system

Abstract

Provide a system. [Solution] means for accepting user registration information; A means for storing the received user registration information in a database; A means for recommending appropriate hobbies based on the user's interests and personality; A means for searching for community information related to the recommended hobby; a means of collecting user feedback and improving the recommendation algorithm; A system including:

Description

[Technical Field]

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

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

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

[0004] In modern society, many people face the problem of finding it difficult to pursue hobbies and interests, resulting in a lack of fulfillment in their lives. It is particularly difficult to find new hobbies, and many people are unable to find activities that interest them. Even if they do find a hobby, it can be time-consuming to find information about related communities and events, and it can be difficult to effectively assess the suitability of those hobbies for individual users. [Means for solving the problem]

[0005] The present invention provides a system that accepts user registration information and stores the accepted user registration information in a database. The system further includes a means for recommending appropriate hobbies based on the user's interests and personality, and a means for searching for community information related to the recommended hobbies. Additionally, the system has a means for collecting feedback from users and improving the recommendation algorithm. This system allows users to efficiently find hobbies that suit them and easily access related communities.

[0006] "User registration information" refers to basic information such as name, email address, and password provided by the user in order to use the system.

[0007] A "database" is a system that systematically stores user registration information and information related to hobbies and communities, and manages it in a form that can be searched and referenced later.

[0008] "Hobbies" are activities or interests that an individual user enjoys in their free time.

[0009] A "recommendation algorithm" is a calculation method or logic for suggesting hobbies that are suitable for a user based on the user's registration information and profile.

[0010] "Community information" refers to information such as online forums, local clubs, and events that users can join regarding specific hobbies or activities.

[0011] "Feedback" refers to opinions such as evaluations and improvements regarding hobby and community recommendations that users provide to the system.

[0012] A "user" is an individual who uses the system.

[0013] A "session" is temporary connection information for managing a series of operations from when a user logs in to when the user logs out of the system. [Brief explanation of the drawings]

[0014] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0015] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0018] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0019] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0020] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0027] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0034] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0035] This invention relates to a "hobby discovery support system" that helps users who do not have any hobbies to find new interests or hobbies. This system recommends hobbies and related communities that are suitable for each user based on the user's registered information, and further improves the recommendation algorithm based on user feedback.

[0036] User Registration / Login

[0037] Examples:

[0038] A user accesses the system and enters their name, email address, and password into the registration form.

[0039] The terminal transmits the entered registration information to the server, which stores this information in a database.

[0040] After registration is complete, the server sends a confirmation email to the user, who then checks the email and performs the login procedure.

[0041] Enter your email address and password into the login form, and the device will send the information to the server, which will then authenticate you.

[0042] Hobby recommendations

[0043] Examples:

[0044] Users answer a questionnaire about their interests and personality on a profile setting page within the system.

[0045] The device sends this data to the server, which then uses a hobby recommendation engine to select appropriate hobbies from a database.

[0046] The recommended hobby list is sent back from the server to the terminal, which displays it to the user.

[0047] Community information search and recommendation

[0048] Examples:

[0049] Users select hobbies that interest them within the system.

[0050] The terminal transmits the selection information to the server, and the server searches a database for community information related to the hobby.

[0051] The server returns relevant online forum and nearby club information to the terminal, which displays this to the user.

[0052] Gathering feedback and improving our algorithms

[0053] Examples:

[0054] Users provide feedback on hobbies and communities recommended by the system.

[0055] The terminal sends the feedback information to the server, which stores it in a database and analyzes it.

[0056] Based on the analysis results, the server improves the hobby recommendation engine's algorithm and improves the accuracy of the next recommendation.

[0057] System Operation

[0058] The specific operation of this system is as follows: Once a user registers and logs in, the system recommends hobbies based on the user's interests and personality information. In addition, by providing community information related to those hobbies, the system makes it easier for users to find places where they can actually experience those hobbies. Based on user feedback, the system improves its recommendation algorithm, enabling it to provide more accurate recommendations.

[0059] In this way, the present invention provides a system that helps users efficiently find new hobbies and deepen their interests, thereby increasing the sense of fulfillment in their lives.

[0060] The processing flow will be explained below.

[0061] Step 1: User Registration

[0062] A user accesses the system and enters their name, email address, and password into the registration form.

[0063] The terminal transmits the entered user registration information to the server.

[0064] The server stores the received registration information in a database.

[0065] The server will send a confirmation email to the user confirming the registration.

[0066] Step 2: User Login

[0067] The user enters their email address and password into the login form.

[0068] The terminal transmits the entered login information to the server.

[0069] The server checks the user information in the database and performs authentication.

[0070] If the authentication is successful, the server creates a session and sends a session ID to the terminal.

[0071] Step 3: Collect user information

[0072] Users visit a profile setup page and answer questions about their interests and personality.

[0073] The terminal transmits the collected user information to the server.

[0074] Step 4: Hobby recommendation

[0075] The server inputs the collected user profile information into the hobby recommendation engine.

[0076] The hobby recommendation engine uses an algorithm to select suitable hobbies for the user from a database.

[0077] The server transmits a list of recommended hobbies to the terminal.

[0078] The terminal displays the recommended hobbies to the user.

[0079] Step 5: Community Search

[0080] Users select hobbies that interest them within the system.

[0081] The terminal transmits the selected hobby information to the server.

[0082] The server searches a database for community information related to the hobby (online forums, local clubs, etc.).

[0083] Step 6: Community Nomination

[0084] The server returns the retrieved community information to the terminal.

[0085] The terminal displays the recommended community information to the user.

[0086] Step 7: Gather feedback

[0087] Users provide feedback on recommended hobbies and communities.

[0088] The terminal transmits the feedback information to the server.

[0089] The server stores the feedback information in a database.

[0090] Step 8: Improve the algorithm

[0091] The server analyzes the collected feedback.

[0092] The server improves the algorithm of the hobby recommendation engine based on the analysis results.

[0093] Through this series of steps, the system can effectively recommend hobbies and communities that are suitable for the user and provide more accurate recommendations.

[0094] Example 1

[0095] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0096] In recent years, many people have no hobbies or are looking for new interests. However, the amount of information available to find suitable hobbies and interests is enormous, making it difficult to efficiently find hobbies that meet individual needs. It is also difficult to find places and communities where people can actually experience their hobbies. Furthermore, there is a need for a method to effectively utilize provided feedback to improve recommendation algorithms and increase user satisfaction.

[0097] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0098] In this invention, the server includes means for accepting user registration information, means for storing the accepted user registration information in a database, means for authenticating the user using user authentication information, means for recommending appropriate hobbies based on the user's interests and personality, means for searching for community information related to the recommended hobbies, and means for collecting feedback from users and improving the recommendation algorithm. This makes it easier for users to efficiently find new hobbies and places where they can experience them, and also makes it possible to dynamically adjust the recommendation algorithm based on the provided feedback, thereby increasing user satisfaction.

[0099] "Means for accepting user registration information" refers to the interface through which a user accesses the system, inputs personal information such as name, email address, and password, and provides that information to the system.

[0100] "Means for saving the received user registration information in a database" refers to a function for safely and efficiently saving the input user registration information in a database.

[0101] "Means of authenticating a user using user authentication information" refers to the process of verifying whether a user is a legitimate registered user based on the email address and password entered into the login form.

[0102] "Means for recommending appropriate hobbies based on the user's interests and personality" refers to the algorithm and its operation that analyzes the questionnaire data answered by the user and suggests the most suitable hobbies.

[0103] "Means for searching for community information related to the recommended hobby" refers to a function that searches a database for community information such as online forums and physical clubs related to the suggested hobby and provides it.

[0104] "Means for collecting user feedback and improving the recommendation algorithm" refers to the process of storing user-provided feedback in a database and analyzing that data to improve the accuracy of the recommendation algorithm.

[0105] The present invention relates to a "hobby discovery support system" that supports users who do not have any hobbies in finding new interests or hobbies. Specific embodiments for carrying out the present invention will be described below.

[0106] User Registration / Login

[0107] This system begins when the user enters registration information. The user accesses the system and enters their name, email address, and password. When the user presses the "Register" button, the terminal sends this registration information to the server. The server saves this in a database (e.g., MySQL (registered trademark) database). The server then sends a confirmation email to the user's email address, and the user clicks on the link in the email to complete the login procedure. The user enters their email address and password in the login form, and the terminal sends the information to the server. The server compares this with the database and authenticates the user.

[0108] Hobby recommendations

[0109] After logging in, the user answers a questionnaire about their interests and personality on the profile setting page within the system. When the user presses the "Submit" button, the device sends this data to the server. The server then runs an interest recommendation engine (e.g., a recommendation algorithm built in Python) based on the collected data and selects appropriate interests from the database. The server then sends the recommended interest list to the device, which then displays it to the user.

[0110] Community information search and recommendation

[0111] The user selects a hobby that interests them from the displayed hobby list. When the user presses the "Select" button, the device sends the selection information to the server. The server searches its database for community information (e.g., online forums or physical clubs) related to the selected hobby. The search results are sent back to the device, which displays them to the user.

[0112] Gathering feedback and improving our algorithms

[0113] The user provides feedback on the hobbies and communities recommended by the system. When the user fills out the feedback form and presses the "Submit" button, the device sends the feedback information to the server, which stores it in a database and analyzes it. Based on the analysis results, the server improves the algorithm of the hobby recommendation engine, thereby improving the accuracy of the next recommendation.

[0114] Specific examples

[0115] User "Yamada Taro" accesses the system and enters his name "Yamada Taro," his email address "taro@example.com," and his password "password123." The server stores this information in a database and sends a confirmation email. The user receives the confirmation email and clicks the link to log in. After logging in, the user answers "blue" to the question "What is your favorite color?", and the device sends this to the server. The server includes hobbies related to blue, such as "fishing" and "astronomy," in a recommendation list and sends it to the device. When the user selects "fishing," the server searches for information such as "fishing forums" and "nearby fishing clubs" and sends it to the device. The user evaluates the fishing recommendation as "appropriate," and the device sends the feedback information to the server, which stores it in a database, analyzes it, and improves the algorithm.

[0116] Prompt Sentence Examples

[0117] "Please recommend a suitable hobby for a woman in her 20s who is interested in the outdoors."

[0118] "Find recommended online communities for middle school students interested in coding."

[0119] In this way, the present invention provides a system that helps users efficiently discover new hobbies and deepen their interests. By recommending hobbies based on the user's interests and personality and providing related community information, the system increases the user's opportunities to actually experience the hobbies, and improves the algorithm based on feedback, thereby increasing recommendation accuracy.

[0120] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0121] Step 1:

[0122] The user enters registration information.

[0123] Specific behavior:

[0124] The user enters their name, email address, and password into the system's registration form.

[0125] Input: Name, Email Address, Password

[0126] Output: Registration information is sent to the device

[0127] Step 2:

[0128] The terminal sends the input information to the server.

[0129] Specific behavior:

[0130] When the user presses the "Register" button, the device sends the user's name, email address, and password to the server.

[0131] Input: Registration information (name, email address, password)

[0132] Output: Registration information passed to the server

[0133] Step 3:

[0134] The server stores it in a database.

[0135] Specific behavior:

[0136] The server stores the received registration information in a database.

[0137] Input: Registration information

[0138] Output: Registration information is saved in the database

[0139] Step 4:

[0140] The server sends a confirmation email.

[0141] Specific behavior:

[0142] The server will send a confirmation email to the registered email address.

[0143] Input: User's email address

[0144] Output: A confirmation email is sent to the user.

[0145] Step 5:

[0146] The user checks the confirmation email and logs in.

[0147] Specific behavior:

[0148] The user clicks on the link in the confirmation email they received, goes to the login page, and enters their email address and password.

[0149] Input: Confirmation email, email address, password

[0150] Output: Login information is sent to the terminal

[0151] Step 6:

[0152] The device sends the login information to the server.

[0153] Specific behavior:

[0154] When a user enters their email address and password into the login form and presses the "Login" button, the device sends the information to the server.

[0155] Input: Login information (email address, password)

[0156] Output: Login information passed to the server

[0157] Step 7:

[0158] The server performs the authentication.

[0159] Specific behavior:

[0160] The server checks the submitted information against a database to authenticate the user, and if authentication is successful, the user is logged into the system.

[0161] Input: Login information, registration information in the database

[0162] Output: Authentication status of the user

[0163] Step 8:

[0164] The user responds to the survey.

[0165] Specific behavior:

[0166] Users answer a questionnaire about their interests and personality on a profile setting page within the system.

[0167] Input: Survey questions, user answers

[0168] Output: Response data is sent to the device

[0169] Step 9:

[0170] The terminal sends the survey results to the server.

[0171] Specific behavior:

[0172] When the user presses the "send" button, the terminal sends the answer data to the server.

[0173] Input: Response data

[0174] Output: Response data is sent to the server

[0175] Step 10:

[0176] The server makes recommendations using a hobby recommendation engine.

[0177] Specific behavior:

[0178] The server runs a hobby recommendation engine (e.g., a recommendation algorithm built in Python) based on the collected data and selects appropriate hobbies from the database.

[0179] Input: Answer data, hobby information in the database

[0180] Output: A list of recommended hobbies

[0181] Step 11:

[0182] The server sends the recommendation list to the terminal.

[0183] Specific behavior:

[0184] The server transmits the generated hobby recommendation list to the terminal.

[0185] Input: Recommended Hobbies List

[0186] Output: The recommendation list is passed to the device.

[0187] Step 12:

[0188] The terminal displays the list to the user.

[0189] Specific behavior:

[0190] The terminal displays the received recommendation list to the user.

[0191] Input: Recommendation list

[0192] Output: User can view the hobby list

[0193] Step 13:

[0194] The user selects a hobby that interests them.

[0195] Specific behavior:

[0196] The user selects a hobby that interests them from the displayed hobby list.

[0197] Input: Interest list, user selection

[0198] Output: The selected data is sent to the terminal.

[0199] Step 14:

[0200] The terminal transmits the selection information to the server.

[0201] Specific behavior:

[0202] When the user presses the "select" button, the terminal transmits the selected hobby information to the server.

[0203] Input: Selection data

[0204] Output: Selection data is passed to the server

[0205] Step 15:

[0206] The server retrieves the community information.

[0207] Specific behavior:

[0208] The server searches a database for community information (e.g., online forums and physical clubs) related to the selected hobby.

[0209] Input: hobby selection data, community information in the database

[0210] Output: Community information list

[0211] Step 16:

[0212] The server transmits the community information to the terminal.

[0213] Specific behavior:

[0214] The server transmits the community information of the search results to the terminal.

[0215] Input: Community Information List

[0216] Output: Community information is passed to the terminal

[0217] Step 17:

[0218] The terminal displays the community information to the user.

[0219] Specific behavior:

[0220] The terminal displays the received community information to the user.

[0221] Input: Community Information

[0222] Output: User can view community information

[0223] Step 18:

[0224] The user provides feedback.

[0225] Specific behavior:

[0226] Users enter feedback about the recommended hobbies and communities in a rating form.

[0227] Input: Evaluation form, user feedback

[0228] Output: Feedback data is sent to the device

[0229] Step 19:

[0230] The terminal sends feedback information to the server.

[0231] Specific behavior:

[0232] When the user presses the "send" button, the terminal sends the feedback information to the server.

[0233] Input: Feedback data

[0234] Output: Feedback data is passed to the server

[0235] Step 20:

[0236] The server stores the feedback in a database.

[0237] Specific behavior:

[0238] The server stores the received feedback in a database.

[0239] Input: Feedback data

[0240] Output: Feedback data is saved in a database

[0241] Step 21:

[0242] The server performs the analysis.

[0243] Specific behavior:

[0244] The server analyzes the stored feedback and extracts data about user interests and satisfaction.

[0245] Input: Feedback data

[0246] Output: Analysis results

[0247] Step 22:

[0248] The server improves the algorithm.

[0249] Specific behavior:

[0250] The server adjusts the hobby recommendation engine's algorithm based on the analysis results, improving the accuracy of recommendations from next time onwards.

[0251] Input: Analysis results

[0252] Output: An improved recommendation algorithm

[0253] (Application example 1)

[0254] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0255] Conventional methods have not only failed to provide users searching for hobbies that match their interests, but also to provide them with information on products and communities related to those hobbies. Furthermore, the accuracy of the information provided is low, making it difficult to increase user satisfaction.

[0256] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0257] In this invention, the server includes means for accepting user registration information, means for storing the accepted user registration information in a database, means for recommending appropriate hobbies based on the user's interests and personality, means for searching for community information related to the recommended hobbies, means for collecting user feedback and improving the recommendation algorithm, means for recommending related products based on the user's interests, and means for providing users with information on related online forums and nearby clubs, thereby enabling users to discover new hobbies based on their interests and simultaneously obtain related product and community information.

[0258] "User registration information" refers to basic information such as name, email address, and password provided by the user when registering with the system.

[0259] "Database" means a digital information management system for storing data related to user registration information, feedback, and hobby recommendations.

[0260] A "hobby recommendation engine" is a software component that calculates and recommends appropriate hobbies based on a user's interests and personality.

[0261] "Community information" is information such as online forums and local clubs related to hobbies that may interest the user.

[0262] "Feedback" refers to information such as evaluations and opinions provided by users regarding recommended hobby or community information.

[0263] A "recommendation algorithm" is a computational method for analyzing user interests and feedback and reflecting them in the next hobby recommendation.

[0264] "Products" are products or services related to a user's interests or hobbies.

[0265] An "online forum" is a place on the Internet where people share information and communicate about a particular hobby or interest.

[0266] A "club" is a physical place or association where people with common hobbies or interests come together.

[0267] The system for implementing this invention allows users to discover new hobbies and provides them with information on products and communities related to those hobbies. This system is mainly composed of three elements: a server, a terminal, and a user.

[0268] System hardware and software configuration

[0269] Hardware

[0270] Server: Runs on the cloud and is responsible for data processing and storage.

[0271] Device: A device that is directly controlled by the user, such as a smartphone or smart glasses.

[0272] software

[0273] Firebase Auth: Provides user authentication and login functionality.

[0274] Firebase Firestore: A database for storing and retrieving data in real time.

[0275] Google® Cloud AI: An AI engine that runs recommendation algorithms and feedback analysis.

[0276] React Native: A framework for building the front end of smartphone apps.

[0277] Processing Details

[0278] User Registration and Login

[0279] Users register their name, email address, and password using a terminal. This information is sent to the server using Firebase Auth for authentication. When the user logs in, the authentication information is sent again to the server, and if authentication is successful, the user can access Firebase Firestore.

[0280] Hobby recommendations

[0281] Users fill out a profile setting page and answer a questionnaire about their interests and personality. This data is sent from the device to a server, where it is processed by a Google Cloud AI recommendation engine to select appropriate hobbies.

[0282] Recommending related products and community information

[0283] Based on the recommended hobbies, the server searches the product database for relevant product information, and also searches the community information stored in Firebase Firestore to provide the user with information on online forums and nearby clubs.

[0284] Gathering feedback and improving the algorithm

[0285] Users provide feedback on the recommended hobbies and community information, which is stored in Firebase Firestore and analyzed by Google Cloud AI to improve the recommendation algorithm.

[0286] Specific examples

[0287] For example, if a user responds that they are interested in "outdoors," the server may recommend outdoor-related products (tents, backpacks, etc.) and may also provide information about online forums related to outdoor activities and nearby hiking clubs.

[0288] Prompt Sentence Examples

[0289] 1. Hobby recommendation prompt:

[0290] Based on your user interest survey response data, please provide the following information:

[0291] Recommended Hobbies List

[0292] A list of product categories related to each hobby

[0293] A brief explanation of the reason for the recommendation

[0294] 2. Community recommendation prompt:

[0295] Based on your selected interests, please provide the following information:

[0296] Online forum URLs related to each hobby

[0297] Nearby hobby club information related to each hobby (with location information)

[0298] This allows users to discover new hobbies based on their own interests and simultaneously obtain information on products and communities related to those hobbies.

[0299] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0300] Step 1:

[0301] A user accesses the system using a terminal and enters their name, email address, and password. The entered registration information is sent from the terminal to the server via Firebase Auth. The server saves this information in a database and sends a confirmation email to the user. The user logs in using the confirmation email they received. The input information is an email address and password, and the output is a flag indicating successful login.

[0302] Step 2:

[0303] After the user logs in, the device will be taken to a profile setting page. The user will then answer a questionnaire about their interests and personality. The survey response data will be sent from the device to the server and stored in Firebase Firestore. The input will be the survey response data, and the output will be the data stored in the database.

[0304] Step 3:

[0305] The server sends a response request to Google Cloud AI based on the survey response data stored in Firebase Firestore, and calculates the hobbies suitable for the user. The calculated hobbies list is returned to the server, which then sends it to the device, which displays it to the user. The input is the survey response data, and the output is the recommended hobbies list.

[0306] Step 4:

[0307] When a user selects a hobby that interests them from the recommended hobbies, the device sends this information to the server. The server searches for related product information from the product database and sends a related product list to the device. It also searches for related online forums and nearby club information from Firebase Firestore and sends this information to the device. The input is the selected hobby information, and the output is a related product list and community information.

[0308] Step 5:

[0309] Users provide feedback on the displayed related product list and community information. The feedback information is sent from the device to the server and stored in Firebase Firestore. The saved feedback information is used for analysis by Google Cloud AI to improve the recommendation algorithm. The input is the feedback information, and the output is an improved recommendation algorithm and improved recommendation accuracy for the next time.

[0310] Step 6:

[0311] The server periodically analyzes the accumulated feedback information and updates the generative AI model via Google Cloud AI, which improves the accuracy of the next hobby and product recommendations and increases user satisfaction. The input is the accumulated feedback information, and the output is the updated generative AI model.

[0312] By following the steps above, users can efficiently discover new hobbies and appropriately obtain product and community information related to those hobbies.

[0313] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0314] This invention relates to a "hobby discovery support system" that helps users who do not have any hobbies to discover new interests and hobbies. In particular, it adds a function to recognize the user's emotional state and recommend appropriate hobbies and related communities based on that emotion. The system also includes a means to collect user emotional feedback and improve the emotion engine.

[0315] User Registration / Login

[0316] Examples:

[0317] A user accesses the system and enters their name, email address, and password into the registration form.

[0318] The terminal transmits the entered user registration information to the server.

[0319] The server stores the received registration information in a database.

[0320] The server will send a confirmation email to the user confirming the registration.

[0321] User Login

[0322] Examples:

[0323] The user enters their email address and password into the login form.

[0324] The terminal transmits the entered login information to the server.

[0325] The server checks the user information in the database and performs authentication.

[0326] If the authentication is successful, the server creates a session and sends a session ID to the terminal.

[0327] User information collection

[0328] Examples:

[0329] Users visit a profile setup page and answer questions about their interests and personality.

[0330] The terminal transmits the collected user information to the server.

[0331] emotion recognition

[0332] Examples:

[0333] Users access the system through an emotion-recognition camera.

[0334] The terminal transmits the user's facial image captured by the camera to the server.

[0335] The server uses an emotion engine to recognize the user's emotions (happiness, sadness, surprise, etc.) from the image.

[0336] The recognized emotion information is stored on the server.

[0337] Hobby recommendations

[0338] Examples:

[0339] The server selects appropriate hobbies using a hobby recommendation engine based on the recognized emotion information and existing profile information.

[0340] The server transmits a list of recommended hobbies to the terminal.

[0341] The terminal displays the recommended hobbies to the user.

[0342] Community Search

[0343] Examples:

[0344] Users select hobbies that interest them within the system.

[0345] The terminal transmits the selected hobby information to the server.

[0346] The server searches a database for community information related to the hobby (online forums, local clubs, etc.).

[0347] Community Recommendations

[0348] Examples:

[0349] The server returns the retrieved community information to the terminal.

[0350] The terminal displays the recommended community information to the user.

[0351] Feedback collection

[0352] Examples:

[0353] Users provide feedback on recommended hobbies and communities.

[0354] The feedback also includes a rating based on the user's emotional state.

[0355] The terminal transmits the feedback information to the server.

[0356] The server stores the feedback information in a database.

[0357] Algorithm Improvement

[0358] Examples:

[0359] The server analyzes the collected feedback.

[0360] The server improves the algorithms of the hobby recommendation engine and the emotion engine based on the analysis results.

[0361] Through this series of steps, the system can effectively recommend hobbies and communities that are suitable for the user and provide more accurate recommendations. By taking the user's emotional state into account, the quality of the recommended hobbies and communities can be further improved, allowing the user to discover new hobbies in a more satisfying way.

[0362] The processing flow will be explained below.

[0363] Step 1: User Registration

[0364] A user accesses the system and enters their name, email address, and password into the registration form.

[0365] The terminal transmits the entered user registration information to the server.

[0366] The server stores the received registration information in a database.

[0367] The server will send a confirmation email to the user confirming the registration.

[0368] Step 2: User Login

[0369] The user enters their email address and password into the login form.

[0370] The terminal transmits the entered login information to the server.

[0371] The server checks the user information in the database and performs authentication.

[0372] If the authentication is successful, the server creates a session and sends a session ID to the terminal.

[0373] Step 3: Collect user information

[0374] Users visit a profile setup page and answer questions about their interests and personality.

[0375] The terminal transmits the collected user information to the server.

[0376] Step 4: Emotion Recognition

[0377] Users access the system through an emotion-recognition camera.

[0378] The terminal transmits the user's facial image captured by the camera to the server.

[0379] The server uses an emotion engine to recognize the user's emotions (happiness, sadness, surprise, etc.) from the image.

[0380] The recognized emotion information is stored on the server.

[0381] Step 5: Hobby recommendation

[0382] The server selects appropriate hobbies using a hobby recommendation engine based on the recognized emotion information and existing profile information.

[0383] The server transmits a list of recommended hobbies to the terminal.

[0384] The terminal displays the recommended hobbies to the user.

[0385] Step 6: Community Search

[0386] Users select hobbies that interest them within the system.

[0387] The terminal transmits the selected hobby information to the server.

[0388] The server searches a database for community information related to the hobby (online forums, local clubs, etc.).

[0389] Step 7: Community Nomination

[0390] The server returns the retrieved community information to the terminal.

[0391] The terminal displays the recommended community information to the user.

[0392] Step 8: Gather feedback

[0393] Users provide feedback on recommended hobbies and communities, including ratings based on the user's emotional state.

[0394] The terminal transmits the feedback information to the server.

[0395] The server stores the feedback information in a database.

[0396] Step 9: Improve the algorithm

[0397] The server analyzes the collected feedback.

[0398] The server improves the algorithms of the hobby recommendation engine and the emotion engine based on the analysis results.

[0399] This detailed processing flow allows users to receive more accurate interest and community recommendations based on their emotional state, and allows us to leverage feedback to continuously improve the algorithm, thereby increasing system performance and user satisfaction.

[0400] Example 2

[0401] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0402] In today's world, it is difficult for users who do not have any hobbies to discover new hobbies or interests that suit them. Furthermore, recommended hobbies and communities may not necessarily be suitable for each user unless the emotional state of each individual user is taken into consideration. Therefore, there is a need for a method to collect users' emotional feedback and use it to improve the system's recommendation accuracy.

[0403] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for accepting user registration information, means for storing the accepted user registration information in a database, means for recognizing the emotional state of the user and recommending appropriate hobbies based on the emotional state and the user's interests and personality, means for searching the database for community information related to the recommended hobbies, and means for collecting feedback from the user and improving the recommendation algorithm and emotion recognition engine based on the feedback. This enables highly accurate recommendation of hobbies and communities based on the user's emotional state.

[0404] "User registration information" refers to personal information such as name, email address, and password that a user enters when accessing the system for the first time.

[0405] A "database" is a data structure that the system uses to store and manage data such as user information, emotional state, and feedback.

[0406] "Emotional state" is information indicating a psychological state such as joy, sadness, surprise, etc., recognized from the user's facial expression.

[0407] "Hobbies" refer to activities or areas in which a user has personal interests or concerns.

[0408] "Recommending" refers to the act of the system presenting hobbies and communities that it deems most suitable based on the user's information.

[0409] "Community information" refers to information such as online forums and physical clubs related to a particular hobby.

[0410] "Feedback" is information such as the user's evaluation and opinions of the recommended hobby or community.

[0411] An "algorithm" is a computational procedure that allows the system to analyze user information and emotional state and recommend optimal hobbies and communities.

[0412] An "emotion recognition engine" is a piece of software that analyzes a user's facial image and other data to recognize their emotional state.

[0413] This invention relates to a "hobby discovery support system" that allows users without hobbies to discover new hobbies and interests that suit them and find communities based on those hobbies. This system has the function of recognizing the user's emotional state and recommending appropriate hobbies and related communities based on that emotion. It can also collect user emotional feedback and use that feedback to improve the system's recommendation algorithm and emotion recognition engine.

[0414] Hardware and Software Configuration

[0415] The main components of the system include:

[0416] Server: Stores and manages user information, emotion information, and feedback information in a database. The server runs an emotion recognition engine and a hobby recommendation engine to provide appropriate information to users.

[0417] Terminal: A device that allows users to input and obtain information. Examples include PCs, smartphones, and tablets.

[0418] Database: A data structure for storing user information, emotion data, hobby information, community information, and feedback information.

[0419] Emotion recognition engine: Software that analyzes a user's facial image to recognize their emotional state. Examples of such engines include Microsoft® Azure® Face API and Google Cloud Vision.

[0420] Hobby recommendation engine: Software that uses a generative AI model to generate optimal hobbies based on a user's emotional state and profile information.

[0421] Details of system processing

[0422] User Registration / Login

[0423] First, a user accesses the system and enters their name, email address, and password. The device sends this to the server, which stores it in a database. Once registration is complete, a confirmation email is sent. When the user logs in, they enter their email address and password, and the device again sends this to the server. The server compares this with the information in the database, and if authentication is successful, it generates a session ID and sends it to the device.

[0424] User information collection

[0425] Users answer questions about their interests and personality on a profile setup page, and the device sends the collected information to a server, which stores it in a database.

[0426] emotion recognition

[0427] The user provides a facial image through the emotion recognition camera, and the device sends the facial image to the server, which then uses an emotion recognition engine to analyze the user's emotional state. The analysis results are then stored in a database.

[0428] Hobby recommendations

[0429] The server runs a hobby recommendation engine using the latest emotion information and user profile information, and sends the generated hobby list to the terminal and displays it to the user.

[0430] Community Search

[0431] The user selects the hobbies they are interested in from the displayed hobbies, and the terminal sends the selection information to the server, which then searches the database for related community information.

[0432] Community Recommendations

[0433] The retrieved community information is sent to the terminal and displayed to the user.

[0434] Feedback collection

[0435] Users provide feedback on their hobbies and communities, and their devices send it to the server, which stores the feedback information in a database.

[0436] Algorithm Improvement

[0437] The server analyzes the collected feedback and dynamically adjusts the parameters of the recommendation algorithm and emotion recognition engine.

[0438] Examples of concrete examples and prompts

[0439] As a specific example of operation, if a user expresses an interest in "painting," the server will recommend hobbies related to "watercolor painting" and "digital art." If the user is interested in "watercolor painting," the server will recommend community information such as "local watercolor painting clubs" and "online watercolor painting forums."

[0440] Here are some examples of prompts:

[0441] "What new hobbies should we recommend to users when they feel joy?"

[0442] "Where is the best community for users interested in watercolor painting?"

[0443] As described above, the "hobby discovery support system" of the present invention realizes highly accurate recommendation of hobbies and communities that take into account the emotional state of the user.

[0444] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0445] Step 1:

[0446] Enter user registration information

[0447] A user fills in the system's registration form with their name, email address, and password, which serves as input data for the system, and is used to identify the user.

[0448] Step 2:

[0449] Sending user registration information

[0450] The device sends the entered user information to the server in the form of an HTTP POST request. The data is encrypted, thereby protecting the user information.

[0451] Step 3:

[0452] Saving user registration information

[0453] The server validates the received user information and checks for invalid data. After validation is complete, the server stores the information in the "User Information" table in the database. As an output, the server generates a confirmation of successful registration and sends it to the mail server.

[0454] Step 4:

[0455] Enter your user login information

[0456] A user enters an email address and password into a login form. This information is the input data for authentication.

[0457] Step 5:

[0458] Sending user login information

[0459] The device sends the entered login information to the server, where it is also encrypted to ensure data security.

[0460] Step 6:

[0461] User authentication process

[0462] The server searches for the corresponding user information in the "User Information" table in the database and compares it with the entered password. If authentication is successful, the server creates a session, generates a session ID and sends it to the terminal. As an output, the terminal displays the main page to the user.

[0463] Step 7:

[0464] User information collection

[0465] Users access a profile setup page and answer questions about their interests and personality, which are then used as input data for the system's profile data.

[0466] Step 8:

[0467] Sending and storing user information

[0468] The terminal sends the collected user information to the server, which stores it in the "User Profile" table in the database. As an output, the server notifies the user that the profile has been set up.

[0469] Step 9:

[0470] Emotion Recognition Camera Setup

[0471] The user activates the emotion recognition camera and captures facial images through the device, which serve as input data for emotion recognition.

[0472] Step 10:

[0473] Facial image transmission and emotion analysis

[0474] The device sends the captured face image to the server, which then calls an emotion recognition engine (e.g., Microsoft Azure Face API) to analyze the user's emotion from the image. As an output, analyzed emotion information is generated and stored in the "emotion data" table in the database.

[0475] Step 11:

[0476] Running a hobby recommendation engine

[0477] The server retrieves the latest emotion information and user profile information and runs an interest recommendation engine. This engine generates appropriate hobbies using a generative AI model. It uses emotion information and profile information as input and generates a list of hobbies as output.

[0478] Step 12:

[0479] Submit and view recommended hobby lists

[0480] The server sends the recommended hobby list to the terminal, which displays it to the user and provides an interface to attract the user's interest.

[0481] Step 13:

[0482] Start a Community Search

[0483] The user selects a hobby from the displayed hobby list that they are interested in. The terminal then sends information about the selected hobby to the server.

[0484] Step 14:

[0485] Search for related community information

[0486] The server retrieves community information related to the selected hobby from a database, such as online forums and physical club data.

[0487] Step 15:

[0488] Submitting and Viewing Community Information

[0489] The server sends the retrieved community information to the terminal, which displays it to the user, allowing the user to access communities that interest them.

[0490] Step 16:

[0491] Feedback Input

[0492] Users input feedback on the recommended hobbies and communities, which serves as input data for improving the system.

[0493] Step 17:

[0494] Send and save feedback

[0495] The terminal sends the feedback information to the server, which stores it in the "feedback data" table of the database. As an output, the server notifies the user of the confirmation of receipt of the feedback.

[0496] Step 18:

[0497] Algorithm analysis and updates

[0498] The server analyzes the collected feedback and dynamically adjusts the parameters of the recommendation algorithm and emotion recognition engine based on the results. The output is an improved algorithm, which improves the accuracy of recommendations from the next time onwards.

[0499] (Application example 2)

[0500] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0501] Conventional recommendation systems recommend hobbies and products based on a user's static interests and personality information, but they lack the ability to provide real-time recommendations that take into account the user's emotional state. This can result in a failure to meet users' momentary needs and a decrease in satisfaction. Furthermore, there is a lack of concrete measures to improve the shopping experience in physical stores.

[0502] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for accepting user registration information, means for storing the accepted user registration information in a database, means for recommending appropriate hobbies based on the user's interests and personality, means for recognizing the user's emotional state using an emotion recognition camera, means for recommending products based on the recognized emotional information, means for displaying the recommended products on a visual device, and means for collecting feedback from users and improving the recommendation algorithm. This enables real-time product recommendations based on the user's emotional state, thereby improving the quality of shopping experiences in physical stores.

[0503] "User registration information" refers to personal information such as the user's name, email address, and password.

[0504] "Database" refers to a computer system or storage for systematically storing and retrieving information.

[0505] "Appropriate hobbies" refer to activities and interests that are recommended based on a user's interests and personality.

[0506] An "emotion recognition camera" refers to an image processing device that captures a user's facial expressions and analyzes their emotional state.

[0507] "Emotion information" refers to data collected by an emotion-recognition camera about a user's emotional state, such as happiness, sadness, or surprise.

[0508] "Means for recommending products" refers to the function of selecting and presenting appropriate products based on the user's emotional information.

[0509] "Visual device" refers to a device that allows a user to receive information visually, such as smart glasses or a head-mounted display.

[0510] "Feedback" refers to the evaluations and impressions that users give about recommended hobbies or products.

[0511] A "recommendation algorithm" refers to a computational method for selecting appropriate hobbies and products using data such as a user's interests, personality, and emotional state.

[0512] "Brick and mortar store" refers to a retail store that is a physical location where users can visit in person to purchase goods or services.

[0513]

[0514] MODE FOR CARRYING OUT THE INVENTION

[0515] This invention is an emotion recognition-based hobby and product recommendation system that improves the shopping experience in brick-and-mortar stores based on the user's emotional state. The system accepts user registration information, stores it in a database, and recommends hobbies and products based on the user's static interests and personality information, as well as real-time emotional information.

[0516] The server includes the following means:

[0517] Method for accepting user registration information: The user enters personal information into the registration form and sends it from the terminal to the server, whereupon the user's basic information is stored in a database.

[0518] A means for storing the received user registration information in a database: The server systematically stores and manages the received information in a database.

[0519] A means of recommending appropriate hobbies based on the user's interests and personality: The server uses a hobby recommendation engine to select and recommend appropriate hobbies based on the data on interests and personality provided by the user.

[0520] A means of recognizing a user's emotional state using an emotion recognition camera: A camera installed in the device (visual device such as smart glasses) captures the user's face in real time and sends the image to an emotion recognition engine to analyze the emotional information.

[0521] Means for recommending products based on recognized emotional information: Based on the recognized emotional information, a recommendation engine is used to select appropriate products and present them to the user.

[0522] Means for displaying recommended products on a visual device: Product information sent from the server is overlaid on the display of the visual device.

[0523] A means of collecting user feedback and improving the recommendation algorithm: User feedback is sent from the device to the server and used to dynamically adjust the recommendation algorithm.

[0524] Hardware and software used

[0525] Hardware: smart glasses, cameras, servers, visual devices (e.g., Google Glass, Vuzix Blade)

[0526] Software: Emotion recognition module (e.g., OpenCV, dlib, Face++ API), hobby recommendation engine, product recommendation engine, database management system

[0527] Data flow and specific examples

[0528] A user wears smart glasses while shopping in a physical store. The glasses' built-in camera captures the user's facial image and analyzes it using an emotion recognition engine. For example, if the system detects that the user looks slightly tired, it generates a list of products with a refreshing effect and overlays them on the smart glasses' display. This allows the user to visually check recommended products while walking around the store.

[0529] Examples of prompt statements

[0530] "Please recommend products suitable for users who look tired. For example, aroma products or massage machines like the ones below."

[0531] In this way, by providing a specific form for implementing the invention, it becomes possible to recommend products in real time according to the user's emotional state, thereby improving the quality of the shopping experience in physical stores.

[0532] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0533] Step 1:

[0534] The server accepts user registration information. The data to be entered includes name, email address, and password. The user enters this data into the registration form and sends it from the terminal to the server. The server receives this data and stores it systematically in a database.

[0535] Step 2:

[0536] The device collects data to recommend appropriate hobbies based on the user's interests and personality. The user accesses a profile setting page and answers questions about their interests and personality. The collected data is sent from the device to a server, which stores it in a database.

[0537] Step 3:

[0538] The device recognizes the user's emotional state using an emotion recognition camera installed in the smart glasses. The camera captures the user's facial image in real time and sends the image to a server. The server then uses an emotion recognition engine to analyze the user's emotional information from the image and stores the results in a database.

[0539] Step 4:

[0540] The server recommends products based on the recognized emotion information. The user's emotion information and past interest data are used as input. The server's recommendation engine uses this data to create a list of appropriate products and sends the information to the device.

[0541] Step 5:

[0542] The terminal displays the recommended products on a visual device. The recommended products are overlaid on the display of the visual device (e.g., smart glasses). The user can view the recommended products through the visual device while moving around the physical store.

[0543] Step 6:

[0544] Users provide feedback on the recommended products and the system's recommendation accuracy. The feedback includes information about interests and satisfaction, and is sent from the device to the server, which stores it in a database.

[0545] Step 7:

[0546] The server improves the recommendation algorithm based on the collected feedback. It analyzes the feedback data and uses the results to dynamically adjust the recommendation algorithm, thereby improving the accuracy of future recommendations.

[0547] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0548] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0549] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0550] [Second embodiment]

[0551] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0552] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0553] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0554] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0555] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0556] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0557] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0558] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0559] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0560] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0561] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0562] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0563] This invention relates to a "hobby discovery support system" that helps users who do not have any hobbies to find new interests or hobbies. This system recommends hobbies and related communities that are suitable for each user based on the user's registered information, and further improves the recommendation algorithm based on user feedback.

[0564] User Registration / Login

[0565] Examples:

[0566] A user accesses the system and enters their name, email address, and password into the registration form.

[0567] The terminal transmits the entered registration information to the server, which stores this information in a database.

[0568] After registration is complete, the server sends a confirmation email to the user, who then checks the email and performs the login procedure.

[0569] Enter your email address and password into the login form, and the device will send the information to the server, which will then authenticate you.

[0570] Hobby recommendations

[0571] Examples:

[0572] Users answer a questionnaire about their interests and personality on a profile setting page within the system.

[0573] The device sends this data to the server, which then uses a hobby recommendation engine to select appropriate hobbies from a database.

[0574] The recommended hobby list is sent back from the server to the terminal, which displays it to the user.

[0575] Community information search and recommendation

[0576] Examples:

[0577] Users select hobbies that interest them within the system.

[0578] The terminal transmits the selection information to the server, and the server searches a database for community information related to the hobby.

[0579] The server returns relevant online forum and nearby club information to the terminal, which displays this to the user.

[0580] Gathering feedback and improving our algorithms

[0581] Examples:

[0582] Users provide feedback on hobbies and communities recommended by the system.

[0583] The terminal sends the feedback information to the server, which stores it in a database and analyzes it.

[0584] Based on the analysis results, the server improves the hobby recommendation engine's algorithm and improves the accuracy of the next recommendation.

[0585] System Operation

[0586] The specific operation of this system is as follows: Once a user registers and logs in, the system recommends hobbies based on the user's interests and personality information. In addition, by providing community information related to those hobbies, the system makes it easier for users to find places where they can actually experience those hobbies. Based on user feedback, the system improves its recommendation algorithm, enabling it to provide more accurate recommendations.

[0587] In this way, the present invention provides a system that helps users efficiently find new hobbies and deepen their interests, thereby increasing the sense of fulfillment in their lives.

[0588] The processing flow will be explained below.

[0589] Step 1: User Registration

[0590] A user accesses the system and enters their name, email address, and password into the registration form.

[0591] The terminal transmits the entered user registration information to the server.

[0592] The server stores the received registration information in a database.

[0593] The server will send a confirmation email to the user confirming the registration.

[0594] Step 2: User Login

[0595] The user enters their email address and password into the login form.

[0596] The terminal transmits the entered login information to the server.

[0597] The server checks the user information in the database and performs authentication.

[0598] If the authentication is successful, the server creates a session and sends a session ID to the terminal.

[0599] Step 3: Collect user information

[0600] Users visit a profile setup page and answer questions about their interests and personality.

[0601] The terminal transmits the collected user information to the server.

[0602] Step 4: Hobby recommendation

[0603] The server inputs the collected user profile information into the hobby recommendation engine.

[0604] The hobby recommendation engine uses an algorithm to select suitable hobbies for the user from a database.

[0605] The server transmits a list of recommended hobbies to the terminal.

[0606] The terminal displays the recommended hobbies to the user.

[0607] Step 5: Community Search

[0608] Users select hobbies that interest them within the system.

[0609] The terminal transmits the selected hobby information to the server.

[0610] The server searches a database for community information related to the hobby (online forums, local clubs, etc.).

[0611] Step 6: Community Nomination

[0612] The server returns the retrieved community information to the terminal.

[0613] The terminal displays the recommended community information to the user.

[0614] Step 7: Gather feedback

[0615] Users provide feedback on recommended hobbies and communities.

[0616] The terminal transmits the feedback information to the server.

[0617] The server stores the feedback information in a database.

[0618] Step 8: Improve the algorithm

[0619] The server analyzes the collected feedback.

[0620] The server improves the algorithm of the hobby recommendation engine based on the analysis results.

[0621] Through this series of steps, the system can effectively recommend hobbies and communities that are suitable for the user and provide more accurate recommendations.

[0622] Example 1

[0623] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0624] In recent years, many people have no hobbies or are looking for new interests. However, the amount of information available to find suitable hobbies and interests is enormous, making it difficult to efficiently find hobbies that meet individual needs. It is also difficult to find places and communities where people can actually experience their hobbies. Furthermore, there is a need for a method to effectively utilize provided feedback to improve recommendation algorithms and increase user satisfaction.

[0625] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0626] In this invention, the server includes means for accepting user registration information, means for storing the accepted user registration information in a database, means for authenticating the user using user authentication information, means for recommending appropriate hobbies based on the user's interests and personality, means for searching for community information related to the recommended hobbies, and means for collecting feedback from users and improving the recommendation algorithm. This makes it easier for users to efficiently find new hobbies and places where they can experience them, and also makes it possible to dynamically adjust the recommendation algorithm based on the provided feedback, thereby increasing user satisfaction.

[0627] "Means for accepting user registration information" refers to the interface through which a user accesses the system, inputs personal information such as name, email address, and password, and provides that information to the system.

[0628] "Means for saving the received user registration information in a database" refers to a function for safely and efficiently saving the input user registration information in a database.

[0629] "Means of authenticating a user using user authentication information" refers to the process of verifying whether a user is a legitimate registered user based on the email address and password entered into the login form.

[0630] "Means for recommending appropriate hobbies based on the user's interests and personality" refers to the algorithm and its operation that analyzes the questionnaire data answered by the user and suggests the most suitable hobbies.

[0631] "Means for searching for community information related to the recommended hobby" refers to a function that searches a database for community information such as online forums and physical clubs related to the suggested hobby and provides it.

[0632] "Means for collecting user feedback and improving the recommendation algorithm" refers to the process of storing user-provided feedback in a database and analyzing that data to improve the accuracy of the recommendation algorithm.

[0633] The present invention relates to a "hobby discovery support system" that supports users who do not have any hobbies in finding new interests or hobbies. Specific embodiments for carrying out the present invention will be described below.

[0634] User Registration / Login

[0635] This system begins when the user enters registration information. The user accesses the system and enters their name, email address, and password. When the user presses the "Register" button, the terminal sends this registration information to the server. The server saves this in a database (e.g., MySQL database). The server then sends a confirmation email to the user's email address, and the user clicks on the link in the email to complete the login procedure. The user enters their email address and password in the login form, and the terminal sends the information to the server. The server compares this with the database and authenticates the user.

[0636] Hobby recommendations

[0637] After logging in, the user answers a questionnaire about their interests and personality on the profile setting page within the system. When the user presses the "Submit" button, the device sends this data to the server. The server then runs an interest recommendation engine (e.g., a recommendation algorithm built in Python) based on the collected data and selects appropriate interests from the database. The server then sends the recommended interest list to the device, which then displays it to the user.

[0638] Community information search and recommendation

[0639] The user selects a hobby that interests them from the displayed hobby list. When the user presses the "Select" button, the device sends the selection information to the server. The server searches its database for community information (e.g., online forums or physical clubs) related to the selected hobby. The search results are sent back to the device, which displays them to the user.

[0640] Gathering feedback and improving our algorithms

[0641] The user provides feedback on the hobbies and communities recommended by the system. When the user fills out the feedback form and presses the "Submit" button, the device sends the feedback information to the server, which stores it in a database and analyzes it. Based on the analysis results, the server improves the algorithm of the hobby recommendation engine, thereby improving the accuracy of the next recommendation.

[0642] Specific examples

[0643] User "Yamada Taro" accesses the system and enters his name "Yamada Taro," his email address "taro@example.com," and his password "password123." The server stores this information in a database and sends a confirmation email. The user receives the confirmation email and clicks the link to log in. After logging in, the user answers "blue" to the question "What is your favorite color?", and the device sends this to the server. The server includes hobbies related to blue, such as "fishing" and "astronomy," in a recommendation list and sends it to the device. When the user selects "fishing," the server searches for information such as "fishing forums" and "nearby fishing clubs" and sends it to the device. The user evaluates the fishing recommendation as "appropriate," and the device sends the feedback information to the server, which stores it in a database, analyzes it, and improves the algorithm.

[0644] Prompt Sentence Examples

[0645] "Please recommend a suitable hobby for a woman in her 20s who is interested in the outdoors."

[0646] "Find recommended online communities for middle school students interested in coding."

[0647] In this way, the present invention provides a system that helps users efficiently discover new hobbies and deepen their interests. By recommending hobbies based on the user's interests and personality and providing related community information, the system increases the user's opportunities to actually experience the hobbies, and improves the algorithm based on feedback, thereby increasing recommendation accuracy.

[0648] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0649] Step 1:

[0650] The user enters registration information.

[0651] Specific behavior:

[0652] The user enters their name, email address, and password into the system's registration form.

[0653] Input: Name, Email Address, Password

[0654] Output: Registration information is sent to the device

[0655] Step 2:

[0656] The terminal sends the input information to the server.

[0657] Specific behavior:

[0658] When the user presses the "Register" button, the device sends the user's name, email address, and password to the server.

[0659] Input: Registration information (name, email address, password)

[0660] Output: Registration information passed to the server

[0661] Step 3:

[0662] The server stores it in a database.

[0663] Specific behavior:

[0664] The server stores the received registration information in a database.

[0665] Input: Registration information

[0666] Output: Registration information is saved in the database

[0667] Step 4:

[0668] The server sends a confirmation email.

[0669] Specific behavior:

[0670] The server will send a confirmation email to the registered email address.

[0671] Input: User's email address

[0672] Output: A confirmation email is sent to the user.

[0673] Step 5:

[0674] The user checks the confirmation email and logs in.

[0675] Specific behavior:

[0676] The user clicks on the link in the confirmation email they received, goes to the login page, and enters their email address and password.

[0677] Input: Confirmation email, email address, password

[0678] Output: Login information is sent to the terminal

[0679] Step 6:

[0680] The device sends the login information to the server.

[0681] Specific behavior:

[0682] When a user enters their email address and password into the login form and presses the "Login" button, the device sends the information to the server.

[0683] Input: Login information (email address, password)

[0684] Output: Login information passed to the server

[0685] Step 7:

[0686] The server performs the authentication.

[0687] Specific behavior:

[0688] The server checks the submitted information against a database to authenticate the user, and if authentication is successful, the user is logged into the system.

[0689] Input: Login information, registration information in the database

[0690] Output: Authentication status of the user

[0691] Step 8:

[0692] The user responds to the survey.

[0693] Specific behavior:

[0694] Users answer a questionnaire about their interests and personality on a profile setting page within the system.

[0695] Input: Survey questions, user answers

[0696] Output: Response data is sent to the device

[0697] Step 9:

[0698] The terminal sends the survey results to the server.

[0699] Specific behavior:

[0700] When the user presses the "send" button, the terminal sends the answer data to the server.

[0701] Input: Response data

[0702] Output: Response data is sent to the server

[0703] Step 10:

[0704] The server makes recommendations using a hobby recommendation engine.

[0705] Specific behavior:

[0706] The server runs a hobby recommendation engine (e.g., a recommendation algorithm built in Python) based on the collected data and selects appropriate hobbies from the database.

[0707] Input: Answer data, hobby information in the database

[0708] Output: A list of recommended hobbies

[0709] Step 11:

[0710] The server sends the recommendation list to the terminal.

[0711] Specific behavior:

[0712] The server transmits the generated hobby recommendation list to the terminal.

[0713] Input: Recommended Hobbies List

[0714] Output: The recommendation list is passed to the device.

[0715] Step 12:

[0716] The terminal displays the list to the user.

[0717] Specific behavior:

[0718] The terminal displays the received recommendation list to the user.

[0719] Input: Recommendation list

[0720] Output: User can view the hobby list

[0721] Step 13:

[0722] The user selects a hobby that interests them.

[0723] Specific behavior:

[0724] The user selects a hobby that interests them from the displayed hobby list.

[0725] Input: Interest list, user selection

[0726] Output: The selected data is sent to the terminal.

[0727] Step 14:

[0728] The terminal transmits the selection information to the server.

[0729] Specific behavior:

[0730] When the user presses the "select" button, the terminal transmits the selected hobby information to the server.

[0731] Input: Selection data

[0732] Output: Selection data is passed to the server

[0733] Step 15:

[0734] The server retrieves the community information.

[0735] Specific behavior:

[0736] The server searches a database for community information (e.g., online forums and physical clubs) related to the selected hobby.

[0737] Input: hobby selection data, community information in the database

[0738] Output: Community information list

[0739] Step 16:

[0740] The server transmits the community information to the terminal.

[0741] Specific behavior:

[0742] The server transmits the community information of the search results to the terminal.

[0743] Input: Community Information List

[0744] Output: Community information is passed to the terminal

[0745] Step 17:

[0746] The terminal displays the community information to the user.

[0747] Specific behavior:

[0748] The terminal displays the received community information to the user.

[0749] Input: Community Information

[0750] Output: User can view community information

[0751] Step 18:

[0752] The user provides feedback.

[0753] Specific behavior:

[0754] Users enter feedback about the recommended hobbies and communities in a rating form.

[0755] Input: Evaluation form, user feedback

[0756] Output: Feedback data is sent to the device

[0757] Step 19:

[0758] The terminal sends feedback information to the server.

[0759] Specific behavior:

[0760] When the user presses the "send" button, the terminal sends the feedback information to the server.

[0761] Input: Feedback data

[0762] Output: Feedback data is passed to the server

[0763] Step 20:

[0764] The server stores the feedback in a database.

[0765] Specific behavior:

[0766] The server stores the received feedback in a database.

[0767] Input: Feedback data

[0768] Output: Feedback data is saved in a database

[0769] Step 21:

[0770] The server performs the analysis.

[0771] Specific behavior:

[0772] The server analyzes the stored feedback and extracts data about user interests and satisfaction.

[0773] Input: Feedback data

[0774] Output: Analysis results

[0775] Step 22:

[0776] The server improves the algorithm.

[0777] Specific behavior:

[0778] The server adjusts the hobby recommendation engine's algorithm based on the analysis results, improving the accuracy of recommendations from next time onwards.

[0779] Input: Analysis results

[0780] Output: An improved recommendation algorithm

[0781] (Application example 1)

[0782] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0783] Conventional methods have not only failed to provide users searching for hobbies that match their interests, but also to provide them with information on products and communities related to those hobbies. Furthermore, the accuracy of the information provided is low, making it difficult to increase user satisfaction.

[0784] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0785] In this invention, the server includes means for accepting user registration information, means for storing the accepted user registration information in a database, means for recommending appropriate hobbies based on the user's interests and personality, means for searching for community information related to the recommended hobbies, means for collecting user feedback and improving the recommendation algorithm, means for recommending related products based on the user's interests, and means for providing users with information on related online forums and nearby clubs, thereby enabling users to discover new hobbies based on their interests and simultaneously obtain related product and community information.

[0786] "User registration information" refers to basic information such as name, email address, and password provided by the user when registering with the system.

[0787] "Database" means a digital information management system for storing data related to user registration information, feedback, and hobby recommendations.

[0788] A "hobby recommendation engine" is a software component that calculates and recommends appropriate hobbies based on a user's interests and personality.

[0789] "Community information" is information such as online forums and local clubs related to hobbies that may interest the user.

[0790] "Feedback" refers to information such as evaluations and opinions provided by users regarding recommended hobby or community information.

[0791] A "recommendation algorithm" is a computational method for analyzing user interests and feedback and reflecting them in the next hobby recommendation.

[0792] "Products" are products or services related to a user's interests or hobbies.

[0793] An "online forum" is a place on the Internet where people share information and communicate about a particular hobby or interest.

[0794] A "club" is a physical place or association where people with common hobbies or interests come together.

[0795] The system for implementing this invention allows users to discover new hobbies and provides them with information on products and communities related to those hobbies. This system is mainly composed of three elements: a server, a terminal, and a user.

[0796] System hardware and software configuration

[0797] Hardware

[0798] Server: Runs on the cloud and is responsible for data processing and storage.

[0799] Device: A device that is directly controlled by the user, such as a smartphone or smart glasses.

[0800] software

[0801] Firebase Auth: Provides user authentication and login functionality.

[0802] Firebase Firestore: A database for storing and retrieving data in real time.

[0803] Google Cloud AI: An AI engine that runs recommendation algorithms and feedback analysis.

[0804] React Native: A framework for building the front end of smartphone apps.

[0805] Processing Details

[0806] User Registration and Login

[0807] Users register their name, email address, and password using a terminal. This information is sent to the server using Firebase Auth for authentication. When the user logs in, the authentication information is sent again to the server, and if authentication is successful, the user can access Firebase Firestore.

[0808] Hobby recommendations

[0809] Users fill out a profile setting page and answer a questionnaire about their interests and personality. This data is sent from the device to a server, where it is processed by a Google Cloud AI recommendation engine to select appropriate hobbies.

[0810] Recommending related products and community information

[0811] Based on the recommended hobbies, the server searches the product database for relevant product information, and also searches the community information stored in Firebase Firestore to provide the user with information on online forums and nearby clubs.

[0812] Gathering feedback and improving the algorithm

[0813] Users provide feedback on the recommended hobbies and community information, which is stored in Firebase Firestore and analyzed by Google Cloud AI to improve the recommendation algorithm.

[0814] Specific examples

[0815] For example, if a user responds that they are interested in "outdoors," the server may recommend outdoor-related products (tents, backpacks, etc.) and may also provide information about online forums related to outdoor activities and nearby hiking clubs.

[0816] Prompt Sentence Examples

[0817] 1. Hobby recommendation prompt:

[0818] Based on your user interest survey response data, please provide the following information:

[0819] Recommended Hobbies List

[0820] A list of product categories related to each hobby

[0821] A brief explanation of the reason for the recommendation

[0822] 2. Community recommendation prompt:

[0823] Based on your selected interests, please provide the following information:

[0824] Online forum URLs related to each hobby

[0825] Nearby hobby club information related to each hobby (with location information)

[0826] This allows users to discover new hobbies based on their own interests and simultaneously obtain information on products and communities related to those hobbies.

[0827] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0828] Step 1:

[0829] A user accesses the system using a terminal and enters their name, email address, and password. The entered registration information is sent from the terminal to the server via Firebase Auth. The server saves this information in a database and sends a confirmation email to the user. The user logs in using the confirmation email they received. The input information is an email address and password, and the output is a flag indicating successful login.

[0830] Step 2:

[0831] After the user logs in, the device will be taken to a profile setting page. The user will then answer a questionnaire about their interests and personality. The survey response data will be sent from the device to the server and stored in Firebase Firestore. The input will be the survey response data, and the output will be the data stored in the database.

[0832] Step 3:

[0833] The server sends a response request to Google Cloud AI based on the survey response data stored in Firebase Firestore, and calculates the hobbies suitable for the user. The calculated hobbies list is returned to the server, which then sends it to the device, which displays it to the user. The input is the survey response data, and the output is the recommended hobbies list.

[0834] Step 4:

[0835] When a user selects a hobby that interests them from the recommended hobbies, the device sends this information to the server. The server searches for related product information from the product database and sends a related product list to the device. It also searches for related online forums and nearby club information from Firebase Firestore and sends this information to the device. The input is the selected hobby information, and the output is a related product list and community information.

[0836] Step 5:

[0837] Users provide feedback on the displayed related product list and community information. The feedback information is sent from the device to the server and stored in Firebase Firestore. The saved feedback information is used for analysis by Google Cloud AI to improve the recommendation algorithm. The input is the feedback information, and the output is an improved recommendation algorithm and improved recommendation accuracy for the next time.

[0838] Step 6:

[0839] The server periodically analyzes the accumulated feedback information and updates the generative AI model via Google Cloud AI, which improves the accuracy of the next hobby and product recommendations and increases user satisfaction. The input is the accumulated feedback information, and the output is the updated generative AI model.

[0840] By following the steps above, users can efficiently discover new hobbies and appropriately obtain product and community information related to those hobbies.

[0841] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0842] This invention relates to a "hobby discovery support system" that helps users who do not have any hobbies to discover new interests and hobbies. In particular, it adds a function to recognize the user's emotional state and recommend appropriate hobbies and related communities based on that emotion. The system also includes a means to collect user emotional feedback and improve the emotion engine.

[0843] User Registration / Login

[0844] Examples:

[0845] A user accesses the system and enters their name, email address, and password into the registration form.

[0846] The terminal transmits the entered user registration information to the server.

[0847] The server stores the received registration information in a database.

[0848] The server will send a confirmation email to the user confirming the registration.

[0849] User Login

[0850] Examples:

[0851] The user enters their email address and password into the login form.

[0852] The terminal transmits the entered login information to the server.

[0853] The server checks the user information in the database and performs authentication.

[0854] If the authentication is successful, the server creates a session and sends a session ID to the terminal.

[0855] User information collection

[0856] Examples:

[0857] Users visit a profile setup page and answer questions about their interests and personality.

[0858] The terminal transmits the collected user information to the server.

[0859] emotion recognition

[0860] Examples:

[0861] Users access the system through an emotion-recognition camera.

[0862] The terminal transmits the user's facial image captured by the camera to the server.

[0863] The server uses an emotion engine to recognize the user's emotions (happiness, sadness, surprise, etc.) from the image.

[0864] The recognized emotion information is stored on the server.

[0865] Hobby recommendations

[0866] Examples:

[0867] The server selects appropriate hobbies using a hobby recommendation engine based on the recognized emotion information and existing profile information.

[0868] The server transmits a list of recommended hobbies to the terminal.

[0869] The terminal displays the recommended hobbies to the user.

[0870] Community Search

[0871] Examples:

[0872] Users select hobbies that interest them within the system.

[0873] The terminal transmits the selected hobby information to the server.

[0874] The server searches a database for community information related to the hobby (online forums, local clubs, etc.).

[0875] Community Recommendations

[0876] Examples:

[0877] The server returns the retrieved community information to the terminal.

[0878] The terminal displays the recommended community information to the user.

[0879] Feedback collection

[0880] Examples:

[0881] Users provide feedback on recommended hobbies and communities.

[0882] The feedback also includes a rating based on the user's emotional state.

[0883] The terminal transmits the feedback information to the server.

[0884] The server stores the feedback information in a database.

[0885] Algorithm Improvement

[0886] Examples:

[0887] The server analyzes the collected feedback.

[0888] The server improves the algorithms of the hobby recommendation engine and the emotion engine based on the analysis results.

[0889] Through this series of steps, the system can effectively recommend hobbies and communities that are suitable for the user and provide more accurate recommendations. By taking the user's emotional state into account, the quality of the recommended hobbies and communities can be further improved, allowing the user to discover new hobbies in a more satisfying way.

[0890] The processing flow will be explained below.

[0891] Step 1: User Registration

[0892] A user accesses the system and enters their name, email address, and password into the registration form.

[0893] The terminal transmits the entered user registration information to the server.

[0894] The server stores the received registration information in a database.

[0895] The server will send a confirmation email to the user confirming the registration.

[0896] Step 2: User Login

[0897] The user enters their email address and password into the login form.

[0898] The terminal transmits the entered login information to the server.

[0899] The server checks the user information in the database and performs authentication.

[0900] If the authentication is successful, the server creates a session and sends a session ID to the terminal.

[0901] Step 3: Collect user information

[0902] Users visit a profile setup page and answer questions about their interests and personality.

[0903] The terminal transmits the collected user information to the server.

[0904] Step 4: Emotion Recognition

[0905] Users access the system through an emotion-recognition camera.

[0906] The terminal transmits the user's facial image captured by the camera to the server.

[0907] The server uses an emotion engine to recognize the user's emotions (happiness, sadness, surprise, etc.) from the image.

[0908] The recognized emotion information is stored on the server.

[0909] Step 5: Hobby recommendation

[0910] The server selects appropriate hobbies using a hobby recommendation engine based on the recognized emotion information and existing profile information.

[0911] The server transmits a list of recommended hobbies to the terminal.

[0912] The terminal displays the recommended hobbies to the user.

[0913] Step 6: Community Search

[0914] Users select hobbies that interest them within the system.

[0915] The terminal transmits the selected hobby information to the server.

[0916] The server searches a database for community information related to the hobby (online forums, local clubs, etc.).

[0917] Step 7: Community Nomination

[0918] The server returns the retrieved community information to the terminal.

[0919] The terminal displays the recommended community information to the user.

[0920] Step 8: Gather feedback

[0921] Users provide feedback on recommended hobbies and communities, including ratings based on the user's emotional state.

[0922] The terminal transmits the feedback information to the server.

[0923] The server stores the feedback information in a database.

[0924] Step 9: Improve the algorithm

[0925] The server analyzes the collected feedback.

[0926] The server improves the algorithms of the hobby recommendation engine and the emotion engine based on the analysis results.

[0927] This detailed processing flow allows users to receive more accurate interest and community recommendations based on their emotional state, and allows us to leverage feedback to continuously improve the algorithm, thereby increasing system performance and user satisfaction.

[0928] Example 2

[0929] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0930] In today's world, it is difficult for users who do not have any hobbies to discover new hobbies or interests that suit them. Furthermore, recommended hobbies and communities may not necessarily be suitable for each user unless the emotional state of each individual user is taken into consideration. Therefore, there is a need for a method to collect users' emotional feedback and use it to improve the system's recommendation accuracy.

[0931] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for accepting user registration information, means for storing the accepted user registration information in a database, means for recognizing the emotional state of the user and recommending appropriate hobbies based on the emotional state and the user's interests and personality, means for searching the database for community information related to the recommended hobbies, and means for collecting feedback from the user and improving the recommendation algorithm and emotion recognition engine based on the feedback. This enables highly accurate recommendation of hobbies and communities based on the user's emotional state.

[0932] "User registration information" refers to personal information such as name, email address, and password that a user enters when accessing the system for the first time.

[0933] A "database" is a data structure that the system uses to store and manage data such as user information, emotional state, and feedback.

[0934] "Emotional state" is information indicating a psychological state such as joy, sadness, surprise, etc., recognized from the user's facial expression.

[0935] "Hobbies" refer to activities or areas in which a user has personal interests or concerns.

[0936] "Recommending" refers to the act of the system presenting hobbies and communities that it deems most suitable based on the user's information.

[0937] "Community information" refers to information such as online forums and physical clubs related to a particular hobby.

[0938] "Feedback" is information such as the user's evaluation and opinions of the recommended hobby or community.

[0939] An "algorithm" is a computational procedure that allows the system to analyze user information and emotional state and recommend optimal hobbies and communities.

[0940] An "emotion recognition engine" is a piece of software that analyzes a user's facial image and other data to recognize their emotional state.

[0941] This invention relates to a "hobby discovery support system" that allows users without hobbies to discover new hobbies and interests that suit them and find communities based on those hobbies. This system has the function of recognizing the user's emotional state and recommending appropriate hobbies and related communities based on that emotion. It can also collect user emotional feedback and use that feedback to improve the system's recommendation algorithm and emotion recognition engine.

[0942] Hardware and Software Configuration

[0943] The main components of the system include:

[0944] Server: Stores and manages user information, emotion information, and feedback information in a database. The server runs an emotion recognition engine and a hobby recommendation engine to provide appropriate information to users.

[0945] Terminal: A device that allows users to input and obtain information. Examples include PCs, smartphones, and tablets.

[0946] Database: A data structure for storing user information, emotion data, hobby information, community information, and feedback information.

[0947] Emotion recognition engine: Software that analyzes a user's facial image to recognize their emotional state. Examples of engines that can be used include Microsoft Azure Face API and Google Cloud Vision.

[0948] Hobby recommendation engine: Software that uses a generative AI model to generate optimal hobbies based on a user's emotional state and profile information.

[0949] Details of system processing

[0950] User Registration / Login

[0951] First, a user accesses the system and enters their name, email address, and password. The device sends this to the server, which stores it in a database. Once registration is complete, a confirmation email is sent. When the user logs in, they enter their email address and password, and the device again sends this to the server. The server compares this with the information in the database, and if authentication is successful, it generates a session ID and sends it to the device.

[0952] User information collection

[0953] Users answer questions about their interests and personality on a profile setup page, and the device sends the collected information to a server, which stores it in a database.

[0954] emotion recognition

[0955] The user provides a facial image through the emotion recognition camera, and the device sends the facial image to the server, which then uses an emotion recognition engine to analyze the user's emotional state. The analysis results are then stored in a database.

[0956] Hobby recommendations

[0957] The server runs a hobby recommendation engine using the latest emotion information and user profile information, and sends the generated hobby list to the terminal and displays it to the user.

[0958] Community Search

[0959] The user selects the hobbies they are interested in from the displayed hobbies, and the terminal sends the selection information to the server, which then searches the database for related community information.

[0960] Community Recommendations

[0961] The retrieved community information is sent to the terminal and displayed to the user.

[0962] Feedback collection

[0963] Users provide feedback on their hobbies and communities, and their devices send it to the server, which stores the feedback information in a database.

[0964] Algorithm Improvement

[0965] The server analyzes the collected feedback and dynamically adjusts the parameters of the recommendation algorithm and emotion recognition engine.

[0966] Examples of concrete examples and prompts

[0967] As a specific example of operation, if a user expresses an interest in "painting," the server will recommend hobbies related to "watercolor painting" and "digital art." If the user is interested in "watercolor painting," the server will recommend community information such as "local watercolor painting clubs" and "online watercolor painting forums."

[0968] Here are some examples of prompts:

[0969] "What new hobbies should we recommend to users when they feel joy?"

[0970] "Where is the best community for users interested in watercolor painting?"

[0971] As described above, the "hobby discovery support system" of the present invention realizes highly accurate recommendation of hobbies and communities that take into account the emotional state of the user.

[0972] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0973] Step 1:

[0974] Enter user registration information

[0975] A user fills in the system's registration form with their name, email address, and password, which serves as input data for the system, and is used to identify the user.

[0976] Step 2:

[0977] Sending user registration information

[0978] The device sends the entered user information to the server in the form of an HTTP POST request. The data is encrypted, thereby protecting the user information.

[0979] Step 3:

[0980] Saving user registration information

[0981] The server validates the received user information and checks for invalid data. After validation is complete, the server stores the information in the "User Information" table in the database. As an output, the server generates a confirmation of successful registration and sends it to the mail server.

[0982] Step 4:

[0983] Enter your user login information

[0984] A user enters an email address and password into a login form. This information is the input data for authentication.

[0985] Step 5:

[0986] Sending user login information

[0987] The device sends the entered login information to the server, where it is also encrypted to ensure data security.

[0988] Step 6:

[0989] User authentication process

[0990] The server searches for the corresponding user information in the "User Information" table in the database and compares it with the entered password. If authentication is successful, the server creates a session, generates a session ID and sends it to the terminal. As an output, the terminal displays the main page to the user.

[0991] Step 7:

[0992] User information collection

[0993] Users access a profile setup page and answer questions about their interests and personality, which are then used as input data for the system's profile data.

[0994] Step 8:

[0995] Sending and storing user information

[0996] The terminal sends the collected user information to the server, which stores it in the "User Profile" table in the database. As an output, the server notifies the user that the profile has been set up.

[0997] Step 9:

[0998] Emotion Recognition Camera Setup

[0999] The user activates the emotion recognition camera and captures facial images through the device, which serve as input data for emotion recognition.

[1000] Step 10:

[1001] Facial image transmission and emotion analysis

[1002] The device sends the captured face image to the server, which then calls an emotion recognition engine (e.g., Microsoft Azure Face API) to analyze the user's emotion from the image. As an output, analyzed emotion information is generated and stored in the "emotion data" table in the database.

[1003] Step 11:

[1004] Running a hobby recommendation engine

[1005] The server retrieves the latest emotion information and user profile information and runs an interest recommendation engine. This engine generates appropriate hobbies using a generative AI model. It uses emotion information and profile information as input and generates a list of hobbies as output.

[1006] Step 12:

[1007] Submit and view recommended hobby lists

[1008] The server sends the recommended hobby list to the terminal, which displays it to the user and provides an interface to attract the user's interest.

[1009] Step 13:

[1010] Start a Community Search

[1011] The user selects a hobby from the displayed hobby list that they are interested in. The terminal then sends information about the selected hobby to the server.

[1012] Step 14:

[1013] Search for related community information

[1014] The server retrieves community information related to the selected hobby from a database, such as online forums and physical club data.

[1015] Step 15:

[1016] Submitting and Viewing Community Information

[1017] The server sends the retrieved community information to the terminal, which displays it to the user, allowing the user to access communities that interest them.

[1018] Step 16:

[1019] Feedback Input

[1020] Users input feedback on the recommended hobbies and communities, which serves as input data for improving the system.

[1021] Step 17:

[1022] Send and save feedback

[1023] The terminal sends the feedback information to the server, which stores it in the "feedback data" table of the database. As an output, the server notifies the user of the confirmation of receipt of the feedback.

[1024] Step 18:

[1025] Algorithm analysis and updates

[1026] The server analyzes the collected feedback and dynamically adjusts the parameters of the recommendation algorithm and emotion recognition engine based on the results. The output is an improved algorithm, which improves the accuracy of recommendations from the next time onwards.

[1027] (Application example 2)

[1028] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1029] Conventional recommendation systems recommend hobbies and products based on a user's static interests and personality information, but they lack the ability to provide real-time recommendations that take into account the user's emotional state. This can result in a failure to meet users' momentary needs and a decrease in satisfaction. Furthermore, there is a lack of concrete measures to improve the shopping experience in physical stores.

[1030] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for accepting user registration information, means for storing the accepted user registration information in a database, means for recommending appropriate hobbies based on the user's interests and personality, means for recognizing the user's emotional state using an emotion recognition camera, means for recommending products based on the recognized emotional information, means for displaying the recommended products on a visual device, and means for collecting feedback from users and improving the recommendation algorithm. This enables real-time product recommendations based on the user's emotional state, thereby improving the quality of shopping experiences in physical stores.

[1031] "User registration information" refers to personal information such as the user's name, email address, and password.

[1032] "Database" refers to a computer system or storage for systematically storing and retrieving information.

[1033] "Appropriate hobbies" refer to activities and interests that are recommended based on a user's interests and personality.

[1034] An "emotion recognition camera" refers to an image processing device that captures a user's facial expressions and analyzes their emotional state.

[1035] "Emotion information" refers to data collected by an emotion-recognition camera about a user's emotional state, such as happiness, sadness, or surprise.

[1036] "Means for recommending products" refers to the function of selecting and presenting appropriate products based on the user's emotional information.

[1037] "Visual device" refers to a device that allows a user to receive information visually, such as smart glasses or a head-mounted display.

[1038] "Feedback" refers to the evaluations and impressions that users give about recommended hobbies or products.

[1039] A "recommendation algorithm" refers to a computational method for selecting appropriate hobbies and products using data such as a user's interests, personality, and emotional state.

[1040] "Brick and mortar store" refers to a retail store that is a physical location where users can visit in person to purchase goods or services.

[1041]

[1042] MODE FOR CARRYING OUT THE INVENTION

[1043] This invention is an emotion recognition-based hobby and product recommendation system that improves the shopping experience in brick-and-mortar stores based on the user's emotional state. The system accepts user registration information, stores it in a database, and recommends hobbies and products based on the user's static interests and personality information, as well as real-time emotional information.

[1044] The server includes the following means:

[1045] Method for accepting user registration information: The user enters personal information into the registration form and sends it from the terminal to the server, whereupon the user's basic information is stored in a database.

[1046] A means for storing the received user registration information in a database: The server systematically stores and manages the received information in a database.

[1047] A means of recommending appropriate hobbies based on the user's interests and personality: The server uses a hobby recommendation engine to select and recommend appropriate hobbies based on the data on interests and personality provided by the user.

[1048] A means of recognizing a user's emotional state using an emotion recognition camera: A camera installed in the device (visual device such as smart glasses) captures the user's face in real time and sends the image to an emotion recognition engine to analyze the emotional information.

[1049] Means for recommending products based on recognized emotional information: Based on the recognized emotional information, a recommendation engine is used to select appropriate products and present them to the user.

[1050] Means for displaying recommended products on a visual device: Product information sent from the server is overlaid on the display of the visual device.

[1051] A means of collecting user feedback and improving the recommendation algorithm: User feedback is sent from the device to the server and used to dynamically adjust the recommendation algorithm.

[1052] Hardware and software used

[1053] Hardware: smart glasses, cameras, servers, visual devices (e.g. Google Glass, Vuzix Blade)

[1054] Software: Emotion recognition module (e.g., OpenCV, dlib, Face++ API), hobby recommendation engine, product recommendation engine, database management system

[1055] Data flow and specific examples

[1056] A user wears smart glasses while shopping in a physical store. The glasses' built-in camera captures the user's facial image and analyzes it using an emotion recognition engine. For example, if the system detects that the user looks slightly tired, it generates a list of products with a refreshing effect and overlays them on the smart glasses' display. This allows the user to visually check recommended products while walking around the store.

[1057] Examples of prompt statements

[1058] "Please recommend products suitable for users who look tired. For example, aroma products or massage machines like the ones below."

[1059] In this way, by providing a specific form for implementing the invention, it becomes possible to recommend products in real time according to the user's emotional state, thereby improving the quality of the shopping experience in physical stores.

[1060] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1061] Step 1:

[1062] The server accepts user registration information. The data to be entered includes name, email address, and password. The user enters this data into the registration form and sends it from the terminal to the server. The server receives this data and stores it systematically in a database.

[1063] Step 2:

[1064] The device collects data to recommend appropriate hobbies based on the user's interests and personality. The user accesses a profile setting page and answers questions about their interests and personality. The collected data is sent from the device to a server, which stores it in a database.

[1065] Step 3:

[1066] The device recognizes the user's emotional state using an emotion recognition camera installed in the smart glasses. The camera captures the user's facial image in real time and sends the image to a server. The server then uses an emotion recognition engine to analyze the user's emotional information from the image and stores the results in a database.

[1067] Step 4:

[1068] The server recommends products based on the recognized emotion information. The user's emotion information and past interest data are used as input. The server's recommendation engine uses this data to create a list of appropriate products and sends the information to the device.

[1069] Step 5:

[1070] The terminal displays the recommended products on a visual device. The recommended products are overlaid on the display of the visual device (e.g., smart glasses). The user can view the recommended products through the visual device while moving around the physical store.

[1071] Step 6:

[1072] Users provide feedback on the recommended products and the system's recommendation accuracy. The feedback includes information about interests and satisfaction, and is sent from the device to the server, which stores it in a database.

[1073] Step 7:

[1074] The server improves the recommendation algorithm based on the collected feedback. It analyzes the feedback data and uses the results to dynamically adjust the recommendation algorithm, thereby improving the accuracy of future recommendations.

[1075] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1076] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1077] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1078] [Third embodiment]

[1079] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1080] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1081] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1082] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1083] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1084] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1085] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1086] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1087] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1088] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1089] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1090] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1091] This invention relates to a "hobby discovery support system" that helps users who do not have any hobbies to find new interests or hobbies. This system recommends hobbies and related communities that are suitable for each user based on the user's registered information, and further improves the recommendation algorithm based on user feedback.

[1092] User Registration / Login

[1093] Examples:

[1094] A user accesses the system and enters their name, email address, and password into the registration form.

[1095] The terminal transmits the entered registration information to the server, which stores this information in a database.

[1096] After registration is complete, the server sends a confirmation email to the user, who then checks the email and performs the login procedure.

[1097] Enter your email address and password into the login form, and the device will send the information to the server, which will then authenticate you.

[1098] Hobby recommendations

[1099] Examples:

[1100] Users answer a questionnaire about their interests and personality on a profile setting page within the system.

[1101] The device sends this data to the server, which then uses a hobby recommendation engine to select appropriate hobbies from a database.

[1102] The recommended hobby list is sent back from the server to the terminal, which displays it to the user.

[1103] Community information search and recommendation

[1104] Examples:

[1105] Users select hobbies that interest them within the system.

[1106] The terminal transmits the selection information to the server, and the server searches a database for community information related to the hobby.

[1107] The server returns relevant online forum and nearby club information to the terminal, which displays this to the user.

[1108] Gathering feedback and improving our algorithms

[1109] Examples:

[1110] Users provide feedback on hobbies and communities recommended by the system.

[1111] The terminal sends the feedback information to the server, which stores it in a database and analyzes it.

[1112] Based on the analysis results, the server improves the hobby recommendation engine's algorithm and improves the accuracy of the next recommendation.

[1113] System Operation

[1114] The specific operation of this system is as follows: Once a user registers and logs in, the system recommends hobbies based on the user's interests and personality information. In addition, by providing community information related to those hobbies, the system makes it easier for users to find places where they can actually experience those hobbies. Based on user feedback, the system improves its recommendation algorithm, enabling it to provide more accurate recommendations.

[1115] In this way, the present invention provides a system that helps users efficiently find new hobbies and deepen their interests, thereby increasing the sense of fulfillment in their lives.

[1116] The processing flow will be explained below.

[1117] Step 1: User Registration

[1118] A user accesses the system and enters their name, email address, and password into the registration form.

[1119] The terminal transmits the entered user registration information to the server.

[1120] The server stores the received registration information in a database.

[1121] The server will send a confirmation email to the user confirming the registration.

[1122] Step 2: User Login

[1123] The user enters their email address and password into the login form.

[1124] The terminal transmits the entered login information to the server.

[1125] The server checks the user information in the database and performs authentication.

[1126] If the authentication is successful, the server creates a session and sends a session ID to the terminal.

[1127] Step 3: Collect user information

[1128] Users visit a profile setup page and answer questions about their interests and personality.

[1129] The terminal transmits the collected user information to the server.

[1130] Step 4: Hobby recommendation

[1131] The server inputs the collected user profile information into the hobby recommendation engine.

[1132] The hobby recommendation engine uses an algorithm to select suitable hobbies for the user from a database.

[1133] The server transmits a list of recommended hobbies to the terminal.

[1134] The terminal displays the recommended hobbies to the user.

[1135] Step 5: Community Search

[1136] Users select hobbies that interest them within the system.

[1137] The terminal transmits the selected hobby information to the server.

[1138] The server searches a database for community information related to the hobby (online forums, local clubs, etc.).

[1139] Step 6: Community Nomination

[1140] The server returns the retrieved community information to the terminal.

[1141] The terminal displays the recommended community information to the user.

[1142] Step 7: Gather feedback

[1143] Users provide feedback on recommended hobbies and communities.

[1144] The terminal transmits the feedback information to the server.

[1145] The server stores the feedback information in a database.

[1146] Step 8: Improve the algorithm

[1147] The server analyzes the collected feedback.

[1148] The server improves the algorithm of the hobby recommendation engine based on the analysis results.

[1149] Through this series of steps, the system can effectively recommend hobbies and communities that are suitable for the user and provide more accurate recommendations.

[1150] Example 1

[1151] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1152] In recent years, many people have no hobbies or are looking for new interests. However, the amount of information available to find suitable hobbies and interests is enormous, making it difficult to efficiently find hobbies that meet individual needs. It is also difficult to find places and communities where people can actually experience their hobbies. Furthermore, there is a need for a method to effectively utilize provided feedback to improve recommendation algorithms and increase user satisfaction.

[1153] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1154] In this invention, the server includes means for accepting user registration information, means for storing the accepted user registration information in a database, means for authenticating the user using user authentication information, means for recommending appropriate hobbies based on the user's interests and personality, means for searching for community information related to the recommended hobbies, and means for collecting feedback from users and improving the recommendation algorithm. This makes it easier for users to efficiently find new hobbies and places where they can experience them, and also makes it possible to dynamically adjust the recommendation algorithm based on the provided feedback, thereby increasing user satisfaction.

[1155] "Means for accepting user registration information" refers to the interface through which a user accesses the system, inputs personal information such as name, email address, and password, and provides that information to the system.

[1156] "Means for saving the received user registration information in a database" refers to a function for safely and efficiently saving the input user registration information in a database.

[1157] "Means of authenticating a user using user authentication information" refers to the process of verifying whether a user is a legitimate registered user based on the email address and password entered into the login form.

[1158] "Means for recommending appropriate hobbies based on the user's interests and personality" refers to the algorithm and its operation that analyzes the questionnaire data answered by the user and suggests the most suitable hobbies.

[1159] "Means for searching for community information related to the recommended hobby" refers to a function that searches a database for community information such as online forums and physical clubs related to the suggested hobby and provides it.

[1160] "Means for collecting user feedback and improving the recommendation algorithm" refers to the process of storing user-provided feedback in a database and analyzing that data to improve the accuracy of the recommendation algorithm.

[1161] The present invention relates to a "hobby discovery support system" that supports users who do not have any hobbies in finding new interests or hobbies. Specific embodiments for carrying out the present invention will be described below.

[1162] User Registration / Login

[1163] This system begins when the user enters registration information. The user accesses the system and enters their name, email address, and password. When the user presses the "Register" button, the terminal sends this registration information to the server. The server saves this in a database (e.g., MySQL database). The server then sends a confirmation email to the user's email address, and the user clicks on the link in the email to complete the login procedure. The user enters their email address and password in the login form, and the terminal sends the information to the server. The server compares this with the database and authenticates the user.

[1164] Hobby recommendations

[1165] After logging in, the user answers a questionnaire about their interests and personality on the profile setting page within the system. When the user presses the "Submit" button, the device sends this data to the server. The server then runs an interest recommendation engine (e.g., a recommendation algorithm built in Python) based on the collected data and selects appropriate interests from the database. The server then sends the recommended interest list to the device, which then displays it to the user.

[1166] Community information search and recommendation

[1167] The user selects a hobby that interests them from the displayed hobby list. When the user presses the "Select" button, the device sends the selection information to the server. The server searches its database for community information (e.g., online forums or physical clubs) related to the selected hobby. The search results are sent back to the device, which displays them to the user.

[1168] Gathering feedback and improving our algorithms

[1169] The user provides feedback on the hobbies and communities recommended by the system. When the user fills out the feedback form and presses the "Submit" button, the device sends the feedback information to the server, which stores it in a database and analyzes it. Based on the analysis results, the server improves the algorithm of the hobby recommendation engine, thereby improving the accuracy of the next recommendation.

[1170] Specific examples

[1171] User "Yamada Taro" accesses the system and enters his name "Yamada Taro," his email address "taro@example.com," and his password "password123." The server stores this information in a database and sends a confirmation email. The user receives the confirmation email and clicks the link to log in. After logging in, the user answers "blue" to the question "What is your favorite color?", and the device sends this to the server. The server includes hobbies related to blue, such as "fishing" and "astronomy," in a recommendation list and sends it to the device. When the user selects "fishing," the server searches for information such as "fishing forums" and "nearby fishing clubs" and sends it to the device. The user evaluates the fishing recommendation as "appropriate," and the device sends the feedback information to the server, which stores it in a database, analyzes it, and improves the algorithm.

[1172] Prompt Sentence Examples

[1173] "Please recommend a suitable hobby for a woman in her 20s who is interested in the outdoors."

[1174] "Find recommended online communities for middle school students interested in coding."

[1175] In this way, the present invention provides a system that helps users efficiently discover new hobbies and deepen their interests. By recommending hobbies based on the user's interests and personality and providing related community information, the system increases the user's opportunities to actually experience the hobbies, and improves the algorithm based on feedback, thereby increasing recommendation accuracy.

[1176] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1177] Step 1:

[1178] The user enters registration information.

[1179] Specific behavior:

[1180] The user enters their name, email address, and password into the system's registration form.

[1181] Input: Name, Email Address, Password

[1182] Output: Registration information is sent to the device

[1183] Step 2:

[1184] The terminal sends the input information to the server.

[1185] Specific behavior:

[1186] When the user presses the "Register" button, the device sends the user's name, email address, and password to the server.

[1187] Input: Registration information (name, email address, password)

[1188] Output: Registration information passed to the server

[1189] Step 3:

[1190] The server stores it in a database.

[1191] Specific behavior:

[1192] The server stores the received registration information in a database.

[1193] Input: Registration information

[1194] Output: Registration information is saved in the database

[1195] Step 4:

[1196] The server sends a confirmation email.

[1197] Specific behavior:

[1198] The server will send a confirmation email to the registered email address.

[1199] Input: User's email address

[1200] Output: A confirmation email is sent to the user.

[1201] Step 5:

[1202] The user checks the confirmation email and logs in.

[1203] Specific behavior:

[1204] The user clicks on the link in the confirmation email they received, goes to the login page, and enters their email address and password.

[1205] Input: Confirmation email, email address, password

[1206] Output: Login information is sent to the terminal

[1207] Step 6:

[1208] The device sends the login information to the server.

[1209] Specific behavior:

[1210] When a user enters their email address and password into the login form and presses the "Login" button, the device sends the information to the server.

[1211] Input: Login information (email address, password)

[1212] Output: Login information passed to the server

[1213] Step 7:

[1214] The server performs the authentication.

[1215] Specific behavior:

[1216] The server checks the submitted information against a database to authenticate the user, and if authentication is successful, the user is logged into the system.

[1217] Input: Login information, registration information in the database

[1218] Output: Authentication status of the user

[1219] Step 8:

[1220] The user responds to the survey.

[1221] Specific behavior:

[1222] Users answer a questionnaire about their interests and personality on a profile setting page within the system.

[1223] Input: Survey questions, user answers

[1224] Output: Response data is sent to the device

[1225] Step 9:

[1226] The terminal sends the survey results to the server.

[1227] Specific behavior:

[1228] When the user presses the "send" button, the terminal sends the answer data to the server.

[1229] Input: Response data

[1230] Output: Response data is sent to the server

[1231] Step 10:

[1232] The server makes recommendations using a hobby recommendation engine.

[1233] Specific behavior:

[1234] The server runs a hobby recommendation engine (e.g., a recommendation algorithm built in Python) based on the collected data and selects appropriate hobbies from the database.

[1235] Input: Answer data, hobby information in the database

[1236] Output: A list of recommended hobbies

[1237] Step 11:

[1238] The server sends the recommendation list to the terminal.

[1239] Specific behavior:

[1240] The server transmits the generated hobby recommendation list to the terminal.

[1241] Input: Recommended Hobbies List

[1242] Output: The recommendation list is passed to the device.

[1243] Step 12:

[1244] The terminal displays the list to the user.

[1245] Specific behavior:

[1246] The terminal displays the received recommendation list to the user.

[1247] Input: Recommendation list

[1248] Output: User can view the hobby list

[1249] Step 13:

[1250] The user selects a hobby that interests them.

[1251] Specific behavior:

[1252] The user selects a hobby that interests them from the displayed hobby list.

[1253] Input: Interest list, user selection

[1254] Output: The selected data is sent to the terminal.

[1255] Step 14:

[1256] The terminal transmits the selection information to the server.

[1257] Specific behavior:

[1258] When the user presses the "select" button, the terminal transmits the selected hobby information to the server.

[1259] Input: Selection data

[1260] Output: Selection data is passed to the server

[1261] Step 15:

[1262] The server retrieves the community information.

[1263] Specific behavior:

[1264] The server searches a database for community information (e.g., online forums and physical clubs) related to the selected hobby.

[1265] Input: hobby selection data, community information in the database

[1266] Output: Community information list

[1267] Step 16:

[1268] The server transmits the community information to the terminal.

[1269] Specific behavior:

[1270] The server transmits the community information of the search results to the terminal.

[1271] Input: Community Information List

[1272] Output: Community information is passed to the terminal

[1273] Step 17:

[1274] The terminal displays the community information to the user.

[1275] Specific behavior:

[1276] The terminal displays the received community information to the user.

[1277] Input: Community Information

[1278] Output: User can view community information

[1279] Step 18:

[1280] The user provides feedback.

[1281] Specific behavior:

[1282] Users enter feedback about the recommended hobbies and communities in a rating form.

[1283] Input: Evaluation form, user feedback

[1284] Output: Feedback data is sent to the device

[1285] Step 19:

[1286] The terminal sends feedback information to the server.

[1287] Specific behavior:

[1288] When the user presses the "send" button, the terminal sends the feedback information to the server.

[1289] Input: Feedback data

[1290] Output: Feedback data is passed to the server

[1291] Step 20:

[1292] The server stores the feedback in a database.

[1293] Specific behavior:

[1294] The server stores the received feedback in a database.

[1295] Input: Feedback data

[1296] Output: Feedback data is saved in a database

[1297] Step 21:

[1298] The server performs the analysis.

[1299] Specific behavior:

[1300] The server analyzes the stored feedback and extracts data about user interests and satisfaction.

[1301] Input: Feedback data

[1302] Output: Analysis results

[1303] Step 22:

[1304] The server improves the algorithm.

[1305] Specific behavior:

[1306] The server adjusts the hobby recommendation engine's algorithm based on the analysis results, improving the accuracy of recommendations from next time onwards.

[1307] Input: Analysis results

[1308] Output: An improved recommendation algorithm

[1309] (Application example 1)

[1310] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1311] Conventional methods have not only failed to provide users searching for hobbies that match their interests, but also to provide them with information on products and communities related to those hobbies. Furthermore, the accuracy of the information provided is low, making it difficult to increase user satisfaction.

[1312] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1313] In this invention, the server includes means for accepting user registration information, means for storing the accepted user registration information in a database, means for recommending appropriate hobbies based on the user's interests and personality, means for searching for community information related to the recommended hobbies, means for collecting user feedback and improving the recommendation algorithm, means for recommending related products based on the user's interests, and means for providing users with information on related online forums and nearby clubs, thereby enabling users to discover new hobbies based on their interests and simultaneously obtain related product and community information.

[1314] "User registration information" refers to basic information such as name, email address, and password provided by the user when registering with the system.

[1315] "Database" means a digital information management system for storing data related to user registration information, feedback, and hobby recommendations.

[1316] A "hobby recommendation engine" is a software component that calculates and recommends appropriate hobbies based on a user's interests and personality.

[1317] "Community information" is information such as online forums and local clubs related to hobbies that may interest the user.

[1318] "Feedback" refers to information such as evaluations and opinions provided by users regarding recommended hobby or community information.

[1319] A "recommendation algorithm" is a computational method for analyzing user interests and feedback and reflecting them in the next hobby recommendation.

[1320] "Products" are products or services related to a user's interests or hobbies.

[1321] An "online forum" is a place on the Internet where people share information and communicate about a particular hobby or interest.

[1322] A "club" is a physical place or association where people with common hobbies or interests come together.

[1323] The system for implementing this invention allows users to discover new hobbies and provides them with information on products and communities related to those hobbies. This system is mainly composed of three elements: a server, a terminal, and a user.

[1324] System hardware and software configuration

[1325] Hardware

[1326] Server: Runs on the cloud and is responsible for data processing and storage.

[1327] Device: A device that is directly controlled by the user, such as a smartphone or smart glasses.

[1328] software

[1329] Firebase Auth: Provides user authentication and login functionality.

[1330] Firebase Firestore: A database for storing and retrieving data in real time.

[1331] Google Cloud AI: An AI engine that runs recommendation algorithms and feedback analysis.

[1332] React Native: A framework for building the front end of smartphone apps.

[1333] Processing Details

[1334] User Registration and Login

[1335] Users register their name, email address, and password using a terminal. This information is sent to the server using Firebase Auth for authentication. When the user logs in, the authentication information is sent again to the server, and if authentication is successful, the user can access Firebase Firestore.

[1336] Hobby recommendations

[1337] Users fill out a profile setting page and answer a questionnaire about their interests and personality. This data is sent from the device to a server, where it is processed by a Google Cloud AI recommendation engine to select appropriate hobbies.

[1338] Recommending related products and community information

[1339] Based on the recommended hobbies, the server searches the product database for relevant product information, and also searches the community information stored in Firebase Firestore to provide the user with information on online forums and nearby clubs.

[1340] Gathering feedback and improving the algorithm

[1341] Users provide feedback on the recommended hobbies and community information, which is stored in Firebase Firestore and analyzed by Google Cloud AI to improve the recommendation algorithm.

[1342] Specific examples

[1343] For example, if a user responds that they are interested in "outdoors," the server may recommend outdoor-related products (tents, backpacks, etc.) and may also provide information about online forums related to outdoor activities and nearby hiking clubs.

[1344] Prompt Sentence Examples

[1345] 1. Hobby recommendation prompt:

[1346] Based on your user interest survey response data, please provide the following information:

[1347] Recommended Hobbies List

[1348] A list of product categories related to each hobby

[1349] A brief explanation of the reason for the recommendation

[1350] 2. Community recommendation prompt:

[1351] Based on your selected interests, please provide the following information:

[1352] Online forum URLs related to each hobby

[1353] Nearby hobby club information related to each hobby (with location information)

[1354] This allows users to discover new hobbies based on their own interests and simultaneously obtain information on products and communities related to those hobbies.

[1355] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1356] Step 1:

[1357] A user accesses the system using a terminal and enters their name, email address, and password. The entered registration information is sent from the terminal to the server via Firebase Auth. The server saves this information in a database and sends a confirmation email to the user. The user logs in using the confirmation email they received. The input information is an email address and password, and the output is a flag indicating successful login.

[1358] Step 2:

[1359] After the user logs in, the device will be taken to a profile setting page. The user will then answer a questionnaire about their interests and personality. The survey response data will be sent from the device to the server and stored in Firebase Firestore. The input will be the survey response data, and the output will be the data stored in the database.

[1360] Step 3:

[1361] The server sends a response request to Google Cloud AI based on the survey response data stored in Firebase Firestore, and calculates the hobbies suitable for the user. The calculated hobbies list is returned to the server, which then sends it to the device, which displays it to the user. The input is the survey response data, and the output is the recommended hobbies list.

[1362] Step 4:

[1363] When a user selects a hobby that interests them from the recommended hobbies, the device sends this information to the server. The server searches for related product information from the product database and sends a related product list to the device. It also searches for related online forums and nearby club information from Firebase Firestore and sends this information to the device. The input is the selected hobby information, and the output is a related product list and community information.

[1364] Step 5:

[1365] Users provide feedback on the displayed related product list and community information. The feedback information is sent from the device to the server and stored in Firebase Firestore. The saved feedback information is used for analysis by Google Cloud AI to improve the recommendation algorithm. The input is the feedback information, and the output is an improved recommendation algorithm and improved recommendation accuracy for the next time.

[1366] Step 6:

[1367] The server periodically analyzes the accumulated feedback information and updates the generative AI model via Google Cloud AI, which improves the accuracy of the next hobby and product recommendations and increases user satisfaction. The input is the accumulated feedback information, and the output is the updated generative AI model.

[1368] By following the steps above, users can efficiently discover new hobbies and appropriately obtain product and community information related to those hobbies.

[1369] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1370] This invention relates to a "hobby discovery support system" that helps users who do not have any hobbies to discover new interests and hobbies. In particular, it adds a function to recognize the user's emotional state and recommend appropriate hobbies and related communities based on that emotion. The system also includes a means to collect user emotional feedback and improve the emotion engine.

[1371] User Registration / Login

[1372] Examples:

[1373] A user accesses the system and enters their name, email address, and password into the registration form.

[1374] The terminal transmits the entered user registration information to the server.

[1375] The server stores the received registration information in a database.

[1376] The server will send a confirmation email to the user confirming the registration.

[1377] User Login

[1378] Examples:

[1379] The user enters their email address and password into the login form.

[1380] The terminal transmits the entered login information to the server.

[1381] The server checks the user information in the database and performs authentication.

[1382] If the authentication is successful, the server creates a session and sends a session ID to the terminal.

[1383] User information collection

[1384] Examples:

[1385] Users visit a profile setup page and answer questions about their interests and personality.

[1386] The terminal transmits the collected user information to the server.

[1387] emotion recognition

[1388] Examples:

[1389] Users access the system through an emotion-recognition camera.

[1390] The terminal transmits the user's facial image captured by the camera to the server.

[1391] The server uses an emotion engine to recognize the user's emotions (happiness, sadness, surprise, etc.) from the image.

[1392] The recognized emotion information is stored on the server.

[1393] Hobby recommendations

[1394] Examples:

[1395] The server selects appropriate hobbies using a hobby recommendation engine based on the recognized emotion information and existing profile information.

[1396] The server transmits a list of recommended hobbies to the terminal.

[1397] The terminal displays the recommended hobbies to the user.

[1398] Community Search

[1399] Examples:

[1400] Users select hobbies that interest them within the system.

[1401] The terminal transmits the selected hobby information to the server.

[1402] The server searches a database for community information related to the hobby (online forums, local clubs, etc.).

[1403] Community Recommendations

[1404] Examples:

[1405] The server returns the retrieved community information to the terminal.

[1406] The terminal displays the recommended community information to the user.

[1407] Feedback collection

[1408] Examples:

[1409] Users provide feedback on recommended hobbies and communities.

[1410] The feedback also includes a rating based on the user's emotional state.

[1411] The terminal transmits the feedback information to the server.

[1412] The server stores the feedback information in a database.

[1413] Algorithm Improvement

[1414] Examples:

[1415] The server analyzes the collected feedback.

[1416] The server improves the algorithms of the hobby recommendation engine and the emotion engine based on the analysis results.

[1417] Through this series of steps, the system can effectively recommend hobbies and communities that are suitable for the user and provide more accurate recommendations. By taking the user's emotional state into account, the quality of the recommended hobbies and communities can be further improved, allowing the user to discover new hobbies in a more satisfying way.

[1418] The processing flow will be explained below.

[1419] Step 1: User Registration

[1420] A user accesses the system and enters their name, email address, and password into the registration form.

[1421] The terminal transmits the entered user registration information to the server.

[1422] The server stores the received registration information in a database.

[1423] The server will send a confirmation email to the user confirming the registration.

[1424] Step 2: User Login

[1425] The user enters their email address and password into the login form.

[1426] The terminal transmits the entered login information to the server.

[1427] The server checks the user information in the database and performs authentication.

[1428] If the authentication is successful, the server creates a session and sends a session ID to the terminal.

[1429] Step 3: Collect user information

[1430] Users visit a profile setup page and answer questions about their interests and personality.

[1431] The terminal transmits the collected user information to the server.

[1432] Step 4: Emotion Recognition

[1433] Users access the system through an emotion-recognition camera.

[1434] The terminal transmits the user's facial image captured by the camera to the server.

[1435] The server uses an emotion engine to recognize the user's emotions (happiness, sadness, surprise, etc.) from the image.

[1436] The recognized emotion information is stored on the server.

[1437] Step 5: Hobby recommendation

[1438] The server selects appropriate hobbies using a hobby recommendation engine based on the recognized emotion information and existing profile information.

[1439] The server transmits a list of recommended hobbies to the terminal.

[1440] The terminal displays the recommended hobbies to the user.

[1441] Step 6: Community Search

[1442] Users select hobbies that interest them within the system.

[1443] The terminal transmits the selected hobby information to the server.

[1444] The server searches a database for community information related to the hobby (online forums, local clubs, etc.).

[1445] Step 7: Community Nomination

[1446] The server returns the retrieved community information to the terminal.

[1447] The terminal displays the recommended community information to the user.

[1448] Step 8: Gather feedback

[1449] Users provide feedback on recommended hobbies and communities, including ratings based on the user's emotional state.

[1450] The terminal transmits the feedback information to the server.

[1451] The server stores the feedback information in a database.

[1452] Step 9: Improve the algorithm

[1453] The server analyzes the collected feedback.

[1454] The server improves the algorithms of the hobby recommendation engine and the emotion engine based on the analysis results.

[1455] This detailed processing flow allows users to receive more accurate interest and community recommendations based on their emotional state, and allows us to leverage feedback to continuously improve the algorithm, thereby increasing system performance and user satisfaction.

[1456] Example 2

[1457] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1458] In today's world, it is difficult for users who do not have any hobbies to discover new hobbies or interests that suit them. Furthermore, recommended hobbies and communities may not necessarily be suitable for each user unless the emotional state of each individual user is taken into consideration. Therefore, there is a need for a method to collect users' emotional feedback and use it to improve the system's recommendation accuracy.

[1459] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for accepting user registration information, means for storing the accepted user registration information in a database, means for recognizing the emotional state of the user and recommending appropriate hobbies based on the emotional state and the user's interests and personality, means for searching the database for community information related to the recommended hobbies, and means for collecting feedback from the user and improving the recommendation algorithm and emotion recognition engine based on the feedback. This enables highly accurate recommendation of hobbies and communities based on the user's emotional state.

[1460] "User registration information" refers to personal information such as name, email address, and password that a user enters when accessing the system for the first time.

[1461] A "database" is a data structure that the system uses to store and manage data such as user information, emotional state, and feedback.

[1462] "Emotional state" is information indicating a psychological state such as joy, sadness, surprise, etc., recognized from the user's facial expression.

[1463] "Hobbies" refer to activities or areas in which a user has personal interests or concerns.

[1464] "Recommending" refers to the act of the system presenting hobbies and communities that it deems most suitable based on the user's information.

[1465] "Community information" refers to information such as online forums and physical clubs related to a particular hobby.

[1466] "Feedback" is information such as the user's evaluation and opinions of the recommended hobby or community.

[1467] An "algorithm" is a computational procedure that allows the system to analyze user information and emotional state and recommend optimal hobbies and communities.

[1468] An "emotion recognition engine" is a piece of software that analyzes a user's facial image and other data to recognize their emotional state.

[1469] This invention relates to a "hobby discovery support system" that allows users without hobbies to discover new hobbies and interests that suit them and find communities based on those hobbies. This system has the function of recognizing the user's emotional state and recommending appropriate hobbies and related communities based on that emotion. It can also collect user emotional feedback and use that feedback to improve the system's recommendation algorithm and emotion recognition engine.

[1470] Hardware and Software Configuration

[1471] The main components of the system include:

[1472] Server: Stores and manages user information, emotion information, and feedback information in a database. The server runs an emotion recognition engine and a hobby recommendation engine to provide appropriate information to users.

[1473] Terminal: A device that allows users to input and obtain information. Examples include PCs, smartphones, and tablets.

[1474] Database: A data structure for storing user information, emotion data, hobby information, community information, and feedback information.

[1475] Emotion recognition engine: Software that analyzes a user's facial image to recognize their emotional state. Examples of engines that can be used include Microsoft Azure Face API and Google Cloud Vision.

[1476] Hobby recommendation engine: Software that uses a generative AI model to generate optimal hobbies based on a user's emotional state and profile information.

[1477] Details of system processing

[1478] User Registration / Login

[1479] First, a user accesses the system and enters their name, email address, and password. The device sends this to the server, which stores it in a database. Once registration is complete, a confirmation email is sent. When the user logs in, they enter their email address and password, and the device again sends this to the server. The server compares this with the information in the database, and if authentication is successful, it generates a session ID and sends it to the device.

[1480] User information collection

[1481] Users answer questions about their interests and personality on a profile setup page, and the device sends the collected information to a server, which stores it in a database.

[1482] emotion recognition

[1483] The user provides a facial image through the emotion recognition camera, and the device sends the facial image to the server, which then uses an emotion recognition engine to analyze the user's emotional state. The analysis results are then stored in a database.

[1484] Hobby recommendations

[1485] The server runs a hobby recommendation engine using the latest emotion information and user profile information, and sends the generated hobby list to the terminal and displays it to the user.

[1486] Community Search

[1487] The user selects the hobbies they are interested in from the displayed hobbies, and the terminal sends the selection information to the server, which then searches the database for related community information.

[1488] Community Recommendations

[1489] The retrieved community information is sent to the terminal and displayed to the user.

[1490] Feedback collection

[1491] Users provide feedback on their hobbies and communities, and their devices send it to the server, which stores the feedback information in a database.

[1492] Algorithm Improvement

[1493] The server analyzes the collected feedback and dynamically adjusts the parameters of the recommendation algorithm and emotion recognition engine.

[1494] Examples of concrete examples and prompts

[1495] As a specific example of operation, if a user expresses an interest in "painting," the server will recommend hobbies related to "watercolor painting" and "digital art." If the user is interested in "watercolor painting," the server will recommend community information such as "local watercolor painting clubs" and "online watercolor painting forums."

[1496] Here are some examples of prompts:

[1497] "What new hobbies should we recommend to users when they feel joy?"

[1498] "Where is the best community for users interested in watercolor painting?"

[1499] As described above, the "hobby discovery support system" of the present invention realizes highly accurate recommendation of hobbies and communities that take into account the emotional state of the user.

[1500] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1501] Step 1:

[1502] Enter user registration information

[1503] A user fills in the system's registration form with their name, email address, and password, which serves as input data for the system, and is used to identify the user.

[1504] Step 2:

[1505] Sending user registration information

[1506] The device sends the entered user information to the server in the form of an HTTP POST request. The data is encrypted, thereby protecting the user information.

[1507] Step 3:

[1508] Saving user registration information

[1509] The server validates the received user information and checks for invalid data. After validation is complete, the server stores the information in the "User Information" table in the database. As an output, the server generates a confirmation of successful registration and sends it to the mail server.

[1510] Step 4:

[1511] Enter your user login information

[1512] A user enters an email address and password into a login form. This information is the input data for authentication.

[1513] Step 5:

[1514] Sending user login information

[1515] The device sends the entered login information to the server, where it is also encrypted to ensure data security.

[1516] Step 6:

[1517] User authentication process

[1518] The server searches for the corresponding user information in the "User Information" table in the database and compares it with the entered password. If authentication is successful, the server creates a session, generates a session ID and sends it to the terminal. As an output, the terminal displays the main page to the user.

[1519] Step 7:

[1520] User information collection

[1521] Users access a profile setup page and answer questions about their interests and personality, which are then used as input data for the system's profile data.

[1522] Step 8:

[1523] Sending and storing user information

[1524] The terminal sends the collected user information to the server, which stores it in the "User Profile" table in the database. As an output, the server notifies the user that the profile has been set up.

[1525] Step 9:

[1526] Emotion Recognition Camera Setup

[1527] The user activates the emotion recognition camera and captures facial images through the device, which serve as input data for emotion recognition.

[1528] Step 10:

[1529] Facial image transmission and emotion analysis

[1530] The device sends the captured face image to the server, which then calls an emotion recognition engine (e.g., Microsoft Azure Face API) to analyze the user's emotion from the image. As an output, analyzed emotion information is generated and stored in the "emotion data" table in the database.

[1531] Step 11:

[1532] Running a hobby recommendation engine

[1533] The server retrieves the latest emotion information and user profile information and runs an interest recommendation engine. This engine generates appropriate hobbies using a generative AI model. It uses emotion information and profile information as input and generates a list of hobbies as output.

[1534] Step 12:

[1535] Submit and view recommended hobby lists

[1536] The server sends the recommended hobby list to the terminal, which displays it to the user and provides an interface to attract the user's interest.

[1537] Step 13:

[1538] Start a Community Search

[1539] The user selects a hobby from the displayed hobby list that they are interested in. The terminal then sends information about the selected hobby to the server.

[1540] Step 14:

[1541] Search for related community information

[1542] The server retrieves community information related to the selected hobby from a database, such as online forums and physical club data.

[1543] Step 15:

[1544] Submitting and Viewing Community Information

[1545] The server sends the retrieved community information to the terminal, which displays it to the user, allowing the user to access communities that interest them.

[1546] Step 16:

[1547] Feedback Input

[1548] Users input feedback on the recommended hobbies and communities, which serves as input data for improving the system.

[1549] Step 17:

[1550] Send and save feedback

[1551] The terminal sends the feedback information to the server, which stores it in the "feedback data" table of the database. As an output, the server notifies the user of the confirmation of receipt of the feedback.

[1552] Step 18:

[1553] Algorithm analysis and updates

[1554] The server analyzes the collected feedback and dynamically adjusts the parameters of the recommendation algorithm and emotion recognition engine based on the results. The output is an improved algorithm, which improves the accuracy of recommendations from the next time onwards.

[1555] (Application example 2)

[1556] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1557] Conventional recommendation systems recommend hobbies and products based on a user's static interests and personality information, but they lack the ability to provide real-time recommendations that take into account the user's emotional state. This can result in a failure to meet users' momentary needs and a decrease in satisfaction. Furthermore, there is a lack of concrete measures to improve the shopping experience in physical stores.

[1558] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for accepting user registration information, means for storing the accepted user registration information in a database, means for recommending appropriate hobbies based on the user's interests and personality, means for recognizing the user's emotional state using an emotion recognition camera, means for recommending products based on the recognized emotional information, means for displaying the recommended products on a visual device, and means for collecting feedback from users and improving the recommendation algorithm. This enables real-time product recommendations based on the user's emotional state, thereby improving the quality of shopping experiences in physical stores.

[1559] "User registration information" refers to personal information such as the user's name, email address, and password.

[1560] "Database" refers to a computer system or storage for systematically storing and retrieving information.

[1561] "Appropriate hobbies" refer to activities and interests that are recommended based on a user's interests and personality.

[1562] An "emotion recognition camera" refers to an image processing device that captures a user's facial expressions and analyzes their emotional state.

[1563] "Emotion information" refers to data collected by an emotion-recognition camera about a user's emotional state, such as happiness, sadness, or surprise.

[1564] "Means for recommending products" refers to the function of selecting and presenting appropriate products based on the user's emotional information.

[1565] "Visual device" refers to a device that allows a user to receive information visually, such as smart glasses or a head-mounted display.

[1566] "Feedback" refers to the evaluations and impressions that users give about recommended hobbies or products.

[1567] A "recommendation algorithm" refers to a computational method for selecting appropriate hobbies and products using data such as a user's interests, personality, and emotional state.

[1568] "Brick and mortar store" refers to a retail store that is a physical location where users can visit in person to purchase goods or services.

[1569]

[1570] MODE FOR CARRYING OUT THE INVENTION

[1571] This invention is an emotion recognition-based hobby and product recommendation system that improves the shopping experience in brick-and-mortar stores based on the user's emotional state. The system accepts user registration information, stores it in a database, and recommends hobbies and products based on the user's static interests and personality information, as well as real-time emotional information.

[1572] The server includes the following means:

[1573] Method for accepting user registration information: The user enters personal information into the registration form and sends it from the terminal to the server, whereupon the user's basic information is stored in a database.

[1574] A means for storing the received user registration information in a database: The server systematically stores and manages the received information in a database.

[1575] A means of recommending appropriate hobbies based on the user's interests and personality: The server uses a hobby recommendation engine to select and recommend appropriate hobbies based on the data on interests and personality provided by the user.

[1576] A means of recognizing a user's emotional state using an emotion recognition camera: A camera installed in the device (visual device such as smart glasses) captures the user's face in real time and sends the image to an emotion recognition engine to analyze the emotional information.

[1577] Means for recommending products based on recognized emotional information: Based on the recognized emotional information, a recommendation engine is used to select appropriate products and present them to the user.

[1578] Means for displaying recommended products on a visual device: Product information sent from the server is overlaid on the display of the visual device.

[1579] A means of collecting user feedback and improving the recommendation algorithm: User feedback is sent from the device to the server and used to dynamically adjust the recommendation algorithm.

[1580] Hardware and software used

[1581] Hardware: smart glasses, cameras, servers, visual devices (e.g. Google Glass, Vuzix Blade)

[1582] Software: Emotion recognition module (e.g., OpenCV, dlib, Face++ API), hobby recommendation engine, product recommendation engine, database management system

[1583] Data flow and specific examples

[1584] A user wears smart glasses while shopping in a physical store. The glasses' built-in camera captures the user's facial image and analyzes it using an emotion recognition engine. For example, if the system detects that the user looks slightly tired, it generates a list of products with a refreshing effect and overlays them on the smart glasses' display. This allows the user to visually check recommended products while walking around the store.

[1585] Examples of prompt statements

[1586] "Please recommend products suitable for users who look tired. For example, aroma products or massage machines like the ones below."

[1587] In this way, by providing a specific form for implementing the invention, it becomes possible to recommend products in real time according to the user's emotional state, thereby improving the quality of the shopping experience in physical stores.

[1588] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1589] Step 1:

[1590] The server accepts user registration information. The data to be entered includes name, email address, and password. The user enters this data into the registration form and sends it from the terminal to the server. The server receives this data and stores it systematically in a database.

[1591] Step 2:

[1592] The device collects data to recommend appropriate hobbies based on the user's interests and personality. The user accesses a profile setting page and answers questions about their interests and personality. The collected data is sent from the device to a server, which stores it in a database.

[1593] Step 3:

[1594] The device recognizes the user's emotional state using an emotion recognition camera installed in the smart glasses. The camera captures the user's facial image in real time and sends the image to a server. The server then uses an emotion recognition engine to analyze the user's emotional information from the image and stores the results in a database.

[1595] Step 4:

[1596] The server recommends products based on the recognized emotion information. The user's emotion information and past interest data are used as input. The server's recommendation engine uses this data to create a list of appropriate products and sends the information to the device.

[1597] Step 5:

[1598] The terminal displays the recommended products on a visual device. The recommended products are overlaid on the display of the visual device (e.g., smart glasses). The user can view the recommended products through the visual device while moving around the physical store.

[1599] Step 6:

[1600] Users provide feedback on the recommended products and the system's recommendation accuracy. The feedback includes information about interests and satisfaction, and is sent from the device to the server, which stores it in a database.

[1601] Step 7:

[1602] The server improves the recommendation algorithm based on the collected feedback. It analyzes the feedback data and uses the results to dynamically adjust the recommendation algorithm, thereby improving the accuracy of future recommendations.

[1603] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1604] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1605] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1606] [Fourth embodiment]

[1607] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1608] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1609] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1610] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1611] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1612] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1613] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1614] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1615] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1616] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1617] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1618] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1619] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1620] This invention relates to a "hobby discovery support system" that helps users who do not have any hobbies to find new interests or hobbies. This system recommends hobbies and related communities that are suitable for each user based on the user's registered information, and further improves the recommendation algorithm based on user feedback.

[1621] User Registration / Login

[1622] Examples:

[1623] A user accesses the system and enters their name, email address, and password into the registration form.

[1624] The terminal transmits the entered registration information to the server, which stores this information in a database.

[1625] After registration is complete, the server sends a confirmation email to the user, who then checks the email and performs the login procedure.

[1626] Enter your email address and password into the login form, and the device will send the information to the server, which will then authenticate you.

[1627] Hobby recommendations

[1628] Examples:

[1629] Users answer a questionnaire about their interests and personality on a profile setting page within the system.

[1630] The device sends this data to the server, which then uses a hobby recommendation engine to select appropriate hobbies from a database.

[1631] The recommended hobby list is sent back from the server to the terminal, which displays it to the user.

[1632] Community information search and recommendation

[1633] Examples:

[1634] Users select hobbies that interest them within the system.

[1635] The terminal transmits the selection information to the server, and the server searches a database for community information related to the hobby.

[1636] The server returns relevant online forum and nearby club information to the terminal, which displays this to the user.

[1637] Gathering feedback and improving our algorithms

[1638] Examples:

[1639] Users provide feedback on hobbies and communities recommended by the system.

[1640] The terminal sends the feedback information to the server, which stores it in a database and analyzes it.

[1641] Based on the analysis results, the server improves the hobby recommendation engine's algorithm and improves the accuracy of the next recommendation.

[1642] System Operation

[1643] The specific operation of this system is as follows: Once a user registers and logs in, the system recommends hobbies based on the user's interests and personality information. In addition, by providing community information related to those hobbies, the system makes it easier for users to find places where they can actually experience those hobbies. Based on user feedback, the system improves its recommendation algorithm, enabling it to provide more accurate recommendations.

[1644] In this way, the present invention provides a system that helps users efficiently find new hobbies and deepen their interests, thereby increasing the sense of fulfillment in their lives.

[1645] The processing flow will be explained below.

[1646] Step 1: User Registration

[1647] A user accesses the system and enters their name, email address, and password into the registration form.

[1648] The terminal transmits the entered user registration information to the server.

[1649] The server stores the received registration information in a database.

[1650] The server will send a confirmation email to the user confirming the registration.

[1651] Step 2: User Login

[1652] The user enters their email address and password into the login form.

[1653] The terminal transmits the entered login information to the server.

[1654] The server checks the user information in the database and performs authentication.

[1655] If the authentication is successful, the server creates a session and sends a session ID to the terminal.

[1656] Step 3: Collect user information

[1657] Users visit a profile setup page and answer questions about their interests and personality.

[1658] The terminal transmits the collected user information to the server.

[1659] Step 4: Hobby recommendation

[1660] The server inputs the collected user profile information into the hobby recommendation engine.

[1661] The hobby recommendation engine uses an algorithm to select suitable hobbies for the user from a database.

[1662] The server transmits a list of recommended hobbies to the terminal.

[1663] The terminal displays the recommended hobbies to the user.

[1664] Step 5: Community Search

[1665] Users select hobbies that interest them within the system.

[1666] The terminal transmits the selected hobby information to the server.

[1667] The server searches a database for community information related to the hobby (online forums, local clubs, etc.).

[1668] Step 6: Community Nomination

[1669] The server returns the retrieved community information to the terminal.

[1670] The terminal displays the recommended community information to the user.

[1671] Step 7: Gather feedback

[1672] Users provide feedback on recommended hobbies and communities.

[1673] The terminal transmits the feedback information to the server.

[1674] The server stores the feedback information in a database.

[1675] Step 8: Improve the algorithm

[1676] The server analyzes the collected feedback.

[1677] The server improves the algorithm of the hobby recommendation engine based on the analysis results.

[1678] Through this series of steps, the system can effectively recommend hobbies and communities that are suitable for the user and provide more accurate recommendations.

[1679] Example 1

[1680] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1681] In recent years, many people have no hobbies or are looking for new interests. However, the amount of information available to find suitable hobbies and interests is enormous, making it difficult to efficiently find hobbies that meet individual needs. It is also difficult to find places and communities where people can actually experience their hobbies. Furthermore, there is a need for a method to effectively utilize provided feedback to improve recommendation algorithms and increase user satisfaction.

[1682] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1683] In this invention, the server includes means for accepting user registration information, means for storing the accepted user registration information in a database, means for authenticating the user using user authentication information, means for recommending appropriate hobbies based on the user's interests and personality, means for searching for community information related to the recommended hobbies, and means for collecting feedback from users and improving the recommendation algorithm. This makes it easier for users to efficiently find new hobbies and places where they can experience them, and also makes it possible to dynamically adjust the recommendation algorithm based on the provided feedback, thereby increasing user satisfaction.

[1684] "Means for accepting user registration information" refers to the interface through which a user accesses the system, inputs personal information such as name, email address, and password, and provides that information to the system.

[1685] "Means for saving the received user registration information in a database" refers to a function for safely and efficiently saving the input user registration information in a database.

[1686] "Means of authenticating a user using user authentication information" refers to the process of verifying whether a user is a legitimate registered user based on the email address and password entered into the login form.

[1687] "Means for recommending appropriate hobbies based on the user's interests and personality" refers to the algorithm and its operation that analyzes the questionnaire data answered by the user and suggests the most suitable hobbies.

[1688] "Means for searching for community information related to the recommended hobby" refers to a function that searches a database for community information such as online forums and physical clubs related to the suggested hobby and provides it.

[1689] "Means for collecting user feedback and improving the recommendation algorithm" refers to the process of storing user-provided feedback in a database and analyzing that data to improve the accuracy of the recommendation algorithm.

[1690] The present invention relates to a "hobby discovery support system" that supports users who do not have any hobbies in finding new interests or hobbies. Specific embodiments for carrying out the present invention will be described below.

[1691] User Registration / Login

[1692] This system begins when the user enters registration information. The user accesses the system and enters their name, email address, and password. When the user presses the "Register" button, the terminal sends this registration information to the server. The server saves this in a database (e.g., MySQL database). The server then sends a confirmation email to the user's email address, and the user clicks on the link in the email to complete the login procedure. The user enters their email address and password in the login form, and the terminal sends the information to the server. The server compares this with the database and authenticates the user.

[1693] Hobby recommendations

[1694] After logging in, the user answers a questionnaire about their interests and personality on the profile setting page within the system. When the user presses the "Submit" button, the device sends this data to the server. The server then runs an interest recommendation engine (e.g., a recommendation algorithm built in Python) based on the collected data and selects appropriate interests from the database. The server then sends the recommended interest list to the device, which then displays it to the user.

[1695] Community information search and recommendation

[1696] The user selects a hobby that interests them from the displayed hobby list. When the user presses the "Select" button, the device sends the selection information to the server. The server searches its database for community information (e.g., online forums or physical clubs) related to the selected hobby. The search results are sent back to the device, which displays them to the user.

[1697] Gathering feedback and improving our algorithms

[1698] The user provides feedback on the hobbies and communities recommended by the system. When the user fills out the feedback form and presses the "Submit" button, the device sends the feedback information to the server, which stores it in a database and analyzes it. Based on the analysis results, the server improves the algorithm of the hobby recommendation engine, thereby improving the accuracy of the next recommendation.

[1699] Specific examples

[1700] User "Yamada Taro" accesses the system and enters his name "Yamada Taro," his email address "taro@example.com," and his password "password123." The server stores this information in a database and sends a confirmation email. The user receives the confirmation email and clicks the link to log in. After logging in, the user answers "blue" to the question "What is your favorite color?", and the device sends this to the server. The server includes hobbies related to blue, such as "fishing" and "astronomy," in a recommendation list and sends it to the device. When the user selects "fishing," the server searches for information such as "fishing forums" and "nearby fishing clubs" and sends it to the device. The user evaluates the fishing recommendation as "appropriate," and the device sends the feedback information to the server, which stores it in a database, analyzes it, and improves the algorithm.

[1701] Prompt Sentence Examples

[1702] "Please recommend a suitable hobby for a woman in her 20s who is interested in the outdoors."

[1703] "Find recommended online communities for middle school students interested in coding."

[1704] In this way, the present invention provides a system that helps users efficiently discover new hobbies and deepen their interests. By recommending hobbies based on the user's interests and personality and providing related community information, the system increases the user's opportunities to actually experience the hobbies, and improves the algorithm based on feedback, thereby increasing recommendation accuracy.

[1705] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1706] Step 1:

[1707] The user enters registration information.

[1708] Specific behavior:

[1709] The user enters their name, email address, and password into the system's registration form.

[1710] Input: Name, Email Address, Password

[1711] Output: Registration information is sent to the device

[1712] Step 2:

[1713] The terminal sends the input information to the server.

[1714] Specific behavior:

[1715] When the user presses the "Register" button, the device sends the user's name, email address, and password to the server.

[1716] Input: Registration information (name, email address, password)

[1717] Output: Registration information passed to the server

[1718] Step 3:

[1719] The server stores it in a database.

[1720] Specific behavior:

[1721] The server stores the received registration information in a database.

[1722] Input: Registration information

[1723] Output: Registration information is saved in the database

[1724] Step 4:

[1725] The server sends a confirmation email.

[1726] Specific behavior:

[1727] The server will send a confirmation email to the registered email address.

[1728] Input: User's email address

[1729] Output: A confirmation email is sent to the user.

[1730] Step 5:

[1731] The user checks the confirmation email and logs in.

[1732] Specific behavior:

[1733] The user clicks on the link in the confirmation email they received, goes to the login page, and enters their email address and password.

[1734] Input: Confirmation email, email address, password

[1735] Output: Login information is sent to the terminal

[1736] Step 6:

[1737] The device sends the login information to the server.

[1738] Specific behavior:

[1739] When a user enters their email address and password into the login form and presses the "Login" button, the device sends the information to the server.

[1740] Input: Login information (email address, password)

[1741] Output: Login information passed to the server

[1742] Step 7:

[1743] The server performs the authentication.

[1744] Specific behavior:

[1745] The server checks the submitted information against a database to authenticate the user, and if authentication is successful, the user is logged into the system.

[1746] Input: Login information, registration information in the database

[1747] Output: Authentication status of the user

[1748] Step 8:

[1749] The user responds to the survey.

[1750] Specific behavior:

[1751] Users answer a questionnaire about their interests and personality on a profile setting page within the system.

[1752] Input: Survey questions, user answers

[1753] Output: Response data is sent to the device

[1754] Step 9:

[1755] The terminal sends the survey results to the server.

[1756] Specific behavior:

[1757] When the user presses the "send" button, the terminal sends the answer data to the server.

[1758] Input: Response data

[1759] Output: Response data is sent to the server

[1760] Step 10:

[1761] The server makes recommendations using a hobby recommendation engine.

[1762] Specific behavior:

[1763] The server runs a hobby recommendation engine (e.g., a recommendation algorithm built in Python) based on the collected data and selects appropriate hobbies from the database.

[1764] Input: Answer data, hobby information in the database

[1765] Output: A list of recommended hobbies

[1766] Step 11:

[1767] The server sends the recommendation list to the terminal.

[1768] Specific behavior:

[1769] The server transmits the generated hobby recommendation list to the terminal.

[1770] Input: Recommended Hobbies List

[1771] Output: The recommendation list is passed to the device.

[1772] Step 12:

[1773] The terminal displays the list to the user.

[1774] Specific behavior:

[1775] The terminal displays the received recommendation list to the user.

[1776] Input: Recommendation list

[1777] Output: User can view the hobby list

[1778] Step 13:

[1779] The user selects a hobby that interests them.

[1780] Specific behavior:

[1781] The user selects a hobby that interests them from the displayed hobby list.

[1782] Input: Interest list, user selection

[1783] Output: The selected data is sent to the terminal.

[1784] Step 14:

[1785] The terminal transmits the selection information to the server.

[1786] Specific behavior:

[1787] When the user presses the "select" button, the terminal transmits the selected hobby information to the server.

[1788] Input: Selection data

[1789] Output: Selection data is passed to the server

[1790] Step 15:

[1791] The server retrieves the community information.

[1792] Specific behavior:

[1793] The server searches a database for community information (e.g., online forums and physical clubs) related to the selected hobby.

[1794] Input: hobby selection data, community information in the database

[1795] Output: Community information list

[1796] Step 16:

[1797] The server transmits the community information to the terminal.

[1798] Specific behavior:

[1799] The server transmits the community information of the search results to the terminal.

[1800] Input: Community Information List

[1801] Output: Community information is passed to the terminal

[1802] Step 17:

[1803] The terminal displays the community information to the user.

[1804] Specific behavior:

[1805] The terminal displays the received community information to the user.

[1806] Input: Community Information

[1807] Output: User can view community information

[1808] Step 18:

[1809] The user provides feedback.

[1810] Specific behavior:

[1811] Users enter feedback about the recommended hobbies and communities in a rating form.

[1812] Input: Evaluation form, user feedback

[1813] Output: Feedback data is sent to the device

[1814] Step 19:

[1815] The terminal sends feedback information to the server.

[1816] Specific behavior:

[1817] When the user presses the "send" button, the terminal sends the feedback information to the server.

[1818] Input: Feedback data

[1819] Output: Feedback data is passed to the server

[1820] Step 20:

[1821] The server stores the feedback in a database.

[1822] Specific behavior:

[1823] The server stores the received feedback in a database.

[1824] Input: Feedback data

[1825] Output: Feedback data is saved in a database

[1826] Step 21:

[1827] The server performs the analysis.

[1828] Specific behavior:

[1829] The server analyzes the stored feedback and extracts data about user interests and satisfaction.

[1830] Input: Feedback data

[1831] Output: Analysis results

[1832] Step 22:

[1833] The server improves the algorithm.

[1834] Specific behavior:

[1835] The server adjusts the hobby recommendation engine's algorithm based on the analysis results, improving the accuracy of recommendations from next time onwards.

[1836] Input: Analysis results

[1837] Output: An improved recommendation algorithm

[1838] (Application example 1)

[1839] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1840] Conventional methods have not only failed to provide users searching for hobbies that match their interests, but also to provide them with information on products and communities related to those hobbies. Furthermore, the accuracy of the information provided is low, making it difficult to increase user satisfaction.

[1841] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1842] In this invention, the server includes means for accepting user registration information, means for storing the accepted user registration information in a database, means for recommending appropriate hobbies based on the user's interests and personality, means for searching for community information related to the recommended hobbies, means for collecting user feedback and improving the recommendation algorithm, means for recommending related products based on the user's interests, and means for providing users with information on related online forums and nearby clubs, thereby enabling users to discover new hobbies based on their interests and simultaneously obtain related product and community information.

[1843] "User registration information" refers to basic information such as name, email address, and password provided by the user when registering with the system.

[1844] "Database" means a digital information management system for storing data related to user registration information, feedback, and hobby recommendations.

[1845] A "hobby recommendation engine" is a software component that calculates and recommends appropriate hobbies based on a user's interests and personality.

[1846] "Community information" is information such as online forums and local clubs related to hobbies that may interest the user.

[1847] "Feedback" refers to information such as evaluations and opinions provided by users regarding recommended hobby or community information.

[1848] A "recommendation algorithm" is a computational method for analyzing user interests and feedback and reflecting them in the next hobby recommendation.

[1849] "Products" are products or services related to a user's interests or hobbies.

[1850] An "online forum" is a place on the Internet where people share information and communicate about a particular hobby or interest.

[1851] A "club" is a physical place or association where people with common hobbies or interests come together.

[1852] The system for implementing this invention allows users to discover new hobbies and provides them with information on products and communities related to those hobbies. This system is mainly composed of three elements: a server, a terminal, and a user.

[1853] System hardware and software configuration

[1854] Hardware

[1855] Server: Runs on the cloud and is responsible for data processing and storage.

[1856] Device: A device that is directly controlled by the user, such as a smartphone or smart glasses.

[1857] software

[1858] Firebase Auth: Provides user authentication and login functionality.

[1859] Firebase Firestore: A database for storing and retrieving data in real time.

[1860] Google Cloud AI: An AI engine that runs recommendation algorithms and feedback analysis.

[1861] React Native: A framework for building the front end of smartphone apps.

[1862] Processing Details

[1863] User Registration and Login

[1864] Users register their name, email address, and password using a terminal. This information is sent to the server using Firebase Auth for authentication. When the user logs in, the authentication information is sent again to the server, and if authentication is successful, the user can access Firebase Firestore.

[1865] Hobby recommendations

[1866] Users fill out a profile setting page and answer a questionnaire about their interests and personality. This data is sent from the device to a server, where it is processed by a Google Cloud AI recommendation engine to select appropriate hobbies.

[1867] Recommending related products and community information

[1868] Based on the recommended hobbies, the server searches the product database for relevant product information, and also searches the community information stored in Firebase Firestore to provide the user with information on online forums and nearby clubs.

[1869] Gathering feedback and improving the algorithm

[1870] Users provide feedback on the recommended hobbies and community information, which is stored in Firebase Firestore and analyzed by Google Cloud AI to improve the recommendation algorithm.

[1871] Specific examples

[1872] For example, if a user responds that they are interested in "outdoors," the server may recommend outdoor-related products (tents, backpacks, etc.) and may also provide information about online forums related to outdoor activities and nearby hiking clubs.

[1873] Prompt Sentence Examples

[1874] 1. Hobby recommendation prompt:

[1875] Based on your user interest survey response data, please provide the following information:

[1876] Recommended Hobbies List

[1877] A list of product categories related to each hobby

[1878] A brief explanation of the reason for the recommendation

[1879] 2. Community recommendation prompt:

[1880] Based on your selected interests, please provide the following information:

[1881] Online forum URLs related to each hobby

[1882] Nearby hobby club information related to each hobby (with location information)

[1883] This allows users to discover new hobbies based on their own interests and simultaneously obtain information on products and communities related to those hobbies.

[1884] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1885] Step 1:

[1886] A user accesses the system using a terminal and enters their name, email address, and password. The entered registration information is sent from the terminal to the server via Firebase Auth. The server saves this information in a database and sends a confirmation email to the user. The user logs in using the confirmation email they received. The input information is an email address and password, and the output is a flag indicating successful login.

[1887] Step 2:

[1888] After the user logs in, the device will be taken to a profile setting page. The user will then answer a questionnaire about their interests and personality. The survey response data will be sent from the device to the server and stored in Firebase Firestore. The input will be the survey response data, and the output will be the data stored in the database.

[1889] Step 3:

[1890] The server sends a response request to Google Cloud AI based on the survey response data stored in Firebase Firestore, and calculates the hobbies suitable for the user. The calculated hobbies list is returned to the server, which then sends it to the device, which displays it to the user. The input is the survey response data, and the output is the recommended hobbies list.

[1891] Step 4:

[1892] When a user selects a hobby that interests them from the recommended hobbies, the device sends this information to the server. The server searches for related product information from the product database and sends a related product list to the device. It also searches for related online forums and nearby club information from Firebase Firestore and sends this information to the device. The input is the selected hobby information, and the output is a related product list and community information.

[1893] Step 5:

[1894] Users provide feedback on the displayed related product list and community information. The feedback information is sent from the device to the server and stored in Firebase Firestore. The saved feedback information is used for analysis by Google Cloud AI to improve the recommendation algorithm. The input is the feedback information, and the output is an improved recommendation algorithm and improved recommendation accuracy for the next time.

[1895] Step 6:

[1896] The server periodically analyzes the accumulated feedback information and updates the generative AI model via Google Cloud AI, which improves the accuracy of the next hobby and product recommendations and increases user satisfaction. The input is the accumulated feedback information, and the output is the updated generative AI model.

[1897] By following the steps above, users can efficiently discover new hobbies and appropriately obtain product and community information related to those hobbies.

[1898] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1899] This invention relates to a "hobby discovery support system" that helps users who do not have any hobbies to discover new interests and hobbies. In particular, it adds a function to recognize the user's emotional state and recommend appropriate hobbies and related communities based on that emotion. The system also includes a means to collect user emotional feedback and improve the emotion engine.

[1900] User Registration / Login

[1901] Examples:

[1902] A user accesses the system and enters their name, email address, and password into the registration form.

[1903] The terminal transmits the entered user registration information to the server.

[1904] The server stores the received registration information in a database.

[1905] The server will send a confirmation email to the user confirming the registration.

[1906] User Login

[1907] Examples:

[1908] The user enters their email address and password into the login form.

[1909] The terminal transmits the entered login information to the server.

[1910] The server checks the user information in the database and performs authentication.

[1911] If the authentication is successful, the server creates a session and sends a session ID to the terminal.

[1912] User information collection

[1913] Examples:

[1914] Users visit a profile setup page and answer questions about their interests and personality.

[1915] The terminal transmits the collected user information to the server.

[1916] emotion recognition

[1917] Examples:

[1918] Users access the system through an emotion-recognition camera.

[1919] The terminal transmits the user's facial image captured by the camera to the server.

[1920] The server uses an emotion engine to recognize the user's emotions (happiness, sadness, surprise, etc.) from the image.

[1921] The recognized emotion information is stored on the server.

[1922] Hobby recommendations

[1923] Examples:

[1924] The server selects appropriate hobbies using a hobby recommendation engine based on the recognized emotion information and existing profile information.

[1925] The server transmits a list of recommended hobbies to the terminal.

[1926] The terminal displays the recommended hobbies to the user.

[1927] Community Search

[1928] Examples:

[1929] Users select hobbies that interest them within the system.

[1930] The terminal transmits the selected hobby information to the server.

[1931] The server searches a database for community information related to the hobby (online forums, local clubs, etc.).

[1932] Community Recommendations

[1933] Examples:

[1934] The server returns the retrieved community information to the terminal.

[1935] The terminal displays the recommended community information to the user.

[1936] Feedback collection

[1937] Examples:

[1938] Users provide feedback on recommended hobbies and communities.

[1939] The feedback also includes a rating based on the user's emotional state.

[1940] The terminal transmits the feedback information to the server.

[1941] The server stores the feedback information in a database.

[1942] Algorithm Improvement

[1943] Examples:

[1944] The server analyzes the collected feedback.

[1945] The server improves the algorithms of the hobby recommendation engine and the emotion engine based on the analysis results.

[1946] Through this series of steps, the system can effectively recommend hobbies and communities that are suitable for the user and provide more accurate recommendations. By taking the user's emotional state into account, the quality of the recommended hobbies and communities can be further improved, allowing the user to discover new hobbies in a more satisfying way.

[1947] The processing flow will be explained below.

[1948] Step 1: User Registration

[1949] A user accesses the system and enters their name, email address, and password into the registration form.

[1950] The terminal transmits the entered user registration information to the server.

[1951] The server stores the received registration information in a database.

[1952] The server will send a confirmation email to the user confirming the registration.

[1953] Step 2: User Login

[1954] The user enters their email address and password into the login form.

[1955] The terminal transmits the entered login information to the server.

[1956] The server checks the user information in the database and performs authentication.

[1957] If the authentication is successful, the server creates a session and sends a session ID to the terminal.

[1958] Step 3: Collect user information

[1959] Users visit a profile setup page and answer questions about their interests and personality.

[1960] The terminal transmits the collected user information to the server.

[1961] Step 4: Emotion Recognition

[1962] Users access the system through an emotion-recognition camera.

[1963] The terminal transmits the user's facial image captured by the camera to the server.

[1964] The server uses an emotion engine to recognize the user's emotions (happiness, sadness, surprise, etc.) from the image.

[1965] The recognized emotion information is stored on the server.

[1966] Step 5: Hobby recommendation

[1967] The server selects appropriate hobbies using a hobby recommendation engine based on the recognized emotion information and existing profile information.

[1968] The server transmits a list of recommended hobbies to the terminal.

[1969] The terminal displays the recommended hobbies to the user.

[1970] Step 6: Community Search

[1971] Users select hobbies that interest them within the system.

[1972] The terminal transmits the selected hobby information to the server.

[1973] The server searches a database for community information related to the hobby (online forums, local clubs, etc.).

[1974] Step 7: Community Nomination

[1975] The server returns the retrieved community information to the terminal.

[1976] The terminal displays the recommended community information to the user.

[1977] Step 8: Gather feedback

[1978] Users provide feedback on recommended hobbies and communities, including ratings based on the user's emotional state.

[1979] The terminal transmits the feedback information to the server.

[1980] The server stores the feedback information in a database.

[1981] Step 9: Improve the algorithm

[1982] The server analyzes the collected feedback.

[1983] The server improves the algorithms of the hobby recommendation engine and the emotion engine based on the analysis results.

[1984] This detailed processing flow allows users to receive more accurate interest and community recommendations based on their emotional state, and allows us to leverage feedback to continuously improve the algorithm, thereby increasing system performance and user satisfaction.

[1985] Example 2

[1986] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1987] In today's world, it is difficult for users who do not have any hobbies to discover new hobbies or interests that suit them. Furthermore, recommended hobbies and communities may not necessarily be suitable for each user unless the emotional state of each individual user is taken into consideration. Therefore, there is a need for a method to collect users' emotional feedback and use it to improve the system's recommendation accuracy.

[1988] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for accepting user registration information, means for storing the accepted user registration information in a database, means for recognizing the emotional state of the user and recommending appropriate hobbies based on the emotional state and the user's interests and personality, means for searching the database for community information related to the recommended hobbies, and means for collecting feedback from the user and improving the recommendation algorithm and emotion recognition engine based on the feedback. This enables highly accurate recommendation of hobbies and communities based on the user's emotional state.

[1989] "User registration information" refers to personal information such as name, email address, and password that a user enters when accessing the system for the first time.

[1990] A "database" is a data structure that the system uses to store and manage data such as user information, emotional state, and feedback.

[1991] "Emotional state" is information indicating a psychological state such as joy, sadness, surprise, etc., recognized from the user's facial expression.

[1992] "Hobbies" refer to activities or areas in which a user has personal interests or concerns.

[1993] "Recommending" refers to the act of the system presenting hobbies and communities that it deems most suitable based on the user's information.

[1994] "Community information" refers to information such as online forums and physical clubs related to a particular hobby.

[1995] "Feedback" is information such as the user's evaluation and opinions of the recommended hobby or community.

[1996] An "algorithm" is a computational procedure that allows the system to analyze user information and emotional state and recommend optimal hobbies and communities.

[1997] An "emotion recognition engine" is a piece of software that analyzes a user's facial image and other data to recognize their emotional state.

[1998] This invention relates to a "hobby discovery support system" that allows users without hobbies to discover new hobbies and interests that suit them and find communities based on those hobbies. This system has the function of recognizing the user's emotional state and recommending appropriate hobbies and related communities based on that emotion. It can also collect user emotional feedback and use that feedback to improve the system's recommendation algorithm and emotion recognition engine.

[1999] Hardware and Software Configuration

[2000] The main components of the system include:

[2001] Server: Stores and manages user information, emotion information, and feedback information in a database. The server runs an emotion recognition engine and a hobby recommendation engine to provide appropriate information to users.

[2002] Terminal: A device that allows users to input and obtain information. Examples include PCs, smartphones, and tablets.

[2003] Database: A data structure for storing user information, emotion data, hobby information, community information, and feedback information.

[2004] Emotion recognition engine: Software that analyzes a user's facial image to recognize their emotional state. Examples of engines that can be used include Microsoft Azure Face API and Google Cloud Vision.

[2005] Hobby recommendation engine: Software that uses a generative AI model to generate optimal hobbies based on a user's emotional state and profile information.

[2006] Details of system processing

[2007] User Registration / Login

[2008] First, a user accesses the system and enters their name, email address, and password. The device sends this to the server, which stores it in a database. Once registration is complete, a confirmation email is sent. When the user logs in, they enter their email address and password, and the device again sends this to the server. The server compares this with the information in the database, and if authentication is successful, it generates a session ID and sends it to the device.

[2009] User information collection

[2010] Users answer questions about their interests and personality on a profile setup page, and the device sends the collected information to a server, which stores it in a database.

[2011] emotion recognition

[2012] The user provides a facial image through the emotion recognition camera, and the device sends the facial image to the server, which then uses an emotion recognition engine to analyze the user's emotional state. The analysis results are then stored in a database.

[2013] Hobby recommendations

[2014] The server runs a hobby recommendation engine using the latest emotion information and user profile information, and sends the generated hobby list to the terminal and displays it to the user.

[2015] Community Search

[2016] The user selects the hobbies they are interested in from the displayed hobbies, and the terminal sends the selection information to the server, which then searches the database for related community information.

[2017] Community Recommendations

[2018] The retrieved community information is sent to the terminal and displayed to the user.

[2019] Feedback collection

[2020] Users provide feedback on their hobbies and communities, and their devices send it to the server, which stores the feedback information in a database.

[2021] Algorithm Improvement

[2022] The server analyzes the collected feedback and dynamically adjusts the parameters of the recommendation algorithm and emotion recognition engine.

[2023] Examples of concrete examples and prompts

[2024] As a specific example of operation, if a user expresses an interest in "painting," the server will recommend hobbies related to "watercolor painting" and "digital art." If the user is interested in "watercolor painting," the server will recommend community information such as "local watercolor painting clubs" and "online watercolor painting forums."

[2025] Here are some examples of prompts:

[2026] "What new hobbies should we recommend to users when they feel joy?"

[2027] "Where is the best community for users interested in watercolor painting?"

[2028] As described above, the "hobby discovery support system" of the present invention realizes highly accurate recommendation of hobbies and communities that take into account the emotional state of the user.

[2029] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2030] Step 1:

[2031] Enter user registration information

[2032] A user fills in the system's registration form with their name, email address, and password, which serves as input data for the system, and is used to identify the user.

[2033] Step 2:

[2034] Sending user registration information

[2035] The device sends the entered user information to the server in the form of an HTTP POST request. The data is encrypted, thereby protecting the user information.

[2036] Step 3:

[2037] Saving user registration information

[2038] The server validates the received user information and checks for invalid data. After validation is complete, the server stores the information in the "User Information" table in the database. As an output, the server generates a confirmation of successful registration and sends it to the mail server.

[2039] Step 4:

[2040] Enter your user login information

[2041] A user enters an email address and password into a login form. This information is the input data for authentication.

[2042] Step 5:

[2043] Sending user login information

[2044] The device sends the entered login information to the server, where it is also encrypted to ensure data security.

[2045] Step 6:

[2046] User authentication process

[2047] The server searches for the corresponding user information in the "User Information" table in the database and compares it with the entered password. If authentication is successful, the server creates a session, generates a session ID and sends it to the terminal. As an output, the terminal displays the main page to the user.

[2048] Step 7:

[2049] User information collection

[2050] Users access a profile setup page and answer questions about their interests and personality, which are then used as input data for the system's profile data.

[2051] Step 8:

[2052] Sending and storing user information

[2053] The terminal sends the collected user information to the server, which stores it in the "User Profile" table in the database. As an output, the server notifies the user that the profile has been set up.

[2054] Step 9:

[2055] Emotion Recognition Camera Setup

[2056] The user activates the emotion recognition camera and captures facial images through the device, which serve as input data for emotion recognition.

[2057] Step 10:

[2058] Facial image transmission and emotion analysis

[2059] The device sends the captured face image to the server, which then calls an emotion recognition engine (e.g., Microsoft Azure Face API) to analyze the user's emotion from the image. As an output, analyzed emotion information is generated and stored in the "emotion data" table in the database.

[2060] Step 11:

[2061] Running a hobby recommendation engine

[2062] The server retrieves the latest emotion information and user profile information and runs an interest recommendation engine. This engine generates appropriate hobbies using a generative AI model. It uses emotion information and profile information as input and generates a list of hobbies as output.

[2063] Step 12:

[2064] Submit and view recommended hobby lists

[2065] The server sends the recommended hobby list to the terminal, which displays it to the user and provides an interface to attract the user's interest.

[2066] Step 13:

[2067] Start a Community Search

[2068] The user selects a hobby from the displayed hobby list that they are interested in. The terminal then sends information about the selected hobby to the server.

[2069] Step 14:

[2070] Search for related community information

[2071] The server retrieves community information related to the selected hobby from a database, such as online forums and physical club data.

[2072] Step 15:

[2073] Submitting and Viewing Community Information

[2074] The server sends the retrieved community information to the terminal, which displays it to the user, allowing the user to access communities that interest them.

[2075] Step 16:

[2076] Feedback Input

[2077] Users input feedback on the recommended hobbies and communities, which serves as input data for improving the system.

[2078] Step 17:

[2079] Send and save feedback

[2080] The terminal sends the feedback information to the server, which stores it in the "feedback data" table of the database. As an output, the server notifies the user of the confirmation of receipt of the feedback.

[2081] Step 18:

[2082] Algorithm analysis and updates

[2083] The server analyzes the collected feedback and dynamically adjusts the parameters of the recommendation algorithm and emotion recognition engine based on the results. The output is an improved algorithm, which improves the accuracy of recommendations from the next time onwards.

[2084] (Application example 2)

[2085] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2086] Conventional recommendation systems recommend hobbies and products based on a user's static interests and personality information, but they lack the ability to provide real-time recommendations that take into account the user's emotional state. This can result in a failure to meet users' momentary needs and a decrease in satisfaction. Furthermore, there is a lack of concrete measures to improve the shopping experience in physical stores.

[2087] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for accepting user registration information, means for storing the accepted user registration information in a database, means for recommending appropriate hobbies based on the user's interests and personality, means for recognizing the user's emotional state using an emotion recognition camera, means for recommending products based on the recognized emotional information, means for displaying the recommended products on a visual device, and means for collecting feedback from users and improving the recommendation algorithm. This enables real-time product recommendations based on the user's emotional state, thereby improving the quality of shopping experiences in physical stores.

[2088] "User registration information" refers to personal information such as the user's name, email address, and password.

[2089] "Database" refers to a computer system or storage for systematically storing and retrieving information.

[2090] "Appropriate hobbies" refer to activities and interests that are recommended based on a user's interests and personality.

[2091] An "emotion recognition camera" refers to an image processing device that captures a user's facial expressions and analyzes their emotional state.

[2092] "Emotion information" refers to data collected by an emotion-recognition camera about a user's emotional state, such as happiness, sadness, or surprise.

[2093] "Means for recommending products" refers to the function of selecting and presenting appropriate products based on the user's emotional information.

[2094] "Visual device" refers to a device that allows a user to receive information visually, such as smart glasses or a head-mounted display.

[2095] "Feedback" refers to the evaluations and impressions that users give about recommended hobbies or products.

[2096] A "recommendation algorithm" refers to a computational method for selecting appropriate hobbies and products using data such as a user's interests, personality, and emotional state.

[2097] "Brick and mortar store" refers to a retail store that is a physical location where users can visit in person to purchase goods or services.

[2098]

[2099] MODE FOR CARRYING OUT THE INVENTION

[2100] This invention is an emotion recognition-based hobby and product recommendation system that improves the shopping experience in brick-and-mortar stores based on the user's emotional state. The system accepts user registration information, stores it in a database, and recommends hobbies and products based on the user's static interests and personality information, as well as real-time emotional information.

[2101] The server includes the following means:

[2102] Method for accepting user registration information: The user enters personal information into the registration form and sends it from the terminal to the server, whereupon the user's basic information is stored in a database.

[2103] A means for storing the received user registration information in a database: The server systematically stores and manages the received information in a database.

[2104] A means of recommending appropriate hobbies based on the user's interests and personality: The server uses a hobby recommendation engine to select and recommend appropriate hobbies based on the data on interests and personality provided by the user.

[2105] A means of recognizing a user's emotional state using an emotion recognition camera: A camera installed in the device (visual device such as smart glasses) captures the user's face in real time and sends the image to an emotion recognition engine to analyze the emotional information.

[2106] Means for recommending products based on recognized emotional information: Based on the recognized emotional information, a recommendation engine is used to select appropriate products and present them to the user.

[2107] Means for displaying recommended products on a visual device: Product information sent from the server is overlaid on the display of the visual device.

[2108] A means of collecting user feedback and improving the recommendation algorithm: User feedback is sent from the device to the server and used to dynamically adjust the recommendation algorithm.

[2109] Hardware and software used

[2110] Hardware: smart glasses, cameras, servers, visual devices (e.g. Google Glass, Vuzix Blade)

[2111] Software: Emotion recognition module (e.g., OpenCV, dlib, Face++ API), hobby recommendation engine, product recommendation engine, database management system

[2112] Data flow and specific examples

[2113] A user wears smart glasses while shopping in a physical store. The glasses' built-in camera captures the user's facial image and analyzes it using an emotion recognition engine. For example, if the system detects that the user looks slightly tired, it generates a list of products with a refreshing effect and overlays them on the smart glasses' display. This allows the user to visually check recommended products while walking around the store.

[2114] Examples of prompt statements

[2115] "Please recommend products suitable for users who look tired. For example, aroma products or massage machines like the ones below."

[2116] In this way, by providing a specific form for implementing the invention, it becomes possible to recommend products in real time according to the user's emotional state, thereby improving the quality of the shopping experience in physical stores.

[2117] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2118] Step 1:

[2119] The server accepts user registration information. The data to be entered includes name, email address, and password. The user enters this data into the registration form and sends it from the terminal to the server. The server receives this data and stores it systematically in a database.

[2120] Step 2:

[2121] The device collects data to recommend appropriate hobbies based on the user's interests and personality. The user accesses a profile setting page and answers questions about their interests and personality. The collected data is sent from the device to a server, which stores it in a database.

[2122] Step 3:

[2123] The device recognizes the user's emotional state using an emotion recognition camera installed in the smart glasses. The camera captures the user's facial image in real time and sends the image to a server. The server then uses an emotion recognition engine to analyze the user's emotional information from the image and stores the results in a database.

[2124] Step 4:

[2125] The server recommends products based on the recognized emotion information. The user's emotion information and past interest data are used as input. The server's recommendation engine uses this data to create a list of appropriate products and sends the information to the device.

[2126] Step 5:

[2127] The terminal displays the recommended products on a visual device. The recommended products are overlaid on the display of the visual device (e.g., smart glasses). The user can view the recommended products through the visual device while moving around the physical store.

[2128] Step 6:

[2129] Users provide feedback on the recommended products and the system's recommendation accuracy. The feedback includes information about interests and satisfaction, and is sent from the device to the server, which stores it in a database.

[2130] Step 7:

[2131] The server improves the recommendation algorithm based on the collected feedback. It analyzes the feedback data and uses the results to dynamically adjust the recommendation algorithm, thereby improving the accuracy of future recommendations.

[2132] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2133] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2134] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2135] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2136] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2137] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2138] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2139] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2140] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2141] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2142] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2143] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2144] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2145] 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.

[2146] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2147] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2148] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2149] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2150] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2151] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2152] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2153] The following is further disclosed regarding the above embodiment.

[2154] (Claim 1)

[2155] means for accepting user registration information;

[2156] A means for storing the received user registration information in a database;

[2157] A means for recommending appropriate hobbies based on the user's interests and personality;

[2158] A means for searching for community information related to the recommended hobby;

[2159] a means of collecting user feedback and improving the recommendation algorithm;

[2160] A system including:

[2161] (Claim 2)

[2162] 10. The system of claim 1, wherein the recommendation algorithm is dynamically adjusted based on feedback provided by the user.

[2163] (Claim 3)

[2164] 10. The system of claim 1, wherein the system searches and recommends online forums and physical clubs as community information.

[2165] "Example 1"

[2166] (Claim 1)

[2167] means for accepting user registration information;

[2168] A means for storing the received user registration information in a database;

[2169] means for authenticating a user using user authentication information;

[2170] A means for recommending appropriate hobbies based on the user's interests and personality;

[2171] A means for searching for community information related to the recommended hobby;

[2172] a means of collecting user feedback and improving the recommendation algorithm;

[2173] A system including:

[2174] (Claim 2)

[2175] 10. The system of claim 1, wherein the recommendation algorithm is dynamically adjusted based on feedback provided by the user.

[2176] (Claim 3)

[2177] 10. The system of claim 1, wherein the system searches and recommends online forums and physical clubs as community information.

[2178] "Application Example 1"

[2179] (Claim 1)

[2180] means for accepting user registration information;

[2181] A means for storing the received user registration information in a database;

[2182] A means for recommending appropriate hobbies based on the user's interests and personality;

[2183] A means for searching for community information related to the recommended hobby;

[2184] a means of collecting user feedback and improving the recommendation algorithm;

[2185] means for recommending related products based on the user's interests;

[2186] A means of providing users with relevant online forums and nearby club information;

[2187] A system including:

[2188] (Claim 2)

[2189] 10. The system of claim 1, wherein the recommendation algorithm is dynamically adjusted based on feedback provided by the user.

[2190] (Claim 3)

[2191] 10. The system of claim 1, wherein the system searches and recommends online forums and physical clubs as community information.

[2192] (Claim 4)

[2193] 10. The system of claim 1, wherein the system provides related products based on the user's interests.

[2194] "Example 2: Combining Emotion Engines"

[2195] (Claim 1)

[2196] means for accepting user registration information;

[2197] A means for storing the received user registration information in a database;

[2198] means for recognizing a user's emotional state and recommending appropriate hobbies based on the emotional state and the user's interests and personality;

[2199] A means for searching a database for community information related to the recommended hobby;

[2200] means for collecting feedback from users and improving the recommendation algorithm and emotion recognition engine based on the feedback;

[2201] A system including:

[2202] (Claim 2)

[2203] 10. The system of claim 1, wherein the recommendation algorithm and emotion recognition engine are dynamically adjusted based on feedback provided by a user.

[2204] (Claim 3)

[2205] 10. The system of claim 1, wherein the system searches and recommends online forums and physical clubs as community information.

[2206] "Application example 2 when combining emotion engines"

[2207] (Claim 1)

[2208] means for accepting user registration information;

[2209] A means for storing the received user registration information in a database;

[2210] A means for recommending appropriate hobbies based on the user's interests and personality;

[2211] means for recognizing the emotional state of a user using an emotion recognition camera;

[2212] a means for recommending products based on the recognized emotion information;

[2213] means for displaying the recommended products on a visual device;

[2214] A means of collecting user feedback and improving the recommendation algorithm;

[2215] A system including:

[2216] (Claim 2)

[2217] 10. The system of claim 1, wherein the recommendation algorithm is dynamically adjusted based on feedback provided by the user.

[2218] (Claim 3)

[2219] 10. The system of claim 1, wherein the system searches and recommends online forums and physical clubs as community information. [Explanation of symbols]

[2220] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for accepting user registration information; A means for storing the received user registration information in a database; A means for recommending appropriate hobbies based on the user's interests and personality; A means for searching for community information related to the recommended hobby; a means of collecting user feedback and improving the recommendation algorithm; A system including:

2. The system of claim 1 , wherein the recommendation algorithm is dynamically adjusted based on feedback provided by the user.

3. 10. The system of claim 1, wherein the system searches and recommends online forums and physical clubs as community information.

Images