system

Abstract

We provide the system. [Solution] A means for receiving information from a user and identifying the relevant information, Artificial intelligence processing means that generates a response based on identified information, An advertising display method that displays an ad after a specific action is completed, A data storage means that processes user input and saves the information, A system that includes this.

Description

Technical Field

[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 the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot's character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

Means for Solving the Problems

[0005] This invention provides a system that delivers a consistent user experience by having artificial intelligence generate responses based on user input and presenting appropriate advertisements after specific actions during use. Furthermore, it includes means to improve advertising effectiveness by selecting relevant advertisements using surveys. This system aims to maintain a comfortable user experience while ensuring profits for advertisers by having a control function that allows for the rapid resumption of agent use after advertisement display.

[0006] A "user" is the entity that uses this system to input information and receive services from the AI ​​agent.

[0007] "Means for receiving information and identifying relevant information" refers to a function that acquires data entered by the user, identifies its content, and uses it for appropriate responses or processing.

[0008] "Artificial intelligence processing means" refers to an algorithm or system that has the function of performing analysis based on received information and generating an appropriate response.

[0009] An "advertising display method" is a function that presents advertisements to users at specific times within a system, making their content visible.

[0010] "Data storage means" refers to a function or device for temporarily or permanently storing information received from users or analysis results from AI.

[0011] "Analysis tools that present survey information to users" refers to a function that presents users with questions to ask for their opinions and preferences, analyzes the results, and uses them for ad selection.

[0012] "Control measures" refer to functions that grant permission to resume using the AI ​​agent after an advertisement has been displayed, and to manage the user experience. [Brief explanation of the drawing]

[0013] [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 a data processing device and a 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, which incorporates an emotion engine. [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]

[0014] An example of an embodiment of the system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0016] In the following embodiments, the numbered processor (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.

[0017] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, the numbered storage 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, etc.

[0019] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0020] 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."

[0021] [First Embodiment]

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

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0028] 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.

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

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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".

[0034] This invention is an advertising-supported system that allows users to use an AI agent free of charge. Users can access the AI ​​agent via a terminal, input information, and receive a response. An embodiment thereof is shown below.

[0035] Program Processing Overview

[0036] 1. Information input and reception

[0037] The user inputs questions or instructions to the AI ​​agent on their device. For example, they might enter a request such as, "What's the weather like today?"

[0038] The device sends this information to the server.

[0039] 2. Information Analysis and Response Generation

[0040] The server provides the received information to the AI ​​model, which then generates an appropriate response through natural language processing.

[0041] This process involves accessing external information sources, such as weather databases, to derive accurate answers.

[0042] 3. Providing a response

[0043] The server sends the generated response to the terminal.

[0044] The device displays the result to the user, and the user receives an answer such as, "Today's weather is sunny."

[0045] 4. Selection and display of advertisements

[0046] After a specific action, the server selects relevant advertisements and sends them to the device.

[0047] For example, after a user retrieves weather information, an advertisement for raincoats could be displayed for 30 seconds.

[0048] 5. Linking surveys and advertisements

[0049] Periodically, the server selects which questions to present, and the terminal then displays them to the user.

[0050] When a user answers a survey, that information is sent to the server, and advertisements for related products and services are displayed again.

[0051] 6. System Control

[0052] Once the advertisement finishes displaying, the device will allow you to use the AI ​​agent again.

[0053] Users can continue to use the AI ​​agent's features.

[0054] Thus, the present invention is a system that naturally integrates advertisements without compromising the user experience, while simultaneously providing effective information to advertisers. A specific example is a sequence of events in which, after obtaining a weather forecast, advertisements for related fashion items are displayed, followed by the user's response actions. With this invention, users can effectively accept advertisements while utilizing AI free of charge.

[0055] The following describes the processing flow.

[0056] Step 1:

[0057] The user operates the device and inputs questions and instructions through the AI ​​agent. For example, they might input, "Tell me the weather for tomorrow."

[0058] Step 2:

[0059] The terminal receives this input and sends a request to the server as a digital message. The request contains the user's question.

[0060] Step 3:

[0061] The server receives the request and inputs it into a natural language processing AI model. The AI ​​model analyzes the user's question and accesses the necessary data sources to generate an appropriate response.

[0062] Step 4:

[0063] The server generates a response based on the analysis results. For example, it might generate information such as, "The forecast for tomorrow is sunny."

[0064] Step 5:

[0065] The server sends the generated response to the terminal. The response contains information related to the user's question.

[0066] Step 6:

[0067] The device receives the response and displays the answer to the user on the screen. The user can then review the provided information.

[0068] Step 7:

[0069] The server checks if a specific action has been completed. Once completed, it selects the next ad to display and sends that information to the device.

[0070] Step 8:

[0071] The device displays the received advertisement. Typically, a 30-second video advertisement is played for the user.

[0072] Step 9:

[0073] If the server needs to display surveys periodically, select a survey and send the data to the device.

[0074] Step 10:

[0075] The device displays a survey on its screen and prompts the user to answer the questions.

[0076] Step 11:

[0077] The user answers the survey, and the device sends the results to the server.

[0078] Step 12:

[0079] The server analyzes the received survey responses and selects the most relevant advertisements.

[0080] Step 13:

[0081] The device presents new advertisements to the user based on the analysis results, attracting their interest.

[0082] Step 14:

[0083] After the advertisement is displayed, the device guides the user to resume using the AI ​​agent. The user can then continue entering questions.

[0084] (Example 1)

[0085] 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."

[0086] In conventional information processing systems, it was difficult to balance the display of advertisements with the user experience when users utilized AI agents. Furthermore, the selection of advertisements was inefficient, making it impossible to provide users with relevant advertising information at the appropriate time. Therefore, there is a need to maximize advertising effectiveness without compromising user convenience.

[0087] 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.

[0088] In this invention, the server includes means for receiving information from a user and identifying the relevant information, means for generating a response based on the identified information using natural language processing, and means for selecting and presenting relevant advertisements after a specific action is completed. This enables the display of advertisements effectively and at an appropriate time while providing valuable information to the user.

[0089] "Means for receiving information from users and identifying relevant information" refers to a configuration that has the function of receiving data provided by users using their terminals and performs a process of extracting and recognizing useful information from that data.

[0090] A "natural language processing means for generating responses based on identified information" is a configuration that has the function of creating a response in natural language using an algorithm based on extracted information.

[0091] An "ad selection mechanism that selects and presents relevant advertisements after a specific action is completed" is a mechanism that, after a specific user operation or request is completed, selects advertisements that are highly relevant to that situation and presents them to the user.

[0092] A "data storage means for transmitting user input and storing information" refers to a configuration that has the function of transmitting user input to another system and storing data for later reuse.

[0093] "Information acquisition means that access external information sources to obtain information" refers to a configuration that has a mechanism for connecting to external databases or information provision services to obtain the necessary data.

[0094] "Analytics for presenting survey information to users and selecting relevant advertisements" refers to a configuration that displays questions to users to conduct a survey and has an analytical function that determines the most suitable advertisement based on their answers.

[0095] "Means of operation that allow the use of agent functions to be resumed after ad presentation" refers to a configuration that provides a procedure for the user to perform an action that allows them to use the AI ​​agent functions again after an ad has been displayed.

[0096] This invention is a system that allows users to naturally experience advertisements while obtaining information by utilizing an AI agent free of charge. This system operates through the cooperation of three parties: the user, the device, and the server.

[0097] Users can access the AI ​​agent via devices such as computers and smartphones. The device receives information entered by the user and sends it to the server. The communication technology used is a common internet protocol (e.g., HTTPS) to maintain a stable connection.

[0098] The server analyzes the received information and generates appropriate responses using natural language processing. This process includes querying external databases (e.g., publicly available weather information APIs). The program, built with a generative AI model, is designed to answer user questions quickly and accurately.

[0099] After generating a response, the server sends the result back to the terminal, which then visually presents the information to the user. The server also selects relevant advertisements based on the user's actions and displays them on the terminal. This allows users to receive both useful information and engaging advertisements.

[0100] As a concrete example, if a user enters a prompt such as "What's the weather like today?", the system first sends that information to the server. The server uses an AI model to analyze the weather data and generate a response. After the response is displayed to the user, advertisements for products related to that information (for example, umbrella advertisements) are presented.

[0101] In this way, users, devices, and servers each play their respective roles and work together to provide users with a practical and engaging experience.

[0102] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0103] Step 1:

[0104] The user connects to the AI ​​agent through their device and inputs information. The input is in the form of text-based prompts, such as "What's the weather like today?". This input is recognized as digital data by the device and sent to the server.

[0105] Step 2:

[0106] The server receives information sent from the terminal. Based on this received data, the server passes prompt sentences to the generative AI model. Natural language processing techniques are used here to perform semantic analysis of the input data and generate appropriate responses. The server accesses external information sources, such as weather databases, as needed to obtain accurate information.

[0107] Step 3:

[0108] The server uses an AI model to generate responses. This generation process employs natural language algorithms to construct context-aware answers. For example, a specific response such as "Today's weather is sunny" is generated. This response data is then sent to the terminal.

[0109] Step 4:

[0110] The terminal displays the response received from the server to the user. This display is provided as visual text information based on the terminal's interface. This allows the user to easily obtain the information they are looking for.

[0111] Step 5:

[0112] After completing a specific action based on the user's request, the server initiates a process to select relevant advertisements. Using AI technology, the most suitable advertisements are chosen based on the user's interests and browsing history. For example, advertisements for outdoor equipment related to sunny days may be selected.

[0113] Step 6:

[0114] Selected advertisements are sent from the server to the device, which then displays the advertisement to the user. The advertisements are set to be displayed for a set period of time, and the process proceeds to the next step after detecting the end of the advertisement. This process ensures that advertisers receive effective information.

[0115] Step 7:

[0116] After the advertisement finishes displaying, the device allows the AI ​​agent to access it again. This action allows the user to continue using the system without interruption. The system is then ready to repeat the same process for any further input from the user.

[0117] (Application Example 1)

[0118] 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."

[0119] In today's world, e-commerce is rapidly expanding, allowing consumers to easily purchase a wide variety of goods and services. However, consumers often struggle to receive timely and relevant promotional information and benefits when making payments. As a result, they may miss out on available discounts and coupons, hindering increased consumer satisfaction. Businesses also face challenges, such as insufficient timely provision of promotional information, leading to missed opportunities for increased sales.

[0120] 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.

[0121] In this invention, the server includes a response generation means that provides relevant sales promotion information based on payment data, a reward calculation means that calculates and displays reward information for the next use, and a control means that allows the user to resume using the agent after the advertisement is displayed. This enables consumers to instantly receive relevant sales promotion information and rewards for the next use when they make a payment, and to smoothly continue using the AI ​​agent's functions after smoothly reviewing the advertisement.

[0122] "Means for receiving information from users and identifying the relevant information" refers to a function that accurately receives information entered by the user from a terminal and identifies what that information means.

[0123] "Artificial intelligence processing means for generating a response based on identified information" refers to an AI-based process for creating an appropriate response based on identified information.

[0124] An "ad display method that displays ads after a specific action is completed" is a function that displays relevant ads at the point when a user's action has come to a close.

[0125] A "data storage method that transitions user input and saves information" is a system that saves data entered by a user while transitioning that data to a different screen or step.

[0126] "Response generation means that provides relevant sales promotion information based on payment data" refers to a process that analyzes a user's payment information and provides relevant sales promotion information.

[0127] The "reward calculation means for calculating and displaying reward information for the next use" is a function that calculates the content of the rewards that will be applied on the next use and displays the results in an easy-to-understand manner for the user.

[0128] "Control measures that allow the user to resume using the agent after the ad has been displayed" refers to a system that allows the user to use the AI ​​agent again without any problems after the ad display has finished.

[0129] To implement this invention, it is first necessary to construct a system for sending and receiving data between a server and a user terminal. The server is equipped with means for receiving information from the user and appropriately identifying it. Specifically, the user inputs questions or instructions via a user terminal such as a smartphone or tablet, and that data is sent to the server.

[0130] The server generates a response using an AI model based on the identified information. This process utilizes generative AI models such as OpenAI's GPT as its natural language processing engine. This AI model has the ability to analyze the received data and generate responses tailored to user needs and relevant promotional information in real time.

[0131] Next, after the user completes a specific action, the server uses advertising means to display relevant advertisements on the user's device. After the advertisements are displayed, the user can use the AI ​​agent again. Here, it is required that the advertisements are displayed smoothly and that subsequent operations continue seamlessly so as not to disrupt the user experience.

[0132] For data storage, a cloud database such as Firebase is used. By properly transferring and saving user input history and payment information, reward information can be calculated and presented to the user upon their next use. A reward calculation method is used for this calculation, generating specific preferential information such as coupons and discounts.

[0133] For example, after a user pays at a restaurant, if they ask the AI ​​agent, "Are there any promotions?", the server will generate the most suitable coupons and benefits for future visits and display them immediately on the terminal. An example of a prompt used by the server in this process would be, "I am paying for the meal at the store specified by the user. Please have the AI ​​agent generate the latest promotional coupons for this payment." This allows users to quickly obtain relevant information, not only improving satisfaction but also helping businesses increase sales.

[0134] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0135] Step 1:

[0136] The user inputs questions or instructions to the AI ​​agent from their device. For example, the user might ask, "Are there any campaigns?" This input is received by the device and sent to the server. The input data is transferred to the server in string format and processed as a request.

[0137] Step 2:

[0138] The server analyzes the user's question received. During this process, natural language processing is performed using OpenAI's GPT generative AI model. The AI ​​agent analyzes the input data and converts the information into a structured data format to understand the user's needs. As a result, it determines what kind of sales promotion information is appropriate.

[0139] Step 3:

[0140] The server retrieves relevant sales promotion information from the database based on the analysis results. It uses Firebase to search payment history and campaign information, identifying suitable coupons and offers. This allows the generative AI model to prepare output data to provide the most useful information to the user.

[0141] Step 4:

[0142] The server sends the generated response and advertising information to the user's device. The offer information and advertisements are displayed on the user's device for the user to review. The output data includes coupon codes and conditions for using the offers.

[0143] Step 5:

[0144] The device displays special offers and advertisements to the user. The user reviews the presented information and, if necessary, follows the on-screen instructions to take further action. Once the advertisement review is complete, the user can continue to use the AI ​​agent's features.

[0145] Step 6:

[0146] When a user receives a reward for their next visit, the server saves that information to a database. This updates the user's usage history and ensures that the reward is applied to their next transaction. The prompt used included the following: "I will pay the fee at the store specified by the user. Please have the AI ​​agent generate the latest promotional coupon for this payment."

[0147] 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.

[0148] This invention relates to an AI agent system that incorporates an emotion engine that recognizes user emotions and adjusts responses accordingly. This system has the function of automatically generating responses based on user input and displaying appropriate advertisements at the time a specific action is completed. Furthermore, it includes a control function that seamlessly maintains user interaction so that the AI ​​agent can continue to be used even after the advertisement is displayed.

[0149] The system consists of a terminal, a server, and an emotion engine. First, the user inputs information via the terminal and interacts with an AI agent. The terminal relays this input to the server, which, in the process of generating a response through its AI processor, also takes the user's emotions into consideration.

[0150] The emotion engine analyzes the user's voice, text, and biometric data to determine their current emotional state. For example, if it detects signs of anxiety, it generates an encouraging message to address that. This emotional data is stored and used in future interactions.

[0151] For example, if a user uses their device to tell the agent, "I'm worried about preparing my presentation," the emotion engine will detect the user's anxiety and the server will respond with an encouraging suggestion such as, "Shall I help you with your preparation?" Then, at an appropriate time, advertisements for presentation-related tools and books will be displayed.

[0152] In this way, by understanding the user's emotional state in real time, it becomes possible to provide personalized responses and select advertisements, thereby improving the quality of the user experience. By incorporating emotion recognition, the effectiveness of advertisements is also increased, and more efficient promotional results can be expected.

[0153] The following describes the processing flow.

[0154] Step 1:

[0155] The user enters a message into the AI ​​agent via their device. For example, they might send something like, "I'm feeling down today."

[0156] Step 2:

[0157] The terminal receives input from the user and sends that data to the server. The message contains text information.

[0158] Step 3:

[0159] The server passes the received data to the emotion engine for analysis. This process determines what emotions the user's text is associated with.

[0160] Step 4:

[0161] The emotion engine processes the data and determines that the user is feeling "depressed." Based on this, it instructs the AI ​​model to generate an appropriate response.

[0162] Step 5:

[0163] The server uses an AI model to generate responses that are appropriate to the user's emotions. For example, it might generate a response like, "Shall we take a break and relax today?"

[0164] Step 6:

[0165] The server sends the generated response to the terminal and displays it to the user. The user receives the support message through the screen.

[0166] Step 7:

[0167] The server then enters a process to select ads that match the user's emotions. It considers emotional data and, for example, associates ads for relaxation products.

[0168] Step 8:

[0169] The device receives advertising data and displays ads to the user at the appropriate time. Afterwards, it can return to the AI ​​agent.

[0170] Step 9:

[0171] The device waits for user input again and allows the AI ​​agent function to resume. The user can continue using the service.

[0172] This system enables emotion-responsive responses and ad presentations, allowing users to receive personalized support.

[0173] (Example 2)

[0174] 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".

[0175] Current artificial intelligence systems suffer from inconsistent user experiences due to their insufficient accuracy in responding to user emotions. Furthermore, frequent interruptions to user interaction due to advertisements hinder continued use. Additionally, ad selection is often not optimized based on user emotions or states, resulting in limited effectiveness.

[0176] 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.

[0177] In this invention, the server includes an analysis means for analyzing the user's emotional state, a generation means for generating a response based on the analyzed emotional state, and a display means for displaying guidance information after a specific task is completed. This allows for the provision of customized responses tailored to the user's emotions, and enables the display of advertisements at the optimal timing without disrupting the user's continuity.

[0178] A "receiving means" is an interface for acquiring information from the user and incorporating it into the system.

[0179] "Intelligent processing means" refers to an algorithm that performs predetermined processing based on identified information.

[0180] "Analysis means" refers to a software or hardware mechanism for analyzing a user's emotional state.

[0181] A "generative means" is a process that has the function of producing a response based on the analyzed emotional state.

[0182] "Display means" refers to a device or screen that visually shows guidance information to the user after a specific task has been completed.

[0183] A "retention mechanism" refers to a data storage system for managing user information, storing it in an appropriate format, and managing its transitions.

[0184] This invention is an artificial intelligence agent system that analyzes a user's emotions in real time and provides personalized responses based on that analysis. The system consists mainly of a terminal, a server, and an emotion analysis engine. A specific embodiment of the system is described below.

[0185] First, the user inputs information into the AI ​​agent in natural language via a device. This device can be a smartphone or computer, and the input is provided as text or voice. In the case of voice input, the device uses speech recognition software to convert the voice into text.

[0186] The input information is sent to the server. The server uses an emotion analysis engine to recognize the user's emotional state from the input information. This analysis uses emotion recognition software that leverages natural language processing technology. Based on the results, a generative AI model generates the optimal response.

[0187] In conjunction with response generation, the server selects relevant advertisements after a specific task is completed and sends them to the device. For example, if a user enters "I'm anxious about moving to a new city," the sentiment analysis engine detects the anxiety, and the generative AI model generates a response such as "A new adventure is about to begin, shall we help?" Simultaneously, an advertisement for a moving service is appropriately displayed.

[0188] As an example of a prompt, the following input could be given to the generative AI model: "Analyze the user's emotions and suggest a response based on those emotions. User input: 'I'm worried about preparing my presentation.'"

[0189] In this way, the system improves the quality of the user experience by providing customized responses and advertisements that respond to the user's emotions.

[0190] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0191] Step 1:

[0192] The user inputs information in natural language via the terminal. This input is provided as either text or voice. In the case of voice input, the terminal converts the voice data into text data using speech recognition software. The output of the input is data in text format.

[0193] Step 2:

[0194] The terminal sends the converted text data to the server. The server receives this data and activates an emotion analysis engine to analyze the user's emotional state. The emotion analysis engine uses natural language processing techniques to extract emotional features from the text data, and the output is the user's emotional state (e.g., anxiety, joy).

[0195] Step 3:

[0196] The server passes the user's emotional state as input to a generative AI model. The generative AI model uses prompts to generate the optimal response corresponding to the emotion. This process employs an algorithm that generates text responses while considering the emotional state. The generated response is the output.

[0197] Step 4:

[0198] The server selects advertisements that are appropriate to the user's context, along with the generated response. The selection of advertisements takes into account the user's emotions and the progress of the conversation. The output is the selection of appropriate advertisements.

[0199] Step 5:

[0200] The device displays the response received from the server along with advertisements. The user can then interact with the agent again based on this information. The display serves to maintain a seamless interaction with the user.

[0201] (Application Example 2)

[0202] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0203] In modern information processing systems, recognizing a user's emotional state in real time and providing personalized information and selecting advertisements based on that understanding is crucial for improving the user experience. However, conventional systems struggle to generate dynamic responses in response to changes in user emotions and to select advertisements based on those emotions. Therefore, there is a need for technologies that enable personalized information provision and efficient advertisement selection that take user emotions into consideration, while ensuring seamless interaction.

[0204] 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.

[0205] In this invention, the server includes means for receiving information from the user and analyzing their emotional state, means for generating and personalizing a response based on the analysis results, and means for displaying advertisements corresponding to the analyzed emotional state. This enables responses and advertisements based on the user's emotions, thereby improving the quality of interaction.

[0206] "Means for receiving information from users and identifying relevant information" refers to technologies for collecting user-provided input data in real time and identifying the content and type of that data.

[0207] "An artificial intelligence processing means for generating responses based on identified information and analyzing the user's emotional state" refers to a technology that includes an algorithm for creating an appropriate response based on identified input data and for estimating the user's emotions.

[0208] "An advertising display method that selects and displays appropriate advertisements based on analyzed emotional states" refers to a technology that selects highly relevant advertisements based on the results of emotional analysis and displays them to the user at the appropriate time.

[0209] "A data storage method that processes user input and saves information" refers to database technology for appropriately structuring and continuously storing data obtained from users.

[0210] "Means for personalizing responses based on analyzed emotional states" refers to a system or method for designing appropriate and specific response content according to each user's emotions.

[0211] "Control mechanisms that allow seamless resumption of agent use" are mechanisms that enable smooth resumption of interaction without disrupting the user experience after an advertisement is displayed or a conversation is interrupted.

[0212] To implement this invention, it is necessary to construct a system including a server, a terminal, and an artificial intelligence agent. This system provides an environment in which user input is captured, emotions are recognized, and personalized advertisements are displayed.

[0213] The device is responsible for collecting voice and text data from the user. This data is sent to the server via natural language processing software such as Google Cloud's Natural Language API or Amazon Comprehend. The server analyzes the user's emotional state using an emotion recognition model based on TENSORFLOW®.

[0214] Based on an analysis of the user's emotional state, the server generates a response. This response is personalized, taking emotional data into consideration, and designed to deepen the user interaction. Furthermore, the analysis results are used as the basis for displaying advertisements, presenting the ads most relevant to the user via the AdMob SDK and other means.

[0215] For example, if a user says, "I'm a little tired," the emotion engine will generate a stress-reducing response and naturally display advertisements for products and services that help users relax at work. Through such interactions, users can receive information that matches their emotions, thus forming a positive impression of the advertisements.

[0216] An example of a prompt message is: "The user has reported fatigue, so provide information about relaxation and display appropriate advertisements." This allows you to give instructions to the generative AI model, enabling dynamic interactions that optimize the user experience.

[0217] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0218] Step 1:

[0219] The user provides input via voice or text through the device. This input is captured by the device and prepared as initial data. The input data is formatted appropriately on the device according to the input format and prepared for transmission to the server.

[0220] Step 2:

[0221] The device captures input data and sends it to the server. The server receives this data and performs text analysis using Google Cloud's Natural Language API or Amazon Comprehend. The analysis generates initial data on the text's content, keywords, and sentiment (e.g., positive, negative, neutral).

[0222] Step 3:

[0223] The server supplies the analyzed text and sentiment data to an emotion recognition model powered by TensorFlow. This step analyzes the user's detailed emotional state and generates specific emotion labels (e.g., fatigue, joy, anxiety). This process generates numerical data from the server indicating which emotions are most strongly expressed.

[0224] Step 4:

[0225] The server generates personalized responses using a generative AI model based on the emotion recognition results. The input includes emotion data and associated contextual information. The AI ​​model uses appropriate prompts to form informative and encouraging messages for the user. The generated responses are sent back to the terminal.

[0226] Step 5:

[0227] The server analyzes sentiment data and selects the most relevant ads for the user. This involves querying a database of ads highly relevant to the user's emotional state. Once ad selection is complete, it prepares to deliver the ads to the user's device via the AdMob SDK.

[0228] Step 6:

[0229] The user's device displays personalized responses and advertisements received from the server. The user can then react to the advertisements or presented responses and provide further input. Continuing this interaction initiates the next processing cycle.

[0230] 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.

[0231] 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.

[0232] 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.

[0233] [Second Embodiment]

[0234] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0235] 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.

[0236] 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).

[0237] 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.

[0238] 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.

[0239] 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).

[0240] 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.

[0241] 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.

[0242] 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.

[0243] 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.

[0244] 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.

[0245] 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".

[0246] This invention is an advertising-supported system that allows users to use an AI agent free of charge. Users can access the AI ​​agent via a terminal, input information, and receive a response. An embodiment thereof is shown below.

[0247] Program Processing Overview

[0248] 1. Information input and reception

[0249] The user inputs questions or instructions to the AI ​​agent on their device. For example, they might enter a request such as, "What's the weather like today?"

[0250] The device sends this information to the server.

[0251] 2. Information Analysis and Response Generation

[0252] The server provides the received information to the AI ​​model, which then generates an appropriate response through natural language processing.

[0253] This process involves accessing external information sources, such as weather databases, to derive accurate answers.

[0254] 3. Providing a response

[0255] The server sends the generated response to the terminal.

[0256] The device displays the result to the user, and the user receives an answer such as, "Today's weather is sunny."

[0257] 4. Selection and display of advertisements

[0258] After a specific action, the server selects relevant advertisements and sends them to the device.

[0259] For example, after a user retrieves weather information, an advertisement for raincoats could be displayed for 30 seconds.

[0260] 5. Linking surveys and advertisements

[0261] Periodically, the server selects which questions to present, and the terminal then displays them to the user.

[0262] When a user answers a survey, that information is sent to the server, and advertisements for related products and services are displayed again.

[0263] 6. System Control

[0264] Once the advertisement finishes displaying, the device will allow you to use the AI ​​agent again.

[0265] Users can continue to use the AI ​​agent's features.

[0266] Thus, the present invention is a system that naturally integrates advertisements without compromising the user experience, while simultaneously providing effective information to advertisers. A specific example is a sequence of events in which, after obtaining a weather forecast, advertisements for related fashion items are displayed, followed by the user's response actions. With this invention, users can effectively accept advertisements while utilizing AI free of charge.

[0267] The following describes the processing flow.

[0268] Step 1:

[0269] The user operates the device and inputs questions and instructions through the AI ​​agent. For example, they might input, "Tell me the weather for tomorrow."

[0270] Step 2:

[0271] The terminal receives this input and sends a request to the server as a digital message. The request contains the user's question.

[0272] Step 3:

[0273] The server receives the request and inputs it into a natural language processing AI model. The AI ​​model analyzes the user's question and accesses the necessary data sources to generate an appropriate response.

[0274] Step 4:

[0275] The server generates a response based on the analysis results. For example, it might generate information such as, "The forecast for tomorrow is sunny."

[0276] Step 5:

[0277] The server sends the response it generated to the terminal. The response contains information regarding the user's question.

[0278] Step 6:

[0279] The terminal receives the response and displays the answer to the user on the screen. The user can check the provided information.

[0280] Step 7:

[0281] The server checks whether a specific action has been completed. After completion, it selects the next advertisement to display and sends that information to the terminal.

[0282] Step 8:

[0283] The terminal displays the received advertisement. Usually, a 30 - second advertisement video is played for the user.

[0284] Step 9:

[0285] If the server needs to periodically present a questionnaire, it selects the questionnaire and sends its data to the terminal.

[0286] Step 10:

[0287] The terminal displays the questionnaire on the screen and prompts the user to answer the questions.

[0288] Step 11:

[0289] ]> The user answers the questionnaire, and the terminal sends the result to the server.

[0290] Step 12:

[0291] The server analyzes the received questionnaire answers and selects relevant advertisements.

[0292] Step 13:

[0293] The device presents new advertisements to the user based on the analysis results, attracting their interest.

[0294] Step 14:

[0295] After the advertisement is displayed, the device guides the user to resume using the AI ​​agent. The user can then continue entering questions.

[0296] (Example 1)

[0297] 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."

[0298] In conventional information processing systems, it was difficult to balance the display of advertisements with the user experience when users utilized AI agents. Furthermore, the selection of advertisements was inefficient, making it impossible to provide users with relevant advertising information at the appropriate time. Therefore, there is a need to maximize advertising effectiveness without compromising user convenience.

[0299] 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.

[0300] In this invention, the server includes means for receiving information from a user and identifying the relevant information, means for generating a response based on the identified information using natural language processing, and means for selecting and presenting relevant advertisements after a specific action is completed. This enables the display of advertisements effectively and at an appropriate time while providing valuable information to the user.

[0301] "Means for receiving information from users and identifying relevant information" refers to a configuration that has the function of receiving data provided by users using their terminals and performs a process of extracting and recognizing useful information from that data.

[0302] The "natural language processing means for generating a response based on the identified information" is a configuration having a function of creating an answer in natural language using an algorithm based on the extracted information.

[0303] The "advertisement selection means for selecting and presenting relevant advertisements after a specific action is completed" is a mechanism that selects advertisements highly relevant to the situation and presents them to the user after the completion of a specific operation or request of the user.

[0304] The "data storage means for transmitting user input and storing information" is a configuration equipped with a function of transmitting user input to other systems and storing data for later reuse.

[0305] The "information acquisition means for accessing an external information source and acquiring information" is a configuration having a mechanism for connecting to an external database or information providing service and acquiring necessary data.

[0306] The "analysis means for presenting questionnaire information to the user and selecting relevant advertisements" is a configuration having an analysis function of displaying questions for conducting a survey on the user and determining the optimal advertisement based on the answers.

[0307] The "operation means for permitting the resumption of the use of the agent function after advertisement presentation" is a construction that provides a procedure for performing an operation so that the user can use the function of the AI agent again after the advertisement is displayed.

[0308] This invention is a system in which a user can freely utilize an AI agent, experience advertisements naturally while obtaining information. This system operates with the cooperation of three parties: the user, the terminal, and the server.

[0309] Users can access the AI ​​agent via devices such as computers and smartphones. The device receives information entered by the user and sends it to the server. The communication technology used is a common internet protocol (e.g., HTTPS) to maintain a stable connection.

[0310] The server analyzes the received information and generates appropriate responses using natural language processing. This process includes querying external databases (e.g., publicly available weather information APIs). The program, built with a generative AI model, is designed to answer user questions quickly and accurately.

[0311] After generating a response, the server sends the result back to the terminal, which then visually presents the information to the user. The server also selects relevant advertisements based on the user's actions and displays them on the terminal. This allows users to receive both useful information and engaging advertisements.

[0312] As a concrete example, if a user enters a prompt such as "What's the weather like today?", the system first sends that information to the server. The server uses an AI model to analyze the weather data and generate a response. After the response is displayed to the user, advertisements for products related to that information (for example, umbrella advertisements) are presented.

[0313] In this way, users, devices, and servers each play their respective roles and work together to provide users with a practical and engaging experience.

[0314] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0315] Step 1:

[0316] The user connects to the AI ​​agent through their device and inputs information. The input is in the form of text-based prompts, such as "What's the weather like today?". This input is recognized as digital data by the device and sent to the server.

[0317] Step 2:

[0318] The server receives information sent from the terminal. Based on this received data, the server passes prompt sentences to the generative AI model. Natural language processing techniques are used here to perform semantic analysis of the input data and generate appropriate responses. The server accesses external information sources, such as weather databases, as needed to obtain accurate information.

[0319] Step 3:

[0320] The server uses an AI model to generate responses. This generation process employs natural language algorithms to construct context-aware answers. For example, a specific response such as "Today's weather is sunny" is generated. This response data is then sent to the terminal.

[0321] Step 4:

[0322] The terminal displays the response received from the server to the user. This display is provided as visual text information based on the terminal's interface. This allows the user to easily obtain the information they are looking for.

[0323] Step 5:

[0324] After completing a specific action based on the user's request, the server initiates a process to select relevant advertisements. Using AI technology, the most suitable advertisements are chosen based on the user's interests and browsing history. For example, advertisements for outdoor equipment related to sunny days may be selected.

[0325] Step 6:

[0326] Selected advertisements are sent from the server to the device, which then displays the advertisement to the user. The advertisements are set to be displayed for a set period of time, and the process proceeds to the next step after detecting the end of the advertisement. This process ensures that advertisers receive effective information.

[0327] Step 7:

[0328] After the advertisement finishes displaying, the device allows the AI ​​agent to access it again. This action allows the user to continue using the system without interruption. The system is then ready to repeat the same process for any further input from the user.

[0329] (Application Example 1)

[0330] 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."

[0331] In today's world, e-commerce is rapidly expanding, allowing consumers to easily purchase a wide variety of goods and services. However, consumers often struggle to receive timely and relevant promotional information and benefits when making payments. As a result, they may miss out on available discounts and coupons, hindering increased consumer satisfaction. Businesses also face challenges, such as insufficient timely provision of promotional information, leading to missed opportunities for increased sales.

[0332] 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.

[0333] In this invention, the server includes a response generation means that provides relevant sales promotion information based on payment data, a reward calculation means that calculates and displays reward information for the next use, and a control means that allows the user to resume using the agent after the advertisement is displayed. This enables consumers to instantly receive relevant sales promotion information and rewards for the next use when they make a payment, and to smoothly continue using the AI ​​agent's functions after smoothly reviewing the advertisement.

[0334] "Means for receiving information from users and identifying the relevant information" refers to a function that accurately receives information entered by the user from a terminal and identifies what that information means.

[0335] "Artificial intelligence processing means for generating a response based on identified information" refers to an AI-based process for creating an appropriate response based on identified information.

[0336] An "ad display method that displays ads after a specific action is completed" is a function that displays relevant ads at the point when a user's action has come to a close.

[0337] A "data storage method that transitions user input and saves information" is a system that saves data entered by a user while transitioning that data to a different screen or step.

[0338] "Response generation means that provides relevant sales promotion information based on payment data" refers to a process that analyzes a user's payment information and provides relevant sales promotion information.

[0339] The "reward calculation means for calculating and displaying reward information for the next use" is a function that calculates the content of the rewards that will be applied on the next use and displays the results in an easy-to-understand manner for the user.

[0340] "Control measures that allow the user to resume using the agent after the ad has been displayed" refers to a system that allows the user to use the AI ​​agent again without any problems after the ad display has finished.

[0341] To implement this invention, it is first necessary to construct a system for sending and receiving data between a server and a user terminal. The server is equipped with means for receiving information from the user and appropriately identifying it. Specifically, the user inputs questions or instructions via a user terminal such as a smartphone or tablet, and that data is sent to the server.

[0342] The server generates a response using an AI model based on the identified information. This process utilizes a generative AI model, such as OpenAI's GPT, as its natural language processing engine. This AI model has the ability to analyze the received data and generate responses tailored to user needs and relevant promotional information in real time.

[0343] Next, after the user completes a specific action, the server uses advertising means to display relevant advertisements on the user's device. After the advertisements are displayed, the user can use the AI ​​agent again. Here, it is required that the advertisements are displayed smoothly and that subsequent operations continue seamlessly so as not to disrupt the user experience.

[0344] For data storage, a cloud database such as Firebase is used. By properly transferring and saving user input history and payment information, reward information can be calculated and presented to the user upon their next use. A reward calculation method is used for this calculation, generating specific preferential information such as coupons and discounts.

[0345] For example, after a user pays at a restaurant, if they ask the AI ​​agent, "Are there any promotions?", the server will generate the most suitable coupons and benefits for future visits and display them immediately on the terminal. An example of a prompt used by the server in this process would be, "I am paying for the meal at the store specified by the user. Please have the AI ​​agent generate the latest promotional coupons for this payment." This allows users to quickly obtain relevant information, not only improving satisfaction but also helping businesses increase sales.

[0346] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0347] Step 1:

[0348] The user inputs questions or instructions to the AI ​​agent from their device. For example, the user might ask, "Are there any campaigns?" This input is received by the device and sent to the server. The input data is transferred to the server in string format and processed as a request.

[0349] Step 2:

[0350] The server analyzes the user's question received. During this process, natural language processing is performed using OpenAI's GPT generative AI model. The AI ​​agent analyzes the input data and converts the information into a structured data format to understand the user's needs. As a result, it determines what kind of sales promotion information is appropriate.

[0351] Step 3:

[0352] The server retrieves relevant sales promotion information from the database based on the analysis results. It uses Firebase to search payment history and campaign information, identifying suitable coupons and offers. This allows the generative AI model to prepare output data to provide the most useful information to the user.

[0353] Step 4:

[0354] The server sends the generated response and advertising information to the user's device. The offer information and advertisements are displayed on the user's device for the user to review. The output data includes coupon codes and conditions for using the offers.

[0355] Step 5:

[0356] The device displays special offers and advertisements to the user. The user reviews the presented information and, if necessary, follows the on-screen instructions to take further action. Once the advertisement review is complete, the user can continue to use the AI ​​agent's features.

[0357] Step 6:

[0358] When a user receives a reward for their next visit, the server saves that information to a database. This updates the user's usage history and ensures that the reward is applied to their next transaction. The prompt used included the following: "I will pay the fee at the store specified by the user. Please have the AI ​​agent generate the latest promotional coupon for this payment."

[0359] 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.

[0360] This invention relates to an AI agent system that incorporates an emotion engine that recognizes user emotions and adjusts responses accordingly. This system has the function of automatically generating responses based on user input and displaying appropriate advertisements at the time a specific action is completed. Furthermore, it includes a control function that seamlessly maintains user interaction so that the AI ​​agent can continue to be used even after the advertisement is displayed.

[0361] The system consists of a terminal, a server, and an emotion engine. First, the user inputs information via the terminal and interacts with an AI agent. The terminal relays this input to the server, which, in the process of generating a response through its AI processor, also takes the user's emotions into consideration.

[0362] The emotion engine analyzes the user's voice, text, and biometric data to determine their current emotional state. For example, if it detects signs of anxiety, it generates an encouraging message to address that. This emotional data is stored and used in future interactions.

[0363] For example, if a user uses their device to tell the agent, "I'm worried about preparing my presentation," the emotion engine will detect the user's anxiety and the server will respond with an encouraging suggestion such as, "Shall I help you with your preparation?" Then, at an appropriate time, advertisements for presentation-related tools and books will be displayed.

[0364] In this way, by understanding the user's emotional state in real time, it becomes possible to provide personalized responses and select advertisements, thereby improving the quality of the user experience. By incorporating emotion recognition, the effectiveness of advertisements is also increased, and more efficient promotional results can be expected.

[0365] The following describes the processing flow.

[0366] Step 1:

[0367] The user enters a message into the AI ​​agent via their device. For example, they might send something like, "I'm feeling down today."

[0368] Step 2:

[0369] The terminal receives input from the user and sends that data to the server. The message contains text information.

[0370] Step 3:

[0371] The server passes the received data to the emotion engine for analysis. This process determines what emotions the user's text is associated with.

[0372] Step 4:

[0373] The emotion engine processes the data and determines that the user is feeling "depressed." Based on this, it instructs the AI ​​model to generate an appropriate response.

[0374] Step 5:

[0375] The server uses an AI model to generate responses that are appropriate to the user's emotions. For example, it might generate a response like, "Shall we take a break and relax today?"

[0376] Step 6:

[0377] The server sends the generated response to the terminal and displays it to the user. The user receives the support message through the screen.

[0378] Step 7:

[0379] The server then enters a process to select ads that match the user's emotions. It considers emotional data and, for example, associates ads for relaxation products.

[0380] Step 8:

[0381] The device receives advertising data and displays ads to the user at the appropriate time. Afterwards, it can return to the AI ​​agent.

[0382] Step 9:

[0383] The device waits for user input again and allows the AI ​​agent function to resume. The user can continue using the service.

[0384] This system enables emotion-responsive responses and ad presentations, allowing users to receive personalized support.

[0385] (Example 2)

[0386] 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".

[0387] Current artificial intelligence systems suffer from inconsistent user experiences due to their insufficient accuracy in responding to user emotions. Furthermore, frequent interruptions to user interaction due to advertisements hinder continued use. Additionally, ad selection is often not optimized based on user emotions or states, resulting in limited effectiveness.

[0388] 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.

[0389] In this invention, the server includes an analysis means for analyzing the user's emotional state, a generation means for generating a response based on the analyzed emotional state, and a display means for displaying guidance information after a specific task is completed. This allows for the provision of customized responses tailored to the user's emotions, and enables the display of advertisements at the optimal timing without disrupting the user's continuity.

[0390] A "receiving means" is an interface for acquiring information from the user and incorporating it into the system.

[0391] "Intelligent processing means" refers to an algorithm that performs predetermined processing based on identified information.

[0392] "Analysis means" refers to a software or hardware mechanism for analyzing a user's emotional state.

[0393] A "generative means" is a process that has the function of producing a response based on the analyzed emotional state.

[0394] "Display means" refers to a device or screen that visually shows guidance information to the user after a specific task has been completed.

[0395] A "retention mechanism" refers to a data storage system for managing user information, storing it in an appropriate format, and managing its transitions.

[0396] This invention is an artificial intelligence agent system that analyzes a user's emotions in real time and provides personalized responses based on that analysis. The system consists mainly of a terminal, a server, and an emotion analysis engine. A specific embodiment of the system is described below.

[0397] First, the user inputs information into the AI ​​agent in natural language via a device. This device can be a smartphone or computer, and the input is provided as text or voice. In the case of voice input, the device uses speech recognition software to convert the voice into text.

[0398] The input information is sent to the server. The server uses an emotion analysis engine to recognize the user's emotional state from the input information. This analysis uses emotion recognition software that leverages natural language processing technology. Based on the results, a generative AI model generates the optimal response.

[0399] In conjunction with response generation, the server selects relevant advertisements after a specific task is completed and sends them to the device. For example, if a user enters "I'm anxious about moving to a new city," the sentiment analysis engine detects the anxiety, and the generative AI model generates a response such as "A new adventure is about to begin, shall we help?" Simultaneously, an advertisement for a moving service is appropriately displayed.

[0400] As an example of a prompt, the following input could be given to the generative AI model: "Analyze the user's emotions and suggest a response based on those emotions. User input: 'I'm worried about preparing my presentation.'"

[0401] In this way, the system improves the quality of the user experience by providing customized responses and advertisements that respond to the user's emotions.

[0402] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0403] Step 1:

[0404] The user inputs information in natural language via the terminal. This input is provided as either text or voice. In the case of voice input, the terminal converts the voice data into text data using speech recognition software. The output of the input is data in text format.

[0405] Step 2:

[0406] The terminal sends the converted text data to the server. The server receives this data and activates an emotion analysis engine to analyze the user's emotional state. The emotion analysis engine uses natural language processing techniques to extract emotional features from the text data, and the output is the user's emotional state (e.g., anxiety, joy).

[0407] Step 3:

[0408] The server passes the user's emotional state as input to a generative AI model. The generative AI model uses prompts to generate the optimal response corresponding to the emotion. This process employs an algorithm that generates text responses while considering the emotional state. The generated response is the output.

[0409] Step 4:

[0410] The server selects advertisements that are appropriate to the user's context, along with the generated response. The selection of advertisements takes into account the user's emotions and the progress of the conversation. The output is the selection of appropriate advertisements.

[0411] Step 5:

[0412] The device displays the response received from the server along with advertisements. The user can then interact with the agent again based on this information. The display serves to maintain a seamless interaction with the user.

[0413] (Application Example 2)

[0414] 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."

[0415] In modern information processing systems, recognizing a user's emotional state in real time and providing personalized information and selecting advertisements based on that understanding is crucial for improving the user experience. However, conventional systems struggle to generate dynamic responses in response to changes in user emotions and to select advertisements based on those emotions. Therefore, there is a need for technologies that enable personalized information provision and efficient advertisement selection that take user emotions into consideration, while ensuring seamless interaction.

[0416] 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.

[0417] In this invention, the server includes means for receiving information from the user and analyzing their emotional state, means for generating and personalizing a response based on the analysis results, and means for displaying advertisements corresponding to the analyzed emotional state. This enables responses and advertisements based on the user's emotions, thereby improving the quality of interaction.

[0418] "Means for receiving information from users and identifying relevant information" refers to technologies for collecting user-provided input data in real time and identifying the content and type of that data.

[0419] "An artificial intelligence processing means for generating responses based on identified information and analyzing the user's emotional state" refers to a technology that includes an algorithm for creating an appropriate response based on identified input data and for estimating the user's emotions.

[0420] "An advertising display method that selects and displays appropriate advertisements based on analyzed emotional states" refers to a technology that selects highly relevant advertisements based on the results of emotional analysis and displays them to the user at the appropriate time.

[0421] "A data storage method that processes user input and saves information" refers to database technology for appropriately structuring and continuously storing data obtained from users.

[0422] "Means for personalizing responses based on analyzed emotional states" refers to a system or method for designing appropriate and specific response content according to each user's emotions.

[0423] "Control mechanisms that allow seamless resumption of agent use" are mechanisms that enable smooth resumption of interaction without disrupting the user experience after an advertisement is displayed or a conversation is interrupted.

[0424] To implement this invention, it is necessary to construct a system including a server, a terminal, and an artificial intelligence agent. This system provides an environment in which user input is captured, emotions are recognized, and personalized advertisements are displayed.

[0425] The device is responsible for collecting voice and text data from the user. This data is sent to the server via natural language processing software such as Google Cloud's Natural Language API or Amazon Comprehend. The server analyzes the user's emotional state using an emotion recognition model based on TensorFlow.

[0426] Based on an analysis of the user's emotional state, the server generates a response. This response is personalized, taking emotional data into consideration, and designed to deepen the user interaction. Furthermore, the analysis results are used as the basis for displaying advertisements, presenting the ads most relevant to the user via the AdMob SDK and other means.

[0427] For example, if a user says, "I'm a little tired," the emotion engine will generate a stress-reducing response and naturally display advertisements for products and services that help users relax at work. Through such interactions, users can receive information that matches their emotions, thus forming a positive impression of the advertisements.

[0428] An example of a prompt message is: "The user has reported fatigue, so provide information about relaxation and display appropriate advertisements." This allows you to give instructions to the generative AI model, enabling dynamic interactions that optimize the user experience.

[0429] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0430] Step 1:

[0431] The user provides input via voice or text through the device. This input is captured by the device and prepared as initial data. The input data is formatted appropriately on the device according to the input format and prepared for transmission to the server.

[0432] Step 2:

[0433] The device captures input data and sends it to the server. The server receives this data and performs text analysis using Google Cloud's Natural Language API or Amazon Comprehend. The analysis generates initial data on the text's content, keywords, and sentiment (e.g., positive, negative, neutral).

[0434] Step 3:

[0435] The server supplies the analyzed text and sentiment data to an emotion recognition model powered by TensorFlow. This step analyzes the user's detailed emotional state and generates specific emotion labels (e.g., fatigue, joy, anxiety). This process generates numerical data from the server indicating which emotions are most strongly expressed.

[0436] Step 4:

[0437] The server generates personalized responses using a generative AI model based on the emotion recognition results. The input includes emotion data and associated contextual information. The AI ​​model uses appropriate prompts to form informative and encouraging messages for the user. The generated responses are sent back to the terminal.

[0438] Step 5:

[0439] The server analyzes sentiment data and selects the most relevant ads for the user. This involves querying a database of ads highly relevant to the user's emotional state. Once ad selection is complete, it prepares to deliver the ads to the user's device via the AdMob SDK.

[0440] Step 6:

[0441] The user's device displays personalized responses and advertisements received from the server. The user can then react to the advertisements or presented responses and provide further input. Continuing this interaction initiates the next processing cycle.

[0442] 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.

[0443] 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.

[0444] 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.

[0445] [Third Embodiment]

[0446] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0447] 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.

[0448] 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).

[0449] 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.

[0450] 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.

[0451] 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).

[0452] 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.

[0453] 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.

[0454] 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.

[0455] 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.

[0456] 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.

[0457] 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".

[0458] This invention is an advertising-supported system that allows users to use an AI agent free of charge. Users can access the AI ​​agent via a terminal, input information, and receive a response. An embodiment thereof is shown below.

[0459] Program Processing Overview

[0460] 1. Information input and reception

[0461] The user inputs questions or instructions to the AI ​​agent on their device. For example, they might enter a request such as, "What's the weather like today?"

[0462] The device sends this information to the server.

[0463] 2. Information Analysis and Response Generation

[0464] The server provides the received information to the AI ​​model, which then generates an appropriate response through natural language processing.

[0465] This process involves accessing external information sources, such as weather databases, to derive accurate answers.

[0466] 3. Providing a response

[0467] The server sends the generated response to the terminal.

[0468] The device displays the result to the user, and the user receives an answer such as, "Today's weather is sunny."

[0469] 4. Selection and display of advertisements

[0470] After a specific action, the server selects relevant advertisements and sends them to the device.

[0471] For example, after a user retrieves weather information, an advertisement for raincoats could be displayed for 30 seconds.

[0472] 5. Linking surveys and advertisements

[0473] Periodically, the server selects which questions to present, and the terminal then displays them to the user.

[0474] When a user answers a survey, that information is sent to the server, and advertisements for related products and services are displayed again.

[0475] 6. System Control

[0476] Once the advertisement finishes displaying, the device will allow you to use the AI ​​agent again.

[0477] Users can continue to use the AI ​​agent's features.

[0478] Thus, the present invention is a system that naturally integrates advertisements without compromising the user experience, while simultaneously providing effective information to advertisers. A specific example is a sequence of events in which, after obtaining a weather forecast, advertisements for related fashion items are displayed, followed by the user's response actions. With this invention, users can effectively accept advertisements while utilizing AI free of charge.

[0479] The following describes the processing flow.

[0480] Step 1:

[0481] The user operates the device and inputs questions and instructions through the AI ​​agent. For example, they might input, "Tell me the weather for tomorrow."

[0482] Step 2:

[0483] The terminal receives this input and sends a request to the server as a digital message. The request contains the user's question.

[0484] Step 3:

[0485] The server receives the request and inputs it into a natural language processing AI model. The AI ​​model analyzes the user's question and accesses the necessary data sources to generate an appropriate response.

[0486] Step 4:

[0487] The server generates a response based on the analysis results. For example, it might generate information such as, "The forecast for tomorrow is sunny."

[0488] Step 5:

[0489] The server sends the generated response to the terminal. The response contains information related to the user's question.

[0490] Step 6:

[0491] The device receives the response and displays the answer to the user on the screen. The user can then review the provided information.

[0492] Step 7:

[0493] The server checks if a specific action has been completed. Once completed, it selects the next ad to display and sends that information to the device.

[0494] Step 8:

[0495] The device displays the received advertisement. Typically, a 30-second video advertisement is played for the user.

[0496] Step 9:

[0497] If the server needs to display surveys periodically, select a survey and send the data to the device.

[0498] Step 10:

[0499] The device displays a survey on its screen and prompts the user to answer the questions.

[0500] Step 11:

[0501] The user answers the survey, and the device sends the results to the server.

[0502] Step 12:

[0503] The server analyzes the received survey responses and selects the most relevant advertisements.

[0504] Step 13:

[0505] The device presents new advertisements to the user based on the analysis results, attracting their interest.

[0506] Step 14:

[0507] After the advertisement is displayed, the device guides the user to resume using the AI ​​agent. The user can then continue entering questions.

[0508] (Example 1)

[0509] 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."

[0510] In conventional information processing systems, it was difficult to balance the display of advertisements with the user experience when users utilized AI agents. Furthermore, the selection of advertisements was inefficient, making it impossible to provide users with relevant advertising information at the appropriate time. Therefore, there is a need to maximize advertising effectiveness without compromising user convenience.

[0511] 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.

[0512] In this invention, the server includes means for receiving information from a user and identifying the relevant information, means for generating a response based on the identified information using natural language processing, and means for selecting and presenting relevant advertisements after a specific action is completed. This enables the display of advertisements effectively and at an appropriate time while providing valuable information to the user.

[0513] "Means for receiving information from users and identifying relevant information" refers to a configuration that has the function of receiving data provided by users using their terminals and performs a process of extracting and recognizing useful information from that data.

[0514] A "natural language processing means for generating responses based on identified information" is a configuration that has the function of creating a response in natural language using an algorithm based on extracted information.

[0515] An "ad selection mechanism that selects and presents relevant advertisements after a specific action is completed" is a mechanism that, after a specific user operation or request is completed, selects advertisements that are highly relevant to that situation and presents them to the user.

[0516] A "data storage means for transmitting user input and storing information" refers to a configuration that has the function of transmitting user input to another system and storing data for later reuse.

[0517] "Information acquisition means that access external information sources to obtain information" refers to a configuration that has a mechanism for connecting to external databases or information provision services to obtain the necessary data.

[0518] "Analytics for presenting survey information to users and selecting relevant advertisements" refers to a configuration that displays questions to users to conduct a survey and has an analytical function that determines the most suitable advertisement based on their answers.

[0519] "Means of operation that allow the use of agent functions to be resumed after ad presentation" refers to a configuration that provides a procedure for the user to perform an action that allows them to use the AI ​​agent functions again after an ad has been displayed.

[0520] This invention is a system that allows users to naturally experience advertisements while obtaining information by utilizing an AI agent free of charge. This system operates through the cooperation of three parties: the user, the device, and the server.

[0521] Users can access the AI ​​agent via devices such as computers and smartphones. The device receives information entered by the user and sends it to the server. The communication technology used is a common internet protocol (e.g., HTTPS) to maintain a stable connection.

[0522] The server analyzes the received information and generates appropriate responses using natural language processing. This process includes querying external databases (e.g., publicly available weather information APIs). The program, built with a generative AI model, is designed to answer user questions quickly and accurately.

[0523] After generating a response, the server sends the result back to the terminal, which then visually presents the information to the user. The server also selects relevant advertisements based on the user's actions and displays them on the terminal. This allows users to receive both useful information and engaging advertisements.

[0524] As a concrete example, if a user enters a prompt such as "What's the weather like today?", the system first sends that information to the server. The server uses an AI model to analyze the weather data and generate a response. After the response is displayed to the user, advertisements for products related to that information (for example, umbrella advertisements) are presented.

[0525] In this way, users, devices, and servers each play their respective roles and work together to provide users with a practical and engaging experience.

[0526] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0527] Step 1:

[0528] The user connects to the AI ​​agent through their device and inputs information. The input is in the form of text-based prompts, such as "What's the weather like today?". This input is recognized as digital data by the device and sent to the server.

[0529] Step 2:

[0530] The server receives information sent from the terminal. Based on this received data, the server passes prompt sentences to the generative AI model. Natural language processing techniques are used here to perform semantic analysis of the input data and generate appropriate responses. The server accesses external information sources, such as weather databases, as needed to obtain accurate information.

[0531] Step 3:

[0532] The server uses an AI model to generate responses. This generation process employs natural language algorithms to construct context-aware answers. For example, a specific response such as "Today's weather is sunny" is generated. This response data is then sent to the terminal.

[0533] Step 4:

[0534] The terminal displays the response received from the server to the user. This display is provided as visual text information based on the terminal's interface. This allows the user to easily obtain the information they are looking for.

[0535] Step 5:

[0536] After completing a specific action based on the user's request, the server initiates a process to select relevant advertisements. Using AI technology, the most suitable advertisements are chosen based on the user's interests and browsing history. For example, advertisements for outdoor equipment related to sunny days may be selected.

[0537] Step 6:

[0538] Selected advertisements are sent from the server to the device, which then displays the advertisement to the user. The advertisements are set to be displayed for a set period of time, and the process proceeds to the next step after detecting the end of the advertisement. This process ensures that advertisers receive effective information.

[0539] Step 7:

[0540] After the advertisement finishes displaying, the device allows the AI ​​agent to access it again. This action allows the user to continue using the system without interruption. The system is then ready to repeat the same process for any further input from the user.

[0541] (Application Example 1)

[0542] 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."

[0543] In today's world, e-commerce is rapidly expanding, allowing consumers to easily purchase a wide variety of goods and services. However, consumers often struggle to receive timely and relevant promotional information and benefits when making payments. As a result, they may miss out on available discounts and coupons, hindering increased consumer satisfaction. Businesses also face challenges, such as insufficient timely provision of promotional information, leading to missed opportunities for increased sales.

[0544] 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.

[0545] In this invention, the server includes a response generation means that provides relevant sales promotion information based on payment data, a reward calculation means that calculates and displays reward information for the next use, and a control means that allows the user to resume using the agent after the advertisement is displayed. This enables consumers to instantly receive relevant sales promotion information and rewards for the next use when they make a payment, and to smoothly continue using the AI ​​agent's functions after smoothly reviewing the advertisement.

[0546] "Means for receiving information from users and identifying the relevant information" refers to a function that accurately receives information entered by the user from a terminal and identifies what that information means.

[0547] "Artificial intelligence processing means for generating a response based on identified information" refers to an AI-based process for creating an appropriate response based on identified information.

[0548] An "ad display method that displays ads after a specific action is completed" is a function that displays relevant ads at the point when a user's action has come to a close.

[0549] A "data storage method that transitions user input and saves information" is a system that saves data entered by a user while transitioning that data to a different screen or step.

[0550] "Response generation means that provides relevant sales promotion information based on payment data" refers to a process that analyzes a user's payment information and provides relevant sales promotion information.

[0551] The "reward calculation means for calculating and displaying reward information for the next use" is a function that calculates the content of the rewards that will be applied on the next use and displays the results in an easy-to-understand manner for the user.

[0552] "Control measures that allow the user to resume using the agent after the ad has been displayed" refers to a system that allows the user to use the AI ​​agent again without any problems after the ad display has finished.

[0553] To implement this invention, it is first necessary to construct a system for sending and receiving data between a server and a user terminal. The server is equipped with means for receiving information from the user and appropriately identifying it. Specifically, the user inputs questions or instructions via a user terminal such as a smartphone or tablet, and that data is sent to the server.

[0554] The server generates a response using an AI model based on the identified information. This process utilizes a generative AI model, such as OpenAI's GPT, as its natural language processing engine. This AI model has the ability to analyze the received data and generate responses tailored to user needs and relevant promotional information in real time.

[0555] Next, after the user completes a specific action, the server uses advertising means to display relevant advertisements on the user's device. After the advertisements are displayed, the user can use the AI ​​agent again. Here, it is required that the advertisements are displayed smoothly and that subsequent operations continue seamlessly so as not to disrupt the user experience.

[0556] For data storage, a cloud database such as Firebase is used. By properly transferring and saving user input history and payment information, reward information can be calculated and presented to the user upon their next use. A reward calculation method is used for this calculation, generating specific preferential information such as coupons and discounts.

[0557] For example, after a user pays at a restaurant, if they ask the AI ​​agent, "Are there any promotions?", the server will generate the most suitable coupons and benefits for future visits and display them immediately on the terminal. An example of a prompt used by the server in this process would be, "I am paying for the meal at the store specified by the user. Please have the AI ​​agent generate the latest promotional coupons for this payment." This allows users to quickly obtain relevant information, not only improving satisfaction but also helping businesses increase sales.

[0558] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0559] Step 1:

[0560] The user inputs questions or instructions to the AI ​​agent from their device. For example, the user might ask, "Are there any campaigns?" This input is received by the device and sent to the server. The input data is transferred to the server in string format and processed as a request.

[0561] Step 2:

[0562] The server analyzes the user's question received. During this process, natural language processing is performed using OpenAI's GPT generative AI model. The AI ​​agent analyzes the input data and converts the information into a structured data format to understand the user's needs. As a result, it determines what kind of sales promotion information is appropriate.

[0563] Step 3:

[0564] The server retrieves relevant sales promotion information from the database based on the analysis results. It uses Firebase to search payment history and campaign information, identifying suitable coupons and offers. This allows the generative AI model to prepare output data to provide the most useful information to the user.

[0565] Step 4:

[0566] The server sends the generated response and advertising information to the user's device. The offer information and advertisements are displayed on the user's device for the user to review. The output data includes coupon codes and conditions for using the offers.

[0567] Step 5:

[0568] The device displays special offers and advertisements to the user. The user reviews the presented information and, if necessary, follows the on-screen instructions to take further action. Once the advertisement review is complete, the user can continue to use the AI ​​agent's features.

[0569] Step 6:

[0570] When a user receives a reward for their next visit, the server saves that information to a database. This updates the user's usage history and ensures that the reward is applied to their next transaction. The prompt used included the following: "I will pay the fee at the store specified by the user. Please have the AI ​​agent generate the latest promotional coupon for this payment."

[0571] 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.

[0572] This invention relates to an AI agent system that incorporates an emotion engine that recognizes user emotions and adjusts responses accordingly. This system has the function of automatically generating responses based on user input and displaying appropriate advertisements at the time a specific action is completed. Furthermore, it includes a control function that seamlessly maintains user interaction so that the AI ​​agent can continue to be used even after the advertisement is displayed.

[0573] The system consists of a terminal, a server, and an emotion engine. First, the user inputs information via the terminal and interacts with an AI agent. The terminal relays this input to the server, which, in the process of generating a response through its AI processor, also takes the user's emotions into consideration.

[0574] The emotion engine analyzes the user's voice, text, and biometric data to determine their current emotional state. For example, if it detects signs of anxiety, it generates an encouraging message to address that. This emotional data is stored and used in future interactions.

[0575] For example, if a user uses their device to tell the agent, "I'm worried about preparing my presentation," the emotion engine will detect the user's anxiety and the server will respond with an encouraging suggestion such as, "Shall I help you with your preparation?" Then, at an appropriate time, advertisements for presentation-related tools and books will be displayed.

[0576] In this way, by understanding the user's emotional state in real time, it becomes possible to provide personalized responses and select advertisements, thereby improving the quality of the user experience. By incorporating emotion recognition, the effectiveness of advertisements is also increased, and more efficient promotional results can be expected.

[0577] The following describes the processing flow.

[0578] Step 1:

[0579] The user enters a message into the AI ​​agent via their device. For example, they might send something like, "I'm feeling down today."

[0580] Step 2:

[0581] The terminal receives input from the user and sends that data to the server. The message contains text information.

[0582] Step 3:

[0583] The server passes the received data to the emotion engine for analysis. This process determines what emotions the user's text is associated with.

[0584] Step 4:

[0585] The emotion engine processes the data and determines that the user is feeling "depressed." Based on this, it instructs the AI ​​model to generate an appropriate response.

[0586] Step 5:

[0587] The server uses an AI model to generate responses that are appropriate to the user's emotions. For example, it might generate a response like, "Shall we take a break and relax today?"

[0588] Step 6:

[0589] The server sends the generated response to the terminal and displays it to the user. The user receives the support message through the screen.

[0590] Step 7:

[0591] The server then enters a process to select ads that match the user's emotions. It considers emotional data and, for example, associates ads for relaxation products.

[0592] Step 8:

[0593] The device receives advertising data and displays ads to the user at the appropriate time. Afterwards, it can return to the AI ​​agent.

[0594] Step 9:

[0595] The device waits for user input again and allows the AI ​​agent function to resume. The user can continue using the service.

[0596] This system enables emotion-responsive responses and ad presentations, allowing users to receive personalized support.

[0597] (Example 2)

[0598] 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."

[0599] Current artificial intelligence systems suffer from inconsistent user experiences due to their insufficient accuracy in responding to user emotions. Furthermore, frequent interruptions to user interaction due to advertisements hinder continued use. Additionally, ad selection is often not optimized based on user emotions or states, resulting in limited effectiveness.

[0600] 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.

[0601] In this invention, the server includes an analysis means for analyzing the user's emotional state, a generation means for generating a response based on the analyzed emotional state, and a display means for displaying guidance information after a specific task is completed. This allows for the provision of customized responses tailored to the user's emotions, and enables the display of advertisements at the optimal timing without disrupting the user's continuity.

[0602] A "receiving means" is an interface for acquiring information from the user and incorporating it into the system.

[0603] "Intelligent processing means" refers to an algorithm that performs predetermined processing based on identified information.

[0604] "Analysis means" refers to a software or hardware mechanism for analyzing a user's emotional state.

[0605] A "generative means" is a process that has the function of producing a response based on the analyzed emotional state.

[0606] "Display means" refers to a device or screen that visually shows guidance information to the user after a specific task has been completed.

[0607] A "retention mechanism" refers to a data storage system for managing user information, storing it in an appropriate format, and managing its transitions.

[0608] This invention is an artificial intelligence agent system that analyzes a user's emotions in real time and provides personalized responses based on that analysis. The system consists mainly of a terminal, a server, and an emotion analysis engine. A specific embodiment of the system is described below.

[0609] First, the user inputs information into the AI ​​agent in natural language via a device. This device can be a smartphone or computer, and the input is provided as text or voice. In the case of voice input, the device uses speech recognition software to convert the voice into text.

[0610] The input information is sent to the server. The server uses an emotion analysis engine to recognize the user's emotional state from the input information. This analysis uses emotion recognition software that leverages natural language processing technology. Based on the results, a generative AI model generates the optimal response.

[0611] In conjunction with response generation, the server selects relevant advertisements after a specific task is completed and sends them to the device. For example, if a user enters "I'm anxious about moving to a new city," the sentiment analysis engine detects the anxiety, and the generative AI model generates a response such as "A new adventure is about to begin, shall we help?" Simultaneously, an advertisement for a moving service is appropriately displayed.

[0612] As an example of a prompt, the following input could be given to the generative AI model: "Analyze the user's emotions and suggest a response based on those emotions. User input: 'I'm worried about preparing my presentation.'"

[0613] In this way, the system improves the quality of the user experience by providing customized responses and advertisements that respond to the user's emotions.

[0614] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0615] Step 1:

[0616] The user inputs information in natural language via the terminal. This input is provided as either text or voice. In the case of voice input, the terminal converts the voice data into text data using speech recognition software. The output of the input is data in text format.

[0617] Step 2:

[0618] The terminal sends the converted text data to the server. The server receives this data and activates an emotion analysis engine to analyze the user's emotional state. The emotion analysis engine uses natural language processing techniques to extract emotional features from the text data, and the output is the user's emotional state (e.g., anxiety, joy).

[0619] Step 3:

[0620] The server passes the user's emotional state as input to a generative AI model. The generative AI model uses prompts to generate the optimal response corresponding to the emotion. This process employs an algorithm that generates text responses while considering the emotional state. The generated response is the output.

[0621] Step 4:

[0622] The server selects advertisements that are appropriate to the user's context, along with the generated response. The selection of advertisements takes into account the user's emotions and the progress of the conversation. The output is the selection of appropriate advertisements.

[0623] Step 5:

[0624] The device displays the response received from the server along with advertisements. The user can then interact with the agent again based on this information. The display serves to maintain a seamless interaction with the user.

[0625] (Application Example 2)

[0626] 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."

[0627] In modern information processing systems, recognizing a user's emotional state in real time and providing personalized information and selecting advertisements based on that understanding is crucial for improving the user experience. However, conventional systems struggle to generate dynamic responses in response to changes in user emotions and to select advertisements based on those emotions. Therefore, there is a need for technologies that enable personalized information provision and efficient advertisement selection that take user emotions into consideration, while ensuring seamless interaction.

[0628] 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.

[0629] In this invention, the server includes means for receiving information from the user and analyzing their emotional state, means for generating and personalizing a response based on the analysis results, and means for displaying advertisements corresponding to the analyzed emotional state. This enables responses and advertisements based on the user's emotions, thereby improving the quality of interaction.

[0630] "Means for receiving information from users and identifying relevant information" refers to technologies for collecting user-provided input data in real time and identifying the content and type of that data.

[0631] "An artificial intelligence processing means for generating responses based on identified information and analyzing the user's emotional state" refers to a technology that includes an algorithm for creating an appropriate response based on identified input data and for estimating the user's emotions.

[0632] "An advertising display method that selects and displays appropriate advertisements based on analyzed emotional states" refers to a technology that selects highly relevant advertisements based on the results of emotional analysis and displays them to the user at the appropriate time.

[0633] "A data storage method that processes user input and saves information" refers to database technology for appropriately structuring and continuously storing data obtained from users.

[0634] "Means for personalizing responses based on analyzed emotional states" refers to a system or method for designing appropriate and specific response content according to each user's emotions.

[0635] "Control mechanisms that allow seamless resumption of agent use" are mechanisms that enable smooth resumption of interaction without disrupting the user experience after an advertisement is displayed or a conversation is interrupted.

[0636] To implement this invention, it is necessary to construct a system including a server, a terminal, and an artificial intelligence agent. This system provides an environment in which user input is captured, emotions are recognized, and personalized advertisements are displayed.

[0637] The device is responsible for collecting voice and text data from the user. This data is sent to the server via natural language processing software such as Google Cloud's Natural Language API or Amazon Comprehend. The server analyzes the user's emotional state using an emotion recognition model based on TensorFlow.

[0638] Based on an analysis of the user's emotional state, the server generates a response. This response is personalized, taking emotional data into consideration, and designed to deepen the user interaction. Furthermore, the analysis results are used as the basis for displaying advertisements, presenting the ads most relevant to the user via the AdMob SDK and other means.

[0639] For example, if a user says, "I'm a little tired," the emotion engine will generate a stress-reducing response and naturally display advertisements for products and services that help users relax at work. Through such interactions, users can receive information that matches their emotions, thus forming a positive impression of the advertisements.

[0640] An example of a prompt message is: "The user has reported fatigue, so provide information about relaxation and display appropriate advertisements." This allows you to give instructions to the generative AI model, enabling dynamic interactions that optimize the user experience.

[0641] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0642] Step 1:

[0643] The user provides input via voice or text through the device. This input is captured by the device and prepared as initial data. The input data is formatted appropriately on the device according to the input format and prepared for transmission to the server.

[0644] Step 2:

[0645] The device captures input data and sends it to the server. The server receives this data and performs text analysis using Google Cloud's Natural Language API or Amazon Comprehend. The analysis generates initial data on the text's content, keywords, and sentiment (e.g., positive, negative, neutral).

[0646] Step 3:

[0647] The server supplies the analyzed text and sentiment data to an emotion recognition model powered by TensorFlow. This step analyzes the user's detailed emotional state and generates specific emotion labels (e.g., fatigue, joy, anxiety). This process generates numerical data from the server indicating which emotions are most strongly expressed.

[0648] Step 4:

[0649] The server generates personalized responses using a generative AI model based on the emotion recognition results. The input includes emotion data and associated contextual information. The AI ​​model uses appropriate prompts to form informative and encouraging messages for the user. The generated responses are sent back to the terminal.

[0650] Step 5:

[0651] The server analyzes sentiment data and selects the most relevant ads for the user. This involves querying a database of ads highly relevant to the user's emotional state. Once ad selection is complete, it prepares to deliver the ads to the user's device via the AdMob SDK.

[0652] Step 6:

[0653] The user's device displays personalized responses and advertisements received from the server. The user can then react to the advertisements or presented responses and provide further input. Continuing this interaction initiates the next processing cycle.

[0654] 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.

[0655] 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.

[0656] 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.

[0657] [Fourth Embodiment]

[0658] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0659] 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.

[0660] 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).

[0661] 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.

[0662] 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.

[0663] 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).

[0664] 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.

[0665] 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.

[0666] 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.

[0667] 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.

[0668] 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.

[0669] 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.

[0670] 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".

[0671] This invention is an advertising-supported system that allows users to use an AI agent free of charge. Users can access the AI ​​agent via a terminal, input information, and receive a response. An embodiment thereof is shown below.

[0672] Program Processing Overview

[0673] 1. Information input and reception

[0674] The user inputs questions or instructions to the AI ​​agent on their device. For example, they might enter a request such as, "What's the weather like today?"

[0675] The device sends this information to the server.

[0676] 2. Information Analysis and Response Generation

[0677] The server provides the received information to the AI ​​model, which then generates an appropriate response through natural language processing.

[0678] This process involves accessing external information sources, such as weather databases, to derive accurate answers.

[0679] 3. Providing a response

[0680] The server sends the generated response to the terminal.

[0681] The device displays the result to the user, and the user receives an answer such as, "Today's weather is sunny."

[0682] 4. Selection and display of advertisements

[0683] After a specific action, the server selects relevant advertisements and sends them to the device.

[0684] For example, after a user retrieves weather information, an advertisement for raincoats could be displayed for 30 seconds.

[0685] 5. Linking surveys and advertisements

[0686] Periodically, the server selects which questions to present, and the terminal then displays them to the user.

[0687] When a user answers a survey, that information is sent to the server, and advertisements for related products and services are displayed again.

[0688] 6. System Control

[0689] Once the advertisement finishes displaying, the device will allow you to use the AI ​​agent again.

[0690] Users can continue to use the AI ​​agent's features.

[0691] Thus, the present invention is a system that naturally integrates advertisements without compromising the user experience, while simultaneously providing effective information to advertisers. A specific example is a sequence of events in which, after obtaining a weather forecast, advertisements for related fashion items are displayed, followed by the user's response actions. With this invention, users can effectively accept advertisements while utilizing AI free of charge.

[0692] The following describes the processing flow.

[0693] Step 1:

[0694] The user operates the device and inputs questions and instructions through the AI ​​agent. For example, they might input, "Tell me the weather for tomorrow."

[0695] Step 2:

[0696] The terminal receives this input and sends a request to the server as a digital message. The request contains the user's question.

[0697] Step 3:

[0698] The server receives the request and inputs it into a natural language processing AI model. The AI ​​model analyzes the user's question and accesses the necessary data sources to generate an appropriate response.

[0699] Step 4:

[0700] The server generates a response based on the analysis results. For example, it might generate information such as, "The forecast for tomorrow is sunny."

[0701] Step 5:

[0702] The server sends the generated response to the terminal. The response contains information related to the user's question.

[0703] Step 6:

[0704] The device receives the response and displays the answer to the user on the screen. The user can then review the provided information.

[0705] Step 7:

[0706] The server checks if a specific action has been completed. Once completed, it selects the next ad to display and sends that information to the device.

[0707] Step 8:

[0708] The device displays the received advertisement. Typically, a 30-second video advertisement is played for the user.

[0709] Step 9:

[0710] If the server needs to display surveys periodically, select a survey and send the data to the device.

[0711] Step 10:

[0712] The device displays a survey on its screen and prompts the user to answer the questions.

[0713] Step 11:

[0714] The user answers the survey, and the device sends the results to the server.

[0715] Step 12:

[0716] The server analyzes the received survey responses and selects the most relevant advertisements.

[0717] Step 13:

[0718] The device presents new advertisements to the user based on the analysis results, attracting their interest.

[0719] Step 14:

[0720] After the advertisement is displayed, the device guides the user to resume using the AI ​​agent. The user can then continue entering questions.

[0721] (Example 1)

[0722] 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".

[0723] In conventional information processing systems, it was difficult to balance the display of advertisements with the user experience when users utilized AI agents. Furthermore, the selection of advertisements was inefficient, making it impossible to provide users with relevant advertising information at the appropriate time. Therefore, there is a need to maximize advertising effectiveness without compromising user convenience.

[0724] 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.

[0725] In this invention, the server includes means for receiving information from a user and identifying the relevant information, means for generating a response based on the identified information using natural language processing, and means for selecting and presenting relevant advertisements after a specific action is completed. This enables the display of advertisements effectively and at an appropriate time while providing valuable information to the user.

[0726] "Means for receiving information from users and identifying relevant information" refers to a configuration that has the function of receiving data provided by users using their terminals and performs a process of extracting and recognizing useful information from that data.

[0727] A "natural language processing means for generating responses based on identified information" is a configuration that has the function of creating a response in natural language using an algorithm based on extracted information.

[0728] An "ad selection mechanism that selects and presents relevant advertisements after a specific action is completed" is a mechanism that, after a specific user operation or request is completed, selects advertisements that are highly relevant to that situation and presents them to the user.

[0729] A "data storage means for transmitting user input and storing information" refers to a configuration that has the function of transmitting user input to another system and storing data for later reuse.

[0730] "Information acquisition means that access external information sources to obtain information" refers to a configuration that has a mechanism for connecting to external databases or information provision services to obtain the necessary data.

[0731] "Analytics for presenting survey information to users and selecting relevant advertisements" refers to a configuration that displays questions to users to conduct a survey and has an analytical function that determines the most suitable advertisement based on their answers.

[0732] "Means of operation that allow the use of agent functions to be resumed after ad presentation" refers to a configuration that provides a procedure for the user to perform an action that allows them to use the AI ​​agent functions again after an ad has been displayed.

[0733] This invention is a system that allows users to naturally experience advertisements while obtaining information by utilizing an AI agent free of charge. This system operates through the cooperation of three parties: the user, the device, and the server.

[0734] Users can access the AI ​​agent via devices such as computers and smartphones. The device receives information entered by the user and sends it to the server. The communication technology used is a common internet protocol (e.g., HTTPS) to maintain a stable connection.

[0735] The server analyzes the received information and generates appropriate responses using natural language processing. This process includes querying external databases (e.g., publicly available weather information APIs). The program, built with a generative AI model, is designed to answer user questions quickly and accurately.

[0736] After generating a response, the server sends the result back to the terminal, which then visually presents the information to the user. The server also selects relevant advertisements based on the user's actions and displays them on the terminal. This allows users to receive both useful information and engaging advertisements.

[0737] As a concrete example, if a user enters a prompt such as "What's the weather like today?", the system first sends that information to the server. The server uses an AI model to analyze the weather data and generate a response. After the response is displayed to the user, advertisements for products related to that information (for example, umbrella advertisements) are presented.

[0738] In this way, users, devices, and servers each play their respective roles and work together to provide users with a practical and engaging experience.

[0739] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0740] Step 1:

[0741] The user connects to the AI ​​agent through their device and inputs information. The input is in the form of text-based prompts, such as "What's the weather like today?". This input is recognized as digital data by the device and sent to the server.

[0742] Step 2:

[0743] The server receives information sent from the terminal. Based on this received data, the server passes prompt sentences to the generative AI model. Natural language processing techniques are used here to perform semantic analysis of the input data and generate appropriate responses. The server accesses external information sources, such as weather databases, as needed to obtain accurate information.

[0744] Step 3:

[0745] The server uses an AI model to generate responses. This generation process employs natural language algorithms to construct context-aware answers. For example, a specific response such as "Today's weather is sunny" is generated. This response data is then sent to the terminal.

[0746] Step 4:

[0747] The terminal displays the response received from the server to the user. This display is provided as visual text information based on the terminal's interface. This allows the user to easily obtain the information they are looking for.

[0748] Step 5:

[0749] After completing a specific action based on the user's request, the server initiates a process to select relevant advertisements. Using AI technology, the most suitable advertisements are chosen based on the user's interests and browsing history. For example, advertisements for outdoor equipment related to sunny days may be selected.

[0750] Step 6:

[0751] Selected advertisements are sent from the server to the device, which then displays the advertisement to the user. The advertisements are set to be displayed for a set period of time, and the process proceeds to the next step after detecting the end of the advertisement. This process ensures that advertisers receive effective information.

[0752] Step 7:

[0753] After the advertisement finishes displaying, the device allows the AI ​​agent to access it again. This action allows the user to continue using the system without interruption. The system is then ready to repeat the same process for any further input from the user.

[0754] (Application Example 1)

[0755] 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".

[0756] In today's world, e-commerce is rapidly expanding, allowing consumers to easily purchase a wide variety of goods and services. However, consumers often struggle to receive timely and relevant promotional information and benefits when making payments. As a result, they may miss out on available discounts and coupons, hindering increased consumer satisfaction. Businesses also face challenges, such as insufficient timely provision of promotional information, leading to missed opportunities for increased sales.

[0757] 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.

[0758] In this invention, the server includes a response generation means that provides relevant sales promotion information based on payment data, a reward calculation means that calculates and displays reward information for the next use, and a control means that allows the user to resume using the agent after the advertisement is displayed. This enables consumers to instantly receive relevant sales promotion information and rewards for the next use when they make a payment, and to smoothly continue using the AI ​​agent's functions after smoothly reviewing the advertisement.

[0759] "Means for receiving information from users and identifying the relevant information" refers to a function that accurately receives information entered by the user from a terminal and identifies what that information means.

[0760] "Artificial intelligence processing means for generating a response based on identified information" refers to an AI-based process for creating an appropriate response based on identified information.

[0761] An "ad display method that displays ads after a specific action is completed" is a function that displays relevant ads at the point when a user's action has come to a close.

[0762] A "data storage method that transitions user input and saves information" is a system that saves data entered by a user while transitioning that data to a different screen or step.

[0763] "Response generation means that provides relevant sales promotion information based on payment data" refers to a process that analyzes a user's payment information and provides relevant sales promotion information.

[0764] The "reward calculation means for calculating and displaying reward information for the next use" is a function that calculates the content of the rewards that will be applied on the next use and displays the results in an easy-to-understand manner for the user.

[0765] "Control measures that allow the user to resume using the agent after the ad has been displayed" refers to a system that allows the user to use the AI ​​agent again without any problems after the ad display has finished.

[0766] To implement this invention, it is first necessary to construct a system for sending and receiving data between a server and a user terminal. The server is equipped with means for receiving information from the user and appropriately identifying it. Specifically, the user inputs questions or instructions via a user terminal such as a smartphone or tablet, and that data is sent to the server.

[0767] The server generates a response using an AI model based on the identified information. This process utilizes a generative AI model, such as OpenAI's GPT, as its natural language processing engine. This AI model has the ability to analyze the received data and generate responses tailored to user needs and relevant promotional information in real time.

[0768] Next, after the user completes a specific action, the server uses advertising means to display relevant advertisements on the user's device. After the advertisements are displayed, the user can use the AI ​​agent again. Here, it is required that the advertisements are displayed smoothly and that subsequent operations continue seamlessly so as not to disrupt the user experience.

[0769] For data storage, a cloud database such as Firebase is used. By properly transferring and saving user input history and payment information, reward information can be calculated and presented to the user upon their next use. A reward calculation method is used for this calculation, generating specific preferential information such as coupons and discounts.

[0770] For example, after a user pays at a restaurant, if they ask the AI ​​agent, "Are there any promotions?", the server will generate the most suitable coupons and benefits for future visits and display them immediately on the terminal. An example of a prompt used by the server in this process would be, "I am paying for the meal at the store specified by the user. Please have the AI ​​agent generate the latest promotional coupons for this payment." This allows users to quickly obtain relevant information, not only improving satisfaction but also helping businesses increase sales.

[0771] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0772] Step 1:

[0773] The user inputs questions or instructions to the AI ​​agent from their device. For example, the user might ask, "Are there any campaigns?" This input is received by the device and sent to the server. The input data is transferred to the server in string format and processed as a request.

[0774] Step 2:

[0775] The server analyzes the user's question received. During this process, natural language processing is performed using OpenAI's GPT generative AI model. The AI ​​agent analyzes the input data and converts the information into a structured data format to understand the user's needs. As a result, it determines what kind of sales promotion information is appropriate.

[0776] Step 3:

[0777] The server retrieves relevant sales promotion information from the database based on the analysis results. It uses Firebase to search payment history and campaign information, identifying suitable coupons and offers. This allows the generative AI model to prepare output data to provide the most useful information to the user.

[0778] Step 4:

[0779] The server sends the generated response and advertising information to the user's device. The offer information and advertisements are displayed on the user's device for the user to review. The output data includes coupon codes and conditions for using the offers.

[0780] Step 5:

[0781] The device displays special offers and advertisements to the user. The user reviews the presented information and, if necessary, follows the on-screen instructions to take further action. Once the advertisement review is complete, the user can continue to use the AI ​​agent's features.

[0782] Step 6:

[0783] When a user receives a reward for their next visit, the server saves that information to a database. This updates the user's usage history and ensures that the reward is applied to their next transaction. The prompt used included the following: "I will pay the fee at the store specified by the user. Please have the AI ​​agent generate the latest promotional coupon for this payment."

[0784] 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.

[0785] This invention relates to an AI agent system that incorporates an emotion engine that recognizes user emotions and adjusts responses accordingly. This system has the function of automatically generating responses based on user input and displaying appropriate advertisements at the time a specific action is completed. Furthermore, it includes a control function that seamlessly maintains user interaction so that the AI ​​agent can continue to be used even after the advertisement is displayed.

[0786] The system consists of a terminal, a server, and an emotion engine. First, the user inputs information via the terminal and interacts with an AI agent. The terminal relays this input to the server, which, in the process of generating a response through its AI processor, also takes the user's emotions into consideration.

[0787] The emotion engine analyzes the user's voice, text, and biometric data to determine their current emotional state. For example, if it detects signs of anxiety, it generates an encouraging message to address that. This emotional data is stored and used in future interactions.

[0788] For example, if a user uses their device to tell the agent, "I'm worried about preparing my presentation," the emotion engine will detect the user's anxiety and the server will respond with an encouraging suggestion such as, "Shall I help you with your preparation?" Then, at an appropriate time, advertisements for presentation-related tools and books will be displayed.

[0789] In this way, by understanding the user's emotional state in real time, it becomes possible to provide personalized responses and select advertisements, thereby improving the quality of the user experience. By incorporating emotion recognition, the effectiveness of advertisements is also increased, and more efficient promotional results can be expected.

[0790] The following describes the processing flow.

[0791] Step 1:

[0792] The user enters a message into the AI ​​agent via their device. For example, they might send something like, "I'm feeling down today."

[0793] Step 2:

[0794] The terminal receives input from the user and sends that data to the server. The message contains text information.

[0795] Step 3:

[0796] The server passes the received data to the emotion engine for analysis. This process determines what emotions the user's text is associated with.

[0797] Step 4:

[0798] The emotion engine processes the data and determines that the user is feeling "depressed." Based on this, it instructs the AI ​​model to generate an appropriate response.

[0799] Step 5:

[0800] The server uses an AI model to generate responses that are appropriate to the user's emotions. For example, it might generate a response like, "Shall we take a break and relax today?"

[0801] Step 6:

[0802] The server sends the generated response to the terminal and displays it to the user. The user receives the support message through the screen.

[0803] Step 7:

[0804] The server then enters a process to select ads that match the user's emotions. It considers emotional data and, for example, associates ads for relaxation products.

[0805] Step 8:

[0806] The device receives advertising data and displays ads to the user at the appropriate time. Afterwards, it can return to the AI ​​agent.

[0807] Step 9:

[0808] The device waits for user input again and allows the AI ​​agent function to resume. The user can continue using the service.

[0809] This system enables emotion-responsive responses and ad presentations, allowing users to receive personalized support.

[0810] (Example 2)

[0811] 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".

[0812] Current artificial intelligence systems suffer from inconsistent user experiences due to their insufficient accuracy in responding to user emotions. Furthermore, frequent interruptions to user interaction due to advertisements hinder continued use. Additionally, ad selection is often not optimized based on user emotions or states, resulting in limited effectiveness.

[0813] 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.

[0814] In this invention, the server includes an analysis means for analyzing the user's emotional state, a generation means for generating a response based on the analyzed emotional state, and a display means for displaying guidance information after a specific task is completed. This allows for the provision of customized responses tailored to the user's emotions, and enables the display of advertisements at the optimal timing without disrupting the user's continuity.

[0815] A "receiving means" is an interface for acquiring information from the user and incorporating it into the system.

[0816] "Intelligent processing means" refers to an algorithm that performs predetermined processing based on identified information.

[0817] "Analysis means" refers to a software or hardware mechanism for analyzing a user's emotional state.

[0818] A "generative means" is a process that has the function of producing a response based on the analyzed emotional state.

[0819] "Display means" refers to a device or screen that visually shows guidance information to the user after a specific task has been completed.

[0820] A "retention mechanism" refers to a data storage system for managing user information, storing it in an appropriate format, and managing its transitions.

[0821] This invention is an artificial intelligence agent system that analyzes a user's emotions in real time and provides personalized responses based on that analysis. The system consists mainly of a terminal, a server, and an emotion analysis engine. A specific embodiment of the system is described below.

[0822] First, the user inputs information into the AI ​​agent in natural language via a device. This device can be a smartphone or computer, and the input is provided as text or voice. In the case of voice input, the device uses speech recognition software to convert the voice into text.

[0823] The input information is sent to the server. The server uses an emotion analysis engine to recognize the user's emotional state from the input information. This analysis uses emotion recognition software that leverages natural language processing technology. Based on the results, a generative AI model generates the optimal response.

[0824] In conjunction with response generation, the server selects relevant advertisements after a specific task is completed and sends them to the device. For example, if a user enters "I'm anxious about moving to a new city," the sentiment analysis engine detects the anxiety, and the generative AI model generates a response such as "A new adventure is about to begin, shall we help?" Simultaneously, an advertisement for a moving service is appropriately displayed.

[0825] As an example of a prompt, the following input could be given to the generative AI model: "Analyze the user's emotions and suggest a response based on those emotions. User input: 'I'm worried about preparing my presentation.'"

[0826] In this way, the system improves the quality of the user experience by providing customized responses and advertisements that respond to the user's emotions.

[0827] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0828] Step 1:

[0829] The user inputs information in natural language via the terminal. This input is provided as either text or voice. In the case of voice input, the terminal converts the voice data into text data using speech recognition software. The output of the input is data in text format.

[0830] Step 2:

[0831] The terminal sends the converted text data to the server. The server receives this data and activates an emotion analysis engine to analyze the user's emotional state. The emotion analysis engine uses natural language processing techniques to extract emotional features from the text data, and the output is the user's emotional state (e.g., anxiety, joy).

[0832] Step 3:

[0833] The server passes the user's emotional state as input to a generative AI model. The generative AI model uses prompts to generate the optimal response corresponding to the emotion. This process employs an algorithm that generates text responses while considering the emotional state. The generated response is the output.

[0834] Step 4:

[0835] The server selects advertisements that are appropriate to the user's context, along with the generated response. The selection of advertisements takes into account the user's emotions and the progress of the conversation. The output is the selection of appropriate advertisements.

[0836] Step 5:

[0837] The device displays the response received from the server along with advertisements. The user can then interact with the agent again based on this information. The display serves to maintain a seamless interaction with the user.

[0838] (Application Example 2)

[0839] 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".

[0840] In modern information processing systems, recognizing a user's emotional state in real time and providing personalized information and selecting advertisements based on that understanding is crucial for improving the user experience. However, conventional systems struggle to generate dynamic responses in response to changes in user emotions and to select advertisements based on those emotions. Therefore, there is a need for technologies that enable personalized information provision and efficient advertisement selection that take user emotions into consideration, while ensuring seamless interaction.

[0841] 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.

[0842] In this invention, the server includes means for receiving information from the user and analyzing their emotional state, means for generating and personalizing a response based on the analysis results, and means for displaying advertisements corresponding to the analyzed emotional state. This enables responses and advertisements based on the user's emotions, thereby improving the quality of interaction.

[0843] "Means for receiving information from users and identifying relevant information" refers to technologies for collecting user-provided input data in real time and identifying the content and type of that data.

[0844] "An artificial intelligence processing means for generating responses based on identified information and analyzing the user's emotional state" refers to a technology that includes an algorithm for creating an appropriate response based on identified input data and for estimating the user's emotions.

[0845] "An advertising display method that selects and displays appropriate advertisements based on analyzed emotional states" refers to a technology that selects highly relevant advertisements based on the results of emotional analysis and displays them to the user at the appropriate time.

[0846] "A data storage method that processes user input and saves information" refers to database technology for appropriately structuring and continuously storing data obtained from users.

[0847] "Means for personalizing responses based on analyzed emotional states" refers to a system or method for designing appropriate and specific response content according to each user's emotions.

[0848] "Control mechanisms that allow seamless resumption of agent use" are mechanisms that enable smooth resumption of interaction without disrupting the user experience after an advertisement is displayed or a conversation is interrupted.

[0849] To implement this invention, it is necessary to construct a system including a server, a terminal, and an artificial intelligence agent. This system provides an environment in which user input is captured, emotions are recognized, and personalized advertisements are displayed.

[0850] The device is responsible for collecting voice and text data from the user. This data is sent to the server via natural language processing software such as Google Cloud's Natural Language API or Amazon Comprehend. The server analyzes the user's emotional state using an emotion recognition model based on TensorFlow.

[0851] Based on an analysis of the user's emotional state, the server generates a response. This response is personalized, taking emotional data into consideration, and designed to deepen the user interaction. Furthermore, the analysis results are used as the basis for displaying advertisements, presenting the ads most relevant to the user via the AdMob SDK and other means.

[0852] For example, if a user says, "I'm a little tired," the emotion engine will generate a stress-reducing response and naturally display advertisements for products and services that help users relax at work. Through such interactions, users can receive information that matches their emotions, thus forming a positive impression of the advertisements.

[0853] An example of a prompt message is: "The user has reported fatigue, so provide information about relaxation and display appropriate advertisements." This allows you to give instructions to the generative AI model, enabling dynamic interactions that optimize the user experience.

[0854] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0855] Step 1:

[0856] The user provides input via voice or text through the device. This input is captured by the device and prepared as initial data. The input data is formatted appropriately on the device according to the input format and prepared for transmission to the server.

[0857] Step 2:

[0858] The device captures input data and sends it to the server. The server receives this data and performs text analysis using Google Cloud's Natural Language API or Amazon Comprehend. The analysis generates initial data on the text's content, keywords, and sentiment (e.g., positive, negative, neutral).

[0859] Step 3:

[0860] The server supplies the analyzed text and sentiment data to an emotion recognition model powered by TensorFlow. This step analyzes the user's detailed emotional state and generates specific emotion labels (e.g., fatigue, joy, anxiety). This process generates numerical data from the server indicating which emotions are most strongly expressed.

[0861] Step 4:

[0862] The server generates personalized responses using a generative AI model based on the emotion recognition results. The input includes emotion data and associated contextual information. The AI ​​model uses appropriate prompts to form informative and encouraging messages for the user. The generated responses are sent back to the terminal.

[0863] Step 5:

[0864] The server analyzes sentiment data and selects the most relevant ads for the user. This involves querying a database of ads highly relevant to the user's emotional state. Once ad selection is complete, it prepares to deliver the ads to the user's device via the AdMob SDK.

[0865] Step 6:

[0866] The user's device displays personalized responses and advertisements received from the server. The user can then react to the advertisements or presented responses and provide further input. Continuing this interaction initiates the next processing cycle.

[0867] 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.

[0868] 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.

[0869] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0870] 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.

[0871] 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. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, 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.

[0872] 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.

[0873] 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.

[0874] 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.

[0875] 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."

[0876] 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.

[0877] 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.

[0878] 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.

[0879] 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.

[0880] 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.

[0881] 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.

[0882] 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.

[0883] 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.

[0884] 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.

[0885] 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.

[0886] 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.

[0887] 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 to be incorporated by reference.

[0888] The following is further disclosed regarding the embodiments described above.

[0889] (Claim 1)

[0890] A means for receiving information from a user and identifying the relevant information,

[0891] Artificial intelligence processing means that generates a response based on identified information,

[0892] An advertising display method that displays an ad after a specific action is completed,

[0893] A data storage means that processes user input and saves the information,

[0894] A system that includes this.

[0895] (Claim 2)

[0896] The system according to claim 1, comprising means for presenting survey information to a user and for selecting relevant advertisements.

[0897] (Claim 3)

[0898] The system according to claim 1, further comprising control means that allows the agent to resume use after the display of an advertisement.

[0899] "Example 1"

[0900] (Claim 1)

[0901] A means for receiving information from a user and identifying the relevant information,

[0902] A natural language processing means that generates a response based on identified information,

[0903] An advertising selection method that selects and presents relevant advertisements after individual actions are completed,

[0904] A data storage means that transmits user input and stores the information,

[0905] Information acquisition means that access external information sources to obtain information,

[0906] A system that includes this.

[0907] (Claim 2)

[0908] The system according to claim 1, comprising analytical means for presenting survey information to a user and selecting relevant advertisements.

[0909] (Claim 3)

[0910] The system according to claim 1, further comprising an operating means that allows the use of the agent function to be resumed after the advertisement has been presented.

[0911] "Application Example 1"

[0912] (Claim 1)

[0913] A means for receiving information from a user and identifying the relevant information,

[0914] Artificial intelligence processing means that generates a response based on identified information,

[0915] An advertising display method that displays an ad after a specific action is completed,

[0916] A data storage means that processes user input and saves the information,

[0917] A response generation means that provides relevant sales promotion information based on payment data,

[0918] A reward calculation method that calculates and displays reward information for the next use,

[0919] A system that includes this.

[0920] (Claim 2)

[0921] The system according to claim 1, comprising means for presenting survey information to a user and for selecting relevant advertisements.

[0922] (Claim 3)

[0923] The system according to claim 1, further comprising control means that allows the agent to resume use after the display of an advertisement.

[0924] "Example 2 of combining an emotion engine"

[0925] (Claim 1)

[0926] A means for receiving information from a user and identifying the relevant information,

[0927] Means for performing intelligent processing based on identified information,

[0928] An analytical means for analyzing the emotional state of users,

[0929] A generation means that generates a response based on the analyzed emotional state,

[0930] A display means that displays guidance information after a specific task has been completed,

[0931] A means for transferring and storing user information,

[0932] A system that includes this.

[0933] (Claim 2)

[0934] The system according to claim 1, comprising analytical means for presenting survey information to users and selecting relevant guidance information.

[0935] (Claim 3)

[0936] The system according to claim 1, further comprising control means that permit the resumption of the use of the intelligent agent after the display of guidance information.

[0937] "Application example 2 when combining with an emotional engine"

[0938] (Claim 1)

[0939] A means for receiving information from a user and identifying the relevant information,

[0940] An artificial intelligence processing means that generates a response based on identified information and analyzes the user's emotional state,

[0941] An advertising display means that, after a specific action is completed, selects and displays an appropriate advertisement based on the analyzed emotional state,

[0942] A data storage means that processes user input and saves the information,

[0943] A system that includes this.

[0944] (Claim 2)

[0945] The system according to claim 1, comprising means for personalizing responses based on analyzed emotional states.

[0946] (Claim 3)

[0947] The system according to claim 1, further comprising control means that, after displaying an advertisement, allows the user to seamlessly resume using the agent while taking into consideration the user's emotional state. [Explanation of symbols]

[0948] 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. A means for receiving information from a user and identifying the relevant information, Artificial intelligence processing means that generates a response based on identified information, An advertising display method that displays an ad after a specific action is completed, A data storage means that processes user input and saves the information, A system that includes this.

2. The system according to claim 1, comprising analytical means for presenting survey information to a user and selecting relevant advertisements.

3. The system according to claim 1, further comprising control means that allows the agent to resume use after the display of an advertisement.

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