system

Abstract

We provide the system. [Solution] A data storage means for storing information entered by the user, A matching method that recommends relevant tasks to users based on saved information, Communication means to facilitate information exchange between users, Information provision means that provide the latest information on environmental protection, 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 persona chatbot control method 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 chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Many individuals and groups interested in forest protection feel it difficult to participate in related jobs and projects. In particular, the problems are the lack of information for accessing appropriate projects and the difficulty of finding activities that match their skills and interests. Furthermore, due to the isolated progress of individual activities, the sharing of knowledge and experience does not progress, and it is difficult to realize effective forest protection activities.

Means for Solving the Problems

[0005] This invention expands opportunities to participate in appropriate projects and jobs by providing a matching means that stores information entered by users and recommends relevant tasks based on that stored information. Furthermore, by providing communication means to facilitate information exchange among users and offering the latest information on environmental protection, it enables participants to share knowledge and experience with each other and promote effective forest conservation activities.

[0006] A "user" refers to an individual or group that uses this system to enter registration information or participate in projects.

[0007] "Information" refers to profile information such as skills, interests, and location registered by users, and is the data used for matching and recommendations.

[0008] A "data storage means" is a part of a system that has the function of collecting registered information and storing it for use in later matching and recommendations.

[0009] A "matching tool" is a component of a system that has the function of recommending relevant activities and jobs based on saved user information.

[0010] "Communication methods" refer to system elements that have functions such as chat and forums to facilitate information exchange and communication among users.

[0011] "Information provision means" refers to the part of a system that has the function of collecting the latest information on environmental protection and disseminating it to users in an easy-to-understand manner. [Brief explanation of the drawing]

[0012] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It 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] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0013] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described according to the accompanying drawings.

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

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

[0016] In the following embodiments, the numbered RAM (Random Access Memory) is a memory where information is temporarily stored and is used as a work memory by the processor.

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

[0018] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

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

[0020] [First Embodiment]

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

[0022] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

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

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

[0025] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

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

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

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

[0029] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

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

[0031] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

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

[0033] This invention is implemented as a system for appropriately matching users with relevant activities and projects based on their input information. This system mainly consists of four main elements: data storage means, matching means, communication means, and information provision means.

[0034] First, users input their skills, interests, and local information using their device. This data is sent from the device to a server and stored using data storage technology. The stored information is then registered as the user's profile.

[0035] Next, the server uses a matching system to recommend relevant activities and projects based on the saved profile information. This process selects the most suitable project, taking into account skills, interests, and geographical conditions. The matching results are notified to the device, and the user can view detailed information.

[0036] Furthermore, the server is equipped with communication capabilities, allowing users to exchange information and engage in discussions. This feature provides online forums and chat rooms, enabling users to share their experiences and knowledge with others.

[0037] The information provision system plays the role of organizing the latest environmental protection information collected from external sources by the server and delivering it to users. This allows users to acquire the latest knowledge and use it to their advantage in their own activities.

[0038] As a concrete example, if a user is interested in forest surveys, they input the skill "Forest Survey" and the region "Hokkaido" into the system, and the server saves this information in a data storage device. Using a matching mechanism, the server finds a suitable forest survey project and notifies the user. The user views this information on their terminal and decides to participate in the project. During this time, they can communicate with other project participants using communication tools and obtain the information and knowledge necessary for the project. In this way, users can efficiently contribute to forest conservation activities while making use of their skills.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] Users access the registration page using their devices and enter their skills, interests, and location information. This information forms the basis for matching.

[0042] Step 2:

[0043] The terminal sends the entered information to the server. The server receives this information and stores it in a database using a data storage device.

[0044] Step 3:

[0045] The server periodically retrieves project and work information from the database. This retrieval is done by collecting publicly available information on new projects.

[0046] Step 4:

[0047] The server matches the user's profile information with project information. This allows it to select the project that best matches the user's skills, interests, and geographical location.

[0048] Step 5:

[0049] The server sends the matching results to the relevant users' devices. Users can receive notifications of matched projects through their devices and view detailed information.

[0050] Step 6:

[0051] By utilizing the communication methods provided by the server, users can interact with other participants in online forums and chats. This facilitates the sharing of necessary information and experiences.

[0052] Step 7:

[0053] The server collects the latest environmental protection information from external sources and distributes it to users through information delivery channels. Users can then view this information on their devices and incorporate it into their own activities.

[0054] (Example 1)

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

[0056] While much information is currently available via the internet, the process of obtaining it has resulted in an excessive amount of data, making it difficult for individual users to discover appropriate activities and plans tailored to their abilities, interests, and local information. Furthermore, there is a lack of systems that enable participants to effectively share their knowledge and experience and utilize the latest information. Therefore, users face challenges in efficiently utilizing information and participating in meaningful activities.

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

[0058] In this invention, the server includes information storage means for storing user inputs regarding abilities, interests, and local information; matching means for analyzing the user's abilities, interests, and local conditions in order to recommend activities and plans based on the stored information; and communication support means for sharing knowledge and experience among users. This enables users to easily find appropriate activities and plans, communicate effectively with other users, and participate in activities efficiently by utilizing the latest information.

[0059] "Information storage" refers to the function of saving user-entered information about abilities, interests, and local area as digital data.

[0060] "Matching" is the process of analyzing users' abilities, interests, and local conditions based on their stored data in order to select suitable activities and plans.

[0061] "Communication support" refers to a function that facilitates the exchange of information and dialogue in order to mutually share knowledge and experiences among users.

[0062] "Information distribution" is a function that takes the role of organizing the latest knowledge obtained from external sources and delivering it to users.

[0063] "Capability" refers to the knowledge and skills a user possesses in a specific field, and is an attribute used in selecting activities and plans within the system.

[0064] "Interest" refers to information that indicates the degree of interest or involvement a user has in a particular activity or field.

[0065] "Local information" refers to geographical data about the places where users live or can engage in activities.

[0066] "Activities and plans" refer to specific projects or events that users can consider participating in or engaging with.

[0067] This invention is an embodiment of a system aimed at efficiently matching many users with appropriate and interesting activities and plans based on their abilities, interests, and local information.

[0068] The server uses information storage means to store data received from users, namely skills, interests, and location information. Hardware-wise, the database server works in conjunction with the communication server to ensure high-speed and secure data storage. Software-wise, an SQL-based database management system is used to design and optimize the data structure.

[0069] Next, the matching process is executed. In this process, the server applies an algorithm to analyze the user's saved profile and select the most suitable activities and plans from among the relevant ones. By applying a generative AI model, a recommendation system based on the user's attributes is realized. This technology matches users with projects that are particularly compatible with their skills and interests.

[0070] The terminal notifies the user of the selection results from the server. The user can view details of the recommended activities and plans on the terminal and decide whether or not to participate. During this time, the user receives information about the project's start date, location, and participation requirements.

[0071] Furthermore, the server provides communication support. The virtual communication platform allows participants to interact and share information and knowledge with each other. This primarily includes online forums and chat functions, contributing to the project's success by enabling participants to exchange experiences.

[0072] Through information distribution channels, the server collects and provides users with the latest information about the environment. This allows users to acquire new knowledge in real time and use it to aid in decision-making.

[0073] For example, if a user possesses the skill of "forest surveying" and wishes to participate in a project in the Hokkaido region, the server will select a forest conservation project that matches their "forest surveying" skill and notify the user. Furthermore, the user can interact with other project participants and advance the project while utilizing the latest environmental information.

[0074] An example of a prompt message might be: "Please describe a system that finds the most suitable project based on the user's skills and location information. Please explain in detail the matching process using a specific example."

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

[0076] Step 1:

[0077] Users input their skills, interests, and local information using a terminal. This information includes specific skills and desired areas of activity. The terminal reviews the entered data and verifies that it is in the correct format. Once input is complete, the terminal sends this data to the server.

[0078] Step 2:

[0079] The server stores the received user data using information storage means. Specifically, this involves registering the user's profile information in the database system. Based on this information, the database organizes the user's abilities, interests, and location information into categories and sets up indexes for quick access.

[0080] Step 3:

[0081] The server analyzes the user profile using matching mechanisms and selects highly relevant activities and plans from the project database. This process uses a generative AI model to compare the user's input information with project requirements and calculate a matching score. This then lists the most suitable project candidates.

[0082] Step 4:

[0083] The server creates recommended project information and sends it to the terminal. The terminal receives this and notifies the user. Specifically, it renders a UI to display the project overview, details, participation requirements, etc., and allows the user to view it.

[0084] Step 5:

[0085] Users view project details on their devices and decide whether or not to participate. After making a decision, they send their intention to participate from their device to the server, which then updates the project participant list by linking that information to it.

[0086] Step 6:

[0087] The server enables information sharing among project participants using communication support tools. It sets up virtual forums and chat systems, allowing participants to freely initiate communication. This functionality allows users to share their knowledge and experience and monitor project progress.

[0088] Step 7:

[0089] The server uses information distribution methods to organize and provide users with the latest information obtained from external sources. The information is updated in real time and notified to users via their terminals. This allows users to always have the latest knowledge and reflect it in their activities.

[0090] (Application Example 1)

[0091] 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."

[0092] In online shopping, it is time-consuming for users to find products based on their interests and purchase history, so there is a need for efficient product recommendation systems. Furthermore, there is a lack of means for users to exchange information about products with each other and obtain reliable feedback. As a result, the shopping experience is not personalized.

[0093] 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.

[0094] In this invention, the server includes a data storage device for storing information entered by the user, a matching device for recommending relevant products to the user based on the stored information, and a communication device for facilitating information exchange between users. This allows users to efficiently find products based on their interests and purchase history, and to receive reliable feedback through information exchange with other users.

[0095] A "user" is an individual who uses the system to search for products or exchange information with other users.

[0096] A "data storage device" is a device that stores information entered by a user and has the function of retrieving it as needed.

[0097] A "product" is an item or service recommended to a user for sale.

[0098] A "matching device" is a device that has the function of selecting and recommending relevant products based on stored user information.

[0099] A "communication device" is a device that has functions to facilitate information exchange between users, such as providing online bulletin boards and chat services.

[0100] This invention is a system that provides personalized product recommendations based on users entering their interests and purchase history into a device such as a smartphone. The server stores the entered information in a data storage device and recommends appropriate products using a matching device. This process involves data processing using machine learning models. Specifically, it utilizes frameworks such as TENSORFLOW® and PyTorch to execute a product recommendation algorithm based on the user's interests.

[0101] The server also features communication equipment to facilitate information exchange between users, providing online bulletin boards and real-time chat. This functionality utilizes WebSocket and RESTful APIs to enable highly immediate information exchange.

[0102] For example, if a user enters that they are interested in "eco-bags," the system can take into account their past purchase history and local information to recommend products made with organic materials. Furthermore, sharing information on message boards with other users allows for reliable feedback on product reviews and user experiences.

[0103] An example of a prompt to input into the generating AI model is, "If a user shows interest in eco-bags, how would you recommend related products?"

[0104] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0105] Step 1:

[0106] The user uses a device to input their interests and purchase history. The device converts this information into data packets and sends them to the server. The input consists of interest keywords and past purchase information, and the output is data packets.

[0107] Step 2:

[0108] The server stores the received data packets in its data storage device. Here, the server performs database operations to update the user's profile information. The input is the data packets, and the output is the updated user profile.

[0109] Step 3:

[0110] The server uses a matching device to recommend products based on stored profile information. The server utilizes a generative AI model to extract features based on input data and select the most suitable product. The input is the user profile, and the output is a list of recommended products.

[0111] Step 4:

[0112] The server uses a communication device to send recommendation results to the terminal. The terminal displays the received list of recommended products to the user. The input is the list of recommended products, and the output is the product information displayed to the user.

[0113] Step 5:

[0114] Users can exchange information with other users based on the displayed product information. The device utilizes real-time chat and bulletin board functions via the server during this process. Input consists of the user's message content, while output is feedback from other users.

[0115] Step 6:

[0116] The server analyzes communication between users and accumulates feedback data on products. This allows the server to obtain data to improve the accuracy of subsequent recommendations. The input is feedback data, and the output is accumulated data.

[0117] 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.

[0118] This invention implements a system that combines an emotion engine to perform information matching and provision that takes user emotions into consideration. The system is equipped with a data storage means, matching means, communication means, information provision means, and an emotion engine.

[0119] First, users input their skills, interests, and local information using a device, thereby creating a profile. The device then sends this information to a server, which stores it in a database using a data storage device.

[0120] Next, the emotion engine recognizes the user's emotions based on the information and behavioral data entered by the user. This emotion information is used to recommend projects and activities optimized for each individual user. Specifically, the server selects projects using a matching method based on the emotions recognized by the emotion engine. As a result, activities and information that match the user's current emotions are notified to the device.

[0121] Furthermore, the emotion engine also influences communication methods. For example, if a user is feeling stressed, communication is optimized by recommending supportive messages in online forums.

[0122] In addition, the emotion engine adjusts how information is presented in the means of information delivery. For example, if a user is in a curious state, detailed and educational content will be presented.

[0123] For example, when a user joins a project, if the emotion engine recognizes that the user is confident, the server will recommend challenging projects or roles. Conversely, if the user is feeling anxious, projects that offer support and guidance will be recommended. In this way, users can choose the activity best suited to their emotions and contribute to forest conservation.

[0124] The following describes the processing flow.

[0125] Step 1:

[0126] Users access the registration page using their devices and enter their skills, interests, and location information. Users also provide sentiment data through periodic surveys and feedback within the system. This information is used to process the sentiment engine.

[0127] Step 2:

[0128] The terminal sends this input information to the server. The server receives the information and stores it in a database using data storage means. Sentiment data is also stored at this time and combined with other information to prepare for later analysis.

[0129] Step 3:

[0130] The server uses an emotion engine to analyze the user's emotional state in real time. This analysis is based on the user's input data, behavioral history, and response results. This process identifies the user's current emotional state.

[0131] Step 4:

[0132] The server uses matching mechanisms to select appropriate projects and activities based on the user's emotional state. For example, if the user is in a positive emotional state, a challenging project will be selected; if they are in a negative emotional state, a supportive or educational project will be chosen. This selection result is notified to the user's device.

[0133] Step 5:

[0134] Users review the selection results on their devices and decide whether to participate in projects that interest them.

[0135] Step 6:

[0136] The server optimizes the communication style to match the user's emotional state through the communication channels. This includes recommended tones within forums and customization of message content.

[0137] Step 7:

[0138] The server organizes information obtained from external sources using information delivery methods and delivers the information in a way that suits the user's emotional state. For example, a highly curious user might be provided with a detailed analytical article.

[0139] Through this step, users can engage with the project in a way that best suits their own emotions and effectively carry out forest conservation activities.

[0140] (Example 2)

[0141] 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".

[0142] Conventional information delivery systems have a problem in that they do not adequately consider the emotions and individual characteristics of users when optimizing information delivery and communication. As a result, users are not provided with the most suitable information and activities, leading to problems such as decreased satisfaction and efficiency.

[0143] 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.

[0144] In this invention, the server includes a storage means for storing information entered by the user, a matching means using an emotion analysis engine that performs emotion recognition to recommend tasks relevant to the user based on the stored information and behavioral data, and a communication means for optimizing information exchange between users. This enables optimal information provision and communication according to the emotional state of the user.

[0145] A "user" is an entity that uses the system to input information and receive recommendations for activities.

[0146] "Memory means" refers to a device or method for storing information entered by a user as data.

[0147] "Action data" refers to information obtained from the user's actions and operations, and is used for emotion recognition.

[0148] An "emotion analysis engine" is a program or algorithm used to recognize and analyze a user's emotions.

[0149] A "matching method" is a method or system for recommending the most suitable tasks or projects based on the user's emotions and stored information.

[0150] "Communication means" refers to a method or device for optimizing the process of exchanging information between users.

[0151] "Information provision means" refers to a method or system for appropriately displaying and providing information that is highly relevant to the user.

[0152] The following describes "modes for carrying out the invention."

[0153] ---

[0154] The system of this invention is implemented with the following configuration.

[0155] The user first uses a device to input their skills, interests, and local information. This device is expected to be an information processing device such as a regular computer or smartphone. This information is configured as a profile and sent from the device to the server.

[0156] The server stores the received information in a database using data storage means. A general-purpose database management system (DBMS) can be used for this storage.

[0157] Next, the server uses an emotion analysis engine to recognize emotions from the user's input information and behavioral data. This emotion analysis engine utilizes existing generative AI models and can analyze emotional states using natural language processing (NLP) techniques. For example, it can determine an emotion from a user's text comments.

[0158] The server uses a matching mechanism to select the most suitable tasks and projects for the user based on emotional information obtained by the emotion analysis engine. The selected results are notified to the terminal via communication. This allows the user to receive activities and information that are appropriate for their current emotions.

[0159] For example, if a user comments "I'm tired" when logging in, the sentiment analysis engine will analyze this information and recommend relaxing activities. An example of a prompt to input into the generative AI model might be, "Please suggest activities to recommend when a user is feeling 'tired'."

[0160] In this way, the system takes into account the user's emotional state and enables the delivery of personalized information.

[0161] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0162] Step 1:

[0163] Users use their devices to input their skills, interests, and local information. This input data is collected in text format and built into a profile. If a user indicates an interest in "programming" and "nature conservation," that data is sent to the server.

[0164] Step 2:

[0165] The terminal sends the collected user profile information to the server. The server receives this information and stores it in a data storage device using a database management system (DBMS). For example, it might execute an "INSERT" query using SQL and save it to the database.

[0166] Step 3:

[0167] The server retrieves user information and behavioral data from the database. Next, it uses an emotion analysis engine incorporating a generative AI model to recognize the user's emotions. This process uses natural language processing to analyze text data and identify emotions. For example, emotional states such as "highly motivated" or "tired" might be output.

[0168] Step 4:

[0169] The server uses matching mechanisms based on recognized emotional information to select the most suitable tasks and projects for the user. The selection process uses algorithms to determine the option that best matches the user's interests, skills, and emotional state. As a result, specific projects and activities are selected.

[0170] Step 5:

[0171] The terminal receives notifications of activities and information selected by the server. These notifications are formatted and displayed in a way that is appropriate to the user's mood. For example, "relaxing volunteer activities" or "challenging coding assignments" may be available.

[0172] Step 6:

[0173] Based on the suggestions the user receives, they can choose to participate in an actual activity or view the information. This result is recorded again as data to be used for personalized suggestions in the future.

[0174] (Application Example 2)

[0175] 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".

[0176] E-commerce sites are expected to improve the user's shopping experience and, consequently, enhance commercial performance by recommending appropriate products based on the user's emotions. However, current systems struggle to provide product recommendations that take emotions into account, and lack the flexibility to respond to users' emotions.

[0177] 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.

[0178] In this invention, the server includes emotion recognition means for detecting the user's emotional state and recommending the most suitable product based on it, data management means for storing information entered by the user, and selection means for recommending activities relevant to the user based on the stored information. This makes it possible to recommend products optimized for the user's emotions and improve the purchasing experience.

[0179] "Data management means" refers to methods for efficiently storing information entered by users and retrieving it as needed.

[0180] "Selection methods" refer to means of analyzing stored information and recommending the most relevant activities and products to the user.

[0181] "Communication control means" are means to facilitate the exchange of information between users and to enable smooth communication.

[0182] "Information distribution means" refers to the means of providing users with the latest information on environmental protection.

[0183] "Emotion recognition means" refers to a method for detecting the emotional state of a user and recommending the most suitable product based on that state.

[0184] An "online communication platform" is a system that provides a space where users can communicate freely.

[0185] The system for realizing this application aims to improve the purchasing experience by detecting the user's emotional state and recommending products based on that emotion. The system includes data management means, selection means, communication control means, information distribution means, and emotion recognition means.

[0186] In this system, the server uses data management tools to efficiently store information entered by users through their terminals. To recognize the user's emotional state, facial recognition software such as Google Cloud Vision API is used as an emotion recognition tool, determining emotions based on video data acquired from the terminal's camera. The server uses TensorFlow to analyze the obtained emotion data and extracts relevant products from the database using a selection tool.

[0187] The extracted product information is transmitted to the terminal via a communication control device, and the terminal uses an information distribution device to present products that are appropriate to the user's emotional state. For example, if the user is feeling stressed, a list of products that help with relaxation will be presented.

[0188] For example, if a user is browsing an online shopping site on their smartphone and the emotion recognition system determines that their current emotion is "stress," the system will generate a prompt saying, "Please recommend products that are suitable for my current emotion," and as a result, the server will display a list of relaxation items.

[0189] Examples of this prompt include the following:

[0190] "What products should be recommended when a user is under stress?"

[0191] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0192] Step 1:

[0193] A user browses an online shopping site using their device, and the camera captures a picture of the user's face. The device receives this facial image data as input and sends it to the Google Cloud Vision API for emotion recognition. The API analyzes this input data and returns the user's emotional state (e.g., joy, stress) as output.

[0194] Step 2:

[0195] The server receives emotional state data sent from the terminal. It analyzes this as input data, runs a generative AI model using TensorFlow, and outputs candidate product categories that best suit the user's emotions. Specifically, it runs an algorithm that evaluates the relationship between emotions and product attributes.

[0196] Step 3:

[0197] The server searches the database for relevant products based on the product category candidates obtained in step 2. It outputs a list of related products as search results. This list includes popular products and products with high review ratings within the category.

[0198] Step 4:

[0199] The server sends the generated list of related products to the terminal via a communication control means. The terminal receives this product list and displays the products to the user using an information distribution means. At this time, product descriptions tailored to the user's mood and links to special feature pages are also presented.

[0200] Step 5:

[0201] The user reviews the presented product list and selects items of interest. This allows them to view detailed pages or proceed with the purchase. For example, a featured page such as "Stress Relief Items" might be displayed.

[0202] 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.

[0203] 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.

[0204] 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.

[0205] [Second Embodiment]

[0206] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0207] 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.

[0208] 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).

[0209] 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.

[0210] 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.

[0211] 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).

[0212] 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.

[0213] 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.

[0214] 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.

[0215] 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.

[0216] 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.

[0217] 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".

[0218] This invention is implemented as a system for appropriately matching users with relevant activities and projects based on their input information. This system mainly consists of four main elements: data storage means, matching means, communication means, and information provision means.

[0219] First, users input their skills, interests, and local information using their device. This data is sent from the device to a server and stored using data storage technology. The stored information is then registered as the user's profile.

[0220] Next, the server uses a matching system to recommend relevant activities and projects based on the saved profile information. This process selects the most suitable project, taking into account skills, interests, and geographical conditions. The matching results are notified to the device, and the user can view detailed information.

[0221] Furthermore, the server is equipped with communication capabilities, allowing users to exchange information and engage in discussions. This feature provides online forums and chat rooms, enabling users to share their experiences and knowledge with others.

[0222] The information provision system plays the role of organizing the latest environmental protection information collected from external sources by the server and delivering it to users. This allows users to acquire the latest knowledge and use it to their advantage in their own activities.

[0223] As a concrete example, if a user is interested in forest surveys, they input the skill "Forest Survey" and the region "Hokkaido" into the system, and the server saves this information in a data storage device. Using a matching mechanism, the server finds a suitable forest survey project and notifies the user. The user views this information on their terminal and decides to participate in the project. During this time, they can communicate with other project participants using communication tools and obtain the information and knowledge necessary for the project. In this way, users can efficiently contribute to forest conservation activities while making use of their skills.

[0224] The following describes the processing flow.

[0225] Step 1:

[0226] Users access the registration page using their devices and enter their skills, interests, and location information. This information forms the basis for matching.

[0227] Step 2:

[0228] The terminal sends the entered information to the server. The server receives this information and stores it in a database using a data storage device.

[0229] Step 3:

[0230] The server periodically retrieves project and work information from the database. This retrieval is done by collecting publicly available information on new projects.

[0231] Step 4:

[0232] The server matches the user's profile information with project information. This allows it to select the project that best matches the user's skills, interests, and geographical location.

[0233] Step 5:

[0234] The server sends the matching results to the relevant users' devices. Users can receive notifications of matched projects through their devices and view detailed information.

[0235] Step 6:

[0236] By utilizing the communication methods provided by the server, users can interact with other participants in online forums and chats. This facilitates the sharing of necessary information and experiences.

[0237] Step 7:

[0238] The server collects the latest environmental protection information from external sources and distributes it to users through information delivery channels. Users can then view this information on their devices and incorporate it into their own activities.

[0239] (Example 1)

[0240] 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".

[0241] While much information is currently available via the internet, the process of obtaining it has resulted in an excessive amount of data, making it difficult for individual users to discover appropriate activities and plans tailored to their abilities, interests, and local information. Furthermore, there is a lack of systems that enable participants to effectively share their knowledge and experience and utilize the latest information. Therefore, users face challenges in efficiently utilizing information and participating in meaningful activities.

[0242] 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.

[0243] In this invention, the server includes information storage means for storing user inputs regarding abilities, interests, and local information; matching means for analyzing the user's abilities, interests, and local conditions in order to recommend activities and plans based on the stored information; and communication support means for sharing knowledge and experience among users. This enables users to easily find appropriate activities and plans, communicate effectively with other users, and participate in activities efficiently by utilizing the latest information.

[0244] "Information storage" refers to the function of saving user-entered information about abilities, interests, and local area as digital data.

[0245] "Matching" is the process of analyzing users' abilities, interests, and local conditions based on their stored data in order to select suitable activities and plans.

[0246] "Communication support" refers to a function that facilitates the exchange of information and dialogue in order to mutually share knowledge and experiences among users.

[0247] "Information distribution" is a function that takes the role of organizing the latest knowledge obtained from external sources and delivering it to users.

[0248] "Capability" refers to the knowledge and skills a user possesses in a specific field, and is an attribute used in selecting activities and plans within the system.

[0249] "Interest" refers to information that indicates the degree of interest or involvement a user has in a particular activity or field.

[0250] "Local information" refers to geographical data about the places where users live or can engage in activities.

[0251] "Activities and plans" refer to specific projects or events that users can consider participating in or engaging with.

[0252] This invention is an embodiment of a system aimed at efficiently matching many users with appropriate and interesting activities and plans based on their abilities, interests, and local information.

[0253] The server uses information storage means to store data received from users, namely skills, interests, and location information. Hardware-wise, the database server works in conjunction with the communication server to ensure high-speed and secure data storage. Software-wise, an SQL-based database management system is used to design and optimize the data structure.

[0254] Next, the matching process is executed. In this process, the server applies an algorithm to analyze the user's saved profile and select the most suitable activities and plans from among the relevant ones. By applying a generative AI model, a recommendation system based on the user's attributes is realized. This technology matches users with projects that are particularly compatible with their skills and interests.

[0255] The terminal notifies the user of the selection results from the server. The user can view details of the recommended activities and plans on the terminal and decide whether or not to participate. During this time, the user receives information about the project's start date, location, and participation requirements.

[0256] Furthermore, the server provides communication support. The virtual communication platform allows participants to interact and share information and knowledge with each other. This primarily includes online forums and chat functions, contributing to the project's success by enabling participants to exchange experiences.

[0257] Through information distribution channels, the server collects and provides users with the latest information about the environment. This allows users to acquire new knowledge in real time and use it to aid in decision-making.

[0258] For example, if a user possesses the skill of "forest surveying" and wishes to participate in a project in the Hokkaido region, the server will select a forest conservation project that matches their "forest surveying" skill and notify the user. Furthermore, the user can interact with other project participants and advance the project while utilizing the latest environmental information.

[0259] An example of a prompt message might be: "Please describe a system that finds the most suitable project based on the user's skills and location information. Please explain in detail the matching process using a specific example."

[0260] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0261] Step 1:

[0262] Users input their skills, interests, and local information using a terminal. This information includes specific skills and desired areas of activity. The terminal reviews the entered data and verifies that it is in the correct format. Once input is complete, the terminal sends this data to the server.

[0263] Step 2:

[0264] The server stores the received user data using information storage means. Specifically, this involves registering the user's profile information in the database system. Based on this information, the database organizes the user's abilities, interests, and location information into categories and sets up indexes for quick access.

[0265] Step 3:

[0266] The server analyzes the user profile using matching mechanisms and selects highly relevant activities and plans from the project database. This process uses a generative AI model to compare the user's input information with project requirements and calculate a matching score. This then lists the most suitable project candidates.

[0267] Step 4:

[0268] The server creates recommended project information and sends it to the terminal. The terminal receives this and notifies the user. Specifically, it renders a UI to display the project overview, details, participation requirements, etc., and allows the user to view it.

[0269] Step 5:

[0270] Users view project details on their devices and decide whether or not to participate. After making a decision, they send their intention to participate from their device to the server, which then updates the project participant list by linking that information to it.

[0271] Step 6:

[0272] The server enables information sharing among project participants using communication support tools. It sets up virtual forums and chat systems, allowing participants to freely initiate communication. This functionality allows users to share their knowledge and experience and monitor project progress.

[0273] Step 7:

[0274] The server uses information distribution methods to organize and provide users with the latest information obtained from external sources. The information is updated in real time and notified to users via their terminals. This allows users to always have the latest knowledge and reflect it in their activities.

[0275] (Application Example 1)

[0276] 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."

[0277] In online shopping, it is time-consuming for users to find products based on their interests and purchase history, so there is a need for efficient product recommendation systems. Furthermore, there is a lack of means for users to exchange information about products with each other and obtain reliable feedback. As a result, the shopping experience is not personalized.

[0278] 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.

[0279] In this invention, the server includes a data storage device for storing information entered by the user, a matching device for recommending relevant products to the user based on the stored information, and a communication device for facilitating information exchange between users. This allows users to efficiently find products based on their interests and purchase history, and to receive reliable feedback through information exchange with other users.

[0280] A "user" is an individual who uses the system to search for products or exchange information with other users.

[0281] A "data storage device" is a device that stores information entered by a user and has the function of retrieving it as needed.

[0282] A "product" is an item or service for sale recommended to users.

[0283] A "matching device" is a device that has the function of selecting and recommending relevant products based on the stored user information.

[0284] A "communication device" is a device that has the function of facilitating information exchange between users and provides an online bulletin board and chat.

[0285] This invention is a system that provides personalized product recommendations by allowing users to input their interests and purchase history into a terminal such as a smartphone. The server stores the input information in a data storage device and uses a matching device to recommend appropriate products. This process includes data processing using a machine learning model. Specifically, frameworks such as TensorFlow and PyTorch are utilized to execute a product recommendation algorithm based on user interests.

[0286] [[ID=

[17] The server also includes a communication device for facilitating information exchange between users and provides an online bulletin board and real-time chat. This function is designed to enable highly immediate information exchange by utilizing WebSocket and RESTful API.

[0287] As a specific example, when a user inputs an interest in "eco bags", the system can recommend products made of organic materials considering the user's past purchase history and regional information. Additionally, through information sharing on the bulletin board with other users, it becomes possible to obtain reliable feedback on product reviews and usage experiences.

[0288] An example of a prompt sentence input to the generative AI model is "When a user shows an interest in eco bags, how do you recommend relevant products?"

[0289] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0290] Step 1:

[0291] The user uses a device to input their interests and purchase history. The device converts this information into data packets and sends them to the server. The input consists of interest keywords and past purchase information, and the output is data packets.

[0292] Step 2:

[0293] The server stores the received data packets in its data storage device. Here, the server performs database operations to update the user's profile information. The input is the data packets, and the output is the updated user profile.

[0294] Step 3:

[0295] The server uses a matching device to recommend products based on stored profile information. The server utilizes a generative AI model to extract features based on input data and select the most suitable product. The input is the user profile, and the output is a list of recommended products.

[0296] Step 4:

[0297] The server uses a communication device to send recommendation results to the terminal. The terminal displays the received list of recommended products to the user. The input is the list of recommended products, and the output is the product information displayed to the user.

[0298] Step 5:

[0299] Users can exchange information with other users based on the displayed product information. The device utilizes real-time chat and bulletin board functions via a server during this process. Input consists of the user's message content, while output is feedback from other users.

[0300] Step 6:

[0301] The server analyzes communication between users and accumulates feedback data on products. This allows the server to obtain data to improve the accuracy of subsequent recommendations. The input is feedback data, and the output is accumulated data.

[0302] 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.

[0303] This invention implements a system that combines an emotion engine with data storage means, matching means, communication means, and information provision means, in addition to the emotion engine.

[0304] First, users input their skills, interests, and local information using a device, thereby creating a profile. The device then sends this information to a server, which stores it in a database using a data storage device.

[0305] Next, the emotion engine recognizes the user's emotions based on the information and behavioral data entered by the user. This emotion information is used to recommend projects and activities optimized for each individual user. Specifically, the server selects projects using a matching method based on the emotions recognized by the emotion engine. As a result, activities and information that match the user's current emotions are notified to the device.

[0306] Furthermore, the emotion engine also influences communication methods. For example, if a user is feeling stressed, communication is optimized by recommending supportive messages in online forums.

[0307] In addition, the emotion engine adjusts the way information is presented in the information providing means. For example, when the user is in a curious state, detailed and educational content is presented.

[0308] As a specific example, when the user participates in a project and the emotion engine recognizes that the user is in a confident state, the server recommends challenging projects or roles. Conversely, when the user is anxious, projects that can provide support and guidance are recommended. In this way, the user can select the optimal activities according to their own emotions and contribute to forest protection.

[0309] The following describes the processing flow.

[0310] Step 1:

[0311] The user uses the terminal to access the registration page and enters skills, interests, and regional information. In addition, the user provides emotion data to the system through regular questionnaires or feedback. This information is used for the processing of the emotion engine.

[0312] Step 2:

[0313] The terminal sends these input information to the server. The server receives the information and stores it in the database by the data storage means. The emotion data is also stored at this time and combined with other information for later analysis.

[0314] Step 3:

[0315] The server uses the emotion engine to analyze the user's emotional state in real time. This analysis is based on the user's input data, behavior history, and answer results. Through this process, the user's current emotional state is identified.

[0316] Step 4:

[0317] The server uses matching mechanisms to select appropriate projects and activities based on the user's emotional state. For example, if the user is in a positive emotional state, a challenging project will be selected; if they are in a negative emotional state, a supportive or educational project will be chosen. This selection result is notified to the user's device.

[0318] Step 5:

[0319] Users review the selection results on their devices and decide whether to participate in projects that interest them.

[0320] Step 6:

[0321] The server optimizes the communication style to match the user's emotional state through the communication channels. This includes recommended tones within forums and customization of message content.

[0322] Step 7:

[0323] The server organizes information obtained from external sources using information delivery methods and delivers the information in a way that suits the user's emotional state. For example, users with a high level of curiosity are provided with detailed analytical articles.

[0324] Through this step, users can engage with the project in a way that best suits their own emotions and effectively carry out forest conservation activities.

[0325] (Example 2)

[0326] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0327] Conventional information delivery systems have a problem in that they do not adequately consider the emotions and individual characteristics of users when optimizing information delivery and communication. As a result, users are not provided with the most suitable information and activities, leading to problems such as decreased satisfaction and efficiency.

[0328] 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.

[0329] In this invention, the server includes a storage means for storing information entered by the user, a matching means using an emotion analysis engine that performs emotion recognition to recommend tasks relevant to the user based on the stored information and behavioral data, and a communication means for optimizing information exchange between users. This enables optimal information provision and communication according to the emotional state of the user.

[0330] A "user" is an entity that uses the system to input information and receive recommendations for activities.

[0331] "Memory means" refers to a device or method for storing information entered by a user as data.

[0332] "Action data" refers to information obtained from the user's actions and operations, and is used for emotion recognition.

[0333] An "emotion analysis engine" is a program or algorithm used to recognize and analyze a user's emotions.

[0334] A "matching method" is a method or system for recommending the most suitable tasks or projects based on the user's emotions and stored information.

[0335] "Communication means" refers to a method or device for optimizing the process of exchanging information between users.

[0336] "Information provision means" refers to a method or system for appropriately displaying and providing information that is highly relevant to the user.

[0337] The following describes "modes for carrying out the invention."

[0338] ---

[0339] The system of this invention is implemented with the following configuration.

[0340] The user first uses a device to input their skills, interests, and local information. This device is expected to be an information processing device such as a regular computer or smartphone. This information is configured as a profile and sent from the device to the server.

[0341] The server stores the received information in a database using data storage means. A general-purpose database management system (DBMS) can be used for this storage.

[0342] Next, the server uses an emotion analysis engine to recognize emotions from the user's input information and behavioral data. This emotion analysis engine utilizes existing generative AI models and can analyze emotional states using natural language processing (NLP) techniques. For example, it can determine an emotion from a user's text comments.

[0343] The server uses a matching mechanism to select the most suitable tasks and projects for the user based on emotional information obtained by the emotion analysis engine. The selected results are notified to the terminal via communication. This allows the user to receive activities and information that are appropriate for their current emotions.

[0344] For example, if a user comments "I'm tired" when logging in, the sentiment analysis engine will analyze this information and recommend relaxing activities. An example of a prompt to input into the generative AI model might be, "Please suggest activities to recommend when a user is feeling 'tired'."

[0345] In this way, the system takes into account the user's emotional state and enables the delivery of personalized information.

[0346] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0347] Step 1:

[0348] Users use their devices to input their skills, interests, and local information. This input data is collected in text format and built into a profile. If a user indicates an interest in "programming" and "nature conservation," that data is sent to the server.

[0349] Step 2:

[0350] The terminal sends the collected user profile information to the server. The server receives this information and stores it in a data storage device using a database management system (DBMS). For example, it might execute an "INSERT" query using SQL and save it to the database.

[0351] Step 3:

[0352] The server retrieves user information and behavioral data from the database. Next, it uses an emotion analysis engine incorporating a generative AI model to recognize the user's emotions. This process uses natural language processing to analyze text data and identify emotions. For example, emotional states such as "highly motivated" or "tired" might be output.

[0353] Step 4:

[0354] The server uses matching mechanisms based on recognized emotional information to select the most suitable tasks and projects for the user. The selection process uses algorithms to determine the option that best matches the user's interests, skills, and emotional state. As a result, specific projects and activities are selected.

[0355] Step 5:

[0356] The terminal receives notifications of activities and information selected by the server. These notifications are formatted and displayed in a way that is appropriate to the user's mood. For example, "relaxing volunteer activities" or "challenging coding assignments" may be available.

[0357] Step 6:

[0358] Based on the suggestions the user receives, they can choose to participate in an actual activity or view the information. This result is recorded again as data to be used for personalized suggestions in the future.

[0359] (Application Example 2)

[0360] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0361] E-commerce sites are expected to improve the user's shopping experience and, consequently, enhance commercial performance by recommending appropriate products based on the user's emotions. However, current systems struggle to provide product recommendations that take emotions into account, and lack the flexibility to respond to users' emotions.

[0362] 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.

[0363] In this invention, the server includes emotion recognition means for detecting the user's emotional state and recommending the most suitable product based on it, data management means for storing information entered by the user, and selection means for recommending activities relevant to the user based on the stored information. This makes it possible to recommend products optimized for the user's emotions and improve the purchasing experience.

[0364] "Data management means" refers to methods for efficiently storing information entered by users and retrieving it as needed.

[0365] "Selection methods" refer to means of analyzing stored information and recommending the most relevant activities and products to the user.

[0366] "Communication control means" are means to facilitate the exchange of information between users and to enable smooth communication.

[0367] "Information distribution means" refers to the means of providing users with the latest information on environmental protection.

[0368] "Emotion recognition means" refers to a method for detecting the emotional state of a user and recommending the most suitable product based on that state.

[0369] An "online communication platform" is a system that provides a space where users can communicate freely.

[0370] The system for realizing this application aims to improve the purchasing experience by detecting the user's emotional state and recommending products based on that emotion. The system includes data management means, selection means, communication control means, information distribution means, and emotion recognition means.

[0371] In this system, the server uses data management tools to efficiently store information entered by users through their terminals. To recognize the user's emotional state, facial recognition software such as the Google Cloud Vision API is used as an emotion recognition tool, determining emotions based on video data acquired from the terminal's camera. The server uses TensorFlow to analyze the obtained emotion data and extracts relevant products from the database using a selection tool.

[0372] The extracted product information is transmitted to the terminal via a communication control device, and the terminal uses an information distribution device to present products that are appropriate to the user's emotional state. For example, if the user is feeling stressed, a list of products that help with relaxation will be presented.

[0373] For example, if a user is browsing an online shopping site on their smartphone and the emotion recognition system determines that their current emotion is "stress," the system will generate a prompt saying, "Please recommend products that are suitable for my current emotion," and as a result, the server will display a list of relaxation items.

[0374] Examples of this prompt include the following:

[0375] "What products should be recommended when a user is under stress?"

[0376] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0377] Step 1:

[0378] A user browses an online shopping site using their device, and the camera captures a picture of the user's face. The device receives this facial image data as input and sends it to the Google Cloud Vision API for emotion recognition. The API analyzes this input data and returns the user's emotional state (e.g., joy, stress) as output.

[0379] Step 2:

[0380] The server receives emotional state data sent from the terminal. It analyzes this as input data, runs a generative AI model using TensorFlow, and outputs candidate product categories that best suit the user's emotions. Specifically, it runs an algorithm that evaluates the relationship between emotions and product attributes.

[0381] Step 3:

[0382] The server searches the database for relevant products based on the product category candidates obtained in step 2. It outputs a list of related products as search results. This list includes popular products and products with high review ratings within the category.

[0383] Step 4:

[0384] The server sends the generated list of related products to the terminal via a communication control means. The terminal receives this product list and displays the products to the user using an information distribution means. At this time, product descriptions tailored to the user's mood and links to special feature pages are also presented.

[0385] Step 5:

[0386] The user reviews the presented product list and selects items of interest. This allows them to view detailed pages or proceed with the purchase. For example, a featured page such as "Stress Relief Items" might be displayed.

[0387] 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.

[0388] 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.

[0389] 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.

[0390] [Third Embodiment]

[0391] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0392] 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.

[0393] 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).

[0394] 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.

[0395] 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.

[0396] 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).

[0397] 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.

[0398] 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.

[0399] 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.

[0400] 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.

[0401] 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.

[0402] 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".

[0403] This invention is implemented as a system for appropriately matching users with relevant activities and projects based on their input information. This system mainly consists of four main elements: data storage means, matching means, communication means, and information provision means.

[0404] First, users input their skills, interests, and local information using their device. This data is sent from the device to a server and stored using data storage technology. The stored information is then registered as the user's profile.

[0405] Next, the server uses a matching system to recommend relevant activities and projects based on the saved profile information. This process selects the most suitable project, taking into account skills, interests, and geographical conditions. The matching results are notified to the device, and the user can view detailed information.

[0406] Furthermore, the server is equipped with communication capabilities, allowing users to exchange information and engage in discussions. This feature provides online forums and chat rooms, enabling users to share their experiences and knowledge with others.

[0407] The information provision system plays the role of organizing the latest environmental protection information collected from external sources by the server and delivering it to users. This allows users to acquire the latest knowledge and use it to their advantage in their own activities.

[0408] As a concrete example, if a user is interested in forest surveys, they input the skill "Forest Survey" and the region "Hokkaido" into the system, and the server saves this information in a data storage device. Using a matching mechanism, the server finds a suitable forest survey project and notifies the user. The user views this information on their terminal and decides to participate in the project. During this time, they can communicate with other project participants using communication tools and obtain the information and knowledge necessary for the project. In this way, users can efficiently contribute to forest conservation activities while making use of their skills.

[0409] The following describes the processing flow.

[0410] Step 1:

[0411] Users access the registration page using their devices and enter their skills, interests, and location information. This information forms the basis for matching.

[0412] Step 2:

[0413] The terminal sends the entered information to the server. The server receives this information and stores it in a database using a data storage device.

[0414] Step 3:

[0415] The server periodically retrieves project and work information from the database. This retrieval is done by collecting publicly available information on new projects.

[0416] Step 4:

[0417] The server matches the user's profile information with project information. This allows it to select the project that best matches the user's skills, interests, and geographical location.

[0418] Step 5:

[0419] The server sends the matching results to the relevant users' devices. Users can receive notifications of matched projects through their devices and view detailed information.

[0420] Step 6:

[0421] By utilizing the communication methods provided by the server, users can interact with other participants in online forums and chats. This facilitates the sharing of necessary information and experiences.

[0422] Step 7:

[0423] The server collects the latest environmental protection information from external sources and distributes it to users through information delivery channels. Users can then view this information on their devices and incorporate it into their own activities.

[0424] (Example 1)

[0425] 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."

[0426] While much information is currently available via the internet, the process of obtaining it has resulted in an excessive amount of data, making it difficult for individual users to discover appropriate activities and plans tailored to their abilities, interests, and local information. Furthermore, there is a lack of systems that enable participants to effectively share their knowledge and experience and utilize the latest information. Therefore, users face challenges in efficiently utilizing information and participating in meaningful activities.

[0427] 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.

[0428] In this invention, the server includes information storage means for storing user inputs regarding abilities, interests, and local information; matching means for analyzing the user's abilities, interests, and local conditions in order to recommend activities and plans based on the stored information; and communication support means for sharing knowledge and experience among users. This enables users to easily find appropriate activities and plans, communicate effectively with other users, and participate in activities efficiently by utilizing the latest information.

[0429] "Information storage" refers to the function of saving user-entered information about abilities, interests, and local area as digital data.

[0430] "Matching" is the process of analyzing users' abilities, interests, and local conditions based on their stored data in order to select suitable activities and plans.

[0431] "Communication support" refers to a function that facilitates the exchange of information and dialogue in order to mutually share knowledge and experiences among users.

[0432] "Information distribution" is a function that takes the role of organizing the latest knowledge obtained from external sources and delivering it to users.

[0433] "Capability" refers to the knowledge and skills a user possesses in a specific field, and is an attribute used in selecting activities and plans within the system.

[0434] "Interest" refers to information that indicates the degree of interest or involvement a user has in a particular activity or field.

[0435] "Local information" refers to geographical data about the places where users live or can engage in activities.

[0436] "Activities and plans" refer to specific projects or events that users can consider participating in or engaging with.

[0437] This invention is an embodiment of a system aimed at efficiently matching many users with appropriate and interesting activities and plans based on their abilities, interests, and local information.

[0438] The server uses information storage means to store data received from users, namely skills, interests, and location information. Hardware-wise, the database server works in conjunction with the communication server to ensure high-speed and secure data storage. Software-wise, an SQL-based database management system is used to design and optimize the data structure.

[0439] Next, the matching process is executed. In this process, the server applies an algorithm to analyze the user's saved profile and select the most suitable activities and plans from among the relevant ones. By applying a generative AI model, a recommendation system based on the user's attributes is realized. This technology matches users with projects that are particularly compatible with their skills and interests.

[0440] The terminal notifies the user of the selection results from the server. The user can view details of the recommended activities and plans on the terminal and decide whether or not to participate. During this time, the user receives information about the project's start date, location, and participation requirements.

[0441] Furthermore, the server provides communication support. The virtual communication platform allows participants to interact and share information and knowledge with each other. This primarily includes online forums and chat functions, contributing to the project's success by enabling participants to exchange experiences.

[0442] Through information distribution channels, the server collects and provides users with the latest information about the environment. This allows users to acquire new knowledge in real time and use it to aid in decision-making.

[0443] For example, if a user possesses the skill of "forest surveying" and wishes to participate in a project in the Hokkaido region, the server will select a forest conservation project that matches their "forest surveying" skill and notify the user. Furthermore, the user can interact with other project participants and advance the project while utilizing the latest environmental information.

[0444] An example of a prompt message might be: "Please describe a system that finds the most suitable project based on the user's skills and location information. Please explain in detail the matching process using a specific example."

[0445] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0446] Step 1:

[0447] Users input their skills, interests, and local information using a terminal. This information includes specific skills and desired areas of activity. The terminal reviews the entered data and verifies that it is in the correct format. Once input is complete, the terminal sends this data to the server.

[0448] Step 2:

[0449] The server stores the received user data using information storage means. Specifically, this involves registering the user's profile information in the database system. Based on this information, the database organizes the user's abilities, interests, and location information into categories and sets up indexes for quick access.

[0450] Step 3:

[0451] The server analyzes the user profile using matching mechanisms and selects highly relevant activities and plans from the project database. This process uses a generative AI model to compare the user's input information with project requirements and calculate a matching score. This then lists the most suitable project candidates.

[0452] Step 4:

[0453] The server creates recommended project information and sends it to the terminal. The terminal receives this and notifies the user. Specifically, it renders a UI to display the project overview, details, participation requirements, etc., and allows the user to view it.

[0454] Step 5:

[0455] Users view project details on their devices and decide whether or not to participate. After making a decision, they send their intention to participate from their device to the server, which then updates the project participant list by linking that information to it.

[0456] Step 6:

[0457] The server enables information sharing among project participants using communication support tools. It sets up virtual forums and chat systems, allowing participants to freely initiate communication. This functionality allows users to share their knowledge and experience and monitor project progress.

[0458] Step 7:

[0459] The server uses information distribution methods to organize and provide users with the latest information obtained from external sources. The information is updated in real time and notified to users via their terminals. This allows users to always have the latest knowledge and reflect it in their activities.

[0460] (Application Example 1)

[0461] 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."

[0462] In online shopping, it is time-consuming for users to find products based on their interests and purchase history, so there is a need for efficient product recommendation systems. Furthermore, there is a lack of means for users to exchange information about products with each other and obtain reliable feedback. As a result, the shopping experience is not personalized.

[0463] 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.

[0464] In this invention, the server includes a data storage device for storing information entered by the user, a matching device for recommending relevant products to the user based on the stored information, and a communication device for facilitating information exchange between users. This allows users to efficiently find products based on their interests and purchase history, and to receive reliable feedback through information exchange with other users.

[0465] A "user" is an individual who uses the system to search for products or exchange information with other users.

[0466] A "data storage device" is a device that stores information entered by a user and has the function of retrieving it as needed.

[0467] A "product" is an item or service recommended to a user for sale.

[0468] A "matching device" is a device that has the function of selecting and recommending relevant products based on stored user information.

[0469] A "communication device" is a device that has functions to facilitate information exchange between users, such as providing online bulletin boards and chat services.

[0470] This invention is a system that provides personalized product recommendations based on the user's interests and purchase history entered into a device such as a smartphone. The server stores the entered information in a data storage device and recommends appropriate products using a matching device. This process involves data processing using machine learning models. Specifically, it utilizes frameworks such as TensorFlow and PyTorch to execute a product recommendation algorithm based on the user's interests.

[0471] The server also features communication equipment to facilitate information exchange between users, providing online bulletin boards and real-time chat. This functionality utilizes WebSocket and RESTful APIs to enable highly immediate information exchange.

[0472] For example, if a user enters that they are interested in "eco-bags," the system can take into account their past purchase history and local information to recommend products made with organic materials. Furthermore, sharing information on message boards with other users allows for reliable feedback on product reviews and user experiences.

[0473] An example of a prompt to input into the generating AI model is, "If a user shows interest in eco-bags, how would you recommend related products?"

[0474] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0475] Step 1:

[0476] The user uses a device to input their interests and purchase history. The device converts this information into data packets and sends them to the server. The input consists of interest keywords and past purchase information, and the output is data packets.

[0477] Step 2:

[0478] The server stores the received data packets in its data storage device. Here, the server performs database operations to update the user's profile information. The input is the data packets, and the output is the updated user profile.

[0479] Step 3:

[0480] The server uses a matching device to recommend products based on stored profile information. The server utilizes a generative AI model to extract features based on input data and select the most suitable product. The input is the user profile, and the output is a list of recommended products.

[0481] Step 4:

[0482] The server uses a communication device to send recommendation results to the terminal. The terminal displays the received list of recommended products to the user. The input is the list of recommended products, and the output is the product information displayed to the user.

[0483] Step 5:

[0484] Users can exchange information with other users based on the displayed product information. The device utilizes real-time chat and bulletin board functions via a server during this process. Input consists of the user's message content, while output is feedback from other users.

[0485] Step 6:

[0486] The server analyzes communication between users and accumulates feedback data on products. This allows the server to obtain data to improve the accuracy of subsequent recommendations. The input is feedback data, and the output is accumulated data.

[0487] 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.

[0488] This invention implements a system that combines an emotion engine with data storage means, matching means, communication means, and information provision means, in addition to the emotion engine.

[0489] First, users input their skills, interests, and local information using a device, thereby creating a profile. The device then sends this information to a server, which stores it in a database using a data storage device.

[0490] Next, the emotion engine recognizes the user's emotions based on the information and behavioral data entered by the user. This emotion information is used to recommend projects and activities optimized for each individual user. Specifically, the server selects projects using a matching method based on the emotions recognized by the emotion engine. As a result, activities and information that match the user's current emotions are notified to the device.

[0491] Furthermore, the emotion engine also influences communication methods. For example, if a user is feeling stressed, communication is optimized by recommending supportive messages in online forums.

[0492] In addition, the emotion engine adjusts how information is presented in the means of information delivery. For example, if a user is in a curious state, detailed and educational content will be presented.

[0493] For example, when a user joins a project, if the emotion engine recognizes that the user is confident, the server will recommend challenging projects or roles. Conversely, if the user is feeling anxious, projects that offer support and guidance will be recommended. In this way, users can choose the activity best suited to their emotions and contribute to forest conservation.

[0494] The following describes the processing flow.

[0495] Step 1:

[0496] Users access the registration page using their devices and enter their skills, interests, and location information. Users also provide sentiment data through periodic surveys and feedback within the system. This information is used to process the sentiment engine.

[0497] Step 2:

[0498] The terminal sends this input information to the server. The server receives the information and stores it in a database using data storage means. Sentiment data is also stored at this time and combined with other information to prepare for later analysis.

[0499] Step 3:

[0500] The server uses an emotion engine to analyze the user's emotional state in real time. This analysis is based on the user's input data, behavioral history, and response results. This process identifies the user's current emotional state.

[0501] Step 4:

[0502] The server uses matching mechanisms to select appropriate projects and activities based on the user's emotional state. For example, if the user is in a positive emotional state, a challenging project will be selected; if they are in a negative emotional state, a supportive or educational project will be chosen. This selection result is notified to the user's device.

[0503] Step 5:

[0504] Users review the selection results on their devices and decide whether to participate in projects that interest them.

[0505] Step 6:

[0506] The server optimizes the communication style to match the user's emotional state through the communication channels. This includes recommended tones within forums and customization of message content.

[0507] Step 7:

[0508] The server organizes information obtained from external sources using information delivery methods and delivers the information in a way that suits the user's emotional state. For example, users with a high level of curiosity are provided with detailed analytical articles.

[0509] Through this step, users can engage with the project in a way that best suits their own emotions and effectively carry out forest conservation activities.

[0510] (Example 2)

[0511] 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."

[0512] Conventional information delivery systems have a problem in that they do not adequately consider the emotions and individual characteristics of users when optimizing information delivery and communication. As a result, users are not provided with the most suitable information and activities, leading to problems such as decreased satisfaction and efficiency.

[0513] 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.

[0514] In this invention, the server includes a storage means for storing information entered by the user, a matching means using an emotion analysis engine that performs emotion recognition to recommend tasks relevant to the user based on the stored information and behavioral data, and a communication means for optimizing information exchange between users. This enables optimal information provision and communication according to the emotional state of the user.

[0515] A "user" is an entity that uses the system to input information and receive recommendations for activities.

[0516] "Memory means" refers to a device or method for storing information entered by a user as data.

[0517] "Action data" refers to information obtained from the user's actions and operations, and is used for emotion recognition.

[0518] An "emotion analysis engine" is a program or algorithm used to recognize and analyze a user's emotions.

[0519] A "matching method" is a method or system for recommending the most suitable tasks or projects based on the user's emotions and stored information.

[0520] "Communication means" refers to a method or device for optimizing the process of exchanging information between users.

[0521] "Information provision means" refers to a method or system for appropriately displaying and providing information that is highly relevant to the user.

[0522] The following describes "modes for carrying out the invention."

[0523] ---

[0524] The system of this invention is implemented with the following configuration.

[0525] The user first uses a device to input their skills, interests, and local information. This device is expected to be an information processing device such as a regular computer or smartphone. This information is configured as a profile and sent from the device to the server.

[0526] The server stores the received information in a database using data storage means. A general-purpose database management system (DBMS) can be used for this storage.

[0527] Next, the server uses an emotion analysis engine to recognize emotions from the user's input information and behavioral data. This emotion analysis engine utilizes existing generative AI models and can analyze emotional states using natural language processing (NLP) techniques. For example, it can determine an emotion from a user's text comments.

[0528] The server uses a matching mechanism to select the most suitable tasks and projects for the user based on emotional information obtained by the emotion analysis engine. The selected results are notified to the terminal via communication. This allows the user to receive activities and information that are appropriate for their current emotions.

[0529] For example, if a user comments "I'm tired" when logging in, the sentiment analysis engine will analyze this information and recommend relaxing activities. An example of a prompt to input into the generative AI model might be, "Please suggest activities to recommend when a user is feeling 'tired'."

[0530] In this way, the system takes into account the user's emotional state and enables the delivery of personalized information.

[0531] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0532] Step 1:

[0533] Users use their devices to input their skills, interests, and local information. This input data is collected in text format and built into a profile. If a user indicates an interest in "programming" and "nature conservation," that data is sent to the server.

[0534] Step 2:

[0535] The terminal sends the collected user profile information to the server. The server receives this information and stores it in a data storage device using a database management system (DBMS). For example, it might execute an "INSERT" query using SQL and save it to the database.

[0536] Step 3:

[0537] The server retrieves user information and behavioral data from the database. Next, it uses an emotion analysis engine incorporating a generative AI model to recognize the user's emotions. This process uses natural language processing to analyze text data and identify emotions. For example, emotional states such as "highly motivated" or "tired" might be output.

[0538] Step 4:

[0539] The server uses matching mechanisms based on recognized emotional information to select the most suitable tasks and projects for the user. The selection process uses algorithms to determine the option that best matches the user's interests, skills, and emotional state. As a result, specific projects and activities are selected.

[0540] Step 5:

[0541] The terminal receives notifications of activities and information selected by the server. These notifications are formatted and displayed in a way that is appropriate to the user's mood. For example, "relaxing volunteer activities" or "challenging coding assignments" may be available.

[0542] Step 6:

[0543] Based on the suggestions the user receives, they can choose to participate in an actual activity or view the information. This result is recorded again as data to be used for personalized suggestions in the future.

[0544] (Application Example 2)

[0545] 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."

[0546] E-commerce sites are expected to improve the user's shopping experience and, consequently, enhance commercial performance by recommending appropriate products based on the user's emotions. However, current systems struggle to provide product recommendations that take emotions into account, and lack the flexibility to respond to users' emotions.

[0547] 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.

[0548] In this invention, the server includes emotion recognition means for detecting the user's emotional state and recommending the most suitable product based on it, data management means for storing information entered by the user, and selection means for recommending activities relevant to the user based on the stored information. This makes it possible to recommend products optimized for the user's emotions and improve the purchasing experience.

[0549] "Data management means" refers to methods for efficiently storing information entered by users and retrieving it as needed.

[0550] "Selection methods" refer to means of analyzing stored information and recommending the most relevant activities and products to the user.

[0551] "Communication control means" are means to facilitate the exchange of information between users and to enable smooth communication.

[0552] "Information distribution means" refers to the means of providing users with the latest information on environmental protection.

[0553] "Emotion recognition means" refers to a method for detecting the emotional state of a user and recommending the most suitable product based on that state.

[0554] An "online communication platform" is a system that provides a space where users can communicate freely.

[0555] The system for realizing this application aims to improve the purchasing experience by detecting the user's emotional state and recommending products based on that emotion. The system includes data management means, selection means, communication control means, information distribution means, and emotion recognition means.

[0556] In this system, the server uses data management tools to efficiently store information entered by users through their terminals. To recognize the user's emotional state, facial recognition software such as the Google Cloud Vision API is used as an emotion recognition tool, determining emotions based on video data acquired from the terminal's camera. The server uses TensorFlow to analyze the obtained emotion data and extracts relevant products from the database using a selection tool.

[0557] The extracted product information is transmitted to the terminal via a communication control device, and the terminal uses an information distribution device to present products that are appropriate to the user's emotional state. For example, if the user is feeling stressed, a list of products that help with relaxation will be presented.

[0558] For example, if a user is browsing an online shopping site on their smartphone and the emotion recognition system determines that their current emotion is "stress," the system will generate a prompt saying, "Please recommend products that are suitable for my current emotion," and as a result, the server will display a list of relaxation items.

[0559] Examples of this prompt include the following:

[0560] "What products should be recommended when a user is under stress?"

[0561] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0562] Step 1:

[0563] A user browses an online shopping site using their device, and the camera captures a picture of the user's face. The device receives this facial image data as input and sends it to the Google Cloud Vision API for emotion recognition. The API analyzes this input data and returns the user's emotional state (e.g., joy, stress) as output.

[0564] Step 2:

[0565] The server receives emotional state data sent from the terminal. It analyzes this as input data, runs a generative AI model using TensorFlow, and outputs candidate product categories that best suit the user's emotions. Specifically, it runs an algorithm that evaluates the relationship between emotions and product attributes.

[0566] Step 3:

[0567] The server searches the database for relevant products based on the product category candidates obtained in step 2. It outputs a list of related products as search results. This list includes popular products and products with high review ratings within the category.

[0568] Step 4:

[0569] The server sends the generated list of related products to the terminal via a communication control means. The terminal receives this product list and displays the products to the user using an information distribution means. At this time, product descriptions tailored to the user's mood and links to special feature pages are also presented.

[0570] Step 5:

[0571] The user reviews the presented product list and selects items of interest. This allows them to view detailed pages or proceed with the purchase. For example, a featured page such as "Stress Relief Items" might be displayed.

[0572] 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.

[0573] 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.

[0574] 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.

[0575] [Fourth Embodiment]

[0576] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0577] 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.

[0578] 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).

[0579] 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.

[0580] 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.

[0581] 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).

[0582] 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.

[0583] 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.

[0584] 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.

[0585] 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.

[0586] 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.

[0587] 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.

[0588] 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".

[0589] This invention is implemented as a system for appropriately matching users with relevant activities and projects based on their input information. This system mainly consists of four main elements: data storage means, matching means, communication means, and information provision means.

[0590] First, users input their skills, interests, and local information using their device. This data is sent from the device to a server and stored using data storage technology. The stored information is then registered as the user's profile.

[0591] Next, the server uses a matching system to recommend relevant activities and projects based on the saved profile information. This process selects the most suitable project, taking into account skills, interests, and geographical conditions. The matching results are notified to the device, and the user can view detailed information.

[0592] Furthermore, the server is equipped with communication capabilities, allowing users to exchange information and engage in discussions. This feature provides online forums and chat rooms, enabling users to share their experiences and knowledge with others.

[0593] The information provision system plays the role of organizing the latest environmental protection information collected from external sources by the server and delivering it to users. This allows users to acquire the latest knowledge and use it to their advantage in their own activities.

[0594] As a concrete example, if a user is interested in forest surveys, they input the skill "Forest Survey" and the region "Hokkaido" into the system, and the server saves this information in a data storage device. Using a matching mechanism, the server finds a suitable forest survey project and notifies the user. The user views this information on their terminal and decides to participate in the project. During this time, they can communicate with other project participants using communication tools and obtain the information and knowledge necessary for the project. In this way, users can efficiently contribute to forest conservation activities while making use of their skills.

[0595] The following describes the processing flow.

[0596] Step 1:

[0597] Users access the registration page using their devices and enter their skills, interests, and location information. This information forms the basis for matching.

[0598] Step 2:

[0599] The terminal sends the entered information to the server. The server receives this information and stores it in a database using a data storage device.

[0600] Step 3:

[0601] The server periodically retrieves project and work information from the database. This retrieval is done by collecting publicly available information on new projects.

[0602] Step 4:

[0603] The server matches the user's profile information with project information. This allows it to select the project that best matches the user's skills, interests, and geographical location.

[0604] Step 5:

[0605] The server sends the matching results to the relevant users' devices. Users can receive notifications of matched projects through their devices and view detailed information.

[0606] Step 6:

[0607] By utilizing the communication methods provided by the server, users can interact with other participants in online forums and chats. This facilitates the sharing of necessary information and experiences.

[0608] Step 7:

[0609] The server collects the latest environmental protection information from external sources and distributes it to users through information delivery channels. Users can then view this information on their devices and incorporate it into their own activities.

[0610] (Example 1)

[0611] 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".

[0612] While much information is currently available via the internet, the process of obtaining it has resulted in an excessive amount of data, making it difficult for individual users to discover appropriate activities and plans tailored to their abilities, interests, and local information. Furthermore, there is a lack of systems that enable participants to effectively share their knowledge and experience and utilize the latest information. Therefore, users face challenges in efficiently utilizing information and participating in meaningful activities.

[0613] 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.

[0614] In this invention, the server includes information storage means for storing user inputs regarding abilities, interests, and local information; matching means for analyzing the user's abilities, interests, and local conditions in order to recommend activities and plans based on the stored information; and communication support means for sharing knowledge and experience among users. This enables users to easily find appropriate activities and plans, communicate effectively with other users, and participate in activities efficiently by utilizing the latest information.

[0615] "Information storage" refers to the function of saving user-entered information about abilities, interests, and local area as digital data.

[0616] "Matching" is the process of analyzing users' abilities, interests, and local conditions based on their stored data in order to select suitable activities and plans.

[0617] "Communication support" refers to a function that facilitates the exchange of information and dialogue in order to mutually share knowledge and experiences among users.

[0618] "Information distribution" is a function that takes the role of organizing the latest knowledge obtained from external sources and delivering it to users.

[0619] "Capability" refers to the knowledge and skills a user possesses in a specific field, and is an attribute used in selecting activities and plans within the system.

[0620] "Interest" refers to information that indicates the degree of interest or involvement a user has in a particular activity or field.

[0621] "Local information" refers to geographical data about the places where users live or can engage in activities.

[0622] "Activities and plans" refer to specific projects or events that users can consider participating in or engaging with.

[0623] This invention is an embodiment of a system aimed at efficiently matching many users with appropriate and interesting activities and plans based on their abilities, interests, and local information.

[0624] The server uses information storage means to store data received from users, namely skills, interests, and location information. Hardware-wise, the database server works in conjunction with the communication server to ensure high-speed and secure data storage. Software-wise, an SQL-based database management system is used to design and optimize the data structure.

[0625] Next, the matching process is executed. In this process, the server applies an algorithm to analyze the user's saved profile and select the most suitable activities and plans from among the relevant ones. By applying a generative AI model, a recommendation system based on the user's attributes is realized. This technology matches users with projects that are particularly compatible with their skills and interests.

[0626] The terminal notifies the user of the selection results from the server. The user can view details of the recommended activities and plans on the terminal and decide whether or not to participate. During this time, the user receives information about the project's start date, location, and participation requirements.

[0627] Furthermore, the server provides communication support. The virtual communication platform allows participants to interact and share information and knowledge with each other. This primarily includes online forums and chat functions, contributing to the project's success by enabling participants to exchange experiences.

[0628] Through information distribution channels, the server collects and provides users with the latest information about the environment. This allows users to acquire new knowledge in real time and use it to aid in decision-making.

[0629] For example, if a user possesses the skill of "forest surveying" and wishes to participate in a project in the Hokkaido region, the server will select a forest conservation project that matches their "forest surveying" skill and notify the user. Furthermore, the user can interact with other project participants and advance the project while utilizing the latest environmental information.

[0630] An example of a prompt message might be: "Please describe a system that finds the most suitable project based on the user's skills and location information. Please explain in detail the matching process using a specific example."

[0631] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0632] Step 1:

[0633] Users input their skills, interests, and local information using a terminal. This information includes specific skills and desired areas of activity. The terminal reviews the entered data and verifies that it is in the correct format. Once input is complete, the terminal sends this data to the server.

[0634] Step 2:

[0635] The server stores the received user data using information storage means. Specifically, this involves registering the user's profile information in the database system. Based on this information, the database organizes the user's abilities, interests, and location information into categories and sets up indexes for quick access.

[0636] Step 3:

[0637] The server analyzes the user profile using matching mechanisms and selects highly relevant activities and plans from the project database. This process uses a generative AI model to compare the user's input information with project requirements and calculate a matching score. This then lists the most suitable project candidates.

[0638] Step 4:

[0639] The server creates recommended project information and sends it to the terminal. The terminal receives this and notifies the user. Specifically, it renders a UI to display the project overview, details, participation requirements, etc., and allows the user to view it.

[0640] Step 5:

[0641] Users view project details on their devices and decide whether or not to participate. After making a decision, they send their intention to participate from their device to the server, which then updates the project participant list by linking that information to it.

[0642] Step 6:

[0643] The server enables information sharing among project participants using communication support tools. It sets up virtual forums and chat systems, allowing participants to freely initiate communication. This functionality allows users to share their knowledge and experience and monitor project progress.

[0644] Step 7:

[0645] The server uses information distribution methods to organize and provide users with the latest information obtained from external sources. The information is updated in real time and notified to users via their terminals. This allows users to always have the latest knowledge and reflect it in their activities.

[0646] (Application Example 1)

[0647] 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".

[0648] In online shopping, it is time-consuming for users to find products based on their interests and purchase history, so there is a need for efficient product recommendation systems. Furthermore, there is a lack of means for users to exchange information about products with each other and obtain reliable feedback. As a result, the shopping experience is not personalized.

[0649] 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.

[0650] In this invention, the server includes a data storage device for storing information entered by the user, a matching device for recommending relevant products to the user based on the stored information, and a communication device for facilitating information exchange between users. This allows users to efficiently find products based on their interests and purchase history, and to receive reliable feedback through information exchange with other users.

[0651] A "user" is an individual who uses the system to search for products or exchange information with other users.

[0652] A "data storage device" is a device that stores information entered by a user and has the function of retrieving it as needed.

[0653] A "product" is an item or service recommended to a user for sale.

[0654] A "matching device" is a device that has the function of selecting and recommending relevant products based on stored user information.

[0655] A "communication device" is a device that has functions to facilitate information exchange between users, such as providing online bulletin boards and chat services.

[0656] This invention is a system that provides personalized product recommendations based on the user's interests and purchase history entered into a device such as a smartphone. The server stores the entered information in a data storage device and recommends appropriate products using a matching device. This process involves data processing using machine learning models. Specifically, it utilizes frameworks such as TensorFlow and PyTorch to execute a product recommendation algorithm based on the user's interests.

[0657] The server also features communication equipment to facilitate information exchange between users, providing online bulletin boards and real-time chat. This functionality utilizes WebSocket and RESTful APIs to enable highly immediate information exchange.

[0658] For example, if a user enters that they are interested in "eco-bags," the system can take into account their past purchase history and local information to recommend products made with organic materials. Furthermore, sharing information on message boards with other users allows for reliable feedback on product reviews and user experiences.

[0659] An example of a prompt to input into the generating AI model is, "If a user shows interest in eco-bags, how would you recommend related products?"

[0660] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0661] Step 1:

[0662] The user uses a device to input their interests and purchase history. The device converts this information into data packets and sends them to the server. The input consists of interest keywords and past purchase information, and the output is data packets.

[0663] Step 2:

[0664] The server stores the received data packets in its data storage device. Here, the server performs database operations to update the user's profile information. The input is the data packets, and the output is the updated user profile.

[0665] Step 3:

[0666] The server uses a matching device to recommend products based on stored profile information. The server utilizes a generative AI model to extract features based on input data and select the most suitable product. The input is the user profile, and the output is a list of recommended products.

[0667] Step 4:

[0668] The server uses a communication device to send recommendation results to the terminal. The terminal displays the received list of recommended products to the user. The input is the list of recommended products, and the output is the product information displayed to the user.

[0669] Step 5:

[0670] Users can exchange information with other users based on the displayed product information. The device utilizes real-time chat and bulletin board functions via a server during this process. Input consists of the user's message content, while output is feedback from other users.

[0671] Step 6:

[0672] The server analyzes communication between users and accumulates feedback data on products. This allows the server to obtain data to improve the accuracy of subsequent recommendations. The input is feedback data, and the output is accumulated data.

[0673] 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.

[0674] This invention implements a system that combines an emotion engine with data storage means, matching means, communication means, and information provision means, in addition to the emotion engine.

[0675] First, users input their skills, interests, and local information using a device, thereby creating a profile. The device then sends this information to a server, which stores it in a database using a data storage device.

[0676] Next, the emotion engine recognizes the user's emotions based on the information and behavioral data entered by the user. This emotion information is used to recommend projects and activities optimized for each individual user. Specifically, the server selects projects using a matching method based on the emotions recognized by the emotion engine. As a result, activities and information that match the user's current emotions are notified to the device.

[0677] Furthermore, the emotion engine also influences communication methods. For example, if a user is feeling stressed, communication is optimized by recommending supportive messages in online forums.

[0678] In addition, the emotion engine adjusts how information is presented in the means of information delivery. For example, if a user is in a curious state, detailed and educational content will be presented.

[0679] For example, when a user joins a project, if the emotion engine recognizes that the user is confident, the server will recommend challenging projects or roles. Conversely, if the user is feeling anxious, projects that offer support and guidance will be recommended. In this way, users can choose the activity best suited to their emotions and contribute to forest conservation.

[0680] The following describes the processing flow.

[0681] Step 1:

[0682] Users access the registration page using their devices and enter their skills, interests, and location information. Users also provide sentiment data through periodic surveys and feedback within the system. This information is used to process the sentiment engine.

[0683] Step 2:

[0684] The terminal sends this input information to the server. The server receives the information and stores it in a database using data storage means. Sentiment data is also stored at this time and combined with other information to prepare for later analysis.

[0685] Step 3:

[0686] The server uses an emotion engine to analyze the user's emotional state in real time. This analysis is based on the user's input data, behavioral history, and response results. This process identifies the user's current emotional state.

[0687] Step 4:

[0688] The server uses matching mechanisms to select appropriate projects and activities based on the user's emotional state. For example, if the user is in a positive emotional state, a challenging project will be selected; if they are in a negative emotional state, a supportive or educational project will be chosen. This selection result is notified to the user's device.

[0689] Step 5:

[0690] Users review the selection results on their devices and decide whether to participate in projects that interest them.

[0691] Step 6:

[0692] The server optimizes the communication style to match the user's emotional state through the communication channels. This includes recommended tones within forums and customization of message content.

[0693] Step 7:

[0694] The server organizes information obtained from external sources using information delivery methods and delivers the information in a way that suits the user's emotional state. For example, users with a high level of curiosity are provided with detailed analytical articles.

[0695] Through this step, users can engage with the project in a way that best suits their own emotions and effectively carry out forest conservation activities.

[0696] (Example 2)

[0697] 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".

[0698] Conventional information delivery systems have a problem in that they do not adequately consider the emotions and individual characteristics of users when optimizing information delivery and communication. As a result, users are not provided with the most suitable information and activities, leading to problems such as decreased satisfaction and efficiency.

[0699] 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.

[0700] In this invention, the server includes a storage means for storing information entered by the user, a matching means using an emotion analysis engine that performs emotion recognition to recommend tasks relevant to the user based on the stored information and behavioral data, and a communication means for optimizing information exchange between users. This enables optimal information provision and communication according to the emotional state of the user.

[0701] A "user" is an entity that uses the system to input information and receive recommendations for activities.

[0702] "Memory means" refers to a device or method for storing information entered by a user as data.

[0703] "Action data" refers to information obtained from the user's actions and operations, and is used for emotion recognition.

[0704] An "emotion analysis engine" is a program or algorithm used to recognize and analyze a user's emotions.

[0705] A "matching method" is a method or system for recommending the most suitable tasks or projects based on the user's emotions and stored information.

[0706] "Communication means" refers to a method or device for optimizing the process of exchanging information between users.

[0707] "Information provision means" refers to a method or system for appropriately displaying and providing information that is highly relevant to the user.

[0708] The following describes "modes for carrying out the invention."

[0709] ---

[0710] The system of this invention is implemented with the following configuration.

[0711] The user first uses a device to input their skills, interests, and local information. This device is expected to be an information processing device such as a regular computer or smartphone. This information is configured as a profile and sent from the device to the server.

[0712] The server stores the received information in a database using data storage means. A general-purpose database management system (DBMS) can be used for this storage.

[0713] Next, the server uses an emotion analysis engine to recognize emotions from the user's input information and behavioral data. This emotion analysis engine utilizes existing generative AI models and can analyze emotional states using natural language processing (NLP) techniques. For example, it can determine an emotion from a user's text comments.

[0714] The server uses a matching mechanism to select the most suitable tasks and projects for the user based on emotional information obtained by the emotion analysis engine. The selected results are notified to the terminal via communication. This allows the user to receive activities and information that are appropriate for their current emotions.

[0715] For example, if a user comments "I'm tired" when logging in, the sentiment analysis engine will analyze this information and recommend relaxing activities. An example of a prompt to input into the generative AI model might be, "Please suggest activities to recommend when a user is feeling 'tired'."

[0716] In this way, the system takes into account the user's emotional state and enables the delivery of personalized information.

[0717] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0718] Step 1:

[0719] Users use their devices to input their skills, interests, and local information. This input data is collected in text format and built into a profile. If a user indicates an interest in "programming" and "nature conservation," that data is sent to the server.

[0720] Step 2:

[0721] The terminal sends the collected user profile information to the server. The server receives this information and stores it in a data storage device using a database management system (DBMS). For example, it might execute an "INSERT" query using SQL and save it to the database.

[0722] Step 3:

[0723] The server retrieves user information and behavioral data from the database. Next, it uses an emotion analysis engine incorporating a generative AI model to recognize the user's emotions. This process uses natural language processing to analyze text data and identify emotions. For example, emotional states such as "highly motivated" or "tired" might be output.

[0724] Step 4:

[0725] The server uses matching mechanisms based on recognized emotional information to select the most suitable tasks and projects for the user. The selection process uses algorithms to determine the option that best matches the user's interests, skills, and emotional state. As a result, specific projects and activities are selected.

[0726] Step 5:

[0727] The terminal receives notifications of activities and information selected by the server. These notifications are formatted and displayed in a way that is appropriate to the user's mood. For example, "relaxing volunteer activities" or "challenging coding assignments" may be available.

[0728] Step 6:

[0729] Based on the suggestions the user receives, they can choose to participate in an actual activity or view the information. This result is recorded again as data to be used for personalized suggestions in the future.

[0730] (Application Example 2)

[0731] 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".

[0732] E-commerce sites are expected to improve the user's shopping experience and, consequently, enhance commercial performance by recommending appropriate products based on the user's emotions. However, current systems struggle to provide product recommendations that take emotions into account, and lack the flexibility to respond to users' emotions.

[0733] 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.

[0734] In this invention, the server includes emotion recognition means for detecting the user's emotional state and recommending the most suitable product based on it, data management means for storing information entered by the user, and selection means for recommending activities relevant to the user based on the stored information. This makes it possible to recommend products optimized for the user's emotions and improve the purchasing experience.

[0735] "Data management means" refers to methods for efficiently storing information entered by users and retrieving it as needed.

[0736] "Selection methods" refer to means of analyzing stored information and recommending the most relevant activities and products to the user.

[0737] "Communication control means" are means to facilitate the exchange of information between users and to enable smooth communication.

[0738] "Information distribution means" refers to the means of providing users with the latest information on environmental protection.

[0739] "Emotion recognition means" refers to a method for detecting the emotional state of a user and recommending the most suitable product based on that state.

[0740] An "online communication platform" is a system that provides a space where users can communicate freely.

[0741] The system for realizing this application aims to improve the purchasing experience by detecting the user's emotional state and recommending products based on that emotion. The system includes data management means, selection means, communication control means, information distribution means, and emotion recognition means.

[0742] In this system, the server uses data management tools to efficiently store information entered by users through their terminals. To recognize the user's emotional state, facial recognition software such as the Google Cloud Vision API is used as an emotion recognition tool, determining emotions based on video data acquired from the terminal's camera. The server uses TensorFlow to analyze the obtained emotion data and extracts relevant products from the database using a selection tool.

[0743] The extracted product information is transmitted to the terminal via a communication control device, and the terminal uses an information distribution device to present products that are appropriate to the user's emotional state. For example, if the user is feeling stressed, a list of products that help with relaxation will be presented.

[0744] For example, if a user is browsing an online shopping site on their smartphone and the emotion recognition system determines that their current emotion is "stress," the system will generate a prompt saying, "Please recommend products that are suitable for my current emotion," and as a result, the server will display a list of relaxation items.

[0745] Examples of this prompt include the following:

[0746] "What products should be recommended when a user is under stress?"

[0747] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0748] Step 1:

[0749] A user browses an online shopping site using their device, and the camera captures a picture of the user's face. The device receives this facial image data as input and sends it to the Google Cloud Vision API for emotion recognition. The API analyzes this input data and returns the user's emotional state (e.g., joy, stress) as output.

[0750] Step 2:

[0751] The server receives emotional state data sent from the terminal. It analyzes this as input data, runs a generative AI model using TensorFlow, and outputs candidate product categories that best suit the user's emotions. Specifically, it runs an algorithm that evaluates the relationship between emotions and product attributes.

[0752] Step 3:

[0753] The server searches the database for relevant products based on the product category candidates obtained in step 2. It outputs a list of related products as search results. This list includes popular products and products with high review ratings within the category.

[0754] Step 4:

[0755] The server sends the generated list of related products to the terminal via a communication control means. The terminal receives this product list and displays the products to the user using an information distribution means. At this time, product descriptions tailored to the user's mood and links to special feature pages are also presented.

[0756] Step 5:

[0757] The user reviews the presented product list and selects items of interest. This allows them to view detailed pages or proceed with the purchase. For example, a featured page such as "Stress Relief Items" might be displayed.

[0758] 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.

[0759] 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.

[0760] 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.

[0761] 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.

[0762] 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.

[0763] 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.

[0764] 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.

[0765] 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.

[0766] 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."

[0767] 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.

[0768] 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.

[0769] 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.

[0770] 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.

[0771] 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.

[0772] 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.

[0773] 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.

[0774] 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.

[0775] 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.

[0776] 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.

[0777] 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.

[0778] 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.

[0779] The following is further disclosed regarding the embodiments described above.

[0780] (Claim 1)

[0781] A data storage means for storing information entered by the user,

[0782] A matching method that recommends relevant tasks to users based on saved information,

[0783] Communication means to facilitate information exchange between users,

[0784] Information provision means that provide the latest information on environmental protection,

[0785] A system that includes this.

[0786] (Claim 2)

[0787] The system according to claim 1, which takes regional conditions into consideration when recommending work based on the user's interests and skills.

[0788] (Claim 3)

[0789] The system according to claim 1, which provides an online forum to enable communication between users.

[0790] "Example 1"

[0791] (Claim 1)

[0792] A means of storing information that users input, including their abilities, interests, and local information,

[0793] In order to recommend activities and plans based on stored information, a matching mechanism is used to analyze the user's abilities, interests, and local conditions.

[0794] A means of supporting communication for sharing knowledge and experience among users,

[0795] Information distribution means for providing users with the latest knowledge from external sources,

[0796] A system that includes this.

[0797] (Claim 2)

[0798] The system according to claim 1, which takes regional conditions into consideration when recommending activities or plans based on the user's abilities and interests.

[0799] (Claim 3)

[0800] The system according to claim 1, which provides a virtual meeting room to enable communication between users.

[0801] "Application Example 1"

[0802] (Claim 1)

[0803] A data storage device and means for storing information entered by the user,

[0804] A matching device and means for recommending relevant products to a user based on stored information.

[0805] Communication devices and means for facilitating information exchange between users,

[0806] An information provision device and means for providing the latest product information,

[0807] A system that includes this.

[0808] (Claim 2)

[0809] The system according to claim 1, which takes regional conditions into consideration when recommending products based on the user's interests and purchase history.

[0810] (Claim 3)

[0811] The system according to claim 1, which provides an online bulletin board to enable communication between users.

[0812] "Example 2 of combining an emotion engine"

[0813] (Claim 1)

[0814] A storage means for storing information entered by the user,

[0815] A matching method using an emotion analysis engine that performs emotion recognition to recommend tasks relevant to the user based on stored information and behavioral data,

[0816] A communication method for optimizing information exchange between users,

[0817] Information provision methods that adjust the way information is presented based on the user's emotions,

[0818] A system that includes this.

[0819] (Claim 2)

[0820] The system according to claim 1, which takes into account regional factors and the emotional state of the user when recommending work based on the user's interests and abilities.

[0821] (Claim 3)

[0822] The system according to claim 1, which provides an online platform for facilitating and optimizing communication between users.

[0823] "Application example 2 when combining with an emotional engine"

[0824] (Claim 1)

[0825] A data management system for storing information entered by users,

[0826] A selection method for recommending relevant activities to users based on saved information,

[0827] Communication control means for facilitating information exchange between users,

[0828] Information distribution methods that provide the latest information on environmental protection,

[0829] A means including an emotion recognition means that detects the emotional state of a user and recommends the most suitable product based on it,

[0830] A system that includes this.

[0831] (Claim 2)

[0832] The system according to claim 1, which takes regional conditions into consideration when recommending activities based on the user's interests and abilities.

[0833] (Claim 3)

[0834] The system according to claim 1, which provides an online communication platform to enable communication between users. [Explanation of Symbols]

[0835] 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 data storage means for storing information entered by the user, A matching method that recommends relevant tasks to users based on saved information, Communication means to facilitate information exchange between users, Information provision means that provide the latest information on environmental protection, A system that includes this.

2. The system according to claim 1, which takes regional conditions into consideration when recommending work based on the user's interests and skills.

3. The system according to claim 1, which provides an online forum to enable communication between users.

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