displayed advertisements.

[0144] Step 7:

[0145] The device displays priority advertising information received from the server to the user (consumer). The displayed content is best suited to the user's current emotional state.

[0146] Step 8:

[0147] The server continuously collects consumer behavior and sentiment data during the execution of advertising campaigns, analyzes campaign performance, and generates detailed reports.

[0148] Step 9:

[0149] Users (businesses) can use the provided reports to evaluate the effectiveness of their advertising campaigns and use that information to develop their next marketing strategies.

[0150] (Example 2)

[0151] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0152] Traditional advertising delivery systems have a problem in that they do not adjust information based on user emotions, thus failing to maximize the effectiveness of advertisements. Furthermore, individual optimization based on user characteristics and behavioral history is not sufficiently implemented, resulting in advertisements that are not appealing to users.

[0153] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0154] In this invention, the server includes means for storing advertising information in a memory device, means for artificial intelligence to adjust priority and recommend information in response to the user's search commands, and means for analyzing the user's emotional state and dynamically adjusting the information based on the analysis results. This makes it possible to provide a highly personalized advertising experience based on the user's emotional state and individual characteristics.

[0155] "Advertising information" refers to information designed to promote specific products or services to users.

[0156] "User" refers to an individual or organization that creates, provides, or views advertisements through the system.

[0157] A "search command" refers to keywords or queries that users enter into a search engine or system to obtain specific information.

[0158] A "storage device" is a device for storing and managing data, and it plays a role in storing advertising information and user data.

[0159] "Artificial intelligence" refers to the technology that enables computer systems to mimic human intellectual behavior to perform data analysis and decision-making.

[0160] "Emotional state" refers to data that represents the user's current emotions and mood, and is analyzed from sources such as voice and facial expressions.

[0161] "Dynamic adjustment" refers to changing the system's display content and provided information in real time based on the user's emotional state and various data.

[0162] A "personalized advertising experience" means providing an experience tailored to each individual by displaying ads and delivering information that are optimized based on the characteristics and emotions of each user.

[0163] This invention is a system that provides users with a highly personalized advertising experience by integrating artificial intelligence and an emotion engine. This system functions through the coordinated efforts of the server, terminal, and user elements.

[0164] Users access the system using their devices and input information about their advertising campaigns. This information includes ad content, target audience, and campaign duration. The devices send this information to a server, which stores it in a database. Examples of database management systems used here include MySQL® and PostgreSQL.

[0165] The server uses artificial intelligence (AI) based on the information it receives to calculate the most optimal ad display. AI implementation typically utilizes frameworks such as TensorFlow or PyTorch. It also adjusts the ranking of ad information to prioritize information relevant to the user's search queries.

[0166] Simultaneously, the user's emotional state is collected in real time by the camera and microphone built into the device. The data collected by the device is analyzed using emotion analysis software, such as Emotion API or Affectiva. The analysis results are sent to a server, where artificial intelligence dynamically adjusts the information based on the emotional data.

[0167] For example, if a user searches for "weekend dinner" and the device recognizes the user's emotional state as "enjoyable," the server can select and display an advertisement image with vibrant colors. As a result, the advertisement can make a stronger impression on the user.

[0168] An example of a prompt would be, "Please list ad content that you would recommend to users in a positive emotional state." Using this prompt helps the generative AI model to more effectively select ads that fit the user's emotions.

[0169] Thus, the present invention aims to maximize the effectiveness of advertising by utilizing users' emotional states and characteristic information. This system allows businesses to effectively adjust their advertising strategies and provides users with an attractive experience.

[0170] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0171] Step 1:

[0172] Users enter advertising campaign information using their devices. This information includes ad content, target audience, and campaign duration. This information is temporarily stored on the device and formatted for transmission to the server.

[0173] Step 2:

[0174] The device sends formatted advertising information to the server. The data is sent to the server using the HTTP protocol. The input data is structured and optimized in JSON format. The server parses the received data for storage in a database and converts it into an SQL query.

[0175] Step 3:

[0176] The server stores the received advertising information in a database. A database management system used here might be MySQL, for example. The stored data is indexed for subsequent processing and optimized for searching.

[0177] Step 4:

[0178] While a user is using the system, the device uses its camera and microphone to capture the user's voice and facial expressions. This input data is analyzed in real time using the Emotion API. This analysis yields output indicating the user's emotional state (e.g., data such as "happy" or "excited").

[0179] Step 5:

[0180] The server receives the results of the sentiment analysis and uses an artificial intelligence model to determine which advertisement is most appropriate for the user's current emotional state. The input data includes the user's emotional state and past behavioral history, and the AI ​​uses this information to calculate recommended advertisements and output the results.

[0181] Step 6:

[0182] The server sends the selected advertising information to the device and displays it to the user. The transmitted data includes the media files necessary for display (such as images and videos) and is immediately reflected in the device's UI.

[0183] Step 7:

[0184] The server records the results of ad displays and user reactions, and evaluates their effectiveness using big data analysis tools. The input data includes metrics such as emotional states and click-through rates, and the output includes conversion rates and overall ad effectiveness.

[0185] (Application Example 2)

[0186] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0187] Traditional advertising delivery systems struggle to consider users' real-time emotional states, making it difficult to optimize ad engagement. Therefore, there is a growing need for more personalized and emotionally resonant ad displays.

[0188] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0189] In this invention, the server includes means for receiving input from a user to set advertising information, means for storing the input advertising information in a database, means for artificial intelligence to adjust priority and recommend information in response to the user's search query based on the stored advertising information, means for analyzing the user's facial movements and determining the resulting emotions, and means for adjusting the displayed advertising information based on the emotions determined by the emotion analysis means. This makes it possible to display advertising information that is adapted to the user's emotional state.

[0190] An "information processing device" is a machine or device that receives data, processes it, and provides information to users.

[0191] "Artificial intelligence" is a technology that allows computer systems to autonomously analyze and process information through learning and reasoning as they operate.

[0192] "Advertising information" refers to detailed data and visual content about products and services, provided with the aim of attracting the user's interest.

[0193] A "database" is a system for organizing information structurally and efficiently storing, searching, and managing it.

[0194] "Emotion analysis means" refers to technology for detecting and interpreting a user's emotional state based on facial movements, voice, and other factors.

[0195] "Adjusting priorities" refers to determining the importance and display order of information that should be presented based on specific criteria or conditions.

[0196] A "user terminal" is a device that a user directly operates to acquire or input information.

[0197] As an embodiment of this invention, an emotion-adaptive advertising display system will be described. This system comprises a user terminal, a server as an information processing device, and an emotion analysis engine.

[0198] First, the user terminal receives user input using a device such as a smartphone or smart glasses, and sets up advertising information. This input information is sent to the server to be stored in a database. On the server, artificial intelligence adjusts the priority of information based on the user's search query and recommends the most suitable advertising information based on the stored advertising information.

[0199] Furthermore, the user's facial movements and voice are captured in real time using the user's device's camera and microphone, and an emotion analysis engine analyzes this data to determine the user's emotional state. This emotional state is sent to a server, and based on the information obtained from the emotion analysis, the displayed advertising information is dynamically adjusted. For this analysis process, a platform such as GOOGLE TENSOR® Flow can be used.

[0200] For example, if a user searches for "lunch spots" and their facial expression is analyzed as showing "surprise," the server can prioritize displaying information about new menu items that would delight them with their surprise, along with vivid images. This can enhance the effectiveness of advertising.

[0201] The evaluation and feedback of the results of this ad engine are performed on the server side and provided to advertisers as a detailed report. This report includes user sentiment data and ad performance data, which helps to adjust the ad strategy.

[0202] An example of a prompt message would be: "Output an example of an ad display when the user is interested in lunch. If their emotion is determined to be surprise, what information should be prioritized?" This would be the format of the input to the generative AI model.

[0203] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0204] Step 1:

[0205] The user terminal receives advertising information input from the user. This input includes an overview of the advertisement, target audience, and display period. This information is sent from the terminal to the server in a structured format and stored in a database. The output is form data sent to the server.

[0206] Step 2:

[0207] The server stores the received advertising information in a database. Simultaneously, when a user makes a search query, it prepares to use artificial intelligence to calculate the priority of the information based on the accumulated advertising data. The output is a list of recommended ads for the search query.

[0208] Step 3:

[0209] The user terminal receives the user's search query. Based on this input, the terminal sends the query to the server. The output is the data transmitted to the server as the search query.

[0210] Step 4:

[0211] The server uses artificial intelligence to select high-priority advertisements based on search queries. This process takes into account the user's past behavior history and profile, and utilizes generative AI models such as TensorFlow. The output is recommended advertisement information sent to the user's device.

[0212] Step 5:

[0213] The user's device receives recommended advertising information. Furthermore, it captures the user's facial expressions and voice in real time using the camera and microphone, and sends this data to an emotion analysis engine. The output consists of facial expression data and voice data for emotion analysis.

[0214] Step 6:

[0215] The server uses an emotion analysis engine to determine the user's emotions based on the received facial and voice data. Based on this determination, it dynamically adjusts the advertising information and re-selects the most suitable advertisement for the user. The output is the adjusted advertising information.

[0216] Step 7:

[0217] The adjusted advertising information is sent to the user's device. The user's device then displays this advertisement to the user. The user's reaction is collected and sent to the server as feedback. The output consists of the advertisement screen displayed to the user and the feedback data.

[0218] Step 8:

[0219] The server analyzes feedback data and generates a report on the effectiveness of the advertisements. This report is provided to the advertiser to help improve their future advertising strategies. The output is an analytical report provided to the advertiser.

[0220] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0221] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0222] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0223] [Second Embodiment]

[0224] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0225] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0226] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0227] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0228] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0229] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0230] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0231] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0232] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0233] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0234] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0235] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0236] This invention relates to an information processing system that optimizes a business's advertising costs by effectively providing advertising information using artificial intelligence. This system includes a mechanism in which the business user inputs advertising information, and based on that, the system prioritizes providing information to consumers.

[0237] The user (business) first accesses the system via their device and inputs the information they wish to offer as an advertising campaign. This information may include, for example, introductions to new products or limited-time offers. The device receives this information and sends it to the server.

[0238] The server stores information entered by users in a database. Based on the stored data, the server uses artificial intelligence algorithms to analyze each user's profile and past behavior history, and provides information recommendations tailored to each individual. In this recommendation process, the algorithm is adjusted to take into account the consumer user's search queries, prioritizing the presentation of the most relevant information.

[0239] As a concrete example, consider a restaurant that wants to launch a new lunch menu. The restaurant owner uses this system to register an advertisement for the new menu and create a campaign with a set budget. When a consumer searches for "delicious lunch in Tokyo," the AI ​​selects restaurants relevant to that search query based on priority and displays them on the consumer's device. In this way, the restaurant can efficiently reach customers and effectively attract more patrons.

[0240] This system also has the functionality to monitor the effectiveness of advertisements and generate performance reports periodically. The server analyzes daily data and compiles reports on ad impressions, click-through rates, customer inquiries, and other metrics, which are then presented to the business. By utilizing this information, the business can formulate its next marketing strategy.

[0241] This format allows businesses to use advertising budgets more effectively than traditional methods, and provides consumers with more relevant information. Therefore, it is possible to improve the overall quality of information provided and enhance convenience for both businesses and consumers.

[0242] The following describes the processing flow.

[0243] Step 1:

[0244] Users (businesses) access the platform using their devices and open the new campaign registration screen. Here, they enter information such as the content of the advertisement (details and images), the advertising period, the target audience, and the advertising budget.

[0245] Step 2:

[0246] The terminal checks the entered campaign information and sends it to the server. The server verifies the received information (for example, checking the correctness of the input format and whether there are any missing items), and then saves the campaign information to the database.

[0247] Step 3:

[0248] The server sends the stored campaign information to the artificial intelligence module. The artificial intelligence module calculates a recommendation score based on the user's attributes, using previously accumulated user data (profile, search history, etc.).

[0249] Step 4:

[0250] When a user (consumer) searches for information from their device, the device sends a search query to the server. The server receives this query and queries the database and the artificial intelligence module.

[0251] Step 5:

[0252] The server selects the most relevant advertising information according to a recommendation score calculated by artificial intelligence, prioritizing and generating search results. This ensures that results that match the user's needs are provided.

[0253] Step 6:

[0254] The terminal displays priority information received from the server to the consumer user. Based on this, the consumer user selects items of interest, views details, or makes inquiries.

[0255] Step 7:

[0256] The server tracks user behavior (number of clicks, frequency of inquiries, etc.) during the campaign and collects performance data. Based on this, it analyzes the effectiveness of the advertisements, generates performance reports periodically, and notifies the business users.

[0257] (Example 1)

[0258] Next, we will describe Example 1. 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."

[0259] In today's information-saturated world, it is becoming increasingly difficult for consumers to access the information they truly need. Similarly, advertisers face the challenge of efficiently using their advertising budgets and effectively reaching their target audience. Therefore, there is a need to build a system that provides information beneficial to both consumers and advertisers.

[0260] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0261] In this invention, the server includes means for transmitting advertising information entered by a user to an information processing device, means for storing the entered advertising information in a database, and means for using artificial intelligence to analyze consumer profile information and past behavioral history based on the stored data, and for personalizing and recommending information. This makes it possible to efficiently provide advertising information that is suitable for consumer needs and to improve the cost-effectiveness for advertisers.

[0262] A "user" is an entity that inputs advertising information into the system and provides that information.

[0263] "Advertising information" refers to data that includes details about products and services offered to consumers, campaign details, and other relevant information.

[0264] An "information processing device" is a computing system that receives, stores, and processes advertising information sent by users.

[0265] A "database" is a storage system used to systematically store and manage advertising information and consumer data.

[0266] "Artificial intelligence" is a program or algorithm that performs analysis and makes recommendations based on data provided by users.

[0267] "Consumer profile information" refers to data that includes consumers' personal attributes, purchase history, and interests.

[0268] "Past behavioral history" refers to the data history of actions and search queries that consumers have taken in the past.

[0269] A "receiving device" is a device used by consumers to receive information.

[0270] This invention relates to an information processing system for effectively managing and distributing advertising information. Specific embodiments for carrying out the invention are described below.

[0271] System Overview

[0272] The system is centered around the user, the device, and the server, each playing a specific role. The user inputs advertising information and sends it to the server via the device. The server receives this information and uses artificial intelligence to deliver optimized advertisements.

[0273] Hardware and software to be used

[0274] User terminal: Users use a personal computer, tablet, or smartphone to enter advertising information via an input interface.

[0275] Server: It uses a high-performance server device and is responsible for storing, analyzing advertisement information, and executing artificial intelligence models.

[0276] Artificial intelligence software: It has machine learning algorithms and data analysis tools and is implemented in programming languages such as Python or R.

[0277] Data processing and operations

[0278] The server stores the advertisement information provided by the user in the database. The artificial intelligence model analyzes the stored information together with the consumer's profile and behavioral history data and performs arithmetic processing for optimal advertisement delivery. As a result, advertisement information suitable for the individual needs of consumers can be presented.

[0279] Specific example

[0280] For example, when a user wants to promote a new product, they use a terminal to input advertisement information. Information such as "Implement a new product promotion with a budget of up to 10,000 yen" is input and sent to the server. The server proceeds with analysis based on this information and makes recommendations by the generated AI model for the most effective reach to consumers.

[0281] Example of a prompt sentence

[0282] As an example of a prompt sentence, "Please generate a proposal using an AI algorithm considering the profile of the target layer and past behavioral data in order to provide effective information regarding the advertisement campaign for the new product." can be considered.

[0283] In this way, by implementing the invention, the user can efficiently distribute advertisements in the market, and the consumer can receive information along their own interests.

[0284] The flow of specific processing in Example will be described using Fig. 11.

[0285] Step 1:

[0286] The user inputs advertising information using a terminal. Specifically, the user describes new products, campaign details, budget, target regions, etc. on the input screen. The input data is temporarily processed by the terminal, formatted, and then sent to the server. The input data includes product names, campaign periods, budget limits, etc.

[0287] Step 2:

[0288] The terminal sends the advertising information to the server. When sending, the data is encrypted and securely transferred via a security protocol. The server temporarily takes in the received advertising information into its internal memory and prepares to save it in the database. When the data reception is complete, the server checks that the data format is appropriate.

[0289] Step 3:

[0290] The server saves the received advertising information in the database. In this saving process, duplicate checks with existing data and data integrity checks are performed. In the database, information is managed by advertising campaign ID and indexed so that it can be efficiently accessed in later processing.

[0291] Step 4:

[0292] Based on the advertising information saved in the database, the server uses artificial intelligence to analyze each consumer's profile information and past behavior history. As input, the saved advertising information and the consumer's demographic data and behavior logs are used. The artificial intelligence model processes these data and generates the most suitable advertising recommendations for specific consumers. The output is a personalized advertising list.

[0293] Step 5:

[0294] The server sends the generated ad recommendations to the consumer's device. Specifically, it selects the most relevant ads based on the search query specified by the consumer and determines their display priority. The output is reflected in the ad display area on the consumer's device. Through this, users can be automatically provided with optimized ads.

[0295] Step 6:

[0296] The server monitors the results of ad impressions and generates performance reports. This process analyzes metrics such as impressions, click-through rates, and conversion rates, and compiles them into daily and monthly reports. The output is a report that visualizes the effectiveness of the ads and is provided to the user to help them plan their next campaign.

[0297] (Application Example 1)

[0298] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0299] Conventional advertising information systems sometimes fail to adequately provide information that accurately captures users' needs and interests. Therefore, there is a need to improve the efficiency and immediacy of advertising while optimizing advertising costs. General advertising systems lack sufficient real-time data analysis for ad display, and are unable to immediately provide information tailored to users' interests. A new system is needed to solve these problems.

[0300] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0301] In this invention, the server includes means for analyzing data based on the usage trends and interests of users and providing personalized advertising information in real time, means for receiving data input from users to set advertising information, and means for the artificial intelligence to adjust the priority for the reference queries of users and recommend information based on the accumulated advertising information. As a result, the personalization and immediacy of advertising information for users are improved, and the optimization of advertising costs becomes possible.

[0302] A "data processing device" is a device that performs operations such as input, analysis, generation, and display of information, and is the core of a system that utilizes digital information.

[0303] "Artificial intelligence" is a technology in which a computer imitates human intellectual activities and has the ability to learn and make inferences based on data.

[0304] "Data input" is a process of receiving information from a user and converting it into a form that can be processed within the system.

[0305] A "database" is a structured collection of information for systematically storing, organizing, and managing information.

[0306] A "reference query" is a request or inquiry for information that a user makes to the system to obtain specific information.

[0307] "Priority" is a criterion for positioning a specific item as more important and to be provided more than others among multiple pieces of information or tasks.

[0308] A "report" is a document that summarizes facts, analysis results, etc. regarding predetermined information and achievements and presents them to users.

[0309] "Usage trend information" is data indicating how the actions and interests of users change over time.

[0310] ​"Real-time" is a term that refers to the operation of a system that processes information and provides results almost simultaneously.

[0311] "Personalization" refers to adjusting information and services to suit the specific needs and preferences of individual users.

[0312] In this embodiment of the invention, an advertising information provision system utilizing artificial intelligence is constructed. The server receives data input from users and manages advertising information via an information processing device. Specifically, the server records the input advertising information in a database and uses artificial intelligence to adjust the priority of information for reference queries based on that information. This adjustment is performed to personalize the information based on accumulated trend information and user interests.

[0313] The server analyzes data in real time using artificial intelligence frameworks such as TensorFlow. The analyzed information is reflected as advertising information displayed on the user's device. The device used to display the advertising information is the user's mobile device, such as a smartphone or tablet.

[0314] By instantly reflecting user trends and interests, advertising information becomes more relevant to the user. For example, when a user planning a trip searches for a tourist destination, advertisements for hotels and restaurants in that area are displayed in real time.

[0315] A key feature of this system is its use of a generative AI model to personalize advertisements through prompt text. For example, a prompt text might instruct a user searching for "Tokyo travel" to suggest relevant travel packages and hotel advertisements. Based on this instruction, the system can quickly provide users with the most relevant advertising information.

[0316] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0317] Step 1:

[0318] The server receives advertising data input from the user's terminal. The terminal then transfers the advertising information entered by the user to the server. This input includes product name, campaign details, budget, etc. The server receives this data and stores it in a database. This data accumulation prepares the foundational data used in subsequent processing.

[0319] Step 2:

[0320] The server retrieves advertising information stored in the database and performs analysis using artificial intelligence. The analysis incorporates user reference queries, trend information, and past behavioral history. Specifically, it uses TensorFlow to analyze behavioral history and adjust the priority of advertising information. The input data consists of queries and historical data, and the output is prioritized advertising information.

[0321] Step 3:

[0322] The server personalizes information based on prioritized advertising data. It uses a generative AI model to execute the prompt "Present ads based on user interests." This generates advertising data optimized for each user. The input is prioritized advertising data, and the output is personalized advertising data.

[0323] Step 4:

[0324] The server returns personalized advertising information to the user's device for display. Based on the received information, the device displays advertisements on the user screen in real time. Specifically, this can be done by displaying advertising information in a notification format or by embedding it within the app. The input is personalized advertising information, and the output is advertisements delivered visually to the user.

[0325] Step 5:

[0326] The server collects data on information provision and generates reports. It analyzes data such as user click-through rates, page views, and conversion rates to evaluate the effectiveness of the advertisements. The analysis generates a performance report for the advertising campaign, which is provided to the advertiser as output. This report is then used to inform future advertising strategies.

[0327] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0328] This invention provides a system that uses artificial intelligence and an emotion engine to deliver advertising information to consumers more effectively. This system sets up advertising information based on user input and stores it in a database. The stored information is then prioritized and recommended by artificial intelligence based on the user's search queries and profile. Furthermore, by combining this with an emotion engine, it is possible to dynamically change the display of information based on the user's emotional state, thereby maximizing the effectiveness of advertising.

[0329] Users (businesses) log in to the system via their terminal and enter the necessary information on a screen for creating advertising campaigns. The terminal sends the entered information to the server, where it is stored in a database. The server analyzes the user input in real time and uses artificial intelligence to prioritize providing information deemed most useful to the customer.

[0330] A notable feature is that when a user (consumer) uses the system, the emotion engine analyzes the user's voice and facial expressions in real time and acquires emotional data. This emotional data is sent to a server, where artificial intelligence adjusts advertising information to match the user's emotional state. For example, if the system recognizes that the user is in a positive state, more vivid and emotionally stimulating content will be recommended.

[0331] As a concrete example, consider a situation where a restaurant wants to advertise a special weekend dinner menu. When a consumer uses this system to search for "weekend dinner," and the device recognizes the user's emotional state as "looking happy," the artificial intelligence will prioritize displaying images along with details of the special dinner menu to match that positive emotion.

[0332] As advertising campaigns progress, the server collects and analyzes a wealth of data, including user sentiment data, to evaluate the success of the ads in real time and provide detailed reports to the advertisers. Based on these reports, advertisers can more effectively adjust their advertising strategies.

[0333] Thus, by combining an emotion engine and artificial intelligence, the present invention makes it possible to provide a highly personalized advertising experience that benefits both businesses and consumers.

[0334] The following describes the processing flow.

[0335] Step 1:

[0336] Users (businesses) access the advertising campaign registration page via their device. There, they enter detailed information about the service or product they want to advertise, the campaign period, and their budget.

[0337] Step 2:

[0338] The device sends the user's input information to the server. After the server verifies the legitimacy of the received advertising information, it saves the information to its database.

[0339] Step 3:

[0340] The server sends the accumulated advertising information to the artificial intelligence module. The AI ​​module analyzes the user's profile information and past behavior history, and sets the optimal priority score for each query.

[0341] Step 4:

[0342] The user (consumer) uses a device to search for information on the target. The device collects data through the user's voice or image data for sentiment analysis by an emotion engine.

[0343] Step 5:

[0344] The emotion engine recognizes the user's emotional state in real time based on collected audio and image data, and sends that information to the server.

[0345] Step 6:

[0346] The server uses an artificial intelligence module to analyze a combination of user search queries and sentiment data, and dynamically adjusts the priority of the displayed advertisements.

[0347] Step 7:

[0348] The device displays priority advertising information received from the server to the user (consumer). The displayed content is best suited to the user's current emotional state.

[0349] Step 8:

[0350] The server continuously collects consumer behavior and sentiment data during the execution of advertising campaigns, analyzes campaign performance, and generates detailed reports.

[0351] Step 9:

[0352] Users (businesses) can use the provided reports to evaluate the effectiveness of their advertising campaigns and use that information to develop their next marketing strategies.

[0353] (Example 2)

[0354] Next, we will describe Example 2. 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".

[0355] Traditional advertising delivery systems have a problem in that they do not adjust information based on user emotions, thus failing to maximize the effectiveness of advertisements. Furthermore, individual optimization based on user characteristics and behavioral history is not sufficiently implemented, resulting in advertisements that are not appealing to users.

[0356] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0357] In this invention, the server includes means for storing advertising information in a memory device, means for artificial intelligence to adjust priority and recommend information in response to the user's search commands, and means for analyzing the user's emotional state and dynamically adjusting the information based on the analysis results. This makes it possible to provide a highly personalized advertising experience based on the user's emotional state and individual characteristics.

[0358] "Advertising information" refers to information designed to promote specific products or services to users.

[0359] "User" refers to an individual or organization that creates, provides, or views advertisements through the system.

[0360] A "search command" refers to keywords or queries that users enter into a search engine or system to obtain specific information.

[0361] A "storage device" is a device for storing and managing data, and it plays a role in storing advertising information and user data.

[0362] "Artificial intelligence" refers to the technology in which computer systems imitate human intellectual behavior to perform data analysis and decision-making.

[0363] "Emotional state" refers to data that represents the user's current emotions and mood, and is analyzed from sources such as voice and facial expressions.

[0364] "Dynamic adjustment" refers to changing the system's display content and provided information in real time based on the user's emotional state and various data.

[0365] A "personalized advertising experience" means providing an experience tailored to each individual by displaying ads and delivering information that are optimized based on the characteristics and emotions of each user.

[0366] This invention is a system that provides users with a highly personalized advertising experience by integrating artificial intelligence and an emotion engine. This system functions through the coordinated efforts of the server, terminal, and user elements.

[0367] Users access the system using their devices and input information about their advertising campaigns. This information includes ad content, target audience, and campaign duration. The devices send this information to a server, which stores it in a database. Examples of database management systems used in this process include MySQL and PostgreSQL.

[0368] The server uses artificial intelligence (AI) based on the information it receives to calculate the most optimal ad display. AI implementation typically utilizes frameworks such as TensorFlow or PyTorch. It also adjusts the ranking of ad information to prioritize information relevant to the user's search queries.

[0369] Simultaneously, the user's emotional state is collected in real time by the camera and microphone built into the device. The data collected by the device is analyzed using emotion analysis software, such as Emotion API or Affectiva. The analysis results are sent to a server, where artificial intelligence dynamically adjusts the information based on the emotional data.

[0370] For example, if a user searches for "weekend dinner" and the device recognizes the user's emotional state as "enjoyable," the server can select and display an advertisement image with vibrant colors. As a result, the advertisement can make a stronger impression on the user.

[0371] An example of a prompt would be, "Please list ad content that you would recommend to users in a positive emotional state." Using this prompt helps the generative AI model to more effectively select ads that fit the user's emotions.

[0372] Thus, the present invention aims to maximize the effectiveness of advertising by utilizing users' emotional states and characteristic information. This system allows businesses to effectively adjust their advertising strategies and provides users with an attractive experience.

[0373] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0374] Step 1:

[0375] Users enter advertising campaign information using their devices. This information includes ad content, target audience, and campaign duration. This information is temporarily stored on the device and formatted for transmission to the server.

[0376] Step 2:

[0377] The device sends formatted advertising information to the server. The data is sent to the server using the HTTP protocol. The input data is structured and optimized in JSON format. The server parses the received data for storage in a database and converts it into an SQL query.

[0378] Step 3:

[0379] The server stores the received advertising information in a database. A database management system used here might be MySQL, for example. The stored data is indexed for subsequent processing and optimized for searching.

[0380] Step 4:

[0381] While a user is using the system, the device uses its camera and microphone to capture the user's voice and facial expressions. This input data is analyzed in real time using the Emotion API. This analysis yields output indicating the user's emotional state (e.g., data such as "happy" or "excited").

[0382] Step 5:

[0383] The server receives the results of the sentiment analysis and uses an artificial intelligence model to determine which advertisement is most appropriate for the user's current emotional state. The input data includes the user's emotional state and past behavioral history, and the AI ​​uses this information to calculate recommended advertisements and output the results.

[0384] Step 6:

[0385] The server sends the selected advertising information to the device and displays it to the user. The transmitted data includes the media files necessary for display (such as images and videos) and is immediately reflected in the device's UI.

[0386] Step 7:

[0387] The server records the results of ad displays and user reactions, and evaluates their effectiveness using big data analysis tools. The input data includes metrics such as emotional states and click-through rates, and the output includes conversion rates and overall ad effectiveness.

[0388] (Application Example 2)

[0389] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0390] Traditional advertising delivery systems have difficulty considering users' real-time emotional states, making it challenging to optimize ad engagement. Therefore, there is a need for more personalized and emotionally resonant ad displays.

[0391] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0392] In this invention, the server includes means for receiving input from a user to set advertising information, means for storing the input advertising information in a database, means for artificial intelligence to adjust priority and recommend information in response to the user's search query based on the stored advertising information, means for analyzing the user's facial movements and determining the resulting emotions, and means for adjusting the displayed advertising information based on the emotions determined by the emotion analysis means. This makes it possible to display advertising information that is adapted to the user's emotional state.

[0393] An "information processing device" is a machine or device that receives data, processes it, and provides information to users.

[0394] "Artificial intelligence" is a technology that enables computer systems to autonomously analyze and process information through learning and reasoning as they operate.

[0395] "Advertising information" refers to detailed data and visual content about products and services, provided with the aim of attracting the user's interest.

[0396] A "database" is a system for organizing information structurally and efficiently storing, searching, and managing it.

[0397] "Emotion analysis means" refers to technology for detecting and interpreting a user's emotional state based on facial movements, voice, and other factors.

[0398] "Adjusting priorities" refers to determining the importance and display order of information that should be presented based on specific criteria or conditions.

[0399] A "user terminal" is a device that a user directly operates to acquire or input information.

[0400] As an embodiment of this invention, an emotion-adaptive advertising display system will be described. This system comprises a user terminal, a server as an information processing device, and an emotion analysis engine.

[0401] First, the user terminal receives user input using a device such as a smartphone or smart glasses, and sets up advertising information. This input information is sent to the server to be stored in a database. On the server, artificial intelligence adjusts the priority of information based on the user's search query and recommends the most suitable advertising information based on the stored advertising information.

[0402] Furthermore, the user's facial movements and voice are captured in real time using the user's device's camera and microphone, and an emotion analysis engine analyzes this data to determine the user's emotional state. This emotional state is sent to a server, and based on the information obtained from the emotion analysis, the displayed advertising information is dynamically adjusted. This analysis process can utilize a platform such as Google® TensorFlow.

[0403] For example, if a user searches for "lunch spots" and their facial expression is analyzed as showing "surprise," the server can prioritize displaying information about new menu items that would delight them with their surprise, along with vivid images. This can enhance the effectiveness of advertising.

[0404] The evaluation and feedback of the results of this ad engine are performed on the server side and provided to advertisers as a detailed report. This report includes user sentiment data and ad performance data, which helps to adjust the ad strategy.

[0405] An example of a prompt message would be: "Output an example of an ad display when the user is interested in lunch. If their emotion is determined to be surprise, what information should be prioritized?" This would be the format of the input to the generative AI model.

[0406] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0407] Step 1:

[0408] The user terminal receives advertising information input from the user. This input includes an overview of the advertisement, target audience, and display period. This information is sent from the terminal to the server in a structured format and stored in a database. The output is form data sent to the server.

[0409] Step 2:

[0410] The server stores the received advertising information in a database. Simultaneously, when a user makes a search query, it prepares to use artificial intelligence to calculate the priority of the information based on the accumulated advertising data. The output is a list of recommended ads for the search query.

[0411] Step 3:

[0412] The user terminal receives the user's search query. Based on this input, the terminal sends the query to the server. The output is the data transmitted to the server as the search query.

[0413] Step 4:

[0414] The server uses artificial intelligence to select high-priority advertisements based on search queries. This process takes into account the user's past behavior history and profile, and utilizes generative AI models such as TensorFlow. The output is recommended advertisement information sent to the user's device.

[0415] Step 5:

[0416] The user's device receives recommended advertising information. Furthermore, it captures the user's facial expressions and voice in real time using the camera and microphone, and sends this data to an emotion analysis engine. The output consists of facial expression data and voice data for emotion analysis.

[0417] Step 6:

[0418] The server uses an emotion analysis engine to determine the user's emotions based on the received facial and voice data. Based on this determination, it dynamically adjusts the advertising information and re-selects the most suitable advertisement for the user. The output is the adjusted advertising information.

[0419] Step 7:

[0420] The adjusted advertising information is sent to the user's device. The user's device then displays this advertisement to the user. The user's reaction is collected and sent to the server as feedback. The output consists of the advertisement screen displayed to the user and the feedback data.

[0421] Step 8:

[0422] The server analyzes feedback data and generates a report on the effectiveness of the advertisements. This report is provided to the advertiser to help improve their future advertising strategies. The output is an analytical report provided to the advertiser.

[0423] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0424] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0425] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0426] [Third Embodiment]

[0427] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0428] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0429] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0430] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0431] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0432] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0433] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0434] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0435] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0436] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0437] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0438] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0439] This invention relates to an information processing system that optimizes a business's advertising costs by effectively providing advertising information using artificial intelligence. This system includes a mechanism in which the business user inputs advertising information, and based on that, the system prioritizes providing information to consumers.

[0440] The user (business) first accesses the system via their device and inputs the information they wish to offer as an advertising campaign. This information may include, for example, introductions to new products or limited-time offers. The device receives this information and sends it to the server.

[0441] The server stores information entered by users in a database. Based on the stored data, the server uses artificial intelligence algorithms to analyze each user's profile and past behavior history, and provides information recommendations tailored to each individual. In this recommendation process, the algorithm is adjusted to take into account the consumer user's search queries, prioritizing the presentation of the most relevant information.

[0442] As a concrete example, consider a restaurant that wants to launch a new lunch menu. The restaurant owner uses this system to register an advertisement for the new menu and create a campaign with a set budget. When a consumer searches for "delicious lunch in Tokyo," the AI ​​selects restaurants relevant to that search query based on priority and displays them on the consumer's device. In this way, the restaurant can efficiently reach customers and effectively attract more patrons.

[0443] This system also has the functionality to monitor the effectiveness of advertisements and generate performance reports periodically. The server analyzes daily data and compiles reports on ad impressions, click-through rates, customer inquiries, and other metrics, which are then presented to the business. By utilizing this information, the business can formulate its next marketing strategy.

[0444] This format allows businesses to use advertising budgets more effectively than traditional methods, and provides consumers with more relevant information. Therefore, it is possible to improve the overall quality of information provided and enhance convenience for both businesses and consumers.

[0445] The following describes the processing flow.

[0446] Step 1:

[0447] Users (businesses) access the platform using their devices and open the new campaign registration screen. Here, they enter information such as the content of the advertisement (details and images), the advertising period, the target audience, and the advertising budget.

[0448] Step 2:

[0449] The terminal checks the entered campaign information and sends it to the server. The server verifies the received information (for example, checking the correctness of the input format and whether there are any missing items), and then saves the campaign information to the database.

[0450] Step 3:

[0451] The server sends the stored campaign information to the artificial intelligence module. The artificial intelligence module calculates a recommendation score based on the user's attributes, using previously accumulated user data (profile, search history, etc.).

[0452] Step 4:

[0453] When a user (consumer) searches for information from their device, the device sends a search query to the server. The server receives this query and queries the database and the artificial intelligence module.

[0454] Step 5:

[0455] The server selects the most relevant advertising information according to a recommendation score calculated by artificial intelligence, prioritizing and generating search results. This ensures that results that match the user's needs are provided.

[0456] Step 6:

[0457] The terminal displays priority information received from the server to the consumer user. Based on this, the consumer user selects items of interest, views details, or makes inquiries.

[0458] Step 7:

[0459] The server tracks user behavior (number of clicks, frequency of inquiries, etc.) during the campaign and collects performance data. Based on this, it analyzes the effectiveness of the advertisements, generates performance reports periodically, and notifies the business users.

[0460] (Example 1)

[0461] Next, we will describe Example 1. 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."

[0462] In today's information-saturated world, it is becoming increasingly difficult for consumers to access the information they truly need. Similarly, advertisers face the challenge of efficiently using their advertising budgets and effectively reaching their target audience. Therefore, there is a need to build a system that provides information beneficial to both consumers and advertisers.

[0463] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0464] In this invention, the server includes means for transmitting advertising information entered by a user to an information processing device, means for storing the entered advertising information in a database, and means for using artificial intelligence to analyze consumer profile information and past behavioral history based on the stored data, and for personalizing and recommending information. This makes it possible to efficiently provide advertising information that is suitable for consumer needs and to improve the cost-effectiveness for advertisers.

[0465] A "user" is an entity that inputs advertising information into the system and provides that information.

[0466] "Advertising information" refers to data that includes details about products and services offered to consumers, campaign details, and other relevant information.

[0467] An "information processing device" is a computing system that receives, stores, and processes advertising information sent by users.

[0468] A "database" is a storage system used to systematically store and manage advertising information and consumer data.

[0469] "Artificial intelligence" is a program or algorithm that performs analysis and makes recommendations based on data provided by users.

[0470] "Consumer profile information" refers to data that includes consumers' personal attributes, purchase history, and interests.

[0471] "Past behavioral history" refers to the data history of actions and search queries that consumers have taken in the past.

[0472] A "receiving device" is a device used by consumers to receive information.

[0473] This invention relates to an information processing system for effectively managing and distributing advertising information. Specific embodiments for carrying out the invention are described below.

[0474] System Overview

[0475] The system is centered around the user, the device, and the server, each playing a specific role. The user inputs advertising information and sends it to the server via the device. The server receives this information and uses artificial intelligence to deliver optimized advertisements.

[0476] Hardware and software to be used

[0477] User terminal: Users use a personal computer, tablet, or smartphone to enter advertising information via an input interface.

[0478] Server: Uses high-performance server equipment and is responsible for storing and analyzing advertising information and running artificial intelligence models.

[0479] Artificial intelligence software: Equipped with machine learning algorithms and data analysis tools, and implemented in programming languages ​​such as Python or R.

[0480] Data processing and calculation

[0481] The server stores the advertising information provided by the user in a database. The artificial intelligence model analyzes the stored information along with the consumer's profile and behavioral history data to perform calculations for optimal ad delivery. This allows for the presentation of advertising information tailored to the individual needs of each consumer.

[0482] Specific example

[0483] For example, if a user wants to promote a new product, they would use their device to input advertising information. They would enter information such as "We will run a new product promotion with a budget of up to 10,000 yen" and send it to the server. The server would then analyze this information and use a generative AI model to recommend the most effective way to reach consumers.

[0484] Example of a prompt

[0485] An example of a prompt might be: "Generate suggestions using an AI algorithm that takes into account the target audience's profile and past behavioral data, in order to provide effective information regarding the advertising campaign for our new product."

[0486] In this way, by implementing the invention, users can efficiently deliver advertisements to the market, and consumers can receive information that aligns with their interests.

[0487] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0488] Step 1:

[0489] Users input advertising information using their devices. Specifically, users enter details about new products or campaigns, budget, target regions, etc., on the input screen. The input data is temporarily processed on the device, formatted, and then sent to the server. The input data includes product name, campaign period, budget limit, etc.

[0490] Step 2:

[0491] The device sends advertising information to the server. During transmission, the data is encrypted and securely transferred via a security protocol. The server temporarily stores the received advertising information in its internal memory and prepares to store it in its database. Once the data has been received, the server verifies that the data format is correct.

[0492] Step 3:

[0493] The server stores the received advertising information in a database. This storage process includes checking for duplicates with existing data and verifying data integrity. In the database, information is managed by advertising campaign ID and indexed to allow for efficient access in subsequent processing.

[0494] Step 4:

[0495] The server uses artificial intelligence to analyze each consumer's profile information and past behavioral history based on advertising information stored in a database. The inputs used are stored advertising information, consumer demographic data, and behavioral logs. The AI ​​model processes this data to generate the most suitable advertising recommendations for each individual consumer. The output is a personalized advertising list.

[0496] Step 5:

[0497] The server sends the generated ad recommendations to the consumer's device. Specifically, it selects the most relevant ads based on the search query specified by the consumer and determines their display priority. The output is reflected in the ad display area on the consumer's device. Through this, users can be automatically provided with optimized ads.

[0498] Step 6:

[0499] The server monitors the results of ad impressions and generates performance reports. This process analyzes metrics such as impressions, click-through rates, and conversion rates, and compiles them into daily and monthly reports. The output is a report that visualizes the effectiveness of the ads and is provided to the user to help them plan their next campaign.

[0500] (Application Example 1)

[0501] Next, we will explain Application Example 1. In the following explanation, 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."

[0502] Conventional advertising information systems sometimes fail to adequately provide information that accurately captures users' needs and interests. Therefore, there is a need to improve the efficiency and immediacy of advertising while optimizing advertising costs. General advertising systems lack sufficient real-time data analysis for ad display, and are unable to immediately provide information tailored to users' interests. A new system is needed to solve these problems.

[0503] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0504] In this invention, the server includes means for analyzing data based on user behavior information and interests and providing personalized advertising information in real time, means for receiving data input from users to set advertising information, and means for artificial intelligence to adjust the priority of information in response to the user's reference queries based on the accumulated advertising information. This improves the personalization and immediacy of advertising information for users and enables optimization of advertising costs.

[0505] A "data processing device" is a device that performs tasks such as inputting, analyzing, generating, and displaying information, and plays a central role in systems that utilize digital information.

[0506] "Artificial intelligence" is a technology in which computers imitate human intellectual activity and possess the ability to learn and reason based on data.

[0507] "Data entry" is the process of receiving information from users and converting it into a format that can be processed within the system.

[0508] A "database" is a structured collection of information used to systematically store, organize, and manage information.

[0509] A "reference query" is a request or inquiry made by a user to a system in order to obtain specific information.

[0510] "Priority" is a criterion used to determine which information or tasks are more important and should be provided more frequently compared to others.

[0511] A "report" is a document that compiles facts, analysis results, and other information related to specific data and outcomes, and presents them to users.

[0512] "Trend information" refers to data that shows how users' behavior and interests change over time.

[0513] "Real-time" is a term that refers to the operation of a system that processes information and provides results almost simultaneously.

[0514] "Personalization" refers to adjusting information and services to suit the specific needs and preferences of individual users.

[0515] In this embodiment of the invention, an advertising information provision system utilizing artificial intelligence is constructed. The server receives data input from users and manages advertising information via an information processing device. Specifically, the server records the input advertising information in a database and uses artificial intelligence to adjust the priority of information for reference queries based on that information. This adjustment is performed to personalize the information based on accumulated trend information and user interests.

[0516] The server analyzes data in real time using artificial intelligence frameworks such as TensorFlow. The analyzed information is reflected as advertising information displayed on the user's device. The device used to display the advertising information is the user's mobile device, such as a smartphone or tablet.

[0517] By instantly reflecting user trends and interests, advertising information becomes more relevant to the user. For example, when a user planning a trip searches for a tourist destination, advertisements for hotels and restaurants in that area are displayed in real time.

[0518] A key feature of this system is its use of a generative AI model to personalize advertisements through prompt text. For example, a prompt text might instruct a user searching for "Tokyo travel" to suggest relevant travel packages and hotel advertisements. Based on this instruction, the system can quickly provide users with the most relevant advertising information.

[0519] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0520] Step 1:

[0521] The server receives advertising data input from the user's terminal. The terminal then transfers the advertising information entered by the user to the server. This input includes product name, campaign details, budget, etc. The server receives this data and stores it in a database. This data accumulation prepares the foundational data used in subsequent processing.

[0522] Step 2:

[0523] The server retrieves advertising information stored in the database and performs analysis using artificial intelligence. The analysis incorporates user reference queries, trend information, and past behavioral history. Specifically, it uses TensorFlow to analyze behavioral history and adjust the priority of advertising information. The input data consists of queries and historical data, and the output is prioritized advertising information.

[0524] Step 3:

[0525] The server personalizes information based on prioritized advertising data. It uses a generative AI model to execute the prompt "Present ads based on user interests." This generates advertising data optimized for each user. The input is prioritized advertising data, and the output is personalized advertising data.

[0526] Step 4:

[0527] The server returns personalized advertising information to the user's device for display. Based on the received information, the device displays advertisements on the user screen in real time. Specifically, this can be done by displaying advertising information in a notification format or by embedding it within the app. The input is personalized advertising information, and the output is advertisements delivered visually to the user.

[0528] Step 5:

[0529] The server collects data on information provision and generates reports. It analyzes data such as user click-through rates, page views, and conversion rates to evaluate the effectiveness of the advertisements. The analysis generates a performance report for the advertising campaign, which is provided to the advertiser as output. This report is then used to inform future advertising strategies.

[0530] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0531] This invention provides a system that uses artificial intelligence and an emotion engine to deliver advertising information to consumers more effectively. This system sets up advertising information based on user input and stores it in a database. The stored information is then prioritized and recommended by artificial intelligence based on the user's search queries and profile. Furthermore, by combining this with an emotion engine, it is possible to dynamically change the display of information based on the user's emotional state, thereby maximizing the effectiveness of advertising.

[0532] Users (businesses) log in to the system via their terminal and enter the necessary information on a screen for creating advertising campaigns. The terminal sends the entered information to the server, where it is stored in a database. The server analyzes the user input in real time and uses artificial intelligence to prioritize providing information deemed most useful to the customer.

[0533] A notable feature is that when a user (consumer) uses the system, the emotion engine analyzes the user's voice and facial expressions in real time and acquires emotional data. This emotional data is sent to a server, where artificial intelligence adjusts advertising information to match the user's emotional state. For example, if the system recognizes that the user is in a positive state, more vivid and emotionally stimulating content will be recommended.

[0534] As a concrete example, consider a situation where a restaurant wants to advertise a special weekend dinner menu. When a consumer uses this system to search for "weekend dinner," and the device recognizes the user's emotional state as "looking happy," the artificial intelligence will prioritize displaying images along with details of the special dinner menu to match that positive emotion.

[0535] As advertising campaigns progress, the server collects and analyzes a wealth of data, including user sentiment data, to evaluate the success of the ads in real time and provide detailed reports to the advertisers. Based on these reports, advertisers can more effectively adjust their advertising strategies.

[0536] Thus, by combining an emotion engine and artificial intelligence, the present invention makes it possible to provide a highly personalized advertising experience that benefits both businesses and consumers.

[0537] The following describes the processing flow.

[0538] Step 1:

[0539] Users (businesses) access the advertising campaign registration page via their device. There, they enter detailed information about the service or product they want to advertise, the campaign period, and their budget.

[0540] Step 2:

[0541] The device sends the user's input information to the server. After the server verifies the legitimacy of the received advertising information, it saves the information to its database.

[0542] Step 3:

[0543] The server sends the accumulated advertising information to the artificial intelligence module. The AI ​​module analyzes the user's profile information and past behavior history, and sets the optimal priority score for each query.

[0544] Step 4:

[0545] The user (consumer) uses a device to search for information on the target. The device collects data through the user's voice or image data for sentiment analysis by an emotion engine.

[0546] Step 5:

[0547] The emotion engine recognizes the user's emotional state in real time based on collected audio and image data, and sends that information to the server.

[0548] Step 6:

[0549] The server uses an artificial intelligence module to analyze a combination of user search queries and sentiment data, and dynamically adjusts the priority of the displayed advertisements.

[0550] Step 7:

[0551] The device displays priority advertising information received from the server to the user (consumer). The displayed content is best suited to the user's current emotional state.

[0552] Step 8:

[0553] The server continuously collects consumer behavior and sentiment data during the execution of advertising campaigns, analyzes campaign performance, and generates detailed reports.

[0554] Step 9:

[0555] Users (businesses) can use the provided reports to evaluate the effectiveness of their advertising campaigns and use that information to develop their next marketing strategies.

[0556] (Example 2)

[0557] Next, we will describe Example 2. 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."

[0558] Traditional advertising delivery systems have a problem in that they do not adjust information based on user emotions, thus failing to maximize the effectiveness of advertisements. Furthermore, individual optimization based on user characteristics and behavioral history is not sufficiently implemented, resulting in advertisements that are not appealing to users.

[0559] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0560] In this invention, the server includes means for storing advertising information in a memory device, means for artificial intelligence to adjust priority and recommend information in response to the user's search commands, and means for analyzing the user's emotional state and dynamically adjusting the information based on the analysis results. This makes it possible to provide a highly personalized advertising experience based on the user's emotional state and individual characteristics.

[0561] "Advertising information" refers to information designed to promote specific products or services to users.

[0562] "User" refers to an individual or organization that creates, provides, or views advertisements through the system.

[0563] A "search command" refers to keywords or queries that users enter into a search engine or system to obtain specific information.

[0564] A "storage device" is a device for storing and managing data, and it plays a role in storing advertising information and user data.

[0565] "Artificial intelligence" refers to the technology in which computer systems imitate human intellectual behavior to perform data analysis and decision-making.

[0566] "Emotional state" refers to data that represents the user's current emotions and mood, and is analyzed from sources such as voice and facial expressions.

[0567] "Dynamic adjustment" refers to changing the system's display content and provided information in real time based on the user's emotional state and various data.

[0568] A "personalized advertising experience" means providing an experience tailored to each individual by displaying ads and delivering information that are optimized based on the characteristics and emotions of each user.

[0569] This invention is a system that provides users with a highly personalized advertising experience by integrating artificial intelligence and an emotion engine. This system functions through the coordinated efforts of the server, terminal, and user elements.

[0570] Users access the system using their devices and input information about their advertising campaigns. This information includes ad content, target audience, and campaign duration. The devices send this information to a server, which stores it in a database. Examples of database management systems used in this process include MySQL and PostgreSQL.

[0571] The server uses artificial intelligence (AI) based on the information it receives to calculate the most optimal ad display. AI implementation typically utilizes frameworks such as TensorFlow or PyTorch. It also adjusts the ranking of ad information to prioritize information relevant to the user's search queries.

[0572] Simultaneously, the user's emotional state is collected in real time by the camera and microphone built into the device. The data collected by the device is analyzed using emotion analysis software, such as Emotion API or Affectiva. The analysis results are sent to a server, where artificial intelligence dynamically adjusts the information based on the emotional data.

[0573] For example, if a user searches for "weekend dinner" and the device recognizes the user's emotional state as "enjoyable," the server can select and display an advertisement image with vibrant colors. As a result, the advertisement can make a stronger impression on the user.

[0574] An example of a prompt would be, "Please list ad content that you would recommend to users in a positive emotional state." Using this prompt helps the generative AI model to more effectively select ads that fit the user's emotions.

[0575] Thus, the present invention aims to maximize the effectiveness of advertising by utilizing users' emotional states and characteristic information. This system allows businesses to effectively adjust their advertising strategies and provides users with an attractive experience.

[0576] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0577] Step 1:

[0578] Users enter advertising campaign information using their devices. This information includes ad content, target audience, and campaign duration. This information is temporarily stored on the device and formatted for transmission to the server.

[0579] Step 2:

[0580] The device sends formatted advertising information to the server. The data is sent to the server using the HTTP protocol. The input data is structured and optimized in JSON format. The server parses the received data for storage in a database and converts it into an SQL query.

[0581] Step 3:

[0582] The server stores the received advertising information in a database. A database management system used here might be MySQL, for example. The stored data is indexed for subsequent processing and optimized for searching.

[0583] Step 4:

[0584] While a user is using the system, the device uses its camera and microphone to capture the user's voice and facial expressions. This input data is analyzed in real time using the Emotion API. This analysis yields output indicating the user's emotional state (e.g., data such as "happy" or "excited").

[0585] Step 5:

[0586] The server receives the results of the sentiment analysis and uses an artificial intelligence model to determine which advertisement is most appropriate for the user's current emotional state. The input data includes the user's emotional state and past behavioral history, and the AI ​​uses this information to calculate recommended advertisements and output the results.

[0587] Step 6:

[0588] The server sends the selected advertising information to the device and displays it to the user. The transmitted data includes the media files necessary for display (such as images and videos) and is immediately reflected in the device's UI.

[0589] Step 7:

[0590] The server records the results of ad displays and user reactions, and evaluates their effectiveness using big data analysis tools. The input data includes metrics such as emotional states and click-through rates, and the output includes conversion rates and overall ad effectiveness.

[0591] (Application Example 2)

[0592] Next, we will explain application example 2. In the following explanation, 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."

[0593] Traditional advertising delivery systems have difficulty considering users' real-time emotional states, making it challenging to optimize ad engagement. Therefore, there is a need for more personalized and emotionally resonant ad displays.

[0594] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0595] In this invention, the server includes means for receiving input from a user to set advertising information, means for storing the input advertising information in a database, means for artificial intelligence to adjust priority and recommend information in response to the user's search query based on the stored advertising information, means for analyzing the user's facial movements and determining the resulting emotions, and means for adjusting the displayed advertising information based on the emotions determined by the emotion analysis means. This makes it possible to display advertising information that is adapted to the user's emotional state.

[0596] An "information processing device" is a machine or device that receives data, processes it, and provides information to users.

[0597] "Artificial intelligence" is a technology that allows computer systems to autonomously analyze and process information through learning and reasoning as they operate.

[0598] "Advertising information" refers to detailed data and visual content about products and services, provided with the aim of attracting the user's interest.

[0599] A "database" is a system for organizing information structurally and efficiently storing, searching, and managing it.

[0600] "Emotion analysis means" refers to technology for detecting and interpreting a user's emotional state based on facial movements, voice, and other factors.

[0601] "Adjusting priorities" refers to determining the importance and display order of information that should be presented based on specific criteria or conditions.

[0602] A "user terminal" is a device that a user directly operates to acquire or input information.

[0603] As an embodiment of this invention, an emotion-adaptive advertising display system will be described. This system comprises a user terminal, a server as an information processing device, and an emotion analysis engine.

[0604] First, the user terminal receives user input using a device such as a smartphone or smart glasses, and sets up advertising information. This input information is sent to the server to be stored in a database. On the server, artificial intelligence adjusts the priority of information based on the user's search query and recommends the most suitable advertising information based on the stored advertising information.

[0605] Furthermore, the user's facial movements and voice are captured in real time using the user's device's camera and microphone, and an emotion analysis engine analyzes this data to determine the user's emotional state. This emotional state is sent to a server, and based on the information obtained from the emotion analysis, the displayed advertising information is dynamically adjusted. This analysis process can utilize a platform such as Google TensorFlow.

[0606] For example, if a user searches for "lunch spots" and their facial expression is analyzed as showing "surprise," the server can prioritize displaying information about new menu items that would delight this surprised feeling, along with vivid images. This can enhance the effectiveness of advertising.

[0607] The evaluation and feedback of the results of this ad engine are performed on the server side and provided to advertisers as a detailed report. This report includes user sentiment data and ad performance data, which helps to adjust the ad strategy.

[0608] An example of a prompt message would be: "Output an example of an ad display when the user is interested in lunch. If their emotion is determined to be surprise, what information should be prioritized?" This would be the format of the input to the generative AI model.

[0609] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0610] Step 1:

[0611] The user terminal receives advertising information input from the user. This input includes an overview of the advertisement, target audience, and display period. This information is sent from the terminal to the server in a structured format and stored in a database. The output is form data sent to the server.

[0612] Step 2:

[0613] The server stores the received advertising information in a database. Simultaneously, when a user makes a search query, it prepares to use artificial intelligence to calculate the priority of the information based on the accumulated advertising data. The output is a list of recommended ads for the search query.

[0614] Step 3:

[0615] The user terminal receives the user's search query. Based on this input, the terminal sends the query to the server. The output is the data transmitted to the server as the search query.

[0616] Step 4:

[0617] The server uses artificial intelligence to select high-priority advertisements based on search queries. This process takes into account the user's past behavior history and profile, and utilizes generative AI models such as TensorFlow. The output is recommended advertisement information sent to the user's device.

[0618] Step 5:

[0619] The user's device receives recommended advertising information. Furthermore, it captures the user's facial expressions and voice in real time using the camera and microphone, and sends this data to an emotion analysis engine. The output consists of facial expression data and voice data for emotion analysis.

[0620] Step 6:

[0621] The server uses an emotion analysis engine to determine the user's emotions based on the received facial and voice data. Based on this determination, it dynamically adjusts the advertising information and re-selects the most suitable advertisement for the user. The output is the adjusted advertising information.

[0622] Step 7:

[0623] The adjusted advertising information is sent to the user's device. The user's device then displays this advertisement to the user. The user's reaction is collected and sent to the server as feedback. The output consists of the advertisement screen displayed to the user and the feedback data.

[0624] Step 8:

[0625] The server analyzes feedback data and generates a report on the effectiveness of the advertisements. This report is provided to the advertiser to help improve their future advertising strategies. The output is an analytical report provided to the advertiser.

[0626] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0627] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0628] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0629] [Fourth Embodiment]

[0630] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0631] As shown in Figure 7, the 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.

[0632] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0633] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0634] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0635] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0636] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0637] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0638] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0639] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0640] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0641] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0642] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0643] This invention relates to an information processing system that optimizes a business's advertising costs by effectively providing advertising information using artificial intelligence. This system includes a mechanism in which the business user inputs advertising information, and based on that, the system prioritizes providing information to consumers.

[0644] The user (business) first accesses the system via their device and inputs the information they wish to offer as an advertising campaign. This information may include, for example, introductions to new products or limited-time offers. The device receives this information and sends it to the server.

[0645] The server stores information entered by users in a database. Based on the stored data, the server uses artificial intelligence algorithms to analyze each user's profile and past behavior history, and provides information recommendations tailored to each individual. In this recommendation process, the algorithm is adjusted to take into account the consumer user's search queries, prioritizing the presentation of the most relevant information.

[0646] As a concrete example, consider a restaurant that wants to launch a new lunch menu. The restaurant owner uses this system to register an advertisement for the new menu and create a campaign with a set budget. When a consumer searches for "delicious lunch in Tokyo," the AI ​​selects restaurants relevant to that search query based on priority and displays them on the consumer's device. In this way, the restaurant can efficiently reach customers and effectively attract more patrons.

[0647] This system also has the functionality to monitor the effectiveness of advertisements and generate performance reports periodically. The server analyzes daily data and compiles reports on ad impressions, click-through rates, customer inquiries, and other metrics, which are then presented to the business. By utilizing this information, the business can formulate its next marketing strategy.

[0648] This format allows businesses to use advertising budgets more effectively than traditional methods, and provides consumers with more relevant information. Therefore, it is possible to improve the overall quality of information provided and enhance convenience for both businesses and consumers.

[0649] The following describes the processing flow.

[0650] Step 1:

[0651] Users (businesses) access the platform using their devices and open the new campaign registration screen. Here, they enter information such as the content of the advertisement (details and images), the advertising period, the target audience, and the advertising budget.

[0652] Step 2:

[0653] The terminal checks the entered campaign information and sends it to the server. The server verifies the received information (for example, checking the correctness of the input format and whether there are any missing items), and then saves the campaign information to the database.

[0654] Step 3:

[0655] The server sends the stored campaign information to the artificial intelligence module. The artificial intelligence module calculates a recommendation score based on the user's attributes, using previously accumulated user data (profile, search history, etc.).

[0656] Step 4:

[0657] When a user (consumer) searches for information from their device, the device sends a search query to the server. The server receives this query and queries the database and the artificial intelligence module.

[0658] Step 5:

[0659] The server selects the most relevant advertising information according to a recommendation score calculated by artificial intelligence, prioritizing and generating search results. This ensures that results that match the user's needs are provided.

[0660] Step 6:

[0661] The terminal displays priority information received from the server to the consumer user. Based on this, the consumer user selects items of interest, views details, or makes inquiries.

[0662] Step 7:

[0663] The server tracks user behavior (number of clicks, frequency of inquiries, etc.) during the campaign and collects performance data. Based on this, it analyzes the effectiveness of the advertisements, generates performance reports periodically, and notifies the business users.

[0664] (Example 1)

[0665] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0666] In today's information-saturated world, it is becoming increasingly difficult for consumers to access the information they truly need. Similarly, advertisers face the challenge of efficiently using their advertising budgets and effectively reaching their target audience. Therefore, there is a need to build a system that provides information beneficial to both consumers and advertisers.

[0667] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0668] In this invention, the server includes means for transmitting advertising information entered by a user to an information processing device, means for storing the entered advertising information in a database, and means for using artificial intelligence to analyze consumer profile information and past behavioral history based on the stored data, and for personalizing and recommending information. This makes it possible to efficiently provide advertising information that is suitable for consumer needs and to improve the cost-effectiveness for advertisers.

[0669] A "user" is an entity that inputs advertising information into the system and provides that information.

[0670] "Advertising information" refers to data that includes details about products and services offered to consumers, campaign details, and other relevant information.

[0671] An "information processing device" is a computing system that receives, stores, and processes advertising information sent by users.

[0672] A "database" is a storage system used to systematically store and manage advertising information and consumer data.

[0673] "Artificial intelligence" is a program or algorithm that performs analysis and makes recommendations based on data provided by users.

[0674] "Consumer profile information" refers to data that includes consumers' personal attributes, purchase history, and interests.

[0675] "Past behavioral history" refers to the data history of actions and search queries that consumers have taken in the past.

[0676] A "receiving device" is a device used by consumers to receive information.

[0677] This invention relates to an information processing system for effectively managing and distributing advertising information. Specific embodiments for carrying out the invention are described below.

[0678] System Overview

[0679] The system is centered around the user, the device, and the server, each playing a specific role. The user inputs advertising information and sends it to the server via the device. The server receives this information and uses artificial intelligence to deliver optimized advertisements.

[0680] Hardware and software to be used

[0681] User terminal: Users use a personal computer, tablet, or smartphone to enter advertising information via an input interface.

[0682] Server: Uses high-performance server equipment and is responsible for storing and analyzing advertising information and running artificial intelligence models.

[0683] Artificial intelligence software: Equipped with machine learning algorithms and data analysis tools, and implemented in programming languages ​​such as Python or R.

[0684] Data processing and calculation

[0685] The server stores the advertising information provided by the user in a database. The artificial intelligence model analyzes the stored information along with the consumer's profile and behavioral history data to perform calculations for optimal ad delivery. This allows for the presentation of advertising information tailored to the individual needs of each consumer.

[0686] Specific example

[0687] For example, if a user wants to promote a new product, they would use their device to input advertising information. They would enter information such as "We will run a new product promotion with a budget of up to 10,000 yen" and send it to the server. The server would then analyze this information and use a generative AI model to recommend the most effective way to reach consumers.

[0688] Example of a prompt

[0689] An example of a prompt might be: "Generate suggestions using an AI algorithm that takes into account the target audience's profile and past behavioral data, in order to provide effective information regarding the advertising campaign for our new product."

[0690] In this way, by implementing the invention, users can efficiently deliver advertisements to the market, and consumers can receive information that aligns with their interests.

[0691] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0692] Step 1:

[0693] Users input advertising information using their devices. Specifically, users enter details about new products or campaigns, budget, target regions, etc., on the input screen. The input data is temporarily processed on the device, formatted, and then sent to the server. The input data includes product name, campaign period, budget limit, etc.

[0694] Step 2:

[0695] The device sends advertising information to the server. During transmission, the data is encrypted and securely transferred via a security protocol. The server temporarily stores the received advertising information in its internal memory and prepares to store it in its database. Once the data has been received, the server verifies that the data format is correct.

[0696] Step 3:

[0697] The server stores the received advertising information in a database. This storage process includes checking for duplicates with existing data and verifying data integrity. In the database, information is managed by advertising campaign ID and indexed to allow for efficient access in subsequent processing.

[0698] Step 4:

[0699] The server uses artificial intelligence to analyze each consumer's profile information and past behavioral history based on advertising information stored in a database. The inputs used are stored advertising information, consumer demographic data, and behavioral logs. The AI ​​model processes this data to generate the most suitable advertising recommendations for each individual consumer. The output is a personalized advertising list.

[0700] Step 5:

[0701] The server sends the generated ad recommendations to the consumer's device. Specifically, it selects the most relevant ads based on the search query specified by the consumer and determines their display priority. The output is reflected in the ad display area on the consumer's device. Through this, users can be automatically provided with optimized ads.

[0702] Step 6:

[0703] The server monitors the results of ad impressions and generates performance reports. This process analyzes metrics such as impressions, click-through rates, and conversion rates, and compiles them into daily and monthly reports. The output is a report that visualizes the effectiveness of the ads and is provided to the user to help them plan their next campaign.

[0704] (Application Example 1)

[0705] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0706] Conventional advertising information systems sometimes fail to adequately provide information that accurately captures users' needs and interests. Therefore, there is a need to improve the efficiency and immediacy of advertising while optimizing advertising costs. General advertising systems lack sufficient real-time data analysis for ad display, and are unable to immediately provide information tailored to users' interests. A new system is needed to solve these problems.

[0707] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0708] In this invention, the server includes means for analyzing data based on user behavior information and interests and providing personalized advertising information in real time, means for receiving data input from users to set advertising information, and means for artificial intelligence to adjust the priority of information in response to the user's reference queries based on the accumulated advertising information. This improves the personalization and immediacy of advertising information for users and enables optimization of advertising costs.

[0709] A "data processing device" is a device that performs tasks such as inputting, analyzing, generating, and displaying information, and plays a central role in systems that utilize digital information.

[0710] "Artificial intelligence" is a technology in which computers imitate human intellectual activity and possess the ability to learn and reason based on data.

[0711] "Data entry" is the process of receiving information from users and converting it into a format that can be processed within the system.

[0712] A "database" is a structured collection of information used to systematically store, organize, and manage information.

[0713] A "reference query" is a request or inquiry made by a user to a system in order to obtain specific information.

[0714] "Priority" is a criterion used to determine which information or tasks are more important and should be provided more frequently compared to others.

[0715] A "report" is a document that compiles facts, analysis results, and other information related to specific data and outcomes, and presents them to users.

[0716] "Trend information" refers to data that shows how users' behavior and interests change over time.

[0717] "Real-time" is a term that refers to the operation of a system that processes information and provides results almost simultaneously.

[0718] "Personalization" refers to adjusting information and services to suit the specific needs and preferences of individual users.

[0719] In this embodiment of the invention, an advertising information provision system utilizing artificial intelligence is constructed. The server receives data input from users and manages advertising information via an information processing device. Specifically, the server records the input advertising information in a database and uses artificial intelligence to adjust the priority of information for reference queries based on that information. This adjustment is performed to personalize the information based on accumulated trend information and user interests.

[0720] The server analyzes data in real time using artificial intelligence frameworks such as TensorFlow. The analyzed information is reflected as advertising information displayed on the user's device. The device used to display the advertising information is the user's mobile device, such as a smartphone or tablet.

[0721] By instantly reflecting user trends and interests, advertising information becomes more relevant to the user. For example, when a user planning a trip searches for a tourist destination, advertisements for hotels and restaurants in that area are displayed in real time.

[0722] A key feature of this system is its use of a generative AI model to personalize advertisements through prompt text. For example, a prompt text might instruct a user searching for "Tokyo travel" to suggest relevant travel packages and hotel advertisements. Based on this instruction, the system can quickly provide users with the most relevant advertising information.

[0723] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0724] Step 1:

[0725] The server receives advertising data input from the user's terminal. The terminal then transfers the advertising information entered by the user to the server. This input includes product name, campaign details, budget, etc. The server receives this data and stores it in a database. This data accumulation prepares the foundational data used in subsequent processing.

[0726] Step 2:

[0727] The server retrieves advertising information stored in the database and performs analysis using artificial intelligence. The analysis incorporates user reference queries, trend information, and past behavioral history. Specifically, it uses TensorFlow to analyze behavioral history and adjust the priority of advertising information. The input data consists of queries and historical data, and the output is prioritized advertising information.

[0728] Step 3:

[0729] The server personalizes information based on prioritized advertising data. It uses a generative AI model to execute the prompt "Present ads based on user interests." This generates advertising data optimized for each user. The input is prioritized advertising data, and the output is personalized advertising data.

[0730] Step 4:

[0731] The server returns personalized advertising information to the user's device for display. Based on the received information, the device displays advertisements on the user screen in real time. Specifically, this can be done by displaying advertising information in a notification format or by embedding it within the app. The input is personalized advertising information, and the output is advertisements delivered visually to the user.

[0732] Step 5:

[0733] The server collects data on information provision and generates reports. It analyzes data such as user click-through rates, page views, and conversion rates to evaluate the effectiveness of the advertisements. The analysis generates a performance report for the advertising campaign, which is provided to the advertiser as output. This report is then used to inform future advertising strategies.

[0734] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0735] This invention provides a system that uses artificial intelligence and an emotion engine to deliver advertising information to consumers more effectively. This system sets up advertising information based on user input and stores it in a database. The stored information is then prioritized and recommended by artificial intelligence based on the user's search queries and profile. Furthermore, by combining this with an emotion engine, it is possible to dynamically change the display of information based on the user's emotional state, thereby maximizing the effectiveness of advertising.

[0736] Users (businesses) log in to the system via their terminal and enter the necessary information on a screen for creating advertising campaigns. The terminal sends the entered information to the server, where it is stored in a database. The server analyzes the user input in real time and uses artificial intelligence to prioritize providing information deemed most useful to the customer.

[0737] A notable feature is that when a user (consumer) uses the system, the emotion engine analyzes the user's voice and facial expressions in real time and acquires emotional data. This emotional data is sent to a server, where artificial intelligence adjusts advertising information to match the user's emotional state. For example, if the system recognizes that the user is in a positive state, more vivid and emotionally stimulating content will be recommended.

[0738] As a concrete example, consider a situation where a restaurant wants to advertise a special weekend dinner menu. When a consumer uses this system to search for "weekend dinner," and the device recognizes the user's emotional state as "looking happy," the artificial intelligence will prioritize displaying images along with details of the special dinner menu to match that positive emotion.

[0739] As advertising campaigns progress, the server collects and analyzes a wealth of data, including user sentiment data, to evaluate the success of the ads in real time and provide detailed reports to the advertisers. Based on these reports, advertisers can more effectively adjust their advertising strategies.

[0740] Thus, by combining an emotion engine and artificial intelligence, the present invention makes it possible to provide a highly personalized advertising experience that benefits both businesses and consumers.

[0741] The following describes the processing flow.

[0742] Step 1:

[0743] Users (businesses) access the advertising campaign registration page via their device. There, they enter detailed information about the service or product they want to advertise, the campaign period, and their budget.

[0744] Step 2:

[0745] The device sends the user's input information to the server. After the server verifies the legitimacy of the received advertising information, it saves the information to its database.

[0746] Step 3:

[0747] The server sends the accumulated advertising information to the artificial intelligence module. The AI ​​module analyzes the user's profile information and past behavior history, and sets the optimal priority score for each query.

[0748] Step 4:

[0749] The user (consumer) uses a device to search for information on the target. The device collects data through the user's voice or image data for sentiment analysis by an emotion engine.

[0750] Step 5:

[0751] The emotion engine recognizes the user's emotional state in real time based on collected audio and image data, and sends that information to the server.

[0752] Step 6:

[0753] The server uses an artificial intelligence module to analyze a combination of user search queries and sentiment data, and dynamically adjusts the priority of the displayed advertisements.

[0754] Step 7:

[0755] The device displays priority advertising information received from the server to the user (consumer). The displayed content is best suited to the user's current emotional state.

[0756] Step 8:

[0757] The server continuously collects consumer behavior and sentiment data during the execution of advertising campaigns, analyzes campaign performance, and generates detailed reports.

[0758] Step 9:

[0759] Users (businesses) can use the provided reports to evaluate the effectiveness of their advertising campaigns and use that information to develop their next marketing strategies.

[0760] (Example 2)

[0761] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0762] Traditional advertising delivery systems have a problem in that they do not adjust information based on user emotions, thus failing to maximize the effectiveness of advertisements. Furthermore, individual optimization based on user characteristics and behavioral history is not sufficiently implemented, resulting in advertisements that are not appealing to users.

[0763] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0764] In this invention, the server includes means for storing advertising information in a memory device, means for artificial intelligence to adjust priority and recommend information in response to the user's search commands, and means for analyzing the user's emotional state and dynamically adjusting the information based on the analysis results. This makes it possible to provide a highly personalized advertising experience based on the user's emotional state and individual characteristics.

[0765] "Advertising information" refers to information designed to promote specific products or services to users.

[0766] "User" refers to an individual or organization that creates, provides, or views advertisements through the system.

[0767] A "search command" refers to keywords or queries that users enter into a search engine or system to obtain specific information.

[0768] A "storage device" is a device for storing and managing data, and it plays a role in storing advertising information and user data.

[0769] "Artificial intelligence" refers to the technology in which computer systems imitate human intellectual behavior to perform data analysis and decision-making.

[0770] "Emotional state" refers to data that represents the user's current emotions and mood, and is analyzed from sources such as voice and facial expressions.

[0771] "Dynamic adjustment" refers to changing the system's display content and provided information in real time based on the user's emotional state and various data.

[0772] A "personalized advertising experience" means providing an experience tailored to each individual by displaying ads and delivering information that are optimized based on the characteristics and emotions of each user.

[0773] This invention is a system that provides users with a highly personalized advertising experience by integrating artificial intelligence and an emotion engine. This system functions through the coordinated efforts of the server, terminal, and user elements.

[0774] Users access the system using their devices and input information about their advertising campaigns. This information includes ad content, target audience, and campaign duration. The devices send this information to a server, which stores it in a database. Examples of database management systems used in this process include MySQL and PostgreSQL.

[0775] The server uses artificial intelligence (AI) based on the information it receives to calculate the most optimal ad display. AI implementation typically utilizes frameworks such as TensorFlow or PyTorch. It also adjusts the ranking of ad information to prioritize information relevant to the user's search queries.

[0776] Simultaneously, the user's emotional state is collected in real time by the camera and microphone built into the device. The data collected by the device is analyzed using emotion analysis software, such as Emotion API or Affectiva. The analysis results are sent to a server, where artificial intelligence dynamically adjusts the information based on the emotional data.

[0777] For example, if a user searches for "weekend dinner" and the device recognizes the user's emotional state as "enjoyable," the server can select and display an advertisement image with vibrant colors. As a result, the advertisement can make a stronger impression on the user.

[0778] An example of a prompt would be, "Please list ad content that you would recommend to users in a positive emotional state." Using this prompt helps the generative AI model to more effectively select ads that fit the user's emotions.

[0779] Thus, the present invention aims to maximize the effectiveness of advertising by utilizing users' emotional states and characteristic information. This system allows businesses to effectively adjust their advertising strategies and provides users with an attractive experience.

[0780] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0781] Step 1:

[0782] Users enter advertising campaign information using their devices. This information includes ad content, target audience, and campaign duration. This information is temporarily stored on the device and formatted for transmission to the server.

[0783] Step 2:

[0784] The device sends formatted advertising information to the server. The data is sent to the server using the HTTP protocol. The input data is structured and optimized in JSON format. The server parses the received data for storage in a database and converts it into an SQL query.

[0785] Step 3:

[0786] The server stores the received advertising information in a database. A database management system used here might be MySQL, for example. The stored data is indexed for subsequent processing and optimized for searching.

[0787] Step 4:

[0788] While a user is using the system, the device uses its camera and microphone to capture the user's voice and facial expressions. This input data is analyzed in real time using the Emotion API. This analysis yields output indicating the user's emotional state (e.g., data such as "happy" or "excited").

[0789] Step 5:

[0790] The server receives the results of the sentiment analysis and uses an artificial intelligence model to determine which advertisement is most appropriate for the user's current emotional state. The input data includes the user's emotional state and past behavioral history, and the AI ​​uses this information to calculate recommended advertisements and output the results.

[0791] Step 6:

[0792] The server sends the selected advertising information to the device and displays it to the user. The transmitted data includes the media files necessary for display (such as images and videos) and is immediately reflected in the device's UI.

[0793] Step 7:

[0794] The server records the results of ad displays and user reactions, and evaluates their effectiveness using big data analysis tools. The input data includes metrics such as emotional states and click-through rates, and the output includes conversion rates and overall ad effectiveness.

[0795] (Application Example 2)

[0796] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0797] Traditional advertising delivery systems have difficulty considering users' real-time emotional states, making it challenging to optimize ad engagement. Therefore, there is a need for more personalized and emotionally resonant ad displays.

[0798] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0799] In this invention, the server includes means for receiving input from a user to set advertising information, means for storing the input advertising information in a database, means for artificial intelligence to adjust priority and recommend information in response to the user's search query based on the stored advertising information, means for analyzing the user's facial movements and determining the resulting emotions, and means for adjusting the displayed advertising information based on the emotions determined by the emotion analysis means. This makes it possible to display advertising information that is adapted to the user's emotional state.

[0800] An "information processing device" is a machine or device that receives data, processes it, and provides information to users.

[0801] "Artificial intelligence" is a technology that allows computer systems to autonomously analyze and process information through learning and reasoning as they operate.

[0802] "Advertising information" refers to detailed data and visual content about products and services, provided with the aim of attracting the user's interest.

[0803] A "database" is a system for organizing information structurally and efficiently storing, searching, and managing it.

[0804] "Emotion analysis means" refers to technology for detecting and interpreting a user's emotional state based on facial movements, voice, and other factors.

[0805] "Adjusting priorities" refers to determining the importance and display order of information that should be presented based on specific criteria or conditions.

[0806] A "user terminal" is a device that a user directly operates to acquire or input information.

[0807] As an embodiment of this invention, an emotion-adaptive advertising display system will be described. This system comprises a user terminal, a server as an information processing device, and an emotion analysis engine.

[0808] First, the user terminal receives user input using a device such as a smartphone or smart glasses, and sets up advertising information. This input information is sent to the server to be stored in a database. On the server, artificial intelligence adjusts the priority of information based on the user's search query and recommends the most suitable advertising information based on the stored advertising information.

[0809] Furthermore, the user's facial movements and voice are captured in real time using the user's device's camera and microphone, and an emotion analysis engine analyzes this data to determine the user's emotional state. This emotional state is sent to a server, and based on the information obtained from the emotion analysis, the displayed advertising information is dynamically adjusted. This analysis process can utilize a platform such as Google TensorFlow.

[0810] For example, if a user searches for "lunch spots" and their facial expression is analyzed as showing "surprise," the server can prioritize displaying information about new menu items that would delight this surprised feeling, along with vivid images. This can enhance the effectiveness of advertising.

[0811] The evaluation and feedback of the results of this ad engine are performed on the server side and provided to advertisers as a detailed report. This report includes user sentiment data and ad performance data, which helps to adjust the ad strategy.

[0812] An example of a prompt message would be: "Output an example of an ad display when the user is interested in lunch. If their emotion is determined to be surprise, what information should be prioritized?" This would be the format of the input to the generative AI model.

[0813] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0814] Step 1:

[0815] The user terminal receives advertising information input from the user. This input includes an overview of the advertisement, target audience, and display period. This information is sent from the terminal to the server in a structured format and stored in a database. The output is form data sent to the server.

[0816] Step 2:

[0817] The server stores the received advertising information in a database. Simultaneously, when a user makes a search query, it prepares to use artificial intelligence to calculate the priority of the information based on the accumulated advertising data. The output is a list of recommended ads for the search query.

[0818] Step 3:

[0819] The user terminal receives the user's search query. Based on this input, the terminal sends the query to the server. The output is the data transmitted to the server as the search query.

[0820] Step 4:

[0821] The server uses artificial intelligence to select high-priority advertisements based on search queries. This process takes into account the user's past behavior history and profile, and utilizes generative AI models such as TensorFlow. The output is recommended advertisement information sent to the user's device.

[0822] Step 5:

[0823] The user's device receives recommended advertising information. Furthermore, it captures the user's facial expressions and voice in real time using the camera and microphone, and sends this data to an emotion analysis engine. The output consists of facial expression data and voice data for emotion analysis.

[0824] Step 6:

[0825] The server uses an emotion analysis engine to determine the user's emotions based on the received facial and voice data. Based on this determination, it dynamically adjusts the advertising information and re-selects the most suitable advertisement for the user. The output is the adjusted advertising information.

[0826] Step 7:

[0827] The adjusted advertising information is sent to the user's device. The user's device then displays this advertisement to the user. The user's reaction is collected and sent to the server as feedback. The output consists of the advertisement screen displayed to the user and the feedback data.

[0828] Step 8:

[0829] The server analyzes feedback data and generates a report on the effectiveness of the advertisements. This report is provided to the advertiser to help improve their future advertising strategies. The output is an analytical report provided to the advertiser.

[0830] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0831] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0832] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0833] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0834] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0835] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0836] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0837] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0838] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0839] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0840] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0841] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0842] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0843] 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.

[0844] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0845] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0846] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0847] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0848] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0849] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0850] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0851] The following is further disclosed regarding the embodiments described above.

[0852] (Claim 1)

[0853] In a system where an information processing device uses artificial intelligence to provide information based on generated advertising information,

[0854] A means of receiving input from users in order to set up advertising information,

[0855] A means of storing the entered advertising information in a database,

[0856] Based on accumulated advertising data, artificial intelligence can adjust the priority of information in response to user search queries and recommend relevant information.

[0857] A means of displaying recommended information on the user's terminal,

[0858] A means of analyzing the results of information provision and generating reports,

[0859] A system that includes this.

[0860] (Claim 2)

[0861] The system according to claim 1, characterized in that the input of advertising information is received via a user terminal provided.

[0862] (Claim 3)

[0863] The system according to claim 1, characterized in that information recommendations by artificial intelligence are made based on the user's profile information and past behavioral history.

[0864] "Example 1"

[0865] (Claim 1)

[0866] A means for transmitting advertising information entered by a user to an information processing device,

[0867] A means of saving the entered advertising information to a database,

[0868] A means of analyzing consumer profile information and past behavioral history using artificial intelligence based on stored data, and providing personalized recommendations.

[0869] A means of adjusting priorities to provide more relevant information in line with consumers' search queries,

[0870] A means of displaying the provided information on the consumer's receiving device,

[0871] A means for monitoring the display and consumption of advertising information and generating performance reports,

[0872] A system that includes this.

[0873] (Claim 2)

[0874] The system according to claim 1, characterized in that advertising information is entered via the user's communication device.

[0875] (Claim 3)

[0876] The system according to claim 1, characterized in that information recommendations by artificial intelligence are made based on consumer characteristics that are derived from their behavioral history and preferences.

[0877] "Application Example 1"

[0878] (Claim 1)

[0879] In a system where a data processing unit uses artificial intelligence to provide information based on generated advertising information,

[0880] A means of receiving data input from users in order to set up advertising information,

[0881] A means of recording the entered advertising information in a database that stores it,

[0882] Based on accumulated advertising data, artificial intelligence can adjust the priority of information in response to user search queries and recommend relevant information.

[0883] A means of displaying recommended information on the user's terminal,

[0884] A means of evaluating the results of information provision and generating a report,

[0885] A means of analyzing data based on user behavior and interests and providing personalized advertising information in real time,

[0886] A system that includes this.

[0887] (Claim 2)

[0888] The system according to claim 1, characterized in that the input of advertising information is received via the user's device provided.

[0889] (Claim 3)

[0890] The system according to claim 1, characterized in that information recommendations by artificial intelligence are made based on the user's attribute information and historical data.

[0891] "Example 2 of combining an emotion engine"

[0892] (Claim 1)

[0893] A means of receiving input from users in order to set up advertising information,

[0894] A means for storing the entered advertising information in a storage device,

[0895] A means by which artificial intelligence recommends information in response to a user's search command, adjusting the priority based on advertising information stored in a memory device.

[0896] A means for analyzing the emotional state of users and dynamically adjusting information based on the analysis results,

[0897] A means of displaying recommended information on the user's terminal,

[0898] A means of analyzing the results of information provision and generating a report,

[0899] A system that includes this.

[0900] (Claim 2)

[0901] The system according to claim 1, characterized in that the input of advertising information is received via a user terminal provided, and the analysis of the user's emotional state is performed via said terminal.

[0902] (Claim 3)

[0903] The system according to claim 1, characterized in that information recommendations by artificial intelligence are made based on the user's characteristic information and past behavioral history, and are adjusted based on the user's emotional state.

[0904] "Application example 2 when combining with an emotional engine"

[0905] (Claim 1)

[0906] In a system where an information processing device uses artificial intelligence to provide information based on generated advertising information,

[0907] A means of receiving input from users in order to set up advertising information,

[0908] A means of storing the entered advertising information in a database,

[0909] Based on accumulated advertising data, artificial intelligence can adjust the priority of information in response to user search queries and recommend relevant information.

[0910] A means of displaying recommended information on the user's terminal,

[0911] A means of analyzing the results of information provision and generating reports,

[0912] An emotion analysis means that analyzes the user's facial movements and determines the resulting emotions,

[0913] A means for adjusting the displayed advertising information based on emotions determined by emotion analysis means,

[0914] A system that includes this.

[0915] (Claim 2)

[0916] The system according to claim 1, characterized in that the input of advertising information is received via a user terminal provided.

[0917] (Claim 3)

[0918] The system according to claim 1, characterized in that information recommendations by artificial intelligence are made based on the user's profile information and past behavioral history. [Explanation of Symbols]

[0919] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. In a system where a data processing unit uses artificial intelligence to provide information based on generated advertising information, A means of receiving data input from users in order to set up advertising information, A means of recording the entered advertising information in a database that stores it, Based on accumulated advertising data, artificial intelligence can adjust the priority of information in response to user search queries and recommend relevant information. A means of displaying recommended information on the user's terminal, A means of evaluating the results of information provision and generating a report, A means of analyzing data based on user behavior and interests and providing personalized advertising information in real time, A system that includes this.

2. The system according to claim 1, characterized in that the input of advertising information is received via the user's device provided.

3. The system according to claim 1, characterized in that information recommendations by artificial intelligence are made based on the user's attribute information and historical data.

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