System

Abstract

A system is provided.SOLUTION: Means for inputting attribute information, relationship information, and budget information of a user, means for proposing an appropriate restaurant on the basis of the information input from the user, means for displaying a generated proposed restaurant list to the user, means for generating an invitation message on the basis of the input information of the user, means for displaying the generated invitation message to the user, means for proposing coordination suitable for a date on the basis of the attribute information of the user, means for displaying the generated coordination proposal to the user, and means for collecting feedback on a date action of the user; Means for improving the accuracy of the next suggestion based on the collected feedback data.SELECTED DRAWING: Figure 1

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 recent years, especially due to the COVID-19 pandemic, an increasing number of young people have little dating experience and are unsure of how to ask someone out. Some people are reluctant to seek out information about romance, and others have few friends and find it difficult to seek advice. This creates a demand for specific support to ensure smooth dating. However, existing restaurant recommendation systems and message creation tools do not fully utilize user information and are unable to meet individual needs. [Means for solving the problem]

[0005] The present invention solves the above problem by providing a system including: means for inputting a user's attribute information, relationship information, and budget information; means for suggesting appropriate restaurants based on the information input by the user; means for displaying the generated list of suggested restaurants to the user; means for generating an invitation message based on the user's input information; means for displaying the generated invitation message to the user; means for suggesting outfits suitable for a date based on the user's attribute information; means for displaying the generated outfit suggestions to the user; means for collecting feedback on the user's date actions; and means for improving the accuracy of subsequent suggestions based on the collected feedback data.

[0006] "User" refers to an individual who uses this system to plan a date.

[0007] "Attribute information" refers to information including characteristics of the user and their date, such as personality, hobbies, age, and gender.

[0008] "Relationship information" refers to information that indicates the type of relationship between the user and their date (friends, lovers, colleagues, etc.).

[0009] "Budget information" refers to information indicating the range of amounts a user intends to spend on a date.

[0010] "Restaurant" refers to a facility that provides meals for users to visit on dates.

[0011] "Suggestion list" refers to a list of multiple options that is generated and presented based on the user's criteria.

[0012] "Generative AI" refers to artificial intelligence technology that automatically generates appropriate messages and suggestions based on input information.

[0013] An "invitation message" refers to a message containing text that allows a user to invite someone on a date.

[0014] "Coordination" refers to a combination of clothing and accessories that are appropriate for a date.

[0015] "Feedback" refers to reactions and opinions regarding the Proposal collected from Users.

[0016] "External API" means an application programming interface provided by an external service. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] overview

[0039] The present invention is a system that provides a series of support to ensure a date goes smoothly, suggesting appropriate restaurants and generating invitation messages based on the user's attribute information, relationship information, and budget information, and also proposing outfits for the date.

[0040] System Configuration

[0041] This system consists of a terminal operated by the user, a server, and an external API. The main functions of the system are as follows:

[0042] 1. Enter and save user information

[0043] The user inputs the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc. into the device.

[0044] The terminal sends the input information to the server, and the server stores the received information in a database.

[0045] 2. Restaurant proposals

[0046] The server calls an external API (e.g., restaurant database API) based on the user's input information and generates an appropriate restaurant list.

[0047] A list of suggested restaurants is sent to the terminal and displayed to the user.

[0048] 3. Generate a teaser message

[0049] The server uses AI technology to generate an invitation message based on the user's attribute information and relationship information.

[0050] The message created is sent to the device, and the user can check and edit the message and send it via a messaging app (e.g., LINE).

[0051] 4. Date coordination suggestions

[0052] The server uses an external API (e.g., a fashion database API) to generate outfits that suit the user's style and the date situation.

[0053] The proposed coordinates are sent to the terminal and provided to the user.

[0054] 5. Collect and use feedback

[0055] The server collects feedback from the user after the date has taken place.

[0056] The feedback data will be used to improve the accuracy of proposals from next time onwards.

[0057] Specific examples of program processing

[0058] 1. User registration and login process

[0059] The device prompts the user to enter their username, email address, and password, and sends them to the server.

[0060] The server saves the input data in a database and performs login authentication.

[0061] An authentication token is generated and sent to the terminal.

[0062] 2. Enter your user information

[0063] The user enters the date details into the terminal.

[0064] The device sends the entered details to the server, where they are stored in a database.

[0065] 3. Restaurant proposals

[0066] The server calls an external restaurant database API based on the user's criteria.

[0067] Appropriate restaurants are selected from the returned data and a list of suggestions is generated.

[0068] The suggestion list is sent to the terminal and displayed to the user.

[0069] 4. Generate a teaser message

[0070] The server uses a generation AI to create an invitation message based on user information.

[0071] The message is sent to the device, where the user can review, edit, and send it through the messaging app.

[0072] 5. Date coordination suggestions

[0073] The server calls the ZOZO API and other services based on the user's style information to generate appropriate outfit suggestions.

[0074] The proposed coordinates are sent to the terminal and displayed to the user.

[0075] 6. Final review and feedback

[0076] The user actually goes on a date based on the provided suggestions and sends the results to the server as feedback.

[0077] The server analyzes the collected feedback to improve the accuracy of the next proposal.

[0078] This allows users to receive a range of support regarding dating and specific suggestions to make their date a success.

[0079] The processing flow will be explained below.

[0080] Program processing flow

[0081] 1. User registration and login process

[0082] Step 1:

[0083] The terminal boots up and displays a login or registration page.

[0084] Step 2:

[0085] The user enters their username, email address, and password.

[0086] Step 3:

[0087] The terminal transmits the user's input information to the server.

[0088] Step 4:

[0089] The server receives the input information and stores it in a database.

[0090] Step 5:

[0091] The server generates an authentication token and sends it to the device.

[0092] Step 6:

[0093] The terminal receives the authentication token and displays the login status to the user.

[0094] 2. Enter user information

[0095] Step 1:

[0096] The device displays a screen for the user to enter detailed information about the date.

[0097] Step 2:

[0098] Users enter the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc.

[0099] Step 3:

[0100] The terminal transmits the input information to the server.

[0101] Step 4:

[0102] The server receives the user information and stores it in a database.

[0103] 3. Restaurant proposals

[0104] Step 1:

[0105] The server sets the request parameters based on the user input information.

[0106] Step 2:

[0107] The server sends a request to an external restaurant database API.

[0108] Step 3:

[0109] The server parses the data returned from the API.

[0110] Step 4:

[0111] The server generates an appropriate restaurant list from the analysis results.

[0112] Step 5:

[0113] The restaurant list generated by the server is sent to the terminal and displayed to the user.

[0114] 4. Generate a teaser message

[0115] Step 1:

[0116] The terminal sends a request to the server to create a message.

[0117] Step 2:

[0118] The server uses generation AI to generate messages based on the other person's attributes and relationship.

[0119] Step 3:

[0120] The server generates a message and sends it to the terminal.

[0121] Step 4:

[0122] The terminal displays the generated message to the user.

[0123] Step 5:

[0124] The user reviews and edits the message and sends it using the messaging app.

[0125] 5. Date coordination suggestions

[0126] Step 1:

[0127] The terminal transmits a fashion suggestion request to the server based on the user's attribute information.

[0128] Step 2:

[0129] The server sends a request to an external fashion database API based on the user's style information.

[0130] Step 3:

[0131] The server parses the data returned from the API.

[0132] Step 4:

[0133] The server generates appropriate coordination suggestions from the analysis results.

[0134] Step 5:

[0135] The coordinate proposal generated by the server is sent to the terminal and displayed to the user.

[0136] 6. Final review and feedback

[0137] Step 1:

[0138] The user reviews the provided suggestions and takes the necessary action (reserving a restaurant, sending a message, selecting an outfit).

[0139] Step 2:

[0140] The terminal sends the user's action status to the server.

[0141] Step 3:

[0142] The server tracks and checks the completion status of user actions.

[0143] Step 4:

[0144] The server sends a feedback collection request to the terminal.

[0145] Step 5:

[0146] The user inputs feedback through the terminal and transmits it to the server.

[0147] Step 6:

[0148] The server analyzes and stores the feedback data to improve the accuracy of future proposals.

[0149] Example 1

[0150] 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."

[0151] When planning a date, users must consider various factors (such as the partner's preferences, the relationship, and budget), which is a time-consuming and labor-intensive process. Furthermore, a wide range of support is required, such as choosing the right restaurant, the content of the invitation, and suggestions for appropriate attire for the date. However, there is no system that can provide all of these elements in one place and efficiently support users in planning a date.

[0152] 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.

[0153] In this invention, the server includes means for inputting user attribute information, relationship information, and budget information, means for utilizing an external API to suggest restaurants, means for generating invitation messages using a generative AI model, means for utilizing an external API to suggest outfits, and means for collecting feedback on the user's date actions. This allows the user to receive a series of support through their device, enabling date planning to proceed smoothly and efficiently.

[0154] "User attribute information" is information indicating individual characteristics of a user, such as age, sex, hobbies, preferences, and occupation.

[0155] "Relationship information" is information indicating the relationship between the user and the date (for example, friends, colleagues, lovers, etc.).

[0156] "Budget information" is information that indicates the range of expenses that can be spent on a date.

[0157] The "means for suggesting restaurants" refers to a function for recommending appropriate restaurants based on the conditions entered by the user.

[0158] An "external API" is a means of referring to an interface for connecting with other services or databases.

[0159] The "suggested restaurant list" is a list of restaurants recommended based on the user's criteria.

[0160] "Means for generating an invitation message" refers to means for using generative AI technology to create an invitation message that meets the user's conditions.

[0161] "Means of using an external API to suggest outfits" refers to a function that links with an external fashion database to recommend outfits suitable for a date.

[0162] The "means for collecting feedback on the user's dating actions" refers to a function for collecting feedback such as the results and impressions of a date after the user has completed the date.

[0163] An "authentication token" is a security token issued to maintain a user's logged-in state.

[0164] A "generative AI model" is an artificial intelligence model that generates appropriate responses and suggestions based on user input data and conditions.

[0165] MODE FOR CARRYING OUT THE INVENTION

[0166] This invention is a system that provides a series of support functions to help users efficiently plan dates. The system consists of a terminal operated by the user, a server, and an external API. The main functions of this system include inputting and saving user information, suggesting restaurants, generating invitation messages, suggesting date coordination, and collecting feedback.

[0167] Entering and saving user information

[0168] The device prompts the user for their username, email address, and password, and sends them to the server, which stores the information in a database and authenticates the login.

[0169] The user inputs detailed information such as the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc. into the device, which then sends the information to the server and stores it in a database.

[0170] Restaurant suggestions

[0171] The server calls an external restaurant database API (for example, a restaurant API with a general name) based on the user's input information.

[0172] The server selects appropriate restaurants from the returned data and generates a list of suggestions, which is then sent to the terminal and displayed to the user.

[0173] Generate an invitation message

[0174] The server uses a generative AI model to create an invitation message based on the user's attribute information and relationship information. The name of the specific generative AI model will be generalized, for example, called "message generation AI technology."

[0175] The generated message is sent to the device, where it is edited and confirmed by the user and then sent via a messaging app (e.g., a generic messaging app).

[0176] Date coordination suggestions

[0177] The server calls an external fashion database API (e.g., a fashion API with a general name) based on the user's style information and suggests appropriate outfits.

[0178] The proposed coordinate information is sent to the terminal and displayed to the user.

[0179] Collecting and using feedback

[0180] After the user has gone on a date, the user transmits the results to the server as feedback.

[0181] The server analyzes the collected feedback and stores it in a database to improve the accuracy of suggestions next time.

[0182] Specific examples

[0183] Example of entering and saving user information

[0184] The user logs in as "Taro Tanaka" and enters date details. For example, the user might enter "Purpose of the date: To deepen intimacy," "Partner's attributes: Female in her 20s," "Relationship type: Colleague," "Budget: 3,000 yen," and "Food preference: Japanese food."

[0185] Specific examples of restaurant proposals

[0186] The server retrieves restaurants that meet the user's criteria from the restaurant API and generates a list of suggestions. For example, it suggests three Japanese restaurants.

[0187] Example of creating a teaser message

[0188] The server uses the generative AI model to generate a message such as, "Hello, would you like to go out to dinner with me this weekend? I have a Japanese restaurant I'd like to recommend."

[0189] Specific examples of date coordination suggestions

[0190] The server uses a fashion API to suggest "a casual jacket and chinos" to the user.

[0191] Prompt Sentence Examples

[0192] "My date is with a colleague, my budget is 3000 yen, and I like Japanese food. Please suggest a suitable restaurant."

[0193] "Generate a teaser message based on the user's information. His hobby is the outdoors, and he's been busy lately."

[0194] This allows users to receive a series of support regarding dates through the system, significantly reducing the time and effort required to plan and carry out dates.

[0195] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0196] Program processing flow

[0197] Step 1: User registration and login process

[0198] The user enters their username, email address, and password and sends them to the terminal. Input data: username, email address, password.

[0199] The terminal sends the entered user data to the server. Data processing: Formats it as an HTTP request.

[0200] The server saves the received data in the database and performs login authentication. Data processing: Adds a record to the database and generates an authentication token. Output: Authentication token.

[0201] The terminal receives the authentication token and changes the user status to logged in. Specific operation: "Login successful" is displayed on the screen.

[0202] Step 2: Enter and save your user information

[0203] The user inputs detailed information about the date (purpose, partner's attributes, relationship, budget, food preferences, etc.) into the terminal. Input data: purpose of the date, partner's attributes, relationship, budget, food preferences.

[0204] The device sends the entered details to the server. Data processing: Formatting as an HTTP request.

[0205] The server saves the received data in the database. Data processing: Adds a record to the database. Output: Confirms that the data is saved.

[0206] Step 3: Restaurant proposal

[0207] The server calls an external restaurant database API based on the user's input information. Input data: User's conditions.

[0208] The server selects appropriate restaurants based on the data returned from the API and generates a list of suggested restaurants. Output data: List of suggested restaurants.

[0209] Data processing: Analyze the returned JSON data and extract restaurants that meet the conditions.

[0210] The terminal receives the recommendation list sent from the server and displays it to the user. Specific operation: The "recommended restaurant list" is displayed on the screen.

[0211] Step 4: Create a teaser message

[0212] The server uses a generative AI model to create an invitation message based on user information. Input data: User attribute information and relationship information. Output data: Invitation message.

[0213] Data processing: Generate messages using generative AI models.

[0214] The device receives the message sent from the server and displays it to the user. Specific operation: An "invitation message" is displayed on the screen.

[0215] The user sends the message they have reviewed and edited through a messaging app (e.g., a generic messaging app). Specific behavior: The messaging app is launched and the message is sent.

[0216] Step 5: Proposal for a date outfit

[0217] The server calls an external fashion database API based on the user's style information and suggests appropriate outfits. Input data: User's style information. Output data: Suggested outfits.

[0218] Data processing: Analyze the response data from the fashion API and extract outfits that suit the user.

[0219] The terminal receives the coordination suggestions sent from the server and displays them to the user. Specific operation: "Recommended coordination" is displayed on the screen.

[0220] Step 6: Collect and use feedback

[0221] After the user has gone on a date, the results and impressions are sent to the server as feedback via the device. Input data: Feedback content.

[0222] The server collects and analyzes the feedback. Data processing: Analyzes the feedback data and stores it in a database. Output data: Saves the analysis results and feedback.

[0223] The server analyzes the collected feedback and updates the system to improve the accuracy of the next suggestion. Specific operation: Improved algorithm, improved suggestion accuracy.

[0224] (Application example 1)

[0225] 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."

[0226] In recent years, when planning a date, selecting an appropriate restaurant, writing an invitation message, and suggesting appropriate outfits for the date have become important. However, planning everything on your own is time-consuming, and there is a lack of support systems that can provide effective suggestions. The present invention aims to provide a support system that smoothly plans and executes such dates, allowing users to easily plan dates.

[0227] 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.

[0228] In this invention, the server includes a means for inputting a user's attribute information, relationship information, and budget information, a means for suggesting appropriate restaurants based on the information input by the user, and a means for displaying the generated list of suggested restaurants to the user. This allows the user to easily receive automatic suggestions for restaurants and date plans that suit them. The server also includes a means for generating an invitation message based on the user's input information, a means for displaying the generated invitation message to the user, a means for assisting with restaurant reservations via a smartphone application based on the user information, a means for inputting a prompt into a generation AI model to generate an invitation message, and a means for enabling the generated message to be sent via a messaging app. This allows the user to easily and effectively create and send an invitation message to the other party. The server also includes a means for acquiring the user's style information and suggesting outfits using a fashion database API, and a means for notifying the user's smartphone of the suggested outfits. This allows the user to receive suggestions for the perfect outfit for a date.

[0229] "User attribute information" refers to personal information such as the user's age, gender, hobbies, and preferences.

[0230] "Relationship information" is information that indicates the depth and attributes of the relationship between the user and the date partner.

[0231] "Budget information" is information about the amount of money the user plans to spend on a date.

[0232] The "means for suggesting restaurants" is a function that selects appropriate restaurants based on the user's budget information and preferences and generates a list.

[0233] The "suggested restaurant list" is a list of restaurants generated to be suggested to the user.

[0234] The "means for generating an invitation message" is a function that automatically creates a date invitation message based on the user's attribute information and relationship information.

[0235] The "Fashion Database API" is an external API that provides appropriate fashion coordination based on the user's style information.

[0236] A "generative AI model" is an artificial intelligence algorithm that takes user input and generates appropriate output based on a specific task.

[0237] A "prompt sentence" is an input sentence given to an AI model, an instruction sentence that starts the generation process.

[0238] A "smartphone application" is application software that runs on a mobile device that a user uses on a daily basis.

[0239] "Coordination suggestions" are suggestions for appropriate clothing and accessories that match the user's preferences and the situation of the date.

[0240] MODE FOR CARRYING OUT THE INVENTION

[0241] This invention is a system that supports users in smoothly planning and executing dates. This system is composed of the following components:

[0242] System Configuration

[0243] This system consists of a smartphone operated by the user, a server, and an external API.

[0244] Hardware used

[0245] Smartphone: A device operated by a user

[0246] Server: A central server that processes and stores data

[0247] Software used

[0248] Firebase Authentication: A service for user registration and login authentication

[0249] Google Places API: An external API for retrieving data from the restaurant database

[0250] OpenAI GPT-3: A generative AI model used to generate teaser messages

[0251] ZOZO API: An external database API used to suggest fashion coordination

[0252] Firebase Firestore: A service for storing user information and managing databases

[0253] Specific explanation of the process

[0254] User Registration and Login

[0255] The server receives the username, email address, and password entered by the user on the smartphone, authenticates this information using Firebase Authentication, and stores it in Firebase Firestore. If authentication is successful, the server generates an authentication token and sends it back to the smartphone.

[0256] Entering user information

[0257] Users enter details of their dates (purpose, partner attributes, budget, food preferences, etc.) on their smartphones, and this information is stored in Firebase Firestore in real time.

[0258] Restaurant suggestions

[0259] The server calls the Google Places API based on the user's budget and preferences to retrieve a list of suitable restaurants, which is then filtered and displayed on the user's smartphone as a suggested restaurant list.

[0260] Generate an invitation message

[0261] The server inputs a prompt into the OpenAI GPT-3 generative AI model to generate a teaser message. An example of this prompt is as follows:

[0262] "Hi {name}! How about meeting for dinner next Friday at a new cafe I found? It's called {cafe_name} and has great reviews and a chic atmosphere. How about {time}? I'd love to join you!"

[0263] The generated message is sent to the user's smartphone, where the user can review, edit, and send it via a messaging app.

[0264] Date coordination suggestions

[0265] The server acquires the user's style information and uses the ZOZO API, a fashion database API, to generate appropriate outfit suggestions. These suggestions are then sent to the user's smartphone and displayed to the user.

[0266] Collecting and using feedback

[0267] Users enter their feedback after the date on their smartphone and send it to the server, which stores the feedback data in Firebase Firestore and analyzes it to improve the accuracy of future suggestions.

[0268] This allows users to receive a series of support regarding dating and get specific suggestions to make their date a success.

[0269] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0270] Step 1:

[0271] A user launches the application using a smartphone and registers by entering their username, email address, and password. The entered information is sent to the server, authenticated using Firebase Authentication, and stored in Firebase Firestore. If authentication is successful, the server generates an authentication token and sends it back to the smartphone. The input data is the user's personal information, and the output is an authentication token.

[0272] Step 2:

[0273] Users input date details (purpose, partner attributes, budget, food preferences, etc.) on their smartphones. The input details are sent to the server in real time and stored in Firebase Firestore. The input data is the date details, and the output is the information stored in the database.

[0274] Step 3:

[0275] The server calls the Google Places API based on the budget information and food preferences entered by the user to obtain an appropriate restaurant list. The restaurant data obtained from the API is filtered to generate an appropriate restaurant list. The generated suggested restaurant list is sent to the smartphone and displayed to the user. The input data is the user's conditions and restaurant data from the API, and the output is the suggested restaurant list.

[0276] Step 4:

[0277] The server inputs a prompt into OpenAI GPT-3 based on the user's attribute information and relationship information to generate an invitation message. The generated message is sent to the smartphone. The user can review and edit the message and send it via a messaging app such as LINE. The input data are the user's attribute information, relationship information, and prompt, and the output is the generated invitation message. Specific examples of prompts are as follows:

[0278] "Hi {name}! How about meeting for dinner next Friday at a new cafe I found? It's called {cafe_name} and has great reviews and a chic atmosphere. How about {time}? I'd love to join you!"

[0279] Step 5:

[0280] The server acquires the user's style information and uses a fashion database API (e.g., the ZOZO API) to suggest outfits. The suggested outfits are sent to the user's smartphone and notified to the user. The input data is the user's style information and data from the fashion database, and the output is the suggested outfits.

[0281] Step 6:

[0282] After a date, users send their feedback on the date to the server via their smartphone. The server stores this feedback data in Firebase Firestore and analyzes it to improve the accuracy of suggestions for the next date. The input data is the user's feedback, and the output is the analyzed data and improvements to the accuracy of suggestions.

[0283] 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.

[0284] overview

[0285] This invention is a system that provides a series of support to help dates proceed smoothly, and by combining the user's attribute information, relationship information, and budget information with an emotion engine that recognizes the user's emotional state, it makes more personalized suggestions and generates messages.

[0286] System configuration

[0287] This system consists of a terminal operated by the user, a server, and an external API. It also includes an emotion engine that recognizes the user's emotions. The main functions of the system are as follows:

[0288] 1. Enter and save user information

[0289] The user inputs the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc. into the device.

[0290] The terminal sends the input information to the server, and the server stores the received information in a database.

[0291] 2. Emotion Engine Recognition

[0292] The device uses a camera and microphone to analyze the user's emotional state using an emotion engine.

[0293] The server receives the analysis results from the emotion engine and stores them in a database.

[0294] 3. Restaurant proposals

[0295] The server sets request parameters based on the user's input information and emotional state.

[0296] The server sends a request to an external restaurant database API.

[0297] An appropriate restaurant list is generated from the returned data and optimized according to the user's emotional state.

[0298] A list of suggested restaurants is sent to the terminal and displayed to the user.

[0299] 4. Generate a teaser message

[0300] The server uses generative AI technology to generate an invitation message based on the user's attribute information, relationship information, and emotional state.

[0301] The generated message is sent to the device, where the user can review and edit it and send it through the messaging app.

[0302] 5. Date coordination suggestions

[0303] The server uses an external fashion database API to generate outfits that suit the user's style, date situation, and emotional state.

[0304] The proposed coordinates are sent to the terminal and provided to the user.

[0305] 6. Collect and use feedback

[0306] The server collects feedback from the user after the date has taken place.

[0307] The feedback data will be used to improve the accuracy of proposals from next time onwards.

[0308] Specific examples of program processing

[0309] 1. User registration and login process

[0310] The device prompts the user to enter their username, email address, and password, and sends them to the server.

[0311] The server receives the input data and stores it in a database.

[0312] An authentication token is generated and sent to the terminal.

[0313] 2. Enter your user information

[0314] The user enters the date details into the terminal.

[0315] The device sends the entered details to the server and stores them in a database.

[0316] 3. Emotion Engine Recognition

[0317] The device uses a camera and microphone to have the emotion engine analyze the user's emotional state.

[0318] The server receives the analysis results from the emotion engine and stores them in a database.

[0319] 4. Restaurant Proposals

[0320] The server calls an external restaurant database API based on the user's conditions and emotional state.

[0321] An appropriate restaurant list is generated from the returned data and optimized according to the user's emotional state.

[0322] The suggestion list is sent to the terminal and displayed to the user.

[0323] 5. Generate a teaser message

[0324] The server uses a generation AI to create an invitation message based on the user's information and emotional state.

[0325] The message is sent to the device, where the user can review, edit, and send it through the messaging app.

[0326] 6. Date coordination suggestions

[0327] The server calls a fashion database API based on the user's style information and emotional state, and generates appropriate coordination suggestions.

[0328] The proposed coordinates are sent to the terminal and displayed to the user.

[0329] 7. Final review and feedback

[0330] The user goes on a date based on the provided suggestions and transmits the results to the server as feedback.

[0331] The server analyzes and stores the collected feedback to improve the accuracy of the next suggestion.

[0332] This allows users to receive a range of dating support and specific suggestions tailored to their emotional state.

[0333] The processing flow will be explained below.

[0334] overview

[0335] This invention is a system that provides a series of support to help dates proceed smoothly, and by combining the user's attribute information, relationship information, and budget information with an emotion engine that recognizes the user's emotional state, it makes more personalized suggestions and generates messages.

[0336] System configuration

[0337] This system consists of a terminal operated by the user, a server, and an external API. It also includes an emotion engine that recognizes the user's emotions. The main functions of the system are as follows:

[0338] 1. User registration and login process

[0339] Step 1:

[0340] The device launches the application and displays the login or registration page.

[0341] Step 2:

[0342] The user enters their username, email address, and password.

[0343] Step 3:

[0344] The terminal transmits the input information to the server.

[0345] Step 4:

[0346] The server stores the received information in a database.

[0347] Step 5:

[0348] The server generates an authentication token and sends it to the device.

[0349] Step 6:

[0350] The terminal receives the authentication token and displays the login status to the user.

[0351] 2. Enter user information

[0352] Step 1:

[0353] The terminal displays a screen for the user to enter detailed date information.

[0354] Step 2:

[0355] Users enter the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc.

[0356] Step 3:

[0357] The terminal transmits the input information to the server.

[0358] Step 4:

[0359] The server stores the received information in a database.

[0360] 3. Emotion Engine Recognition

[0361] Step 1:

[0362] The device will ask the user for permission to access the camera and microphone.

[0363] Step 2:

[0364] The user allows camera and microphone access.

[0365] Step 3:

[0366] The device uses a camera and microphone to record the user's facial expressions and voice and transmits them to the emotion engine.

[0367] Step 4:

[0368] The emotion engine analyzes the user's emotional state and sends the results to the server.

[0369] Step 5:

[0370] The server stores the analysis results from the emotion engine in a database.

[0371] 4. Restaurant Proposals

[0372] Step 1:

[0373] The server sets the request parameters based on the user's details and emotional state.

[0374] Step 2:

[0375] The server sends a request to an external restaurant database API.

[0376] Step 3:

[0377] The server parses the data returned from the API.

[0378] Step 4:

[0379] The server generates an appropriate restaurant list from the analysis results and optimizes it according to the user's emotional state.

[0380] Step 5:

[0381] The restaurant list generated by the server is sent to the terminal and displayed to the user.

[0382] 5. Generate a teaser message

[0383] Step 1:

[0384] The terminal sends a request to the server to create a message.

[0385] Step 2:

[0386] The server uses generation AI to generate messages based on the user's attribute information, relationship information, and emotional state.

[0387] Step 3:

[0388] The server generates a message and sends it to the terminal.

[0389] Step 4:

[0390] The terminal displays the generated message to the user.

[0391] Step 5:

[0392] The user reviews and edits the message and sends it using the messaging app.

[0393] 6. Date coordination suggestions

[0394] Step 1:

[0395] The terminal transmits a fashion suggestion request to the server based on the user's attribute information.

[0396] Step 2:

[0397] The server sends a request to an external fashion database API based on the user's style information and emotional state.

[0398] Step 3:

[0399] The server parses the data returned from the API.

[0400] Step 4:

[0401] The server generates appropriate coordination suggestions from the analysis results and optimizes them based on the emotional state.

[0402] Step 5:

[0403] The coordinate proposal generated by the server is sent to the terminal and displayed to the user.

[0404] 7. Final review and feedback

[0405] Step 1:

[0406] The user reviews the provided suggestions and takes the necessary action (reserving a restaurant, sending a message, selecting an outfit).

[0407] Step 2:

[0408] The terminal sends the user's action status to the server.

[0409] Step 3:

[0410] The server tracks and checks the completion status of user actions.

[0411] Step 4:

[0412] The server sends a feedback collection request to the terminal.

[0413] Step 5:

[0414] The user inputs feedback through the terminal and transmits it to the server.

[0415] Step 6:

[0416] The server analyzes and stores the feedback data to improve the accuracy of the next proposal.

[0417] Example 2

[0418] 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."

[0419] When planning a date, there is a lack of personalized suggestions that take into account the user's attributes, relationship information, budget information, and even emotional state. Furthermore, since there is no systematic support that integrates multiple elements, it is difficult for users to plan the best date.

[0420] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0421] In this invention, the server includes means for inputting user attribute information, relationship information, and budget information, means for suggesting appropriate restaurants based on the information input by the user and the user's emotional state, and means for generating an invitation message based on the input information and the user's emotional state, thereby enabling the user to easily plan an optimal date taking into account multiple factors including the attribute information and the user's emotional state.

[0422] "User attribute information" is data that indicates individual characteristics and features of a user, and includes age, gender, occupation, hobbies, and the like.

[0423] "Relationship information" is data indicating the relationship the user has with the person they are dating, and includes friends, business partners, lovers, family, and the like.

[0424] "Budget information" is data regarding the amount of money a user wants to spend on a date.

[0425] "Emotional state" is data that indicates the user's current emotions and moods, and includes positive, negative, neutral, and the like.

[0426] The "suggested restaurant list" is a list of restaurants suitable for a date, generated by the server based on the user's input information and emotional state.

[0427] An "invitation message" is a message for inviting someone on a date, generated using AI generation technology based on the user's attribute information and emotional state.

[0428] "Coordination suggestions" are data that suggest outfits suitable for a date based on the user's style information and emotional state.

[0429] "Server" means a computer system that stores and analyzes data and communicates with external APIs.

[0430] A "terminal" is a device operated by a user, such as a computer, smartphone, or tablet.

[0431] MODE FOR CARRYING OUT THE INVENTION

[0432] The present invention is a system that provides personalized date plans. This system can determine the user's emotional state in addition to user attribute information, relationship information, and budget information, and make appropriate suggestions. The system is primarily composed of a server, a terminal, and an external API. The operation of the system is described in detail below.

[0433] User registration and login process

[0434] The first thing a user does is enter their username, email address, and password into the device, which is then sent to the server, where it is stored in a database and an authentication token is generated and sent to the device.

[0435] Entering user information

[0436] Users select from a list of dating purposes and enter detailed information such as the partner's attributes, relationship status, budget, food preferences, etc. This information is sent from the device to the server and stored in a database.

[0437] Emotion Engine Recognition

[0438] The user's emotional state is collected by showing their facial expressions to the camera or speaking into the microphone. The device sends these images and sounds to the emotion engine for analysis. The analysis results are sent to the server and stored in a database.

[0439] Restaurant suggestions

[0440] The server sets request parameters based on the user's input information and emotional state, and sends a request to an external restaurant database API. It generates an appropriate restaurant list from the returned data and optimizes the list based on the user's emotional state. The optimized restaurant list is sent to the device and displayed to the user.

[0441] Generate an invitation message

[0442] The server uses generative AI technology to create an invitation message based on the user's attribute information, relationship information, and emotional state. The generated message is sent to the device, where the user can review and edit it and send it through the messaging app.

[0443] Date coordination suggestions

[0444] The server generates outfit suggestions based on the user's style information and emotional state using an external fashion database API, and the resulting outfit suggestions are sent to the device and provided to the user.

[0445] Final review and feedback gathering

[0446] After a date, users input their satisfaction and areas for improvement into their device and send the feedback data to the server, which collects and stores the feedback data and uses it to improve the accuracy of future suggestions.

[0447] Examples of concrete examples and prompts

[0448] For example, a user might use the system as follows:

[0449] 1. A user accesses the system and creates an account by entering a username, email address, and password.

[0450] 2. The user enters the details of the date (e.g., budget is under 5,000 yen, food preference is Italian).

[0451] 3. The user smiles at the camera, and the emotion engine recognizes "positive emotion."

[0452] 4. The server generates a list of Italian restaurant suggestions and optimizes it according to the user's emotional state.

[0453] 5. The server uses a generation AI to generate an invitation message saying, "Would you like to join us for some Italian food this weekend?"

[0454] 6. The server suggests fashion coordination that matches the user's taste.

[0455] 7. After the date, the user sends feedback saying, "The date was great, but the restaurant was booked and we had to wait a long time."

[0456] Examples of prompts are:

[0457] 1. "User information: Name = Yamada Taro, Budget = Under 5,000 yen, Food preference = Italian food, Relationship = Friend"

[0458] 2. "Emotional state: Positive"

[0459] 3. "Generate a teaser message."

[0460] In this way, the system can propose personalized date plans to users and provide optimal restaurant recommendations and fashion coordination based on the user's emotional state.

[0461] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0462] The flow of this system's program processing

[0463] Step 1: User registration and login process

[0464] Input: Username, Email Address, Password

[0465] Operation:

[0466] The user enters their username, email address, and password on the device.

[0467] The terminal transmits this information to the server.

[0468] The server receives the transmitted user information and stores it in a database.

[0469] The server generates an authentication token and sends it to the device.

[0470] Output: Authentication token

[0471] Step 2: Enter your user information

[0472] Input: purpose of date, partner's attributes, relationship status, budget, food preferences

[0473] Operation:

[0474] The user inputs the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc. into the device.

[0475] The terminal sends the entered details to the server.

[0476] The server stores the submitted details in a database.

[0477] Output: Saved user details

[0478] Step 3: Recognizing the Emotion Engine

[0479] Input: Video data, audio data

[0480] Operation:

[0481] The user shows their facial expressions to the camera and speaks into the microphone.

[0482] The device collects video and audio and sends it to the emotion engine.

[0483] The emotion engine analyzes video and audio to identify the user's emotional state.

[0484] The server stores the analysis results received from the emotion engine in a database.

[0485] Output: User's emotional state

[0486] Step 4: Restaurant proposal

[0487] Input: User details, emotional state

[0488] Operation:

[0489] The server sets request parameters based on the user's input information and emotional state.

[0490] The server sends a request to an external restaurant database API.

[0491] The server receives the data returned from the external restaurant database API.

[0492] The server optimizes the restaurant list based on the user's emotional state.

[0493] The server transmits the optimized restaurant list to the terminal.

[0494] Output: A list of suggested restaurants

[0495] Step 5: Create a teaser message

[0496] Input: User information, emotional state

[0497] Operation:

[0498] The server creates a prompt for the generative AI model to use.

[0499] The server sends a prompt to the generation AI model, which generates an invitation message.

[0500] The server sends the generated message to the terminal.

[0501] The terminal displays the message to the user, who can then view and edit it.

[0502] The user sends the final message through a messaging app.

[0503] Output: Teaser message

[0504] Step 6: Proposal for a date outfit

[0505] Input: User style information, emotional state

[0506] Operation:

[0507] The server sends a request to an external fashion database API based on the user's style information and emotional state.

[0508] The server generates coordination suggestions based on the data returned from the external fashion database API.

[0509] The server transmits the generated coordination proposal to the terminal.

[0510] The terminal displays the coordination suggestions to the user.

[0511] Output: Date coordination suggestions

[0512] Step 7: Final review and feedback gathering

[0513] Input: Post-date feedback

[0514] Operation:

[0515] The user enters their satisfaction and areas for improvement after the date into the device.

[0516] The terminal transmits the feedback data to the server.

[0517] The server stores the feedback data in a database.

[0518] The server analyzes the feedback data and uses it to improve the accuracy of future proposals.

[0519] Output: Feedback data

[0520] In this way, at each processing step of the system, specific processes such as user input, data collection, analysis, and proposal generation are performed, allowing users to receive personalized dating support.

[0521] (Application example 2)

[0522] 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."

[0523] Conventional dating support systems handle basic data such as user attribute information, relationship information, and budget information, but do not take the user's emotional state into account, resulting in a lack of personalized suggestions and making it difficult to provide optimal suggestions.The present invention analyzes the user's emotional state and reflects this in the suggestions, enabling more personalized date plans to be proposed, thereby improving user satisfaction.

[0524] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0525] In this invention, the server includes means for recognizing a user's emotional state using an emotion engine that analyzes the user's emotional state, means for storing the analysis results from the emotion engine in a database, means for optimizing a suggested restaurant list based on the user's emotional state, and means for generating coordination suggestions based on the user's style information and emotional state using a fashion database API, thereby enabling personalized suggestions based on the user's emotions.

[0526] "User attribute information" is data that indicates personal characteristics of a user, such as age, gender, and hobbies.

[0527] "Relationship information" is data indicating the relationship between the user and the dater (e.g., first meeting, long-term relationship, friends).

[0528] "Budget information" is data indicating the amount of money a user can spend on a date.

[0529] An "emotion engine" is software or an algorithm that analyzes data such as a user's facial expressions and voice, and recognizes their emotional state (happiness, sadness, tension, etc.).

[0530] The "suggested restaurant list" is a list of restaurants selected based on the user's input information and emotional state.

[0531] An "invitation message" is a message created for the purpose of inviting someone on a date.

[0532] "Coordination suggestions" are suggestions for combinations of clothing, accessories, etc. that are suited to the user's style information and emotional state.

[0533] "Feedback data" refers to information such as evaluations and opinions provided by users after a date, and is data that is used to improve the accuracy of suggestions from the next date onwards.

[0534] The "restaurant database API" is an interface for communicating with an external restaurant information database and obtaining restaurant information.

[0535] "Generative AI technology" is an artificial intelligence technology that generates natural language based on large amounts of data.

[0536] The "Fashion Database API" is an interface for communicating with external fashion information databases and obtaining information on fashion items.

[0537] This invention is a system for supporting users in dating, and is composed of the following main elements and procedures. Specifically, the system processes and shares data while communicating with the server, terminals, and users, to propose date plans and collect feedback.

[0538] 1. Enter and save user information

[0539] The user inputs attribute information such as the purpose of the date, relationship status, budget, and food preferences from the terminal. The terminal sends the input information to the server, which then stores the information in a database.

[0540] 2. Emotion Engine Recognition

[0541] The user analyzes their emotional state using the smartphone's camera and microphone. The user's facial expressions and voice are then analyzed by the emotion engine, and their emotional state is recognized. The analysis results are sent to the server and stored in a database.

[0542] 3. Restaurant proposals and optimization

[0543] The server calls an external restaurant database API based on the user's input information and emotional state. Based on the returned information, it generates a restaurant list that takes into account the analysis results of the emotion engine and displays it to the user. This allows it to suggest restaurants that best suit the user's emotional state.

[0544] 4. Generate a teaser message

[0545] Generative AI technology (e.g., natural language generation models) is used to generate invitation messages based on the user's attributes, relationship information, and emotional state. The generated messages are sent to the device, where the user can review and edit them before sending them through a messaging app.

[0546] 5. Date coordination suggestions

[0547] The server calls a fashion database API based on the user's style information, date situation, and emotional state to generate outfit suggestions, which are then sent to the device and displayed to the user.

[0548] 6. Collect and use feedback

[0549] After the date, users provide feedback on the application, which the server analyzes and stores in a database to improve the accuracy of future suggestions.

[0550] Specific examples

[0551] Software and hardware used

[0552] Emotion engine: Microsoft Azure Face API and Amazon Rekognition

[0553] Restaurant database API: Google Places API, Tabelog API

[0554] Natural Language Generation Technology: OpenAI's GPT-3

[0555] Fashion database API: Rakuten Fashion API

[0556] Device: Smartphone

[0557] Server: General web server

[0558] Examples of prompt statements

[0559] The purpose of the date is an anniversary, the relationship is long-term, and the user's emotional state is joy. Based on this information, please generate an invitation message to send to your partner.

[0560] In this way, the system of the present invention can take into account the user's emotional state, thereby proposing more personalized date plans and improving user satisfaction.

[0561] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0562] Step 1:

[0563] Input: The user enters demographic information such as the purpose of the date, relationship status, budget, and food preferences.

[0564] How it works: The device collects information through a user input form and sends it to the server.

[0565] Output: The server stores the received information in a database.

[0566] Step 2:

[0567] Input: Video and audio data from the user's camera and microphone.

[0568] How it works: The device uses the camera and microphone to send data to the emotion engine, which analyzes the user's emotional state. The server then stores the analysis results in a database.

[0569] Output: An analysis of the user's emotional state.

[0570] Step 3:

[0571] Input: User demographic information, relationship information, budget information, and emotional state.

[0572] How it works: The server calls an external restaurant database API to retrieve a list of appropriate restaurants based on the input information. The retrieved list is then optimized based on the user's emotional state.

[0573] Output: A list of restaurants that fit your emotional state.

[0574] Step 4:

[0575] Input: User attribute information, relationship information, and emotional state.

[0576] How it works: The server uses generative AI technology to generate a prompt. For example, "The purpose of the date is an anniversary, the relationship is long-term, and the user's emotional state is joy. Based on this information, please generate an invitation message to send to the other person."

[0577] Output: The generated teaser message.

[0578] Step 5:

[0579] Input: User's demographic information, style information, and emotional state.

[0580] How it works: The server calls the fashion database API and generates outfit suggestions suitable for the user.

[0581] Output: Coordination suggestions.

[0582] Step 6:

[0583] Input: Feedback information entered by the user after the date.

[0584] How it works: The server collects feedback information and stores it in a database to improve the accuracy of suggestions next time.

[0585] Output: Feedback data is accumulated to improve the accuracy of future suggestions.

[0586] 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.

[0587] 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.

[0588] 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.

[0589] [Second embodiment]

[0590] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0591] 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.

[0592] 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).

[0593] 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.

[0594] 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.

[0595] 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).

[0596] 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.

[0597] 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.

[0598] 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.

[0599] 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.

[0600] 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.

[0601] 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."

[0602] overview

[0603] The present invention is a system that provides a series of support to ensure a date goes smoothly, suggesting appropriate restaurants and generating invitation messages based on the user's attribute information, relationship information, and budget information, and also proposing outfits for the date.

[0604] System Configuration

[0605] This system consists of a terminal operated by the user, a server, and an external API. The main functions of the system are as follows:

[0606] 1. Enter and save user information

[0607] The user inputs the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc. into the device.

[0608] The terminal sends the input information to the server, and the server stores the received information in a database.

[0609] 2. Restaurant proposals

[0610] The server calls an external API (e.g., restaurant database API) based on the user's input information and generates an appropriate restaurant list.

[0611] A list of suggested restaurants is sent to the terminal and displayed to the user.

[0612] 3. Generate a teaser message

[0613] The server uses AI technology to generate an invitation message based on the user's attribute information and relationship information.

[0614] The message created is sent to the device, and the user can check and edit the message and send it via a messaging app (e.g., LINE).

[0615] 4. Date coordination suggestions

[0616] The server uses an external API (e.g., a fashion database API) to generate outfits that suit the user's style and the date situation.

[0617] The proposed coordinates are sent to the terminal and provided to the user.

[0618] 5. Collect and use feedback

[0619] The server collects feedback from the user after the date has taken place.

[0620] The feedback data will be used to improve the accuracy of proposals from next time onwards.

[0621] Specific examples of program processing

[0622] 1. User registration and login process

[0623] The device prompts the user to enter their username, email address, and password, and sends them to the server.

[0624] The server saves the input data in a database and performs login authentication.

[0625] An authentication token is generated and sent to the terminal.

[0626] 2. Enter your user information

[0627] The user enters the date details into the terminal.

[0628] The device sends the entered details to the server, where they are stored in a database.

[0629] 3. Restaurant proposals

[0630] The server calls an external restaurant database API based on the user's criteria.

[0631] Appropriate restaurants are selected from the returned data and a list of suggestions is generated.

[0632] The suggestion list is sent to the terminal and displayed to the user.

[0633] 4. Generate a teaser message

[0634] The server uses a generation AI to create an invitation message based on user information.

[0635] The message is sent to the device, where the user can review, edit, and send it through the messaging app.

[0636] 5. Date coordination suggestions

[0637] The server calls the ZOZO API and other services based on the user's style information to generate appropriate outfit suggestions.

[0638] The proposed coordinates are sent to the terminal and displayed to the user.

[0639] 6. Final review and feedback

[0640] The user actually goes on a date based on the provided suggestions and sends the results to the server as feedback.

[0641] The server analyzes the collected feedback to improve the accuracy of the next proposal.

[0642] This allows users to receive a range of support regarding dating and specific suggestions to make their date a success.

[0643] The processing flow will be explained below.

[0644] Program processing flow

[0645] 1. User registration and login process

[0646] Step 1:

[0647] The terminal boots up and displays a login or registration page.

[0648] Step 2:

[0649] The user enters their username, email address, and password.

[0650] Step 3:

[0651] The terminal transmits the user's input information to the server.

[0652] Step 4:

[0653] The server receives the input information and stores it in a database.

[0654] Step 5:

[0655] The server generates an authentication token and sends it to the device.

[0656] Step 6:

[0657] The terminal receives the authentication token and displays the login status to the user.

[0658] 2. Enter user information

[0659] Step 1:

[0660] The device displays a screen for the user to enter detailed information about the date.

[0661] Step 2:

[0662] Users enter the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc.

[0663] Step 3:

[0664] The terminal transmits the input information to the server.

[0665] Step 4:

[0666] The server receives the user information and stores it in a database.

[0667] 3. Restaurant proposals

[0668] Step 1:

[0669] The server sets the request parameters based on the user input information.

[0670] Step 2:

[0671] The server sends a request to an external restaurant database API.

[0672] Step 3:

[0673] The server parses the data returned from the API.

[0674] Step 4:

[0675] The server generates an appropriate restaurant list from the analysis results.

[0676] Step 5:

[0677] The restaurant list generated by the server is sent to the terminal and displayed to the user.

[0678] 4. Generate a teaser message

[0679] Step 1:

[0680] The terminal sends a request to the server to create a message.

[0681] Step 2:

[0682] The server uses generation AI to generate messages based on the other person's attributes and relationship.

[0683] Step 3:

[0684] The server generates a message and sends it to the terminal.

[0685] Step 4:

[0686] The terminal displays the generated message to the user.

[0687] Step 5:

[0688] The user reviews and edits the message and sends it using the messaging app.

[0689] 5. Date coordination suggestions

[0690] Step 1:

[0691] The terminal transmits a fashion suggestion request to the server based on the user's attribute information.

[0692] Step 2:

[0693] The server sends a request to an external fashion database API based on the user's style information.

[0694] Step 3:

[0695] The server parses the data returned from the API.

[0696] Step 4:

[0697] The server generates appropriate coordination suggestions from the analysis results.

[0698] Step 5:

[0699] The coordinate proposal generated by the server is sent to the terminal and displayed to the user.

[0700] 6. Final review and feedback

[0701] Step 1:

[0702] The user reviews the provided suggestions and takes the necessary action (reserving a restaurant, sending a message, selecting an outfit).

[0703] Step 2:

[0704] The terminal sends the user's action status to the server.

[0705] Step 3:

[0706] The server tracks and checks the completion status of user actions.

[0707] Step 4:

[0708] The server sends a feedback collection request to the terminal.

[0709] Step 5:

[0710] The user inputs feedback through the terminal and transmits it to the server.

[0711] Step 6:

[0712] The server analyzes and stores the feedback data to improve the accuracy of future proposals.

[0713] Example 1

[0714] 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."

[0715] When planning a date, users must consider various factors (such as the partner's preferences, the relationship, and budget), which is a time-consuming and labor-intensive process. Furthermore, a wide range of support is required, such as choosing the right restaurant, the content of the invitation, and suggestions for appropriate attire for the date. However, there is no system that can provide all of these elements in one place and efficiently support users in planning a date.

[0716] 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.

[0717] In this invention, the server includes means for inputting user attribute information, relationship information, and budget information, means for utilizing an external API to suggest restaurants, means for generating invitation messages using a generative AI model, means for utilizing an external API to suggest outfits, and means for collecting feedback on the user's date actions. This allows the user to receive a series of support through their device, enabling date planning to proceed smoothly and efficiently.

[0718] "User attribute information" is information indicating individual characteristics of a user, such as age, sex, hobbies, preferences, and occupation.

[0719] "Relationship information" is information indicating the relationship between the user and the date (for example, friends, colleagues, lovers, etc.).

[0720] "Budget information" is information that indicates the range of expenses that can be spent on a date.

[0721] The "means for suggesting restaurants" refers to a function for recommending appropriate restaurants based on the conditions entered by the user.

[0722] An "external API" is a means of referring to an interface for connecting with other services or databases.

[0723] The "suggested restaurant list" is a list of restaurants recommended based on the user's criteria.

[0724] "Means for generating an invitation message" refers to means for using generative AI technology to create an invitation message that meets the user's conditions.

[0725] "Means of using an external API to suggest outfits" refers to a function that links with an external fashion database to recommend outfits suitable for a date.

[0726] The "means for collecting feedback on the user's dating actions" refers to a function for collecting feedback such as the results and impressions of a date after the user has completed the date.

[0727] An "authentication token" is a security token issued to maintain a user's logged-in state.

[0728] A "generative AI model" is an artificial intelligence model that generates appropriate responses and suggestions based on user input data and conditions.

[0729] MODE FOR CARRYING OUT THE INVENTION

[0730] This invention is a system that provides a series of support functions to help users efficiently plan dates. The system consists of a terminal operated by the user, a server, and an external API. The main functions of this system include inputting and saving user information, suggesting restaurants, generating invitation messages, suggesting date coordination, and collecting feedback.

[0731] Entering and saving user information

[0732] The device prompts the user for their username, email address, and password, and sends them to the server, which stores the information in a database and authenticates the login.

[0733] The user inputs detailed information such as the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc. into the device, which then sends the information to the server and stores it in a database.

[0734] Restaurant suggestions

[0735] The server calls an external restaurant database API (for example, a restaurant API with a general name) based on the user's input information.

[0736] The server selects appropriate restaurants from the returned data and generates a list of suggestions, which is then sent to the terminal and displayed to the user.

[0737] Generate an invitation message

[0738] The server uses a generative AI model to create an invitation message based on the user's attribute information and relationship information. The name of the specific generative AI model will be generalized, for example, called "message generation AI technology."

[0739] The generated message is sent to the device, where it is edited and confirmed by the user and then sent via a messaging app (e.g., a generic messaging app).

[0740] Date coordination suggestions

[0741] The server calls an external fashion database API (e.g., a fashion API with a general name) based on the user's style information and suggests appropriate outfits.

[0742] The proposed coordinate information is sent to the terminal and displayed to the user.

[0743] Collecting and using feedback

[0744] After the user has gone on a date, the user transmits the results to the server as feedback.

[0745] The server analyzes the collected feedback and stores it in a database to improve the accuracy of suggestions next time.

[0746] Specific examples

[0747] Example of entering and saving user information

[0748] The user logs in as "Taro Tanaka" and enters date details. For example, the user might enter "Purpose of the date: To deepen intimacy," "Partner's attributes: Female in her 20s," "Relationship type: Colleague," "Budget: 3,000 yen," and "Food preference: Japanese food."

[0749] Specific examples of restaurant proposals

[0750] The server retrieves restaurants that meet the user's criteria from the restaurant API and generates a list of suggestions. For example, it suggests three Japanese restaurants.

[0751] Example of creating a teaser message

[0752] The server uses the generative AI model to generate a message such as, "Hello, would you like to go out to dinner with me this weekend? I have a Japanese restaurant I'd like to recommend."

[0753] Specific examples of date coordination suggestions

[0754] The server uses a fashion API to suggest "a casual jacket and chinos" to the user.

[0755] Prompt Sentence Examples

[0756] "My date is with a colleague, my budget is 3000 yen, and I like Japanese food. Please suggest a suitable restaurant."

[0757] "Generate a teaser message based on the user's information. His hobby is the outdoors, and he's been busy lately."

[0758] This allows users to receive a series of support regarding dates through the system, significantly reducing the time and effort required to plan and carry out dates.

[0759] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0760] Program processing flow

[0761] Step 1: User registration and login process

[0762] The user enters their username, email address, and password and sends them to the terminal. Input data: username, email address, password.

[0763] The terminal sends the entered user data to the server. Data processing: Formats it as an HTTP request.

[0764] The server saves the received data in the database and performs login authentication. Data processing: Adds a record to the database and generates an authentication token. Output: Authentication token.

[0765] The terminal receives the authentication token and changes the user status to logged in. Specific operation: "Login successful" is displayed on the screen.

[0766] Step 2: Enter and save your user information

[0767] The user inputs detailed information about the date (purpose, partner's attributes, relationship, budget, food preferences, etc.) into the terminal. Input data: purpose of the date, partner's attributes, relationship, budget, food preferences.

[0768] The device sends the entered details to the server. Data processing: Formatting as an HTTP request.

[0769] The server saves the received data in the database. Data processing: Adds a record to the database. Output: Confirms that the data is saved.

[0770] Step 3: Restaurant proposal

[0771] The server calls an external restaurant database API based on the user's input information. Input data: User's conditions.

[0772] The server selects appropriate restaurants based on the data returned from the API and generates a list of suggested restaurants. Output data: List of suggested restaurants.

[0773] Data processing: Analyze the returned JSON data and extract restaurants that meet the conditions.

[0774] The terminal receives the recommendation list sent from the server and displays it to the user. Specific operation: The "recommended restaurant list" is displayed on the screen.

[0775] Step 4: Create a teaser message

[0776] The server uses a generative AI model to create an invitation message based on user information. Input data: User attribute information and relationship information. Output data: Invitation message.

[0777] Data processing: Generate messages using generative AI models.

[0778] The device receives the message sent from the server and displays it to the user. Specific operation: An "invitation message" is displayed on the screen.

[0779] The user sends the message they have reviewed and edited through a messaging app (e.g., a generic messaging app). Specific behavior: The messaging app is launched and the message is sent.

[0780] Step 5: Proposal for a date outfit

[0781] The server calls an external fashion database API based on the user's style information and suggests appropriate outfits. Input data: User's style information. Output data: Suggested outfits.

[0782] Data processing: Analyze the response data from the fashion API and extract outfits that suit the user.

[0783] The terminal receives the coordination suggestions sent from the server and displays them to the user. Specific operation: "Recommended coordination" is displayed on the screen.

[0784] Step 6: Collect and use feedback

[0785] After the user has gone on a date, the results and impressions are sent to the server as feedback via the device. Input data: Feedback content.

[0786] The server collects and analyzes the feedback. Data processing: Analyzes the feedback data and stores it in a database. Output data: Saves the analysis results and feedback.

[0787] The server analyzes the collected feedback and updates the system to improve the accuracy of the next suggestion. Specific operation: Improved algorithm, improved suggestion accuracy.

[0788] (Application example 1)

[0789] 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."

[0790] In recent years, when planning a date, selecting an appropriate restaurant, writing an invitation message, and suggesting appropriate outfits for the date have become important. However, planning everything on your own is time-consuming, and there is a lack of support systems that can provide effective suggestions. The present invention aims to provide a support system that smoothly plans and executes such dates, allowing users to easily plan dates.

[0791] 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.

[0792] In this invention, the server includes a means for inputting a user's attribute information, relationship information, and budget information, a means for suggesting appropriate restaurants based on the information input by the user, and a means for displaying the generated list of suggested restaurants to the user. This allows the user to easily receive automatic suggestions for restaurants and date plans that suit them. The server also includes a means for generating an invitation message based on the user's input information, a means for displaying the generated invitation message to the user, a means for assisting with restaurant reservations via a smartphone application based on the user information, a means for inputting a prompt into a generation AI model to generate an invitation message, and a means for enabling the generated message to be sent via a messaging app. This allows the user to easily and effectively create and send an invitation message to the other party. The server also includes a means for acquiring the user's style information and suggesting outfits using a fashion database API, and a means for notifying the user's smartphone of the suggested outfits. This allows the user to receive suggestions for the perfect outfit for a date.

[0793] "User attribute information" refers to personal information such as the user's age, gender, hobbies, and preferences.

[0794] "Relationship information" is information that indicates the depth and attributes of the relationship between the user and the date partner.

[0795] "Budget information" is information about the amount of money the user plans to spend on a date.

[0796] The "means for suggesting restaurants" is a function that selects appropriate restaurants based on the user's budget information and preferences and generates a list.

[0797] The "suggested restaurant list" is a list of restaurants generated to be suggested to the user.

[0798] The "means for generating an invitation message" is a function that automatically creates a date invitation message based on the user's attribute information and relationship information.

[0799] The "Fashion Database API" is an external API that provides appropriate fashion coordination based on the user's style information.

[0800] A "generative AI model" is an artificial intelligence algorithm that takes user input and generates appropriate output based on a specific task.

[0801] A "prompt sentence" is an input sentence given to an AI model, an instruction sentence that starts the generation process.

[0802] A "smartphone application" is application software that runs on a mobile device that a user uses on a daily basis.

[0803] "Coordination suggestions" are suggestions for appropriate clothing and accessories that match the user's preferences and the situation of the date.

[0804] MODE FOR CARRYING OUT THE INVENTION

[0805] This invention is a system that supports users in smoothly planning and executing dates. This system is composed of the following components:

[0806] System Configuration

[0807] This system consists of a smartphone operated by the user, a server, and an external API.

[0808] Hardware used

[0809] Smartphone: A device operated by a user

[0810] Server: A central server that processes and stores data

[0811] Software used

[0812] Firebase Authentication: A service for user registration and login authentication

[0813] Google Places API: An external API for retrieving data from the restaurant database

[0814] OpenAI GPT-3: A generative AI model used to generate teaser messages

[0815] ZOZO API: An external database API used to suggest fashion coordination

[0816] Firebase Firestore: A service for storing user information and managing databases

[0817] Specific explanation of the process

[0818] User Registration and Login

[0819] The server receives the username, email address, and password entered by the user on the smartphone, authenticates this information using Firebase Authentication, and stores it in Firebase Firestore. If authentication is successful, the server generates an authentication token and sends it back to the smartphone.

[0820] Entering user information

[0821] Users enter details of their dates (purpose, partner attributes, budget, food preferences, etc.) on their smartphones, and this information is stored in Firebase Firestore in real time.

[0822] Restaurant suggestions

[0823] The server calls the Google Places API based on the user's budget and preferences to retrieve a list of suitable restaurants, which is then filtered and displayed on the user's smartphone as a suggested restaurant list.

[0824] Generate an invitation message

[0825] The server inputs a prompt into the generative AI model, OpenAI GPT-3, to generate a teaser message. An example of this prompt is as follows:

[0826] "Hi {name}! How about meeting for dinner next Friday at a new cafe I found? It's called {cafe_name} and has great reviews and a chic atmosphere. How about {time}? I'd love to join you!"

[0827] The generated message is sent to the user's smartphone, where the user can review, edit, and send it via a messaging app.

[0828] Date coordination suggestions

[0829] The server acquires the user's style information and uses the ZOZO API, a fashion database API, to generate appropriate outfit suggestions. These suggestions are then sent to the user's smartphone and displayed to the user.

[0830] Collecting and using feedback

[0831] Users enter their feedback after the date on their smartphone and send it to the server, which stores the feedback data in Firebase Firestore and analyzes it to improve the accuracy of future suggestions.

[0832] This allows users to receive a series of support regarding dating and get specific suggestions to make their date a success.

[0833] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0834] Step 1:

[0835] A user launches the application using a smartphone and registers by entering their username, email address, and password. The entered information is sent to the server, authenticated using Firebase Authentication, and stored in Firebase Firestore. If authentication is successful, the server generates an authentication token and sends it back to the smartphone. The input data is the user's personal information, and the output is an authentication token.

[0836] Step 2:

[0837] Users input date details (purpose, partner attributes, budget, food preferences, etc.) on their smartphones. The input details are sent to the server in real time and stored in Firebase Firestore. The input data is the date details, and the output is the information stored in the database.

[0838] Step 3:

[0839] The server calls the Google Places API based on the budget information and food preferences entered by the user to obtain an appropriate restaurant list. The restaurant data obtained from the API is filtered to generate an appropriate restaurant list. The generated suggested restaurant list is sent to the smartphone and displayed to the user. The input data is the user's conditions and restaurant data from the API, and the output is the suggested restaurant list.

[0840] Step 4:

[0841] The server inputs a prompt into OpenAI GPT-3 based on the user's attribute information and relationship information to generate an invitation message. The generated message is sent to the smartphone. The user can review and edit the message and send it via a messaging app such as LINE. The input data are the user's attribute information, relationship information, and prompt, and the output is the generated invitation message. Specific examples of prompts are as follows:

[0842] "Hi {name}! How about meeting for dinner next Friday at a new cafe I found? It's called {cafe_name} and has great reviews and a chic atmosphere. How about {time}? I'd love to join you!"

[0843] Step 5:

[0844] The server acquires the user's style information and uses a fashion database API (e.g., the ZOZO API) to suggest outfits. The suggested outfits are sent to the user's smartphone and notified to the user. The input data is the user's style information and data from the fashion database, and the output is the suggested outfits.

[0845] Step 6:

[0846] After a date, users send their feedback on the date to the server via their smartphone. The server stores this feedback data in Firebase Firestore and analyzes it to improve the accuracy of suggestions for the next date. The input data is the user's feedback, and the output is the analyzed data and improvements to the accuracy of suggestions.

[0847] 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.

[0848] overview

[0849] This invention is a system that provides a series of support to help dates proceed smoothly, and by combining the user's attribute information, relationship information, and budget information with an emotion engine that recognizes the user's emotional state, it makes more personalized suggestions and generates messages.

[0850] System configuration

[0851] This system consists of a terminal operated by the user, a server, and an external API. It also includes an emotion engine that recognizes the user's emotions. The main functions of the system are as follows:

[0852] 1. Enter and save user information

[0853] The user inputs the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc. into the device.

[0854] The terminal sends the input information to the server, and the server stores the received information in a database.

[0855] 2. Emotion Engine Recognition

[0856] The device uses a camera and microphone to analyze the user's emotional state using an emotion engine.

[0857] The server receives the analysis results from the emotion engine and stores them in a database.

[0858] 3. Restaurant proposals

[0859] The server sets request parameters based on the user's input information and emotional state.

[0860] The server sends a request to an external restaurant database API.

[0861] An appropriate restaurant list is generated from the returned data and optimized according to the user's emotional state.

[0862] A list of suggested restaurants is sent to the terminal and displayed to the user.

[0863] 4. Generate a teaser message

[0864] The server uses generative AI technology to generate an invitation message based on the user's attribute information, relationship information, and emotional state.

[0865] The generated message is sent to the device, where the user can review and edit it and send it through the messaging app.

[0866] 5. Date coordination suggestions

[0867] The server uses an external fashion database API to generate outfits that suit the user's style, date situation, and emotional state.

[0868] The proposed coordinates are sent to the terminal and provided to the user.

[0869] 6. Collect and use feedback

[0870] The server collects feedback from the user after the date has taken place.

[0871] The feedback data will be used to improve the accuracy of proposals from next time onwards.

[0872] Specific examples of program processing

[0873] 1. User registration and login process

[0874] The device prompts the user to enter their username, email address, and password, and sends them to the server.

[0875] The server receives the input data and stores it in a database.

[0876] An authentication token is generated and sent to the terminal.

[0877] 2. Enter your user information

[0878] The user enters the date details into the terminal.

[0879] The device sends the entered details to the server and stores them in a database.

[0880] 3. Emotion Engine Recognition

[0881] The device uses a camera and microphone to have the emotion engine analyze the user's emotional state.

[0882] The server receives the analysis results from the emotion engine and stores them in a database.

[0883] 4. Restaurant Proposals

[0884] The server calls an external restaurant database API based on the user's conditions and emotional state.

[0885] An appropriate restaurant list is generated from the returned data and optimized according to the user's emotional state.

[0886] The suggestion list is sent to the terminal and displayed to the user.

[0887] 5. Generate a teaser message

[0888] The server uses a generation AI to create an invitation message based on the user's information and emotional state.

[0889] The message is sent to the device, where the user can review, edit, and send it through the messaging app.

[0890] 6. Date coordination suggestions

[0891] The server calls a fashion database API based on the user's style information and emotional state, and generates appropriate coordination suggestions.

[0892] The proposed coordinates are sent to the terminal and displayed to the user.

[0893] 7. Final review and feedback

[0894] The user goes on a date based on the provided suggestions and transmits the results to the server as feedback.

[0895] The server analyzes and stores the collected feedback to improve the accuracy of the next suggestion.

[0896] This allows users to receive a range of dating support and specific suggestions tailored to their emotional state.

[0897] The processing flow will be explained below.

[0898] overview

[0899] This invention is a system that provides a series of support to help dates proceed smoothly, and by combining the user's attribute information, relationship information, and budget information with an emotion engine that recognizes the user's emotional state, it makes more personalized suggestions and generates messages.

[0900] System configuration

[0901] This system consists of a terminal operated by the user, a server, and an external API. It also includes an emotion engine that recognizes the user's emotions. The main functions of the system are as follows:

[0902] 1. User registration and login process

[0903] Step 1:

[0904] The device launches the application and displays the login or registration page.

[0905] Step 2:

[0906] The user enters their username, email address, and password.

[0907] Step 3:

[0908] The terminal transmits the input information to the server.

[0909] Step 4:

[0910] The server stores the received information in a database.

[0911] Step 5:

[0912] The server generates an authentication token and sends it to the device.

[0913] Step 6:

[0914] The terminal receives the authentication token and displays the login status to the user.

[0915] 2. Enter user information

[0916] Step 1:

[0917] The terminal displays a screen for the user to enter detailed date information.

[0918] Step 2:

[0919] Users enter the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc.

[0920] Step 3:

[0921] The terminal transmits the input information to the server.

[0922] Step 4:

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

[0924] 3. Emotion Engine Recognition

[0925] Step 1:

[0926] The device will ask the user for permission to access the camera and microphone.

[0927] Step 2:

[0928] The user allows camera and microphone access.

[0929] Step 3:

[0930] The device uses a camera and microphone to record the user's facial expressions and voice and transmits them to the emotion engine.

[0931] Step 4:

[0932] The emotion engine analyzes the user's emotional state and sends the results to the server.

[0933] Step 5:

[0934] The server stores the analysis results from the emotion engine in a database.

[0935] 4. Restaurant Proposals

[0936] Step 1:

[0937] The server sets the request parameters based on the user's details and emotional state.

[0938] Step 2:

[0939] The server sends a request to an external restaurant database API.

[0940] Step 3:

[0941] The server parses the data returned from the API.

[0942] Step 4:

[0943] The server generates an appropriate list of restaurants based on the analysis results and optimizes it according to the user's emotional state.

[0944] Step 5:

[0945] The restaurant list generated by the server is sent to the terminal and displayed to the user.

[0946] 5. Generate a teaser message

[0947] Step 1:

[0948] The terminal sends a request to the server to create a message.

[0949] Step 2:

[0950] The server uses generation AI to generate messages based on the user's attribute information, relationship information, and emotional state.

[0951] Step 3:

[0952] The server generates a message and sends it to the terminal.

[0953] Step 4:

[0954] The terminal displays the generated message to the user.

[0955] Step 5:

[0956] The user reviews and edits the message and sends it using the messaging app.

[0957] 6. Date coordination suggestions

[0958] Step 1:

[0959] The terminal transmits a fashion suggestion request to the server based on the user's attribute information.

[0960] Step 2:

[0961] The server sends a request to an external fashion database API based on the user's style information and emotional state.

[0962] Step 3:

[0963] The server parses the data returned from the API.

[0964] Step 4:

[0965] The server generates appropriate coordination suggestions from the analysis results and optimizes them based on the emotional state.

[0966] Step 5:

[0967] The coordinate proposal generated by the server is sent to the terminal and displayed to the user.

[0968] 7. Final review and feedback

[0969] Step 1:

[0970] The user reviews the provided suggestions and takes the necessary action (reserving a restaurant, sending a message, selecting an outfit).

[0971] Step 2:

[0972] The terminal sends the user's action status to the server.

[0973] Step 3:

[0974] The server tracks and checks the completion status of user actions.

[0975] Step 4:

[0976] The server sends a feedback collection request to the terminal.

[0977] Step 5:

[0978] The user inputs feedback through the terminal and transmits it to the server.

[0979] Step 6:

[0980] The server analyzes and stores the feedback data to improve the accuracy of the next proposal.

[0981] Example 2

[0982] 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."

[0983] When planning a date, there is a lack of personalized suggestions that take into account the user's attributes, relationship information, budget information, and even emotional state. Furthermore, since there is no systematic support that integrates multiple elements, it is difficult for users to plan the best date.

[0984] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0985] In this invention, the server includes means for inputting user attribute information, relationship information, and budget information, means for suggesting appropriate restaurants based on the information input by the user and the user's emotional state, and means for generating an invitation message based on the input information and the user's emotional state, thereby enabling the user to easily plan an optimal date taking into account multiple factors including the attribute information and the user's emotional state.

[0986] "User attribute information" is data that indicates individual characteristics and features of a user, and includes age, gender, occupation, hobbies, and the like.

[0987] "Relationship information" is data indicating the relationship the user has with the person they are dating, and includes friends, business partners, lovers, family, and the like.

[0988] "Budget information" is data regarding the amount of money a user wants to spend on a date.

[0989] "Emotional state" is data that indicates the user's current emotions and moods, and includes positive, negative, neutral, and the like.

[0990] The "suggested restaurant list" is a list of restaurants suitable for a date, generated by the server based on the user's input information and emotional state.

[0991] An "invitation message" is a message for inviting someone on a date, generated using AI generation technology based on the user's attribute information and emotional state.

[0992] "Coordination suggestions" are data that suggest outfits suitable for a date based on the user's style information and emotional state.

[0993] "Server" means a computer system that stores and analyzes data and communicates with external APIs.

[0994] A "terminal" is a device operated by a user, such as a computer, smartphone, or tablet.

[0995] MODE FOR CARRYING OUT THE INVENTION

[0996] The present invention is a system that provides personalized date plans. This system can determine the user's emotional state in addition to user attribute information, relationship information, and budget information, and make appropriate suggestions. The system is primarily composed of a server, a terminal, and an external API. The operation of the system is described in detail below.

[0997] User registration and login process

[0998] The first thing a user does is enter their username, email address, and password into the device, which is then sent to the server, where it is stored in a database and an authentication token is generated and sent to the device.

[0999] Entering user information

[1000] Users select from a list of dating purposes and enter detailed information such as the partner's attributes, relationship status, budget, food preferences, etc. This information is sent from the device to the server and stored in a database.

[1001] Emotion Engine Recognition

[1002] The user's emotional state is collected by showing their facial expressions to the camera or speaking into the microphone. The device sends these images and sounds to the emotion engine for analysis. The analysis results are sent to the server and stored in a database.

[1003] Restaurant suggestions

[1004] The server sets request parameters based on the user's input information and emotional state, and sends a request to an external restaurant database API. It generates an appropriate restaurant list from the returned data and optimizes the list based on the user's emotional state. The optimized restaurant list is sent to the device and displayed to the user.

[1005] Generate an invitation message

[1006] The server uses generative AI technology to create an invitation message based on the user's attribute information, relationship information, and emotional state. The generated message is sent to the device, where the user can review and edit it and send it through the messaging app.

[1007] Date coordination suggestions

[1008] The server generates outfit suggestions based on the user's style information and emotional state using an external fashion database API, and the resulting outfit suggestions are sent to the device and provided to the user.

[1009] Final review and feedback gathering

[1010] After a date, users input their satisfaction and areas for improvement into their device and send the feedback data to the server, which collects and stores the feedback data and uses it to improve the accuracy of future suggestions.

[1011] Examples of concrete examples and prompts

[1012] For example, a user might use the system as follows:

[1013] 1. A user accesses the system and creates an account by entering a username, email address, and password.

[1014] 2. The user enters the details of the date (e.g., budget is under 5,000 yen, food preference is Italian).

[1015] 3. The user smiles at the camera, and the emotion engine recognizes "positive emotion."

[1016] 4. The server generates a list of Italian restaurant suggestions and optimizes it according to the user's emotional state.

[1017] 5. The server uses a generation AI to generate an invitation message saying, "Would you like to join us for some Italian food this weekend?"

[1018] 6. The server suggests fashion coordination that matches the user's taste.

[1019] 7. After the date, the user sends feedback saying, "The date was great, but the restaurant was booked and we had to wait a long time."

[1020] Examples of prompts are:

[1021] 1. "User information: Name = Yamada Taro, Budget = Under 5,000 yen, Food preference = Italian food, Relationship = Friend"

[1022] 2. "Emotional state: Positive"

[1023] 3. "Generate a teaser message."

[1024] In this way, the system can propose personalized date plans to users and provide optimal restaurant recommendations and fashion coordination based on the user's emotional state.

[1025] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1026] The flow of this system's program processing

[1027] Step 1: User registration and login process

[1028] Input: Username, Email Address, Password

[1029] Operation:

[1030] The user enters their username, email address, and password on the device.

[1031] The terminal transmits this information to the server.

[1032] The server receives the transmitted user information and stores it in a database.

[1033] The server generates an authentication token and sends it to the device.

[1034] Output: Authentication token

[1035] Step 2: Enter your user information

[1036] Input: purpose of date, partner's attributes, relationship status, budget, food preferences

[1037] Operation:

[1038] The user inputs the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc. into the device.

[1039] The terminal sends the entered details to the server.

[1040] The server stores the submitted details in a database.

[1041] Output: Saved user details

[1042] Step 3: Recognizing the Emotion Engine

[1043] Input: Video data, audio data

[1044] Operation:

[1045] The user shows their facial expressions to the camera and speaks into the microphone.

[1046] The device collects video and audio and sends it to the emotion engine.

[1047] The emotion engine analyzes video and audio to identify the user's emotional state.

[1048] The server stores the analysis results received from the emotion engine in a database.

[1049] Output: User's emotional state

[1050] Step 4: Restaurant proposal

[1051] Input: User details, emotional state

[1052] Operation:

[1053] The server sets request parameters based on the user's input information and emotional state.

[1054] The server sends a request to an external restaurant database API.

[1055] The server receives the data returned from the external restaurant database API.

[1056] The server optimizes the restaurant list based on the user's emotional state.

[1057] The server transmits the optimized restaurant list to the terminal.

[1058] Output: A list of suggested restaurants

[1059] Step 5: Create a teaser message

[1060] Input: User information, emotional state

[1061] Operation:

[1062] The server creates a prompt for the generative AI model to use.

[1063] The server sends a prompt to the generation AI model, which generates an invitation message.

[1064] The server sends the generated message to the terminal.

[1065] The terminal displays the message to the user, who can then view and edit it.

[1066] The user sends the final message through a messaging app.

[1067] Output: Teaser message

[1068] Step 6: Proposal for a date outfit

[1069] Input: User style information, emotional state

[1070] Operation:

[1071] The server sends a request to an external fashion database API based on the user's style information and emotional state.

[1072] The server generates coordination suggestions based on the data returned from the external fashion database API.

[1073] The server transmits the generated coordination proposal to the terminal.

[1074] The terminal displays the coordination suggestions to the user.

[1075] Output: Date coordination suggestions

[1076] Step 7: Final review and feedback gathering

[1077] Input: Post-date feedback

[1078] Operation:

[1079] The user enters their satisfaction and areas for improvement after the date into the device.

[1080] The terminal transmits the feedback data to the server.

[1081] The server stores the feedback data in a database.

[1082] The server analyzes the feedback data and uses it to improve the accuracy of future proposals.

[1083] Output: Feedback data

[1084] In this way, at each processing step of the system, specific processes such as user input, data collection, analysis, and proposal generation are performed, allowing users to receive personalized dating support.

[1085] (Application example 2)

[1086] 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."

[1087] Conventional dating support systems handle basic data such as user attribute information, relationship information, and budget information, but do not take the user's emotional state into account, resulting in a lack of personalized suggestions and making it difficult to provide optimal suggestions.The present invention analyzes the user's emotional state and reflects this in the suggestions, enabling more personalized date plans to be proposed, thereby improving user satisfaction.

[1088] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1089] In this invention, the server includes means for recognizing a user's emotional state using an emotion engine that analyzes the user's emotional state, means for storing the analysis results from the emotion engine in a database, means for optimizing a suggested restaurant list based on the user's emotional state, and means for generating coordination suggestions based on the user's style information and emotional state using a fashion database API, thereby enabling personalized suggestions based on the user's emotions.

[1090] "User attribute information" is data that indicates personal characteristics of a user, such as age, gender, and hobbies.

[1091] "Relationship information" is data indicating the relationship between the user and the dater (e.g., first meeting, long-term relationship, friends).

[1092] "Budget information" is data indicating the amount of money a user can spend on a date.

[1093] An "emotion engine" is software or an algorithm that analyzes data such as a user's facial expressions and voice, and recognizes their emotional state (happiness, sadness, tension, etc.).

[1094] The "suggested restaurant list" is a list of restaurants selected based on the user's input information and emotional state.

[1095] An "invitation message" is a message created for the purpose of inviting someone on a date.

[1096] "Coordination suggestions" are suggestions for combinations of clothing, accessories, etc. that are suited to the user's style information and emotional state.

[1097] "Feedback data" refers to information such as evaluations and opinions provided by users after a date, and is data that is used to improve the accuracy of suggestions from the next date onwards.

[1098] The "restaurant database API" is an interface for communicating with an external restaurant information database and obtaining restaurant information.

[1099] "Generative AI technology" is an artificial intelligence technology that generates natural language based on large amounts of data.

[1100] The "Fashion Database API" is an interface for communicating with external fashion information databases and obtaining information on fashion items.

[1101] This invention is a system for supporting users in dating, and is composed of the following main elements and procedures. Specifically, the system processes and shares data while communicating with the server, terminals, and users, to propose date plans and collect feedback.

[1102] 1. Enter and save user information

[1103] The user inputs attribute information such as the purpose of the date, relationship status, budget, and food preferences from the terminal. The terminal sends the input information to the server, which then stores the information in a database.

[1104] 2. Emotion Engine Recognition

[1105] The user analyzes their emotional state using the smartphone's camera and microphone. The user's facial expressions and voice are then analyzed by the emotion engine, and their emotional state is recognized. The analysis results are sent to the server and stored in a database.

[1106] 3. Restaurant proposals and optimization

[1107] The server calls an external restaurant database API based on the user's input information and emotional state. Based on the returned information, it generates a restaurant list that takes into account the analysis results of the emotion engine and displays it to the user. This allows it to suggest restaurants that best suit the user's emotional state.

[1108] 4. Generate a teaser message

[1109] Generative AI technology (e.g., natural language generation models) is used to generate invitation messages based on the user's attributes, relationship information, and emotional state. The generated messages are sent to the device, where the user can review and edit them before sending them through a messaging app.

[1110] 5. Date coordination suggestions

[1111] The server calls a fashion database API based on the user's style information, date situation, and emotional state to generate outfit suggestions, which are then sent to the device and displayed to the user.

[1112] 6. Collect and use feedback

[1113] After the date, users provide feedback on the application, which the server analyzes and stores in a database to improve the accuracy of future suggestions.

[1114] Specific examples

[1115] Software and hardware used

[1116] Emotion engine: Microsoft Azure Face API and Amazon Rekognition

[1117] Restaurant database API: Google Places API, Tabelog API

[1118] Natural Language Generation Technology: OpenAI's GPT-3

[1119] Fashion database API: Rakuten Fashion API

[1120] Device: Smartphone

[1121] Server: General web server

[1122] Examples of prompt statements

[1123] The purpose of the date is an anniversary, the relationship is long-term, and the user's emotional state is joy. Based on this information, please generate an invitation message to send to your partner.

[1124] In this way, the system of the present invention can take into account the user's emotional state, thereby realizing more personalized date plan suggestions and improving user satisfaction.

[1125] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1126] Step 1:

[1127] Input: The user enters demographic information such as the purpose of the date, relationship status, budget, and food preferences.

[1128] How it works: The device collects information through a user input form and sends it to the server.

[1129] Output: The server stores the received information in a database.

[1130] Step 2:

[1131] Input: Video and audio data from the user's camera and microphone.

[1132] How it works: The device uses the camera and microphone to send data to the emotion engine, which analyzes the user's emotional state. The server then stores the analysis results in a database.

[1133] Output: An analysis of the user's emotional state.

[1134] Step 3:

[1135] Input: User demographic information, relationship information, budget information, and emotional state.

[1136] How it works: The server calls an external restaurant database API to retrieve a list of appropriate restaurants based on the input information. The retrieved list is then optimized based on the user's emotional state.

[1137] Output: A list of restaurants that fit your emotional state.

[1138] Step 4:

[1139] Input: User attribute information, relationship information, and emotional state.

[1140] How it works: The server uses generative AI technology to generate a prompt. For example, "The purpose of the date is an anniversary, the relationship is long-term, and the user's emotional state is joy. Based on this information, please generate an invitation message to send to the other person."

[1141] Output: The generated teaser message.

[1142] Step 5:

[1143] Input: User's demographic information, style information, and emotional state.

[1144] How it works: The server calls the fashion database API and generates outfit suggestions suitable for the user.

[1145] Output: Coordination suggestions.

[1146] Step 6:

[1147] Input: Feedback information entered by the user after the date.

[1148] How it works: The server collects feedback information and stores it in a database to improve the accuracy of suggestions next time.

[1149] Output: Feedback data is accumulated to improve the accuracy of future suggestions.

[1150] 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.

[1151] 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.

[1152] 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.

[1153] [Third embodiment]

[1154] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1155] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1156] 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).

[1157] 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.

[1158] 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.

[1159] 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).

[1160] 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.

[1161] 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.

[1162] 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.

[1163] 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.

[1164] 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.

[1165] 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."

[1166] overview

[1167] The present invention is a system that provides a series of support to ensure a date goes smoothly, suggesting appropriate restaurants and generating invitation messages based on the user's attribute information, relationship information, and budget information, and also proposing outfits for the date.

[1168] System Configuration

[1169] This system consists of a terminal operated by the user, a server, and an external API. The main functions of the system are as follows:

[1170] 1. Enter and save user information

[1171] The user inputs the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc. into the device.

[1172] The terminal sends the input information to the server, and the server stores the received information in a database.

[1173] 2. Restaurant proposals

[1174] The server calls an external API (e.g., restaurant database API) based on the user's input information and generates an appropriate restaurant list.

[1175] A list of suggested restaurants is sent to the terminal and displayed to the user.

[1176] 3. Generate a teaser message

[1177] The server uses AI technology to generate an invitation message based on the user's attribute information and relationship information.

[1178] The message created is sent to the device, and the user can check and edit the message and send it via a messaging app (e.g., LINE).

[1179] 4. Date coordination suggestions

[1180] The server uses an external API (e.g., a fashion database API) to generate outfits that suit the user's style and the date situation.

[1181] The proposed coordinates are sent to the terminal and provided to the user.

[1182] 5. Collect and use feedback

[1183] The server collects feedback from the user after the date has taken place.

[1184] The feedback data will be used to improve the accuracy of proposals from next time onwards.

[1185] Specific examples of program processing

[1186] 1. User registration and login process

[1187] The device prompts the user to enter their username, email address, and password, and sends them to the server.

[1188] The server saves the input data in a database and performs login authentication.

[1189] An authentication token is generated and sent to the terminal.

[1190] 2. Enter your user information

[1191] The user enters the date details into the terminal.

[1192] The device sends the entered details to the server, where they are stored in a database.

[1193] 3. Restaurant proposals

[1194] The server calls an external restaurant database API based on the user's criteria.

[1195] Appropriate restaurants are selected from the returned data and a list of suggestions is generated.

[1196] The suggestion list is sent to the terminal and displayed to the user.

[1197] 4. Generate a teaser message

[1198] The server uses a generation AI to create an invitation message based on user information.

[1199] The message is sent to the device, where the user can review, edit, and send it through the messaging app.

[1200] 5. Date coordination suggestions

[1201] The server calls the ZOZO API and other services based on the user's style information to generate appropriate outfit suggestions.

[1202] The proposed coordinates are sent to the terminal and displayed to the user.

[1203] 6. Final review and feedback

[1204] The user actually goes on a date based on the provided suggestions and sends the results to the server as feedback.

[1205] The server analyzes the collected feedback to improve the accuracy of the next proposal.

[1206] This allows users to receive a range of support regarding dating and specific suggestions to make their date a success.

[1207] The processing flow will be explained below.

[1208] Program processing flow

[1209] 1. User registration and login process

[1210] Step 1:

[1211] The terminal boots up and displays a login or registration page.

[1212] Step 2:

[1213] The user enters their username, email address, and password.

[1214] Step 3:

[1215] The terminal transmits the user's input information to the server.

[1216] Step 4:

[1217] The server receives the input information and stores it in a database.

[1218] Step 5:

[1219] The server generates an authentication token and sends it to the device.

[1220] Step 6:

[1221] The terminal receives the authentication token and displays the login status to the user.

[1222] 2. Enter user information

[1223] Step 1:

[1224] The device displays a screen for the user to enter detailed information about the date.

[1225] Step 2:

[1226] Users enter the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc.

[1227] Step 3:

[1228] The terminal transmits the input information to the server.

[1229] Step 4:

[1230] The server receives the user information and stores it in a database.

[1231] 3. Restaurant proposals

[1232] Step 1:

[1233] The server sets the request parameters based on the user input information.

[1234] Step 2:

[1235] The server sends a request to an external restaurant database API.

[1236] Step 3:

[1237] The server parses the data returned from the API.

[1238] Step 4:

[1239] The server generates an appropriate restaurant list from the analysis results.

[1240] Step 5:

[1241] The restaurant list generated by the server is sent to the terminal and displayed to the user.

[1242] 4. Generate a teaser message

[1243] Step 1:

[1244] The terminal sends a request to the server to create a message.

[1245] Step 2:

[1246] The server uses generation AI to generate messages based on the other person's attributes and relationship.

[1247] Step 3:

[1248] The server generates a message and sends it to the terminal.

[1249] Step 4:

[1250] The terminal displays the generated message to the user.

[1251] Step 5:

[1252] The user reviews and edits the message and sends it using the messaging app.

[1253] 5. Date coordination suggestions

[1254] Step 1:

[1255] The terminal transmits a fashion suggestion request to the server based on the user's attribute information.

[1256] Step 2:

[1257] The server sends a request to an external fashion database API based on the user's style information.

[1258] Step 3:

[1259] The server parses the data returned from the API.

[1260] Step 4:

[1261] The server generates appropriate coordination suggestions from the analysis results.

[1262] Step 5:

[1263] The coordinate proposal generated by the server is sent to the terminal and displayed to the user.

[1264] 6. Final review and feedback

[1265] Step 1:

[1266] The user reviews the provided suggestions and takes the necessary action (reserving a restaurant, sending a message, selecting an outfit).

[1267] Step 2:

[1268] The terminal sends the user's action status to the server.

[1269] Step 3:

[1270] The server tracks and checks the completion status of user actions.

[1271] Step 4:

[1272] The server sends a feedback collection request to the terminal.

[1273] Step 5:

[1274] The user inputs feedback through the terminal and transmits it to the server.

[1275] Step 6:

[1276] The server analyzes and stores the feedback data to improve the accuracy of future proposals.

[1277] Example 1

[1278] 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."

[1279] When planning a date, users must consider various factors (such as the partner's preferences, the relationship, and budget), which is a time-consuming and labor-intensive process. Furthermore, a wide range of support is required, such as choosing the right restaurant, the content of the invitation, and suggestions for appropriate attire for the date. However, there is no system that can provide all of these elements in one place and efficiently support users in planning a date.

[1280] 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.

[1281] In this invention, the server includes means for inputting user attribute information, relationship information, and budget information, means for utilizing an external API to suggest restaurants, means for generating invitation messages using a generative AI model, means for utilizing an external API to suggest outfits, and means for collecting feedback on the user's date actions. This allows the user to receive a series of support through their device, enabling date planning to proceed smoothly and efficiently.

[1282] "User attribute information" is information indicating individual characteristics of a user, such as age, sex, hobbies, preferences, and occupation.

[1283] "Relationship information" is information indicating the relationship between the user and the date (for example, friends, colleagues, lovers, etc.).

[1284] "Budget information" is information that indicates the range of expenses that can be spent on a date.

[1285] The "means for suggesting restaurants" refers to a function for recommending appropriate restaurants based on the conditions entered by the user.

[1286] An "external API" is a means of referring to an interface for connecting with other services or databases.

[1287] The "suggested restaurant list" is a list of restaurants recommended based on the user's criteria.

[1288] "Means for generating an invitation message" refers to means for using generative AI technology to create an invitation message that meets the user's conditions.

[1289] "Means of using an external API to suggest outfits" refers to a function that links with an external fashion database to recommend outfits suitable for a date.

[1290] The "means for collecting feedback on the user's dating actions" refers to a function for collecting feedback such as the results and impressions of a date after the user has completed the date.

[1291] An "authentication token" is a security token issued to maintain a user's logged-in state.

[1292] A "generative AI model" is an artificial intelligence model that generates appropriate responses and suggestions based on user input data and conditions.

[1293] MODE FOR CARRYING OUT THE INVENTION

[1294] This invention is a system that provides a series of support functions to help users efficiently plan dates. The system consists of a terminal operated by the user, a server, and an external API. The main functions of this system include inputting and saving user information, suggesting restaurants, generating invitation messages, suggesting date coordination, and collecting feedback.

[1295] Entering and saving user information

[1296] The device prompts the user for their username, email address, and password, and sends them to the server, which stores the information in a database and authenticates the login.

[1297] The user inputs detailed information such as the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc. into the device, which then sends the information to the server and stores it in a database.

[1298] Restaurant suggestions

[1299] The server calls an external restaurant database API (for example, a restaurant API with a general name) based on the user's input information.

[1300] The server selects appropriate restaurants from the returned data and generates a list of suggestions, which is then sent to the terminal and displayed to the user.

[1301] Generate an invitation message

[1302] The server uses a generative AI model to create an invitation message based on the user's attribute information and relationship information. The name of the specific generative AI model will be generalized, for example, called "message generation AI technology."

[1303] The generated message is sent to the device, where it is edited and confirmed by the user and then sent via a messaging app (e.g., a generic messaging app).

[1304] Date coordination suggestions

[1305] The server calls an external fashion database API (e.g., a fashion API with a general name) based on the user's style information and suggests appropriate outfits.

[1306] The proposed coordinate information is sent to the terminal and displayed to the user.

[1307] Collecting and using feedback

[1308] After the user has gone on a date, the user transmits the results to the server as feedback.

[1309] The server analyzes the collected feedback and stores it in a database to improve the accuracy of suggestions next time.

[1310] Specific examples

[1311] Example of entering and saving user information

[1312] The user logs in as "Taro Tanaka" and enters date details. For example, the user might enter "Purpose of the date: To deepen intimacy," "Partner's attributes: Female in her 20s," "Relationship type: Colleague," "Budget: 3,000 yen," and "Food preference: Japanese food."

[1313] Specific examples of restaurant proposals

[1314] The server retrieves restaurants that meet the user's criteria from the restaurant API and generates a list of suggestions. For example, it suggests three Japanese restaurants.

[1315] Example of creating a teaser message

[1316] The server uses the generative AI model to generate a message such as, "Hello, would you like to go out to dinner with me this weekend? I have a Japanese restaurant I'd like to recommend."

[1317] Specific examples of date coordination suggestions

[1318] The server uses a fashion API to suggest "a casual jacket and chinos" to the user.

[1319] Prompt Sentence Examples

[1320] "My date is with a colleague, my budget is 3000 yen, and I like Japanese food. Please suggest a suitable restaurant."

[1321] "Generate a teaser message based on the user's information. His hobby is the outdoors, and he's been busy lately."

[1322] This allows users to receive a series of support regarding dates through the system, significantly reducing the time and effort required to plan and carry out dates.

[1323] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1324] Program processing flow

[1325] Step 1: User registration and login process

[1326] The user enters their username, email address, and password and sends them to the terminal. Input data: username, email address, password.

[1327] The terminal sends the entered user data to the server. Data processing: Formats it as an HTTP request.

[1328] The server saves the received data in the database and performs login authentication. Data processing: Adds a record to the database and generates an authentication token. Output: Authentication token.

[1329] The terminal receives the authentication token and changes the user status to logged in. Specific operation: "Login successful" is displayed on the screen.

[1330] Step 2: Enter and save your user information

[1331] The user inputs detailed information about the date (purpose, partner's attributes, relationship, budget, food preferences, etc.) into the terminal. Input data: purpose of the date, partner's attributes, relationship, budget, food preferences.

[1332] The device sends the entered details to the server. Data processing: Formatting as an HTTP request.

[1333] The server saves the received data in the database. Data processing: Adds a record to the database. Output: Confirms that the data is saved.

[1334] Step 3: Restaurant proposal

[1335] The server calls an external restaurant database API based on the user's input information. Input data: User's conditions.

[1336] The server selects appropriate restaurants based on the data returned from the API and generates a list of suggested restaurants. Output data: List of suggested restaurants.

[1337] Data processing: Analyze the returned JSON data and extract restaurants that meet the conditions.

[1338] The terminal receives the recommendation list sent from the server and displays it to the user. Specific operation: The "recommended restaurant list" is displayed on the screen.

[1339] Step 4: Create a teaser message

[1340] The server uses a generative AI model to create an invitation message based on user information. Input data: User attribute information and relationship information. Output data: Invitation message.

[1341] Data processing: Generate messages using generative AI models.

[1342] The device receives the message sent from the server and displays it to the user. Specific operation: An "invitation message" is displayed on the screen.

[1343] The user sends the message they have reviewed and edited through a messaging app (e.g., a generic messaging app). Specific behavior: The messaging app is launched and the message is sent.

[1344] Step 5: Proposal for a date outfit

[1345] The server calls an external fashion database API based on the user's style information and suggests appropriate outfits. Input data: User's style information. Output data: Suggested outfits.

[1346] Data processing: Analyze the response data from the fashion API and extract outfits that suit the user.

[1347] The terminal receives the coordination suggestions sent from the server and displays them to the user. Specific operation: "Recommended coordination" is displayed on the screen.

[1348] Step 6: Collect and use feedback

[1349] After the user has gone on a date, the results and impressions are sent to the server as feedback via the device. Input data: Feedback content.

[1350] The server collects and analyzes the feedback. Data processing: Analyzes the feedback data and stores it in a database. Output data: Saves the analysis results and feedback.

[1351] The server analyzes the collected feedback and updates the system to improve the accuracy of the next suggestion. Specific operation: Improved algorithm, improved suggestion accuracy.

[1352] (Application example 1)

[1353] 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."

[1354] In recent years, when planning a date, selecting an appropriate restaurant, writing an invitation message, and suggesting appropriate outfits for the date have become important. However, planning everything on your own is time-consuming, and there is a lack of support systems that can provide effective suggestions. The present invention aims to provide a support system that smoothly plans and executes such dates, allowing users to easily plan dates.

[1355] 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.

[1356] In this invention, the server includes a means for inputting a user's attribute information, relationship information, and budget information, a means for suggesting appropriate restaurants based on the information input by the user, and a means for displaying the generated list of suggested restaurants to the user. This allows the user to easily receive automatic suggestions for restaurants and date plans that suit them. The server also includes a means for generating an invitation message based on the user's input information, a means for displaying the generated invitation message to the user, a means for assisting with restaurant reservations via a smartphone application based on the user information, a means for inputting a prompt into a generation AI model to generate an invitation message, and a means for enabling the generated message to be sent via a messaging app. This allows the user to easily and effectively create and send an invitation message to the other party. The server also includes a means for acquiring the user's style information and suggesting outfits using a fashion database API, and a means for notifying the user's smartphone of the suggested outfits. This allows the user to receive suggestions for the perfect outfit for a date.

[1357] "User attribute information" refers to personal information such as the user's age, gender, hobbies, and preferences.

[1358] "Relationship information" is information that indicates the depth and attributes of the relationship between the user and the date partner.

[1359] "Budget information" is information about the amount of money the user plans to spend on a date.

[1360] The "means for suggesting restaurants" is a function that selects appropriate restaurants based on the user's budget information and preferences and generates a list.

[1361] The "suggested restaurant list" is a list of restaurants generated to be suggested to the user.

[1362] The "means for generating an invitation message" is a function that automatically creates a date invitation message based on the user's attribute information and relationship information.

[1363] The "Fashion Database API" is an external API that provides appropriate fashion coordination based on the user's style information.

[1364] A "generative AI model" is an artificial intelligence algorithm that takes user input and generates appropriate output based on a specific task.

[1365] A "prompt sentence" is an input sentence given to an AI model, an instruction sentence that starts the generation process.

[1366] A "smartphone application" is application software that runs on a mobile device that a user uses on a daily basis.

[1367] "Coordination suggestions" are suggestions for appropriate clothing and accessories that match the user's preferences and the situation of the date.

[1368] MODE FOR CARRYING OUT THE INVENTION

[1369] This invention is a system that supports users in smoothly planning and executing dates. This system is composed of the following components:

[1370] System Configuration

[1371] This system consists of a smartphone operated by the user, a server, and an external API.

[1372] Hardware used

[1373] Smartphone: A device operated by a user

[1374] Server: A central server that processes and stores data

[1375] Software used

[1376] Firebase Authentication: A service for user registration and login authentication

[1377] Google Places API: An external API for retrieving data from the restaurant database

[1378] OpenAI GPT-3: A generative AI model used to generate teaser messages

[1379] ZOZO API: An external database API used to suggest fashion coordination

[1380] Firebase Firestore: A service for storing user information and managing databases

[1381] Specific explanation of the process

[1382] User Registration and Login

[1383] The server receives the username, email address, and password entered by the user on the smartphone, authenticates this information using Firebase Authentication, and stores it in Firebase Firestore. If authentication is successful, the server generates an authentication token and sends it back to the smartphone.

[1384] Entering user information

[1385] Users enter details of their dates (purpose, partner attributes, budget, food preferences, etc.) on their smartphones, and this information is stored in Firebase Firestore in real time.

[1386] Restaurant suggestions

[1387] The server calls the Google Places API based on the user's budget and preferences to retrieve a list of suitable restaurants, which is then filtered and displayed on the user's smartphone as a suggested restaurant list.

[1388] Generate an invitation message

[1389] The server inputs a prompt into the OpenAI GPT-3 generative AI model to generate a teaser message. An example of this prompt is as follows:

[1390] "Hi {name}! How about meeting for dinner next Friday at a new cafe I found? It's called {cafe_name} and has great reviews and a chic atmosphere. How about {time}? I'd love to join you!"

[1391] The generated message is sent to the user's smartphone, where the user can review, edit, and send it via a messaging app.

[1392] Date coordination suggestions

[1393] The server acquires the user's style information and uses the ZOZO API, a fashion database API, to generate appropriate outfit suggestions. These suggestions are then sent to the user's smartphone and displayed to the user.

[1394] Collecting and using feedback

[1395] Users enter their feedback after the date on their smartphone and send it to the server, which stores the feedback data in Firebase Firestore and analyzes it to improve the accuracy of future suggestions.

[1396] This allows users to receive a series of support regarding dating and get specific suggestions to make their date a success.

[1397] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1398] Step 1:

[1399] A user launches the application using a smartphone and registers by entering their username, email address, and password. The entered information is sent to the server, authenticated using Firebase Authentication, and stored in Firebase Firestore. If authentication is successful, the server generates an authentication token and sends it back to the smartphone. The input data is the user's personal information, and the output is an authentication token.

[1400] Step 2:

[1401] Users input date details (purpose, partner attributes, budget, food preferences, etc.) on their smartphones. The input details are sent to the server in real time and stored in Firebase Firestore. The input data is the date details, and the output is the information stored in the database.

[1402] Step 3:

[1403] The server calls the Google Places API based on the budget information and food preferences entered by the user to obtain an appropriate restaurant list. The restaurant data obtained from the API is filtered to generate an appropriate restaurant list. The generated suggested restaurant list is sent to the smartphone and displayed to the user. The input data is the user's conditions and restaurant data from the API, and the output is the suggested restaurant list.

[1404] Step 4:

[1405] The server inputs a prompt into OpenAI GPT-3 based on the user's attribute information and relationship information to generate an invitation message. The generated message is sent to the smartphone. The user can review and edit the message and send it via a messaging app such as LINE. The input data are the user's attribute information, relationship information, and prompt, and the output is the generated invitation message. Specific examples of prompts are as follows:

[1406] "Hi {name}! How about meeting for dinner next Friday at a new cafe I found? It's called {cafe_name} and has great reviews and a chic atmosphere. How about {time}? I'd love to join you!"

[1407] Step 5:

[1408] The server acquires the user's style information and uses a fashion database API (e.g., the ZOZO API) to suggest outfits. The suggested outfits are sent to the user's smartphone and notified to the user. The input data is the user's style information and data from the fashion database, and the output is the suggested outfits.

[1409] Step 6:

[1410] After a date, users send their feedback on the date to the server via their smartphone. The server stores this feedback data in Firebase Firestore and analyzes it to improve the accuracy of suggestions for the next date. The input data is the user's feedback, and the output is the analyzed data and improvements to the accuracy of suggestions.

[1411] 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.

[1412] overview

[1413] This invention is a system that provides a series of support to help dates proceed smoothly, and by combining the user's attribute information, relationship information, and budget information with an emotion engine that recognizes the user's emotional state, it makes more personalized suggestions and generates messages.

[1414] System configuration

[1415] This system consists of a terminal operated by the user, a server, and an external API. It also includes an emotion engine that recognizes the user's emotions. The main functions of the system are as follows:

[1416] 1. Enter and save user information

[1417] The user inputs the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc. into the device.

[1418] The terminal sends the input information to the server, and the server stores the received information in a database.

[1419] 2. Emotion Engine Recognition

[1420] The device uses a camera and microphone to analyze the user's emotional state using an emotion engine.

[1421] The server receives the analysis results from the emotion engine and stores them in a database.

[1422] 3. Restaurant proposals

[1423] The server sets request parameters based on the user's input information and emotional state.

[1424] The server sends a request to an external restaurant database API.

[1425] An appropriate restaurant list is generated from the returned data and optimized according to the user's emotional state.

[1426] A list of suggested restaurants is sent to the terminal and displayed to the user.

[1427] 4. Generate a teaser message

[1428] The server uses generative AI technology to generate an invitation message based on the user's attribute information, relationship information, and emotional state.

[1429] The generated message is sent to the device, where the user can review and edit it and send it through the messaging app.

[1430] 5. Date coordination suggestions

[1431] The server uses an external fashion database API to generate outfits that suit the user's style, date situation, and emotional state.

[1432] The proposed coordinates are sent to the terminal and provided to the user.

[1433] 6. Collect and use feedback

[1434] The server collects feedback from the user after the date has taken place.

[1435] The feedback data will be used to improve the accuracy of proposals from next time onwards.

[1436] Specific examples of program processing

[1437] 1. User registration and login process

[1438] The device prompts the user to enter their username, email address, and password, and sends them to the server.

[1439] The server receives the input data and stores it in a database.

[1440] An authentication token is generated and sent to the terminal.

[1441] 2. Enter your user information

[1442] The user enters the date details into the terminal.

[1443] The device sends the entered details to the server and stores them in a database.

[1444] 3. Emotion Engine Recognition

[1445] The device uses a camera and microphone to have the emotion engine analyze the user's emotional state.

[1446] The server receives the analysis results from the emotion engine and stores them in a database.

[1447] 4. Restaurant Proposals

[1448] The server calls an external restaurant database API based on the user's conditions and emotional state.

[1449] An appropriate restaurant list is generated from the returned data and optimized according to the user's emotional state.

[1450] The suggestion list is sent to the terminal and displayed to the user.

[1451] 5. Generate a teaser message

[1452] The server uses a generation AI to create an invitation message based on the user's information and emotional state.

[1453] The message is sent to the device, where the user can review, edit, and send it through the messaging app.

[1454] 6. Date coordination suggestions

[1455] The server calls a fashion database API based on the user's style information and emotional state, and generates appropriate coordination suggestions.

[1456] The proposed coordinates are sent to the terminal and displayed to the user.

[1457] 7. Final review and feedback

[1458] The user goes on a date based on the provided suggestions and transmits the results to the server as feedback.

[1459] The server analyzes and stores the collected feedback to improve the accuracy of the next suggestion.

[1460] This allows users to receive a range of dating support and specific suggestions tailored to their emotional state.

[1461] The processing flow will be explained below.

[1462] overview

[1463] This invention is a system that provides a series of support to help dates proceed smoothly, and by combining the user's attribute information, relationship information, and budget information with an emotion engine that recognizes the user's emotional state, it makes more personalized suggestions and generates messages.

[1464] System configuration

[1465] This system consists of a terminal operated by the user, a server, and an external API. It also includes an emotion engine that recognizes the user's emotions. The main functions of the system are as follows:

[1466] 1. User registration and login process

[1467] Step 1:

[1468] The device launches the application and displays the login or registration page.

[1469] Step 2:

[1470] The user enters their username, email address, and password.

[1471] Step 3:

[1472] The terminal transmits the input information to the server.

[1473] Step 4:

[1474] The server stores the received information in a database.

[1475] Step 5:

[1476] The server generates an authentication token and sends it to the device.

[1477] Step 6:

[1478] The terminal receives the authentication token and displays the login status to the user.

[1479] 2. Enter user information

[1480] Step 1:

[1481] The terminal displays a screen for the user to enter detailed date information.

[1482] Step 2:

[1483] Users enter the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc.

[1484] Step 3:

[1485] The terminal transmits the input information to the server.

[1486] Step 4:

[1487] The server stores the received information in a database.

[1488] 3. Emotion Engine Recognition

[1489] Step 1:

[1490] The device will ask the user for permission to access the camera and microphone.

[1491] Step 2:

[1492] The user allows camera and microphone access.

[1493] Step 3:

[1494] The device uses a camera and microphone to record the user's facial expressions and voice and transmits them to the emotion engine.

[1495] Step 4:

[1496] The emotion engine analyzes the user's emotional state and sends the results to the server.

[1497] Step 5:

[1498] The server stores the analysis results from the emotion engine in a database.

[1499] 4. Restaurant Proposals

[1500] Step 1:

[1501] The server sets the request parameters based on the user's details and emotional state.

[1502] Step 2:

[1503] The server sends a request to an external restaurant database API.

[1504] Step 3:

[1505] The server parses the data returned from the API.

[1506] Step 4:

[1507] The server generates an appropriate restaurant list from the analysis results and optimizes it according to the user's emotional state.

[1508] Step 5:

[1509] The restaurant list generated by the server is sent to the terminal and displayed to the user.

[1510] 5. Generate a teaser message

[1511] Step 1:

[1512] The terminal sends a request to the server to create a message.

[1513] Step 2:

[1514] The server uses generation AI to generate messages based on the user's attribute information, relationship information, and emotional state.

[1515] Step 3:

[1516] The server generates a message and sends it to the terminal.

[1517] Step 4:

[1518] The terminal displays the generated message to the user.

[1519] Step 5:

[1520] The user reviews and edits the message and sends it using the messaging app.

[1521] 6. Date coordination suggestions

[1522] Step 1:

[1523] The terminal transmits a fashion suggestion request to the server based on the user's attribute information.

[1524] Step 2:

[1525] The server sends a request to an external fashion database API based on the user's style information and emotional state.

[1526] Step 3:

[1527] The server parses the data returned from the API.

[1528] Step 4:

[1529] The server generates appropriate coordination suggestions from the analysis results and optimizes them based on the emotional state.

[1530] Step 5:

[1531] The coordinate proposal generated by the server is sent to the terminal and displayed to the user.

[1532] 7. Final review and feedback

[1533] Step 1:

[1534] The user reviews the provided suggestions and takes the necessary action (reserving a restaurant, sending a message, selecting an outfit).

[1535] Step 2:

[1536] The terminal sends the user's action status to the server.

[1537] Step 3:

[1538] The server tracks and checks the completion status of user actions.

[1539] Step 4:

[1540] The server sends a feedback collection request to the terminal.

[1541] Step 5:

[1542] The user inputs feedback through the terminal and transmits it to the server.

[1543] Step 6:

[1544] The server analyzes and stores the feedback data to improve the accuracy of the next proposal.

[1545] Example 2

[1546] 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."

[1547] When planning a date, there is a lack of personalized suggestions that take into account the user's attributes, relationship information, budget information, and even emotional state. Furthermore, since there is no systematic support that integrates multiple elements, it is difficult for users to plan the best date.

[1548] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1549] In this invention, the server includes means for inputting user attribute information, relationship information, and budget information, means for suggesting appropriate restaurants based on the information input by the user and the user's emotional state, and means for generating an invitation message based on the input information and the user's emotional state, thereby enabling the user to easily plan an optimal date taking into account multiple factors including the attribute information and the user's emotional state.

[1550] "User attribute information" is data that indicates individual characteristics and features of a user, and includes age, gender, occupation, hobbies, and the like.

[1551] "Relationship information" is data indicating the relationship the user has with the person they are dating, and includes friends, business partners, lovers, family, and the like.

[1552] "Budget information" is data regarding the amount of money a user wants to spend on a date.

[1553] "Emotional state" is data that indicates the user's current emotions and moods, and includes positive, negative, neutral, and the like.

[1554] The "suggested restaurant list" is a list of restaurants suitable for a date, generated by the server based on the user's input information and emotional state.

[1555] An "invitation message" is a message for inviting someone on a date, generated using AI generation technology based on the user's attribute information and emotional state.

[1556] "Coordination suggestions" are data that suggest outfits suitable for a date based on the user's style information and emotional state.

[1557] "Server" means a computer system that stores and analyzes data and communicates with external APIs.

[1558] A "terminal" is a device operated by a user, such as a computer, smartphone, or tablet.

[1559] MODE FOR CARRYING OUT THE INVENTION

[1560] The present invention is a system that provides personalized date plans. This system can determine the user's emotional state in addition to user attribute information, relationship information, and budget information, and make appropriate suggestions. The system is primarily composed of a server, a terminal, and an external API. The operation of the system is described in detail below.

[1561] User registration and login process

[1562] The first thing a user does is enter their username, email address, and password into the device, which is then sent to the server, where it is stored in a database and an authentication token is generated and sent to the device.

[1563] Entering user information

[1564] Users select from a list of dating purposes and enter detailed information such as the partner's attributes, relationship status, budget, food preferences, etc. This information is sent from the device to the server and stored in a database.

[1565] Emotion Engine Recognition

[1566] The user's emotional state is collected by showing their facial expressions to the camera or speaking into the microphone. The device sends these images and sounds to the emotion engine for analysis. The analysis results are sent to the server and stored in a database.

[1567] Restaurant suggestions

[1568] The server sets request parameters based on the user's input information and emotional state, and sends a request to an external restaurant database API. It generates an appropriate restaurant list from the returned data and optimizes the list based on the user's emotional state. The optimized restaurant list is sent to the device and displayed to the user.

[1569] Generate an invitation message

[1570] The server uses generative AI technology to create an invitation message based on the user's attribute information, relationship information, and emotional state. The generated message is sent to the device, where the user can review and edit it and send it through the messaging app.

[1571] Date coordination suggestions

[1572] The server generates outfit suggestions based on the user's style information and emotional state using an external fashion database API, and the resulting outfit suggestions are sent to the device and provided to the user.

[1573] Final review and feedback gathering

[1574] After a date, users input their satisfaction and areas for improvement into their device and send the feedback data to the server, which collects and stores the feedback data and uses it to improve the accuracy of future suggestions.

[1575] Examples of concrete examples and prompts

[1576] For example, a user might use the system as follows:

[1577] 1. A user accesses the system and creates an account by entering a username, email address, and password.

[1578] 2. The user enters the details of the date (e.g., budget is under 5,000 yen, food preference is Italian).

[1579] 3. The user smiles at the camera, and the emotion engine recognizes "positive emotion."

[1580] 4. The server generates a list of Italian restaurant suggestions and optimizes it according to the user's emotional state.

[1581] 5. The server uses a generation AI to generate an invitation message saying, "Would you like to join us for some Italian food this weekend?"

[1582] 6. The server suggests fashion coordination that matches the user's taste.

[1583] 7. After the date, the user sends feedback saying, "The date was great, but the restaurant was booked and we had to wait a long time."

[1584] Examples of prompts are:

[1585] 1. "User information: Name = Yamada Taro, Budget = Under 5,000 yen, Food preference = Italian food, Relationship = Friend"

[1586] 2. "Emotional state: Positive"

[1587] 3. "Generate a teaser message."

[1588] In this way, the system can propose personalized date plans to users and provide optimal restaurant recommendations and fashion coordination based on the user's emotional state.

[1589] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1590] The flow of this system's program processing

[1591] Step 1: User registration and login process

[1592] Input: Username, Email Address, Password

[1593] Operation:

[1594] The user enters their username, email address, and password on the device.

[1595] The terminal transmits this information to the server.

[1596] The server receives the transmitted user information and stores it in a database.

[1597] The server generates an authentication token and sends it to the device.

[1598] Output: Authentication token

[1599] Step 2: Enter your user information

[1600] Input: purpose of date, partner's attributes, relationship status, budget, food preferences

[1601] Operation:

[1602] The user inputs the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc. into the device.

[1603] The terminal sends the entered details to the server.

[1604] The server stores the submitted details in a database.

[1605] Output: Saved user details

[1606] Step 3: Recognizing the Emotion Engine

[1607] Input: Video data, audio data

[1608] Operation:

[1609] The user shows their facial expressions to the camera and speaks into the microphone.

[1610] The device collects video and audio and sends it to the emotion engine.

[1611] The emotion engine analyzes video and audio to identify the user's emotional state.

[1612] The server stores the analysis results received from the emotion engine in a database.

[1613] Output: User's emotional state

[1614] Step 4: Restaurant proposal

[1615] Input: User details, emotional state

[1616] Operation:

[1617] The server sets request parameters based on the user's input information and emotional state.

[1618] The server sends a request to an external restaurant database API.

[1619] The server receives the data returned from the external restaurant database API.

[1620] The server optimizes the restaurant list based on the user's emotional state.

[1621] The server transmits the optimized restaurant list to the terminal.

[1622] Output: A list of suggested restaurants

[1623] Step 5: Create a teaser message

[1624] Input: User information, emotional state

[1625] Operation:

[1626] The server creates a prompt for the generative AI model to use.

[1627] The server sends a prompt to the generation AI model, which generates an invitation message.

[1628] The server sends the generated message to the terminal.

[1629] The terminal displays the message to the user, who can then view and edit it.

[1630] The user sends the final message through a messaging app.

[1631] Output: Teaser message

[1632] Step 6: Proposal for a date outfit

[1633] Input: User style information, emotional state

[1634] Operation:

[1635] The server sends a request to an external fashion database API based on the user's style information and emotional state.

[1636] The server generates coordination suggestions based on the data returned from the external fashion database API.

[1637] The server transmits the generated coordination proposal to the terminal.

[1638] The terminal displays the coordination suggestions to the user.

[1639] Output: Date coordination suggestions

[1640] Step 7: Final review and feedback gathering

[1641] Input: Post-date feedback

[1642] Operation:

[1643] The user enters their satisfaction and areas for improvement after the date into the device.

[1644] The terminal transmits the feedback data to the server.

[1645] The server stores the feedback data in a database.

[1646] The server analyzes the feedback data and uses it to improve the accuracy of future proposals.

[1647] Output: Feedback data

[1648] In this way, at each processing step of the system, specific processes such as user input, data collection, analysis, and proposal generation are performed, allowing users to receive personalized dating support.

[1649] (Application example 2)

[1650] 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."

[1651] Conventional dating support systems handle basic data such as user attribute information, relationship information, and budget information, but do not take the user's emotional state into account, resulting in a lack of personalized suggestions and making it difficult to provide optimal suggestions.The present invention analyzes the user's emotional state and reflects this in the suggestions, enabling more personalized date plans to be proposed, thereby improving user satisfaction.

[1652] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1653] In this invention, the server includes means for recognizing a user's emotional state using an emotion engine that analyzes the user's emotional state, means for storing the analysis results from the emotion engine in a database, means for optimizing a suggested restaurant list based on the user's emotional state, and means for generating coordination suggestions based on the user's style information and emotional state using a fashion database API, thereby enabling personalized suggestions based on the user's emotions.

[1654] "User attribute information" is data that indicates personal characteristics of a user, such as age, gender, and hobbies.

[1655] "Relationship information" is data indicating the relationship between the user and the dater (e.g., first meeting, long-term relationship, friends).

[1656] "Budget information" is data indicating the amount of money a user can spend on a date.

[1657] An "emotion engine" is software or an algorithm that analyzes data such as a user's facial expressions and voice, and recognizes their emotional state (happiness, sadness, tension, etc.).

[1658] The "suggested restaurant list" is a list of restaurants selected based on the user's input information and emotional state.

[1659] An "invitation message" is a message created for the purpose of inviting someone on a date.

[1660] "Coordination suggestions" are suggestions for combinations of clothing, accessories, etc. that are suited to the user's style information and emotional state.

[1661] "Feedback data" refers to information such as evaluations and opinions provided by users after a date, and is data that is used to improve the accuracy of suggestions from the next date onwards.

[1662] The "restaurant database API" is an interface for communicating with an external restaurant information database and obtaining restaurant information.

[1663] "Generative AI technology" is an artificial intelligence technology that generates natural language based on large amounts of data.

[1664] The "Fashion Database API" is an interface for communicating with external fashion information databases and obtaining information on fashion items.

[1665] This invention is a system for supporting users in dating, and is composed of the following main elements and procedures. Specifically, the system processes and shares data while communicating with the server, terminals, and users, to propose date plans and collect feedback.

[1666] 1. Enter and save user information

[1667] The user inputs attribute information such as the purpose of the date, relationship status, budget, and food preferences from the terminal. The terminal sends the input information to the server, which then stores the information in a database.

[1668] 2. Emotion Engine Recognition

[1669] The user analyzes their emotional state using the smartphone's camera and microphone. The user's facial expressions and voice are then analyzed by the emotion engine, and their emotional state is recognized. The analysis results are sent to the server and stored in a database.

[1670] 3. Restaurant proposals and optimization

[1671] The server calls an external restaurant database API based on the user's input information and emotional state. Based on the returned information, it generates a restaurant list that takes into account the analysis results of the emotion engine and displays it to the user. This allows it to suggest restaurants that best suit the user's emotional state.

[1672] 4. Generate a teaser message

[1673] Generative AI technology (e.g., natural language generation models) is used to generate invitation messages based on the user's attributes, relationship information, and emotional state. The generated messages are sent to the device, where the user can review and edit them before sending them through a messaging app.

[1674] 5. Date coordination suggestions

[1675] The server calls a fashion database API based on the user's style information, date situation, and emotional state to generate outfit suggestions, which are then sent to the device and displayed to the user.

[1676] 6. Collect and use feedback

[1677] After the date, users provide feedback on the application, which the server analyzes and stores in a database to improve the accuracy of future suggestions.

[1678] Specific examples

[1679] Software and hardware used

[1680] Emotion engine: Microsoft Azure Face API and Amazon Rekognition

[1681] Restaurant database API: Google Places API, Tabelog API

[1682] Natural Language Generation Technology: OpenAI's GPT-3

[1683] Fashion database API: Rakuten Fashion API

[1684] Device: Smartphone

[1685] Server: General web server

[1686] Examples of prompt statements

[1687] The purpose of the date is an anniversary, the relationship is long-term, and the user's emotional state is joy. Based on this information, please generate an invitation message to send to your partner.

[1688] In this way, the system of the present invention can take into account the user's emotional state, thereby realizing more personalized date plan suggestions and improving user satisfaction.

[1689] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1690] Step 1:

[1691] Input: The user enters demographic information such as the purpose of the date, relationship status, budget, and food preferences.

[1692] How it works: The device collects information through a user input form and sends it to the server.

[1693] Output: The server stores the received information in a database.

[1694] Step 2:

[1695] Input: Video and audio data from the user's camera and microphone.

[1696] How it works: The device uses the camera and microphone to send data to the emotion engine, which analyzes the user's emotional state. The server then stores the analysis results in a database.

[1697] Output: An analysis of the user's emotional state.

[1698] Step 3:

[1699] Input: User demographic information, relationship information, budget information, and emotional state.

[1700] How it works: The server calls an external restaurant database API to retrieve a list of appropriate restaurants based on the input information. The retrieved list is then optimized based on the user's emotional state.

[1701] Output: A list of restaurants that fit your emotional state.

[1702] Step 4:

[1703] Input: User attribute information, relationship information, and emotional state.

[1704] How it works: The server uses generative AI technology to generate a prompt. For example, "The purpose of the date is an anniversary, the relationship is long-term, and the user's emotional state is joy. Based on this information, please generate an invitation message to send to the other person."

[1705] Output: The generated teaser message.

[1706] Step 5:

[1707] Input: User's demographic information, style information, and emotional state.

[1708] How it works: The server calls the fashion database API and generates outfit suggestions suitable for the user.

[1709] Output: Coordination suggestions.

[1710] Step 6:

[1711] Input: Feedback information entered by the user after the date.

[1712] How it works: The server collects feedback information and stores it in a database to improve the accuracy of suggestions next time.

[1713] Output: Feedback data is accumulated to improve the accuracy of future suggestions.

[1714] 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.

[1715] 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.

[1716] 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.

[1717] [Fourth embodiment]

[1718] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1719] 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.

[1720] 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).

[1721] 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.

[1722] 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.

[1723] 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).

[1724] 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.

[1725] 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.

[1726] 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.

[1727] 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.

[1728] 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.

[1729] 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.

[1730] 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."

[1731] overview

[1732] The present invention is a system that provides a series of support to ensure a date goes smoothly, suggesting appropriate restaurants and generating invitation messages based on the user's attribute information, relationship information, and budget information, and also proposing outfits for the date.

[1733] System Configuration

[1734] This system consists of a terminal operated by the user, a server, and an external API. The main functions of the system are as follows:

[1735] 1. Enter and save user information

[1736] The user inputs the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc. into the device.

[1737] The terminal sends the input information to the server, and the server stores the received information in a database.

[1738] 2. Restaurant proposals

[1739] The server calls an external API (e.g., restaurant database API) based on the user's input information and generates an appropriate restaurant list.

[1740] A list of suggested restaurants is sent to the terminal and displayed to the user.

[1741] 3. Generate a teaser message

[1742] The server uses AI technology to generate an invitation message based on the user's attribute information and relationship information.

[1743] The message created is sent to the device, and the user can check and edit the message and send it via a messaging app (e.g., LINE).

[1744] 4. Date coordination suggestions

[1745] The server uses an external API (e.g., a fashion database API) to generate outfits that suit the user's style and the date situation.

[1746] The proposed coordinates are sent to the terminal and provided to the user.

[1747] 5. Collect and use feedback

[1748] The server collects feedback from the user after the date has taken place.

[1749] The feedback data will be used to improve the accuracy of proposals from next time onwards.

[1750] Specific examples of program processing

[1751] 1. User registration and login process

[1752] The device prompts the user to enter their username, email address, and password, and sends them to the server.

[1753] The server saves the input data in a database and performs login authentication.

[1754] An authentication token is generated and sent to the terminal.

[1755] 2. Enter your user information

[1756] The user enters the date details into the terminal.

[1757] The device sends the entered details to the server, where they are stored in a database.

[1758] 3. Restaurant proposals

[1759] The server calls an external restaurant database API based on the user's criteria.

[1760] Appropriate restaurants are selected from the returned data and a list of suggestions is generated.

[1761] The suggestion list is sent to the terminal and displayed to the user.

[1762] 4. Generate a teaser message

[1763] The server uses a generation AI to create an invitation message based on user information.

[1764] The message is sent to the device, where the user can review, edit, and send it through the messaging app.

[1765] 5. Date coordination suggestions

[1766] The server calls the ZOZO API and other services based on the user's style information to generate appropriate outfit suggestions.

[1767] The proposed coordinates are sent to the terminal and displayed to the user.

[1768] 6. Final review and feedback

[1769] The user actually goes on a date based on the provided suggestions and sends the results to the server as feedback.

[1770] The server analyzes the collected feedback to improve the accuracy of the next proposal.

[1771] This allows users to receive a range of support regarding dating and specific suggestions to make their date a success.

[1772] The processing flow will be explained below.

[1773] Program processing flow

[1774] 1. User registration and login process

[1775] Step 1:

[1776] The terminal boots up and displays a login or registration page.

[1777] Step 2:

[1778] The user enters their username, email address, and password.

[1779] Step 3:

[1780] The terminal transmits the user's input information to the server.

[1781] Step 4:

[1782] The server receives the input information and stores it in a database.

[1783] Step 5:

[1784] The server generates an authentication token and sends it to the device.

[1785] Step 6:

[1786] The terminal receives the authentication token and displays the login status to the user.

[1787] 2. Enter user information

[1788] Step 1:

[1789] The device displays a screen for the user to enter detailed information about the date.

[1790] Step 2:

[1791] Users enter the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc.

[1792] Step 3:

[1793] The terminal transmits the input information to the server.

[1794] Step 4:

[1795] The server receives the user information and stores it in a database.

[1796] 3. Restaurant proposals

[1797] Step 1:

[1798] The server sets the request parameters based on the user input information.

[1799] Step 2:

[1800] The server sends a request to an external restaurant database API.

[1801] Step 3:

[1802] The server parses the data returned from the API.

[1803] Step 4:

[1804] The server generates an appropriate restaurant list from the analysis results.

[1805] Step 5:

[1806] The restaurant list generated by the server is sent to the terminal and displayed to the user.

[1807] 4. Generate a teaser message

[1808] Step 1:

[1809] The terminal sends a request to the server to create a message.

[1810] Step 2:

[1811] The server uses generation AI to generate messages based on the other person's attributes and relationship.

[1812] Step 3:

[1813] The server generates a message and sends it to the terminal.

[1814] Step 4:

[1815] The terminal displays the generated message to the user.

[1816] Step 5:

[1817] The user reviews and edits the message and sends it using the messaging app.

[1818] 5. Date coordination suggestions

[1819] Step 1:

[1820] The terminal transmits a fashion suggestion request to the server based on the user's attribute information.

[1821] Step 2:

[1822] The server sends a request to an external fashion database API based on the user's style information.

[1823] Step 3:

[1824] The server parses the data returned from the API.

[1825] Step 4:

[1826] The server generates appropriate coordination suggestions from the analysis results.

[1827] Step 5:

[1828] The coordinate proposal generated by the server is sent to the terminal and displayed to the user.

[1829] 6. Final review and feedback

[1830] Step 1:

[1831] The user reviews the provided suggestions and takes the necessary action (reserving a restaurant, sending a message, selecting an outfit).

[1832] Step 2:

[1833] The terminal sends the user's action status to the server.

[1834] Step 3:

[1835] The server tracks and checks the completion status of user actions.

[1836] Step 4:

[1837] The server sends a feedback collection request to the terminal.

[1838] Step 5:

[1839] The user inputs feedback through the terminal and transmits it to the server.

[1840] Step 6:

[1841] The server analyzes and stores the feedback data to improve the accuracy of future proposals.

[1842] Example 1

[1843] 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."

[1844] When planning a date, users must consider various factors (such as the partner's preferences, the relationship, and budget), which is a time-consuming and labor-intensive process. Furthermore, a wide range of support is required, such as choosing the right restaurant, the content of the invitation, and suggestions for appropriate attire for the date. However, there is no system that can provide all of these elements in one place and efficiently support users in planning a date.

[1845] 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.

[1846] In this invention, the server includes means for inputting user attribute information, relationship information, and budget information, means for utilizing an external API to suggest restaurants, means for generating invitation messages using a generative AI model, means for utilizing an external API to suggest outfits, and means for collecting feedback on the user's date actions. This allows the user to receive a series of support through their device, enabling date planning to proceed smoothly and efficiently.

[1847] "User attribute information" is information indicating individual characteristics of a user, such as age, sex, hobbies, preferences, and occupation.

[1848] "Relationship information" is information indicating the relationship between the user and the date (for example, friends, colleagues, lovers, etc.).

[1849] "Budget information" is information that indicates the range of expenses that can be spent on a date.

[1850] The "means for suggesting restaurants" refers to a function for recommending appropriate restaurants based on the conditions entered by the user.

[1851] An "external API" is a means of referring to an interface for connecting with other services or databases.

[1852] The "suggested restaurant list" is a list of restaurants recommended based on the user's criteria.

[1853] "Means for generating an invitation message" refers to means for using generative AI technology to create an invitation message that meets the user's conditions.

[1854] "Means of using an external API to suggest outfits" refers to a function that links with an external fashion database to recommend outfits suitable for a date.

[1855] The "means for collecting feedback on the user's dating actions" refers to a function for collecting feedback such as the results and impressions of a date after the user has completed the date.

[1856] An "authentication token" is a security token issued to maintain a user's logged-in state.

[1857] A "generative AI model" is an artificial intelligence model that generates appropriate responses and suggestions based on user input data and conditions.

[1858] MODE FOR CARRYING OUT THE INVENTION

[1859] This invention is a system that provides a series of support functions to help users efficiently plan dates. The system consists of a terminal operated by the user, a server, and an external API. The main functions of this system include inputting and saving user information, suggesting restaurants, generating invitation messages, suggesting date coordination, and collecting feedback.

[1860] Entering and saving user information

[1861] The device prompts the user for their username, email address, and password, and sends them to the server, which stores the information in a database and authenticates the login.

[1862] The user inputs detailed information such as the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc. into the device, which then sends the information to the server and stores it in a database.

[1863] Restaurant suggestions

[1864] The server calls an external restaurant database API (for example, a restaurant API with a general name) based on the user's input information.

[1865] The server selects appropriate restaurants from the returned data and generates a list of suggestions, which is then sent to the terminal and displayed to the user.

[1866] Generate an invitation message

[1867] The server uses a generative AI model to create an invitation message based on the user's attribute information and relationship information. The name of the specific generative AI model will be generalized, for example, called "message generation AI technology."

[1868] The generated message is sent to the device, where it is edited and confirmed by the user and then sent via a messaging app (e.g., a generic messaging app).

[1869] Date coordination suggestions

[1870] The server calls an external fashion database API (e.g., a fashion API with a general name) based on the user's style information and suggests appropriate outfits.

[1871] The proposed coordinate information is sent to the terminal and displayed to the user.

[1872] Collecting and using feedback

[1873] After the user has gone on a date, the user transmits the results to the server as feedback.

[1874] The server analyzes the collected feedback and stores it in a database to improve the accuracy of suggestions next time.

[1875] Specific examples

[1876] Example of entering and saving user information

[1877] The user logs in as "Taro Tanaka" and enters date details. For example, the user might enter "Purpose of the date: To deepen intimacy," "Partner's attributes: Female in her 20s," "Relationship type: Colleague," "Budget: 3,000 yen," and "Food preference: Japanese food."

[1878] Specific examples of restaurant proposals

[1879] The server retrieves restaurants that meet the user's criteria from the restaurant API and generates a list of suggestions. For example, it suggests three Japanese restaurants.

[1880] Example of creating a teaser message

[1881] The server uses the generative AI model to generate a message such as, "Hello, would you like to go out to dinner with me this weekend? I have a Japanese restaurant I'd like to recommend."

[1882] Specific examples of date coordination suggestions

[1883] The server uses a fashion API to suggest "a casual jacket and chinos" to the user.

[1884] Prompt Sentence Examples

[1885] "My date is with a colleague, my budget is 3000 yen, and I like Japanese food. Please suggest a suitable restaurant."

[1886] "Generate a teaser message based on the user's information. His hobby is the outdoors, and he's been busy lately."

[1887] This allows users to receive a series of support related to dates through the system, significantly reducing the time and effort required to plan and carry out dates.

[1888] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1889] Program processing flow

[1890] Step 1: User registration and login process

[1891] The user enters their username, email address, and password and sends them to the terminal. Input data: username, email address, password.

[1892] The terminal sends the entered user data to the server. Data processing: Formats it as an HTTP request.

[1893] The server saves the received data in the database and performs login authentication. Data processing: Adds a record to the database and generates an authentication token. Output: Authentication token.

[1894] The terminal receives the authentication token and changes the user status to logged in. Specific operation: "Login successful" is displayed on the screen.

[1895] Step 2: Enter and save your user information

[1896] The user inputs detailed information about the date (purpose, partner's attributes, relationship, budget, food preferences, etc.) into the terminal. Input data: purpose of the date, partner's attributes, relationship, budget, food preferences.

[1897] The device sends the entered details to the server. Data processing: Formatting as an HTTP request.

[1898] The server saves the received data in the database. Data processing: Adds a record to the database. Output: Confirms that the data is saved.

[1899] Step 3: Restaurant proposal

[1900] The server calls an external restaurant database API based on the user's input information. Input data: User's conditions.

[1901] The server selects appropriate restaurants based on the data returned from the API and generates a list of suggested restaurants. Output data: List of suggested restaurants.

[1902] Data processing: Analyze the returned JSON data and extract restaurants that meet the conditions.

[1903] The terminal receives the recommendation list sent from the server and displays it to the user. Specific operation: The "recommended restaurant list" is displayed on the screen.

[1904] Step 4: Create a teaser message

[1905] The server uses a generative AI model to create an invitation message based on user information. Input data: User attribute information and relationship information. Output data: Invitation message.

[1906] Data processing: Generate messages using generative AI models.

[1907] The device receives the message sent from the server and displays it to the user. Specific operation: An "invitation message" is displayed on the screen.

[1908] The user sends the message they have reviewed and edited through a messaging app (e.g., a generic messaging app). Specific behavior: The messaging app is launched and the message is sent.

[1909] Step 5: Proposal for a date outfit

[1910] The server calls an external fashion database API based on the user's style information and suggests appropriate outfits. Input data: User's style information. Output data: Suggested outfits.

[1911] Data processing: Analyze the response data from the fashion API and extract outfits that suit the user.

[1912] The terminal receives the coordination suggestions sent from the server and displays them to the user. Specific operation: "Recommended coordination" is displayed on the screen.

[1913] Step 6: Collect and use feedback

[1914] After the user has gone on a date, the results and impressions are sent to the server as feedback via the device. Input data: Feedback content.

[1915] The server collects and analyzes the feedback. Data processing: Analyzes the feedback data and stores it in a database. Output data: Saves the analysis results and feedback.

[1916] The server analyzes the collected feedback and updates the system to improve the accuracy of the next suggestion. Specific operation: Improved algorithm, improved suggestion accuracy.

[1917] (Application example 1)

[1918] 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."

[1919] In recent years, when planning a date, selecting an appropriate restaurant, writing an invitation message, and suggesting appropriate outfits for the date have become important. However, planning everything on your own is time-consuming, and there is a lack of support systems that can provide effective suggestions. The present invention aims to provide a support system that smoothly plans and executes such dates, allowing users to easily plan dates.

[1920] 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.

[1921] In this invention, the server includes a means for inputting a user's attribute information, relationship information, and budget information, a means for suggesting appropriate restaurants based on the information input by the user, and a means for displaying the generated list of suggested restaurants to the user. This allows the user to easily receive automatic suggestions for restaurants and date plans that suit them. The server also includes a means for generating an invitation message based on the user's input information, a means for displaying the generated invitation message to the user, a means for assisting with restaurant reservations via a smartphone application based on the user information, a means for inputting a prompt into a generation AI model to generate an invitation message, and a means for enabling the generated message to be sent via a messaging app. This allows the user to easily and effectively create and send an invitation message to the other party. The server also includes a means for acquiring the user's style information and suggesting outfits using a fashion database API, and a means for notifying the user's smartphone of the suggested outfits. This allows the user to receive suggestions for the perfect outfit for a date.

[1922] "User attribute information" refers to personal information such as the user's age, gender, hobbies, and preferences.

[1923] "Relationship information" is information that indicates the depth and attributes of the relationship between the user and the date partner.

[1924] "Budget information" is information about the amount of money the user plans to spend on a date.

[1925] The "means for suggesting restaurants" is a function that selects appropriate restaurants based on the user's budget information and preferences and generates a list.

[1926] The "suggested restaurant list" is a list of restaurants generated to be suggested to the user.

[1927] The "means for generating an invitation message" is a function that automatically creates a date invitation message based on the user's attribute information and relationship information.

[1928] The "Fashion Database API" is an external API that provides appropriate fashion coordination based on the user's style information.

[1929] A "generative AI model" is an artificial intelligence algorithm that takes user input and generates appropriate output based on a specific task.

[1930] A "prompt sentence" is an input sentence given to an AI model, an instruction sentence that starts the generation process.

[1931] A "smartphone application" is application software that runs on a mobile device that a user uses on a daily basis.

[1932] "Coordination suggestions" are suggestions for appropriate clothing and accessories that match the user's preferences and the situation of the date.

[1933] MODE FOR CARRYING OUT THE INVENTION

[1934] This invention is a system that supports users in smoothly planning and executing dates. This system is composed of the following components:

[1935] System Configuration

[1936] This system consists of a smartphone operated by the user, a server, and an external API.

[1937] Hardware used

[1938] Smartphone: A device operated by a user

[1939] Server: A central server that processes and stores data

[1940] Software used

[1941] Firebase Authentication: A service for user registration and login authentication

[1942] Google Places API: An external API for retrieving data from the restaurant database

[1943] OpenAI GPT-3: A generative AI model used to generate teaser messages

[1944] ZOZO API: An external database API used to suggest fashion coordination

[1945] Firebase Firestore: A service for storing user information and managing databases

[1946] Specific explanation of the process

[1947] User Registration and Login

[1948] The server receives the username, email address, and password entered by the user on the smartphone, authenticates this information using Firebase Authentication, and stores it in Firebase Firestore. If authentication is successful, the server generates an authentication token and sends it back to the smartphone.

[1949] Entering user information

[1950] Users enter details of their dates (purpose, partner attributes, budget, food preferences, etc.) on their smartphones, and this information is stored in Firebase Firestore in real time.

[1951] Restaurant suggestions

[1952] The server calls the Google Places API based on the user's budget and preferences to retrieve a list of suitable restaurants, which is then filtered and displayed on the user's smartphone as a suggested restaurant list.

[1953] Generate an invitation message

[1954] The server inputs a prompt into the generative AI model, OpenAI GPT-3, to generate a teaser message. An example of this prompt is as follows:

[1955] "Hi {name}! How about meeting for dinner next Friday at a new cafe I found? It's called {cafe_name} and has great reviews and a chic atmosphere. How about {time}? I'd love to join you!"

[1956] The generated message is sent to the user's smartphone, where the user can review, edit, and send it via a messaging app.

[1957] Date coordination suggestions

[1958] The server acquires the user's style information and uses the ZOZO API, a fashion database API, to generate appropriate outfit suggestions. These suggestions are then sent to the user's smartphone and displayed to the user.

[1959] Collecting and using feedback

[1960] Users enter their feedback after the date on their smartphone and send it to the server, which stores the feedback data in Firebase Firestore and analyzes it to improve the accuracy of future suggestions.

[1961] This allows users to receive a series of support regarding dating and get specific suggestions to make their date a success.

[1962] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1963] Step 1:

[1964] A user launches the application using a smartphone and registers by entering their username, email address, and password. The entered information is sent to the server, authenticated using Firebase Authentication, and stored in Firebase Firestore. If authentication is successful, the server generates an authentication token and sends it back to the smartphone. The input data is the user's personal information, and the output is an authentication token.

[1965] Step 2:

[1966] Users input date details (purpose, partner attributes, budget, food preferences, etc.) on their smartphones. The input details are sent to the server in real time and stored in Firebase Firestore. The input data is the date details, and the output is the information stored in the database.

[1967] Step 3:

[1968] The server calls the Google Places API based on the budget information and food preferences entered by the user to obtain an appropriate restaurant list. The restaurant data obtained from the API is filtered to generate an appropriate restaurant list. The generated suggested restaurant list is sent to the smartphone and displayed to the user. The input data is the user's conditions and restaurant data from the API, and the output is the suggested restaurant list.

[1969] Step 4:

[1970] The server inputs a prompt into OpenAI GPT-3 based on the user's attribute information and relationship information to generate an invitation message. The generated message is sent to the smartphone. The user can review and edit the message and send it via a messaging app such as LINE. The input data are the user's attribute information, relationship information, and prompt, and the output is the generated invitation message. Specific examples of prompts are as follows:

[1971] "Hi {name}! How about meeting for dinner next Friday at a new cafe I found? It's called {cafe_name} and has great reviews and a chic atmosphere. How about {time}? I'd love to join you!"

[1972] Step 5:

[1973] The server acquires the user's style information and uses a fashion database API (e.g., the ZOZO API) to suggest outfits. The suggested outfits are sent to the user's smartphone and notified to the user. The input data is the user's style information and data from the fashion database, and the output is the suggested outfits.

[1974] Step 6:

[1975] After a date, users send their feedback on the date to the server via their smartphone. The server stores this feedback data in Firebase Firestore and analyzes it to improve the accuracy of suggestions for the next date. The input data is the user's feedback, and the output is the analyzed data and improvements to the accuracy of suggestions.

[1976] 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.

[1977] overview

[1978] This invention is a system that provides a series of support to help dates proceed smoothly, and by combining the user's attribute information, relationship information, and budget information with an emotion engine that recognizes the user's emotional state, it makes more personalized suggestions and generates messages.

[1979] System configuration

[1980] This system consists of a terminal operated by the user, a server, and an external API. It also includes an emotion engine that recognizes the user's emotions. The main functions of the system are as follows:

[1981] 1. Enter and save user information

[1982] The user inputs the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc. into the device.

[1983] The terminal sends the input information to the server, and the server stores the received information in a database.

[1984] 2. Emotion Engine Recognition

[1985] The device uses a camera and microphone to analyze the user's emotional state using an emotion engine.

[1986] The server receives the analysis results from the emotion engine and stores them in a database.

[1987] 3. Restaurant proposals

[1988] The server sets request parameters based on the user's input information and emotional state.

[1989] The server sends a request to an external restaurant database API.

[1990] An appropriate restaurant list is generated from the returned data and optimized according to the user's emotional state.

[1991] A list of suggested restaurants is sent to the terminal and displayed to the user.

[1992] 4. Generate a teaser message

[1993] The server uses generative AI technology to generate an invitation message based on the user's attribute information, relationship information, and emotional state.

[1994] The generated message is sent to the device, where the user can review and edit it and send it through the messaging app.

[1995] 5. Date coordination suggestions

[1996] The server uses an external fashion database API to generate outfits that suit the user's style, date situation, and emotional state.

[1997] The proposed coordinates are sent to the terminal and provided to the user.

[1998] 6. Collect and use feedback

[1999] The server collects feedback from the user after the date has taken place.

[2000] The feedback data will be used to improve the accuracy of proposals from next time onwards.

[2001] Specific examples of program processing

[2002] 1. User registration and login process

[2003] The device prompts the user to enter their username, email address, and password, and sends them to the server.

[2004] The server receives the input data and stores it in a database.

[2005] An authentication token is generated and sent to the terminal.

[2006] 2. Enter your user information

[2007] The user enters the date details into the terminal.

[2008] The device sends the entered details to the server and stores them in a database.

[2009] 3. Emotion Engine Recognition

[2010] The device uses a camera and microphone to have the emotion engine analyze the user's emotional state.

[2011] The server receives the analysis results from the emotion engine and stores them in a database.

[2012] 4. Restaurant Proposals

[2013] The server calls an external restaurant database API based on the user's conditions and emotional state.

[2014] An appropriate restaurant list is generated from the returned data and optimized according to the user's emotional state.

[2015] The suggestion list is sent to the terminal and displayed to the user.

[2016] 5. Generate a teaser message

[2017] The server uses a generation AI to create an invitation message based on the user's information and emotional state.

[2018] The message is sent to the device, where the user can review, edit, and send it through the messaging app.

[2019] 6. Date coordination suggestions

[2020] The server calls a fashion database API based on the user's style information and emotional state, and generates appropriate coordination suggestions.

[2021] The proposed coordinates are sent to the terminal and displayed to the user.

[2022] 7. Final review and feedback

[2023] The user goes on a date based on the provided suggestions and transmits the results to the server as feedback.

[2024] The server analyzes and stores the collected feedback to improve the accuracy of the next suggestion.

[2025] This allows users to receive a range of dating support and specific suggestions tailored to their emotional state.

[2026] The processing flow will be explained below.

[2027] overview

[2028] This invention is a system that provides a series of support to help dates proceed smoothly, and by combining the user's attribute information, relationship information, and budget information with an emotion engine that recognizes the user's emotional state, it makes more personalized suggestions and generates messages.

[2029] System configuration

[2030] This system consists of a terminal operated by the user, a server, and an external API. It also includes an emotion engine that recognizes the user's emotions. The main functions of the system are as follows:

[2031] 1. User registration and login process

[2032] Step 1:

[2033] The device launches the application and displays the login or registration page.

[2034] Step 2:

[2035] The user enters their username, email address, and password.

[2036] Step 3:

[2037] The terminal transmits the input information to the server.

[2038] Step 4:

[2039] The server stores the received information in a database.

[2040] Step 5:

[2041] The server generates an authentication token and sends it to the device.

[2042] Step 6:

[2043] The terminal receives the authentication token and displays the login status to the user.

[2044] 2. Enter user information

[2045] Step 1:

[2046] The terminal displays a screen for the user to enter detailed date information.

[2047] Step 2:

[2048] Users enter the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc.

[2049] Step 3:

[2050] The terminal transmits the input information to the server.

[2051] Step 4:

[2052] The server stores the received information in a database.

[2053] 3. Emotion Engine Recognition

[2054] Step 1:

[2055] The device will ask the user for permission to access the camera and microphone.

[2056] Step 2:

[2057] The user allows camera and microphone access.

[2058] Step 3:

[2059] The device uses a camera and microphone to record the user's facial expressions and voice and transmits them to the emotion engine.

[2060] Step 4:

[2061] The emotion engine analyzes the user's emotional state and sends the results to the server.

[2062] Step 5:

[2063] The server stores the analysis results from the emotion engine in a database.

[2064] 4. Restaurant Proposals

[2065] Step 1:

[2066] The server sets the request parameters based on the user's details and emotional state.

[2067] Step 2:

[2068] The server sends a request to an external restaurant database API.

[2069] Step 3:

[2070] The server parses the data returned from the API.

[2071] Step 4:

[2072] The server generates an appropriate list of restaurants based on the analysis results and optimizes it according to the user's emotional state.

[2073] Step 5:

[2074] The restaurant list generated by the server is sent to the terminal and displayed to the user.

[2075] 5. Generate a teaser message

[2076] Step 1:

[2077] The terminal sends a request to the server to create a message.

[2078] Step 2:

[2079] The server uses generation AI to generate messages based on the user's attribute information, relationship information, and emotional state.

[2080] Step 3:

[2081] The server generates a message and sends it to the terminal.

[2082] Step 4:

[2083] The terminal displays the generated message to the user.

[2084] Step 5:

[2085] The user reviews and edits the message and sends it using the messaging app.

[2086] 6. Date coordination suggestions

[2087] Step 1:

[2088] The terminal transmits a fashion suggestion request to the server based on the user's attribute information.

[2089] Step 2:

[2090] The server sends a request to an external fashion database API based on the user's style information and emotional state.

[2091] Step 3:

[2092] The server parses the data returned from the API.

[2093] Step 4:

[2094] The server generates appropriate coordination suggestions from the analysis results and optimizes them based on the emotional state.

[2095] Step 5:

[2096] The coordinate proposal generated by the server is sent to the terminal and displayed to the user.

[2097] 7. Final review and feedback

[2098] Step 1:

[2099] The user reviews the provided suggestions and takes the necessary action (reserving a restaurant, sending a message, selecting an outfit).

[2100] Step 2:

[2101] The terminal sends the user's action status to the server.

[2102] Step 3:

[2103] The server tracks and checks the completion status of user actions.

[2104] Step 4:

[2105] The server sends a feedback collection request to the terminal.

[2106] Step 5:

[2107] The user inputs feedback through the terminal and transmits it to the server.

[2108] Step 6:

[2109] The server analyzes and stores the feedback data to improve the accuracy of the next proposal.

[2110] Example 2

[2111] 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."

[2112] When planning a date, there is a lack of personalized suggestions that take into account the user's attributes, relationship information, budget information, and even emotional state. Furthermore, since there is no systematic support that integrates multiple elements, it is difficult for users to plan the best date.

[2113] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2114] In this invention, the server includes means for inputting user attribute information, relationship information, and budget information, means for suggesting appropriate restaurants based on the information input by the user and the user's emotional state, and means for generating an invitation message based on the input information and the user's emotional state, thereby enabling the user to easily plan an optimal date taking into account multiple factors including the attribute information and the user's emotional state.

[2115] "User attribute information" is data that indicates individual characteristics and features of a user, and includes age, gender, occupation, hobbies, and the like.

[2116] "Relationship information" is data indicating the relationship the user has with the person they are dating, and includes friends, business partners, lovers, family, and the like.

[2117] "Budget information" is data regarding the amount of money a user wants to spend on a date.

[2118] "Emotional state" is data that indicates the user's current emotions and moods, and includes positive, negative, neutral, and the like.

[2119] The "suggested restaurant list" is a list of restaurants suitable for a date, generated by the server based on the user's input information and emotional state.

[2120] An "invitation message" is a message for inviting someone on a date, generated using AI generation technology based on the user's attribute information and emotional state.

[2121] "Coordination suggestions" are data that suggest outfits suitable for a date based on the user's style information and emotional state.

[2122] "Server" means a computer system that stores and analyzes data and communicates with external APIs.

[2123] A "terminal" is a device operated by a user, such as a computer, smartphone, or tablet.

[2124] MODE FOR CARRYING OUT THE INVENTION

[2125] The present invention is a system that provides personalized date plans. This system can determine the user's emotional state in addition to user attribute information, relationship information, and budget information, and make appropriate suggestions. The system is primarily composed of a server, a terminal, and an external API. The operation of the system is described in detail below.

[2126] User registration and login process

[2127] The first thing a user does is enter their username, email address, and password into the device, which is then sent to the server, where it is stored in a database and an authentication token is generated and sent to the device.

[2128] Entering user information

[2129] Users select from a list of dating purposes and enter detailed information such as the partner's attributes, relationship status, budget, food preferences, etc. This information is sent from the device to the server and stored in a database.

[2130] Emotion Engine Recognition

[2131] The user's emotional state is collected by showing their facial expressions to the camera or speaking into the microphone. The device sends these images and sounds to the emotion engine for analysis. The analysis results are sent to the server and stored in a database.

[2132] Restaurant suggestions

[2133] The server sets request parameters based on the user's input information and emotional state, and sends a request to an external restaurant database API. It generates an appropriate restaurant list from the returned data and optimizes the list based on the user's emotional state. The optimized restaurant list is sent to the device and displayed to the user.

[2134] Generate an invitation message

[2135] The server uses generative AI technology to create an invitation message based on the user's attribute information, relationship information, and emotional state. The generated message is sent to the device, where the user can review and edit it and send it through the messaging app.

[2136] Date coordination suggestions

[2137] The server generates outfit suggestions based on the user's style information and emotional state using an external fashion database API, and the resulting outfit suggestions are sent to the device and provided to the user.

[2138] Final review and feedback gathering

[2139] After a date, users input their satisfaction and areas for improvement into their device and send the feedback data to the server, which collects and stores the feedback data and uses it to improve the accuracy of future suggestions.

[2140] Examples of concrete examples and prompts

[2141] For example, a user might use the system as follows:

[2142] 1. A user accesses the system and creates an account by entering a username, email address, and password.

[2143] 2. The user enters the details of the date (e.g., budget is under 5,000 yen, food preference is Italian).

[2144] 3. The user smiles at the camera, and the emotion engine recognizes "positive emotion."

[2145] 4. The server generates a list of Italian restaurant suggestions and optimizes it according to the user's emotional state.

[2146] 5. The server uses a generation AI to generate an invitation message saying, "Would you like to join us for some Italian food this weekend?"

[2147] 6. The server suggests fashion coordination that matches the user's taste.

[2148] 7. After the date, the user sends feedback saying, "The date was great, but the restaurant was booked and we had to wait a long time."

[2149] Examples of prompts are:

[2150] 1. "User information: Name = Yamada Taro, Budget = Under 5,000 yen, Food preference = Italian food, Relationship = Friend"

[2151] 2. "Emotional state: Positive"

[2152] 3. "Generate a teaser message."

[2153] In this way, the system can propose personalized date plans to users and provide optimal restaurant recommendations and fashion coordination based on the user's emotional state.

[2154] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2155] The flow of this system's program processing

[2156] Step 1: User registration and login process

[2157] Input: Username, Email Address, Password

[2158] Operation:

[2159] The user enters their username, email address, and password on the device.

[2160] The terminal transmits this information to the server.

[2161] The server receives the transmitted user information and stores it in a database.

[2162] The server generates an authentication token and sends it to the device.

[2163] Output: Authentication token

[2164] Step 2: Enter your user information

[2165] Input: purpose of date, partner's attributes, relationship status, budget, food preferences

[2166] Operation:

[2167] The user inputs the purpose of the date, the partner's attributes, relationship status, budget, food preferences, etc. into the device.

[2168] The terminal sends the entered details to the server.

[2169] The server stores the submitted details in a database.

[2170] Output: Saved user details

[2171] Step 3: Recognizing the Emotion Engine

[2172] Input: Video data, audio data

[2173] Operation:

[2174] The user shows their facial expressions to the camera and speaks into the microphone.

[2175] The device collects video and audio and sends it to the emotion engine.

[2176] The emotion engine analyzes video and audio to identify the user's emotional state.

[2177] The server stores the analysis results received from the emotion engine in a database.

[2178] Output: User's emotional state

[2179] Step 4: Restaurant proposal

[2180] Input: User details, emotional state

[2181] Operation:

[2182] The server sets request parameters based on the user's input information and emotional state.

[2183] The server sends a request to an external restaurant database API.

[2184] The server receives the data returned from the external restaurant database API.

[2185] The server optimizes the restaurant list based on the user's emotional state.

[2186] The server transmits the optimized restaurant list to the terminal.

[2187] Output: A list of suggested restaurants

[2188] Step 5: Create a teaser message

[2189] Input: User information, emotional state

[2190] Operation:

[2191] The server creates a prompt for the generative AI model to use.

[2192] The server sends a prompt to the generation AI model, which generates an invitation message.

[2193] The server sends the generated message to the terminal.

[2194] The terminal displays the message to the user, who can then view and edit it.

[2195] The user sends the final message through a messaging app.

[2196] Output: Teaser message

[2197] Step 6: Proposal for a date outfit

[2198] Input: User style information, emotional state

[2199] Operation:

[2200] The server sends a request to an external fashion database API based on the user's style information and emotional state.

[2201] The server generates coordination suggestions based on the data returned from the external fashion database API.

[2202] The server transmits the generated coordination proposal to the terminal.

[2203] The terminal displays the coordination suggestions to the user.

[2204] Output: Date coordination suggestions

[2205] Step 7: Final review and feedback gathering

[2206] Input: Post-date feedback

[2207] Operation:

[2208] The user enters their satisfaction and areas for improvement after the date into the device.

[2209] The terminal transmits the feedback data to the server.

[2210] The server stores the feedback data in a database.

[2211] The server analyzes the feedback data and uses it to improve the accuracy of future proposals.

[2212] Output: Feedback data

[2213] In this way, at each processing step of the system, specific processes such as user input, data collection, analysis, and proposal generation are performed, allowing users to receive personalized dating support.

[2214] (Application example 2)

[2215] 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."

[2216] Conventional dating support systems handle basic data such as user attribute information, relationship information, and budget information, but do not take the user's emotional state into account, resulting in a lack of personalized suggestions and making it difficult to provide optimal suggestions.The present invention analyzes the user's emotional state and reflects this in the suggestions, enabling more personalized date plans to be proposed, thereby improving user satisfaction.

[2217] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2218] In this invention, the server includes means for recognizing a user's emotional state using an emotion engine that analyzes the user's emotional state, means for storing the analysis results from the emotion engine in a database, means for optimizing a suggested restaurant list based on the user's emotional state, and means for generating coordination suggestions based on the user's style information and emotional state using a fashion database API, thereby enabling personalized suggestions based on the user's emotions.

[2219] "User attribute information" is data that indicates personal characteristics of a user, such as age, gender, and hobbies.

[2220] "Relationship information" is data indicating the relationship between the user and the dater (e.g., first meeting, long-term relationship, friends).

[2221] "Budget information" is data indicating the amount of money a user can spend on a date.

[2222] An "emotion engine" is software or an algorithm that analyzes data such as a user's facial expressions and voice, and recognizes their emotional state (happiness, sadness, tension, etc.).

[2223] The "suggested restaurant list" is a list of restaurants selected based on the user's input information and emotional state.

[2224] An "invitation message" is a message created for the purpose of inviting someone on a date.

[2225] "Coordination suggestions" are suggestions for combinations of clothing, accessories, etc. that are suited to the user's style information and emotional state.

[2226] "Feedback data" refers to information such as evaluations and opinions provided by users after a date, and is data that is used to improve the accuracy of suggestions from the next date onwards.

[2227] The "restaurant database API" is an interface for communicating with an external restaurant information database and obtaining restaurant information.

[2228] "Generative AI technology" is an artificial intelligence technology that generates natural language based on large amounts of data.

[2229] The "Fashion Database API" is an interface for communicating with external fashion information databases and obtaining information on fashion items.

[2230] This invention is a system for supporting users in dating, and is composed of the following main elements and procedures. Specifically, the system processes and shares data while communicating with the server, terminals, and users, to propose date plans and collect feedback.

[2231] 1. Enter and save user information

[2232] The user inputs attribute information such as the purpose of the date, relationship status, budget, and food preferences from the terminal. The terminal sends the input information to the server, which then stores the information in a database.

[2233] 2. Emotion Engine Recognition

[2234] The user analyzes their emotional state using the smartphone's camera and microphone. The user's facial expressions and voice are then analyzed by the emotion engine, and their emotional state is recognized. The analysis results are sent to the server and stored in a database.

[2235] 3. Restaurant proposals and optimization

[2236] The server calls an external restaurant database API based on the user's input information and emotional state. Based on the returned information, it generates a restaurant list that takes into account the analysis results of the emotion engine and displays it to the user. This allows it to suggest restaurants that best suit the user's emotional state.

[2237] 4. Generate a teaser message

[2238] Generative AI technology (e.g., natural language generation models) is used to generate invitation messages based on the user's attributes, relationship information, and emotional state. The generated messages are sent to the device, where the user can review and edit them before sending them through a messaging app.

[2239] 5. Date coordination suggestions

[2240] The server calls a fashion database API based on the user's style information, date situation, and emotional state to generate outfit suggestions, which are then sent to the device and displayed to the user.

[2241] 6. Collect and use feedback

[2242] After the date, users provide feedback on the application, which the server analyzes and stores in a database to improve the accuracy of future suggestions.

[2243] Specific examples

[2244] Software and hardware used

[2245] Emotion engine: Microsoft Azure Face API and Amazon Rekognition

[2246] Restaurant database API: Google Places API, Tabelog API

[2247] Natural Language Generation Technology: OpenAI's GPT-3

[2248] Fashion database API: Rakuten Fashion API

[2249] Device: Smartphone

[2250] Server: General web server

[2251] Examples of prompt statements

[2252] The purpose of the date is an anniversary, the relationship is long-term, and the user's emotional state is joy. Based on this information, please generate an invitation message to send to your partner.

[2253] In this way, the system of the present invention can take into account the user's emotional state, thereby realizing more personalized date plan suggestions and improving user satisfaction.

[2254] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2255] Step 1:

[2256] Input: The user enters demographic information such as the purpose of the date, relationship status, budget, and food preferences.

[2257] How it works: The device collects information through a user input form and sends it to the server.

[2258] Output: The server stores the received information in a database.

[2259] Step 2:

[2260] Input: Video and audio data from the user's camera and microphone.

[2261] How it works: The device uses the camera and microphone to send data to the emotion engine, which analyzes the user's emotional state. The server then stores the analysis results in a database.

[2262] Output: An analysis of the user's emotional state.

[2263] Step 3:

[2264] Input: User demographic information, relationship information, budget information, and emotional state.

[2265] How it works: The server calls an external restaurant database API to retrieve a list of appropriate restaurants based on the input information. The retrieved list is then optimized based on the user's emotional state.

[2266] Output: A list of restaurants that fit your emotional state.

[2267] Step 4:

[2268] Input: User attribute information, relationship information, and emotional state.

[2269] How it works: The server uses generative AI technology to generate a prompt. For example, "The purpose of the date is an anniversary, the relationship is long-term, and the user's emotional state is joy. Based on this information, please generate an invitation message to send to the other person."

[2270] Output: The generated teaser message.

[2271] Step 5:

[2272] Input: User's demographic information, style information, and emotional state.

[2273] How it works: The server calls the fashion database API and generates outfit suggestions suitable for the user.

[2274] Output: Coordination suggestions.

[2275] Step 6:

[2276] Input: Feedback information entered by the user after the date.

[2277] How it works: The server collects feedback information and stores it in a database to improve the accuracy of suggestions next time.

[2278] Output: Feedback data is accumulated to improve the accuracy of future suggestions.

[2279] 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.

[2280] 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.

[2281] 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.

[2282] 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.

[2283] 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.

[2284] 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.

[2285] 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).

[2286] 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.

[2287] 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."

[2288] 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.

[2289] 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).

[2290] 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.

[2291] 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.

[2292] 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.

[2293] 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.

[2294] 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.

[2295] 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.

[2296] 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.

[2297] 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.

[2298] 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.

[2299] 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.

[2300] The following is further disclosed regarding the above embodiment.

[2301] (Claim 1)

[2302] A means for inputting user attribute information, relationship information, and budget information;

[2303] A means for suggesting appropriate restaurants based on information input by a user;

[2304] A means for displaying the generated suggested restaurant list to a user;

[2305] means for generating an invitation message based on user input information;

[2306] means for displaying the generated invitation message to a user;

[2307] A means for suggesting an outfit suitable for a date based on user attribute information;

[2308] means for displaying the generated coordination proposal to a user;

[2309] a means for collecting feedback on a user's dating actions;

[2310] The system includes a means to improve the accuracy of the next proposal based on the collected feedback data.

[2311] (Claim 2)

[2312] The system of claim 1 , wherein the suggested restaurant list is generated using an external restaurant database API.

[2313] (Claim 3)

[2314] 10. The system of claim 1, wherein the teaser message is generated using generative AI techniques.

[2315] "Example 1"

[2316] (Claim 1)

[2317] A means for inputting user attribute information, relationship information, and budget information;

[2318] A means for suggesting appropriate restaurants based on information input by a user;

[2319] A means for displaying the generated suggested restaurant list to a user;

[2320] means for generating an invitation message based on user input information;

[2321] means for displaying the generated invitation to a user;

[2322] A means for suggesting clothes suitable for a date based on attribute information of the user;

[2323] means for displaying the generated outfit suggestions to a user;

[2324] a means for collecting feedback on a user's dating actions;

[2325] A method to improve the accuracy of the next proposal based on the collected feedback data, and

[2326] a means for authenticating a user's login;

[2327] a means for storing user information in a database;

[2328] A means to obtain a list of suggested restaurants from an external API,

[2329] A means of obtaining clothing suggestions from an external API,

[2330] A system including means for generating a teaser using a generative AI model.

[2331] (Claim 2)

[2332] The system of claim 1 , wherein the suggested restaurant list is generated using an external restaurant database API.

[2333] (Claim 3)

[2334] 10. The system of claim 1, wherein the teaser is generated using generative AI techniques.

[2335] "Application Example 1"

[2336] (Claim 1)

[2337] A means for inputting user attribute information, relationship information, and budget information;

[2338] A means for suggesting appropriate restaurants based on information input by a user;

[2339] A means for displaying the generated suggested restaurant list to a user;

[2340] means for generating an invitation message based on user input information;

[2341] means for displaying the generated invitation message to a user;

[2342] A means for suggesting an outfit suitable for a date based on user attribute information;

[2343] means for displaying the generated coordination proposal to a user;

[2344] a means for collecting feedback on a user's dating actions;

[2345] A method to improve the accuracy of the next proposal based on the collected feedback data, and

[2346] A means for supporting restaurant reservations through a smartphone application based on user information;

[2347] A means for inputting a prompt sentence into a generative AI model to generate an invitation message;

[2348] means for enabling the generated message to be sent via a messaging app;

[2349] A means of acquiring the user's style information and suggesting coordination using a fashion database API;

[2350] A means of notifying the user of suggested outfits via their smartphone

[2351] A system including:

[2352] (Claim 2)

[2353] The system according to claim 1, wherein the suggested restaurant list is generated using an external restaurant database API.

[2354] (Claim 3)

[2355] 10. The system of claim 1, wherein the teaser message is generated using generative AI techniques.

[2356] "Example 2: Combining Emotion Engines"

[2357] (Claim 1)

[2358] A means for inputting user attribute information, relationship information, and budget information;

[2359] A means for suggesting appropriate restaurants based on information input by a user and the user's emotional state;

[2360] A means for displaying the generated suggested restaurant list to a user;

[2361] means for generating an invitation message based on the input information and the emotional state;

[2362] means for displaying the generated invitation message to a user;

[2363] means for suggesting outfits suitable for a date based on style information and emotional state of the user;

[2364] means for displaying the generated coordination proposal to a user;

[2365] a means for collecting feedback on a user's dating actions;

[2366] The system includes a means to improve the accuracy of the next proposal based on the collected feedback data.

[2367] (Claim 2)

[2368] The system of claim 1 , wherein the suggested restaurant list is generated using an external restaurant database API.

[2369] (Claim 3)

[2370] 10. The system of claim 1, wherein the teaser message is generated using generative AI techniques.

[2371] "Application example 2 when combining emotion engines"

[2372] (Claim 1)

[2373] A means for inputting user attribute information, relationship information, and budget information;

[2374] A means for suggesting appropriate restaurants based on information input by a user;

[2375] A means for displaying the generated suggested restaurant list to a user;

[2376] means for generating an invitation message based on user input information;

[2377] means for displaying the generated invitation message to a user;

[2378] A means for suggesting an outfit suitable for a date based on user attribute information;

[2379] means for displaying the generated coordination proposal to a user;

[2380] a means for collecting feedback on a user's dating actions;

[2381] A method to improve the accuracy of the next proposal based on the collected feedback data, and

[2382] means for recognizing a user's emotional state using an emotion engine that analyzes the user's emotional state;

[2383] a means for storing the analysis results from the emotion engine in a database;

[2384] means for optimizing the suggested restaurant list based on the emotional state of the user;

[2385] A means for generating coordination suggestions based on the user's style information and emotional state using a fashion database API;

[2386] A system including:

[2387] (Claim 2)

[2388] The system of claim 1 , wherein the suggested restaurant list is generated using an external restaurant database API.

[2389] (Claim 3)

[2390] 10. The system of claim 1, wherein the teaser message is generated using generative AI techniques. [Explanation of symbols]

[2391] 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. A means for inputting user attribute information, relationship information, and budget information; A means for suggesting appropriate restaurants based on information input by a user; A means for displaying the generated suggested restaurant list to a user; means for generating an invitation message based on user input information; means for displaying the generated invitation message to a user; A means for suggesting an outfit suitable for a date based on user attribute information; means for displaying the generated coordination proposal to a user; a means for collecting feedback on a user's dating actions; The system includes a means to improve the accuracy of the next proposal based on the collected feedback data.

2. The system of claim 1 , wherein the suggested restaurant list is generated using an external restaurant database API.

3. The system of claim 1 , wherein the invitation message is generated using generative AI techniques.

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