system

Abstract

We provide the system. [Solution] A means of collecting information on the user's interests and preferences, A means of using generative artificial intelligence to select other users based on collected interest and preference information, and to match selected users with each other. A means of providing an online communication environment that allows selected users to interact with each other via a communication network, The aforementioned generating artificial intelligence provides means for providing information to facilitate conversation within an online communication environment, 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, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] As part of preventing dementia in the elderly, it is important to promote communication with others. However, it is difficult for the elderly to find communication partners that match their hobbies and interests. Furthermore, there is a lack of means to support the continuation of communication and the development of interests, which does not lead to the prevention of mental frailty.

Means for Solving the Problems

[0005] This invention utilizes generative artificial intelligence to collect information on the user's interests and preferences, and based on this, selects appropriate interaction partners. It also provides an online communication environment where selected users can interact with each other via a communication network. Furthermore, the generative artificial intelligence provides information to facilitate conversation, stimulating user interaction and presenting new topics related to interests, thereby preventing mental frailty and contributing to dementia prevention.

[0006] "User" refers to the individual who uses this system, and is particularly intended for the elderly.

[0007] "Interest and preference information" refers to data such as personal hobbies, interests, and favorite activities that users register or provide.

[0008] "Generative artificial intelligence" refers to artificial intelligence that uses machine learning techniques such as deep learning to analyze user data and is used to select appropriate interaction partners and facilitate conversations.

[0009] "Matching" refers to the process of selecting appropriate interaction partners based on the user's interests and preferences, and connecting them with each other.

[0010] A "communication network" refers to electronic connection methods, including the internet, used for sending and receiving digital data.

[0011] An "online communication environment" refers to platforms such as chat and video calls that allow users to interact with each other in real time via the internet.

[0012] "Information to facilitate conversation" refers to specific content such as topics, subjects, and questions provided by the generated artificial intelligence to facilitate smooth communication between users.

[0013] "Feedback information" refers to data in which users provide opinions and evaluations regarding their interaction experiences and system usage.

[0014] "Means of adjusting algorithms" refers to technical methods for improving the processing power and accuracy of generative artificial intelligence using feedback information and new data. [Brief explanation of the drawing]

[0015] [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]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of 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.

[0019] In the following embodiments, a RAM (Random Access Memory) with a reference numeral is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, a storage with a reference numeral is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include a flash memory (SSD (Solid State Drive)), a magnetic disk (e.g., a hard disk), or a magnetic tape, etc.

[0021] 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).

[0022] 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."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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".

[0036] This invention provides an online platform that allows elderly and other users to connect with appropriate partners based on their interests and preferences, and to communicate regularly and continuously. The program processing of this system is described below.

[0037] User registration and information gathering

[0038] Users first access the application using their device and create an individual account. During registration, they are asked to enter their name, age, hobbies, interests, etc. This information is received by the server and stored in the database as the user's profile.

[0039] Matching and interaction begin

[0040] The server uses generative artificial intelligence to analyze the user's interests and preferences and evaluate their relevance to other users. This allows it to match users with common hobbies and interests and select appropriate candidates. Once the selection is complete, the server notifies the user of the matching results on their device. If the user approves, the server sets up an online communication environment via the communication network, and two-way interaction begins.

[0041] Conversation support and information provision

[0042] In online communication environments, generative AI regularly provides topics and relevant information to stimulate conversation. To ensure smooth interaction between users, the AI ​​offers real-time information and questions related to the conversation. It also suggests topics to pique new interests, supporting natural communication among users.

[0043] Gathering feedback and improving the system

[0044] After the interaction, the server prompts the user to provide feedback. This feedback information is stored on the server and used to adjust the algorithms of the generating AI. This improves the accuracy of future matching and conversation support, and provides a better user experience.

[0045] Specific example

[0046] For example, if elderly person A, who has registered using a device, expresses interest in "gardening," the server will select person B, who also enjoys gardening, as a matching partner. In the online communication environment provided by the server, A and B can exchange information about gardening and converse based on seasonal gardening advice provided by the AI. After the interaction ends, the user sends feedback to the server, and this information is used for future improvements.

[0047] The following describes the processing flow.

[0048] Step 1:

[0049] The terminal boots up, and the user accesses the new registration screen. The user enters information about their name, age, gender, hobbies, and interests, and presses the "Register" button. The server receives this information and saves each user's information to the database. Once saving is complete, the server generates a unique profile ID for each user.

[0050] Step 2:

[0051] The server periodically scans user information in the database and selects matching candidates based on each user's interests and preferences. Generating AI analyzes hobbies and past interaction history to calculate similarity. Based on these results, a candidate list is created. The server then performs matching based on this list and notifies the user of the selected candidates.

[0052] Step 3:

[0053] The user receives and accepts a matching proposal from the server. The device sends the acceptance information to the server. The server invites the accepted users to an online communication environment, such as LINE Open Chat, via the communication network. This allows the users to begin interacting on the designated platform.

[0054] Step 4:

[0055] The server integrates a generative AI into the online communication environment to facilitate conversation. The generative AI provides topics and information based on the user's past statements and interests. By regularly providing AI-generated reminders and suggestions for new topics, users can keep the chat active.

[0056] Step 5:

[0057] Once the interaction with the user ends, the device receives a feedback request from the server. The user provides feedback on the interaction and sends the results to the server via the device. The server stores the feedback information and uses it as adjustment data for the generation AI algorithm. This allows for continuous improvement of the quality of matching and conversation support in subsequent interactions.

[0058] (Example 1)

[0059] 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."

[0060] This platform addresses the challenge faced by elderly and other users who find it difficult to find partners who match their interests and preferences and to maintain smooth conversations. Furthermore, it is necessary to provide a platform that promotes natural dialogue among users and enables long-term interaction.

[0061] 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.

[0062] In this invention, the server includes means for collecting user attribute information, means for selecting other users based on the collected attribute information using a generative model and connecting the selected users with each other, and means for providing a virtual communication environment in which the selected users can interact with each other via a communication network. This makes it possible for users to easily connect with people who share their interests, thereby promoting more active dialogue and continuous communication.

[0063] "User attribute information" refers to data that shows an individual's characteristics such as age, hobbies, and interests.

[0064] A "generative model" is an artificial intelligence software trained using a large amount of data, designed to generate outputs tailored to specific purposes.

[0065] A "communication network" is the infrastructure used to send and receive data via the internet and other digital networks.

[0066] A "virtual communication environment" is a digital space created for communicating with others online.

[0067] "Selection" is the process of choosing a target based on specific criteria.

[0068] This invention relates to a method for providing an online platform that allows users to interact with each other based on their interests and preferences. The following describes a specific form for implementing this system.

[0069] First, the user accesses the system's application using a terminal and creates an individual account. During this process, the user enters information such as their name, age, hobbies, and interests. This information is sent to the server and stored in the database as user attribute information. Through this process, the system creates an individual profile for each user.

[0070] Next, the server uses a generative AI model to analyze user attribute information stored in the database. This identifies users who may share common hobbies and interests, and selects the best matching candidates. The analysis and selection process employs sophisticated algorithms that evaluate relevance based on user attribute information.

[0071] Subsequently, the server establishes a virtual communication environment through the communication network, allowing selected users to interact with each other. In this environment, a generative AI model provides relevant information and questions in real time to facilitate conversation and stimulate dialogue between users.

[0072] As a concrete example, consider a scenario where two users, A and B, who are both interested in gardening, are matched. The server uses an AI model to provide users with the latest gardening information and seasonal advice, improving the quality of their conversations. Through these conversations based on these topics, users A and B can build a deeper relationship.

[0073] An example of a prompt message would be: "Person A is interested in gardening. Based on this information, have the AI ​​provide topics related to gardening to support communication between Person A and Person B."

[0074] As described above, this system utilizes generative AI models to support natural communication based on user interests and preferences, thereby improving the quality of the user experience.

[0075] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0076] Step 1:

[0077] The user accesses the application using their device and enters information such as their name, age, hobbies, and interests. This information is sent from the device to the server, which then stores it in a database as attribute information. This results in the output indicating the creation of a user profile.

[0078] Step 2:

[0079] The server retrieves attribute information of all users stored in the database as input and uses a generative AI model to analyze the relationships between users who may share common hobbies or interests. This data calculation results in the output of selecting users who are candidates for matching.

[0080] Step 3:

[0081] The server notifies the terminal of the matching results selected by the generated AI model. When the user accepts the matching via the terminal, the server sets up a virtual interaction environment between the selected users using the communication network. This operation results in an output indicating that the users are ready to begin interacting online.

[0082] Step 4:

[0083] Within the virtual interaction environment, the server uses a generative AI model to monitor conversations between users in real time. It generates relevant topics and questions from the input conversation content and sends them to the terminal to stimulate the conversation. This process results in users gaining new information and perspectives through the dialogue.

[0084] Step 5:

[0085] Once the interaction ends, the server receives feedback from the user via the terminal. This feedback is used to adjust the algorithm of future generation AI models. This data processing yields an output that contributes to improving the accuracy of future matching and conversational assistance.

[0086] (Application Example 1)

[0087] 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."

[0088] In an aging society, promoting continuous and natural communication is crucial to improving the quality of life for elderly people who experience loneliness. However, finding someone with common interests and hobbies is difficult, and opportunities for facilitating smooth conversation are limited. A new system is needed to address this challenge.

[0089] 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.

[0090] In this invention, the server includes means for collecting user characteristics, means for selecting other users based on the collected characteristics using generative artificial intelligence and linking the selected users together, means for providing an electronic communication environment in which the selected users can interact with each other via a communication network, means for the generative artificial intelligence to provide information to facilitate dialogue within the electronic communication environment, and means for the generative artificial intelligence to provide relevant content based on the users' shared hobbies and to facilitate dialogue thereon. This enables elderly people to engage in continuous and active communication with others based on their own interests.

[0091] "User characteristics" refer to the individual features of a user, such as their interests, hobbies, and preferences.

[0092] "Generative artificial intelligence" refers to a system that uses artificial intelligence technology to analyze data and generate new information and insights.

[0093] A "communication network" refers to an information infrastructure that transmits and receives data via a network and connects users to one another.

[0094] An "electronic communication environment" refers to a digital platform that allows users to interact with each other via the internet.

[0095] A "shared hobby" refers to interests or activities that different users share with each other, serving as a common theme that facilitates interaction.

[0096] "Relevant content" refers to information and topics that are directly linked to the user's characteristics or shared interests, and is provided especially to deepen dialogue and interaction.

[0097] The system for carrying out this invention operates in a network environment including a server and user terminals. The server has the ability to select other users with common interests by collecting user characteristics and analyzing them using generative artificial intelligence. The selected users can interact with each other in an electronic communication environment via the communication network. In this electronic communication environment, the generative AI model provides information in real time to facilitate dialogue between users. Specifically, it presents content related to the users' common interests and facilitates dialogue based on that content, thereby achieving natural interaction.

[0098] The hardware used is the user's device (e.g., a smartphone), while the software runs on a server. Advanced AI technologies, such as AI models from Google Cloud Platform, are used for generating artificial intelligence. This allows for appropriate matching and content generation based on collected characteristic information.

[0099] As a concrete example, user A, an elderly person using a terminal, is matched with another user B, who is interested in gardening. The server provides relevant gardening information and seasonal advice via a generative AI, stimulating dialogue between the two users. This process also generates new topics from the generated information. By utilizing the generative AI model, users can receive relevant trivia and questions while watching content related to their shared hobby. An example of a prompt might be, "Generate relevant trivia and questions while the user is watching content related to their shared hobby. These questions should encourage discussion based on location information related to the movie they are watching."

[0100] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0101] Step 1:

[0102] The user uses their device to create an account and enter information about their interests and preferences. This input data includes name, age, hobbies, and interests, and is sent from the device to the server. The server receives this data and stores it in a database. Based on the input information, a user profile is generated in the database.

[0103] Step 2:

[0104] The server uses a generative AI model to analyze profile information in the database. It uses user profiles as input to select users with common hobbies and interests. The AI ​​model analyzes data patterns and outputs the most suitable matching candidates. The server then generates a message to notify the user of the results.

[0105] Step 3:

[0106] The user confirms the matching results on their device and gives their approval. The server then sets up an electronic communication environment between the selected users via the communication network. The server sends connection information to the user's device, providing a platform for two-way communication.

[0107] Step 4:

[0108] The server-based AI generates information and topics to stimulate conversation. It uses data on the matched users' shared interests as input to generate relevant content. This information is sent to the user's device and used as material to facilitate dialogue. As a result, users receive interesting trivia and questions in real time.

[0109] Step 5:

[0110] Once the interaction with the user is complete, the device sends feedback to the server. This feedback is taken in as input data and used to improve the algorithm of the generating AI. The server analyzes this feedback to improve the accuracy of future matching and dialogue support.

[0111] 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.

[0112] This invention is a system that combines generative artificial intelligence and an emotion engine to effectively promote online interaction among users. Specific embodiments of this system are described below.

[0113] User registration and information gathering

[0114] Users access the application through their device and register by entering their name, age, hobbies, and interests. This information is stored in a database by the server, and a profile is created.

[0115] Matching and interaction begin

[0116] The server uses generative artificial intelligence to analyze users' interests and preferences and match them with other users. The generative AI selects users with common hobbies and interests and sends notifications to candidates. Once a user approves the match, the server sets up an online communication environment such as LINE via the communication network to facilitate interaction.

[0117] Conversation support and emotion recognition

[0118] Within the online communication environment, a generative AI provides topics and relevant information to stimulate conversation, while an emotion engine recognizes the user's emotions in real time. The emotion engine analyzes the user's facial expressions and voice tone to determine their emotional state. Based on this emotional information, the server adjusts the tone and content of the conversation accordingly, resulting in a more natural and personalized interaction.

[0119] Feedback gathering and algorithm adjustments

[0120] After the interaction ends, users are asked to provide feedback via their devices. The feedback information provided by users is collected on a server and used to improve the algorithms of the generating AI and the functionality of the emotion engine. This continuously improves the accuracy and effectiveness of the entire system so that a better experience can be provided in the next interaction.

[0121] Specific example

[0122] For example, if elderly person A, who has registered through their device, is interested in "listening to music," the server will select person B, who shares the same interest, as a matching partner and begin online communication. When the emotion engine recognizes A's joyful expression, the generative AI will suggest music-related topics and questions, facilitating further interaction and conversation. Depending on A's mood, the generative AI will also suggest new genres of music to broaden their interests. After the interaction ends, user feedback is used to improve the quality of future matching and conversation support.

[0123] The following describes the processing flow.

[0124] Step 1:

[0125] The terminal launches the application, and the user accesses the registration screen. The user enters information such as name, age, hobbies, and interests, and registers. The server receives this information and stores it in a database. Based on the stored information, the server generates a profile ID for each user.

[0126] Step 2:

[0127] The server periodically scans the database to analyze user interests and preferences. Generating AI analyzes the user's profile and selects other users with similar interests. The server notifies the user of the selected matching candidates. The user receives the notification on their device and accepts the match.

[0128] Step 3:

[0129] The server invites matched users to an online communication environment such as LINE via the communication network. Users accept the invitation through their devices and begin online interaction. Interaction takes place via text chat and video calls.

[0130] Step 4:

[0131] During online communication, an emotion engine collects emotional data from the user's camera and microphone. Based on the emotional information recognized by the emotion engine, the server uses generative AI to adjust the tone and topics of the conversation. For example, if the generative AI determines that the user is excited, it will offer relevant and interesting topics to liven up the conversation.

[0132] Step 5:

[0133] After the interaction, a feedback form is sent to the user via their device. The user enters their thoughts and suggestions for improvement regarding the interaction and sends them to the server. The server analyzes this feedback information and adjusts the algorithms of the generation AI and emotion engine. These improvements will enhance the accuracy of future matching and the quality of conversational support.

[0134] (Example 2)

[0135] 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".

[0136] In online communication, there is a need to appropriately match users, effectively stimulate dialogue, and provide personalized experiences that respond to individual emotional states. However, current technology faces the challenge of accurately understanding users' hobbies, preferences, and emotional states, and continuously improving the system based on their feedback.

[0137] 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.

[0138] In this invention, the server includes means for acquiring and storing user identification information, means for selecting other users based on the acquired identification information using computing resources and associating the selected users with each other, means for providing a virtual communication environment in which the selected users can interact via a communication network, means for determining the user's emotions using an emotion recognition function and adjusting the content of the conversation based on the determined emotion information, and means for collecting evaluation information from the user and modifying the procedures of the computing resources based on the evaluation information. This enables appropriate matching based on the user's hobbies, preferences, and emotional state, the provision of personalized conversations, and continuous improvement of the system by utilizing feedback.

[0139] "Identifiable information" refers to identifiable data about the user, such as their name, age, hobbies, and interests.

[0140] "Computational resources" refers to algorithms such as generative artificial intelligence and emotion recognition engines, and the combination of hardware and software used to execute them.

[0141] "Communication network" refers to network infrastructure for transmitting digital information, including the internet and mobile communications.

[0142] A "virtual communication environment" refers to an environment where users can communicate with each other in a digital space through messaging platforms such as LINE.

[0143] "Emotion recognition function" refers to technology that analyzes the user's facial expressions, voice tone, etc., to determine their current emotional state.

[0144] "Evaluation information" refers to feedback data provided by users based on their interaction experiences.

[0145] This invention is a system that combines a generative AI model and an emotion recognition engine to facilitate appropriate online interaction among users. Users access the application using a terminal and register by entering their specific information. The data transmitted from the terminal is stored in a database by the server.

[0146] The server uses stored specific information and leverages generative AI models, which are computational resources, to analyze the user's hobbies and preferences. Based on this analysis, it selects other users with common interests and performs matching. After matching, the server provides a virtual communication environment via a communication network. This environment is built using messaging platforms such as LINE, and users begin interacting with each other.

[0147] Within the communication environment, the server uses a generative AI model to suggest prompts and relevant information to stimulate conversation. For example, it generates prompts such as, "Are there any artists you've been interested in lately?" to help the conversation flow smoothly.

[0148] Furthermore, the emotion recognition function analyzes the user's facial expressions and voice tone in real time to determine their emotional state. Based on this emotional information, the server adjusts the content and tone of the conversation to achieve a more natural and personalized interaction.

[0149] Furthermore, after the interaction ends, the server collects feedback from the terminal and uses this evaluation information to improve the algorithms and emotion recognition functions of the generated AI model. This continuously improves the overall performance and accuracy of the system in order to provide users with a better experience in the next interaction.

[0150] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0151] Step 1:

[0152] Users access the application using their device and enter specific information such as their name, age, hobbies, and interests. This information is sent from the device to the server. The server stores the received information in a database and generates a user profile. This profile forms the basis for matching in subsequent processing.

[0153] Step 2:

[0154] The server retrieves user identification information stored in the database and activates a generative AI model. The generative AI model analyzes the user's interests and preferences and selects other users who share common identification information. As a result of this analysis, a list of potential matching users is generated. Based on this list, the server notifies the user of any matching opportunities.

[0155] Step 3:

[0156] When a user accepts a matching notification, the server uses the network to set up a virtual communication environment such as LINE. In this environment, the selected users can begin a conversation. The server then uses a generative AI model to generate and provide prompts to stimulate the conversation. For example, it might output a prompt such as, "Tell me about your favorite music lately."

[0157] Step 4:

[0158] Within the virtual communication environment, emotion recognition functions analyze the user's facial expressions and voice tone in real time to determine their emotional state. The server then adjusts the content and tone of the dialogue based on the acquired emotion data. This process makes the conversation more natural and personalized. In particular, the generative AI model provides more relevant prompts as the conversation progresses.

[0159] Step 5:

[0160] After an interaction ends, the server collects feedback from the user via the terminal. This feedback information is important data, including user satisfaction and suggestions. The server analyzes this data and uses the evaluation information to improve the generative AI model and the algorithms for emotion recognition. Incorporating feedback improves the overall accuracy of the system, enabling it to provide a better experience for future interactions.

[0161] (Application Example 2)

[0162] 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".

[0163] Traditional online communication systems, even with matching based on user interests and preferences, sometimes fail to facilitate smooth conversations between users. Furthermore, in physical stores, it's difficult to grasp customer interests and emotions in real time and provide appropriate products and information. This results in an inability to effectively stimulate customer purchasing intent and missed sales opportunities. To address this challenge, a more dynamic and personalized information delivery system that transcends the boundaries between online and offline is required.

[0164] 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.

[0165] In this invention, the server includes means for collecting user interest and preference information, means for selecting other users based on the collected interest and preference information using generative artificial intelligence and matching the selected users with each other, means for providing an online communication environment in which the selected users can interact with each other via a communication network, means for the generative artificial intelligence to provide information to facilitate conversation within the online communication environment, and means for analyzing the user's facial expressions in real time using an image acquisition device to perform emotion analysis and providing specific item information using the analyzed emotion information. This enables not only the smooth promotion of conversations between users via online communication but also the provision of optimized information to customers in physical stores.

[0166] "User" refers to an individual or group that utilizes the system or device, provides information about their interests and preferences, and enjoys online or in-store experiences.

[0167] "Generative artificial intelligence" is a technology that analyzes data given in a digital environment, generates or processes information according to an intended purpose, and enables intelligent behavior similar to that of humans.

[0168] "Matching" is the process of appropriately combining users based on specific criteria, and it plays a role in promoting interactions that match their interests and preferences.

[0169] An "online communication environment" is a technological foundation that provides a platform enabling users to interact with each other in real time via the internet or other digital networks.

[0170] "Emotional analysis" is a technique used to analyze and judge a user's emotional state from their facial expressions, voice, etc., in order to understand their psychological condition.

[0171] An "image acquisition device" is a device that captures photographs and videos, and is used to acquire visual data such as the user's facial expressions in real time.

[0172] "Product information" refers to detailed information about a specific product and is part of a product introduction that is suggested based on the user's interests and feelings.

[0173] The system for carrying out this invention consists of a server, a terminal, and an interface with the user.

[0174] The server collects user interest and preference information via digital input and analyzes it using generative artificial intelligence. Based on the analyzed data, it selects and matches other users with similar interests. This process utilizes a database management system and data analysis tools such as Python and R.

[0175] The terminal provides an online communication environment to enable smooth communication between selected users. This allows for real-time voice and video communication via the internet, and may utilize video call technologies such as WebRTC as software libraries.

[0176] Furthermore, to perform emotion analysis, a camera built into the device (specifically, smart glasses or a headset with camera functionality) captures the user's facial expressions in real time. Based on this visual data, the emotional state is analyzed using an image processing library such as OpenCV. The analysis results are then sent to a server and fed back as specific item information optimized for the user's emotions.

[0177] As a concrete example, a service could be provided where product information corresponding to the location where a customer stops smiling in a store is displayed on the smart glasses' screen. In this case, the generating AI would generate a message such as, "We recommend this Pinot Noir to customers who have previously purchased red wine. Would you like information about a tasting?" Furthermore, an example of a prompt to the generating AI model would be, "Please provide prompts to develop a real-time recommendation system for product information that will interest customers in the store, based on their facial expressions and purchase history." This overall system configuration enables personalized information provision based on individual interests and emotions.

[0178] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0179] Step 1:

[0180] Users use their devices to input their interests, preferences, and basic profile information. This information is sent to a server and stored in a database. Based on this stored information, a user profile is created using a database management system.

[0181] Step 2:

[0182] The server uses artificial intelligence to analyze users' interests and preferences based on stored profile information. The analyzed data is used for matching with other users. Using data analysis tools, commonalities between profiles are identified and selected as potential interaction candidates. This selected information is sent to the target users through a notification system.

[0183] Step 3:

[0184] The selected users access an online communication environment on their devices and connect with other selected users. Communication takes place in real time, with voice and video transmitted via calling software. In this step, a video calling library such as WebRTC is running to facilitate communication between users.

[0185] Step 4:

[0186] The camera on the device captures the user's facial expressions and sends the visual data to the server. The server processes this visual data using OpenCV and analyzes the user's emotional state. The analysis results are sent to a generating AI, which then generates information based on those emotions.

[0187] Step 5:

[0188] The generating AI uses analyzed emotional data and pre-collected preference data to generate optimal product information and suggestions for the user. This information is displayed on the device's screen and provided to the user. For example, information that a particular product is on sale might be displayed on the smart glasses' screen. Other specific suggestions are generated in a similar manner.

[0189] Step 6:

[0190] After the interaction ends, users send feedback via their devices. This feedback is collected on the server and used to improve the algorithms and sentiment analysis functions of the generated AI model. This will improve the quality of future matching and information provision.

[0191] 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.

[0192] 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.

[0193] 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.

[0194] [Second Embodiment]

[0195] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0196] 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.

[0197] 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).

[0198] 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.

[0199] 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.

[0200] 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).

[0201] 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.

[0202] 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.

[0203] 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.

[0204] 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.

[0205] 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.

[0206] 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".

[0207] This invention provides an online platform that allows elderly and other users to connect with appropriate partners based on their interests and preferences, and to communicate regularly and continuously. The program processing of this system is described below.

[0208] User registration and information gathering

[0209] Users first access the application using their device and create an individual account. During registration, they are asked to enter their name, age, hobbies, interests, etc. This information is received by the server and stored in the database as the user's profile.

[0210] Matching and interaction begin

[0211] The server uses generative artificial intelligence to analyze the user's interests and preferences and evaluate their relevance to other users. This allows it to match users with common hobbies and interests and select appropriate candidates. Once the selection is complete, the server notifies the user of the matching results on their device. If the user approves, the server sets up an online communication environment via the communication network, and two-way interaction begins.

[0212] Conversation support and information provision

[0213] In online communication environments, generative AI regularly provides topics and relevant information to stimulate conversation. To ensure smooth interaction between users, the AI ​​offers real-time information and questions related to the conversation. It also suggests topics to pique new interests, supporting natural communication among users.

[0214] Gathering feedback and improving the system

[0215] After the interaction, the server prompts the user to provide feedback. This feedback information is stored on the server and used to adjust the algorithms of the generating AI. This improves the accuracy of future matching and conversation support, and provides a better user experience.

[0216] Specific example

[0217] For example, if elderly person A, who has registered using a device, expresses interest in "gardening," the server will select person B, who also enjoys gardening, as a matching partner. In the online communication environment provided by the server, A and B can exchange information about gardening and converse based on seasonal gardening advice provided by the AI. After the interaction ends, the user sends feedback to the server, and this information is used for future improvements.

[0218] The following describes the processing flow.

[0219] Step 1:

[0220] The terminal boots up, and the user accesses the new registration screen. The user enters information about their name, age, gender, hobbies, and interests, and presses the "Register" button. The server receives this information and saves each user's information to the database. Once saving is complete, the server generates a unique profile ID for each user.

[0221] Step 2:

[0222] The server periodically scans user information in the database and selects matching candidates based on each user's interests and preferences. Generating AI analyzes hobbies and past interaction history to calculate similarity. Based on these results, a candidate list is created. The server then performs matching based on this list and notifies the user of the selected candidates.

[0223] Step 3:

[0224] The user receives and accepts a matching proposal from the server. The device sends the acceptance information to the server. The server invites the accepted users to an online communication environment, such as LINE Open Chat, via the communication network. This allows the users to begin interacting on the designated platform.

[0225] Step 4:

[0226] The server integrates a generative AI into the online communication environment to facilitate conversation. The generative AI provides topics and information based on the user's past statements and interests. By regularly providing AI-generated reminders and suggestions for new topics, users can keep the chat active.

[0227] Step 5:

[0228] Once the interaction with the user ends, the device receives a feedback request from the server. The user provides feedback on the interaction and sends the results to the server via the device. The server stores the feedback information and uses it as adjustment data for the generation AI algorithm. This allows for continuous improvement of the quality of matching and conversation support in subsequent interactions.

[0229] (Example 1)

[0230] 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."

[0231] This platform addresses the challenge faced by elderly and other users who find it difficult to find partners who match their interests and preferences and to maintain smooth conversations. Furthermore, it is necessary to provide a platform that promotes natural dialogue among users and enables long-term interaction.

[0232] 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.

[0233] In this invention, the server includes means for collecting user attribute information, means for selecting other users based on the collected attribute information using a generative model and connecting the selected users with each other, and means for providing a virtual communication environment in which the selected users can interact with each other via a communication network. This makes it possible for users to easily connect with people who share their interests, thereby promoting more active dialogue and continuous communication.

[0234] "User attribute information" refers to data that shows an individual's characteristics such as age, hobbies, and interests.

[0235] A "generative model" is an artificial intelligence software trained using a large amount of data, designed to generate outputs tailored to specific purposes.

[0236] A "communication network" is the infrastructure used to send and receive data via the internet and other digital networks.

[0237] A "virtual communication environment" is a digital space created for communicating with others online.

[0238] "Selection" is the process of choosing a target based on specific criteria.

[0239] This invention relates to a method for providing an online platform that allows users to interact with each other based on their interests and preferences. The following describes a specific form for implementing this system.

[0240] First, the user accesses the system's application using a terminal and creates an individual account. During this process, the user enters information such as their name, age, hobbies, and interests. This information is sent to the server and stored in the database as user attribute information. Through this process, the system creates an individual profile for each user.

[0241] Next, the server uses a generative AI model to analyze user attribute information stored in the database. This identifies users who may share common hobbies and interests, and selects the best matching candidates. The analysis and selection process employs sophisticated algorithms that evaluate relevance based on user attribute information.

[0242] Subsequently, the server establishes a virtual communication environment through the communication network, allowing selected users to interact with each other. In this environment, a generative AI model provides relevant information and questions in real time to facilitate conversation and stimulate dialogue between users.

[0243] As a concrete example, consider a scenario where two users, A and B, who are both interested in gardening, are matched. The server uses an AI model to provide users with the latest gardening information and seasonal advice, improving the quality of their conversations. Through these conversations based on these topics, users A and B can build a deeper relationship.

[0244] An example of a prompt message would be: "Person A is interested in gardening. Based on this information, have the AI ​​provide topics related to gardening to support communication between Person A and Person B."

[0245] As described above, this system utilizes generative AI models to support natural communication based on user interests and preferences, thereby improving the quality of the user experience.

[0246] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0247] Step 1:

[0248] The user accesses the application using their device and enters information such as their name, age, hobbies, and interests. This information is sent from the device to the server, which then stores it in a database as attribute information. This results in the output indicating the creation of a user profile.

[0249] Step 2:

[0250] The server retrieves attribute information of all users stored in the database as input and uses a generative AI model to analyze the relationships between users who may share common hobbies or interests. This data calculation results in the output of selecting users who are candidates for matching.

[0251] Step 3:

[0252] The server notifies the terminal of the matching results selected by the generated AI model. When the user accepts the matching via the terminal, the server sets up a virtual interaction environment between the selected users using the communication network. This operation results in an output indicating that the users are ready to begin interacting online.

[0253] Step 4:

[0254] Within the virtual interaction environment, the server uses a generative AI model to monitor conversations between users in real time. It generates relevant topics and questions from the input conversation content and sends them to the terminal to stimulate the conversation. This process results in users gaining new information and perspectives through the dialogue.

[0255] Step 5:

[0256] Once the interaction ends, the server receives feedback from the user via the terminal. This feedback is used to adjust the algorithm of future generation AI models. This data processing yields an output that contributes to improving the accuracy of future matching and conversational assistance.

[0257] (Application Example 1)

[0258] 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."

[0259] In an aging society, promoting continuous and natural communication is crucial to improving the quality of life for elderly people who experience loneliness. However, finding someone with common interests and hobbies is difficult, and opportunities for facilitating smooth conversation are limited. A new system is needed to address this challenge.

[0260] 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.

[0261] In this invention, the server includes means for collecting user characteristics, means for selecting other users based on the collected characteristics using generative artificial intelligence and linking the selected users together, means for providing an electronic communication environment in which the selected users can interact with each other via a communication network, means for the generative artificial intelligence to provide information to facilitate dialogue within the electronic communication environment, and means for the generative artificial intelligence to provide relevant content based on the users' shared hobbies and to facilitate dialogue thereon. This enables elderly people to engage in continuous and active communication with others based on their own interests.

[0262] "User characteristics" refer to the individual features of a user, such as their interests, hobbies, and preferences.

[0263] "Generative artificial intelligence" refers to a system that uses artificial intelligence technology to analyze data and generate new information and insights.

[0264] A "communication network" refers to an information infrastructure that transmits and receives data via a network and connects users to one another.

[0265] An "electronic communication environment" refers to a digital platform that allows users to interact with each other via the internet.

[0266] A "shared hobby" refers to interests or activities that different users share with each other, serving as a common theme that facilitates interaction.

[0267] "Relevant content" refers to information and topics that are directly linked to the user's characteristics or shared interests, and is provided especially to deepen dialogue and interaction.

[0268] The system for carrying out this invention operates in a network environment including a server and user terminals. The server has the ability to select other users with common interests by collecting user characteristics and analyzing them using generative artificial intelligence. The selected users can interact with each other in an electronic communication environment via the communication network. In this electronic communication environment, the generative AI model provides information in real time to facilitate dialogue between users. Specifically, it presents content related to the users' common interests and facilitates dialogue based on that content, thereby achieving natural interaction.

[0269] The hardware used is the user's device (e.g., a smartphone), while the software runs on a server. Advanced AI technologies, such as Google Cloud Platform's AI models, are used for generating artificial intelligence. This allows for appropriate matching and content generation based on collected characteristic information.

[0270] As a concrete example, user A, an elderly person using a terminal, is matched with another user B, who is interested in gardening. The server provides relevant gardening information and seasonal advice via a generative AI, stimulating dialogue between the two users. This process also generates new topics from the generated information. By utilizing the generative AI model, users can receive relevant trivia and questions while watching content related to their shared hobby. An example of a prompt might be, "Generate relevant trivia and questions while the user is watching content related to their shared hobby. These questions should encourage discussion based on location information related to the movie they are watching."

[0271] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0272] Step 1:

[0273] The user uses their device to create an account and enter information about their interests and preferences. This input data includes name, age, hobbies, and interests, and is sent from the device to the server. The server receives this data and stores it in a database. Based on the input information, a user profile is generated in the database.

[0274] Step 2:

[0275] The server uses a generative AI model to analyze profile information in the database. It uses user profiles as input to select users with common hobbies and interests. The AI ​​model analyzes data patterns and outputs the most suitable matching candidates. The server then generates a message to notify the user of the results.

[0276] Step 3:

[0277] The user checks the matching results on the terminal and gives approval. The server then sets up an electronic communication environment between the selected users via the communication network accordingly. The server transmits connection information to the user terminals to provide a two-way conversation platform.

[0278] Step 4:

[0279] The generative AI in the server generates information and topics for activating the conversation. Using data related to the common hobbies of the matched users as input, it generates relevant content. This information is transmitted to the user terminals and used as material for promoting conversation. As a result, users receive interesting trivia and questions in real time.

[0280] Step 5:

[0281] When the interaction with the user ends, the terminal sends feedback to the server. This feedback is taken in as input data and utilized to improve the generative AI's algorithm. The server analyzes this feedback and uses it to enhance the accuracy of the next matching and conversation support.

[0282] Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion recognition model 59 and perform specific processing using the user's emotions.

[0283] The present invention is a system that combines a generative artificial intelligence and an emotion engine to effectively promote online communication between users. The following describes specific embodiments of this system.

[0284] User registration and information collection

[0285] The user accesses the application through the terminal and inputs name, age, hobbies, and interests for registration. This information is saved in the database by the server, and a profile is created.

[0286] Matching and Communication Initiation

[0287] The server analyzes the user's interest and preference information by a generative artificial intelligence and performs matching with other users. The generative AI selects users with common hobbies and interests and sends notifications to the candidates. When the user approves the matching, the server sets up an online communication environment such as LINE via the communication network and promotes communication.

[0288] Conversation Support and Emotion Recognition

[0289] In the online communication environment, in addition to the generative AI providing topics and related information to activate the conversation, an emotion engine recognizes the user's emotions in real time. The emotion engine analyzes the user's facial expressions and voice tones to determine the user's emotional state. Based on this, the server appropriately adjusts the tone and content of the conversation according to the emotion information, realizing a more natural and personalized communication.

[0290] [[ID=D19]]Feedback Collection and Algorithm Adjustment

[0291] After the communication ends, feedback is requested from the user through the terminal. The feedback information provided by the user is aggregated on the server and utilized to improve the algorithm of the generative AI and the functions of the emotion engine. As a result, the accuracy and effectiveness of the entire system are continuously improved so that a better experience can be provided in the next communication.

[0292] Specific Example

[0293] For example, if elderly person A, who has registered through their device, is interested in "listening to music," the server will select person B, who shares the same interest, as a matching partner and begin online communication. When the emotion engine recognizes A's joyful expression, the generative AI will suggest music-related topics and questions, facilitating further interaction and conversation. Depending on A's mood, the generative AI will also suggest new genres of music to broaden their interests. After the interaction ends, user feedback is used to improve the quality of future matching and conversation support.

[0294] The following describes the processing flow.

[0295] Step 1:

[0296] The terminal launches the application, and the user accesses the registration screen. The user enters information such as name, age, hobbies, and interests, and registers. The server receives this information and stores it in a database. Based on the stored information, the server generates a profile ID for each user.

[0297] Step 2:

[0298] The server periodically scans the database to analyze user interests and preferences. Generating AI analyzes the user's profile and selects other users with similar interests. The server notifies the user of the selected matching candidates. The user receives the notification on their device and accepts the match.

[0299] Step 3:

[0300] The server invites matched users to an online communication environment such as LINE via the communication network. Users accept the invitation through their devices and begin online interaction. Interaction takes place via text chat and video calls.

[0301] Step 4:

[0302] During online communication, the emotion engine collects emotion data from the user's camera and microphone. Based on the emotion information recognized by the emotion engine, the server adjusts the tone and topic of the conversation using the generative AI. For example, if the user is determined to be excited, the generative AI provides relevant and interesting topics to activate the conversation.

[0303] Step 5:

[0304] After the communication, a feedback form is sent to the user through the terminal. The user inputs their feelings and improvement points about the communication and sends them to the server. The server analyzes this feedback information and adjusts the algorithms of the generative AI and the emotion engine. Through improvement, the accuracy of future matching and the quality of conversation support are improved.

[0305] (Example 2)

[0306] Next, Example 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0307] In online communication, it is required to perform appropriate matching between users, effectively activate the conversation, and provide a personalized experience according to the individual emotional state. However, in the current technology, there is a problem that it is difficult to accurately grasp the hobbies, preferences, and emotional states of users and continuously improve the system by making use of the feedback.

[0308] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0309] In this invention, the server includes means for acquiring and storing user identification information, means for selecting other users based on the acquired identification information using computing resources and associating the selected users with each other, means for providing a virtual communication environment in which the selected users can interact via a communication network, means for determining the user's emotions using an emotion recognition function and adjusting the content of the conversation based on the determined emotion information, and means for collecting evaluation information from the user and modifying the procedures of the computing resources based on the evaluation information. This enables appropriate matching based on the user's hobbies, preferences, and emotional state, the provision of personalized conversations, and continuous improvement of the system by utilizing feedback.

[0310] "Identifiable information" refers to identifiable data about the user, such as their name, age, hobbies, and interests.

[0311] "Computational resources" refers to algorithms such as generative artificial intelligence and emotion recognition engines, and the combination of hardware and software used to execute them.

[0312] "Communication network" refers to network infrastructure for transmitting digital information, including the internet and mobile communications.

[0313] A "virtual communication environment" refers to an environment where users can communicate with each other in a digital space through messaging platforms such as LINE.

[0314] "Emotion recognition function" refers to technology that analyzes the user's facial expressions, voice tone, etc., to determine their current emotional state.

[0315] "Evaluation information" refers to feedback data provided by users based on their interaction experiences.

[0316] This invention is a system that combines a generative AI model and an emotion recognition engine to facilitate appropriate online interaction among users. Users access the application using a terminal and register by entering their specific information. The data transmitted from the terminal is stored in a database by the server.

[0317] The server uses stored specific information and leverages generative AI models, which are computational resources, to analyze the user's hobbies and preferences. Based on this analysis, it selects other users with common interests and performs matching. After matching, the server provides a virtual communication environment via a communication network. This environment is built using messaging platforms such as LINE, and users begin interacting with each other.

[0318] Within the communication environment, the server uses a generative AI model to suggest prompts and relevant information to stimulate conversation. For example, it generates prompts such as, "Are there any artists you've been interested in lately?" to help the conversation flow smoothly.

[0319] Furthermore, the emotion recognition function analyzes the user's facial expressions and voice tone in real time to determine their emotional state. Based on this emotional information, the server adjusts the content and tone of the conversation to achieve a more natural and personalized interaction.

[0320] Furthermore, after the interaction ends, the server collects feedback from the terminal and uses this evaluation information to improve the algorithms and emotion recognition functions of the generated AI model. This continuously improves the overall performance and accuracy of the system in order to provide users with a better experience in the next interaction.

[0321] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0322] Step 1:

[0323] Users access the application using their device and enter specific information such as their name, age, hobbies, and interests. This information is sent from the device to the server. The server stores the received information in a database and generates a user profile. This profile forms the basis for matching in subsequent processing.

[0324] Step 2:

[0325] The server retrieves user identification information stored in the database and activates a generative AI model. The generative AI model analyzes the user's interests and preferences and selects other users who share common identification information. As a result of this analysis, a list of potential matching users is generated. Based on this list, the server notifies the user of any matching opportunities.

[0326] Step 3:

[0327] When a user accepts a matching notification, the server uses the network to set up a virtual communication environment such as LINE. In this environment, the selected users can begin a conversation. The server then uses a generative AI model to generate and provide prompts to stimulate the conversation. For example, it might output a prompt such as, "Tell me about your favorite music lately."

[0328] Step 4:

[0329] Within the virtual communication environment, emotion recognition functions analyze the user's facial expressions and voice tone in real time to determine their emotional state. The server then adjusts the content and tone of the dialogue based on the acquired emotion data. This process makes the conversation more natural and personalized. In particular, the generative AI model provides more relevant prompts as the conversation progresses.

[0330] Step 5:

[0331] After an interaction ends, the server collects feedback from the user via the terminal. This feedback information is important data, including user satisfaction and suggestions. The server analyzes this data and uses the evaluation information to improve the generative AI model and the algorithms for emotion recognition. Incorporating feedback improves the overall accuracy of the system, enabling it to provide a better experience for future interactions.

[0332] (Application Example 2)

[0333] 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 as the "terminal".

[0334] Traditional online communication systems, even with matching based on user interests and preferences, sometimes fail to facilitate smooth conversations between users. Furthermore, in physical stores, it's difficult to grasp customer interests and emotions in real time and provide appropriate products and information. This results in an inability to effectively stimulate customer purchasing intent and missed sales opportunities. To address this challenge, a more dynamic and personalized information delivery system that transcends the boundaries between online and offline is required.

[0335] 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.

[0336] In this invention, the server includes means for collecting user interest and preference information, means for selecting other users based on the collected interest and preference information using generative artificial intelligence and matching the selected users with each other, means for providing an online communication environment in which the selected users can interact with each other via a communication network, means for the generative artificial intelligence to provide information to facilitate conversation within the online communication environment, and means for analyzing the user's facial expressions in real time using an image acquisition device to perform emotion analysis and providing specific item information using the analyzed emotion information. This enables not only the smooth promotion of conversations between users via online communication but also the provision of optimized information to customers in physical stores.

[0337] "User" refers to an individual or group that utilizes the system or device, provides information about their interests and preferences, and enjoys online or in-store experiences.

[0338] "Generative artificial intelligence" is a technology that analyzes data given in a digital environment, generates or processes information according to an intended purpose, and enables intelligent behavior similar to that of humans.

[0339] "Matching" is the process of appropriately combining users based on specific criteria, and it plays a role in promoting interactions that match their interests and preferences.

[0340] An "online communication environment" is a technological foundation that provides a platform enabling users to interact with each other in real time via the internet or other digital networks.

[0341] "Emotional analysis" is a technique used to analyze and judge a user's emotional state from their facial expressions, voice, etc., in order to understand their psychological condition.

[0342] An "image acquisition device" is a device that captures photographs and videos, and is used to acquire visual data such as the user's facial expressions in real time.

[0343] "Product information" refers to detailed information about a specific product and is part of a product introduction that is suggested based on the user's interests and feelings.

[0344] The system for carrying out this invention consists of a server, a terminal, and an interface with the user.

[0345] The server collects user interest and preference information via digital input and analyzes it using generative artificial intelligence. Based on the analyzed data, it selects and matches other users with similar interests. This process utilizes a database management system and data analysis tools such as Python and R.

[0346] The terminal provides an online communication environment to enable smooth communication between selected users. This allows for real-time voice and video communication via the internet, and may utilize video call technologies such as WebRTC as software libraries.

[0347] Furthermore, to perform emotion analysis, a camera built into the device (specifically, smart glasses or a headset with camera functionality) captures the user's facial expressions in real time. Based on this visual data, the emotional state is analyzed using an image processing library such as OpenCV. The analysis results are then sent to a server and fed back as specific item information optimized for the user's emotions.

[0348] As a concrete example, a service could be provided where product information corresponding to the location where a customer stops smiling in a store is displayed on the smart glasses' screen. In this case, the generating AI would generate a message such as, "We recommend this Pinot Noir to customers who have previously purchased red wine. Would you like information about a tasting?" Furthermore, an example of a prompt to the generating AI model would be, "Please provide prompts to develop a real-time recommendation system for product information that will interest customers in the store, based on their facial expressions and purchase history." This overall system configuration enables personalized information provision based on individual interests and emotions.

[0349] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0350] Step 1:

[0351] Users use their devices to input their interests, preferences, and basic profile information. This information is sent to a server and stored in a database. Based on this stored information, a user profile is created using a database management system.

[0352] Step 2:

[0353] The server uses artificial intelligence to analyze users' interests and preferences based on stored profile information. The analyzed data is used for matching with other users. Using data analysis tools, commonalities between profiles are identified and selected as potential interaction candidates. This selected information is sent to the target users through a notification system.

[0354] Step 3:

[0355] The selected users access an online communication environment on their devices and connect with other selected users. Communication takes place in real time, with voice and video transmitted via calling software. In this step, a video calling library such as WebRTC is running to facilitate communication between users.

[0356] Step 4:

[0357] The camera on the device captures the user's facial expressions and sends the visual data to the server. The server processes this visual data using OpenCV and analyzes the user's emotional state. The analysis results are sent to a generating AI, which then generates information based on those emotions.

[0358] Step 5:

[0359] The generating AI uses analyzed emotional data and pre-collected preference data to generate optimal product information and suggestions for the user. This information is displayed on the device's screen and provided to the user. For example, information that a particular product is on sale might be displayed on the smart glasses' screen. Other specific suggestions are generated in a similar manner.

[0360] Step 6:

[0361] After the interaction ends, users send feedback via their devices. This feedback is collected on the server and used to improve the algorithms and sentiment analysis functions of the generated AI model. This will improve the quality of future matching and information provision.

[0362] 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.

[0363] 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.

[0364] 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.

[0365] [Third Embodiment]

[0366] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0367] 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.

[0368] 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).

[0369] 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.

[0370] 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.

[0371] 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).

[0372] 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.

[0373] 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.

[0374] 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.

[0375] 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.

[0376] 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.

[0377] 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".

[0378] This invention provides an online platform that allows elderly and other users to connect with appropriate partners based on their interests and preferences, and to communicate regularly and continuously. The program processing of this system is described below.

[0379] User registration and information gathering

[0380] Users first access the application using their device and create an individual account. During registration, they are asked to enter their name, age, hobbies, interests, etc. This information is received by the server and stored in the database as the user's profile.

[0381] Matching and interaction begin

[0382] The server uses generative artificial intelligence to analyze the user's interests and preferences and evaluate their relevance to other users. This allows it to match users with common hobbies and interests and select appropriate candidates. Once the selection is complete, the server notifies the user of the matching results on their device. If the user approves, the server sets up an online communication environment via the communication network, and two-way interaction begins.

[0383] Conversation support and information provision

[0384] In online communication environments, generative AI regularly provides topics and relevant information to stimulate conversation. To ensure smooth interaction between users, the AI ​​offers real-time information and questions related to the conversation. It also suggests topics to pique new interests, supporting natural communication among users.

[0385] Gathering feedback and improving the system

[0386] After the interaction, the server prompts the user to provide feedback. This feedback information is stored on the server and used to adjust the algorithms of the generating AI. This improves the accuracy of future matching and conversation support, and provides a better user experience.

[0387] Specific example

[0388] For example, if elderly person A, who has registered using a device, expresses interest in "gardening," the server will select person B, who also enjoys gardening, as a matching partner. In the online communication environment provided by the server, A and B can exchange information about gardening and converse based on seasonal gardening advice provided by the AI. After the interaction ends, the user sends feedback to the server, and this information is used for future improvements.

[0389] The following describes the processing flow.

[0390] Step 1:

[0391] The terminal boots up, and the user accesses the new registration screen. The user enters information about their name, age, gender, hobbies, and interests, and presses the "Register" button. The server receives this information and saves each user's information to the database. Once saving is complete, the server generates a unique profile ID for each user.

[0392] Step 2:

[0393] The server periodically scans user information in the database and selects matching candidates based on each user's interests and preferences. Generating AI analyzes hobbies and past interaction history to calculate similarity. Based on these results, a candidate list is created. The server then performs matching based on this list and notifies the user of the selected candidates.

[0394] Step 3:

[0395] The user receives and accepts a matching proposal from the server. The device sends the acceptance information to the server. The server invites the accepted users to an online communication environment, such as LINE Open Chat, via the communication network. This allows the users to begin interacting on the designated platform.

[0396] Step 4:

[0397] The server integrates a generative AI into the online communication environment to facilitate conversation. The generative AI provides topics and information based on the user's past statements and interests. By regularly providing AI-generated reminders and suggestions for new topics, users can keep the chat active.

[0398] Step 5:

[0399] Once the interaction with the user ends, the device receives a feedback request from the server. The user provides feedback on the interaction and sends the results to the server via the device. The server stores the feedback information and uses it as adjustment data for the generation AI algorithm. This allows for continuous improvement of the quality of matching and conversation support in subsequent interactions.

[0400] (Example 1)

[0401] 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."

[0402] This platform addresses the challenge faced by elderly and other users who find it difficult to find partners who match their interests and preferences and to maintain smooth conversations. Furthermore, it is necessary to provide a platform that promotes natural dialogue among users and enables long-term interaction.

[0403] 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.

[0404] In this invention, the server includes means for collecting user attribute information, means for selecting other users based on the collected attribute information using a generative model and connecting the selected users with each other, and means for providing a virtual communication environment in which the selected users can interact with each other via a communication network. This makes it possible for users to easily connect with people who share their interests, thereby promoting more active dialogue and continuous communication.

[0405] "User attribute information" refers to data that shows an individual's characteristics such as age, hobbies, and interests.

[0406] A "generative model" is an artificial intelligence software trained using a large amount of data, designed to generate outputs tailored to specific purposes.

[0407] A "communication network" is the infrastructure used to send and receive data via the internet and other digital networks.

[0408] A "virtual communication environment" is a digital space created for communicating with others online.

[0409] "Selection" is the process of choosing a target based on specific criteria.

[0410] This invention relates to a method for providing an online platform that allows users to interact with each other based on their interests and preferences. The following describes a specific form for implementing this system.

[0411] First, the user accesses the system's application using a terminal and creates an individual account. During this process, the user enters information such as their name, age, hobbies, and interests. This information is sent to the server and stored in the database as user attribute information. Through this process, the system creates an individual profile for each user.

[0412] Next, the server uses a generative AI model to analyze user attribute information stored in the database. This identifies users who may share common hobbies and interests, and selects the best matching candidates. The analysis and selection process employs sophisticated algorithms that evaluate relevance based on user attribute information.

[0413] Subsequently, the server establishes a virtual communication environment through the communication network, allowing selected users to interact with each other. In this environment, a generative AI model provides relevant information and questions in real time to facilitate conversation and stimulate dialogue between users.

[0414] As a concrete example, consider a scenario where two users, A and B, who are both interested in gardening, are matched. The server uses an AI model to provide users with the latest gardening information and seasonal advice, improving the quality of their conversations. Through these conversations based on these topics, users A and B can build a deeper relationship.

[0415] An example of a prompt message would be: "Person A is interested in gardening. Based on this information, have the AI ​​provide topics related to gardening to support communication between Person A and Person B."

[0416] As described above, this system utilizes generative AI models to support natural communication based on user interests and preferences, thereby improving the quality of the user experience.

[0417] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0418] Step 1:

[0419] The user accesses the application using their device and enters information such as their name, age, hobbies, and interests. This information is sent from the device to the server, which then stores it in a database as attribute information. This results in the output indicating the creation of a user profile.

[0420] Step 2:

[0421] The server retrieves attribute information of all users stored in the database as input and uses a generative AI model to analyze the relationships between users who may share common hobbies or interests. This data calculation results in the output of selecting users who are candidates for matching.

[0422] Step 3:

[0423] The server notifies the terminal of the matching results selected by the generated AI model. When the user accepts the matching via the terminal, the server sets up a virtual interaction environment between the selected users using the communication network. This operation results in an output indicating that the users are ready to begin interacting online.

[0424] Step 4:

[0425] Within the virtual interaction environment, the server uses a generative AI model to monitor conversations between users in real time. It generates relevant topics and questions from the input conversation content and sends them to the terminal to stimulate the conversation. This process results in users gaining new information and perspectives through the dialogue.

[0426] Step 5:

[0427] Once the interaction ends, the server receives feedback from the user via the terminal. This feedback is used to adjust the algorithm of future generation AI models. This data processing yields an output that contributes to improving the accuracy of future matching and conversational assistance.

[0428] (Application Example 1)

[0429] 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."

[0430] In an aging society, promoting continuous and natural communication is crucial to improving the quality of life for elderly people who experience loneliness. However, finding someone with common interests and hobbies is difficult, and opportunities for facilitating smooth conversation are limited. A new system is needed to address this challenge.

[0431] 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.

[0432] In this invention, the server includes means for collecting user characteristics, means for selecting other users based on the collected characteristics using generative artificial intelligence and linking the selected users together, means for providing an electronic communication environment in which the selected users can interact with each other via a communication network, means for the generative artificial intelligence to provide information to facilitate dialogue within the electronic communication environment, and means for the generative artificial intelligence to provide relevant content based on the users' shared hobbies and to facilitate dialogue thereon. This enables elderly people to engage in continuous and active communication with others based on their own interests.

[0433] "User characteristics" refer to the individual features of a user, such as their interests, hobbies, and preferences.

[0434] "Generative artificial intelligence" refers to a system that uses artificial intelligence technology to analyze data and generate new information and insights.

[0435] A "communication network" refers to an information infrastructure that transmits and receives data via a network and connects users to one another.

[0436] An "electronic communication environment" refers to a digital platform that allows users to interact with each other via the internet.

[0437] A "shared hobby" refers to interests or activities that different users share with each other, serving as a common theme that facilitates interaction.

[0438] "Relevant content" refers to information and topics that are directly linked to the user's characteristics or shared interests, and is provided especially to deepen dialogue and interaction.

[0439] The system for carrying out this invention operates in a network environment including a server and user terminals. The server has the ability to select other users with common interests by collecting user characteristics and analyzing them using generative artificial intelligence. The selected users can interact with each other in an electronic communication environment via the communication network. In this electronic communication environment, the generative AI model provides information in real time to facilitate dialogue between users. Specifically, it presents content related to the users' common interests and facilitates dialogue based on that content, thereby achieving natural interaction.

[0440] The hardware used is the user's device (e.g., a smartphone), while the software runs on a server. Advanced AI technologies, such as Google Cloud Platform's AI models, are used for generating artificial intelligence. This allows for appropriate matching and content generation based on collected characteristic information.

[0441] As a concrete example, user A, an elderly person using a terminal, is matched with another user B, who is interested in gardening. The server provides relevant gardening information and seasonal advice via a generative AI, stimulating dialogue between the two users. This process also generates new topics from the generated information. By utilizing the generative AI model, users can receive relevant trivia and questions while watching content related to their shared hobby. An example of a prompt might be, "Generate relevant trivia and questions while the user is watching content related to their shared hobby. These questions should encourage discussion based on location information related to the movie they are watching."

[0442] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0443] Step 1:

[0444] The user uses their device to create an account and enter information about their interests and preferences. This input data includes name, age, hobbies, and interests, and is sent from the device to the server. The server receives this data and stores it in a database. Based on the input information, a user profile is generated in the database.

[0445] Step 2:

[0446] The server uses a generative AI model to analyze profile information in the database. It uses user profiles as input to select users with common hobbies and interests. The AI ​​model analyzes data patterns and outputs the most suitable matching candidates. The server then generates a message to notify the user of the results.

[0447] Step 3:

[0448] The user confirms the matching results on their device and gives their approval. The server then sets up an electronic communication environment between the selected users via the communication network. The server sends connection information to the user's device, providing a platform for two-way communication.

[0449] Step 4:

[0450] The server-based AI generates information and topics to stimulate conversation. It uses data on the matched users' shared interests as input to generate relevant content. This information is sent to the user's device and used as material to facilitate dialogue. As a result, users receive interesting trivia and questions in real time.

[0451] Step 5:

[0452] Once the interaction with the user is complete, the device sends feedback to the server. This feedback is taken in as input data and used to improve the algorithm of the generating AI. The server analyzes this feedback to improve the accuracy of future matching and dialogue support.

[0453] 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.

[0454] This invention is a system that combines generative artificial intelligence and an emotion engine to effectively promote online interaction among users. Specific embodiments of this system are described below.

[0455] User registration and information gathering

[0456] Users access the application through their device and register by entering their name, age, hobbies, and interests. This information is stored in a database by the server, and a profile is created.

[0457] Matching and interaction begin

[0458] The server uses generative artificial intelligence to analyze users' interests and preferences and match them with other users. The generative AI selects users with common hobbies and interests and sends notifications to candidates. Once a user approves the match, the server sets up an online communication environment such as LINE via the communication network to facilitate interaction.

[0459] Conversation support and emotion recognition

[0460] Within the online communication environment, a generative AI provides topics and relevant information to stimulate conversation, while an emotion engine recognizes the user's emotions in real time. The emotion engine analyzes the user's facial expressions and voice tone to determine their emotional state. Based on this emotional information, the server adjusts the tone and content of the conversation accordingly, resulting in a more natural and personalized interaction.

[0461] Feedback gathering and algorithm adjustments

[0462] After the interaction ends, users are asked to provide feedback via their devices. The feedback information provided by users is collected on a server and used to improve the algorithms of the generating AI and the functionality of the emotion engine. This continuously improves the accuracy and effectiveness of the entire system so that a better experience can be provided in the next interaction.

[0463] Specific example

[0464] For example, if elderly person A, who has registered through their device, is interested in "listening to music," the server will select person B, who shares the same interest, as a matching partner and begin online communication. When the emotion engine recognizes A's joyful expression, the generative AI will suggest music-related topics and questions, facilitating further interaction and conversation. Depending on A's mood, the generative AI will also suggest new genres of music to broaden their interests. After the interaction ends, user feedback is used to improve the quality of future matching and conversation support.

[0465] The following describes the processing flow.

[0466] Step 1:

[0467] The terminal launches the application, and the user accesses the registration screen. The user enters information such as name, age, hobbies, and interests, and registers. The server receives this information and stores it in a database. Based on the stored information, the server generates a profile ID for each user.

[0468] Step 2:

[0469] The server periodically scans the database to analyze user interests and preferences. Generating AI analyzes the user's profile and selects other users with similar interests. The server notifies the user of the selected matching candidates. The user receives the notification on their device and accepts the match.

[0470] Step 3:

[0471] The server invites matched users to an online communication environment such as LINE via the communication network. Users accept the invitation through their devices and begin online interaction. Interaction takes place via text chat and video calls.

[0472] Step 4:

[0473] During online communication, an emotion engine collects emotional data from the user's camera and microphone. Based on the emotional information recognized by the emotion engine, the server uses generative AI to adjust the tone and topics of the conversation. For example, if the generative AI determines that the user is excited, it will offer relevant and interesting topics to liven up the conversation.

[0474] Step 5:

[0475] After the interaction, a feedback form is sent to the user via their device. The user enters their thoughts and suggestions for improvement regarding the interaction and sends them to the server. The server analyzes this feedback information and adjusts the algorithms of the generation AI and emotion engine. These improvements will enhance the accuracy of future matching and the quality of conversational support.

[0476] (Example 2)

[0477] 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."

[0478] In online communication, there is a need to appropriately match users, effectively stimulate dialogue, and provide personalized experiences that respond to individual emotional states. However, current technology faces the challenge of accurately understanding users' hobbies, preferences, and emotional states, and continuously improving the system based on their feedback.

[0479] 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.

[0480] In this invention, the server includes means for acquiring and storing user identification information, means for selecting other users based on the acquired identification information using computing resources and associating the selected users with each other, means for providing a virtual communication environment in which the selected users can interact via a communication network, means for determining the user's emotions using an emotion recognition function and adjusting the content of the conversation based on the determined emotion information, and means for collecting evaluation information from the user and modifying the procedures of the computing resources based on the evaluation information. This enables appropriate matching based on the user's hobbies, preferences, and emotional state, the provision of personalized conversations, and continuous improvement of the system by utilizing feedback.

[0481] "Identifiable information" refers to identifiable data about the user, such as their name, age, hobbies, and interests.

[0482] "Computational resources" refers to algorithms such as generative artificial intelligence and emotion recognition engines, and the combination of hardware and software used to execute them.

[0483] "Communication network" refers to network infrastructure for transmitting digital information, including the internet and mobile communications.

[0484] A "virtual communication environment" refers to an environment where users can communicate with each other in a digital space through messaging platforms such as LINE.

[0485] "Emotion recognition function" refers to technology that analyzes the user's facial expressions, voice tone, etc., to determine their current emotional state.

[0486] "Evaluation information" refers to feedback data provided by users based on their interaction experiences.

[0487] This invention is a system that combines a generative AI model and an emotion recognition engine to facilitate appropriate online interaction among users. Users access the application using a terminal and register by entering their specific information. The data transmitted from the terminal is stored in a database by the server.

[0488] The server uses stored specific information and leverages generative AI models, which are computational resources, to analyze the user's hobbies and preferences. Based on this analysis, it selects other users with common interests and performs matching. After matching, the server provides a virtual communication environment via a communication network. This environment is built using messaging platforms such as LINE, and users begin interacting with each other.

[0489] Within the communication environment, the server uses a generative AI model to suggest prompts and relevant information to stimulate conversation. For example, it generates prompts such as, "Are there any artists you've been interested in lately?" to help the conversation flow smoothly.

[0490] Furthermore, the emotion recognition function analyzes the user's facial expressions and voice tone in real time to determine their emotional state. Based on this emotional information, the server adjusts the content and tone of the conversation to achieve a more natural and personalized interaction.

[0491] Furthermore, after the interaction ends, the server collects feedback from the terminal and uses this evaluation information to improve the algorithms and emotion recognition functions of the generated AI model. This continuously improves the overall performance and accuracy of the system in order to provide users with a better experience in the next interaction.

[0492] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0493] Step 1:

[0494] Users access the application using their device and enter specific information such as their name, age, hobbies, and interests. This information is sent from the device to the server. The server stores the received information in a database and generates a user profile. This profile forms the basis for matching in subsequent processing.

[0495] Step 2:

[0496] The server retrieves user identification information stored in the database and activates a generative AI model. The generative AI model analyzes the user's interests and preferences and selects other users who share common identification information. As a result of this analysis, a list of potential matching users is generated. Based on this list, the server notifies the user of any matching opportunities.

[0497] Step 3:

[0498] When a user accepts a matching notification, the server uses the network to set up a virtual communication environment such as LINE. In this environment, the selected users can begin a conversation. The server then uses a generative AI model to generate and provide prompts to stimulate the conversation. For example, it might output a prompt such as, "Tell me about your favorite music lately."

[0499] Step 4:

[0500] Within the virtual communication environment, emotion recognition functions analyze the user's facial expressions and voice tone in real time to determine their emotional state. The server then adjusts the content and tone of the dialogue based on the acquired emotion data. This process makes the conversation more natural and personalized. In particular, the generative AI model provides more relevant prompts as the conversation progresses.

[0501] Step 5:

[0502] After an interaction ends, the server collects feedback from the user via the terminal. This feedback information is important data, including user satisfaction and suggestions. The server analyzes this data and uses the evaluation information to improve the generative AI model and the algorithms for emotion recognition. Incorporating feedback improves the overall accuracy of the system, enabling it to provide a better experience for future interactions.

[0503] (Application Example 2)

[0504] 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."

[0505] Traditional online communication systems, even with matching based on user interests and preferences, sometimes fail to facilitate smooth conversations between users. Furthermore, in physical stores, it's difficult to grasp customer interests and emotions in real time and provide appropriate products and information. This results in an inability to effectively stimulate customer purchasing intent and missed sales opportunities. To address this challenge, a more dynamic and personalized information delivery system that transcends the boundaries between online and offline is required.

[0506] 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.

[0507] In this invention, the server includes means for collecting user interest and preference information, means for selecting other users based on the collected interest and preference information using generative artificial intelligence and matching the selected users with each other, means for providing an online communication environment in which the selected users can interact with each other via a communication network, means for the generative artificial intelligence to provide information to facilitate conversation within the online communication environment, and means for analyzing the user's facial expressions in real time using an image acquisition device to perform emotion analysis and providing specific item information using the analyzed emotion information. This enables not only the smooth promotion of conversations between users via online communication but also the provision of optimized information to customers in physical stores.

[0508] "User" refers to an individual or group that utilizes the system or device, provides information about their interests and preferences, and enjoys online or in-store experiences.

[0509] "Generative artificial intelligence" is a technology that analyzes data given in a digital environment, generates or processes information according to an intended purpose, and enables intelligent behavior similar to that of humans.

[0510] "Matching" is the process of appropriately combining users based on specific criteria, and it plays a role in promoting interactions that match their interests and preferences.

[0511] An "online communication environment" is a technological foundation that provides a platform enabling users to interact with each other in real time via the internet or other digital networks.

[0512] "Emotional analysis" is a technique used to analyze and judge a user's emotional state from their facial expressions, voice, etc., in order to understand their psychological condition.

[0513] An "image acquisition device" is a device that captures photographs and videos, and is used to acquire visual data such as the user's facial expressions in real time.

[0514] "Product information" refers to detailed information about a specific product and is part of a product introduction that is suggested based on the user's interests and feelings.

[0515] The system for carrying out this invention consists of a server, a terminal, and an interface with the user.

[0516] The server collects user interest and preference information via digital input and analyzes it using generative artificial intelligence. Based on the analyzed data, it selects and matches other users with similar interests. This process utilizes a database management system and data analysis tools such as Python and R.

[0517] The terminal provides an online communication environment to enable smooth communication between selected users. This allows for real-time voice and video communication via the internet, and may utilize video call technologies such as WebRTC as software libraries.

[0518] Furthermore, to perform emotion analysis, a camera built into the device (specifically, smart glasses or a headset with camera functionality) captures the user's facial expressions in real time. Based on this visual data, the emotional state is analyzed using an image processing library such as OpenCV. The analysis results are then sent to a server and fed back as specific item information optimized for the user's emotions.

[0519] As a concrete example, a service could be provided where product information corresponding to the location where a customer stops smiling in a store is displayed on the smart glasses' screen. In this case, the generating AI would generate a message such as, "We recommend this Pinot Noir to customers who have previously purchased red wine. Would you like information about a tasting?" Furthermore, an example of a prompt to the generating AI model would be, "Please provide prompts to develop a real-time recommendation system for product information that will interest customers in the store, based on their facial expressions and purchase history." This overall system configuration enables personalized information provision based on individual interests and emotions.

[0520] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0521] Step 1:

[0522] Users use their devices to input their interests, preferences, and basic profile information. This information is sent to a server and stored in a database. Based on this stored information, a user profile is created using a database management system.

[0523] Step 2:

[0524] The server uses artificial intelligence to analyze users' interests and preferences based on stored profile information. The analyzed data is used for matching with other users. Using data analysis tools, commonalities between profiles are identified and selected as potential interaction candidates. This selected information is sent to the target users through a notification system.

[0525] Step 3:

[0526] The selected users access an online communication environment on their devices and connect with other selected users. Communication takes place in real time, with voice and video transmitted via calling software. In this step, a video calling library such as WebRTC is running to facilitate communication between users.

[0527] Step 4:

[0528] The camera on the device captures the user's facial expressions and sends the visual data to the server. The server processes this visual data using OpenCV and analyzes the user's emotional state. The analysis results are sent to a generating AI, which then generates information based on those emotions.

[0529] Step 5:

[0530] The generating AI uses analyzed emotional data and pre-collected preference data to generate optimal product information and suggestions for the user. This information is displayed on the device's screen and provided to the user. For example, information that a particular product is on sale might be displayed on the smart glasses' screen. Other specific suggestions are generated in a similar manner.

[0531] Step 6:

[0532] After the interaction ends, users send feedback via their devices. This feedback is collected on the server and used to improve the algorithms and sentiment analysis functions of the generated AI model. This will improve the quality of future matching and information provision.

[0533] 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.

[0534] 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.

[0535] 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.

[0536] [Fourth Embodiment]

[0537] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0538] 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.

[0539] 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).

[0540] 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.

[0541] 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.

[0542] 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).

[0543] 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.

[0544] 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.

[0545] 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.

[0546] 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.

[0547] 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.

[0548] 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.

[0549] 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".

[0550] This invention provides an online platform that allows elderly and other users to connect with appropriate partners based on their interests and preferences, and to communicate regularly and continuously. The program processing of this system is described below.

[0551] User registration and information gathering

[0552] Users first access the application using their device and create an individual account. During registration, they are asked to enter their name, age, hobbies, interests, etc. This information is received by the server and stored in the database as the user's profile.

[0553] Matching and interaction begin

[0554] The server uses generative artificial intelligence to analyze the user's interests and preferences and evaluate their relevance to other users. This allows it to match users with common hobbies and interests and select appropriate candidates. Once the selection is complete, the server notifies the user of the matching results on their device. If the user approves, the server sets up an online communication environment via the communication network, and two-way interaction begins.

[0555] Conversation support and information provision

[0556] In online communication environments, generative AI regularly provides topics and relevant information to stimulate conversation. To ensure smooth interaction between users, the AI ​​offers real-time information and questions related to the conversation. It also suggests topics to pique new interests, supporting natural communication among users.

[0557] Gathering feedback and improving the system

[0558] After the interaction, the server prompts the user to provide feedback. This feedback information is stored on the server and used to adjust the algorithms of the generating AI. This improves the accuracy of future matching and conversation support, and provides a better user experience.

[0559] Specific example

[0560] For example, if elderly person A, who has registered using a device, expresses interest in "gardening," the server will select person B, who also enjoys gardening, as a matching partner. In the online communication environment provided by the server, A and B can exchange information about gardening and converse based on seasonal gardening advice provided by the AI. After the interaction ends, the user sends feedback to the server, and this information is used for future improvements.

[0561] The following describes the processing flow.

[0562] Step 1:

[0563] The terminal boots up, and the user accesses the new registration screen. The user enters information about their name, age, gender, hobbies, and interests, and presses the "Register" button. The server receives this information and saves each user's information to the database. Once saving is complete, the server generates a unique profile ID for each user.

[0564] Step 2:

[0565] The server periodically scans user information in the database and selects matching candidates based on each user's interests and preferences. Generating AI analyzes hobbies and past interaction history to calculate similarity. Based on these results, a candidate list is created. The server then performs matching based on this list and notifies the user of the selected candidates.

[0566] Step 3:

[0567] The user receives and accepts a matching proposal from the server. The device sends the acceptance information to the server. The server invites the accepted users to an online communication environment, such as LINE Open Chat, via the communication network. This allows the users to begin interacting on the designated platform.

[0568] Step 4:

[0569] The server integrates a generative AI into the online communication environment to facilitate conversation. The generative AI provides topics and information based on the user's past statements and interests. By regularly providing AI-generated reminders and suggestions for new topics, users can keep the chat active.

[0570] Step 5:

[0571] Once the interaction with the user ends, the device receives a feedback request from the server. The user provides feedback on the interaction and sends the results to the server via the device. The server stores the feedback information and uses it as adjustment data for the generation AI algorithm. This allows for continuous improvement of the quality of matching and conversation support in subsequent interactions.

[0572] (Example 1)

[0573] 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".

[0574] This platform addresses the challenge faced by elderly and other users who find it difficult to find partners who match their interests and preferences and to maintain smooth conversations. Furthermore, it is necessary to provide a platform that promotes natural dialogue among users and enables long-term interaction.

[0575] 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.

[0576] In this invention, the server includes means for collecting user attribute information, means for selecting other users based on the collected attribute information using a generative model and connecting the selected users with each other, and means for providing a virtual communication environment in which the selected users can interact with each other via a communication network. This makes it possible for users to easily connect with people who share their interests, thereby promoting more active dialogue and continuous communication.

[0577] "User attribute information" refers to data that shows an individual's characteristics such as age, hobbies, and interests.

[0578] A "generative model" is an artificial intelligence software trained using a large amount of data, designed to generate outputs tailored to specific purposes.

[0579] A "communication network" is the infrastructure used to send and receive data via the internet and other digital networks.

[0580] A "virtual communication environment" is a digital space created for communicating with others online.

[0581] "Selection" is the process of choosing a target based on specific criteria.

[0582] This invention relates to a method for providing an online platform that allows users to interact with each other based on their interests and preferences. The following describes a specific form for implementing this system.

[0583] First, the user accesses the system's application using a terminal and creates an individual account. During this process, the user enters information such as their name, age, hobbies, and interests. This information is sent to the server and stored in the database as user attribute information. Through this process, the system creates an individual profile for each user.

[0584] Next, the server uses a generative AI model to analyze user attribute information stored in the database. This identifies users who may share common hobbies and interests, and selects the best matching candidates. The analysis and selection process employs sophisticated algorithms that evaluate relevance based on user attribute information.

[0585] Subsequently, the server establishes a virtual communication environment through the communication network, allowing selected users to interact with each other. In this environment, a generative AI model provides relevant information and questions in real time to facilitate conversation and stimulate dialogue between users.

[0586] As a concrete example, consider a scenario where two users, A and B, who are both interested in gardening, are matched. The server uses an AI model to provide users with the latest gardening information and seasonal advice, improving the quality of their conversations. Through these conversations based on these topics, users A and B can build a deeper relationship.

[0587] An example of a prompt message would be: "Person A is interested in gardening. Based on this information, have the AI ​​provide topics related to gardening to support communication between Person A and Person B."

[0588] As described above, this system utilizes generative AI models to support natural communication based on user interests and preferences, thereby improving the quality of the user experience.

[0589] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0590] Step 1:

[0591] The user accesses the application using their device and enters information such as their name, age, hobbies, and interests. This information is sent from the device to the server, which then stores it in a database as attribute information. This results in the output indicating the creation of a user profile.

[0592] Step 2:

[0593] The server retrieves attribute information of all users stored in the database as input and uses a generative AI model to analyze the relationships between users who may share common hobbies or interests. This data calculation results in the output of selecting users who are candidates for matching.

[0594] Step 3:

[0595] The server notifies the terminal of the matching results selected by the generated AI model. When the user accepts the matching via the terminal, the server sets up a virtual interaction environment between the selected users using the communication network. This operation results in an output indicating that the users are ready to begin interacting online.

[0596] Step 4:

[0597] Within the virtual interaction environment, the server uses a generative AI model to monitor conversations between users in real time. It generates relevant topics and questions from the input conversation content and sends them to the terminal to stimulate the conversation. This process results in users gaining new information and perspectives through the dialogue.

[0598] Step 5:

[0599] Once the interaction ends, the server receives feedback from the user via the terminal. This feedback is used to adjust the algorithm of future generation AI models. This data processing yields an output that contributes to improving the accuracy of future matching and conversational assistance.

[0600] (Application Example 1)

[0601] 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".

[0602] In an aging society, promoting continuous and natural communication is crucial to improving the quality of life for elderly people who experience loneliness. However, finding someone with common interests and hobbies is difficult, and opportunities for facilitating smooth conversation are limited. A new system is needed to address this challenge.

[0603] 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.

[0604] In this invention, the server includes means for collecting user characteristics, means for selecting other users based on the collected characteristics using generative artificial intelligence and linking the selected users together, means for providing an electronic communication environment in which the selected users can interact with each other via a communication network, means for the generative artificial intelligence to provide information to facilitate dialogue within the electronic communication environment, and means for the generative artificial intelligence to provide relevant content based on the users' shared hobbies and to facilitate dialogue thereon. This enables elderly people to engage in continuous and active communication with others based on their own interests.

[0605] "User characteristics" refer to the individual features of a user, such as their interests, hobbies, and preferences.

[0606] "Generative artificial intelligence" refers to a system that uses artificial intelligence technology to analyze data and generate new information and insights.

[0607] A "communication network" refers to an information infrastructure that transmits and receives data via a network and connects users to one another.

[0608] An "electronic communication environment" refers to a digital platform that allows users to interact with each other via the internet.

[0609] A "shared hobby" refers to interests or activities that different users share with each other, serving as a common theme that facilitates interaction.

[0610] "Relevant content" refers to information and topics that are directly linked to the user's characteristics or shared interests, and is provided especially to deepen dialogue and interaction.

[0611] The system for carrying out this invention operates in a network environment including a server and user terminals. The server has the ability to select other users with common interests by collecting user characteristics and analyzing them using generative artificial intelligence. The selected users can interact with each other in an electronic communication environment via the communication network. In this electronic communication environment, the generative AI model provides information in real time to facilitate dialogue between users. Specifically, it presents content related to the users' common interests and facilitates dialogue based on that content, thereby achieving natural interaction.

[0612] The hardware used is the user's device (e.g., a smartphone), while the software runs on a server. Advanced AI technologies, such as Google Cloud Platform's AI models, are used for generating artificial intelligence. This allows for appropriate matching and content generation based on collected characteristic information.

[0613] As a concrete example, user A, an elderly person using a terminal, is matched with another user B, who is interested in gardening. The server provides relevant gardening information and seasonal advice via a generative AI, stimulating dialogue between the two users. This process also generates new topics from the generated information. By utilizing the generative AI model, users can receive relevant trivia and questions while watching content related to their shared hobby. An example of a prompt might be, "Generate relevant trivia and questions while the user is watching content related to their shared hobby. These questions should encourage discussion based on location information related to the movie they are watching."

[0614] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0615] Step 1:

[0616] The user uses their device to create an account and enter information about their interests and preferences. This input data includes name, age, hobbies, and interests, and is sent from the device to the server. The server receives this data and stores it in a database. Based on the input information, a user profile is generated in the database.

[0617] Step 2:

[0618] The server uses a generative AI model to analyze profile information in the database. It uses user profiles as input to select users with common hobbies and interests. The AI ​​model analyzes data patterns and outputs the most suitable matching candidates. The server then generates a message to notify the user of the results.

[0619] Step 3:

[0620] The user confirms the matching results on their device and gives their approval. The server then sets up an electronic communication environment between the selected users via the communication network. The server sends connection information to the user's device, providing a platform for two-way communication.

[0621] Step 4:

[0622] The server-based AI generates information and topics to stimulate conversation. It uses data on the matched users' shared interests as input to generate relevant content. This information is sent to the user's device and used as material to facilitate dialogue. As a result, users receive interesting trivia and questions in real time.

[0623] Step 5:

[0624] Once the interaction with the user is complete, the device sends feedback to the server. This feedback is taken in as input data and used to improve the algorithm of the generating AI. The server analyzes this feedback to improve the accuracy of future matching and dialogue support.

[0625] 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.

[0626] This invention is a system that combines generative artificial intelligence and an emotion engine to effectively promote online interaction among users. Specific embodiments of this system are described below.

[0627] User registration and information gathering

[0628] Users access the application through their device and register by entering their name, age, hobbies, and interests. This information is stored in a database by the server, and a profile is created.

[0629] Matching and interaction begin

[0630] The server uses generative artificial intelligence to analyze users' interests and preferences and match them with other users. The generative AI selects users with common hobbies and interests and sends notifications to candidates. Once a user approves the match, the server sets up an online communication environment such as LINE via the communication network to facilitate interaction.

[0631] Conversation support and emotion recognition

[0632] Within the online communication environment, a generative AI provides topics and relevant information to stimulate conversation, while an emotion engine recognizes the user's emotions in real time. The emotion engine analyzes the user's facial expressions and voice tone to determine their emotional state. Based on this emotional information, the server adjusts the tone and content of the conversation accordingly, resulting in a more natural and personalized interaction.

[0633] Feedback gathering and algorithm adjustments

[0634] After the interaction ends, users are asked to provide feedback via their devices. The feedback information provided by users is collected on a server and used to improve the algorithms of the generating AI and the functionality of the emotion engine. This continuously improves the accuracy and effectiveness of the entire system so that a better experience can be provided in the next interaction.

[0635] Specific example

[0636] For example, if elderly person A, who has registered through their device, is interested in "listening to music," the server will select person B, who shares the same interest, as a matching partner and begin online communication. When the emotion engine recognizes A's joyful expression, the generative AI will suggest music-related topics and questions, facilitating further interaction and conversation. Depending on A's mood, the generative AI will also suggest new genres of music to broaden their interests. After the interaction ends, user feedback is used to improve the quality of future matching and conversation support.

[0637] The following describes the processing flow.

[0638] Step 1:

[0639] The terminal launches the application, and the user accesses the registration screen. The user enters information such as name, age, hobbies, and interests, and registers. The server receives this information and stores it in a database. Based on the stored information, the server generates a profile ID for each user.

[0640] Step 2:

[0641] The server periodically scans the database to analyze user interests and preferences. Generating AI analyzes the user's profile and selects other users with similar interests. The server notifies the user of the selected matching candidates. The user receives the notification on their device and accepts the match.

[0642] Step 3:

[0643] The server invites matched users to an online communication environment such as LINE via the communication network. Users accept the invitation through their devices and begin online interaction. Interaction takes place via text chat and video calls.

[0644] Step 4:

[0645] During online communication, an emotion engine collects emotional data from the user's camera and microphone. Based on the emotional information recognized by the emotion engine, the server uses generative AI to adjust the tone and topics of the conversation. For example, if the generative AI determines that the user is excited, it will offer relevant and interesting topics to liven up the conversation.

[0646] Step 5:

[0647] After the interaction, a feedback form is sent to the user via their device. The user enters their thoughts and suggestions for improvement regarding the interaction and sends them to the server. The server analyzes this feedback information and adjusts the algorithms of the generation AI and emotion engine. These improvements will enhance the accuracy of future matching and the quality of conversational support.

[0648] (Example 2)

[0649] 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".

[0650] In online communication, there is a need to appropriately match users, effectively stimulate dialogue, and provide personalized experiences that respond to individual emotional states. However, current technology faces the challenge of accurately understanding users' hobbies, preferences, and emotional states, and continuously improving the system based on their feedback.

[0651] 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.

[0652] In this invention, the server includes means for acquiring and storing user identification information, means for selecting other users based on the acquired identification information using computing resources and associating the selected users with each other, means for providing a virtual communication environment in which the selected users can interact via a communication network, means for determining the user's emotions using an emotion recognition function and adjusting the content of the conversation based on the determined emotion information, and means for collecting evaluation information from the user and modifying the procedures of the computing resources based on the evaluation information. This enables appropriate matching based on the user's hobbies, preferences, and emotional state, the provision of personalized conversations, and continuous improvement of the system by utilizing feedback.

[0653] "Identifiable information" refers to identifiable data about the user, such as their name, age, hobbies, and interests.

[0654] "Computational resources" refers to algorithms such as generative artificial intelligence and emotion recognition engines, and the combination of hardware and software used to execute them.

[0655] "Communication network" refers to network infrastructure for transmitting digital information, including the internet and mobile communications.

[0656] A "virtual communication environment" refers to an environment where users can communicate with each other in a digital space through messaging platforms such as LINE.

[0657] "Emotion recognition function" refers to technology that analyzes the user's facial expressions, voice tone, etc., to determine their current emotional state.

[0658] "Evaluation information" refers to feedback data provided by users based on their interaction experiences.

[0659] This invention is a system that combines a generative AI model and an emotion recognition engine to facilitate appropriate online interaction among users. Users access the application using a terminal and register by entering their specific information. The data transmitted from the terminal is stored in a database by the server.

[0660] The server uses stored specific information and leverages generative AI models, which are computational resources, to analyze the user's hobbies and preferences. Based on this analysis, it selects other users with common interests and performs matching. After matching, the server provides a virtual communication environment via a communication network. This environment is built using messaging platforms such as LINE, and users begin interacting with each other.

[0661] Within the communication environment, the server uses a generative AI model to suggest prompts and relevant information to stimulate conversation. For example, it generates prompts such as, "Are there any artists you've been interested in lately?" to help the conversation flow smoothly.

[0662] Furthermore, the emotion recognition function analyzes the user's facial expressions and voice tone in real time to determine their emotional state. Based on this emotional information, the server adjusts the content and tone of the conversation to achieve a more natural and personalized interaction.

[0663] Furthermore, after the interaction ends, the server collects feedback from the terminal and uses this evaluation information to improve the algorithms and emotion recognition functions of the generated AI model. This continuously improves the overall performance and accuracy of the system in order to provide users with a better experience in the next interaction.

[0664] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0665] Step 1:

[0666] Users access the application using their device and enter specific information such as their name, age, hobbies, and interests. This information is sent from the device to the server. The server stores the received information in a database and generates a user profile. This profile forms the basis for matching in subsequent processing.

[0667] Step 2:

[0668] The server retrieves user identification information stored in the database and activates a generative AI model. The generative AI model analyzes the user's interests and preferences and selects other users who share common identification information. As a result of this analysis, a list of potential matching users is generated. Based on this list, the server notifies the user of any matching opportunities.

[0669] Step 3:

[0670] When a user accepts a matching notification, the server uses the network to set up a virtual communication environment such as LINE. In this environment, the selected users can begin a conversation. The server then uses a generative AI model to generate and provide prompts to stimulate the conversation. For example, it might output a prompt such as, "Tell me about your favorite music lately."

[0671] Step 4:

[0672] Within the virtual communication environment, emotion recognition functions analyze the user's facial expressions and voice tone in real time to determine their emotional state. The server then adjusts the content and tone of the dialogue based on the acquired emotion data. This process makes the conversation more natural and personalized. In particular, the generative AI model provides more relevant prompts as the conversation progresses.

[0673] Step 5:

[0674] After an interaction ends, the server collects feedback from the user via the terminal. This feedback information is important data, including user satisfaction and suggestions. The server analyzes this data and uses the evaluation information to improve the generative AI model and the algorithms for emotion recognition. Incorporating feedback improves the overall accuracy of the system, enabling it to provide a better experience for future interactions.

[0675] (Application Example 2)

[0676] 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".

[0677] Traditional online communication systems, even with matching based on user interests and preferences, sometimes fail to facilitate smooth conversations between users. Furthermore, in physical stores, it's difficult to grasp customer interests and emotions in real time and provide appropriate products and information. This results in an inability to effectively stimulate customer purchasing intent and missed sales opportunities. To address this challenge, a more dynamic and personalized information delivery system that transcends the boundaries between online and offline is required.

[0678] 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.

[0679] In this invention, the server includes means for collecting user interest and preference information, means for selecting other users based on the collected interest and preference information using generative artificial intelligence and matching the selected users with each other, means for providing an online communication environment in which the selected users can interact with each other via a communication network, means for the generative artificial intelligence to provide information to facilitate conversation within the online communication environment, and means for analyzing the user's facial expressions in real time using an image acquisition device to perform emotion analysis and providing specific item information using the analyzed emotion information. This enables not only the smooth promotion of conversations between users via online communication but also the provision of optimized information to customers in physical stores.

[0680] "User" refers to an individual or group that utilizes the system or device, provides information about their interests and preferences, and enjoys online or in-store experiences.

[0681] "Generative artificial intelligence" is a technology that analyzes data given in a digital environment, generates or processes information according to an intended purpose, and enables intelligent behavior similar to that of humans.

[0682] "Matching" is the process of appropriately combining users based on specific criteria, and it plays a role in promoting interactions that match their interests and preferences.

[0683] An "online communication environment" is a technological foundation that provides a platform enabling users to interact with each other in real time via the internet or other digital networks.

[0684] "Emotional analysis" is a technique used to analyze and judge a user's emotional state from their facial expressions, voice, etc., in order to understand their psychological condition.

[0685] An "image acquisition device" is a device that captures photographs and videos, and is used to acquire visual data such as the user's facial expressions in real time.

[0686] "Product information" refers to detailed information about a specific product and is part of a product introduction that is suggested based on the user's interests and feelings.

[0687] The system for carrying out this invention consists of a server, a terminal, and an interface with the user.

[0688] The server collects user interest and preference information via digital input and analyzes it using generative artificial intelligence. Based on the analyzed data, it selects and matches other users with similar interests. This process utilizes a database management system and data analysis tools such as Python and R.

[0689] The terminal provides an online communication environment to enable smooth communication between selected users. This allows for real-time voice and video communication via the internet, and may utilize video call technologies such as WebRTC as software libraries.

[0690] Furthermore, to perform emotion analysis, a camera built into the device (specifically, smart glasses or a headset with camera functionality) captures the user's facial expressions in real time. Based on this visual data, the emotional state is analyzed using an image processing library such as OpenCV. The analysis results are then sent to a server and fed back as specific item information optimized for the user's emotions.

[0691] As a concrete example, a service could be provided where product information corresponding to the location where a customer stops smiling in a store is displayed on the smart glasses' screen. In this case, the generating AI would generate a message such as, "We recommend this Pinot Noir to customers who have previously purchased red wine. Would you like information about a tasting?" Furthermore, an example of a prompt to the generating AI model would be, "Please provide prompts to develop a real-time recommendation system for product information that will interest customers in the store, based on their facial expressions and purchase history." This overall system configuration enables personalized information provision based on individual interests and emotions.

[0692] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0693] Step 1:

[0694] Users use their devices to input their interests, preferences, and basic profile information. This information is sent to a server and stored in a database. Based on this stored information, a user profile is created using a database management system.

[0695] Step 2:

[0696] The server uses artificial intelligence to analyze users' interests and preferences based on stored profile information. The analyzed data is used for matching with other users. Using data analysis tools, commonalities between profiles are identified and selected as potential interaction candidates. This selected information is sent to the target users through a notification system.

[0697] Step 3:

[0698] The selected users access an online communication environment on their devices and connect with other selected users. Communication takes place in real time, with voice and video transmitted via calling software. In this step, a video calling library such as WebRTC is running to facilitate communication between users.

[0699] Step 4:

[0700] The camera on the device captures the user's facial expressions and sends the visual data to the server. The server processes this visual data using OpenCV and analyzes the user's emotional state. The analysis results are sent to a generating AI, which then generates information based on those emotions.

[0701] Step 5:

[0702] The generating AI uses analyzed emotional data and pre-collected preference data to generate optimal product information and suggestions for the user. This information is displayed on the device's screen and provided to the user. For example, information that a particular product is on sale might be displayed on the smart glasses' screen. Other specific suggestions are generated in a similar manner.

[0703] Step 6:

[0704] After the interaction ends, users send feedback via their devices. This feedback is collected on the server and used to improve the algorithms and sentiment analysis functions of the generated AI model. This will improve the quality of future matching and information provision.

[0705] 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.

[0706] 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.

[0707] 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.

[0708] 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.

[0709] 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.

[0710] 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.

[0711] 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.

[0712] 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.

[0713] 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."

[0714] 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.

[0715] 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.

[0716] 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.

[0717] 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.

[0718] 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.

[0719] 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.

[0720] 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.

[0721] 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.

[0722] 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.

[0723] 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.

[0724] 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.

[0725] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0726] The following is further disclosed regarding the embodiments described above.

[0727] (Claim 1)

[0728] A means of collecting information on the user's interests and preferences,

[0729] A means of using generative artificial intelligence to select other users based on collected interest and preference information, and to match selected users with each other.

[0730] A means of providing an online communication environment that allows selected users to interact with each other via a communication network,

[0731] The aforementioned generating artificial intelligence provides means for providing information to facilitate conversation within an online communication environment,

[0732] A system that includes this.

[0733] (Claim 2)

[0734] The system according to claim 1, characterized in that the information provided by the generating artificial intelligence within an online communication environment is related to the user's interests and conversation topics.

[0735] (Claim 3)

[0736] The system according to claim 1, further comprising means for collecting feedback information from users and adjusting the algorithm of the generated artificial intelligence based on the feedback information.

[0737] "Example 1"

[0738] (Claim 1)

[0739] Means for collecting user attribute information,

[0740] A means of using a generative model to select other users based on collected attribute information and to connect the selected users with each other,

[0741] A means of providing a virtual communication environment in which selected users can interact with each other via a communication network,

[0742] The generative model provides means for providing information to facilitate dialogue within a virtual interaction environment,

[0743] A system that includes means for collecting user feedback and adjusting the generative model based on that feedback.

[0744] (Claim 2)

[0745] The system according to claim 1, characterized in that the information provided by the generative model within the virtual interaction environment is themes and dialogue content related to the user's preferences.

[0746] (Claim 3)

[0747] The system according to claim 1, further comprising means for improving the generative model based on collected opinion information.

[0748] "Application Example 1"

[0749] (Claim 1)

[0750] Means for collecting user characteristics,

[0751] A means of using generative artificial intelligence to select other users based on collected characteristics and to link the selected users together,

[0752] A means of providing an electronic communication environment that allows selected users to interact with each other via a communication network,

[0753] The aforementioned artificial intelligence provides means for facilitating dialogue within an electronic communication environment,

[0754] The aforementioned generating artificial intelligence provides relevant content based on the user's shared interests and has means to prompt dialogue based on that content.

[0755] A system that includes this.

[0756] (Claim 2)

[0757] The system according to claim 1, characterized in that the information provided by the generating artificial intelligence within an electronic communication environment is related to the user's hobbies and serves as the subject of the conversation.

[0758] (Claim 3)

[0759] The system according to claim 1, further comprising means for collecting information from users and adjusting the technology of generated artificial intelligence based on that information.

[0760] "Example 2 of combining an emotion engine"

[0761] (Claim 1)

[0762] Means for acquiring and storing user identification information,

[0763] A means of using computing resources to select other users based on acquired specific information and to associate the selected users with each other,

[0764] A means of providing a virtual communication environment in which selected users can interact via a communication network,

[0765] The computing resources include means for presenting materials to facilitate dialogue within a virtual communication environment,

[0766] A means of determining the user's emotions using emotion recognition functionality and adjusting the content of the dialogue based on the determined emotion information,

[0767] A means of collecting evaluation information from users and modifying the procedures for computing resources based on that evaluation information,

[0768] A system that includes this.

[0769] (Claim 2)

[0770] The system according to claim 1, characterized in that the materials provided by the computing resources within the virtual communication environment are topics and conversation content related to the user's specific interests.

[0771] (Claim 3)

[0772] The system according to claim 1, further comprising means for dynamically adjusting the content or tone of a dialogue based on the user's emotional state.

[0773] "Application example 2 when combining with an emotional engine"

[0774] (Claim 1)

[0775] A means of collecting information on the user's interests and preferences,

[0776] A means of using generative artificial intelligence to select other users based on collected interest and preference information, and to match selected users with each other.

[0777] A means of providing an online communication environment that allows selected users to interact with each other via a communication network,

[0778] The aforementioned generating artificial intelligence provides means for facilitating conversations within an online communication environment,

[0779] A means of providing information about a specific item by using an image acquisition device to analyze the user's facial expressions in real time for emotion analysis, and by using the analyzed emotion information.

[0780] A system that includes this.

[0781] (Claim 2)

[0782] The system according to claim 1, characterized in that the information provided by the generating artificial intelligence within an online communication environment is related to the user's interests and conversation topics, and further recommends specific items based on emotional information.

[0783] (Claim 3)

[0784] The system according to claim 1, further comprising means for collecting user feedback information and adjusting the settings of the generated artificial intelligence algorithm and emotion engine based on that feedback information. [Explanation of symbols]

[0785] 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 of collecting information on the user's interests and preferences, A means of using generative artificial intelligence to select other users based on collected interest and preference information, and to match selected users with each other. A means of providing an online communication environment that allows selected users to interact with each other via a communication network, The aforementioned generating artificial intelligence provides means for providing information to facilitate conversation within an online communication environment, A system that includes this.

2. The system according to claim 1, characterized in that the information provided by the generating artificial intelligence within an online communication environment is related to the user's interests and conversation topics.

3. The system according to claim 1, further comprising means for collecting feedback information from users and adjusting the algorithm of the generated artificial intelligence based on the feedback information.

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