System

Abstract

A system is provided.SOLUTION: The system includes a means for inputting a desire by a user, a means for analyzing the input desire and determining a category, a means for generating necessary information based on the desire, a means for providing the generated information to the user, and a means for automatically establishing communication with an associated stakeholder.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 modern society, people have a wide range of dreams and hopes, but they lack efficient ways to obtain the specific procedures and information needed to realize them. For example, if someone wants to become a traditional craftsman, participate in volunteer activities in a developing country, or live and work in a specific region, information on specific aspirations is fragmented, and services that provide related information in a unified manner are extremely limited. There is also a lack of efficient ways to establish contact with relevant stakeholders. For this reason, it is necessary to eliminate the barriers people face in the process of realizing their dreams and hopes. [Means for solving the problem]

[0005] In order to solve the above problems, the present invention provides a system including a means for a user to input his / her wishes, a means for analyzing the input wishes and determining a category, a means for generating necessary information based on the wishes, a means for providing the generated information to the user, and a means for automatically establishing contact with relevant stakeholders. This system uses artificial intelligence to generate information based on the wishes, and further uses an application program interface for establishing contact with relevant stakeholders, thereby efficiently and effectively supporting the realization of the user's dreams and wishes.

[0006] "User" refers to a person who utilizes the system to input their preferences and obtain information.

[0007] "Hope" refers to the dreams and goals that users want to achieve.

[0008] "Means" refers to the methods or methods used to achieve a particular end.

[0009] "Analysis" refers to the act of processing input information to understand it and extract meaning.

[0010] A "category" refers to a group for classifying items that have the same properties or characteristics.

[0011] "Generate" refers to the act of creating new information or data.

[0012] "Information" refers to the collection of knowledge or data provided to users.

[0013] "Stakeholders" refer to organizations and people involved in realizing users' wishes.

[0014] "Establishing contact" refers to the act of establishing procedures and methods for contacting a particular person.

[0015] A "system" refers to an entire device or group of programs that consists of multiple means and methods and that are used to achieve a specific purpose.

[0016] "Artificial intelligence" refers to programs and technologies that mimic human intelligence and automatically analyze and generate information.

[0017] "Application Program Interface" refers to a standardized interface for exchanging information and utilizing functions between different software programs. [Brief explanation of the drawings]

[0018] [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

[0019] 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.

[0020] First, the terms used in the following description will be explained.

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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."

[0039] The embodiment of the present invention is described below. First, the system consists of a web interface for users to input their preferences, an information processing module using generative AI, an information provision module, and a module for establishing contact with stakeholders.

[0040] System Overview

[0041] 1. User input module: A form is provided for users to enter their preferences. Through this form, users can enter specific preferences, such as "I want to become a traditional craftsman" or "I want to participate in volunteer activities in developing countries."

[0042] 2. Generative AI module: The server calls the generative AI and analyzes the input preference. Based on the analysis results, it generates relevant information and returns it to the server. For example, for a preference such as "I want to become a traditional craftsman," it generates information on appropriate training programs, related companies, and necessary qualifications.

[0043] 3. Information provision module: The server formats the information received from the generation AI and provides it to the user, allowing the user to obtain the necessary procedures and detailed information.

[0044] 4. Contact Establishment Module: The server automatically establishes contact with relevant stakeholders, for example, providing contact information for training programs, real estate agencies, local government information, etc.

[0045] Explaining program processing in natural language

[0046] User Input Module

[0047] A user accesses the portal site and enters their wishes. For example, they might enter a wish to "participate in volunteer activities in developing countries." When the user confirms the information and clicks the submit button, this information is sent to the server.

[0048] Generative AI Module

[0049] The server receives the user's wishes and passes them to the generation AI. The generation AI analyzes the wishes and collects and generates the necessary information from the relevant database. For example, for a wish to "participate in volunteer activities in developing countries," the following information is generated:

[0050] List of volunteer organizations

[0051] Required procedures (visa, vaccinations, etc.)

[0052] Local living information

[0053] Information Module

[0054] The server receives the information returned by the AI ​​generator and formats it into a user-friendly format, which is then presented to the user through a web page or application, such as a list of volunteer organizations, details of procedures, or information useful for local life.

[0055] Contact Establishment Module

[0056] The server automatically establishes contact with relevant stakeholders (e.g., volunteer organizations, visa application agencies, vaccination agencies) by using an API to retrieve each stakeholder's contact information and provide it to the user.

[0057] Specific examples

[0058] User Input

[0059] 1. The user enters into the portal site, "I want to become a traditional craftsman."

[0060] 2. The user checks the input and clicks the submit button.

[0061] information generation

[0062] 1. The server passes the input to the generation AI.

[0063] 2. The AI ​​analyzes keywords such as "traditional crafts" and "repair craftsman" and generates the following information:

[0064] List of schools for training repair craftsmen (traditional craft technical colleges, craft skills training schools, etc.)

[0065] A list of potential job opportunities and related companies

[0066] Information on the qualifications and skills required for repair craftsmen

[0067] Providing information

[0068] 1. The server receives information from the generation AI.

[0069] 2. The server formats the information and displays it to the user, allowing them to retrieve specific instructions and details they need.

[0070] Establishing contact

[0071] 1. The server calls an API to establish contact with a specific stakeholder (training school, company, certification body, etc.).

[0072] 2. The server retrieves the contact information of each stakeholder and provides it to the user.

[0073] In this way, this system provides consistent support, from the moment the user inputs their wishes, through to the AI ​​analyzing and generating information, providing the information, and establishing contact with relevant stakeholders, making it possible for users to realize their dreams and hopes.

[0074] The processing flow will be explained below.

[0075] Step 1:

[0076] The user accesses the portal site.

[0077] Step 2:

[0078] The user enters their desired interests (e.g., "I want to become a traditional craftsman") into the provided input form.

[0079] Step 3:

[0080] The user checks the input information and clicks the "Submit" button.

[0081] Step 4:

[0082] The server receives the desired data from the user.

[0083] Step 5:

[0084] The server analyzes the received data and determines the desired category (e.g., occupation, volunteering, residential choice, hobby).

[0085] Step 6:

[0086] The server passes the discrimination results to the generation AI module.

[0087] Step 7:

[0088] The generation AI analyzes the desired data it receives and collects the necessary information from relevant databases.

[0089] Step 8:

[0090] Based on the collected information, the generation AI generates specific information (e.g., training programs, related companies, qualification information, etc.) that corresponds to the user's wishes.

[0091] Step 9:

[0092] The generation AI returns the generated information to the server in JSON format.

[0093] Step 10:

[0094] The server receives the JSON data returned by the generated AI.

[0095] Step 11:

[0096] The server formats the received data into a user-friendly format (e.g., an HTML page).

[0097] Step 12:

[0098] The server provides the formatted information to the user.

[0099] Step 13:

[0100] The user views the provided information and obtains the necessary procedures and detailed information.

[0101] Step 14:

[0102] The server invokes an API to establish contact with the relevant stakeholders.

[0103] Step 15:

[0104] The server retrieves stakeholder contact information through an API.

[0105] Step 16:

[0106] The server provides the retrieved contact information to the user.

[0107] Step 17:

[0108] Users will be contacted directly with the relevant stakeholders using the contact information provided.

[0109] Step 18:

[0110] If a user requires additional information or support, they submit a request to the server using the contact form.

[0111] Step 19:

[0112] The server receives additional requests and calls the generation AI again to generate the necessary information and provide it to the user.

[0113] Example 1

[0114] 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."

[0115] In conventional systems, even if users input specific requests, it was difficult to properly analyze them and provide the necessary information quickly and accurately. Furthermore, there were insufficient means for establishing contact with relevant stakeholders, which often required users to search for the necessary information themselves, which was time-consuming and labor-intensive. This resulted in delays in realizing users' requests.

[0116] 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.

[0117] In this invention, the server includes: means for a user to input preferences; means for analyzing the input preferences and determining categories; means including a generative AI model for generating necessary information based on the preferences; means for providing the generated information to the user; means for formatting the generated information into a user-friendly format; and means including an application program interface for automatically establishing contact with relevant stakeholders. This makes it possible to quickly and accurately generate and provide information based on the preferences input by the user, and automatically establish contact with relevant stakeholders.

[0118] "User" means an individual or entity that uses the System to input preferences and obtain information.

[0119] "Means for inputting preferences" refers to a mechanism that provides an interface that allows users to input their preferences in text format.

[0120] The "means for analyzing and determining the category" is an algorithm that analyzes the input preference and determines the appropriate category based on the content.

[0121] A "generative AI model" is a model that uses artificial intelligence technology to generate relevant information based on the user's wishes.

[0122] "Means for generating information" refers to the function of using a generative AI model to collect and generate information according to the user's wishes.

[0123] The "means of providing to users" refers to a mechanism for formatting the generated information and providing it to users in an easy-to-read format.

[0124] The "means for formatting into a user-friendly format" refers to a processing means for converting the generated information into a format that is easy for the user to understand.

[0125] "Relevant stakeholders" are institutions, organizations, and companies that can provide information and services relevant to the user's wishes.

[0126] "Application Program Interface for automatically establishing contact" refers to API technology that the system uses to automatically communicate with external stakeholders.

[0127] A "system" is a set of computer programs and their execution environment that integrate user input, information analysis and generation, information provision, and stakeholder contact establishment.

[0128] The present invention is implemented using a user interface, a generative AI model, a server, a database, and an application program interface (API) that supports users from inputting their preferences to providing information and establishing contact with relevant stakeholders.

[0129] 1. User Input Module

[0130] Users access the system's portal site using a web browser. The portal site provides a form for users to enter their preferences. Users enter their preferences specifically and click the submit button. This input form is implemented using HTML and JavaScript.

[0131] Examples:

[0132] A user enters into a portal site that they would like to participate in volunteer activities in developing countries.

[0133] 2. Data Transmission and Reception

[0134] The server receives the data entered by the user in the input form. The data is sent to the server as an HTTP POST request, and the server parses the request to extract the input. This process uses AJAX techniques to send the data asynchronously.

[0135] 3. Generative AI Module

[0136] The server passes the received data to the generative AI. The generative AI model uses natural language processing technology to analyze the input text and collect and generate relevant information. The generative AI model is cloud-based and runs using advanced computing resources.

[0137] Examples:

[0138] The generative AI model generates the following information in response to the input "I want to participate in volunteer work in developing countries":

[0139] List of volunteer organizations

[0140] Required procedures (visa, vaccinations, etc.)

[0141] Local living information

[0142] 4. Information Module

[0143] The server receives the information returned by the generation AI and formats it into a user-friendly format using an HTML template engine (e.g., Thymeleaf or ERB) and presents the information as a web page, allowing the user to retrieve specific procedures and necessary details.

[0144] 5. Contact Establishment Module

[0145] The server uses the API to establish contact with relevant stakeholders (e.g., volunteer organizations, visa application agencies, vaccination agencies), parses the contact information returned by the API, and provides it to the user.

[0146] Examples:

[0147] The server calls a specific API to retrieve contact information for the volunteer organization.

[0148] Prompt Sentence Examples

[0149] "What is the process for participating in volunteer work in developing countries?"

[0150] "Please provide me with the information I need to become a traditional craftsman."

[0151] In this way, the system provides comprehensive support to help users realize their wishes through a series of processes. By using a generative AI model, it is possible to provide users with quick and accurate information and automatically establish contact with relevant stakeholders, thereby increasing user convenience.

[0152] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0153] Step 1:

[0154] A user accesses the portal site and enters their wishes. This input form uses HTML and JavaScript, providing an interface that makes it easy for users to enter their wishes. The input data is "I would like to participate in volunteer activities in developing countries," and the submit button is clicked.

[0155] Input: User's wishes (e.g., "I would like to participate in volunteer activities in developing countries")

[0156] Output: Desired data sent

[0157] Step 2:

[0158] The server receives the desired data sent by the user as an HTTP POST request and parses it. A backend service (e.g., Node.js or Django) is used to process the HTTP request and extract the submitted data.

[0159] Input: Submitted desired data

[0160] Output: Parsed desired data

[0161] Step 3:

[0162] The server passes the parsed desired data to a generative AI model, which uses natural language processing techniques to analyze the input text and generate relevant information. This process runs on cloud-based infrastructure (e.g., AWS or Google Cloud).

[0163] Input: Analyzed preference data (e.g., "I would like to participate in volunteer activities in developing countries")

[0164] Output: Generated relevant information (e.g., list of volunteer organizations, necessary procedures, local living information)

[0165] Step 4:

[0166] The server receives the information returned by the generative AI model and formats it into a user-friendly format using an HTML template engine (e.g., Thymeleaf, ERB). The formatted information is then presented to the user in a clear and reliable manner.

[0167] Input: Generated relevant information (e.g., list of volunteer organizations, necessary procedures, local living information)

[0168] Output: Formatted information

[0169] Step 5:

[0170] The server formats the information and displays it in a user interface, allowing users to easily access specific procedures and required details. The display process is performed using a front-end framework (e.g., React, Vue.js).

[0171] Input: Formatted information

[0172] Output: Information displayed on the web page

[0173] Step 6:

[0174] The server makes API calls to establish contact with relevant stakeholders, e.g. to retrieve contact information for volunteer organisations, visa application agencies, vaccination agencies etc. For this purpose it uses external APIs (e.g. REST APIs).

[0175] Input: Request for required stakeholder information

[0176] Output: Retrieved contact information

[0177] Step 7:

[0178] The server parses the retrieved contact information and provides it to the user, formatting it and displaying it in a user-friendly format.

[0179] Input: Obtained contact information

[0180] Output: Formatted contact information

[0181] Through each of the above steps, users can quickly and accurately obtain information based on their wishes and establish contact with relevant stakeholders, greatly improving user convenience and accelerating the realization of their wishes.

[0182] (Application example 1)

[0183] 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."

[0184] The present invention relates to a system that efficiently supports users' purchasing behavior by quickly and accurately providing the information desired by the user and presenting product information in specific categories based on that desire. It also aims to enable users to smoothly acquire products by automatically establishing contact with relevant stakeholders. Furthermore, it aims to provide a system that generates product information tailored to the user's budget and enables real-time inventory confirmation.

[0185] 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.

[0186] In this invention, the server includes a means for a user to input preferences, a means for analyzing the input preferences and determining a category, a means for generating necessary information based on the preferences, a means for providing the generated information to the user, a means for automatically establishing contact with relevant stakeholders, a means for providing the generated information as a list of products in a specific category, a means for generating product information with a budget limit based on the user's preferences, and a means for checking product inventory in real time based on the user's preferences and budget. This allows users to easily obtain product information that meets their preferences and makes selections that fit their budget. Furthermore, smooth communication with stakeholders enables a fast and efficient purchasing process.

[0187] "User" means a person who uses the system to input wishes and requests and receive information and services.

[0188] "Wishes" refer to specific requests, desired information, products, etc. that users input into the system.

[0189] "Means" refer to the methods, processes, or modules that a system uses to achieve a specific function.

[0190] "Analysis" is the process of examining input data or information and determining its meaning or category.

[0191] A "category" is a standard or classification for grouping and classifying information.

[0192] "Necessary information" refers to data and materials that are useful to the user and are generated according to the user's wishes.

[0193] "Generate" refers to the process of creating new information or data based on input data.

[0194] "Providing" means presenting the generated information to the user in a format that is easy to view.

[0195] "Stakeholders" are external parties, organizations, and companies that are involved with the system.

[0196] "Automatically establish contact" means that the system automatically coordinates with the necessary stakeholders at the user's request.

[0197] A "product list" is a list of multiple products selected based on the user's preferences.

[0198] The "budget limit" is the upper limit of the amount that a user sets when purchasing a desired product.

[0199] "Real-time inventory check" refers to the process of instantly checking current inventory status.

[0200] An embodiment of the present invention is described below. The system comprises a means for a user to input preferences, a means for analyzing the input preferences and determining a category, a means for generating necessary information based on the preferences, a means for providing the generated information to the user, and a means for automatically establishing contact with relevant stakeholders. The system further includes a means for providing the generated information as a list of products in a specific category, a means for generating product information with a budget limit based on the user's preferences, and a means for checking the availability of products in real time based on the user's preferences and budget.

[0201] System configuration

[0202] User Input Module:

[0203] It provides a form for users to enter their preferences. Through this form, users can enter specific preferences such as "I want eco-friendly fashion items" or "I want recommended gadgets for under 10,000 yen." The form includes items such as the desired product category and budget.

[0204] Generative AI module:

[0205] The server receives the user's request and passes it to the generation AI, which includes Hugging Face's Transformers pipeline (e.g., GPT-3). The generation AI analyzes the user's request and collects and generates the necessary information from the relevant database.

[0206] Specifically, if a user inputs "I want eco-friendly fashion items," the AI ​​will generate a list of eco-certified fashion products. Similarly, if a user inputs "I want recommended gadgets under 10,000 yen," the AI ​​will generate a list of highly rated gadgets within that budget.

[0207] Informational modules:

[0208] The server receives the information returned by the generation AI, formats it, and provides it to the user in the form of a link to a detailed page containing product images, prices, ratings, and availability, allowing the user to find the product information that best suits their needs.

[0209] Contact Establishment Module:

[0210] The server establishes contact with relevant stakeholders (e.g., merchants and delivery services) by, for example, using APIs to check stock availability with merchants in real time and providing delivery options, thus providing a smooth product purchase experience for the user.

[0211] Program processing

[0212] The system includes a web server built using the Flask framework. The user input module allows users to input their preferences and send them to the server. The generation AI module uses Hugging Face's GPT-3 to analyze the user's preferences and generate relevant information. The information provision module formats the generated information and displays it to the user. The contact establishment module uses the requests library to connect with external stakeholders via API, providing real-time inventory confirmation and delivery options.

[0213] Specific examples

[0214] For example, if a user enters "I'm looking for eco-friendly fashion items" into a form, the Generative AI will generate information based on the following prompt:

[0215] text

[0216] User's preference: Eco-friendly fashion items, Budget: Under 5,000 yen

[0217] In response, the AI ​​generates a list of items such as eco bags and bamboo toothbrushes. This information is formatted and provided to the user along with a link to the product's detail page. The server also checks inventory in real time through API connections with retailers, providing the user with the current inventory status.

[0218] Thus, the present invention is a system that not only analyzes user desires and provides appropriate product information, but also establishes smooth communication with related stakeholders.

[0219] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0220] Step 1:

[0221] User preference input

[0222] The user accesses the device's web interface and inputs their preferences, such as "I want eco-friendly fashion items" or "I want recommended gadgets for under 10,000 yen." The input data includes information about the desired product category and budget. The input data is converted to JSON format and sent to the server.

[0223] Input: User's preference (category, budget, etc.)

[0224] Output: Desired data in JSON format

[0225] Step 2:

[0226] Desired analysis and category determination

[0227] The server receives the user's desired data in JSON format. This data is then passed to a generative AI model (such as GPT-3) for analysis. The generative AI analyzes the user's preferences and determines the desired product category and conditions. It also generates a prompt based on the analyzed content.

[0228] Input: Desired data in JSON format

[0229] Output: Analysis results (prompt statements, etc.)

[0230] What happens:

[0231] Invoking a generative AI (e.g., GPT-3 for Hugging Face)

[0232] Generate prompt statement

[0233] Step 3:

[0234] information generation

[0235] The server then collects the necessary information from relevant databases based on the analysis results from the generation AI. For example, it generates a list of eco-friendly fashion items or a list of recommended gadgets under 10,000 yen. The collected information consists of detailed data such as product name, price, rating, and stock status.

[0236] Input: Analysis results (user's desired category, budget, etc.)

[0237] Output: Product information list

[0238] What happens:

[0239] Database Access and Information Collection

[0240] Step 4:

[0241] Providing information

[0242] The server formats the collected product information and converts it into a user-friendly format. The formatted information is provided to the user as a link to a detail page that includes product images, prices, ratings, stock status, etc. The technologies used are web page generation using Flask and HTML rendering using a template engine.

[0243] Input: Product information list

[0244] Output: Formatted product information (web page, application display format)

[0245] What happens:

[0246] HTML rendering, information presentation using Flask

[0247] Step 5:

[0248] Establishing contact with stakeholders

[0249] The server establishes contact with relevant stakeholders (e.g., sellers, delivery services, etc.). For example, it uses the requests library to call seller APIs to check inventory in real time, and delivery service APIs to provide delivery options. This allows users to instantly check current stock availability and delivery terms.

[0250] Input: Product information list, user's desired conditions

[0251] Output: Detailed inventory check results, shipping options information

[0252] What happens:

[0253] API calls and external integration using the requests library

[0254] In this way, the system analyzes the user's preferences at each step and provides appropriate product information. By establishing smooth communication with stakeholders, the system streamlines the user's purchasing behavior.

[0255] 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.

[0256] The following describes an embodiment of the present invention. The system of the present invention has a function to respond to the emotional state of the user by combining a means for inputting user preferences, a means for generating and providing information using a generation AI, a means for establishing contact with stakeholders, and an emotion engine.

[0257] System Overview

[0258] 1. User input module: A form is provided for users to enter their preferences. Through this form, users can enter specific preferences, such as "I want to become a traditional craftsman" or "I want to participate in volunteer activities in developing countries."

[0259] 2. Emotion Recognition Module: The emotion engine built into the server analyzes the user's input and interactions to recognize the user's emotional state (e.g., joy, sadness, anxiety).

[0260] 3. Generative AI module: The server calls the generative AI and analyzes the input desires and emotional state. Based on the analysis results, the necessary information is collected from related databases and generated. For example, for the desire to "become a traditional craftsman" and the emotional state of "being curious," appropriate training programs, related companies, and necessary qualifications are generated.

[0261] 4. Information provision module: The server formats the information received from the generation AI and provides it to the user. The information provided takes into account the analysis results of the emotion engine and is provided in content and expression that is appropriate for the user's emotional state. This allows the user to obtain the necessary procedures and detailed information.

[0262] 5. Contact Establishment Module: The server automatically establishes contact with relevant stakeholders by using APIs to obtain contact information for each stakeholder and providing it to the user.

[0263] Explaining program processing in natural language

[0264] User Input Module

[0265] A user accesses the portal site and enters their wishes. For example, they might enter a wish to "participate in volunteer activities in developing countries." When the user confirms the information and clicks the submit button, this information is sent to the server.

[0266] Emotion Recognition Module

[0267] The server receives the desired data from the user and simultaneously analyzes the user's emotional state using an emotion engine, for example, determining whether the user is "excited" or "anxious" based on the user's typing speed and choice of words.

[0268] Generative AI Module

[0269] The server passes the user's wishes and emotional state to the generation AI. The generation AI analyzes the wishes and emotional state, and collects and generates the necessary information from the relevant database. For example, for the wish to "participate in volunteer activities in developing countries" and the emotional state of "excited," the following information is generated:

[0270] List of volunteer organizations

[0271] Required procedures (visa, vaccinations, etc.)

[0272] Local living information

[0273] Information Module

[0274] The server receives the information returned by the generation AI and formats it into a user-friendly format (e.g., an HTML page). It incorporates the analysis results of the emotion engine and includes expressions and messages appropriate to the user's emotional state. For example, if the user is "excited," a positive and encouraging message is displayed.

[0275] Contact Establishment Module

[0276] The server calls an API to establish contact with relevant stakeholders (e.g., volunteer organizations, visa application agencies, vaccination agencies), retrieves contact information for each stakeholder, and provides it to the user.

[0277] Specific examples

[0278] User Input

[0279] 1. The user enters into the portal site, "I want to become a traditional craftsman."

[0280] 2. The user checks the input and clicks the submit button.

[0281] Information generation and emotion recognition

[0282] 1. The server uses the input content along with the emotion engine to analyze the user's emotional state.

[0283] 2. The generating AI analyzes keywords such as "traditional craftsman" and "repair craftsman" and the emotional state "excited" to generate the following information:

[0284] List of schools for training repair craftsmen (traditional craft technical colleges, craft skills training schools, etc.)

[0285] A list of potential job opportunities and related companies

[0286] Information on the qualifications and skills required for repair craftsmen

[0287] Providing information

[0288] 1. The server receives information from the generation AI.

[0289] 2. The server formats the information and displays it with an encouraging message appropriate to the user's emotional state, such as "You're one step closer to making your dreams come true!"

[0290] Establishing contact

[0291] 1. The server calls an API to establish contact with a specific stakeholder (training school, company, certification body, etc.).

[0292] 2. The server retrieves the contact information of each stakeholder and provides it to the user.

[0293] In this way, the system effectively supports the realization of users' dreams and hopes through a series of steps: starting with the user inputting their wishes, followed by analysis and generation of information using generative AI, analysis of their emotional state using an emotion engine and provision of information accordingly, and finally establishing contact with relevant stakeholders.

[0294] The processing flow will be explained below.

[0295] Step 1:

[0296] The user accesses the portal site.

[0297] Step 2:

[0298] The user enters their desired interests (e.g., "I want to become a traditional craftsman") into the provided input form.

[0299] Step 3:

[0300] The user checks the input information and clicks the "Submit" button.

[0301] Step 4:

[0302] The server receives the desired data from the user.

[0303] Step 5:

[0304] The server analyzes the received data and determines the desired category (e.g., occupation, volunteering, residential choice, hobby).

[0305] Step 6:

[0306] The server passes the results of the discrimination to the generation AI module and emotion engine.

[0307] Step 7:

[0308] The emotion engine analyzes user input and determines the user's emotional state (e.g., happy, sad, anxious).

[0309] Step 8:

[0310] The generative AI analyzes the user's wishes and emotional state, and collects and generates the necessary information from relevant databases.

[0311] Step 9:

[0312] The generation AI generates information based on user preferences (e.g., a list of training programs, a list of related companies, and required qualifications).

[0313] Step 10:

[0314] The generation AI returns the generated information to the server in JSON format.

[0315] Step 11:

[0316] The server receives the JSON data returned by the generated AI.

[0317] Step 12:

[0318] The server formats the received data into a user-friendly format (e.g., HTML page), incorporating the analysis results of the emotion engine and adding expressions appropriate to the user's emotional state.

[0319] Step 13:

[0320] The server provides the formatted information to the user. The user then browses the information and obtains the necessary procedures and detailed information. For example, a message such as "You're one step closer to making your dreams come true!" is displayed.

[0321] Step 14:

[0322] The server invokes an API to establish contact with the relevant stakeholders.

[0323] Step 15:

[0324] The server retrieves stakeholder contact information through an API.

[0325] Step 16:

[0326] The server provides the retrieved contact information to the user.

[0327] Step 17:

[0328] Users will be contacted directly with the relevant stakeholders using the contact information provided.

[0329] Step 18:

[0330] If a user requires additional information or support, they submit a request to the server using the contact form.

[0331] Step 19:

[0332] The server receives additional requests and again calls the generation AI and emotion engine to generate the necessary information and provide it to the user.

[0333] Example 2

[0334] 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."

[0335] When a user inputs their preferences, it is important to provide information that matches those preferences. However, conventional systems often provide information without considering the user's emotional state, which fails to sufficiently improve user satisfaction. Furthermore, establishing contact with relevant stakeholders must be done manually, which is time-consuming and reduces efficiency. Furthermore, generating information based on preferences requires accuracy and appropriate category determination, but conventional systems are unable to address these challenges.

[0336] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for a user to input a preference, a means for analyzing the input preference and determining a category, a means for generating necessary information based on the preference, a means for providing the generated information to the user, a means for automatically establishing contact with relevant stakeholders, an emotion recognition means for analyzing the user's emotional state, and a means for adjusting the information presentation method based on the emotional state. This makes it possible to provide information taking the user's emotional state into consideration, thereby improving user satisfaction and increasing the efficiency of establishing contact with stakeholders. Furthermore, accurate information generation and category determination can be performed based on the preference.

[0337] The "means for user input of wishes" is an interface that allows a user to input specific wishes or requests to the system.

[0338] The "means for analyzing input preferences and determining categories" is a function for analyzing preferences input by the user and classifying the contents into specific categories.

[0339] "Means for generating necessary information based on user preferences" refers to a function that automatically collects and generates relevant information based on user preferences.

[0340] The "means for providing the generated information to the user" is a function for providing the generated information to the user in an appropriate format.

[0341] "Means for automatically establishing contact with relevant stakeholders" means means for automatically obtaining and providing contact information for third parties relevant to the user's wishes.

[0342] The "emotion recognition means for analyzing the user's emotional state" is a function for analyzing the user's input data and behavior to identify the user's emotional state.

[0343] The "means for adjusting the method of presenting information based on the emotional state" is a function for adjusting the method of presenting information and the content of messages according to the emotional state of the user.

[0344] The embodiment of the present invention is described below. The system of the present invention has a function to respond to the emotional state of the user by combining a means for inputting user preferences, a means for generating and providing information using a generative AI, a means for establishing contact with stakeholders, and an emotion engine.

[0345] System Overview

[0346] 1. User Input Module:

[0347] A form is provided for users to enter their aspirations. For example, they can enter specific aspirations such as "I want to become a repair craftsman of traditional crafts" or "I want to participate in volunteer activities in developing countries." This form is implemented as a web page, and the input contents are sent to the server.

[0348] 2. Emotion Recognition Module:

[0349] The server analyzes the received user preference data using an emotion engine to identify the user's emotional state (e.g., joy, sadness, anxiety) using algorithms such as typing speed, keywords in the sentence, and context analysis.

[0350] 3. Generative AI module:

[0351] The server passes the user's wishes and emotional state to the generation AI, which then collects and generates the necessary information from relevant databases based on those wishes and emotional state. For example, in response to a wish to "participate in volunteer activities in developing countries" and an emotional state of "excitement," the generation AI generates a list of volunteer organizations, necessary procedures (visas, vaccinations, etc.), and information about life in the local area.

[0352] 4. Information module:

[0353] The server formats the information received from the generation AI and provides it to the user. The information provided takes into account the analysis results of the emotion engine and is provided with content and expression appropriate to the user's emotional state. For example, if the user is "excited," a positive and encouraging message will be included.

[0354] 5. Contact Establishment Module:

[0355] The server calls an API to establish contact with relevant stakeholders (e.g., volunteer organizations, companies, certification bodies), retrieves contact information for each stakeholder, and provides it to the user.

[0356] Specific examples

[0357] User Input

[0358] Users enter "I want to become a traditional craftsman" into the portal site.

[0359] The user checks the input contents and clicks the send button.

[0360] Information generation and emotion recognition

[0361] The server uses the input together with an emotion engine to analyze the user's emotional state.

[0362] The AI ​​analyzes keywords such as "traditional craftsman" and "repair craftsman" along with the emotional state of "excited" to generate the following information:

[0363] List of schools for training repair craftsmen (traditional craft technical colleges, craft skills training schools, etc.)

[0364] A list of potential job opportunities and related companies

[0365] Information on the qualifications and skills required for repair craftsmen

[0366] Providing information

[0367] The server receives information from the generating AI.

[0368] The server formats the information and displays it with an encouraging message appropriate to the user's emotional state, such as "You're one step closer to making your dreams come true!"

[0369] Establishing contact

[0370] The server calls an API to establish contact with a particular stakeholder (training school, company, certification body, etc.).

[0371] The server retrieves the contact information of each stakeholder and provides it to the user.

[0372] Prompt Sentence Examples

[0373] The following prompt sentences are examples of specific requests that can be entered into the user input module:

[0374] I would like to become a traditional craftsman. Which training school should I attend? Are there any companies that I can work for? I would also like to know about related qualifications.

[0375] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0376] Step 1: User Input

[0377] The user accesses the portal site of the system and enters their wishes into the provided form. For example, they enter their wish to "participate in volunteer activities in developing countries."

[0378] Input: The desired text data entered by the user.

[0379] Output: The desired text data entered is sent to the server as is.

[0380] Step 2: Sending User Input

[0381] The user checks the input and clicks the submit button, which sends the input data to the server.

[0382] Input: The event when the submit button is clicked and the desired text data entered.

[0383] Output: The desired text data sent to the server.

[0384] Step 3: Emotion Recognition

[0385] The server launches an emotion engine based on the received desired data. The emotion engine analyzes the input text and determines the user's emotional state. For example, it analyzes keywords and context in the text to identify emotions such as "excited" or "anxious."

[0386] Input: The desired text data received by the server.

[0387] Output: The user's emotional state (e.g., "excited").

[0388] Step 4: Analyze your desires and emotional state

[0389] The server passes the emotion recognition results and the user's desired data to the generation AI, which then analyzes the data and searches related databases to collect the necessary information.

[0390] Input: User's desired text data and emotional state.

[0391] Output: Analysis results and collected information based on wishes and emotions.

[0392] Step 5: Information Generation

[0393] The generative AI generates the necessary information based on the analysis results of the input. For example, based on the desire to "participate in volunteer activities in developing countries" and the emotional state of "excited," the following information is generated:

[0394] List of volunteer organizations

[0395] Required procedures (visa, vaccinations, etc.)

[0396] Local living information

[0397] Input: Analysis results based on desires and emotional state.

[0398] Output: A list of the generated information.

[0399] Step 6: Provide information

[0400] The server receives the information returned by the generation AI and formats it in a user-friendly format. Taking into account the results of the emotion engine, the server provides information in a way that is appropriate to the user's emotional state. For example, if the user is "excited," a positive and encouraging message is displayed.

[0401] Input: A generated list of information and an emotional state.

[0402] Output: The formatted information presented to the user.

[0403] Step 7: Establishing Contact

[0404] The server calls the API to obtain contact information for relevant stakeholders (e.g., volunteer organizations, companies, certification bodies), and provides the obtained information to the user to support the next action.

[0405] Input: User preferences and relevant stakeholder information.

[0406] Output: Stakeholder contact information and information provided to users.

[0407] (Application example 2)

[0408] 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."

[0409] Conventional shopping support systems collect user preferences, but offer only uniform product and service recommendations based on those preferences, lacking personalized recommendations that take into account the user's emotional state. This results in a less than satisfying shopping experience. Furthermore, establishing contact with stakeholders to realize the user's preferences is a manual process that is inefficient. This results in a complex and time-consuming process for users to take action.

[0410] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to input a preference, means for analyzing the input preference and determining a category, means for generating necessary information based on the preference and the user's emotional state, means for providing the generated information to the user, means for automatically establishing contact with relevant stakeholders, means for analyzing the user's emotional state using an emotion engine, and means for adjusting the presentation of the generated information based on the analyzed emotional state. This enables the proposal of appropriate and personalized products and services based on the user's preference, resulting in a more satisfying shopping experience. Furthermore, because contact with relevant stakeholders is automatically established, the process for the user to realize their preference is made more efficient.

[0411] "User input means" is an interface that allows a user to input desired products or services.

[0412] The "category determination means" is a means for analyzing the desires input by the user and classifying them into an appropriate category.

[0413] The "information generation means" is a means for generating necessary information based on the user's wishes and emotional state.

[0414] "Information provision means" refers to a means for providing the generated information to the user in an appropriate format.

[0415] A "contact establishment method" is a method for automatically establishing contact with relevant stakeholders.

[0416] The "emotion engine" is an engine for analyzing the user's emotional state.

[0417] The "emotion analysis means" is a means for analyzing the user's emotional state using an emotion engine.

[0418] The "expression adjusting means" is a means for adjusting the expression of the generated information based on the analyzed emotional state.

[0419] "Generative AI" is artificial intelligence that generates information based on desires and emotional states.

[0420] "Application Program Interface" means a program interface for establishing contact with stakeholders.

[0421] The following describes the mode for carrying out this invention. The present invention is a personalized shopping assistant system for improving the shopping experience in brick-and-mortar stores. This system is installed on a smartphone or smart glasses and analyzes the user's desires and emotional state to suggest optimal products and services.

[0422] System Configuration

[0423] Hardware and Software

[0424] 1. User Input Method:

[0425] Using a smartphone or smart glasses, the device provides an interface for users to input their preferences, typically using a touchscreen or voice input.

[0426] 2. Category determination method:

[0427] We analyze the user's input preferences and classify them into appropriate categories. We use common natural language processing (NLP) tools and libraries (e.g., NLTK, spaCy) to analyze preferences.

[0428] 3. Emotion analysis means:

[0429] The emotional state of the user is analyzed using an emotion engine. Emotion analysis takes into account keywords in the input, sentence structure, input speed, etc. The emotion engine uses the Python EmotionRecognizer library.

[0430] 4. Information generation means:

[0431] Based on the user's preferences and emotional state, information is generated using generative AI (e.g., OpenAI's GPT-3). The generated information is retrieved from relevant databases to suggest optimal products and services to the user.

[0432] 5. Information provision method:

[0433] The generated information is presented to the user through the display of a smartphone or smart glasses, and the way this information is displayed is adjusted based on the results of emotion analysis.

[0434] 6. Means of establishing contact:

[0435] Use APIs to automatically establish contact with relevant stakeholders, allowing for efficient communication with volunteer organizations, certification bodies, vaccination agencies, etc.

[0436] Example of processing flow

[0437] 1. User Input

[0438] A user uses a smartphone or smart glasses to input the product or service they are looking for, for example, "I'm looking for new fashion items."

[0439] 2. Category determination

[0440] The server analyzes the input and classifies it into a "fashion" category, using NLP tools to determine relationships.

[0441] 3. Emotion analysis

[0442] The emotion engine analyzes the user's emotional state to determine that they are "curious." The emotion is determined from the input speed and keywords in the text.

[0443] 4. Information generation

[0444] Enter the following prompts into the generative AI model (OpenAI's GPT-3) to generate information:

[0445] Want: Looking for new fashion items

[0446] Emotion: Curious

[0447] Please suggest products or services that best fit these criteria.

[0448] Based on these prompts, the generative AI generates information about the latest trending items and the stores that sell them.

[0449] 5. Information provision

[0450] The server receives the generated information, adjusts the display format to match the user's emotional state, and displays it on the smartphone or smart glasses screen, for example, displaying product images and descriptions along with encouraging messages.

[0451] 6. Establishing Contact

[0452] The server makes API calls to establish contact with the relevant store or support service, providing the contact information to the user so they can contact them directly.

[0453] As described above, this system analyzes users' preferences and emotional state, suggests optimal products and services, and improves the shopping experience. It also automatically establishes contact with relevant stakeholders, allowing users to take action smoothly.

[0454] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0455] Step 1:

[0456] Users input their desired products or services through the interface of their smartphone or smart glasses. The input data is sent to the server by the user device. An example input might be "I'm looking for a new fashion item."

[0457] Input: User's preference (text)

[0458] Output: Desired data sent to the server

[0459] Step 2:

[0460] The server analyzes the received desired data. For analysis, it uses NLP tools (e.g., NLTK or spaCy) to extract related keywords from the input content and determine the category. In this case, the keyword "fashion" is extracted and the category "fashion" is determined.

[0461] Input: User's desired data

[0462] Output: Parsed category (e.g. fashion)

[0463] Step 3:

[0464] The server performs emotion recognition based on the desired data. It uses an emotion engine (e.g., EmotionRecognizer library) to analyze the user's emotional state based on their text expression and typing speed. In this case, the emotion is analyzed as "curious."

[0465] Input: User's desired data

[0466] Output: Parsed emotional state (e.g., curious)

[0467] Step 4:

[0468] The server generates information by sending prompts to a generative AI model (e.g., OpenAI's GPT-3) based on the user's desires and emotional state. An example prompt is "Desire: Looking for a new fashion item. Emotion: Curious. Please suggest products and services that best suit these conditions." The generative AI analyzes this and generates information.

[0469] Input: User's desires and emotional state

[0470] Output: Generated information (e.g., latest trending items and store information)

[0471] Step 5:

[0472] The server receives the generated information and adjusts the display format based on the emotion analysis results. For example, the display format may be adjusted to include an encouraging message. The adjusted information is then displayed on the display of the smartphone or smart glasses.

[0473] Input: Generated information and emotional state

[0474] Output: Adjusted display information

[0475] Step 6:

[0476] The server calls the API to establish contact with the relevant stakeholders (stores and support services). The contact information obtained through the API is provided to the user so that they can contact them directly.

[0477] Input: Relevant stakeholder information

[0478] Output: Stakeholder contact information

[0479] 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.

[0480] 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.

[0481] 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.

[0482] [Second embodiment]

[0483] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0484] 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.

[0485] 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).

[0486] 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.

[0487] 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.

[0488] 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).

[0489] 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.

[0490] 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.

[0491] 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.

[0492] 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.

[0493] 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.

[0494] 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."

[0495] The embodiment of the present invention is described below. First, the system consists of a web interface for users to input their preferences, an information processing module using generative AI, an information provision module, and a module for establishing contact with stakeholders.

[0496] System Overview

[0497] 1. User input module: A form is provided for users to enter their preferences. Through this form, users can enter specific preferences, such as "I want to become a traditional craftsman" or "I want to participate in volunteer activities in developing countries."

[0498] 2. Generative AI module: The server calls the generative AI and analyzes the input preference. Based on the analysis results, it generates relevant information and returns it to the server. For example, for a preference such as "I want to become a traditional craftsman," it generates information on appropriate training programs, related companies, and necessary qualifications.

[0499] 3. Information provision module: The server formats the information received from the generation AI and provides it to the user, allowing the user to obtain the necessary procedures and detailed information.

[0500] 4. Contact Establishment Module: The server automatically establishes contact with relevant stakeholders, for example, providing contact information for training programs, real estate agencies, local government information, etc.

[0501] Explaining program processing in natural language

[0502] User Input Module

[0503] A user accesses the portal site and enters their wishes. For example, they might enter a wish to "participate in volunteer activities in developing countries." When the user confirms the information and clicks the submit button, this information is sent to the server.

[0504] Generative AI Module

[0505] The server receives the user's wishes and passes them to the generation AI. The generation AI analyzes the wishes and collects and generates the necessary information from the relevant database. For example, for a wish to "participate in volunteer activities in developing countries," the following information is generated:

[0506] List of volunteer organizations

[0507] Required procedures (visa, vaccinations, etc.)

[0508] Local living information

[0509] Information Module

[0510] The server receives the information returned by the AI ​​generator and formats it into a user-friendly format, which is then presented to the user through a web page or application, such as a list of volunteer organizations, details of procedures, or information useful for local life.

[0511] Contact Establishment Module

[0512] The server automatically establishes contact with relevant stakeholders (e.g., volunteer organizations, visa application agencies, vaccination agencies) by using an API to retrieve each stakeholder's contact information and provide it to the user.

[0513] Specific examples

[0514] User Input

[0515] 1. The user enters into the portal site, "I want to become a traditional craftsman."

[0516] 2. The user checks the input and clicks the submit button.

[0517] information generation

[0518] 1. The server passes the input to the generation AI.

[0519] 2. The AI ​​analyzes keywords such as "traditional crafts" and "repair craftsman" and generates the following information:

[0520] List of schools for training repair craftsmen (traditional craft technical colleges, craft skills training schools, etc.)

[0521] A list of potential job opportunities and related companies

[0522] Information on the qualifications and skills required for repair craftsmen

[0523] Providing information

[0524] 1. The server receives information from the generation AI.

[0525] 2. The server formats the information and displays it to the user, allowing them to retrieve specific instructions and details they need.

[0526] Establishing contact

[0527] 1. The server calls an API to establish contact with a specific stakeholder (training school, company, certification body, etc.).

[0528] 2. The server retrieves the contact information of each stakeholder and provides it to the user.

[0529] In this way, this system provides consistent support, from the moment the user inputs their wishes, through to the AI ​​analyzing and generating information, providing the information, and establishing contact with relevant stakeholders, making it possible for users to realize their dreams and hopes.

[0530] The processing flow will be explained below.

[0531] Step 1:

[0532] The user accesses the portal site.

[0533] Step 2:

[0534] The user enters their desired interests (e.g., "I want to become a traditional craftsman") into the provided input form.

[0535] Step 3:

[0536] The user checks the input information and clicks the "Submit" button.

[0537] Step 4:

[0538] The server receives the desired data from the user.

[0539] Step 5:

[0540] The server analyzes the received data and determines the desired category (e.g., occupation, volunteering, residential choice, hobby).

[0541] Step 6:

[0542] The server passes the discrimination results to the generation AI module.

[0543] Step 7:

[0544] The generation AI analyzes the desired data it receives and collects the necessary information from relevant databases.

[0545] Step 8:

[0546] Based on the collected information, the generation AI generates specific information (e.g., training programs, related companies, qualification information, etc.) that corresponds to the user's wishes.

[0547] Step 9:

[0548] The generation AI returns the generated information to the server in JSON format.

[0549] Step 10:

[0550] The server receives the JSON data returned by the generated AI.

[0551] Step 11:

[0552] The server formats the received data into a user-friendly format (e.g., an HTML page).

[0553] Step 12:

[0554] The server provides the formatted information to the user.

[0555] Step 13:

[0556] The user views the provided information and obtains the necessary procedures and detailed information.

[0557] Step 14:

[0558] The server invokes an API to establish contact with the relevant stakeholders.

[0559] Step 15:

[0560] The server retrieves stakeholder contact information through an API.

[0561] Step 16:

[0562] The server provides the retrieved contact information to the user.

[0563] Step 17:

[0564] Users will be contacted directly with the relevant stakeholders using the contact information provided.

[0565] Step 18:

[0566] If a user requires additional information or support, they submit a request to the server using the contact form.

[0567] Step 19:

[0568] The server receives additional requests and calls the generation AI again to generate the necessary information and provide it to the user.

[0569] Example 1

[0570] 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."

[0571] In conventional systems, even if users input specific requests, it was difficult to properly analyze them and provide the necessary information quickly and accurately. Furthermore, there were insufficient means for establishing contact with relevant stakeholders, which often required users to search for the necessary information themselves, which was time-consuming and labor-intensive. This resulted in delays in realizing users' requests.

[0572] 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.

[0573] In this invention, the server includes: means for a user to input preferences; means for analyzing the input preferences and determining categories; means including a generative AI model for generating necessary information based on the preferences; means for providing the generated information to the user; means for formatting the generated information into a user-friendly format; and means including an application program interface for automatically establishing contact with relevant stakeholders. This makes it possible to quickly and accurately generate and provide information based on the preferences input by the user, and automatically establish contact with relevant stakeholders.

[0574] "User" means an individual or entity that uses the System to input preferences and obtain information.

[0575] "Means for inputting preferences" refers to a mechanism that provides an interface that allows users to input their preferences in text format.

[0576] The "means for analyzing and determining the category" is an algorithm that analyzes the input preference and determines the appropriate category based on the content.

[0577] A "generative AI model" is a model that uses artificial intelligence technology to generate relevant information based on the user's wishes.

[0578] "Means for generating information" refers to the function of using a generative AI model to collect and generate information according to the user's wishes.

[0579] The "means of providing to users" refers to a mechanism for formatting the generated information and providing it to users in an easy-to-read format.

[0580] The "means for formatting into a user-friendly format" refers to a processing means for converting the generated information into a format that is easy for the user to understand.

[0581] "Relevant stakeholders" are institutions, organizations, and companies that can provide information and services relevant to the user's wishes.

[0582] "Application Program Interface for automatically establishing contact" refers to API technology that the system uses to automatically communicate with external stakeholders.

[0583] A "system" is a set of computer programs and their execution environment that integrate user input, information analysis and generation, information provision, and stakeholder contact establishment.

[0584] The present invention is implemented using a user interface, a generative AI model, a server, a database, and an application program interface (API) that supports users from inputting their preferences to providing information and establishing contact with relevant stakeholders.

[0585] 1. User Input Module

[0586] Users access the system's portal site using a web browser. The portal site provides a form for users to enter their preferences. Users enter their preferences specifically and click the submit button. This input form is implemented using HTML and JavaScript.

[0587] Examples:

[0588] A user enters into a portal site that they would like to participate in volunteer activities in developing countries.

[0589] 2. Data Transmission and Reception

[0590] The server receives the data entered by the user in the input form. The data is sent to the server as an HTTP POST request, and the server parses the request to extract the input. This process uses AJAX techniques to send the data asynchronously.

[0591] 3. Generative AI Module

[0592] The server passes the received data to the generative AI. The generative AI model uses natural language processing technology to analyze the input text and collect and generate relevant information. The generative AI model is cloud-based and runs using advanced computing resources.

[0593] Examples:

[0594] The generative AI model generates the following information in response to the input "I want to participate in volunteer work in developing countries":

[0595] List of volunteer organizations

[0596] Required procedures (visa, vaccinations, etc.)

[0597] Local living information

[0598] 4. Information Module

[0599] The server receives the information returned by the generation AI and formats it into a user-friendly format using an HTML template engine (e.g., Thymeleaf or ERB) and presents the information as a web page, allowing the user to retrieve specific procedures and necessary details.

[0600] 5. Contact Establishment Module

[0601] The server uses the API to establish contact with relevant stakeholders (e.g., volunteer organizations, visa application agencies, vaccination agencies), parses the contact information returned by the API, and provides it to the user.

[0602] Examples:

[0603] The server calls a specific API to retrieve contact information for the volunteer organization.

[0604] Prompt Sentence Examples

[0605] "What is the process for participating in volunteer work in developing countries?"

[0606] "Please provide me with the information I need to become a traditional craftsman."

[0607] In this way, the system provides comprehensive support to help users realize their wishes through a series of processes. By using a generative AI model, it is possible to provide users with quick and accurate information and automatically establish contact with relevant stakeholders, thereby increasing user convenience.

[0608] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0609] Step 1:

[0610] A user accesses the portal site and enters their wishes. This input form uses HTML and JavaScript, providing an interface that makes it easy for users to enter their wishes. The input data is "I would like to participate in volunteer activities in developing countries," and the submit button is clicked.

[0611] Input: User's wishes (e.g., "I would like to participate in volunteer activities in developing countries")

[0612] Output: Desired data sent

[0613] Step 2:

[0614] The server receives the desired data sent by the user as an HTTP POST request and parses it. A backend service (e.g., Node.js or Django) is used to process the HTTP request and extract the submitted data.

[0615] Input: Submitted desired data

[0616] Output: Parsed desired data

[0617] Step 3:

[0618] The server passes the parsed desired data to a generative AI model, which uses natural language processing techniques to analyze the input text and generate relevant information. This process runs on cloud-based infrastructure (e.g., AWS or Google Cloud).

[0619] Input: Analyzed preference data (e.g., "I would like to participate in volunteer activities in developing countries")

[0620] Output: Generated relevant information (e.g., list of volunteer organizations, necessary procedures, local living information)

[0621] Step 4:

[0622] The server receives the information returned by the generative AI model and formats it into a user-friendly format using an HTML template engine (e.g., Thymeleaf, ERB). The formatted information is then presented to the user in a clear and reliable manner.

[0623] Input: Generated relevant information (e.g., list of volunteer organizations, necessary procedures, local living information)

[0624] Output: Formatted information

[0625] Step 5:

[0626] The server formats the information and displays it in a user interface, allowing users to easily access specific procedures and required details. The display process is performed using a front-end framework (e.g., React, Vue.js).

[0627] Input: Formatted information

[0628] Output: Information displayed on the web page

[0629] Step 6:

[0630] The server makes API calls to establish contact with relevant stakeholders, e.g. to retrieve contact information for volunteer organisations, visa application agencies, vaccination agencies etc. For this purpose it uses external APIs (e.g. REST APIs).

[0631] Input: Request for required stakeholder information

[0632] Output: Retrieved contact information

[0633] Step 7:

[0634] The server parses the retrieved contact information and provides it to the user, formatting it and displaying it in a user-friendly format.

[0635] Input: Obtained contact information

[0636] Output: Formatted contact information

[0637] Through each of the above steps, users can quickly and accurately obtain information based on their wishes and establish contact with relevant stakeholders, greatly improving user convenience and accelerating the realization of their wishes.

[0638] (Application example 1)

[0639] 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."

[0640] The present invention relates to a system that efficiently supports users' purchasing behavior by quickly and accurately providing the information desired by the user and presenting product information in specific categories based on that desire. It also aims to enable users to smoothly acquire products by automatically establishing contact with relevant stakeholders. Furthermore, it aims to provide a system that generates product information tailored to the user's budget and enables real-time inventory confirmation.

[0641] 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.

[0642] In this invention, the server includes a means for a user to input preferences, a means for analyzing the input preferences and determining a category, a means for generating necessary information based on the preferences, a means for providing the generated information to the user, a means for automatically establishing contact with relevant stakeholders, a means for providing the generated information as a list of products in a specific category, a means for generating product information with a budget limit based on the user's preferences, and a means for checking product inventory in real time based on the user's preferences and budget. This allows users to easily obtain product information that meets their preferences and makes selections that fit their budget. Furthermore, smooth communication with stakeholders enables a fast and efficient purchasing process.

[0643] "User" means a person who uses the system to input wishes and requests and receive information and services.

[0644] "Wishes" refer to specific requests, desired information, products, etc. that users input into the system.

[0645] "Means" refer to the methods, processes, or modules that a system uses to achieve a specific function.

[0646] "Analysis" is the process of examining input data or information and determining its meaning or category.

[0647] A "category" is a standard or classification for grouping and classifying information.

[0648] "Necessary information" refers to data and materials that are useful to the user and are generated according to the user's wishes.

[0649] "Generate" refers to the process of creating new information or data based on input data.

[0650] "Providing" means presenting the generated information to the user in a format that is easy to view.

[0651] "Stakeholders" are external parties, organizations, and companies that are involved with the system.

[0652] "Automatically establish contact" means that the system automatically coordinates with the necessary stakeholders at the user's request.

[0653] A "product list" is a list of multiple products selected based on the user's preferences.

[0654] The "budget limit" is the upper limit of the amount that a user sets when purchasing a desired product.

[0655] "Real-time inventory check" refers to the process of instantly checking current inventory status.

[0656] An embodiment of the present invention is described below. The system comprises a means for a user to input preferences, a means for analyzing the input preferences and determining a category, a means for generating necessary information based on the preferences, a means for providing the generated information to the user, and a means for automatically establishing contact with relevant stakeholders. The system further includes a means for providing the generated information as a list of products in a specific category, a means for generating product information with a budget limit based on the user's preferences, and a means for checking the availability of products in real time based on the user's preferences and budget.

[0657] System configuration

[0658] User Input Module:

[0659] It provides a form for users to enter their preferences. Through this form, users can enter specific preferences such as "I want eco-friendly fashion items" or "I want recommended gadgets for under 10,000 yen." The form includes items such as the desired product category and budget.

[0660] Generative AI module:

[0661] The server receives the user's request and passes it to the generation AI, which includes Hugging Face's Transformers pipeline (e.g., GPT-3). The generation AI analyzes the user's request and collects and generates the necessary information from the relevant database.

[0662] Specifically, if a user inputs "I want eco-friendly fashion items," the AI ​​will generate a list of eco-certified fashion products. Similarly, if a user inputs "I want recommended gadgets under 10,000 yen," the AI ​​will generate a list of highly rated gadgets within that budget.

[0663] Informational modules:

[0664] The server receives the information returned by the generation AI, formats it, and provides it to the user in the form of a link to a detailed page containing product images, prices, ratings, and availability, allowing the user to find the product information that best suits their needs.

[0665] Contact Establishment Module:

[0666] The server establishes contact with relevant stakeholders (e.g., merchants and delivery services) by, for example, using APIs to check stock availability with merchants in real time and providing delivery options, thus providing a smooth product purchase experience for the user.

[0667] Program processing

[0668] The system includes a web server built using the Flask framework. The user input module allows users to input their preferences and send them to the server. The generation AI module uses Hugging Face's GPT-3 to analyze the user's preferences and generate relevant information. The information provision module formats the generated information and displays it to the user. The contact establishment module uses the requests library to connect with external stakeholders via API, providing real-time inventory confirmation and delivery options.

[0669] Specific examples

[0670] For example, if a user enters "I'm looking for eco-friendly fashion items" into a form, the Generative AI will generate information based on the following prompt:

[0671] text

[0672] User's preference: Eco-friendly fashion items, Budget: Under 5,000 yen

[0673] In response, the AI ​​generates a list of items such as eco bags and bamboo toothbrushes. This information is formatted and provided to the user along with a link to the product's detail page. The server also checks inventory in real time through API connections with retailers, providing the user with the current inventory status.

[0674] Thus, the present invention is a system that not only analyzes user desires and provides appropriate product information, but also establishes smooth communication with related stakeholders.

[0675] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0676] Step 1:

[0677] User preference input

[0678] The user accesses the device's web interface and inputs their preferences, such as "I want eco-friendly fashion items" or "I want recommended gadgets for under 10,000 yen." The input data includes information about the desired product category and budget. The input data is converted to JSON format and sent to the server.

[0679] Input: User's preference (category, budget, etc.)

[0680] Output: Desired data in JSON format

[0681] Step 2:

[0682] Desired analysis and category determination

[0683] The server receives the user's desired data in JSON format. This data is then passed to a generative AI model (such as GPT-3) for analysis. The generative AI analyzes the user's preferences and determines the desired product category and conditions. It also generates a prompt based on the analyzed content.

[0684] Input: Desired data in JSON format

[0685] Output: Analysis results (prompt statements, etc.)

[0686] What happens:

[0687] Invoking a generative AI (e.g., GPT-3 for Hugging Face)

[0688] Generate prompt statement

[0689] Step 3:

[0690] information generation

[0691] The server then collects the necessary information from relevant databases based on the analysis results from the generation AI. For example, it generates a list of eco-friendly fashion items or a list of recommended gadgets under 10,000 yen. The collected information consists of detailed data such as product name, price, rating, and stock status.

[0692] Input: Analysis results (user's desired category, budget, etc.)

[0693] Output: Product information list

[0694] What happens:

[0695] Database Access and Information Collection

[0696] Step 4:

[0697] Providing information

[0698] The server formats the collected product information and converts it into a user-friendly format. The formatted information is provided to the user as a link to a detail page that includes product images, prices, ratings, stock status, etc. The technologies used are web page generation using Flask and HTML rendering using a template engine.

[0699] Input: Product information list

[0700] Output: Formatted product information (web page, application display format)

[0701] What happens:

[0702] HTML rendering, information presentation using Flask

[0703] Step 5:

[0704] Establishing contact with stakeholders

[0705] The server establishes contact with relevant stakeholders (e.g., sellers, delivery services, etc.). For example, it uses the requests library to call seller APIs to check inventory in real time, and delivery service APIs to provide delivery options. This allows users to instantly check current stock availability and delivery terms.

[0706] Input: Product information list, user's desired conditions

[0707] Output: Detailed inventory check results, shipping options information

[0708] What happens:

[0709] API calls and external integration using the requests library

[0710] In this way, the system analyzes the user's preferences at each step and provides appropriate product information. By establishing smooth communication with stakeholders, the system streamlines the user's purchasing behavior.

[0711] 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.

[0712] The following describes an embodiment of the present invention. The system of the present invention has a function to respond to the emotional state of the user by combining a means for inputting user preferences, a means for generating and providing information using a generation AI, a means for establishing contact with stakeholders, and an emotion engine.

[0713] System Overview

[0714] 1. User input module: A form is provided for users to enter their preferences. Through this form, users can enter specific preferences, such as "I want to become a traditional craftsman" or "I want to participate in volunteer activities in developing countries."

[0715] 2. Emotion Recognition Module: The emotion engine built into the server analyzes the user's input and interactions to recognize the user's emotional state (e.g., joy, sadness, anxiety).

[0716] 3. Generative AI module: The server calls the generative AI and analyzes the input desires and emotional state. Based on the analysis results, the necessary information is collected from related databases and generated. For example, for the desire to "become a traditional craftsman" and the emotional state of "being curious," appropriate training programs, related companies, and necessary qualifications are generated.

[0717] 4. Information provision module: The server formats the information received from the generation AI and provides it to the user. The information provided takes into account the analysis results of the emotion engine and is provided in content and expression that is appropriate for the user's emotional state. This allows the user to obtain the necessary procedures and detailed information.

[0718] 5. Contact Establishment Module: The server automatically establishes contact with relevant stakeholders by using APIs to obtain contact information for each stakeholder and providing it to the user.

[0719] Explaining program processing in natural language

[0720] User Input Module

[0721] A user accesses the portal site and enters their wishes. For example, they might enter a wish to "participate in volunteer activities in developing countries." When the user confirms the information and clicks the submit button, this information is sent to the server.

[0722] Emotion Recognition Module

[0723] The server receives the desired data from the user and simultaneously analyzes the user's emotional state using an emotion engine, for example, determining whether the user is "excited" or "anxious" based on the user's typing speed and choice of words.

[0724] Generative AI Module

[0725] The server passes the user's wishes and emotional state to the generation AI. The generation AI analyzes the wishes and emotional state, and collects and generates the necessary information from the relevant database. For example, for the wish to "participate in volunteer activities in developing countries" and the emotional state of "excited," the following information is generated:

[0726] List of volunteer organizations

[0727] Required procedures (visa, vaccinations, etc.)

[0728] Local living information

[0729] Information Module

[0730] The server receives the information returned by the generation AI and formats it into a user-friendly format (e.g., an HTML page). It incorporates the analysis results of the emotion engine and includes expressions and messages appropriate to the user's emotional state. For example, if the user is "excited," a positive and encouraging message is displayed.

[0731] Contact Establishment Module

[0732] The server calls an API to establish contact with relevant stakeholders (e.g., volunteer organizations, visa application agencies, vaccination agencies), retrieves contact information for each stakeholder, and provides it to the user.

[0733] Specific examples

[0734] User Input

[0735] 1. The user enters into the portal site, "I want to become a traditional craftsman."

[0736] 2. The user checks the input and clicks the submit button.

[0737] Information generation and emotion recognition

[0738] 1. The server uses the input content along with the emotion engine to analyze the user's emotional state.

[0739] 2. The generating AI analyzes keywords such as "traditional craftsman" and "repair craftsman" and the emotional state "excited" to generate the following information:

[0740] List of schools for training repair craftsmen (traditional craft technical colleges, craft skills training schools, etc.)

[0741] A list of potential job opportunities and related companies

[0742] Information on the qualifications and skills required for repair craftsmen

[0743] Providing information

[0744] 1. The server receives information from the generation AI.

[0745] 2. The server formats the information and displays it with an encouraging message appropriate to the user's emotional state, such as "You're one step closer to making your dreams come true!"

[0746] Establishing contact

[0747] 1. The server calls an API to establish contact with a specific stakeholder (training school, company, certification body, etc.).

[0748] 2. The server retrieves the contact information of each stakeholder and provides it to the user.

[0749] In this way, the system effectively supports the realization of users' dreams and hopes through a series of steps: starting with the user inputting their wishes, followed by analysis and generation of information using generative AI, analysis of their emotional state using an emotion engine and provision of information accordingly, and finally establishing contact with relevant stakeholders.

[0750] The processing flow will be explained below.

[0751] Step 1:

[0752] The user accesses the portal site.

[0753] Step 2:

[0754] The user enters their desired interests (e.g., "I want to become a traditional craftsman") into the provided input form.

[0755] Step 3:

[0756] The user checks the input information and clicks the "Submit" button.

[0757] Step 4:

[0758] The server receives the desired data from the user.

[0759] Step 5:

[0760] The server analyzes the received data and determines the desired category (e.g., occupation, volunteering, residential choice, hobby).

[0761] Step 6:

[0762] The server passes the results of the discrimination to the generation AI module and emotion engine.

[0763] Step 7:

[0764] The emotion engine analyzes user input and determines the user's emotional state (e.g., happy, sad, anxious).

[0765] Step 8:

[0766] The generative AI analyzes the user's wishes and emotional state, and collects and generates the necessary information from relevant databases.

[0767] Step 9:

[0768] The generation AI generates information based on user preferences (e.g., a list of training programs, a list of related companies, and required qualifications).

[0769] Step 10:

[0770] The generation AI returns the generated information to the server in JSON format.

[0771] Step 11:

[0772] The server receives the JSON data returned by the generated AI.

[0773] Step 12:

[0774] The server formats the received data into a user-friendly format (e.g., HTML page), incorporating the analysis results of the emotion engine and adding expressions appropriate to the user's emotional state.

[0775] Step 13:

[0776] The server provides the formatted information to the user. The user then browses the information and obtains the necessary procedures and detailed information. For example, a message such as "You're one step closer to making your dreams come true!" is displayed.

[0777] Step 14:

[0778] The server invokes an API to establish contact with the relevant stakeholders.

[0779] Step 15:

[0780] The server retrieves stakeholder contact information through an API.

[0781] Step 16:

[0782] The server provides the retrieved contact information to the user.

[0783] Step 17:

[0784] Users will be contacted directly with the relevant stakeholders using the contact information provided.

[0785] Step 18:

[0786] If a user requires additional information or support, they submit a request to the server using the contact form.

[0787] Step 19:

[0788] The server receives additional requests and again calls the generation AI and emotion engine to generate the necessary information and provide it to the user.

[0789] Example 2

[0790] 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."

[0791] When a user inputs their preferences, it is important to provide information that matches those preferences. However, conventional systems often provide information without considering the user's emotional state, which fails to sufficiently improve user satisfaction. Furthermore, establishing contact with relevant stakeholders must be done manually, which is time-consuming and reduces efficiency. Furthermore, generating information based on preferences requires accuracy and appropriate category determination, but conventional systems are unable to address these challenges.

[0792] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for a user to input a preference, a means for analyzing the input preference and determining a category, a means for generating necessary information based on the preference, a means for providing the generated information to the user, a means for automatically establishing contact with relevant stakeholders, an emotion recognition means for analyzing the user's emotional state, and a means for adjusting the information presentation method based on the emotional state. This makes it possible to provide information taking the user's emotional state into consideration, thereby improving user satisfaction and increasing the efficiency of establishing contact with stakeholders. Furthermore, accurate information generation and category determination can be performed based on the preference.

[0793] The "means for user input of wishes" is an interface that allows a user to input specific wishes or requests to the system.

[0794] The "means for analyzing input preferences and determining categories" is a function for analyzing preferences input by the user and classifying the contents into specific categories.

[0795] "Means for generating necessary information based on user preferences" refers to a function that automatically collects and generates relevant information based on user preferences.

[0796] The "means for providing the generated information to the user" is a function for providing the generated information to the user in an appropriate format.

[0797] "Means for automatically establishing contact with relevant stakeholders" means means for automatically obtaining and providing contact information for third parties relevant to the user's wishes.

[0798] The "emotion recognition means for analyzing the user's emotional state" is a function for analyzing the user's input data and behavior to identify the user's emotional state.

[0799] The "means for adjusting the method of presenting information based on the emotional state" is a function for adjusting the method of presenting information and the content of messages according to the emotional state of the user.

[0800] The embodiment of the present invention is described below. The system of the present invention has a function to respond to the emotional state of the user by combining a means for inputting user preferences, a means for generating and providing information using a generative AI, a means for establishing contact with stakeholders, and an emotion engine.

[0801] System Overview

[0802] 1. User Input Module:

[0803] A form is provided for users to enter their aspirations. For example, they can enter specific aspirations such as "I want to become a repair craftsman of traditional crafts" or "I want to participate in volunteer activities in developing countries." This form is implemented as a web page, and the input contents are sent to the server.

[0804] 2. Emotion Recognition Module:

[0805] The server analyzes the received user preference data using an emotion engine to identify the user's emotional state (e.g., joy, sadness, anxiety) using algorithms such as typing speed, keywords in the sentence, and context analysis.

[0806] 3. Generative AI module:

[0807] The server passes the user's wishes and emotional state to the generation AI, which then collects and generates the necessary information from relevant databases based on those wishes and emotional state. For example, in response to a wish to "participate in volunteer activities in developing countries" and an emotional state of "excitement," the generation AI generates a list of volunteer organizations, necessary procedures (visas, vaccinations, etc.), and information about life in the local area.

[0808] 4. Information module:

[0809] The server formats the information received from the generation AI and provides it to the user. The information provided takes into account the analysis results of the emotion engine and is provided with content and expression appropriate to the user's emotional state. For example, if the user is "excited," a positive and encouraging message will be included.

[0810] 5. Contact Establishment Module:

[0811] The server calls an API to establish contact with relevant stakeholders (e.g., volunteer organizations, companies, certification bodies), retrieves contact information for each stakeholder, and provides it to the user.

[0812] Specific examples

[0813] User Input

[0814] Users enter "I want to become a traditional craftsman" into the portal site.

[0815] The user checks the input contents and clicks the send button.

[0816] Information generation and emotion recognition

[0817] The server uses the input together with an emotion engine to analyze the user's emotional state.

[0818] The AI ​​analyzes keywords such as "traditional craftsman" and "repair craftsman" along with the emotional state of "excited" to generate the following information:

[0819] List of schools for training repair craftsmen (traditional craft technical colleges, craft skills training schools, etc.)

[0820] A list of potential job opportunities and related companies

[0821] Information on the qualifications and skills required for repair craftsmen

[0822] Providing information

[0823] The server receives information from the generating AI.

[0824] The server formats the information and displays it with an encouraging message appropriate to the user's emotional state, such as "You're one step closer to making your dreams come true!"

[0825] Establishing contact

[0826] The server calls an API to establish contact with a particular stakeholder (training school, company, certification body, etc.).

[0827] The server retrieves the contact information of each stakeholder and provides it to the user.

[0828] Prompt Sentence Examples

[0829] The following prompt sentences are examples of specific requests that can be entered into the user input module:

[0830] I would like to become a traditional craftsman. Which training school should I attend? Are there any companies that I can work for? I would also like to know about related qualifications.

[0831] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0832] Step 1: User Input

[0833] The user accesses the portal site of the system and enters their wishes into the provided form. For example, they enter their wish to "participate in volunteer activities in developing countries."

[0834] Input: The desired text data entered by the user.

[0835] Output: The desired text data entered is sent to the server as is.

[0836] Step 2: Sending User Input

[0837] The user checks the input and clicks the submit button, which sends the input data to the server.

[0838] Input: The event when the submit button is clicked and the desired text data entered.

[0839] Output: The desired text data sent to the server.

[0840] Step 3: Emotion Recognition

[0841] The server launches an emotion engine based on the received desired data. The emotion engine analyzes the input text and determines the user's emotional state. For example, it analyzes keywords and context in the text to identify emotions such as "excited" or "anxious."

[0842] Input: The desired text data received by the server.

[0843] Output: The user's emotional state (e.g., "excited").

[0844] Step 4: Analyze your desires and emotional state

[0845] The server passes the emotion recognition results and the user's desired data to the generation AI, which then analyzes the data and searches related databases to collect the necessary information.

[0846] Input: User's desired text data and emotional state.

[0847] Output: Analysis results and collected information based on wishes and emotions.

[0848] Step 5: Information Generation

[0849] The generative AI generates the necessary information based on the analysis results of the input. For example, based on the desire to "participate in volunteer activities in developing countries" and the emotional state of "excited," the following information is generated:

[0850] List of volunteer organizations

[0851] Required procedures (visa, vaccinations, etc.)

[0852] Local living information

[0853] Input: Analysis results based on desires and emotional state.

[0854] Output: A list of the generated information.

[0855] Step 6: Provide information

[0856] The server receives the information returned by the generation AI and formats it in a user-friendly format. Taking into account the results of the emotion engine, the server provides information in a way that is appropriate to the user's emotional state. For example, if the user is "excited," a positive and encouraging message is displayed.

[0857] Input: A generated list of information and an emotional state.

[0858] Output: The formatted information presented to the user.

[0859] Step 7: Establishing Contact

[0860] The server calls the API to obtain contact information for relevant stakeholders (e.g., volunteer organizations, companies, certification bodies), and provides the obtained information to the user to support the next action.

[0861] Input: User preferences and relevant stakeholder information.

[0862] Output: Stakeholder contact information and information provided to users.

[0863] (Application example 2)

[0864] 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."

[0865] Conventional shopping support systems collect user preferences, but offer only uniform product and service recommendations based on those preferences, lacking personalized recommendations that take into account the user's emotional state. This results in a less than satisfying shopping experience. Furthermore, establishing contact with stakeholders to realize the user's preferences is a manual process that is inefficient. This results in a complex and time-consuming process for users to take action.

[0866] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to input a preference, means for analyzing the input preference and determining a category, means for generating necessary information based on the preference and the user's emotional state, means for providing the generated information to the user, means for automatically establishing contact with relevant stakeholders, means for analyzing the user's emotional state using an emotion engine, and means for adjusting the presentation of the generated information based on the analyzed emotional state. This enables the proposal of appropriate and personalized products and services based on the user's preference, resulting in a more satisfying shopping experience. Furthermore, because contact with relevant stakeholders is automatically established, the process for the user to realize their preference is made more efficient.

[0867] "User input means" is an interface that allows a user to input desired products or services.

[0868] The "category determination means" is a means for analyzing the desires input by the user and classifying them into an appropriate category.

[0869] The "information generation means" is a means for generating necessary information based on the user's wishes and emotional state.

[0870] "Information provision means" refers to a means for providing the generated information to the user in an appropriate format.

[0871] A "contact establishment method" is a method for automatically establishing contact with relevant stakeholders.

[0872] The "emotion engine" is an engine for analyzing the user's emotional state.

[0873] The "emotion analysis means" is a means for analyzing the user's emotional state using an emotion engine.

[0874] The "expression adjusting means" is a means for adjusting the expression of the generated information based on the analyzed emotional state.

[0875] "Generative AI" is artificial intelligence that generates information based on desires and emotional states.

[0876] "Application Program Interface" means a program interface for establishing contact with stakeholders.

[0877] The following describes the mode for carrying out this invention. The present invention is a personalized shopping assistant system for improving the shopping experience in brick-and-mortar stores. This system is installed on a smartphone or smart glasses and analyzes the user's desires and emotional state to suggest optimal products and services.

[0878] System Configuration

[0879] Hardware and Software

[0880] 1. User Input Method:

[0881] Using a smartphone or smart glasses, the device provides an interface for users to input their preferences, typically using a touchscreen or voice input.

[0882] 2. Category determination method:

[0883] We analyze the user's input preferences and classify them into appropriate categories. We use common natural language processing (NLP) tools and libraries (e.g., NLTK, spaCy) to analyze preferences.

[0884] 3. Emotion analysis means:

[0885] The emotional state of the user is analyzed using an emotion engine. Emotion analysis takes into account keywords in the input, sentence structure, input speed, etc. The emotion engine uses the Python EmotionRecognizer library.

[0886] 4. Information generation means:

[0887] Based on the user's preferences and emotional state, information is generated using generative AI (e.g., OpenAI's GPT-3). The generated information is retrieved from relevant databases to suggest optimal products and services to the user.

[0888] 5. Information provision method:

[0889] The generated information is presented to the user through the display of a smartphone or smart glasses, and the way this information is displayed is adjusted based on the results of emotion analysis.

[0890] 6. Means of establishing contact:

[0891] Use APIs to automatically establish contact with relevant stakeholders, allowing for efficient communication with volunteer organizations, certification bodies, vaccination agencies, etc.

[0892] Example of processing flow

[0893] 1. User Input

[0894] A user uses a smartphone or smart glasses to input the product or service they are looking for, for example, "I'm looking for new fashion items."

[0895] 2. Category determination

[0896] The server analyzes the input and classifies it into a "fashion" category, using NLP tools to determine relationships.

[0897] 3. Emotion analysis

[0898] The emotion engine analyzes the user's emotional state to determine that they are "curious." The emotion is determined from the input speed and keywords in the text.

[0899] 4. Information generation

[0900] Enter the following prompts into the generative AI model (OpenAI's GPT-3) to generate information:

[0901] Want: Looking for new fashion items

[0902] Emotion: Curious

[0903] Please suggest products or services that best fit these criteria.

[0904] Based on these prompts, the generative AI generates information about the latest trending items and the stores that sell them.

[0905] 5. Information provision

[0906] The server receives the generated information, adjusts the display format to match the user's emotional state, and displays it on the smartphone or smart glasses screen, for example, displaying product images and descriptions along with encouraging messages.

[0907] 6. Establishing Contact

[0908] The server makes API calls to establish contact with the relevant store or support service, providing the contact information to the user so they can contact them directly.

[0909] As described above, this system analyzes users' preferences and emotional state, suggests optimal products and services, and improves the shopping experience. It also automatically establishes contact with relevant stakeholders, allowing users to take action smoothly.

[0910] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0911] Step 1:

[0912] Users input their desired products or services through the interface of their smartphone or smart glasses. The input data is sent to the server by the user device. An example input might be "I'm looking for a new fashion item."

[0913] Input: User's preference (text)

[0914] Output: Desired data sent to the server

[0915] Step 2:

[0916] The server analyzes the received desired data. For analysis, it uses NLP tools (e.g., NLTK or spaCy) to extract related keywords from the input content and determine the category. In this case, the keyword "fashion" is extracted and the category "fashion" is determined.

[0917] Input: User's desired data

[0918] Output: Parsed category (e.g. fashion)

[0919] Step 3:

[0920] The server performs emotion recognition based on the desired data. It uses an emotion engine (e.g., EmotionRecognizer library) to analyze the user's emotional state based on their text expression and typing speed. In this case, the emotion is analyzed as "curious."

[0921] Input: User's desired data

[0922] Output: Parsed emotional state (e.g., curious)

[0923] Step 4:

[0924] The server generates information by sending prompts to a generative AI model (e.g., OpenAI's GPT-3) based on the user's desires and emotional state. An example prompt is "Desire: Looking for a new fashion item. Emotion: Curious. Please suggest products and services that best suit these conditions." The generative AI analyzes this and generates information.

[0925] Input: User's desires and emotional state

[0926] Output: Generated information (e.g., latest trending items and store information)

[0927] Step 5:

[0928] The server receives the generated information and adjusts the display format based on the emotion analysis results. For example, the display format may be adjusted to include an encouraging message. The adjusted information is then displayed on the display of the smartphone or smart glasses.

[0929] Input: Generated information and emotional state

[0930] Output: Adjusted display information

[0931] Step 6:

[0932] The server calls the API to establish contact with the relevant stakeholders (stores and support services). The contact information obtained through the API is provided to the user so that they can contact them directly.

[0933] Input: Relevant stakeholder information

[0934] Output: Stakeholder contact information

[0935] 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.

[0936] 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.

[0937] 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.

[0938] [Third embodiment]

[0939] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0940] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0941] 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).

[0942] 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.

[0943] 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.

[0944] 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).

[0945] 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.

[0946] 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.

[0947] 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.

[0948] 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.

[0949] 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.

[0950] 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."

[0951] The embodiment of the present invention is described below. First, the system consists of a web interface for users to input their preferences, an information processing module using generative AI, an information provision module, and a module for establishing contact with stakeholders.

[0952] System Overview

[0953] 1. User input module: A form is provided for users to enter their preferences. Through this form, users can enter specific preferences, such as "I want to become a traditional craftsman" or "I want to participate in volunteer activities in developing countries."

[0954] 2. Generative AI module: The server calls the generative AI and analyzes the input preference. Based on the analysis results, it generates relevant information and returns it to the server. For example, for a preference such as "I want to become a traditional craftsman," it generates information on appropriate training programs, related companies, and necessary qualifications.

[0955] 3. Information provision module: The server formats the information received from the generation AI and provides it to the user, allowing the user to obtain the necessary procedures and detailed information.

[0956] 4. Contact Establishment Module: The server automatically establishes contact with relevant stakeholders, for example, providing contact information for training programs, real estate agencies, local government information, etc.

[0957] Explaining program processing in natural language

[0958] User Input Module

[0959] A user accesses the portal site and enters their wishes. For example, they might enter a wish to "participate in volunteer activities in developing countries." When the user confirms the information and clicks the submit button, this information is sent to the server.

[0960] Generative AI Module

[0961] The server receives the user's wishes and passes them to the generation AI. The generation AI analyzes the wishes and collects and generates the necessary information from the relevant database. For example, for a wish to "participate in volunteer activities in developing countries," the following information is generated:

[0962] List of volunteer organizations

[0963] Required procedures (visa, vaccinations, etc.)

[0964] Local living information

[0965] Information Module

[0966] The server receives the information returned by the AI ​​generator and formats it into a user-friendly format, which is then presented to the user through a web page or application, such as a list of volunteer organizations, details of procedures, or information useful for local life.

[0967] Contact Establishment Module

[0968] The server automatically establishes contact with relevant stakeholders (e.g., volunteer organizations, visa application agencies, vaccination agencies) by using an API to retrieve each stakeholder's contact information and provide it to the user.

[0969] Specific examples

[0970] User Input

[0971] 1. The user enters into the portal site, "I want to become a traditional craftsman."

[0972] 2. The user checks the input and clicks the submit button.

[0973] information generation

[0974] 1. The server passes the input to the generation AI.

[0975] 2. The AI ​​analyzes keywords such as "traditional crafts" and "repair craftsman" and generates the following information:

[0976] List of schools for training repair craftsmen (traditional craft technical colleges, craft skills training schools, etc.)

[0977] A list of potential job opportunities and related companies

[0978] Information on the qualifications and skills required for repair craftsmen

[0979] Providing information

[0980] 1. The server receives information from the generation AI.

[0981] 2. The server formats the information and displays it to the user, allowing them to retrieve specific instructions and details they need.

[0982] Establishing contact

[0983] 1. The server calls an API to establish contact with a specific stakeholder (training school, company, certification body, etc.).

[0984] 2. The server retrieves the contact information of each stakeholder and provides it to the user.

[0985] In this way, this system provides consistent support, from the moment the user inputs their wishes, through to the AI ​​analyzing and generating information, providing the information, and establishing contact with relevant stakeholders, making it possible for users to realize their dreams and hopes.

[0986] The processing flow will be explained below.

[0987] Step 1:

[0988] The user accesses the portal site.

[0989] Step 2:

[0990] The user enters their desired interests (e.g., "I want to become a traditional craftsman") into the provided input form.

[0991] Step 3:

[0992] The user checks the input information and clicks the "Submit" button.

[0993] Step 4:

[0994] The server receives the desired data from the user.

[0995] Step 5:

[0996] The server analyzes the received data and determines the desired category (e.g., occupation, volunteering, residential choice, hobby).

[0997] Step 6:

[0998] The server passes the discrimination results to the generation AI module.

[0999] Step 7:

[1000] The generation AI analyzes the desired data it receives and collects the necessary information from relevant databases.

[1001] Step 8:

[1002] Based on the collected information, the generation AI generates specific information (e.g., training programs, related companies, qualification information, etc.) that corresponds to the user's wishes.

[1003] Step 9:

[1004] The generation AI returns the generated information to the server in JSON format.

[1005] Step 10:

[1006] The server receives the JSON data returned by the generated AI.

[1007] Step 11:

[1008] The server formats the received data into a user-friendly format (e.g., an HTML page).

[1009] Step 12:

[1010] The server provides the formatted information to the user.

[1011] Step 13:

[1012] The user views the provided information and obtains the necessary procedures and detailed information.

[1013] Step 14:

[1014] The server invokes an API to establish contact with the relevant stakeholders.

[1015] Step 15:

[1016] The server retrieves stakeholder contact information through an API.

[1017] Step 16:

[1018] The server provides the retrieved contact information to the user.

[1019] Step 17:

[1020] Users will be contacted directly with the relevant stakeholders using the contact information provided.

[1021] Step 18:

[1022] If a user requires additional information or support, they submit a request to the server using the contact form.

[1023] Step 19:

[1024] The server receives additional requests and calls the generation AI again to generate the necessary information and provide it to the user.

[1025] Example 1

[1026] 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."

[1027] In conventional systems, even if users input specific requests, it was difficult to properly analyze them and provide the necessary information quickly and accurately. Furthermore, there were insufficient means for establishing contact with relevant stakeholders, which often required users to search for the necessary information themselves, which was time-consuming and labor-intensive. This resulted in delays in realizing users' requests.

[1028] 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.

[1029] In this invention, the server includes: means for a user to input preferences; means for analyzing the input preferences and determining categories; means including a generative AI model for generating necessary information based on the preferences; means for providing the generated information to the user; means for formatting the generated information into a user-friendly format; and means including an application program interface for automatically establishing contact with relevant stakeholders. This makes it possible to quickly and accurately generate and provide information based on the preferences input by the user, and automatically establish contact with relevant stakeholders.

[1030] "User" means an individual or entity that uses the System to input preferences and obtain information.

[1031] "Means for inputting preferences" refers to a mechanism that provides an interface that allows users to input their preferences in text format.

[1032] The "means for analyzing and determining the category" is an algorithm that analyzes the input preference and determines the appropriate category based on the content.

[1033] A "generative AI model" is a model that uses artificial intelligence technology to generate relevant information based on the user's wishes.

[1034] "Means for generating information" refers to the function of using a generative AI model to collect and generate information according to the user's wishes.

[1035] The "means of providing to users" refers to a mechanism for formatting the generated information and providing it to users in an easy-to-read format.

[1036] The "means for formatting into a user-friendly format" refers to a processing means for converting the generated information into a format that is easy for the user to understand.

[1037] "Relevant stakeholders" are institutions, organizations, and companies that can provide information and services relevant to the user's wishes.

[1038] "Application Program Interface for automatically establishing contact" refers to API technology that the system uses to automatically communicate with external stakeholders.

[1039] A "system" is a set of computer programs and their execution environment that integrate user input, information analysis and generation, information provision, and stakeholder contact establishment.

[1040] The present invention is implemented using a user interface, a generative AI model, a server, a database, and an application program interface (API) that supports users from inputting their preferences to providing information and establishing contact with relevant stakeholders.

[1041] 1. User Input Module

[1042] Users access the system's portal site using a web browser. The portal site provides a form for users to enter their preferences. Users enter their preferences specifically and click the submit button. This input form is implemented using HTML and JavaScript.

[1043] Examples:

[1044] A user enters into a portal site that they would like to participate in volunteer activities in developing countries.

[1045] 2. Data Transmission and Reception

[1046] The server receives the data entered by the user in the input form. The data is sent to the server as an HTTP POST request, and the server parses the request to extract the input. This process uses AJAX techniques to send the data asynchronously.

[1047] 3. Generative AI Module

[1048] The server passes the received data to the generative AI. The generative AI model uses natural language processing technology to analyze the input text and collect and generate relevant information. The generative AI model is cloud-based and runs using advanced computing resources.

[1049] Examples:

[1050] The generative AI model generates the following information in response to the input "I want to participate in volunteer work in developing countries":

[1051] List of volunteer organizations

[1052] Required procedures (visa, vaccinations, etc.)

[1053] Local living information

[1054] 4. Information Module

[1055] The server receives the information returned by the generation AI and formats it into a user-friendly format using an HTML template engine (e.g., Thymeleaf or ERB) and presents the information as a web page, allowing the user to retrieve specific procedures and necessary details.

[1056] 5. Contact Establishment Module

[1057] The server uses the API to establish contact with relevant stakeholders (e.g., volunteer organizations, visa application agencies, vaccination agencies), parses the contact information returned by the API, and provides it to the user.

[1058] Examples:

[1059] The server calls a specific API to retrieve contact information for the volunteer organization.

[1060] Prompt Sentence Examples

[1061] "What is the process for participating in volunteer work in developing countries?"

[1062] "Please provide me with the information I need to become a traditional craftsman."

[1063] In this way, the system provides comprehensive support to help users realize their wishes through a series of processes. By using a generative AI model, it is possible to provide users with quick and accurate information and automatically establish contact with relevant stakeholders, thereby increasing user convenience.

[1064] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1065] Step 1:

[1066] A user accesses the portal site and enters their wishes. This input form uses HTML and JavaScript, providing an interface that makes it easy for users to enter their wishes. The input data is "I would like to participate in volunteer activities in developing countries," and the submit button is clicked.

[1067] Input: User's wishes (e.g., "I would like to participate in volunteer activities in developing countries")

[1068] Output: Desired data sent

[1069] Step 2:

[1070] The server receives the desired data sent by the user as an HTTP POST request and parses it. A backend service (e.g., Node.js or Django) is used to process the HTTP request and extract the submitted data.

[1071] Input: Submitted desired data

[1072] Output: Parsed desired data

[1073] Step 3:

[1074] The server passes the parsed desired data to a generative AI model, which uses natural language processing techniques to analyze the input text and generate relevant information. This process runs on cloud-based infrastructure (e.g., AWS or Google Cloud).

[1075] Input: Analyzed preference data (e.g., "I would like to participate in volunteer activities in developing countries")

[1076] Output: Generated relevant information (e.g., list of volunteer organizations, necessary procedures, local living information)

[1077] Step 4:

[1078] The server receives the information returned by the generative AI model and formats it into a user-friendly format using an HTML template engine (e.g., Thymeleaf, ERB). The formatted information is then presented to the user in a clear and reliable manner.

[1079] Input: Generated relevant information (e.g., list of volunteer organizations, necessary procedures, local living information)

[1080] Output: Formatted information

[1081] Step 5:

[1082] The server formats the information and displays it in a user interface, allowing users to easily access specific procedures and required details. The display process is performed using a front-end framework (e.g., React, Vue.js).

[1083] Input: Formatted information

[1084] Output: Information displayed on the web page

[1085] Step 6:

[1086] The server makes API calls to establish contact with relevant stakeholders, e.g. to retrieve contact information for volunteer organisations, visa application agencies, vaccination agencies etc. For this purpose it uses external APIs (e.g. REST APIs).

[1087] Input: Request for required stakeholder information

[1088] Output: Retrieved contact information

[1089] Step 7:

[1090] The server parses the retrieved contact information and provides it to the user, formatting it and displaying it in a user-friendly format.

[1091] Input: Obtained contact information

[1092] Output: Formatted contact information

[1093] Through each of the above steps, users can quickly and accurately obtain information based on their wishes and establish contact with relevant stakeholders, greatly improving user convenience and accelerating the realization of their wishes.

[1094] (Application example 1)

[1095] 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."

[1096] The present invention relates to a system that efficiently supports users' purchasing behavior by quickly and accurately providing the information desired by the user and presenting product information in specific categories based on that desire. It also aims to enable users to smoothly acquire products by automatically establishing contact with relevant stakeholders. Furthermore, it aims to provide a system that generates product information tailored to the user's budget and enables real-time inventory confirmation.

[1097] 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.

[1098] In this invention, the server includes a means for a user to input preferences, a means for analyzing the input preferences and determining a category, a means for generating necessary information based on the preferences, a means for providing the generated information to the user, a means for automatically establishing contact with relevant stakeholders, a means for providing the generated information as a list of products in a specific category, a means for generating product information with a budget limit based on the user's preferences, and a means for checking product inventory in real time based on the user's preferences and budget. This allows users to easily obtain product information that meets their preferences and makes selections that fit their budget. Furthermore, smooth communication with stakeholders enables a fast and efficient purchasing process.

[1099] "User" means a person who uses the system to input wishes and requests and receive information and services.

[1100] "Wishes" refer to specific requests, desired information, products, etc. that users input into the system.

[1101] "Means" refer to the methods, processes, or modules that a system uses to achieve a specific function.

[1102] "Analysis" is the process of examining input data or information and determining its meaning or category.

[1103] A "category" is a standard or classification for grouping and classifying information.

[1104] "Necessary information" refers to data and materials that are useful to the user and are generated according to the user's wishes.

[1105] "Generate" refers to the process of creating new information or data based on input data.

[1106] "Providing" means presenting the generated information to the user in a format that is easy to view.

[1107] "Stakeholders" are external parties, organizations, and companies that are involved with the system.

[1108] "Automatically establish contact" means that the system automatically coordinates with the necessary stakeholders at the user's request.

[1109] A "product list" is a list of multiple products selected based on the user's preferences.

[1110] The "budget limit" is the upper limit of the amount that a user sets when purchasing a desired product.

[1111] "Real-time inventory check" refers to the process of instantly checking current inventory status.

[1112] An embodiment of the present invention is described below. The system comprises a means for a user to input preferences, a means for analyzing the input preferences and determining a category, a means for generating necessary information based on the preferences, a means for providing the generated information to the user, and a means for automatically establishing contact with relevant stakeholders. The system further includes a means for providing the generated information as a list of products in a specific category, a means for generating product information with a budget limit based on the user's preferences, and a means for checking the availability of products in real time based on the user's preferences and budget.

[1113] System configuration

[1114] User Input Module:

[1115] It provides a form for users to enter their preferences. Through this form, users can enter specific preferences such as "I want eco-friendly fashion items" or "I want recommended gadgets for under 10,000 yen." The form includes items such as the desired product category and budget.

[1116] Generative AI module:

[1117] The server receives the user's request and passes it to the generation AI, which includes Hugging Face's Transformers pipeline (e.g., GPT-3). The generation AI analyzes the user's request and collects and generates the necessary information from the relevant database.

[1118] Specifically, if a user inputs "I want eco-friendly fashion items," the AI ​​will generate a list of eco-certified fashion products. Similarly, if a user inputs "I want recommended gadgets under 10,000 yen," the AI ​​will generate a list of highly rated gadgets within that budget.

[1119] Informational modules:

[1120] The server receives the information returned by the generation AI, formats it, and provides it to the user in the form of a link to a detailed page containing product images, prices, ratings, and availability, allowing the user to find the product information that best suits their needs.

[1121] Contact Establishment Module:

[1122] The server establishes contact with relevant stakeholders (e.g., merchants and delivery services) by, for example, using APIs to check stock availability with merchants in real time and providing delivery options, thus providing a smooth product purchase experience for the user.

[1123] Program processing

[1124] The system includes a web server built using the Flask framework. The user input module allows users to input their preferences and send them to the server. The generation AI module uses Hugging Face's GPT-3 to analyze the user's preferences and generate relevant information. The information provision module formats the generated information and displays it to the user. The contact establishment module uses the requests library to connect with external stakeholders via API, providing real-time inventory confirmation and delivery options.

[1125] Specific examples

[1126] For example, if a user enters "I'm looking for eco-friendly fashion items" into a form, the Generative AI will generate information based on the following prompt:

[1127] text

[1128] User's preference: Eco-friendly fashion items, Budget: Under 5,000 yen

[1129] In response, the AI ​​generates a list of items such as eco bags and bamboo toothbrushes. This information is formatted and provided to the user along with a link to the product's detail page. The server also checks inventory in real time through API connections with retailers, providing the user with the current inventory status.

[1130] Thus, the present invention is a system that not only analyzes user desires and provides appropriate product information, but also establishes smooth communication with related stakeholders.

[1131] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1132] Step 1:

[1133] User preference input

[1134] The user accesses the device's web interface and inputs their preferences, such as "I want eco-friendly fashion items" or "I want recommended gadgets for under 10,000 yen." The input data includes information about the desired product category and budget. The input data is converted to JSON format and sent to the server.

[1135] Input: User's preference (category, budget, etc.)

[1136] Output: Desired data in JSON format

[1137] Step 2:

[1138] Desired analysis and category determination

[1139] The server receives the user's desired data in JSON format. This data is then passed to a generative AI model (such as GPT-3) for analysis. The generative AI analyzes the user's preferences and determines the desired product category and conditions. It also generates a prompt based on the analyzed content.

[1140] Input: Desired data in JSON format

[1141] Output: Analysis results (prompt statements, etc.)

[1142] What happens:

[1143] Invoking a generative AI (e.g., GPT-3 for Hugging Face)

[1144] Generate prompt statement

[1145] Step 3:

[1146] information generation

[1147] The server then collects the necessary information from relevant databases based on the analysis results from the generation AI. For example, it generates a list of eco-friendly fashion items or a list of recommended gadgets under 10,000 yen. The collected information consists of detailed data such as product name, price, rating, and stock status.

[1148] Input: Analysis results (user's desired category, budget, etc.)

[1149] Output: Product information list

[1150] What happens:

[1151] Database Access and Information Collection

[1152] Step 4:

[1153] Providing information

[1154] The server formats the collected product information and converts it into a user-friendly format. The formatted information is provided to the user as a link to a detail page that includes product images, prices, ratings, stock status, etc. The technologies used are web page generation using Flask and HTML rendering using a template engine.

[1155] Input: Product information list

[1156] Output: Formatted product information (web page, application display format)

[1157] What happens:

[1158] HTML rendering, information presentation using Flask

[1159] Step 5:

[1160] Establishing contact with stakeholders

[1161] The server establishes contact with relevant stakeholders (e.g., sellers, delivery services, etc.). For example, it uses the requests library to call seller APIs to check inventory in real time, and delivery service APIs to provide delivery options. This allows users to instantly check current stock availability and delivery terms.

[1162] Input: Product information list, user's desired conditions

[1163] Output: Detailed inventory check results, shipping options information

[1164] What happens:

[1165] API calls and external integration using the requests library

[1166] In this way, the system analyzes the user's preferences at each step and provides appropriate product information. By establishing smooth communication with stakeholders, the system streamlines the user's purchasing behavior.

[1167] 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.

[1168] The following describes an embodiment of the present invention. The system of the present invention has a function to respond to the emotional state of the user by combining a means for inputting user preferences, a means for generating and providing information using a generation AI, a means for establishing contact with stakeholders, and an emotion engine.

[1169] System Overview

[1170] 1. User input module: A form is provided for users to enter their preferences. Through this form, users can enter specific preferences, such as "I want to become a traditional craftsman" or "I want to participate in volunteer activities in developing countries."

[1171] 2. Emotion Recognition Module: The emotion engine built into the server analyzes the user's input and interactions to recognize the user's emotional state (e.g., joy, sadness, anxiety).

[1172] 3. Generative AI module: The server calls the generative AI and analyzes the input desires and emotional state. Based on the analysis results, the necessary information is collected from related databases and generated. For example, for the desire to "become a traditional craftsman" and the emotional state of "being curious," appropriate training programs, related companies, and necessary qualifications are generated.

[1173] 4. Information provision module: The server formats the information received from the generation AI and provides it to the user. The information provided takes into account the analysis results of the emotion engine and is provided in content and expression that is appropriate for the user's emotional state. This allows the user to obtain the necessary procedures and detailed information.

[1174] 5. Contact Establishment Module: The server automatically establishes contact with relevant stakeholders by using APIs to obtain contact information for each stakeholder and providing it to the user.

[1175] Explaining program processing in natural language

[1176] User Input Module

[1177] A user accesses the portal site and enters their wishes. For example, they might enter a wish to "participate in volunteer activities in developing countries." When the user confirms the information and clicks the submit button, this information is sent to the server.

[1178] Emotion Recognition Module

[1179] The server receives the desired data from the user and simultaneously analyzes the user's emotional state using an emotion engine, for example, determining whether the user is "excited" or "anxious" based on the user's typing speed and choice of words.

[1180] Generative AI Module

[1181] The server passes the user's wishes and emotional state to the generation AI. The generation AI analyzes the wishes and emotional state, and collects and generates the necessary information from the relevant database. For example, for the wish to "participate in volunteer activities in developing countries" and the emotional state of "excited," the following information is generated:

[1182] List of volunteer organizations

[1183] Required procedures (visa, vaccinations, etc.)

[1184] Local living information

[1185] Information Module

[1186] The server receives the information returned by the generation AI and formats it into a user-friendly format (e.g., an HTML page). It incorporates the analysis results of the emotion engine and includes expressions and messages appropriate to the user's emotional state. For example, if the user is "excited," a positive and encouraging message is displayed.

[1187] Contact Establishment Module

[1188] The server calls an API to establish contact with relevant stakeholders (e.g., volunteer organizations, visa application agencies, vaccination agencies), retrieves contact information for each stakeholder, and provides it to the user.

[1189] Specific examples

[1190] User Input

[1191] 1. The user enters into the portal site, "I want to become a traditional craftsman."

[1192] 2. The user checks the input and clicks the submit button.

[1193] Information generation and emotion recognition

[1194] 1. The server uses the input content along with the emotion engine to analyze the user's emotional state.

[1195] 2. The generating AI analyzes keywords such as "traditional craftsman" and "repair craftsman" and the emotional state "excited" to generate the following information:

[1196] List of schools for training repair craftsmen (traditional craft technical colleges, craft skills training schools, etc.)

[1197] A list of potential job opportunities and related companies

[1198] Information on the qualifications and skills required for repair craftsmen

[1199] Providing information

[1200] 1. The server receives information from the generation AI.

[1201] 2. The server formats the information and displays it with an encouraging message appropriate to the user's emotional state, such as "You're one step closer to making your dreams come true!"

[1202] Establishing contact

[1203] 1. The server calls an API to establish contact with a specific stakeholder (training school, company, certification body, etc.).

[1204] 2. The server retrieves the contact information of each stakeholder and provides it to the user.

[1205] In this way, the system effectively supports the realization of users' dreams and hopes through a series of steps: starting with the user inputting their wishes, followed by analysis and generation of information using generative AI, analysis of their emotional state using an emotion engine and provision of information accordingly, and finally establishing contact with relevant stakeholders.

[1206] The processing flow will be explained below.

[1207] Step 1:

[1208] The user accesses the portal site.

[1209] Step 2:

[1210] The user enters their desired interests (e.g., "I want to become a traditional craftsman") into the provided input form.

[1211] Step 3:

[1212] The user checks the input information and clicks the "Submit" button.

[1213] Step 4:

[1214] The server receives the desired data from the user.

[1215] Step 5:

[1216] The server analyzes the received data and determines the desired category (e.g., occupation, volunteering, residential choice, hobby).

[1217] Step 6:

[1218] The server passes the results of the discrimination to the generation AI module and emotion engine.

[1219] Step 7:

[1220] The emotion engine analyzes user input and determines the user's emotional state (e.g., happy, sad, anxious).

[1221] Step 8:

[1222] The generative AI analyzes the user's wishes and emotional state, and collects and generates the necessary information from relevant databases.

[1223] Step 9:

[1224] The generation AI generates information based on user preferences (e.g., a list of training programs, a list of related companies, and required qualifications).

[1225] Step 10:

[1226] The generation AI returns the generated information to the server in JSON format.

[1227] Step 11:

[1228] The server receives the JSON data returned by the generated AI.

[1229] Step 12:

[1230] The server formats the received data into a user-friendly format (e.g., HTML page), incorporating the analysis results of the emotion engine and adding expressions appropriate to the user's emotional state.

[1231] Step 13:

[1232] The server provides the formatted information to the user. The user then browses the information and obtains the necessary procedures and detailed information. For example, a message such as "You're one step closer to making your dreams come true!" is displayed.

[1233] Step 14:

[1234] The server invokes an API to establish contact with the relevant stakeholders.

[1235] Step 15:

[1236] The server retrieves stakeholder contact information through an API.

[1237] Step 16:

[1238] The server provides the retrieved contact information to the user.

[1239] Step 17:

[1240] Users will be contacted directly with the relevant stakeholders using the contact information provided.

[1241] Step 18:

[1242] If a user requires additional information or support, they submit a request to the server using the contact form.

[1243] Step 19:

[1244] The server receives additional requests and again calls the generation AI and emotion engine to generate the necessary information and provide it to the user.

[1245] Example 2

[1246] 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."

[1247] When a user inputs their preferences, it is important to provide information that matches those preferences. However, conventional systems often provide information without considering the user's emotional state, which fails to sufficiently improve user satisfaction. Furthermore, establishing contact with relevant stakeholders must be done manually, which is time-consuming and reduces efficiency. Furthermore, generating information based on preferences requires accuracy and appropriate category determination, but conventional systems are unable to address these challenges.

[1248] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for a user to input a preference, a means for analyzing the input preference and determining a category, a means for generating necessary information based on the preference, a means for providing the generated information to the user, a means for automatically establishing contact with relevant stakeholders, an emotion recognition means for analyzing the user's emotional state, and a means for adjusting the information presentation method based on the emotional state. This makes it possible to provide information taking the user's emotional state into consideration, thereby improving user satisfaction and increasing the efficiency of establishing contact with stakeholders. Furthermore, accurate information generation and category determination can be performed based on the preference.

[1249] The "means for user input of wishes" is an interface that allows a user to input specific wishes or requests to the system.

[1250] The "means for analyzing input preferences and determining categories" is a function for analyzing preferences input by the user and classifying the contents into specific categories.

[1251] "Means for generating necessary information based on user preferences" refers to a function that automatically collects and generates relevant information based on user preferences.

[1252] The "means for providing the generated information to the user" is a function for providing the generated information to the user in an appropriate format.

[1253] "Means for automatically establishing contact with relevant stakeholders" means means for automatically obtaining and providing contact information for third parties relevant to the user's wishes.

[1254] The "emotion recognition means for analyzing the user's emotional state" is a function for analyzing the user's input data and behavior to identify the user's emotional state.

[1255] The "means for adjusting the method of presenting information based on the emotional state" is a function for adjusting the method of presenting information and the content of messages according to the emotional state of the user.

[1256] The embodiment of the present invention is described below. The system of the present invention has a function to respond to the emotional state of the user by combining a means for inputting user preferences, a means for generating and providing information using a generative AI, a means for establishing contact with stakeholders, and an emotion engine.

[1257] System Overview

[1258] 1. User Input Module:

[1259] A form is provided for users to enter their aspirations. For example, they can enter specific aspirations such as "I want to become a repair craftsman of traditional crafts" or "I want to participate in volunteer activities in developing countries." This form is implemented as a web page, and the input contents are sent to the server.

[1260] 2. Emotion Recognition Module:

[1261] The server analyzes the received user preference data using an emotion engine to identify the user's emotional state (e.g., joy, sadness, anxiety) using algorithms such as typing speed, keywords in the sentence, and context analysis.

[1262] 3. Generative AI module:

[1263] The server passes the user's wishes and emotional state to the generation AI, which then collects and generates the necessary information from relevant databases based on those wishes and emotional state. For example, in response to a wish to "participate in volunteer activities in developing countries" and an emotional state of "excitement," the generation AI generates a list of volunteer organizations, necessary procedures (visas, vaccinations, etc.), and information about life in the local area.

[1264] 4. Information module:

[1265] The server formats the information received from the generation AI and provides it to the user. The information provided takes into account the analysis results of the emotion engine and is provided with content and expression appropriate to the user's emotional state. For example, if the user is "excited," a positive and encouraging message will be included.

[1266] 5. Contact Establishment Module:

[1267] The server calls an API to establish contact with relevant stakeholders (e.g., volunteer organizations, companies, certification bodies), retrieves contact information for each stakeholder, and provides it to the user.

[1268] Specific examples

[1269] User Input

[1270] Users enter "I want to become a traditional craftsman" into the portal site.

[1271] The user checks the input contents and clicks the send button.

[1272] Information generation and emotion recognition

[1273] The server uses the input together with an emotion engine to analyze the user's emotional state.

[1274] The AI ​​analyzes keywords such as "traditional craftsman" and "repair craftsman" along with the emotional state of "excited" to generate the following information:

[1275] List of schools for training repair craftsmen (traditional craft technical colleges, craft skills training schools, etc.)

[1276] A list of potential job opportunities and related companies

[1277] Information on the qualifications and skills required for repair craftsmen

[1278] Providing information

[1279] The server receives information from the generating AI.

[1280] The server formats the information and displays it with an encouraging message appropriate to the user's emotional state, such as "You're one step closer to making your dreams come true!"

[1281] Establishing contact

[1282] The server calls an API to establish contact with a particular stakeholder (training school, company, certification body, etc.).

[1283] The server retrieves the contact information of each stakeholder and provides it to the user.

[1284] Prompt Sentence Examples

[1285] The following prompt sentences are examples of specific requests that can be entered into the user input module:

[1286] I would like to become a traditional craftsman. Which training school should I attend? Are there any companies that I can work for? I would also like to know about related qualifications.

[1287] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1288] Step 1: User Input

[1289] The user accesses the portal site of the system and enters their wishes into the provided form. For example, they enter their wish to "participate in volunteer activities in developing countries."

[1290] Input: The desired text data entered by the user.

[1291] Output: The desired text data entered is sent to the server as is.

[1292] Step 2: Sending User Input

[1293] The user checks the input and clicks the submit button, which sends the input data to the server.

[1294] Input: The event when the submit button is clicked and the desired text data entered.

[1295] Output: The desired text data sent to the server.

[1296] Step 3: Emotion Recognition

[1297] The server launches an emotion engine based on the received desired data. The emotion engine analyzes the input text and determines the user's emotional state. For example, it analyzes keywords and context in the text to identify emotions such as "excited" or "anxious."

[1298] Input: The desired text data received by the server.

[1299] Output: The user's emotional state (e.g., "excited").

[1300] Step 4: Analyze your desires and emotional state

[1301] The server passes the emotion recognition results and the user's desired data to the generation AI, which then analyzes the data and searches related databases to collect the necessary information.

[1302] Input: User's desired text data and emotional state.

[1303] Output: Analysis results and collected information based on wishes and emotions.

[1304] Step 5: Information Generation

[1305] The generative AI generates the necessary information based on the analysis results of the input. For example, based on the desire to "participate in volunteer activities in developing countries" and the emotional state of "excited," the following information is generated:

[1306] List of volunteer organizations

[1307] Required procedures (visa, vaccinations, etc.)

[1308] Local living information

[1309] Input: Analysis results based on desires and emotional state.

[1310] Output: A list of the generated information.

[1311] Step 6: Provide information

[1312] The server receives the information returned by the generation AI and formats it in a user-friendly format. Taking into account the results of the emotion engine, the server provides information in a way that is appropriate to the user's emotional state. For example, if the user is "excited," a positive and encouraging message is displayed.

[1313] Input: A generated list of information and an emotional state.

[1314] Output: The formatted information presented to the user.

[1315] Step 7: Establishing Contact

[1316] The server calls the API to obtain contact information for relevant stakeholders (e.g., volunteer organizations, companies, certification bodies), and provides the obtained information to the user to support the next action.

[1317] Input: User preferences and relevant stakeholder information.

[1318] Output: Stakeholder contact information and information provided to users.

[1319] (Application example 2)

[1320] 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."

[1321] Conventional shopping support systems collect user preferences, but offer only uniform product and service recommendations based on those preferences, lacking personalized recommendations that take into account the user's emotional state. This results in a less than satisfying shopping experience. Furthermore, establishing contact with stakeholders to realize the user's preferences is a manual process that is inefficient. This results in a complex and time-consuming process for users to take action.

[1322] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to input a preference, means for analyzing the input preference and determining a category, means for generating necessary information based on the preference and the user's emotional state, means for providing the generated information to the user, means for automatically establishing contact with relevant stakeholders, means for analyzing the user's emotional state using an emotion engine, and means for adjusting the presentation of the generated information based on the analyzed emotional state. This enables the proposal of appropriate and personalized products and services based on the user's preference, resulting in a more satisfying shopping experience. Furthermore, because contact with relevant stakeholders is automatically established, the process for the user to realize their preference is made more efficient.

[1323] "User input means" is an interface that allows a user to input desired products or services.

[1324] The "category determination means" is a means for analyzing the desires input by the user and classifying them into an appropriate category.

[1325] The "information generation means" is a means for generating necessary information based on the user's wishes and emotional state.

[1326] "Information provision means" refers to a means for providing the generated information to the user in an appropriate format.

[1327] A "contact establishment method" is a method for automatically establishing contact with relevant stakeholders.

[1328] The "emotion engine" is an engine for analyzing the user's emotional state.

[1329] The "emotion analysis means" is a means for analyzing the user's emotional state using an emotion engine.

[1330] The "expression adjusting means" is a means for adjusting the expression of the generated information based on the analyzed emotional state.

[1331] "Generative AI" is artificial intelligence that generates information based on desires and emotional states.

[1332] "Application Program Interface" means a program interface for establishing contact with stakeholders.

[1333] The following describes the mode for carrying out this invention. The present invention is a personalized shopping assistant system for improving the shopping experience in brick-and-mortar stores. This system is installed on a smartphone or smart glasses and analyzes the user's desires and emotional state to suggest optimal products and services.

[1334] System Configuration

[1335] Hardware and Software

[1336] 1. User Input Method:

[1337] Using a smartphone or smart glasses, the device provides an interface for users to input their preferences, typically using a touchscreen or voice input.

[1338] 2. Category determination method:

[1339] We analyze the user's input preferences and classify them into appropriate categories. We use common natural language processing (NLP) tools and libraries (e.g., NLTK, spaCy) to analyze preferences.

[1340] 3. Emotion analysis means:

[1341] The emotional state of the user is analyzed using an emotion engine. Emotion analysis takes into account keywords in the input, sentence structure, input speed, etc. The emotion engine uses the Python EmotionRecognizer library.

[1342] 4. Information generation means:

[1343] Based on the user's preferences and emotional state, information is generated using generative AI (e.g., OpenAI's GPT-3). The generated information is retrieved from relevant databases to suggest optimal products and services to the user.

[1344] 5. Information provision method:

[1345] The generated information is presented to the user through the display of a smartphone or smart glasses, and the way this information is displayed is adjusted based on the results of emotion analysis.

[1346] 6. Means of establishing contact:

[1347] Use APIs to automatically establish contact with relevant stakeholders, allowing for efficient communication with volunteer organizations, certification bodies, vaccination agencies, etc.

[1348] Example of processing flow

[1349] 1. User Input

[1350] A user uses a smartphone or smart glasses to input the product or service they are looking for, for example, "I'm looking for new fashion items."

[1351] 2. Category determination

[1352] The server analyzes the input and classifies it into a "fashion" category, using NLP tools to determine relationships.

[1353] 3. Emotion analysis

[1354] The emotion engine analyzes the user's emotional state to determine that they are "curious." The emotion is determined from the input speed and keywords in the text.

[1355] 4. Information generation

[1356] Enter the following prompts into the generative AI model (OpenAI's GPT-3) to generate information:

[1357] Want: Looking for new fashion items

[1358] Emotion: Curious

[1359] Please suggest products or services that best fit these criteria.

[1360] Based on these prompts, the generative AI generates information about the latest trending items and the stores that sell them.

[1361] 5. Information provision

[1362] The server receives the generated information, adjusts the display format to match the user's emotional state, and displays it on the smartphone or smart glasses screen, for example, displaying product images and descriptions along with encouraging messages.

[1363] 6. Establishing Contact

[1364] The server makes API calls to establish contact with the relevant store or support service, providing the contact information to the user so they can contact them directly.

[1365] As described above, this system analyzes users' preferences and emotional state, suggests optimal products and services, and improves the shopping experience. It also automatically establishes contact with relevant stakeholders, allowing users to take action smoothly.

[1366] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1367] Step 1:

[1368] Users input their desired products or services through the interface of their smartphone or smart glasses. The input data is sent to the server by the user device. An example input might be "I'm looking for a new fashion item."

[1369] Input: User's preference (text)

[1370] Output: Desired data sent to the server

[1371] Step 2:

[1372] The server analyzes the received desired data. For analysis, it uses NLP tools (e.g., NLTK or spaCy) to extract related keywords from the input content and determine the category. In this case, the keyword "fashion" is extracted and the category "fashion" is determined.

[1373] Input: User's desired data

[1374] Output: Parsed category (e.g. fashion)

[1375] Step 3:

[1376] The server performs emotion recognition based on the desired data. It uses an emotion engine (e.g., EmotionRecognizer library) to analyze the user's emotional state based on their text expression and typing speed. In this case, the emotion is analyzed as "curious."

[1377] Input: User's desired data

[1378] Output: Parsed emotional state (e.g., curious)

[1379] Step 4:

[1380] The server generates information by sending prompts to a generative AI model (e.g., OpenAI's GPT-3) based on the user's desires and emotional state. An example prompt is "Desire: Looking for a new fashion item. Emotion: Curious. Please suggest products and services that best suit these conditions." The generative AI analyzes this and generates information.

[1381] Input: User's desires and emotional state

[1382] Output: Generated information (e.g., latest trending items and store information)

[1383] Step 5:

[1384] The server receives the generated information and adjusts the display format based on the emotion analysis results. For example, the display format may be adjusted to include an encouraging message. The adjusted information is then displayed on the display of the smartphone or smart glasses.

[1385] Input: Generated information and emotional state

[1386] Output: Adjusted display information

[1387] Step 6:

[1388] The server calls the API to establish contact with the relevant stakeholders (stores and support services). The contact information obtained through the API is provided to the user so that they can contact them directly.

[1389] Input: Relevant stakeholder information

[1390] Output: Stakeholder contact information

[1391] 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.

[1392] 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.

[1393] 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.

[1394] [Fourth embodiment]

[1395] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1396] 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.

[1397] 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).

[1398] 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.

[1399] 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.

[1400] 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).

[1401] 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.

[1402] 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.

[1403] 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.

[1404] 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.

[1405] 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.

[1406] 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.

[1407] 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."

[1408] The embodiment of the present invention is described below. First, the system consists of a web interface for users to input their preferences, an information processing module using generative AI, an information provision module, and a module for establishing contact with stakeholders.

[1409] System Overview

[1410] 1. User input module: A form is provided for users to enter their preferences. Through this form, users can enter specific preferences, such as "I want to become a traditional craftsman" or "I want to participate in volunteer activities in developing countries."

[1411] 2. Generative AI module: The server calls the generative AI and analyzes the input preference. Based on the analysis results, it generates relevant information and returns it to the server. For example, for a preference such as "I want to become a traditional craftsman," it generates information on appropriate training programs, related companies, and necessary qualifications.

[1412] 3. Information provision module: The server formats the information received from the generation AI and provides it to the user, allowing the user to obtain the necessary procedures and detailed information.

[1413] 4. Contact Establishment Module: The server automatically establishes contact with relevant stakeholders, for example, providing contact information for training programs, real estate agencies, local government information, etc.

[1414] Explaining program processing in natural language

[1415] User Input Module

[1416] A user accesses the portal site and enters their wishes. For example, they might enter a wish to "participate in volunteer activities in developing countries." When the user confirms the information and clicks the submit button, this information is sent to the server.

[1417] Generative AI Module

[1418] The server receives the user's wishes and passes them to the generation AI. The generation AI analyzes the wishes and collects and generates the necessary information from the relevant database. For example, for a wish to "participate in volunteer activities in developing countries," the following information is generated:

[1419] List of volunteer organizations

[1420] Required procedures (visa, vaccinations, etc.)

[1421] Local living information

[1422] Information Module

[1423] The server receives the information returned by the AI ​​generator and formats it into a user-friendly format, which is then presented to the user through a web page or application, such as a list of volunteer organizations, details of procedures, or information useful for local life.

[1424] Contact Establishment Module

[1425] The server automatically establishes contact with relevant stakeholders (e.g., volunteer organizations, visa application agencies, vaccination agencies) by using an API to retrieve each stakeholder's contact information and provide it to the user.

[1426] Specific examples

[1427] User Input

[1428] 1. The user enters into the portal site, "I want to become a traditional craftsman."

[1429] 2. The user checks the input and clicks the submit button.

[1430] information generation

[1431] 1. The server passes the input to the generation AI.

[1432] 2. The AI ​​analyzes keywords such as "traditional crafts" and "repair craftsman" and generates the following information:

[1433] List of schools for training repair craftsmen (traditional craft technical colleges, craft skills training schools, etc.)

[1434] A list of potential job opportunities and related companies

[1435] Information on the qualifications and skills required for repair craftsmen

[1436] Providing information

[1437] 1. The server receives information from the generation AI.

[1438] 2. The server formats the information and displays it to the user, allowing them to retrieve specific instructions and details they need.

[1439] Establishing contact

[1440] 1. The server calls an API to establish contact with a specific stakeholder (training school, company, certification body, etc.).

[1441] 2. The server retrieves the contact information of each stakeholder and provides it to the user.

[1442] In this way, this system provides consistent support, from the moment the user inputs their wishes, through to the AI ​​analyzing and generating information, providing the information, and establishing contact with relevant stakeholders, making it possible for users to realize their dreams and hopes.

[1443] The processing flow will be explained below.

[1444] Step 1:

[1445] The user accesses the portal site.

[1446] Step 2:

[1447] The user enters their desired interests (e.g., "I want to become a traditional craftsman") into the provided input form.

[1448] Step 3:

[1449] The user checks the input information and clicks the "Submit" button.

[1450] Step 4:

[1451] The server receives the desired data from the user.

[1452] Step 5:

[1453] The server analyzes the received data and determines the desired category (e.g., occupation, volunteering, residential choice, hobby).

[1454] Step 6:

[1455] The server passes the discrimination results to the generation AI module.

[1456] Step 7:

[1457] The generation AI analyzes the desired data it receives and collects the necessary information from relevant databases.

[1458] Step 8:

[1459] Based on the collected information, the generation AI generates specific information (e.g., training programs, related companies, qualification information, etc.) that corresponds to the user's wishes.

[1460] Step 9:

[1461] The generation AI returns the generated information to the server in JSON format.

[1462] Step 10:

[1463] The server receives the JSON data returned by the generated AI.

[1464] Step 11:

[1465] The server formats the received data into a user-friendly format (e.g., an HTML page).

[1466] Step 12:

[1467] The server provides the formatted information to the user.

[1468] Step 13:

[1469] The user views the provided information and obtains the necessary procedures and detailed information.

[1470] Step 14:

[1471] The server invokes an API to establish contact with the relevant stakeholders.

[1472] Step 15:

[1473] The server retrieves stakeholder contact information through an API.

[1474] Step 16:

[1475] The server provides the retrieved contact information to the user.

[1476] Step 17:

[1477] Users will be contacted directly with the relevant stakeholders using the contact information provided.

[1478] Step 18:

[1479] If a user requires additional information or support, they submit a request to the server using the contact form.

[1480] Step 19:

[1481] The server receives additional requests and calls the generation AI again to generate the necessary information and provide it to the user.

[1482] Example 1

[1483] 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."

[1484] In conventional systems, even if users input specific requests, it was difficult to properly analyze them and provide the necessary information quickly and accurately. Furthermore, there were insufficient means for establishing contact with relevant stakeholders, which often required users to search for the necessary information themselves, which was time-consuming and labor-intensive. This resulted in delays in realizing users' requests.

[1485] 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.

[1486] In this invention, the server includes: means for a user to input preferences; means for analyzing the input preferences and determining categories; means including a generative AI model for generating necessary information based on the preferences; means for providing the generated information to the user; means for formatting the generated information into a user-friendly format; and means including an application program interface for automatically establishing contact with relevant stakeholders. This makes it possible to quickly and accurately generate and provide information based on the preferences input by the user, and automatically establish contact with relevant stakeholders.

[1487] "User" means an individual or entity that uses the System to input preferences and obtain information.

[1488] "Means for inputting preferences" refers to a mechanism that provides an interface that allows users to input their preferences in text format.

[1489] The "means for analyzing and determining the category" is an algorithm that analyzes the input preference and determines the appropriate category based on the content.

[1490] A "generative AI model" is a model that uses artificial intelligence technology to generate relevant information based on the user's wishes.

[1491] "Means for generating information" refers to the function of using a generative AI model to collect and generate information according to the user's wishes.

[1492] The "means of providing to users" refers to a mechanism for formatting the generated information and providing it to users in an easy-to-read format.

[1493] The "means for formatting into a user-friendly format" refers to a processing means for converting the generated information into a format that is easy for the user to understand.

[1494] "Relevant stakeholders" are institutions, organizations, and companies that can provide information and services relevant to the user's wishes.

[1495] "Application Program Interface for automatically establishing contact" refers to API technology that the system uses to automatically communicate with external stakeholders.

[1496] A "system" is a set of computer programs and their execution environment that integrate user input, information analysis and generation, information provision, and stakeholder contact establishment.

[1497] The present invention is implemented using a user interface, a generative AI model, a server, a database, and an application program interface (API) that supports users from inputting their preferences to providing information and establishing contact with relevant stakeholders.

[1498] 1. User Input Module

[1499] Users access the system's portal site using a web browser. The portal site provides a form for users to enter their preferences. Users enter their preferences specifically and click the submit button. This input form is implemented using HTML and JavaScript.

[1500] Examples:

[1501] A user enters into a portal site that they would like to participate in volunteer activities in developing countries.

[1502] 2. Data Transmission and Reception

[1503] The server receives the data entered by the user in the input form. The data is sent to the server as an HTTP POST request, and the server parses the request to extract the input. This process uses AJAX techniques to send the data asynchronously.

[1504] 3. Generative AI Module

[1505] The server passes the received data to the generative AI. The generative AI model uses natural language processing technology to analyze the input text and collect and generate relevant information. The generative AI model is cloud-based and runs using advanced computing resources.

[1506] Examples:

[1507] The generative AI model generates the following information in response to the input "I want to participate in volunteer work in developing countries":

[1508] List of volunteer organizations

[1509] Required procedures (visa, vaccinations, etc.)

[1510] Local living information

[1511] 4. Information Module

[1512] The server receives the information returned by the generation AI and formats it into a user-friendly format using an HTML template engine (e.g., Thymeleaf or ERB) and presents the information as a web page, allowing the user to retrieve specific procedures and necessary details.

[1513] 5. Contact Establishment Module

[1514] The server uses the API to establish contact with relevant stakeholders (e.g., volunteer organizations, visa application agencies, vaccination agencies), parses the contact information returned by the API, and provides it to the user.

[1515] Examples:

[1516] The server calls a specific API to retrieve contact information for the volunteer organization.

[1517] Prompt Sentence Examples

[1518] "What is the process for participating in volunteer work in developing countries?"

[1519] "Please provide me with the information I need to become a traditional craftsman."

[1520] In this way, the system provides comprehensive support to help users realize their wishes through a series of processes. By using a generative AI model, it is possible to provide users with quick and accurate information and automatically establish contact with relevant stakeholders, thereby increasing user convenience.

[1521] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1522] Step 1:

[1523] A user accesses the portal site and enters their wishes. This input form uses HTML and JavaScript, providing an interface that makes it easy for users to enter their wishes. The input data is "I would like to participate in volunteer activities in developing countries," and the submit button is clicked.

[1524] Input: User's wishes (e.g., "I would like to participate in volunteer activities in developing countries")

[1525] Output: Desired data sent

[1526] Step 2:

[1527] The server receives the desired data sent by the user as an HTTP POST request and parses it. A backend service (e.g., Node.js or Django) is used to process the HTTP request and extract the submitted data.

[1528] Input: Submitted desired data

[1529] Output: Parsed desired data

[1530] Step 3:

[1531] The server passes the parsed desired data to a generative AI model, which uses natural language processing techniques to analyze the input text and generate relevant information. This process runs on cloud-based infrastructure (e.g., AWS or Google Cloud).

[1532] Input: Analyzed preference data (e.g., "I would like to participate in volunteer activities in developing countries")

[1533] Output: Generated relevant information (e.g., list of volunteer organizations, necessary procedures, local living information)

[1534] Step 4:

[1535] The server receives the information returned by the generative AI model and formats it into a user-friendly format using an HTML template engine (e.g., Thymeleaf, ERB). The formatted information is then presented to the user in a clear and reliable manner.

[1536] Input: Generated relevant information (e.g., list of volunteer organizations, necessary procedures, local living information)

[1537] Output: Formatted information

[1538] Step 5:

[1539] The server formats the information and displays it in a user interface, allowing users to easily access specific procedures and required details. The display process is performed using a front-end framework (e.g., React, Vue.js).

[1540] Input: Formatted information

[1541] Output: Information displayed on the web page

[1542] Step 6:

[1543] The server makes API calls to establish contact with relevant stakeholders, e.g. to retrieve contact information for volunteer organisations, visa application agencies, vaccination agencies etc. For this purpose it uses external APIs (e.g. REST APIs).

[1544] Input: Request for required stakeholder information

[1545] Output: Retrieved contact information

[1546] Step 7:

[1547] The server parses the retrieved contact information and provides it to the user, formatting it and displaying it in a user-friendly format.

[1548] Input: Obtained contact information

[1549] Output: Formatted contact information

[1550] Through each of the above steps, users can quickly and accurately obtain information based on their wishes and establish contact with relevant stakeholders, greatly improving user convenience and accelerating the realization of their wishes.

[1551] (Application example 1)

[1552] 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."

[1553] The present invention relates to a system that efficiently supports users' purchasing behavior by quickly and accurately providing the information desired by the user and presenting product information in specific categories based on that desire. It also aims to enable users to smoothly acquire products by automatically establishing contact with relevant stakeholders. Furthermore, it aims to provide a system that generates product information tailored to the user's budget and enables real-time inventory confirmation.

[1554] 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.

[1555] In this invention, the server includes a means for a user to input preferences, a means for analyzing the input preferences and determining a category, a means for generating necessary information based on the preferences, a means for providing the generated information to the user, a means for automatically establishing contact with relevant stakeholders, a means for providing the generated information as a list of products in a specific category, a means for generating product information with a budget limit based on the user's preferences, and a means for checking product inventory in real time based on the user's preferences and budget. This allows users to easily obtain product information that meets their preferences and makes selections that fit their budget. Furthermore, smooth communication with stakeholders enables a fast and efficient purchasing process.

[1556] "User" means a person who uses the system to input wishes and requests and receive information and services.

[1557] "Wishes" refer to specific requests, desired information, products, etc. that users input into the system.

[1558] "Means" refer to the methods, processes, or modules that a system uses to achieve a specific function.

[1559] "Analysis" is the process of examining input data or information and determining its meaning or category.

[1560] A "category" is a standard or classification for grouping and classifying information.

[1561] "Necessary information" refers to data and materials that are useful to the user and are generated according to the user's wishes.

[1562] "Generate" refers to the process of creating new information or data based on input data.

[1563] "Providing" means presenting the generated information to the user in a format that is easy to view.

[1564] "Stakeholders" are external parties, organizations, and companies that are involved with the system.

[1565] "Automatically establish contact" means that the system automatically coordinates with the necessary stakeholders at the user's request.

[1566] A "product list" is a list of multiple products selected based on the user's preferences.

[1567] The "budget limit" is the upper limit of the amount that a user sets when purchasing a desired product.

[1568] "Real-time inventory check" refers to the process of instantly checking current inventory status.

[1569] An embodiment of the present invention is described below. The system comprises a means for a user to input preferences, a means for analyzing the input preferences and determining a category, a means for generating necessary information based on the preferences, a means for providing the generated information to the user, and a means for automatically establishing contact with relevant stakeholders. The system further includes a means for providing the generated information as a list of products in a specific category, a means for generating product information with a budget limit based on the user's preferences, and a means for checking the availability of products in real time based on the user's preferences and budget.

[1570] System configuration

[1571] User Input Module:

[1572] It provides a form for users to enter their preferences. Through this form, users can enter specific preferences such as "I want eco-friendly fashion items" or "I want recommended gadgets for under 10,000 yen." The form includes items such as the desired product category and budget.

[1573] Generative AI module:

[1574] The server receives the user's request and passes it to the generation AI, which includes Hugging Face's Transformers pipeline (e.g., GPT-3). The generation AI analyzes the user's request and collects and generates the necessary information from the relevant database.

[1575] Specifically, if a user inputs "I want eco-friendly fashion items," the AI ​​will generate a list of eco-certified fashion products. Similarly, if a user inputs "I want recommended gadgets under 10,000 yen," the AI ​​will generate a list of highly rated gadgets within that budget.

[1576] Informational modules:

[1577] The server receives the information returned by the generation AI, formats it, and provides it to the user in the form of a link to a detailed page containing product images, prices, ratings, and availability, allowing the user to find the product information that best suits their needs.

[1578] Contact Establishment Module:

[1579] The server establishes contact with relevant stakeholders (e.g., merchants and delivery services) by, for example, using APIs to check stock availability with merchants in real time and providing delivery options, thus providing a smooth product purchase experience for the user.

[1580] Program processing

[1581] The system includes a web server built using the Flask framework. The user input module allows users to input their preferences and send them to the server. The generation AI module uses Hugging Face's GPT-3 to analyze the user's preferences and generate relevant information. The information provision module formats the generated information and displays it to the user. The contact establishment module uses the requests library to connect with external stakeholders via API, providing real-time inventory confirmation and delivery options.

[1582] Specific examples

[1583] For example, if a user enters "I'm looking for eco-friendly fashion items" into a form, the Generative AI will generate information based on the following prompt:

[1584] text

[1585] User's preference: Eco-friendly fashion items, Budget: Under 5,000 yen

[1586] In response, the AI ​​generates a list of items such as eco bags and bamboo toothbrushes. This information is formatted and provided to the user along with a link to the product's detail page. The server also checks inventory in real time through API connections with retailers, providing the user with the current inventory status.

[1587] Thus, the present invention is a system that not only analyzes user desires and provides appropriate product information, but also establishes smooth communication with related stakeholders.

[1588] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1589] Step 1:

[1590] User preference input

[1591] The user accesses the device's web interface and inputs their preferences, such as "I want eco-friendly fashion items" or "I want recommended gadgets for under 10,000 yen." The input data includes information about the desired product category and budget. The input data is converted to JSON format and sent to the server.

[1592] Input: User's preference (category, budget, etc.)

[1593] Output: Desired data in JSON format

[1594] Step 2:

[1595] Desired analysis and category determination

[1596] The server receives the user's desired data in JSON format. This data is then passed to a generative AI model (such as GPT-3) for analysis. The generative AI analyzes the user's preferences and determines the desired product category and conditions. It also generates a prompt based on the analyzed content.

[1597] Input: Desired data in JSON format

[1598] Output: Analysis results (prompt statements, etc.)

[1599] What happens:

[1600] Invoking a generative AI (e.g., GPT-3 for Hugging Face)

[1601] Generate prompt statement

[1602] Step 3:

[1603] information generation

[1604] The server then collects the necessary information from relevant databases based on the analysis results from the generation AI. For example, it generates a list of eco-friendly fashion items or a list of recommended gadgets under 10,000 yen. The collected information consists of detailed data such as product name, price, rating, and stock status.

[1605] Input: Analysis results (user's desired category, budget, etc.)

[1606] Output: Product information list

[1607] What happens:

[1608] Database Access and Information Collection

[1609] Step 4:

[1610] Providing information

[1611] The server formats the collected product information and converts it into a user-friendly format. The formatted information is provided to the user as a link to a detail page that includes product images, prices, ratings, stock status, etc. The technologies used are web page generation using Flask and HTML rendering using a template engine.

[1612] Input: Product information list

[1613] Output: Formatted product information (web page, application display format)

[1614] What happens:

[1615] HTML rendering, information presentation using Flask

[1616] Step 5:

[1617] Establishing contact with stakeholders

[1618] The server establishes contact with relevant stakeholders (e.g., sellers, delivery services, etc.). For example, it uses the requests library to call seller APIs to check inventory in real time, and delivery service APIs to provide delivery options. This allows users to instantly check current stock availability and delivery terms.

[1619] Input: Product information list, user's desired conditions

[1620] Output: Detailed inventory check results, shipping options information

[1621] What happens:

[1622] API calls and external integration using the requests library

[1623] In this way, the system analyzes the user's preferences at each step and provides appropriate product information. By establishing smooth communication with stakeholders, the system streamlines the user's purchasing behavior.

[1624] 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.

[1625] The following describes an embodiment of the present invention. The system of the present invention has a function to respond to the emotional state of the user by combining a means for inputting user preferences, a means for generating and providing information using a generation AI, a means for establishing contact with stakeholders, and an emotion engine.

[1626] System Overview

[1627] 1. User input module: A form is provided for users to enter their preferences. Through this form, users can enter specific preferences, such as "I want to become a traditional craftsman" or "I want to participate in volunteer activities in developing countries."

[1628] 2. Emotion Recognition Module: The emotion engine built into the server analyzes the user's input and interactions to recognize the user's emotional state (e.g., joy, sadness, anxiety).

[1629] 3. Generative AI module: The server calls the generative AI and analyzes the input desires and emotional state. Based on the analysis results, the necessary information is collected from related databases and generated. For example, for the desire to "become a traditional craftsman" and the emotional state of "being curious," appropriate training programs, related companies, and necessary qualifications are generated.

[1630] 4. Information provision module: The server formats the information received from the generation AI and provides it to the user. The information provided takes into account the analysis results of the emotion engine and is provided in content and expression that is appropriate for the user's emotional state. This allows the user to obtain the necessary procedures and detailed information.

[1631] 5. Contact Establishment Module: The server automatically establishes contact with relevant stakeholders by using APIs to obtain contact information for each stakeholder and providing it to the user.

[1632] Explaining program processing in natural language

[1633] User Input Module

[1634] A user accesses the portal site and enters their wishes. For example, they might enter a wish to "participate in volunteer activities in developing countries." When the user confirms the information and clicks the submit button, this information is sent to the server.

[1635] Emotion Recognition Module

[1636] The server receives the desired data from the user and simultaneously analyzes the user's emotional state using an emotion engine, for example, determining whether the user is "excited" or "anxious" based on the user's typing speed and choice of words.

[1637] Generative AI Module

[1638] The server passes the user's wishes and emotional state to the generation AI. The generation AI analyzes the wishes and emotional state, and collects and generates the necessary information from the relevant database. For example, for the wish to "participate in volunteer activities in developing countries" and the emotional state of "excited," the following information is generated:

[1639] List of volunteer organizations

[1640] Required procedures (visa, vaccinations, etc.)

[1641] Local living information

[1642] Information Module

[1643] The server receives the information returned by the generation AI and formats it into a user-friendly format (e.g., an HTML page). It incorporates the analysis results of the emotion engine and includes expressions and messages appropriate to the user's emotional state. For example, if the user is "excited," a positive and encouraging message is displayed.

[1644] Contact Establishment Module

[1645] The server calls an API to establish contact with relevant stakeholders (e.g., volunteer organizations, visa application agencies, vaccination agencies), retrieves contact information for each stakeholder, and provides it to the user.

[1646] Specific examples

[1647] User Input

[1648] 1. The user enters into the portal site, "I want to become a traditional craftsman."

[1649] 2. The user checks the input and clicks the submit button.

[1650] Information generation and emotion recognition

[1651] 1. The server uses the input content along with the emotion engine to analyze the user's emotional state.

[1652] 2. The generating AI analyzes keywords such as "traditional craftsman" and "repair craftsman" and the emotional state "excited" to generate the following information:

[1653] List of schools for training repair craftsmen (traditional craft technical colleges, craft skills training schools, etc.)

[1654] A list of potential job opportunities and related companies

[1655] Information on the qualifications and skills required for repair craftsmen

[1656] Providing information

[1657] 1. The server receives information from the generation AI.

[1658] 2. The server formats the information and displays it with an encouraging message appropriate to the user's emotional state, such as "You're one step closer to making your dreams come true!"

[1659] Establishing contact

[1660] 1. The server calls an API to establish contact with a specific stakeholder (training school, company, certification body, etc.).

[1661] 2. The server retrieves the contact information of each stakeholder and provides it to the user.

[1662] In this way, the system effectively supports the realization of users' dreams and hopes through a series of steps: starting with the user inputting their wishes, followed by analysis and generation of information using generative AI, analysis of their emotional state using an emotion engine and provision of information accordingly, and finally establishing contact with relevant stakeholders.

[1663] The processing flow will be explained below.

[1664] Step 1:

[1665] The user accesses the portal site.

[1666] Step 2:

[1667] The user enters their desired interests (e.g., "I want to become a traditional craftsman") into the provided input form.

[1668] Step 3:

[1669] The user checks the input information and clicks the "Submit" button.

[1670] Step 4:

[1671] The server receives the desired data from the user.

[1672] Step 5:

[1673] The server analyzes the received data and determines the desired category (e.g., occupation, volunteering, residential choice, hobby).

[1674] Step 6:

[1675] The server passes the results of the discrimination to the generation AI module and emotion engine.

[1676] Step 7:

[1677] The emotion engine analyzes user input and determines the user's emotional state (e.g., happy, sad, anxious).

[1678] Step 8:

[1679] The generative AI analyzes the user's wishes and emotional state, and collects and generates the necessary information from relevant databases.

[1680] Step 9:

[1681] The generation AI generates information based on user preferences (e.g., a list of training programs, a list of related companies, and required qualifications).

[1682] Step 10:

[1683] The generation AI returns the generated information to the server in JSON format.

[1684] Step 11:

[1685] The server receives the JSON data returned by the generated AI.

[1686] Step 12:

[1687] The server formats the received data into a user-friendly format (e.g., HTML page), incorporating the analysis results of the emotion engine and adding expressions appropriate to the user's emotional state.

[1688] Step 13:

[1689] The server provides the formatted information to the user. The user then browses the information and obtains the necessary procedures and detailed information. For example, a message such as "You're one step closer to making your dreams come true!" is displayed.

[1690] Step 14:

[1691] The server invokes an API to establish contact with the relevant stakeholders.

[1692] Step 15:

[1693] The server retrieves stakeholder contact information through an API.

[1694] Step 16:

[1695] The server provides the retrieved contact information to the user.

[1696] Step 17:

[1697] Users will be contacted directly with the relevant stakeholders using the contact information provided.

[1698] Step 18:

[1699] If a user requires additional information or support, they submit a request to the server using the contact form.

[1700] Step 19:

[1701] The server receives additional requests and again calls the generation AI and emotion engine to generate the necessary information and provide it to the user.

[1702] Example 2

[1703] 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."

[1704] When a user inputs their preferences, it is important to provide information that matches those preferences. However, conventional systems often provide information without considering the user's emotional state, which fails to sufficiently improve user satisfaction. Furthermore, establishing contact with relevant stakeholders must be done manually, which is time-consuming and reduces efficiency. Furthermore, generating information based on preferences requires accuracy and appropriate category determination, but conventional systems are unable to address these challenges.

[1705] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for a user to input a preference, a means for analyzing the input preference and determining a category, a means for generating necessary information based on the preference, a means for providing the generated information to the user, a means for automatically establishing contact with relevant stakeholders, an emotion recognition means for analyzing the user's emotional state, and a means for adjusting the information presentation method based on the emotional state. This makes it possible to provide information taking the user's emotional state into consideration, thereby improving user satisfaction and increasing the efficiency of establishing contact with stakeholders. Furthermore, accurate information generation and category determination can be performed based on the preference.

[1706] The "means for user input of wishes" is an interface that allows a user to input specific wishes or requests to the system.

[1707] The "means for analyzing input preferences and determining categories" is a function for analyzing preferences input by the user and classifying the contents into specific categories.

[1708] "Means for generating necessary information based on user preferences" refers to a function that automatically collects and generates relevant information based on user preferences.

[1709] The "means for providing the generated information to the user" is a function for providing the generated information to the user in an appropriate format.

[1710] "Means for automatically establishing contact with relevant stakeholders" means means for automatically obtaining and providing contact information for third parties relevant to the user's wishes.

[1711] The "emotion recognition means for analyzing the user's emotional state" is a function for analyzing the user's input data and behavior to identify the user's emotional state.

[1712] The "means for adjusting the method of presenting information based on the emotional state" is a function for adjusting the method of presenting information and the content of messages according to the emotional state of the user.

[1713] The embodiment of the present invention is described below. The system of the present invention has a function to respond to the emotional state of the user by combining a means for inputting user preferences, a means for generating and providing information using a generative AI, a means for establishing contact with stakeholders, and an emotion engine.

[1714] System Overview

[1715] 1. User Input Module:

[1716] A form is provided for users to enter their aspirations. For example, they can enter specific aspirations such as "I want to become a repair craftsman of traditional crafts" or "I want to participate in volunteer activities in developing countries." This form is implemented as a web page, and the input contents are sent to the server.

[1717] 2. Emotion Recognition Module:

[1718] The server analyzes the received user preference data using an emotion engine to identify the user's emotional state (e.g., joy, sadness, anxiety) using algorithms such as typing speed, keywords in the sentence, and context analysis.

[1719] 3. Generative AI module:

[1720] The server passes the user's wishes and emotional state to the generation AI, which then collects and generates the necessary information from relevant databases based on those wishes and emotional state. For example, in response to a wish to "participate in volunteer activities in developing countries" and an emotional state of "excitement," the generation AI generates a list of volunteer organizations, necessary procedures (visas, vaccinations, etc.), and information about life in the local area.

[1721] 4. Information module:

[1722] The server formats the information received from the generation AI and provides it to the user. The information provided takes into account the analysis results of the emotion engine and is provided with content and expression appropriate to the user's emotional state. For example, if the user is "excited," a positive and encouraging message will be included.

[1723] 5. Contact Establishment Module:

[1724] The server calls an API to establish contact with relevant stakeholders (e.g., volunteer organizations, companies, certification bodies), retrieves contact information for each stakeholder, and provides it to the user.

[1725] Specific examples

[1726] User Input

[1727] Users enter "I want to become a traditional craftsman" into the portal site.

[1728] The user checks the input contents and clicks the send button.

[1729] Information generation and emotion recognition

[1730] The server uses the input together with an emotion engine to analyze the user's emotional state.

[1731] The AI ​​analyzes keywords such as "traditional craftsman" and "repair craftsman" along with the emotional state of "excited" to generate the following information:

[1732] List of schools for training repair craftsmen (traditional craft technical colleges, craft skills training schools, etc.)

[1733] A list of potential job opportunities and related companies

[1734] Information on the qualifications and skills required for repair craftsmen

[1735] Providing information

[1736] The server receives information from the generating AI.

[1737] The server formats the information and displays it with an encouraging message appropriate to the user's emotional state, such as "You're one step closer to making your dreams come true!"

[1738] Establishing contact

[1739] The server calls an API to establish contact with a particular stakeholder (training school, company, certification body, etc.).

[1740] The server retrieves the contact information of each stakeholder and provides it to the user.

[1741] Prompt Sentence Examples

[1742] The following prompt sentences are examples of specific requests that can be entered into the user input module:

[1743] I would like to become a traditional craftsman. Which training school should I attend? Are there any companies that I can work for? I would also like to know about related qualifications.

[1744] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1745] Step 1: User Input

[1746] The user accesses the portal site of the system and enters their wishes into the provided form. For example, they enter their wish to "participate in volunteer activities in developing countries."

[1747] Input: The desired text data entered by the user.

[1748] Output: The desired text data entered is sent to the server as is.

[1749] Step 2: Sending User Input

[1750] The user checks the input and clicks the submit button, which sends the input data to the server.

[1751] Input: The event when the submit button is clicked and the desired text data entered.

[1752] Output: The desired text data sent to the server.

[1753] Step 3: Emotion Recognition

[1754] The server launches an emotion engine based on the received desired data. The emotion engine analyzes the input text and determines the user's emotional state. For example, it analyzes keywords and context in the text to identify emotions such as "excited" or "anxious."

[1755] Input: The desired text data received by the server.

[1756] Output: The user's emotional state (e.g., "excited").

[1757] Step 4: Analyze your desires and emotional state

[1758] The server passes the emotion recognition results and the user's desired data to the generation AI, which then analyzes the data and searches related databases to collect the necessary information.

[1759] Input: User's desired text data and emotional state.

[1760] Output: Analysis results and collected information based on wishes and emotions.

[1761] Step 5: Information Generation

[1762] The generative AI generates the necessary information based on the analysis results of the input. For example, based on the desire to "participate in volunteer activities in developing countries" and the emotional state of "excited," the following information is generated:

[1763] List of volunteer organizations

[1764] Required procedures (visa, vaccinations, etc.)

[1765] Local living information

[1766] Input: Analysis results based on desires and emotional state.

[1767] Output: A list of the generated information.

[1768] Step 6: Provide information

[1769] The server receives the information returned by the generation AI and formats it in a user-friendly format. Taking into account the results of the emotion engine, the server provides information in a way that is appropriate to the user's emotional state. For example, if the user is "excited," a positive and encouraging message is displayed.

[1770] Input: A generated list of information and an emotional state.

[1771] Output: The formatted information presented to the user.

[1772] Step 7: Establishing Contact

[1773] The server calls the API to obtain contact information for relevant stakeholders (e.g., volunteer organizations, companies, certification bodies), and provides the obtained information to the user to support the next action.

[1774] Input: User preferences and relevant stakeholder information.

[1775] Output: Stakeholder contact information and information provided to users.

[1776] (Application example 2)

[1777] 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."

[1778] Conventional shopping support systems collect user preferences, but offer only uniform product and service recommendations based on those preferences, lacking personalized recommendations that take into account the user's emotional state. This results in a less than satisfying shopping experience. Furthermore, establishing contact with stakeholders to realize the user's preferences is a manual process that is inefficient. This results in a complex and time-consuming process for users to take action.

[1779] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to input a preference, means for analyzing the input preference and determining a category, means for generating necessary information based on the preference and the user's emotional state, means for providing the generated information to the user, means for automatically establishing contact with relevant stakeholders, means for analyzing the user's emotional state using an emotion engine, and means for adjusting the presentation of the generated information based on the analyzed emotional state. This enables the proposal of appropriate and personalized products and services based on the user's preference, resulting in a more satisfying shopping experience. Furthermore, because contact with relevant stakeholders is automatically established, the process for the user to realize their preference is made more efficient.

[1780] "User input means" is an interface that allows a user to input desired products or services.

[1781] The "category determination means" is a means for analyzing the desires input by the user and classifying them into an appropriate category.

[1782] The "information generation means" is a means for generating necessary information based on the user's wishes and emotional state.

[1783] "Information provision means" refers to a means for providing the generated information to the user in an appropriate format.

[1784] A "contact establishment method" is a method for automatically establishing contact with relevant stakeholders.

[1785] The "emotion engine" is an engine for analyzing the user's emotional state.

[1786] The "emotion analysis means" is a means for analyzing the user's emotional state using an emotion engine.

[1787] The "expression adjusting means" is a means for adjusting the expression of the generated information based on the analyzed emotional state.

[1788] "Generative AI" is artificial intelligence that generates information based on desires and emotional states.

[1789] "Application Program Interface" means a program interface for establishing contact with stakeholders.

[1790] The following describes the mode for carrying out this invention. The present invention is a personalized shopping assistant system for improving the shopping experience in brick-and-mortar stores. This system is installed on a smartphone or smart glasses and analyzes the user's desires and emotional state to suggest optimal products and services.

[1791] System Configuration

[1792] Hardware and Software

[1793] 1. User Input Method:

[1794] Using a smartphone or smart glasses, the device provides an interface for users to input their preferences, typically using a touchscreen or voice input.

[1795] 2. Category determination method:

[1796] We analyze the user's input preferences and classify them into appropriate categories. We use common natural language processing (NLP) tools and libraries (e.g., NLTK, spaCy) to analyze preferences.

[1797] 3. Emotion analysis means:

[1798] The emotional state of the user is analyzed using an emotion engine. Emotion analysis takes into account keywords in the input, sentence structure, input speed, etc. The emotion engine uses the Python EmotionRecognizer library.

[1799] 4. Information generation means:

[1800] Based on the user's preferences and emotional state, information is generated using generative AI (e.g., OpenAI's GPT-3). The generated information is retrieved from relevant databases to suggest optimal products and services to the user.

[1801] 5. Information provision method:

[1802] The generated information is presented to the user through the display of a smartphone or smart glasses, and the way this information is displayed is adjusted based on the results of emotion analysis.

[1803] 6. Means of establishing contact:

[1804] Use APIs to automatically establish contact with relevant stakeholders, allowing for efficient communication with volunteer organizations, certification bodies, vaccination agencies, etc.

[1805] Example of processing flow

[1806] 1. User Input

[1807] A user uses a smartphone or smart glasses to input the product or service they are looking for, for example, "I'm looking for new fashion items."

[1808] 2. Category determination

[1809] The server analyzes the input and classifies it into a "fashion" category, using NLP tools to determine relationships.

[1810] 3. Emotion analysis

[1811] The emotion engine analyzes the user's emotional state to determine that they are "curious." The emotion is determined from the input speed and keywords in the text.

[1812] 4. Information generation

[1813] Enter the following prompts into the generative AI model (OpenAI's GPT-3) to generate information:

[1814] Want: Looking for new fashion items

[1815] Emotion: Curious

[1816] Please suggest products or services that best fit these criteria.

[1817] Based on these prompts, the generative AI generates information about the latest trending items and the stores that sell them.

[1818] 5. Information provision

[1819] The server receives the generated information, adjusts the display format to match the user's emotional state, and displays it on the smartphone or smart glasses screen, for example, displaying product images and descriptions along with encouraging messages.

[1820] 6. Establishing Contact

[1821] The server makes API calls to establish contact with the relevant store or support service, providing the contact information to the user so they can contact them directly.

[1822] As described above, this system analyzes users' preferences and emotional state, suggests optimal products and services, and improves the shopping experience. It also automatically establishes contact with relevant stakeholders, allowing users to take action smoothly.

[1823] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1824] Step 1:

[1825] Users input their desired products or services through the interface of their smartphone or smart glasses. The input data is sent to the server by the user device. An example input might be "I'm looking for a new fashion item."

[1826] Input: User's preference (text)

[1827] Output: Desired data sent to the server

[1828] Step 2:

[1829] The server analyzes the received desired data. For analysis, it uses NLP tools (e.g., NLTK or spaCy) to extract related keywords from the input content and determine the category. In this case, the keyword "fashion" is extracted and the category "fashion" is determined.

[1830] Input: User's desired data

[1831] Output: Parsed category (e.g. fashion)

[1832] Step 3:

[1833] The server performs emotion recognition based on the desired data. It uses an emotion engine (e.g., EmotionRecognizer library) to analyze the user's emotional state based on their text expression and typing speed. In this case, the emotion is analyzed as "curious."

[1834] Input: User's desired data

[1835] Output: Parsed emotional state (e.g., curious)

[1836] Step 4:

[1837] The server generates information by sending prompts to a generative AI model (e.g., OpenAI's GPT-3) based on the user's desires and emotional state. An example prompt is "Desire: Looking for a new fashion item. Emotion: Curious. Please suggest products and services that best suit these conditions." The generative AI analyzes this and generates information.

[1838] Input: User's desires and emotional state

[1839] Output: Generated information (e.g., latest trending items and store information)

[1840] Step 5:

[1841] The server receives the generated information and adjusts the display format based on the emotion analysis results. For example, the display format may be adjusted to include an encouraging message. The adjusted information is then displayed on the display of the smartphone or smart glasses.

[1842] Input: Generated information and emotional state

[1843] Output: Adjusted display information

[1844] Step 6:

[1845] The server calls the API to establish contact with the relevant stakeholders (stores and support services). The contact information obtained through the API is provided to the user so that they can contact them directly.

[1846] Input: Relevant stakeholder information

[1847] Output: Stakeholder contact information

[1848] 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.

[1849] 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.

[1850] 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.

[1851] 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.

[1852] 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.

[1853] 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.

[1854] 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).

[1855] 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.

[1856] 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."

[1857] 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.

[1858] 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).

[1859] 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.

[1860] 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.

[1861] 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.

[1862] 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.

[1863] 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.

[1864] 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.

[1865] 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.

[1866] 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.

[1867] 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.

[1868] 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.

[1869] The following is further disclosed regarding the above embodiment.

[1870] (Claim 1)

[1871] a means for the user to input their preferences;

[1872] A means for analyzing the input preference and determining the category;

[1873] a means for generating the required information based on the user's wishes;

[1874] a means for providing the generated information to a user;

[1875] means of automatically establishing contact with relevant stakeholders;

[1876] A system including:

[1877] (Claim 2)

[1878] 10. The system of claim 1, including artificial intelligence for generating information based on preferences.

[1879] (Claim 3)

[1880] 10. The system of claim 1, including an application program interface for establishing contact with stakeholders.

[1881] "Example 1"

[1882] (Claim 1)

[1883] a means for the user to input their preferences;

[1884] A means for analyzing the input preference and determining the category;

[1885] means including a generative AI model for generating the required information based on the desires;

[1886] a means for providing the generated information to a user;

[1887] a means of formatting the generated information into a user-friendly format;

[1888] means including an application program interface for automatically establishing contact with relevant stakeholders;

[1889] A system including:

[1890] (Claim 2)

[1891] 10. The system of claim 1, including a generative AI model for generating information based on preferences.

[1892] (Claim 3)

[1893] 10. The system of claim 1, including an application program interface for establishing contact with stakeholders.

[1894] "Application Example 1"

[1895] (Claim 1)

[1896] a means for the user to input their preferences;

[1897] A means for analyzing the input preference and determining the category;

[1898] a means for generating the required information based on the user's wishes;

[1899] a means for providing the generated information to a user;

[1900] means of automatically establishing contact with relevant stakeholders;

[1901] a means for providing the generated information as a list of products in a particular category;

[1902] A means for generating product information having a budget limit based on a user's wishes;

[1903] A way to check real-time product availability based on user preferences and budget,

[1904] A system including:

[1905] (Claim 2)

[1906] 10. The system of claim 1, including artificial intelligence for generating information based on preferences.

[1907] (Claim 3)

[1908] 10. The system of claim 1, including an application program interface for establishing contact with stakeholders.

[1909] "Example 2: Combining Emotion Engines"

[1910] (Claim 1)

[1911] a means for the user to input their preferences;

[1912] A means for analyzing the input preference and determining the category;

[1913] a means for generating the required information based on the user's wishes;

[1914] a means for providing the generated information to a user;

[1915] means of automatically establishing contact with relevant stakeholders;

[1916] an emotion recognition means for analyzing the emotional state of a user;

[1917] a means for adjusting the presentation of information based on emotional state;

[1918] A system including:

[1919] (Claim 2)

[1920] 10. The system of claim 1, including artificial intelligence for generating information based on preferences.

[1921] (Claim 3)

[1922] 10. The system of claim 1, including an application program interface for establishing contact with stakeholders.

[1923] "Application example 2 when combining emotion engines"

[1924] (Claim 1)

[1925] a means for the user to input their preferences;

[1926] A means for analyzing the input preference and determining the category;

[1927] means for generating the required information based on the desires and emotional state of the user;

[1928] a means for providing the generated information to a user;

[1929] means of automatically establishing contact with relevant stakeholders;

[1930] means for analyzing the emotional state of a user using an emotion engine;

[1931] means for adjusting the presentation of the generated information based on the analyzed emotional state;

[1932] A system including:

[1933] (Claim 2)

[1934] 10. The system of claim 1, including a generative artificial intelligence for generating information based on the desires and emotional state of the user.

[1935] (Claim 3)

[1936] 10. The system of claim 1, including an application program interface for establishing contact with stakeholders. [Explanation of symbols]

[1937] 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 the user to input their preferences; A means for analyzing the input preference and determining the category; a means for generating the required information based on the user's wishes; a means for providing the generated information to a user; means of automatically establishing contact with relevant stakeholders; A system including:

2. 10. The system of claim 1, including artificial intelligence for generating information based on preferences.

3. 10. The system of claim 1, further comprising an application program interface for establishing contact with stakeholders.

Images