system

Abstract

Provide a system. 【Solution means】Means for receiving the content of the user's trouble input, Means for analyzing and classifying the content of the trouble by a generative artificial intelligence, Means for generating an optimal advice based on the classified trouble, Means for presenting the generated advice to the user, Means for selecting companies and services necessary for trouble solving, Means for presenting the selected companies and services to the user, Means for receiving the user's selection result and transmitting the user information to the selected company, Means for collecting and managing referral fees A system including.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including the steps of receiving a user utterance; adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot; encoding the prompt; and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In conventional counseling services for troubles, it has been difficult to appropriately analyze a user's trouble and provide a solution quickly and accurately.Moreover, there has been a lack of means for promptly connecting to experts and services necessary for trouble-solving, and there have been problems with user satisfaction.Furthermore, since there has been no function for proposing additional support means such as crowdfunding, it has been difficult to provide comprehensive solutions for a wide variety of troubles.

Means for Solving the Problems

[0005] To solve the above problems, the present invention provides the following means. First, it provides means for receiving the content of the user's problem, and means for analyzing and classifying the content of the problem using generative artificial intelligence. Next, it provides means for generating optimal advice based on the classified problem, and means for presenting that advice to the user. It also provides means for selecting companies and services necessary for solving the problem, and means for presenting them to the user. Furthermore, it provides a system that includes means for receiving the user's selection results, transmitting user information to the selected companies, and means for collecting and managing referral fees. As a result, the user can obtain solutions to their problems quickly and appropriately and have seamless access to the necessary experts and services. In addition, by providing means for proposing a crowdfunding platform, comprehensive support for a wide range of problems becomes possible.

[0006] A "problem" refers to a problem or issue that a user wants to solve.

[0007] "Generative artificial intelligence" refers to technologies or systems that use machine learning and deep learning to perform natural language processing and data analysis to generate information.

[0008] "Analysis" refers to the process of analyzing text data entered by users and understanding its content.

[0009] "Classification" refers to the process of dividing analyzed data into specific categories or groups.

[0010] "Advice" refers to suggestions or instructions aimed at solving problems that users are facing.

[0011] A "company" refers to a legal entity or organization that provides specific services or products.

[0012] "Service" refers to various forms of support and assistance provided to users.

[0013] "Selection" refers to the process of choosing the most appropriate option from a large number of candidates.

[0014] "User information" refers to detailed data about personal information and concerns related to the user.

[0015] "Referral fees" refer to the compensation received from a company for introducing its services or products to users.

[0016] "Management" refers to the process of properly storing, organizing, and managing information and resources.

[0017] A "crowdfunding platform" refers to a website or application that provides systems and services for raising funds online.

[0018] "The nature of the problem" refers to the detailed information about the specific issues or difficulties the user is facing. [Brief explanation of the drawing]

[0019] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8]It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0020] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0021] First, the terms used in the following description will be described.

[0022] In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0023] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0024] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0025] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0027] [First Embodiment]

[0028] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0029] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0032] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0035] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0039] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0040] This invention provides a system for receiving and analyzing users' problems, providing appropriate advice, and seamlessly connecting them to the companies and services necessary for resolving those problems. Specific embodiments for carrying out this invention are described below.

[0041] 1. Basic System Configuration

[0042] This system consists of the following main components:

[0043] Terminal: A device that provides an interface for users to input their concerns.

[0044] Server: The central system that analyzes and classifies problems, generates advice, and selects companies and services.

[0045] Generative artificial intelligence: AI models for analyzing problems and generating advice.

[0046] Database: Stores information about companies and services and uses it for selection.

[0047] 2. System Operation

[0048] Receiving and analyzing problems

[0049] 1. The user accesses the device and enters their problem in text format.

[0050] 2. The terminal receives the entered content of the problem and sends the data to the server.

[0051] 3. The server passes the received data to a generative artificial intelligence (AI) for analysis. The generative AI extracts keywords from the text and performs sentiment analysis to analyze the content of the problem in detail.

[0052] 4. Based on the analysis results, the server classifies the problems into specific categories (e.g., inheritance, childcare, health issues, etc.).

[0053] Providing advice

[0054] 5. Based on the analysis results, the server selects an advice template appropriate to the category of the problem. Furthermore, it uses generative artificial intelligence to generate customized advice tailored to the user's specific problem.

[0055] 6. Once the server has finished generating the advice, it sends the generated results to the terminal.

[0056] 7. The device displays the received advice to the user. This allows the user to obtain guidance for specific solutions.

[0057] Proposal of solutions and connection

[0058] 8. The server accesses the database and selects relevant companies and services based on the analyzed problem category. For example, in the case of inheritance, it retrieves a list of reliable tax accounting firms.

[0059] 9. The server sends a list of selected companies and services to the terminal.

[0060] 10. The device displays a list of relevant companies and services to the user. The user can select the desired company or service from the list.

[0061] 11. When a user selects a company or service, the device sends the selection to the server.

[0062] 12. The server sends user information to the selected company and performs the matching process.

[0063] Crowdfunding proposal (optional)

[0064] 13. The server will suggest an appropriate crowdfunding platform if funding is needed to solve the user's problem.

[0065] 14. The server sends information from the crowdfunding platform to the device.

[0066] 15. The device displays crowdfunding platform proposals to the user, allowing them to receive further support as needed.

[0067] Management of referral fees

[0068] 16. The server operates a system to collect referral fees from partner companies when a match is successfully made with selected companies or services. The management and billing process for referral fees is entrusted to a dedicated management system.

[0069] Specific example

[0070] For example, if user A has concerns about inheritance, it would look like this:

[0071] 1. User A enters "I'm worried about inheritance" into the portal site.

[0072] 2. The terminal sends the input content to the server.

[0073] 3. The server uses generative artificial intelligence to analyze the text and categorize it under the "inheritance" category.

[0074] 4. The server generates advice regarding inheritance and sends it to the terminal.

[0075] 5. The device displays advice to user A (e.g., "Regarding inheritance procedures").

[0076] 6. The server selects a list of trusted tax accounting firms from its database and sends it to the terminal.

[0077] 7. The terminal displays the list to user A.

[0078] 8. User A selects a specific tax accounting firm.

[0079] 9. The terminal sends the selection result to the server.

[0080] 10. The server sends User A's information to the selected tax accounting firm and performs the matching process.

[0081] 11. The server collects referral fees from the tax accounting firm and records them in the management system.

[0082] In this way, the present invention provides a system for efficiently and effectively solving users' problems, and means for implementing the same.

[0083] The following describes the processing flow.

[0084] Step 1:

[0085] The user accesses the portal site using their device and enters the details of their problem as text.

[0086] Step 2:

[0087] The terminal receives user input and sends that information to the server.

[0088] Step 3:

[0089] The server receives text data about the problem and passes it to a generative artificial intelligence for analysis.

[0090] Step 4:

[0091] The generative artificial intelligence on the server analyzes the text, extracting keywords and performing sentiment analysis.

[0092] Step 5:

[0093] The server uses the analysis results to classify the problems into specific categories (e.g., inheritance, childcare, health issues, etc.).

[0094] Step 6:

[0095] Based on the analysis results, the server selects an advice template corresponding to the problem category.

[0096] Step 7:

[0097] The server uses generative artificial intelligence to generate customized advice tailored to the user's specific concerns.

[0098] Step 8:

[0099] The server sends the generated advice to the terminal.

[0100] Step 9:

[0101] The device displays generated advice to the user.

[0102] Step 10:

[0103] Based on the analysis results, the server selects companies and services from its database that are suitable for solving the problem.

[0104] Step 11:

[0105] The server generates a list of selected companies and services and sends it to the terminal.

[0106] Step 12:

[0107] The device displays a list of companies and services related to the user.

[0108] Step 13:

[0109] Users select companies or services that interest them from a presented list.

[0110] Step 14:

[0111] The terminal sends the user's selection results to the server.

[0112] Step 15:

[0113] The server sends user information to the selected companies based on the user's selection results.

[0114] Step 16:

[0115] The server waits for a response from the selected company, and if the matching is successful, it sends the result to the terminal.

[0116] Step 17:

[0117] The device notifies the user of the matching result.

[0118] Step 18:

[0119] Users will contact the selected companies and services directly and proceed with specific procedures to resolve their issues.

[0120] Step 19:

[0121] Once the server completes the matching process, it manages the referral fees from partner companies and initiates the billing process.

[0122] Step 20:

[0123] The server receives the referral fee and records it in the management system.

[0124] Step 21:

[0125] In some cases, the server will send appropriate platform information to the terminal to suggest a crowdfunding platform.

[0126] Step 22:

[0127] The device displays crowdfunding platform proposals to the user.

[0128] Step 23:

[0129] Users can utilize crowdfunding platforms as needed to receive further support.

[0130] (Example 1)

[0131] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0132] In modern society, individuals face a wide variety of problems and challenges, often requiring specialized knowledge and support to resolve. However, selecting the right company or service, and receiving prompt and accurate advice, is difficult. Existing systems require users to gather information and perform the necessary procedures themselves, which consumes considerable time and effort. Furthermore, if appropriate experts or services cannot be found, the problem may worsen. Therefore, there is a need for efficient and effective means to resolve users' problems.

[0133] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0134] In this invention, the server includes a device for receiving the content of a user's problem, a device for analyzing and classifying the content of the problem using generative artificial intelligence, a device for generating optimal advice based on the classified problem, a device for presenting the generated advice to the user, a device for selecting relevant businesses and services necessary for solving the problem, a device for presenting the selected businesses and services to the user, a device for receiving the user's selection results and transmitting user information to the selected businesses, and a device for collecting and managing referral fees. As a result, the user can efficiently analyze their problem, receive appropriate advice, quickly connect to the necessary businesses and services, and obtain support for problem solving.

[0135] A "user" refers to an individual who attempts to solve their own problems using this system.

[0136] A "device" refers to a device that provides an interface for users to input their concerns. Specifically, this includes computers, smartphones, tablets, and so on.

[0137] A "server" refers to a central computer system that analyzes, classifies, and provides advice on problems, as well as selecting and matching relevant businesses and services.

[0138] "Generative artificial intelligence" refers to an AI model that analyzes input text data, extracts keywords, and performs sentiment analysis to understand the user's concerns in detail and generate appropriate advice.

[0139] "Analyzing" refers to using generative artificial intelligence to extract keywords and perform sentiment analysis on input data, thereby gaining a detailed understanding of its content.

[0140] "Classifying" refers to categorizing users' concerns into specific categories (e.g., inheritance, childcare, health issues, etc.) based on the analysis results.

[0141] "Generating advice" refers to using generative artificial intelligence based on category-specific templates to create customized solutions or guidelines for a user's specific problems.

[0142] "Presenting" refers to displaying generated advice and information about related businesses and services to the user.

[0143] "Selecting" refers to extracting and choosing relevant businesses and services from a database based on the analyzed categories of problems.

[0144] "Transmitting user information" refers to sending necessary user information via the network to the business entity or service selected by the user.

[0145] A "business entity" refers to an organization or company that provides the specialized knowledge and services necessary to solve a problem.

[0146] "Referral fee" refers to the commission collected from a partnering business when a user and business are successfully matched.

[0147] A "crowdfunding platform" refers to a service that allows users to raise funds online to solve their problems.

[0148] This invention provides a system for receiving and analyzing users' problems, offering appropriate advice, and seamlessly connecting them to the necessary companies and services for resolving those problems. This system consists of the following main components:

[0149] 1. Terminal: A device that provides an interface for users to input their problems. Specifically, this includes computers, smartphones, and tablets. Users input their problems in text format via the terminal.

[0150] 2. Server: This is the central system that analyzes, classifies, and provides advice on problems, as well as selecting and matching relevant businesses and services. Specifically, generative artificial intelligence (e.g., GPT-3®) is used as the software, and it is executed within the server to perform data analysis and advice generation.

[0151] 3. Generative Artificial Intelligence: This AI model analyzes text data entered by the user, extracts keywords, and performs sentiment analysis to understand the user's concerns in detail and generate appropriate advice. This AI model heavily relies on the analysis of text data and the generation of advice.

[0152] 4. Database: Used to store information about companies and services, and to search for and select appropriate businesses and services that meet users' needs. Detailed information about businesses and services is registered within the database.

[0153] System operation details

[0154] Receiving and analyzing problems

[0155] When a user enters their problem into their device, the device sends that text data to a server via an HTTP request. The server then passes the received data to a generative artificial intelligence (AI). This AI extracts keywords and performs sentiment analysis based on the input text data, providing a detailed analysis of the user's problem.

[0156] Generating and providing advice

[0157] The server categorizes the user's concerns into specific categories based on the analysis results from the generative artificial intelligence. It then selects an advice template corresponding to the category and uses the generative artificial intelligence again to generate customized advice tailored to the user's specific concerns. The generated advice is sent from the server to the terminal and displayed to the user.

[0158] Selection of companies and services

[0159] The server selects relevant businesses and services based on the problem categories analyzed from the database. This selection is sent to the terminal as a list of businesses and services and displayed to the user. The user can then select their desired business or service from the displayed list.

[0160] User information submission and matching

[0161] When a user selects their desired business entity or service, the selection is sent from the terminal to the server. The server then sends the user information to the selected business entity and performs a matching process. This allows the user to quickly access the appropriate service.

[0162] Specific example

[0163] For example, if user A has concerns about inheritance, it would look like this:

[0164] 1. User A enters "I'm worried about inheritance" into the terminal.

[0165] 2. The device sends the text data to the server.

[0166] 3. The server uses generative artificial intelligence to analyze the text and categorize it under the "inheritance" category.

[0167] 4. The server generates advice regarding inheritance and sends it to the terminal.

[0168] 5. The device displays advice to user A (e.g., "Regarding inheritance procedures").

[0169] 6. The server selects a trusted expert from the database and sends the list to the terminal.

[0170] 7. The terminal displays the list to user A.

[0171] 8. User A selects a specific expert.

[0172] 9. The terminal sends the selection result to the server.

[0173] 10. The server sends User A's information to the selected expert and performs the matching process.

[0174] In this way, the present invention provides a system and means for implementing it that efficiently and effectively solves users' problems.

[0175] Example of a prompt

[0176] An example of a prompt message might read: "Please enter your problem in text format and send it to the server. The server will pass the text data to a generative artificial intelligence system that will analyze and classify your problem. It will then provide appropriate advice and a list of relevant businesses and services."

[0177] This system is a powerful tool for efficiently analyzing users' problems and providing quick and appropriate solutions.

[0178] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0179] Step 1:

[0180] The user enters their problem in text format into the device.

[0181] Input: Text data of the user's problem

[0182] Output: Text data received by the terminal

[0183] Users access the input interface of a portal site or application and describe their problems in detail. This text data is received by the device.

[0184] Step 2:

[0185] The terminal sends the entered text data about the problem to the server.

[0186] Input: Text data received on the device

[0187] Output: Text data transferred to the server

[0188] The terminal receives text data and sends it to the server via a communication method such as an HTTP request. HTTPS is the recommended communication protocol.

[0189] Step 3:

[0190] The server receives text data and passes it to a generative artificial intelligence for analysis.

[0191] Input: Text data transferred to the server

[0192] Output: Analyzed problem data (keywords, emotions, categories)

[0193] The server passes text data to a generative artificial intelligence (e.g., GPT-3). The generative AI extracts keywords from the text and performs sentiment analysis to analyze the content of the problem. As a result, the category and keywords of the problem are extracted.

[0194] Step 4:

[0195] The server categorizes the problems based on the analysis results.

[0196] Input: Analyzed problem data

[0197] Output: Categorized problem data

[0198] The server uses the analysis results from the generative artificial intelligence to classify the problems into specific categories. For example, it might categorize them into "inheritance," "childcare," or "health problems."

[0199] Step 5:

[0200] The server selects an advice template based on the category and uses generative artificial intelligence to generate customized advice.

[0201] Input: Categorized problem data

[0202] Output: Customized advice data

[0203] The server selects a pre-prepared advice template and uses generative artificial intelligence to customize the advice to address the user's specific concerns. The generated advice is output in text format.

[0204] Step 6:

[0205] The server sends the generated advice data to the terminal.

[0206] Input: Customized advice data

[0207] Output: Advice data transferred to the terminal

[0208] The server sends the generated advice data back to the terminal via an HTTP request. HTTPS is recommended to ensure the reliability of the communication.

[0209] Step 7:

[0210] The device displays the advice it has received to the user.

[0211] Input: Advice data transferred to the device

[0212] Output: Advice displayed to the user

[0213] The device displays the received advice data in a user-friendly format, allowing the user to obtain concrete guidance for solutions.

[0214] Step 8:

[0215] The server accesses the database and selects the relevant entities and services.

[0216] Input: Categorized problem data

[0217] Output: List of selected entities and services

[0218] Based on the analyzed problem categories, the server selects relevant businesses and services from the database. This results in a list of the businesses and services best suited to the user's problem.

[0219] Step 9:

[0220] The server sends a list of selected entities and services to the terminal.

[0221] Input: List of selected entities or services

[0222] Output: List of entities and services transferred to the terminal

[0223] The server sends a list of selected entities and services to the terminal. This is also done via an HTTP request.

[0224] Step 10:

[0225] The device displays a list of businesses and services associated with the device to the user.

[0226] Input: List of entities and services transferred to the terminal

[0227] Output: A list of entities and services displayed to the user.

[0228] The terminal displays a list of received entities and services to the user. The user can select the desired entity or service from this list.

[0229] Step 11:

[0230] When a user selects a company or service, the device sends that selection to the server.

[0231] Input: Information about the business entity or service selected by the user.

[0232] Output: Selection results sent to the server

[0233] When a user selects a specific business entity or service, the selection result is sent from the terminal to the server.

[0234] Step 12:

[0235] The server sends user information to the selected business entity and performs the matching process.

[0236] Input: Selection results sent to the server

[0237] Output: User information sent to the selected entity

[0238] The server sends user information to the selected business entity and performs a matching process. This allows users to quickly receive the support they need.

[0239] Step 13 (Optional):

[0240] The server sends information from the crowdfunding platform to the device.

[0241] Input: Problem data indicating that a crowdfunding proposal is deemed necessary.

[0242] Output: Information about the crowdfunding platform sent to the device.

[0243] In some cases, the server may determine that the user needs funding to solve their problem and send information about an appropriate crowdfunding platform.

[0244] Step 14 (Optional):

[0245] The device displays crowdfunding platform proposals to the user.

[0246] Input: Information from the crowdfunding platform sent to the device.

[0247] Output: Information about the crowdfunding platform displayed to the user.

[0248] The device displays project information from crowdfunding platforms to the user. The user can then receive further funding as needed.

[0249] Step 15:

[0250] The server collects and manages referral fees.

[0251] Input: Information on businesses and users that have been successfully matched.

[0252] Output: Collected referral fees and records in the management system

[0253] When a match is successful, the server collects a referral fee from the partner company and records it in a dedicated management system. This process is automated and functions as part of the revenue model.

[0254] (Application Example 1)

[0255] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0256] Traditional problem-solving systems have a problem in that they cannot quickly provide appropriate advice or relevant store information to users who are having trouble choosing products in a physical store. Therefore, users have to search for information and find solutions themselves, which is time-consuming and requires effort. Furthermore, the system in question is required not only to analyze the user's problem and present a suitable solution, but also to provide users with a way to quickly and effectively resolve their problem in a physical store.

[0257] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0258] In this invention, the server includes means for receiving the content of a user's problem, means for analyzing and classifying the content of the problem using generative artificial intelligence, means for generating optimal advice based on the classified problem, means for presenting the generated advice to the user, means for selecting companies and services necessary to solve the problem, means for presenting the selected companies and services to the user, means for receiving the user's selection results and transmitting user information to the selected companies, means for collecting and managing referral fees, means for providing information on relevant stores to resolve difficulties when the user is having trouble choosing a product, means for presenting information on the relevant stores to the user, and means for accessing a database for providing information on the stores. As a result, when a user is having trouble choosing a product in a physical store, they can use their smartphone to input their problem, and the system will analyze the problem and quickly provide appropriate solutions and information on relevant stores.

[0259] Definitions of important words

[0260] "A means of receiving user input about their concerns" refers to a function that allows users to input their concerns in text format using a specific device, and for the system to receive that input.

[0261] "Means for analyzing and classifying the content of the aforementioned problems using generative artificial intelligence" refers to a system that uses a generative AI model to extract keywords and perform sentiment analysis from input text data, and has the function of classifying the content of the problems into specific categories.

[0262] "Means for generating optimal advice based on the classified problems" refers to a function that generates advice best suited to solving the user's problems based on the analyzed and classified data.

[0263] "Means for presenting the generated advice to the user" refers to a means that has the function of displaying the generated advice on a device accessible to the user.

[0264] "Means for selecting companies and services necessary to solve the aforementioned problems" refers to a function that searches a database for and selects companies and services suitable for solving the user's problems.

[0265] "Means for presenting the selected companies and services to the user" refers to a function that displays a list of selected companies and services on the user's device.

[0266] "Means for receiving user selection results and transmitting user information to selected companies" refers to a system that receives company information selected by the user and transmits the user's information to the selected companies.

[0267] "Means for collecting and managing referral fees" refers to a system that collects referral fees from companies when a match is successful and manages those fees.

[0268] "A means of providing information on relevant stores to resolve difficulties when a user has trouble choosing a product" refers to a function that provides information on suitable stores to resolve difficulties a user encounters when choosing a product.

[0269] "Means for presenting information about the relevant stores to the user" refers to a means that has the function of displaying information about the relevant stores on the user's device.

[0270] "Means for accessing a database to provide information about the store" refers to a means that has the function of accessing a database and obtaining information in order to provide information about the relevant store.

[0271] Modes for carrying out the invention

[0272] This invention provides a system that allows users to input their concerns using their smartphone when they are having trouble choosing products in a physical store. The system then analyzes these concerns and quickly provides appropriate solutions and information about relevant stores. The following describes in detail specific embodiments for carrying out this invention.

[0273] 1. Basic System Configuration

[0274] This system consists of the following main components:

[0275] Device: A smartphone that provides an interface for users to input their problems or concerns.

[0276] Server: The central system that analyzes and classifies problems, generates advice, and selects companies and services.

[0277] Generative artificial intelligence (AI model): An AI model designed to analyze problems and generate advice.

[0278] Database: Stores information about companies and related stores, and uses it for selection.

[0279] 2. System Operation

[0280] Receiving and analyzing problems

[0281] 1. The user uses their smartphone to enter a specific problem in text format. For example, they might type, "I don't know what to get my child for their birthday."

[0282] 2. The terminal receives the entered content of the problem and sends the data to the server.

[0283] 3. The server passes the received data to a generative artificial intelligence (e.g., OpenAI's GPT-4) for analysis. The AI ​​model extracts keywords from the text and performs sentiment analysis to analyze the content of the problem in detail.

[0284] 4. Based on the analysis results, the server classifies the worries into specific categories (e.g., birthday presents).

[0285] Provision of advice

[0286] 5. Based on the analysis results, the server selects an advice template suitable for the category of the worry. Furthermore, using generative artificial intelligence, it generates customized advice according to the user's specific worry.

[0287] 6. When the generation of advice is completed, the server sends the generation result to the terminal.

[0288] 7. The terminal displays the received advice to the user. For example, specific advice such as "Toys, books, games, etc. are suitable as birthday presents" is displayed.

[0289] Provision of store information

[0290] 8. The server accesses the database and selects relevant stores based on the analyzed category of the worry. For example, it obtains a list such as "toy store", "bookstore", etc.

[0291] 9. The server sends the list of selected stores to the terminal.

[0292] 10. The terminal displays the list of relevant stores to the user. The user can select the desired store from the list.

[0293] 11. When the user selects a specific store, detailed information about that store (e.g., address, contact information, business hours) is displayed.

[0294] Proposal of crowdfunding (optional)

[0295] 12. When funds are required to solve a user's problem in some cases, the server proposes an appropriate crowdfunding platform.

[0296] 13. The server sends information about the crowdfunding platform to the terminal.

[0297] 14. The terminal displays the proposal of the crowdfunding platform to the user and can receive further assistance if necessary.

[0298] With this system, the user can quickly obtain specific advice and related store information for effectively solving the difficulties associated with selecting products in a physical store. As a specific example of a prompt sentence, there is an example of "I don't know what's good for my child's birthday present".

[0299] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0300] Processing steps of the program

[0301] Step 1:

[0302] The user uses a smartphone to input a problem in text form.

[0303] Input: The user inputs "I don't know what's good for my child's birthday present" into the application of the smartphone.

[0304] Specific operation: The user fills in the problem in the text box and presses the "Send" button.

[0305] Step 2:

[0306] The terminal receives the content of the input problem and sends the data to the server.

[0307] Input: The text data input by the user.

[0308] Data processing: The terminal converts the text data into JSON format and sends it to the server.

[0309] Output: Input data in JSON format is sent to the server.

[0310] Specific operation: The terminal formats the text data into JSON format and sends an HTTP request to the server's API endpoint.

[0311] Step 3:

[0312] The server passes the received data to a generative artificial intelligence for analysis. The AI ​​model extracts keywords from the text and performs sentiment analysis to analyze the content of the problem in detail.

[0313] Input: Input data in JSON format.

[0314] Data processing: An AI model (e.g., GPT-4) extracts keywords from text, performs sentiment analysis, and categorizes the data.

[0315] Output: The analysis results (categories and keywords) are returned to the server.

[0316] Specific operation: The server sends an API request to the AI ​​model, the model performs text analysis, and returns the analysis results to the server.

[0317] Step 4:

[0318] Based on the analysis results, the server categorizes the problem into a specific category (e.g., birthday present).

[0319] Input: Analysis results returned from the AI ​​model.

[0320] Data processing: Based on the analysis results, the data is classified into specific categories.

[0321] Output: Classified data is generated.

[0322] Specific operation: The server compares the analysis results with a preset category list to identify the corresponding category.

[0323] Step 5:

[0324] Based on the analysis results, the server selects an advice template appropriate to the problem category and uses generative artificial intelligence to generate personalized advice for the user.

[0325] Input: Categorized data and advice templates.

[0326] Data processing: AI models generate customized advice.

[0327] Output: Customized advice.

[0328] Specific operation: The server passes an advice template to the AI ​​model, which then generates advice that customizes the template based on categorical data.

[0329] Step 6:

[0330] Once the server has finished generating the advice, it sends the results to the terminal.

[0331] Input: Generated advice data.

[0332] Data processing: Convert the advice data to JSON format.

[0333] Output: Advice data in JSON format is sent to the terminal.

[0334] Specific operation: The server formats the generated advice into JSON format and sends an HTTP request to the terminal's API endpoint.

[0335] Step 7:

[0336] The device displays the received advice to the user.

[0337] Input: Advice data in JSON format received from the server.

[0338] Output: Advice displayed to the user.

[0339] Specific operation: The terminal parses the JSON data and displays advice in the user interface.

[0340] Step 8:

[0341] The server accesses the database and selects relevant stores based on the analyzed problem categories.

[0342] Input: Classified category data.

[0343] Data processing: Based on category data, relevant store information is searched and retrieved from the database.

[0344] Output: List of store information.

[0345] Specific operation: The server sends category data as a query to the database and retrieves related store information.

[0346] Step 9:

[0347] The server sends a list of selected stores to the terminal.

[0348] Input: List of store information.

[0349] Data processing: Convert store information to JSON format.

[0350] Output: A list of stores in JSON format is sent to the terminal.

[0351] Specific operation: The server formats the store information in JSON format and sends an HTTP request to the terminal's API endpoint.

[0352] Step 10:

[0353] The terminal displays a list of relevant stores to the user.

[0354] Input: A list of stores in JSON format received from the server.

[0355] Output: A list of stores displayed to the user.

[0356] Specific operation: The terminal parses the JSON data and displays the store information as a list in the user interface.

[0357] Step 11:

[0358] When a user selects a specific store, detailed information about that store is displayed.

[0359] Input: User's store selection action.

[0360] Output: Detailed information about the selected store.

[0361] Specific action: The device displays detailed information about the selected store (e.g., address, contact information, business hours).

[0362] Step 12:

[0363] The server will, in some cases, suggest an appropriate crowdfunding platform when funding is needed to solve a user's problem.

[0364] Input: User's problem and analysis results.

[0365] Data processing: AI analysis to propose crowdfunding platforms.

[0366] Output: Proposal for a crowdfunding platform.

[0367] Specific operation: The server proposes a crowdfunding campaign based on the analysis results and sends it to the terminal.

[0368] Step 13:

[0369] The device displays proposals from crowdfunding platforms to the user, allowing them to receive further support as needed.

[0370] Input: Crowdfunding proposal information received from the server.

[0371] Output: Crowdfunding information displayed to the user.

[0372] Specific action: The device displays crowdfunding proposals it has received in the user interface.

[0373] Through these steps, users can use their smartphones to get quick and effective advice and relevant store information when they have trouble choosing products in a physical store.

[0374] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0375] This invention provides a system that receives and analyzes users' concerns, provides appropriate advice, and seamlessly connects them to the necessary companies and services for resolution, in addition to an emotion engine that recognizes the user's emotions. Specific embodiments for carrying out this invention will be described below.

[0376] Basic System Configuration

[0377] This system consists of the following main components:

[0378] Terminal: A device that provides an interface for users to input their concerns.

[0379] Server: The central system that analyzes problems, recognizes emotions, generates advice, and selects companies and services.

[0380] Generative artificial intelligence: AI models for analyzing problems and generating advice.

[0381] Emotion engine: A system that recognizes and analyzes emotions from text entered by the user.

[0382] Database: Stores information about companies and services and uses it for selection.

[0383] System operation

[0384] Receiving and analyzing problems

[0385] 1. The user accesses the device and enters their problem in text format.

[0386] 2. The terminal receives the entered content of the problem and sends the data to the server.

[0387] 3. The server passes the received data to the generative artificial intelligence and the emotion engine for analysis. The generative artificial intelligence extracts keywords from the text and performs emotion analysis to analyze the content of the problem in detail.

[0388] 4. The emotion engine on the server determines the emotional state from the user's input and feeds the result back to the generative artificial intelligence.

[0389] 5. The server classifies the problem into a specific category (e.g., inheritance, childcare, health issues, etc.) based on the analysis results and sentiment analysis results.

[0390] Providing advice

[0391] 6. Based on the analysis results, the server selects an advice template appropriate to the category of the problem. Furthermore, it uses generative artificial intelligence to generate customized advice that is tailored to the user's specific problem and emotional state.

[0392] 7. The server sends the generated advice to the terminal.

[0393] 8. The device displays generated advice to the user. This allows the user to receive guidance on solutions that take their emotional state into consideration.

[0394] Proposal of solutions and connection

[0395] 9. Based on the analysis results, the server selects companies and services from the database that are suitable for solving the problem. The results of the sentiment analysis are also taken into consideration in the selection process.

[0396] 10. The server generates a list of selected companies and services and sends it to the terminal.

[0397] 11. The device displays a list of companies and services related to the user.

[0398] 12. The user selects companies or services of interest from the presented list.

[0399] 13. The terminal sends the user's selection results to the server.

[0400] 14. The server sends user information to the selected companies based on the user's selection results.

[0401] Crowdfunding proposal (optional)

[0402] 15. The server will suggest an appropriate crowdfunding platform if, in some cases, funding is needed to solve the user's problem.

[0403] 16. The server sends information from the crowdfunding platform to the device.

[0404] 17. The device displays crowdfunding platform proposals to the user, allowing them to receive further support as needed.

[0405] Management of referral fees

[0406] 18. The server operates a system to collect referral fees from partner companies when a match is successfully made with selected companies or services. The management and billing process for referral fees is entrusted to a dedicated management system.

[0407] Specific example

[0408] For example, if user B has concerns about childcare, it would look like this:

[0409] 1. User B enters their "childcare concerns" into the portal site.

[0410] 2. The terminal sends the input content to the server.

[0411] 3. The server uses generative artificial intelligence and an emotion engine to analyze the text and classify it into the "childcare" category. At the same time, the emotion engine recognizes user B's mental state and emotions.

[0412] 4. The server generates advice and creates customized advice that takes sentiment analysis results into account.

[0413] 5. The server sends the generated advice to the terminal, which then displays it to user B (e.g., "How to manage stress in childcare").

[0414] 6. The server selects suitable childcare support companies and services from the database and sends the list to the terminal.

[0415] 7. The device displays a list to User B, and User B selects a specific childcare support service.

[0416] 8. The device sends the selection results to the server.

[0417] 9. The server sends User B's information to the selected childcare support service and performs the matching process.

[0418] 10. The server collects referral fees from childcare support services and records them in the management system.

[0419] In this way, the present invention realizes a system that analyzes user concerns, including their emotions, provides solutions, and seamlessly connects to businesses and services.

[0420] The following describes the processing flow.

[0421] Step 1:

[0422] The user accesses the portal site using their device and enters the details of their problem as text.

[0423] Step 2:

[0424] The terminal receives user input and sends that information to the server.

[0425] Step 3:

[0426] The server receives the text data of the problem and passes it to a generative artificial intelligence to begin analysis.

[0427] Step 4:

[0428] The server passes user input data to the emotion engine, which then recognizes the user's emotional state.

[0429] Step 5:

[0430] Generative artificial intelligence analyzes text data, extracting keywords and performing sentiment analysis. Simultaneously, a sentiment engine determines the user's emotional state.

[0431] Step 6:

[0432] The server collects analysis results from generative artificial intelligence and emotion engines, and classifies the problems into specific categories (e.g., inheritance, childcare, health issues, etc.).

[0433] Step 7:

[0434] The server selects an advice template that corresponds to the problem category.

[0435] Step 8:

[0436] The server uses generative artificial intelligence to generate customized advice based on the user's specific concerns and emotional state.

[0437] Step 9:

[0438] The server sends the generated advice to the terminal.

[0439] Step 10:

[0440] The device displays generated advice to the user. This provides the user with specific solutions that take their emotional state into consideration.

[0441] Step 11:

[0442] Based on the analysis results, the server selects companies and services from its database that are necessary to solve the problem. The results of the emotional analysis are also taken into consideration in the selection process.

[0443] Step 12:

[0444] The server generates a list of selected companies and services and sends it to the terminal.

[0445] Step 13:

[0446] The device displays a list of companies and services related to the user.

[0447] Step 14:

[0448] Users select companies or services that interest them from a presented list.

[0449] Step 15:

[0450] The terminal sends the user's selection results to the server.

[0451] Step 16:

[0452] The server sends user information to the selected companies based on the user's selection results.

[0453] Step 17:

[0454] The server waits for a response from the selected company, and if the matching is successful, it sends the result to the terminal.

[0455] Step 18:

[0456] The device notifies the user of the matching result.

[0457] Step 19:

[0458] Users will contact the selected companies and services directly and proceed with specific procedures to resolve their issues.

[0459] Step 20:

[0460] Once the server completes the matching process, it manages the referral fees from partner companies and initiates the billing process.

[0461] Step 21:

[0462] The server receives the referral fee and records it in the management system.

[0463] Step 22:

[0464] In some cases, the server will send appropriate platform information to the terminal to suggest a crowdfunding platform.

[0465] Step 23:

[0466] The device displays crowdfunding platform proposals to the user.

[0467] Step 24:

[0468] Users can utilize crowdfunding platforms as needed to receive further support.

[0469] (Example 2)

[0470] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0471] Conventional problem-solving support systems lacked the technology to appropriately recognize users' emotions and customize advice based on them. Furthermore, they lacked the functionality to seamlessly suggest and connect users with suitable services and companies. As a result, users often failed to alleviate stress or find appropriate services. This invention aims to solve these problems and provide users with a more effective means of resolving their problems.

[0472] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0473] In this invention, the server includes means for receiving the content of the user's problem, means for analyzing and classifying the content of the problem using generative artificial intelligence, and means for determining the user's emotional state from the user's input using an emotion analysis engine. This makes it possible to analyze the user's problem in detail and provide customized advice based on their emotional state. The server also includes means for generating optimal advice based on the classified problem, means for presenting the generated advice to the user, means for selecting the services necessary to solve the problem, means for presenting the selected services to the user, means for receiving the user's selection results and transmitting user information to the selected services, and means for collecting and managing referral fees. This enables efficient problem solving by providing the information and services necessary to solve the user's problem in a centralized manner.

[0474] A "user" refers to a person who accesses the system and inputs their own concerns or requests.

[0475] "Generative artificial intelligence" refers to artificial intelligence technology that analyzes text data entered by users and performs categorization and generates customized advice.

[0476] An "emotion analysis engine" refers to a system that identifies and analyzes emotional states from text data entered by users.

[0477] "Means for receiving the content of concerns" refers to a function that receives text data entered by the user and securely transmits it to the server.

[0478] "Methods for analyzing and classifying the content of problems" refers to a function that uses generative artificial intelligence to analyze text data of problems entered by users and classify it into specific categories.

[0479] "Means for determining emotional state" refers to a function that uses an emotion analysis engine to determine the user's emotional state from their text data.

[0480] "Means for generating optimal advice" refers to a function that generates customized advice based on analyzed concerns and emotional states.

[0481] "Means of providing advice to the user" refers to a function that sends the generated advice to the user's device and displays it.

[0482] "A means of selecting services necessary for solving a problem" refers to a function that selects services or companies suitable for solving a problem from a database based on the analysis results.

[0483] "Means of presenting services to users" refers to functions that transmit and display information about selected services and companies to the user's device.

[0484] "Means of sending user information to a service" refers to a function that sends user information to a selected service based on the user's choices.

[0485] "Means of collecting and managing referral fees" refers to the function of collecting and managing referral fees from partnered services when a match with a selected service is successful.

[0486] This invention is a system that receives and analyzes users' problems, provides appropriate advice, and seamlessly connects them to the services necessary for resolving those problems. Specific embodiments are described below.

[0487] Basic System Configuration

[0488] This system consists of the following main components:

[0489] Terminal: A device that provides an interface for users to input their concerns. Specifically, this includes personal computers and smartphones.

[0490] Server: The central system that analyzes problems, recognizes emotions, generates advice, and selects services.

[0491] Generative artificial intelligence: AI models used for analyzing problems and generating advice. Specifically, OpenAI's GPT-3 falls into this category.

[0492] Sentiment analysis engine: A system that recognizes and analyzes emotions from text entered by the user. IBM Watson® is an example of this type of system.

[0493] Database: Stores service information and is used for selection. Specifically, this refers to Microsoft® Azure® SQL Database.

[0494] System Operation Description

[0495] 1. The user accesses the device and enters their problem in text format. At this time, they open a browser, access the system's website, and enter "I've been feeling stressed lately because of childcare" into the input form.

[0496] 2. The terminal receives the entered problem content and sends the data to the server. Specifically, a JavaScript® function is called, and the text data is sent to the server via an HTTPS request.

[0497] 3. The server passes the received data to a generative artificial intelligence and an emotion analysis engine for analysis. The server is built with Python, and at this stage, it sends the data to OpenAI's GPT-3 and IBM Watson via API.

[0498] 4. The emotion analysis engine determines the emotional state from the user's input and feeds the result back to the generative artificial intelligence. The server receives the emotion analysis results returned from IBM Watson and applies that data to the GPT-3 model.

[0499] 5. The server classifies the problem into a specific category based on the analysis results and sentiment analysis results. For example, based on the keyword "childcare," an algorithm is run to classify the problem as being related to childcare.

[0500] 6. Based on the analysis results, the server selects an appropriate advice template and generates customized advice using generative artificial intelligence.

[0501] Examples of prompt statements:

[0502] User-entered text about their problem: 'I've been feeling stressed lately because of childcare. What should I do?'

[0503] Analyze the emotional state of this text and generate advice on managing parenting stress.

[0504] 7. The server sends the generated advice to the terminal, and the terminal displays the advice to the user. The received advice text is rendered into a specified HTML element on the web page.

[0505] 8. Based on the analysis results, the server selects a service suitable for solving the user's problem. Specifically, it uses SQL queries to search the database for services related to the user's problem.

[0506] 9. The server generates a list of selected services and sends it to the terminal. The list is serialized in JSON format and sent as an HTTPS response.

[0507] 10. The device displays a list of services relevant to the user, and the user selects a service of interest from the presented list.

[0508] 11. The terminal sends the user's selection to the server, and the server sends the user information to the selected service. An HTTP POST request containing the user information is sent to the API endpoint of the selected service.

[0509] 12. When a match is successfully made with a selected service, the server collects and manages a referral fee from the partnered service. The management and billing processes will use a dedicated management system.

[0510] As described above, the present invention is a system that efficiently solves users' problems by comprehensively analyzing their concerns and providing customized advice and suitable services.

[0511] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0512] Specific processing steps of the system

[0513] Step 1:

[0514] The user accesses the device and enters their problem in text format.

[0515] Input: User's problem text (e.g., "I've been feeling stressed lately because of childcare")

[0516] Specific actions: Open a browser, access the system's website, and enter text into the input form.

[0517] Output: Text data of the entered problem

[0518] Step 2:

[0519] The terminal receives the entered problem details and sends the data to the server.

[0520] Input: Text data of the problem

[0521] Specific operation: A JavaScript function is called, and text data is sent to the server via an HTTPS request.

[0522] Output: Text data of the problem sent to the server

[0523] Step 3:

[0524] The server passes the received data to a generative artificial intelligence and an emotion analysis engine for analysis.

[0525] Input: Text data of the problem sent to the server

[0526] Specific operation: The server is built in Python and sends data via API to generative artificial intelligence (e.g., OpenAI's GPT-3) and sentiment analysis engines (e.g., IBM Watson).

[0527] Output: Analysis results from generative artificial intelligence and emotion analysis engine

[0528] Step 4:

[0529] The emotion analysis engine identifies the user's emotional state from their input and feeds the results back to the generative artificial intelligence.

[0530] Input: User's text data

[0531] Specific operation: An emotion analysis engine (e.g., IBM Watson) analyzes text data and determines the emotional state.

[0532] Output: Emotion analysis results

[0533] Step 5:

[0534] The server categorizes the problem into a specific category based on the analysis results and emotion analysis results.

[0535] Input: Analysis results and sentiment analysis results

[0536] Specific operation: Perform category classification using a keyword extraction algorithm or machine learning model (e.g., keyword extraction using natural language processing techniques).

[0537] Output: Category classification results

[0538] Step 6:

[0539] Based on the analysis results, the server selects an appropriate advice template and generates customized advice using generative artificial intelligence.

[0540] Input: Category classification results, sentiment analysis results

[0541] Specific operation: The server retrieves the necessary templates from the database and generates prompts using generative artificial intelligence (e.g., OpenAI's GPT-3).

[0542] Examples of prompt statements:

[0543] User-entered text about their problem: 'I've been feeling stressed lately because of childcare. What should I do?'

[0544] Analyze the emotional state of this text and generate advice on managing parenting stress.

[0545] Output: Generated customization advice

[0546] Step 7:

[0547] The server sends the generated advice to the terminal, and the terminal displays the advice to the user.

[0548] Input: Generated customization advice

[0549] Specific operation: The generated advice text is returned to the device as an HTTPS response, and the device renders the received data on a web page (e.g., (Display text).

[0550] Output: Advice displayed to the user

[0551] Step 8:

[0552] Based on the analysis results, the server selects the service best suited to solving the problem.

[0553] Input: Analysis results and generated customized advice results

[0554] Specific operation: Use SQL queries to search the database for service information related to solving the problem.

[0555] Output: List of selected services

[0556] Step 9:

[0557] The server generates a list of selected services and sends it to the terminal.

[0558] Input: List of service information

[0559] Specific operation: Serialize the list into JSON format and send it as an HTTPS response.

[0560] Output: Service list sent to the terminal

[0561] Step 10:

[0562] The device displays a list of services relevant to the user, and the user selects a service of interest from the presented list.

[0563] Input: Service List

[0564] Specific operation: The received list data is placed on a specified HTML element on a web page (e.g., Render it to ) and allow the user to select it.

[0565] Output: User service selection

[0566] Step 11:

[0567] The terminal sends the user's selection results to the server, and the server sends the user information to the selected service.

[0568] Input: User's selection result

[0569] Specific operation: An HTTP request containing the user's selection information is sent to the server, and the server sends an HTTP POST request containing the user information to the API endpoint of the selected service.

[0570] Output: User information sent to the service

[0571] Step 12:

[0572] When a match is successfully made with a selected service, the server collects a referral fee from the partnered service and manages the transaction.

[0573] Input: Matching success information

[0574] Specific operation: Upon successful matching, an API call for referral fee billing is automatically made and recorded in the management system.

[0575] Output: Management information for collected referral fees

[0576] The above outlines the specific processing steps of the system.

[0577] (Application Example 2)

[0578] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0579] In modern industrial environments, there is a need to optimize the efficiency of factory robots and workers while also enabling flexible responses that take into account the emotional state of workers. However, there is no system that comprehensively understands the operating status and error information of factory robots along with the emotional state of workers and takes immediate, appropriate action. As a result, the risk of decreased efficiency and deterioration in work quality is increasing.

[0580] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for receiving the content of a problem input by the user, means for analyzing and classifying the content of the problem using generative artificial intelligence, means for generating optimal advice based on the classified problem, means for presenting the generated advice to the user, means for selecting companies and services necessary to solve the problem, means for presenting the selected companies and services to the user, means for receiving the user's selection results and transmitting user information to the selected companies, means for collecting and managing referral fees, means for collecting operational data from industrial machinery, means for collecting and analyzing worker emotion data, means for generating and presenting advice regarding the operation of industrial machinery based on the analysis results, and means for connecting to external technical support services as needed. This makes it possible to comprehensively manage the status of both factory robots and workers and to take appropriate action immediately.

[0581] A "user" is someone who works in a factory or someone who uses the system to input data about their worries and emotions.

[0582] "Generative artificial intelligence" is an artificial intelligence technology that analyzes and classifies input data and generates optimal advice.

[0583] "Problems" refer to the issues and challenges that users face, and are information provided to the system through input.

[0584] "Advice" refers to guidelines for solutions and improvements generated by generative artificial intelligence based on the analysis results.

[0585] "Industrial machinery" is a general term for robots and production equipment used in factories, and is the subject of operational data collection.

[0586] "Operational data" refers to data related to the operating status of industrial machinery, such as operating hours and error codes.

[0587] "Emotional data" refers to data about a user's emotional state, including information such as stress levels and fatigue levels.

[0588] A "server" is a central information processing device that performs tasks such as data analysis, advice generation, and selection of companies and services.

[0589] "Means" refers to the specific methods or devices used to realize each function of the system.

[0590] "External technical support services" refer to external companies or experts that provide problem-solving and technical support within the factory.

[0591] Modes for carrying out the invention

[0592] Basic System Configuration

[0593] The system that implements this application consists of the following main components.

[0594] 1. Terminal: A device that provides an interface for users to input data about their worries and emotions. Specifically, this includes tablet devices and smart glasses.

[0595] 2. Server: This is the central system that analyzes problems, recognizes emotions, generates advice, and selects companies and services. It is equipped with a database, generative artificial intelligence (AI), and an emotion engine.

[0596] 3. Industrial machinery: These are robots and production equipment used in factories, and are the subjects of operational data collection.

[0597] System operation

[0598] Data collection

[0599] The device collects data on worries and emotions entered by the user. This emotional data is entered by the user using a tablet or smart glasses. For example, the user receives the following prompt: "Please enter your current stress level on a scale of 1 to 5, with 1 being the lowest and 5 being the highest." The collected data is sent to the server.

[0600] Industrial machinery is equipped with operational sensors that collect operational data such as operating time, temperature, and error codes. This data is also periodically transmitted to a server.

[0601] Data Analysis

[0602] The server receives collected data on worries, emotions, and operational data. Generative artificial intelligence (using TENSORFLOW®) analyzes the text data and classifies the worries. Simultaneously, the emotion engine analyzes the emotion data and recognizes the user's mental state and emotions.

[0603] Generating advice

[0604] Based on the analysis results and sentiment analysis results, the server generates advice on how to resolve problems and errors in industrial machinery. This advice is customized to the specific situation of the user and the industrial machinery. For example, it might generate specific advice such as, "The machine temperature is high. Please check the cooling system. Also, the worker's stress level is high. We recommend taking a break."

[0605] Providing advice and connecting

[0606] The terminal displays the generated advice to the user. Furthermore, if necessary, the server seamlessly connects with external technical support services to provide real-time support.

[0607] Hardware and software to use

[0608] Hardware:

[0609] Industrial machinery (with operation data collection sensors)

[0610] Tablet devices and smart glasses (for inputting emotional data)

[0611] software:

[0612] Python: Data Analysis and AI Model Building

[0613] TensorFlow: Implementing Generative Artificial Intelligence and Emotion Engines

[0614] MySQL®: Storage and management of collected data

[0615] REST API: Data reception and transmission interface

[0616] Flask: Server construction and API development

[0617] Specific example

[0618] User A is working in a factory and inputs emotional data into a tablet device. For example, in response to the prompt, "Please enter your current stress level on a scale of 1 to 5. 1 is the lowest, and 5 is the highest," User A enters 3. The device sends this data to a server, which analyzes it and generates advice. Next, the advice is sent to the device, displaying to User A, "Your current stress level is high, so we recommend taking a break. Also, the machine temperature is high, so please check the cooling system." Furthermore, if necessary, the system can connect to external technical support services for additional assistance.

[0619] This system will improve efficiency within the factory and allow for flexible responses that take into account the health of the workers.

[0620] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0621] Step 1:

[0622] The user accesses the device and inputs emotional data. Specifically, the user receives a prompt message, "Please enter your current stress level on a scale of 1 to 5. 1 is the lowest, and 5 is the highest," and enters their stress level. The stress level (e.g., 3) is collected as input data.

[0623] Step 2:

[0624] The device sends collected emotional data to the server. The device converts the stress level value (e.g., 3) into JSON format and transfers it to the server via a REST API. The input is the user's emotional data, and the output is the data transmission to the server.

[0625] Step 3:

[0626] Industrial machinery collects operational data and sends it to a server. This operational data includes operating time, temperature, and error codes. For example, data might be collected showing an operating time of 500 minutes, a temperature of 75 degrees, and an error code of 0.

[0627] Step 4:

[0628] The server receives the collected sentiment and operational data and stores it in a database. The server uses MySQL to store the sentiment and operational data. Specific data inserted into the database includes stress levels, uptime, temperature, and error codes.

[0629] Step 5:

[0630] The server uses generative artificial intelligence to analyze emotional and operational data. During the analysis, the emotional engine assesses the user's stress level, and the generative AI model (using TensorFlow) comprehensively analyzes the operational and emotional data. As a result of the analysis, factors contributing to decreased work efficiency and machine error situations are identified.

[0631] Step 6:

[0632] The server generates advice based on the analysis results. The generated advice is specific, such as, "The machine temperature is high, please check the cooling system. Also, the worker's stress level is high; we recommend taking a break." The input is the analysis results, and the output is the generated advice.

[0633] Step 7:

[0634] The server sends the generated advice to the terminal. The server converts the generated advice into JSON format and sends it to the terminal via a REST API. The input is the generated advice, and the output is the data sent to the terminal.

[0635] Step 8:

[0636] The terminal displays advice to the user. For example, the tablet screen might display, "The machine temperature is high; please check the cooling system. Also, the worker's stress level is high; a break is recommended." The input is the advice received from the server, and the output is what is displayed to the user.

[0637] Step 9:

[0638] The server connects to an external technical support service as needed. If the user requests additional support, the server sends the user's status and the required support details to the external technical support service. This provides real-time technical support. The input is the user's support request, and the output is the connection to the external technical support service.

[0639] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0640] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0641] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0642] [Second Embodiment]

[0643] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0644] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0645] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0646] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0647] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0648] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0649] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0650] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0651] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0652] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0653] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0654] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0655] This invention provides a system for receiving and analyzing users' problems, providing appropriate advice, and seamlessly connecting them to the companies and services necessary for resolving those problems. Specific embodiments for carrying out this invention are described below.

[0656] 1. Basic System Configuration

[0657] This system consists of the following main components:

[0658] Terminal: A device that provides an interface for users to input their concerns.

[0659] Server: The central system that analyzes and classifies problems, generates advice, and selects companies and services.

[0660] Generative artificial intelligence: AI models for analyzing problems and generating advice.

[0661] Database: Stores information about companies and services and uses it for selection.

[0662] 2. System Operation

[0663] Receiving and analyzing problems

[0664] 1. The user accesses the device and enters their problem in text format.

[0665] 2. The terminal receives the entered content of the problem and sends the data to the server.

[0666] 3. The server passes the received data to a generative artificial intelligence (AI) for analysis. The generative AI extracts keywords from the text and performs sentiment analysis to analyze the content of the problem in detail.

[0667] 4. Based on the analysis results, the server classifies the problems into specific categories (e.g., inheritance, childcare, health issues, etc.).

[0668] Providing advice

[0669] 5. Based on the analysis results, the server selects an advice template appropriate to the category of the problem. Furthermore, it uses generative artificial intelligence to generate customized advice tailored to the user's specific problem.

[0670] 6. Once the server has finished generating the advice, it sends the generated results to the terminal.

[0671] 7. The device displays the received advice to the user. This allows the user to obtain guidance for specific solutions.

[0672] Proposal of solutions and connection

[0673] 8. The server accesses the database and selects relevant companies and services based on the analyzed problem category. For example, in the case of inheritance, it retrieves a list of reliable tax accounting firms.

[0674] 9. The server sends a list of selected companies and services to the terminal.

[0675] 10. The device displays a list of relevant companies and services to the user. The user can select the desired company or service from the list.

[0676] 11. When a user selects a company or service, the device sends the selection to the server.

[0677] 12. The server sends user information to the selected company and performs the matching process.

[0678] Crowdfunding proposal (optional)

[0679] 13. The server will suggest an appropriate crowdfunding platform if funding is needed to solve the user's problem.

[0680] 14. The server sends information from the crowdfunding platform to the device.

[0681] 15. The device displays crowdfunding platform proposals to the user, allowing them to receive further support as needed.

[0682] Management of referral fees

[0683] 16. The server operates a system to collect referral fees from partner companies when a match is successfully made with selected companies or services. The management and billing process for referral fees is entrusted to a dedicated management system.

[0684] Specific example

[0685] For example, if user A has concerns about inheritance, it would look like this:

[0686] 1. User A enters "I'm worried about inheritance" into the portal site.

[0687] 2. The terminal sends the input content to the server.

[0688] 3. The server uses generative artificial intelligence to analyze the text and categorize it under the "inheritance" category.

[0689] 4. The server generates advice regarding inheritance and sends it to the terminal.

[0690] 5. The device displays advice to user A (e.g., "Regarding inheritance procedures").

[0691] 6. The server selects a list of trusted tax accounting firms from its database and sends it to the terminal.

[0692] 7. The terminal displays the list to user A.

[0693] 8. User A selects a specific tax accounting firm.

[0694] 9. The terminal sends the selection result to the server.

[0695] 10. The server sends User A's information to the selected tax accounting firm and performs the matching process.

[0696] 11. The server collects referral fees from the tax accounting firm and records them in the management system.

[0697] In this way, the present invention provides a system for efficiently and effectively solving users' problems, and means for implementing the same.

[0698] The following describes the processing flow.

[0699] Step 1:

[0700] The user accesses the portal site using their device and enters the details of their problem as text.

[0701] Step 2:

[0702] The terminal receives user input and sends that information to the server.

[0703] Step 3:

[0704] The server receives text data about the problem and passes it to a generative artificial intelligence for analysis.

[0705] Step 4:

[0706] The generative artificial intelligence on the server analyzes the text, extracting keywords and performing sentiment analysis.

[0707] Step 5:

[0708] The server uses the analysis results to classify the problems into specific categories (e.g., inheritance, childcare, health issues, etc.).

[0709] Step 6:

[0710] Based on the analysis results, the server selects an advice template corresponding to the problem category.

[0711] Step 7:

[0712] The server uses generative artificial intelligence to generate customized advice tailored to the user's specific concerns.

[0713] Step 8:

[0714] The server sends the generated advice to the terminal.

[0715] Step 9:

[0716] The device displays generated advice to the user.

[0717] Step 10:

[0718] Based on the analysis results, the server selects companies and services from its database that are suitable for solving the problem.

[0719] Step 11:

[0720] The server generates a list of selected companies and services and sends it to the terminal.

[0721] Step 12:

[0722] The device displays a list of companies and services related to the user.

[0723] Step 13:

[0724] Users select companies or services that interest them from a presented list.

[0725] Step 14:

[0726] The terminal sends the user's selection results to the server.

[0727] Step 15:

[0728] The server sends user information to the selected companies based on the user's selection results.

[0729] Step 16:

[0730] The server waits for a response from the selected company, and if the matching is successful, it sends the result to the terminal.

[0731] Step 17:

[0732] The device notifies the user of the matching result.

[0733] Step 18:

[0734] Users will contact the selected companies and services directly and proceed with specific procedures to resolve their issues.

[0735] Step 19:

[0736] Once the server completes the matching process, it manages the referral fees from partner companies and initiates the billing process.

[0737] Step 20:

[0738] The server receives the referral fee and records it in the management system.

[0739] Step 21:

[0740] In some cases, the server will send appropriate platform information to the terminal to suggest a crowdfunding platform.

[0741] Step 22:

[0742] The device displays crowdfunding platform proposals to the user.

[0743] Step 23:

[0744] Users can utilize crowdfunding platforms as needed to receive further support.

[0745] (Example 1)

[0746] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0747] In modern society, individuals face a wide variety of problems and challenges, often requiring specialized knowledge and support to resolve. However, selecting the right company or service, and receiving prompt and accurate advice, is difficult. Existing systems require users to gather information and perform the necessary procedures themselves, which consumes considerable time and effort. Furthermore, if appropriate experts or services cannot be found, the problem may worsen. Therefore, there is a need for efficient and effective means to resolve users' problems.

[0748] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0749] In this invention, the server includes a device for receiving the content of a user's problem, a device for analyzing and classifying the content of the problem using generative artificial intelligence, a device for generating optimal advice based on the classified problem, a device for presenting the generated advice to the user, a device for selecting relevant businesses and services necessary for solving the problem, a device for presenting the selected businesses and services to the user, a device for receiving the user's selection results and transmitting user information to the selected businesses, and a device for collecting and managing referral fees. As a result, the user can efficiently analyze their problem, receive appropriate advice, quickly connect to the necessary businesses and services, and obtain support for problem solving.

[0750] A "user" refers to an individual who attempts to solve their own problems using this system.

[0751] A "device" refers to a device that provides an interface for users to input their concerns. Specifically, this includes computers, smartphones, tablets, and so on.

[0752] A "server" refers to a central computer system that analyzes, classifies, and provides advice on problems, as well as selecting and matching relevant businesses and services.

[0753] "Generative artificial intelligence" refers to an AI model that analyzes input text data, extracts keywords, and performs sentiment analysis to understand the user's concerns in detail and generate appropriate advice.

[0754] "Analyzing" refers to using generative artificial intelligence to extract keywords and perform sentiment analysis on input data, thereby gaining a detailed understanding of its content.

[0755] "Classifying" refers to categorizing users' concerns into specific categories (e.g., inheritance, childcare, health issues, etc.) based on the analysis results.

[0756] "Generating advice" refers to using generative artificial intelligence based on category-specific templates to create customized solutions or guidelines for a user's specific problems.

[0757] "Presenting" refers to displaying generated advice and information about related businesses and services to the user.

[0758] "Selecting" refers to extracting and choosing relevant businesses and services from a database based on the analyzed categories of problems.

[0759] "Transmitting user information" refers to sending necessary user information via the network to the business entity or service selected by the user.

[0760] A "business entity" refers to an organization or company that provides the specialized knowledge and services necessary to solve a problem.

[0761] "Referral fee" refers to the commission collected from a partnering business when a user and business are successfully matched.

[0762] A "crowdfunding platform" refers to a service that allows users to raise funds online to solve their problems.

[0763] This invention provides a system for receiving and analyzing users' problems, offering appropriate advice, and seamlessly connecting them to the necessary companies and services for resolving those problems. This system consists of the following main components:

[0764] 1. Terminal: A device that provides an interface for users to input their problems. Specifically, this includes computers, smartphones, and tablets. Users input their problems in text format via the terminal.

[0765] 2. Server: This is the central system that analyzes, classifies, and provides advice on problems, as well as selecting and matching relevant businesses and services. Specifically, generative artificial intelligence (e.g., GPT-3) is used as the software, and it is executed within the server to perform data analysis and advice generation.

[0766] 3. Generative Artificial Intelligence: This AI model analyzes text data entered by the user, extracts keywords, and performs sentiment analysis to understand the user's concerns in detail and generate appropriate advice. This AI model heavily relies on the analysis of text data and the generation of advice.

[0767] 4. Database: Used to store information about companies and services, and to search for and select appropriate businesses and services that meet users' needs. Detailed information about businesses and services is registered within the database.

[0768] System operation details

[0769] Receiving and analyzing problems

[0770] When a user enters their problem into their device, the device sends that text data to a server via an HTTP request. The server then passes the received data to a generative artificial intelligence (AI). This AI extracts keywords and performs sentiment analysis based on the input text data, providing a detailed analysis of the user's problem.

[0771] Generating and providing advice

[0772] The server categorizes the user's concerns into specific categories based on the analysis results from the generative artificial intelligence. It then selects an advice template corresponding to the category and uses the generative artificial intelligence again to generate customized advice tailored to the user's specific concerns. The generated advice is sent from the server to the terminal and displayed to the user.

[0773] Selection of companies and services

[0774] The server selects relevant businesses and services based on the problem categories analyzed from the database. This selection is sent to the terminal as a list of businesses and services and displayed to the user. The user can then select their desired business or service from the displayed list.

[0775] User information submission and matching

[0776] When a user selects their desired business entity or service, the selection is sent from the terminal to the server. The server then sends the user information to the selected business entity and performs a matching process. This allows the user to quickly access the appropriate service.

[0777] Specific example

[0778] For example, if user A has concerns about inheritance, it would look like this:

[0779] 1. User A enters "I'm worried about inheritance" into the terminal.

[0780] 2. The device sends the text data to the server.

[0781] 3. The server uses generative artificial intelligence to analyze the text and categorize it under the "inheritance" category.

[0782] 4. The server generates advice regarding inheritance and sends it to the terminal.

[0783] 5. The device displays advice to user A (e.g., "Regarding inheritance procedures").

[0784] 6. The server selects a trusted expert from the database and sends the list to the terminal.

[0785] 7. The terminal displays the list to user A.

[0786] 8. User A selects a specific expert.

[0787] 9. The terminal sends the selection result to the server.

[0788] 10. The server sends User A's information to the selected expert and performs the matching process.

[0789] In this way, the present invention provides a system and means for implementing it that efficiently and effectively solves users' problems.

[0790] Example of a prompt

[0791] An example of a prompt message might read: "Please enter your problem in text format and send it to the server. The server will pass the text data to a generative artificial intelligence system that will analyze and classify your problem. It will then provide appropriate advice and a list of relevant businesses and services."

[0792] This system is a powerful tool for efficiently analyzing users' problems and providing quick and appropriate solutions.

[0793] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0794] Step 1:

[0795] The user enters their problem in text format into the device.

[0796] Input: Text data of the user's problem

[0797] Output: Text data received by the terminal

[0798] Users access the input interface of a portal site or application and describe their problems in detail. This text data is received by the device.

[0799] Step 2:

[0800] The terminal sends the entered text data about the problem to the server.

[0801] Input: Text data received on the device

[0802] Output: Text data transferred to the server

[0803] The terminal receives text data and sends it to the server via a communication method such as an HTTP request. HTTPS is the recommended communication protocol.

[0804] Step 3:

[0805] The server receives text data and passes it to a generative artificial intelligence for analysis.

[0806] Input: Text data transferred to the server

[0807] Output: Analyzed problem data (keywords, emotions, categories)

[0808] The server passes text data to a generative artificial intelligence (e.g., GPT-3). The generative AI extracts keywords from the text and performs sentiment analysis to analyze the content of the problem. As a result, the category and keywords of the problem are extracted.

[0809] Step 4:

[0810] The server categorizes the problems based on the analysis results.

[0811] Input: Analyzed problem data

[0812] Output: Categorized problem data

[0813] The server uses the analysis results from the generative artificial intelligence to classify the problems into specific categories. For example, it might categorize them into "inheritance," "childcare," or "health problems."

[0814] Step 5:

[0815] The server selects an advice template based on the category and uses generative artificial intelligence to generate customized advice.

[0816] Input: Categorized problem data

[0817] Output: Customized advice data

[0818] The server selects a pre-prepared advice template and uses generative artificial intelligence to customize the advice to address the user's specific concerns. The generated advice is output in text format.

[0819] Step 6:

[0820] The server sends the generated advice data to the terminal.

[0821] Input: Customized advice data

[0822] Output: Advice data transferred to the terminal

[0823] The server sends the generated advice data back to the terminal via an HTTP request. HTTPS is recommended to ensure the reliability of the communication.

[0824] Step 7:

[0825] The device displays the advice it has received to the user.

[0826] Input: Advice data transferred to the device

[0827] Output: Advice displayed to the user

[0828] The device displays the received advice data in a user-friendly format, allowing the user to obtain concrete guidance for solutions.

[0829] Step 8:

[0830] The server accesses the database and selects the relevant entities and services.

[0831] Input: Categorized problem data

[0832] Output: List of selected entities and services

[0833] Based on the analyzed problem categories, the server selects relevant businesses and services from the database. This results in a list of the businesses and services best suited to the user's problem.

[0834] Step 9:

[0835] The server sends a list of selected entities and services to the terminal.

[0836] Input: List of selected entities or services

[0837] Output: List of entities and services transferred to the terminal

[0838] The server sends a list of selected entities and services to the terminal. This is also done via an HTTP request.

[0839] Step 10:

[0840] The device displays a list of businesses and services associated with the device to the user.

[0841] Input: List of entities and services transferred to the terminal

[0842] Output: A list of entities and services displayed to the user.

[0843] The terminal displays a list of received entities and services to the user. The user can select the desired entity or service from this list.

[0844] Step 11:

[0845] When a user selects a company or service, the device sends that selection to the server.

[0846] Input: Information about the business entity or service selected by the user.

[0847] Output: Selection results sent to the server

[0848] When a user selects a specific business entity or service, the selection result is sent from the terminal to the server.

[0849] Step 12:

[0850] The server sends user information to the selected business entity and performs the matching process.

[0851] Input: Selection results sent to the server

[0852] Output: User information sent to the selected entity

[0853] The server sends user information to the selected business entity and performs a matching process. This allows users to quickly receive the support they need.

[0854] Step 13 (Optional):

[0855] The server sends information from the crowdfunding platform to the device.

[0856] Input: Problem data indicating that a crowdfunding proposal is deemed necessary.

[0857] Output: Information about the crowdfunding platform sent to the device.

[0858] In some cases, the server may determine that the user needs funding to solve their problem and send information about an appropriate crowdfunding platform.

[0859] Step 14 (Optional):

[0860] The device displays crowdfunding platform proposals to the user.

[0861] Input: Information from the crowdfunding platform sent to the device.

[0862] Output: Information about the crowdfunding platform displayed to the user.

[0863] The device displays project information from crowdfunding platforms to the user. The user can then receive further funding as needed.

[0864] Step 15:

[0865] The server collects and manages referral fees.

[0866] Input: Information on businesses and users that have been successfully matched.

[0867] Output: Collected referral fees and records in the management system

[0868] When a match is successful, the server collects a referral fee from the partner company and records it in a dedicated management system. This process is automated and functions as part of the revenue model.

[0869] (Application Example 1)

[0870] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0871] Traditional problem-solving systems have a problem in that they cannot quickly provide appropriate advice or relevant store information to users who are having trouble choosing products in a physical store. Therefore, users have to search for information and find solutions themselves, which is time-consuming and requires effort. Furthermore, the system in question is required not only to analyze the user's problem and present a suitable solution, but also to provide users with a way to quickly and effectively resolve their problem in a physical store.

[0872] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0873] In this invention, the server includes means for receiving the content of a user's problem, means for analyzing and classifying the content of the problem using generative artificial intelligence, means for generating optimal advice based on the classified problem, means for presenting the generated advice to the user, means for selecting companies and services necessary to solve the problem, means for presenting the selected companies and services to the user, means for receiving the user's selection results and transmitting user information to the selected companies, means for collecting and managing referral fees, means for providing information on relevant stores to resolve difficulties when the user is having trouble choosing a product, means for presenting information on the relevant stores to the user, and means for accessing a database for providing information on the stores. As a result, when a user is having trouble choosing a product in a physical store, they can use their smartphone to input their problem, and the system will analyze the problem and quickly provide appropriate solutions and information on relevant stores.

[0874] Definitions of important words

[0875] "A means of receiving user input about their concerns" refers to a function that allows users to input their concerns in text format using a specific device, and for the system to receive that input.

[0876] "Means for analyzing and classifying the content of the aforementioned problems using generative artificial intelligence" refers to a system that uses a generative AI model to extract keywords and perform sentiment analysis from input text data, and has the function of classifying the content of the problems into specific categories.

[0877] "Means for generating optimal advice based on the classified problems" refers to a function that generates advice best suited to solving the user's problems based on the analyzed and classified data.

[0878] "Means for presenting the generated advice to the user" refers to a means that has the function of displaying the generated advice on a device accessible to the user.

[0879] "Means for selecting companies and services necessary to solve the aforementioned problems" refers to a function that searches a database for and selects companies and services suitable for solving the user's problems.

[0880] "Means for presenting the selected companies and services to the user" refers to a function that displays a list of selected companies and services on the user's device.

[0881] "Means for receiving user selection results and transmitting user information to selected companies" refers to a system that receives company information selected by the user and transmits the user's information to the selected companies.

[0882] "Means for collecting and managing referral fees" refers to a system that collects referral fees from companies when a match is successful and manages those fees.

[0883] "A means of providing information on relevant stores to resolve difficulties when a user has trouble choosing a product" refers to a function that provides information on suitable stores to resolve difficulties a user encounters when choosing a product.

[0884] "Means for presenting information about the relevant stores to the user" refers to a means that has the function of displaying information about the relevant stores on the user's device.

[0885] "Means for accessing a database to provide information about the store" refers to a means that has the function of accessing a database and obtaining information in order to provide information about the relevant store.

[0886] Modes for carrying out the invention

[0887] This invention provides a system that allows users to input their concerns using their smartphone when they are having trouble choosing products in a physical store. The system then analyzes these concerns and quickly provides appropriate solutions and information about relevant stores. The following describes in detail specific embodiments for carrying out this invention.

[0888] 1. Basic System Configuration

[0889] This system consists of the following main components:

[0890] Device: A smartphone that provides an interface for users to input their problems or concerns.

[0891] Server: The central system that analyzes and classifies problems, generates advice, and selects companies and services.

[0892] Generative artificial intelligence (AI model): An AI model designed to analyze problems and generate advice.

[0893] Database: Stores information about companies and related stores, and uses it for selection.

[0894] 2. System Operation

[0895] Receiving and analyzing problems

[0896] 1. The user uses their smartphone to enter a specific problem in text format. For example, they might type, "I don't know what to get my child for their birthday."

[0897] 2. The terminal receives the entered content of the problem and sends the data to the server.

[0898] 3. The server passes the received data to a generative artificial intelligence (e.g., OpenAI's GPT-4) for analysis. The AI ​​model extracts keywords from the text and performs sentiment analysis to analyze the content of the problem in detail.

[0899] 4. Based on the analysis results, the server classifies the problem into a specific category (e.g., birthday present).

[0900] Providing advice

[0901] 5. Based on the analysis results, the server selects an advice template appropriate to the category of the problem. Furthermore, it uses generative artificial intelligence to generate customized advice tailored to the user's specific problem.

[0902] 6. Once the server has finished generating the advice, it sends the generated results to the terminal.

[0903] 7. The device displays the received advice to the user. For example, it might display specific advice such as, "Toys, books, and games are suitable as birthday presents."

[0904] Providing store information

[0905] 8. The server accesses the database and selects relevant stores based on the analyzed problem categories. For example, it retrieves lists such as "toy stores" and "bookstores."

[0906] 9. The server sends a list of selected stores to the terminal.

[0907] 10. The terminal displays a list of relevant stores to the user. The user can select their desired store from the list.

[0908] 11. When a user selects a specific store, detailed information about that store (e.g., address, contact information, business hours) is displayed.

[0909] Crowdfunding proposal (optional)

[0910] 12. The server will suggest an appropriate crowdfunding platform if funding is needed to solve the user's problem.

[0911] 13. The server sends information from the crowdfunding platform to the device.

[0912] 14. The device displays crowdfunding platform proposals to the user, allowing them to receive further support as needed.

[0913] This system allows users to quickly obtain specific advice and relevant store information to effectively resolve the difficulties they face when choosing products in physical stores. An example of a prompt message is, "I don't know what would be a good birthday present for my child."

[0914] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0915] Program processing steps

[0916] Step 1:

[0917] The user enters their problem in text format using their smartphone.

[0918] Input: The user enters "I don't know what would be a good birthday present for my child" into a smartphone application.

[0919] Specific action: The user enters their problem into a text box and presses the "Submit" button.

[0920] Step 2:

[0921] The terminal receives the entered problem details and sends the data to the server.

[0922] Input: Text data entered by the user.

[0923] Data processing: The terminal converts the text data into JSON format and sends it to the server.

[0924] Output: Input data in JSON format is sent to the server.

[0925] Specific operation: The terminal formats the text data into JSON format and sends an HTTP request to the server's API endpoint.

[0926] Step 3:

[0927] The server passes the received data to a generative artificial intelligence for analysis. The AI ​​model extracts keywords from the text and performs sentiment analysis to analyze the content of the problem in detail.

[0928] Input: Input data in JSON format.

[0929] Data processing: An AI model (e.g., GPT-4) extracts keywords from text, performs sentiment analysis, and categorizes the data.

[0930] Output: The analysis results (categories and keywords) are returned to the server.

[0931] Specific operation: The server sends an API request to the AI ​​model, the model performs text analysis, and returns the analysis results to the server.

[0932] Step 4:

[0933] Based on the analysis results, the server categorizes the problem into a specific category (e.g., birthday present).

[0934] Input: Analysis results returned from the AI ​​model.

[0935] Data processing: Based on the analysis results, the data is classified into specific categories.

[0936] Output: Classified data is generated.

[0937] Specific operation: The server compares the analysis results with a preset category list to identify the corresponding category.

[0938] Step 5:

[0939] Based on the analysis results, the server selects an advice template appropriate to the problem category and uses generative artificial intelligence to generate personalized advice for the user.

[0940] Input: Categorized data and advice templates.

[0941] Data processing: AI models generate customized advice.

[0942] Output: Customized advice.

[0943] Specific operation: The server passes an advice template to the AI ​​model, which then generates advice that customizes the template based on categorical data.

[0944] Step 6:

[0945] Once the server has finished generating the advice, it sends the results to the terminal.

[0946] Input: Generated advice data.

[0947] Data processing: Convert the advice data to JSON format.

[0948] Output: Advice data in JSON format is sent to the terminal.

[0949] Specific operation: The server formats the generated advice into JSON format and sends an HTTP request to the terminal's API endpoint.

[0950] Step 7:

[0951] The device displays the received advice to the user.

[0952] Input: Advice data in JSON format received from the server.

[0953] Output: Advice displayed to the user.

[0954] Specific operation: The terminal parses the JSON data and displays advice in the user interface.

[0955] Step 8:

[0956] The server accesses the database and selects relevant stores based on the analyzed problem categories.

[0957] Input: Classified category data.

[0958] Data processing: Based on category data, relevant store information is searched and retrieved from the database.

[0959] Output: List of store information.

[0960] Specific operation: The server sends category data as a query to the database and retrieves related store information.

[0961] Step 9:

[0962] The server sends a list of selected stores to the terminal.

[0963] Input: List of store information.

[0964] Data processing: Convert store information to JSON format.

[0965] Output: A list of stores in JSON format is sent to the terminal.

[0966] Specific operation: The server formats the store information in JSON format and sends an HTTP request to the terminal's API endpoint.

[0967] Step 10:

[0968] The terminal displays a list of relevant stores to the user.

[0969] Input: A list of stores in JSON format received from the server.

[0970] Output: A list of stores displayed to the user.

[0971] Specific operation: The terminal parses the JSON data and displays the store information as a list in the user interface.

[0972] Step 11:

[0973] When a user selects a specific store, detailed information about that store is displayed.

[0974] Input: User's store selection action.

[0975] Output: Detailed information about the selected store.

[0976] Specific action: The device displays detailed information about the selected store (e.g., address, contact information, business hours).

[0977] Step 12:

[0978] The server will, in some cases, suggest an appropriate crowdfunding platform when funding is needed to solve a user's problem.

[0979] Input: User's problem and analysis results.

[0980] Data processing: AI analysis to propose crowdfunding platforms.

[0981] Output: Proposal for a crowdfunding platform.

[0982] Specific operation: The server proposes a crowdfunding campaign based on the analysis results and sends it to the terminal.

[0983] Step 13:

[0984] The device displays proposals from crowdfunding platforms to the user, allowing them to receive further support as needed.

[0985] Input: Crowdfunding proposal information received from the server.

[0986] Output: Crowdfunding information displayed to the user.

[0987] Specific action: The device displays crowdfunding proposals it has received in the user interface.

[0988] Through these steps, users can use their smartphones to get quick and effective advice and relevant store information when they have trouble choosing products in a physical store.

[0989] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0990] This invention provides a system that receives and analyzes users' concerns, provides appropriate advice, and seamlessly connects them to the necessary companies and services for resolution, in addition to an emotion engine that recognizes the user's emotions. Specific embodiments for carrying out this invention will be described below.

[0991] Basic System Configuration

[0992] This system consists of the following main components:

[0993] Terminal: A device that provides an interface for users to input their concerns.

[0994] Server: The central system that analyzes problems, recognizes emotions, generates advice, and selects companies and services.

[0995] Generative artificial intelligence: AI models for analyzing problems and generating advice.

[0996] Emotion engine: A system that recognizes and analyzes emotions from text entered by the user.

[0997] Database: Stores information about companies and services and uses it for selection.

[0998] System operation

[0999] Receiving and analyzing problems

[1000] 1. The user accesses the device and enters their problem in text format.

[1001] 2. The terminal receives the entered content of the problem and sends the data to the server.

[1002] 3. The server passes the received data to the generative artificial intelligence and the emotion engine for analysis. The generative artificial intelligence extracts keywords from the text and performs emotion analysis to analyze the content of the problem in detail.

[1003] 4. The emotion engine on the server determines the emotional state from the user's input and feeds the result back to the generative artificial intelligence.

[1004] 5. The server classifies the problem into a specific category (e.g., inheritance, childcare, health issues, etc.) based on the analysis results and sentiment analysis results.

[1005] Providing advice

[1006] 6. Based on the analysis results, the server selects an advice template appropriate to the category of the problem. Furthermore, it uses generative artificial intelligence to generate customized advice that is tailored to the user's specific problem and emotional state.

[1007] 7. The server sends the generated advice to the terminal.

[1008] 8. The device displays generated advice to the user. This allows the user to receive guidance on solutions that take their emotional state into consideration.

[1009] Proposal of solutions and connection

[1010] 9. Based on the analysis results, the server selects companies and services from the database that are suitable for solving the problem. The results of the sentiment analysis are also taken into consideration in the selection process.

[1011] 10. The server generates a list of selected companies and services and sends it to the terminal.

[1012] 11. The device displays a list of companies and services related to the user.

[1013] 12. The user selects companies or services of interest from the presented list.

[1014] 13. The terminal sends the user's selection results to the server.

[1015] 14. The server sends user information to the selected companies based on the user's selection results.

[1016] Crowdfunding proposal (optional)

[1017] 15. The server will suggest an appropriate crowdfunding platform if, in some cases, funding is needed to solve the user's problem.

[1018] 16. The server sends information from the crowdfunding platform to the device.

[1019] 17. The device displays crowdfunding platform proposals to the user, allowing them to receive further support as needed.

[1020] Management of referral fees

[1021] 18. The server operates a system to collect referral fees from partner companies when a match is successfully made with selected companies or services. The management and billing process for referral fees is entrusted to a dedicated management system.

[1022] Specific example

[1023] For example, if user B has concerns about childcare, it would look like this:

[1024] 1. User B enters their "childcare concerns" into the portal site.

[1025] 2. The terminal sends the input content to the server.

[1026] 3. The server uses generative artificial intelligence and an emotion engine to analyze the text and classify it into the "childcare" category. At the same time, the emotion engine recognizes user B's mental state and emotions.

[1027] 4. The server generates advice and creates customized advice that takes sentiment analysis results into account.

[1028] 5. The server sends the generated advice to the terminal, which then displays it to user B (e.g., "How to manage stress in childcare").

[1029] 6. The server selects suitable childcare support companies and services from the database and sends the list to the terminal.

[1030] 7. The device displays a list to User B, and User B selects a specific childcare support service.

[1031] 8. The device sends the selection results to the server.

[1032] 9. The server sends User B's information to the selected childcare support service and performs the matching process.

[1033] 10. The server collects referral fees from childcare support services and records them in the management system.

[1034] In this way, the present invention realizes a system that analyzes user concerns, including their emotions, provides solutions, and seamlessly connects to businesses and services.

[1035] The following describes the processing flow.

[1036] Step 1:

[1037] The user accesses the portal site using their device and enters the details of their problem as text.

[1038] Step 2:

[1039] The terminal receives user input and sends that information to the server.

[1040] Step 3:

[1041] The server receives the text data of the problem and passes it to a generative artificial intelligence to begin analysis.

[1042] Step 4:

[1043] The server passes user input data to the emotion engine, which then recognizes the user's emotional state.

[1044] Step 5:

[1045] Generative artificial intelligence analyzes text data, extracting keywords and performing sentiment analysis. Simultaneously, a sentiment engine determines the user's emotional state.

[1046] Step 6:

[1047] The server collects analysis results from generative artificial intelligence and emotion engines, and classifies the problems into specific categories (e.g., inheritance, childcare, health issues, etc.).

[1048] Step 7:

[1049] The server selects an advice template that corresponds to the problem category.

[1050] Step 8:

[1051] The server uses generative artificial intelligence to generate customized advice based on the user's specific concerns and emotional state.

[1052] Step 9:

[1053] The server sends the generated advice to the terminal.

[1054] Step 10:

[1055] The device displays generated advice to the user. This provides the user with specific solutions that take their emotional state into consideration.

[1056] Step 11:

[1057] Based on the analysis results, the server selects companies and services from its database that are necessary to solve the problem. The results of the emotional analysis are also taken into consideration in the selection process.

[1058] Step 12:

[1059] The server generates a list of selected companies and services and sends it to the terminal.

[1060] Step 13:

[1061] The device displays a list of companies and services related to the user.

[1062] Step 14:

[1063] Users select companies or services that interest them from a presented list.

[1064] Step 15:

[1065] The terminal sends the user's selection results to the server.

[1066] Step 16:

[1067] The server sends user information to the selected companies based on the user's selection results.

[1068] Step 17:

[1069] The server waits for a response from the selected company, and if the matching is successful, it sends the result to the terminal.

[1070] Step 18:

[1071] The device notifies the user of the matching result.

[1072] Step 19:

[1073] Users will contact the selected companies and services directly and proceed with specific procedures to resolve their issues.

[1074] Step 20:

[1075] Once the server completes the matching process, it manages the referral fees from partner companies and initiates the billing process.

[1076] Step 21:

[1077] The server receives the referral fee and records it in the management system.

[1078] Step 22:

[1079] In some cases, the server will send appropriate platform information to the terminal to suggest a crowdfunding platform.

[1080] Step 23:

[1081] The device displays crowdfunding platform proposals to the user.

[1082] Step 24:

[1083] Users can utilize crowdfunding platforms as needed to receive further support.

[1084] (Example 2)

[1085] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[1086] Conventional problem-solving support systems lacked the technology to appropriately recognize users' emotions and customize advice based on them. Furthermore, they lacked the functionality to seamlessly suggest and connect users with suitable services and companies. As a result, users often failed to alleviate stress or find appropriate services. This invention aims to solve these problems and provide users with a more effective means of resolving their problems.

[1087] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1088] In this invention, the server includes means for receiving the content of the user's problem, means for analyzing and classifying the content of the problem using generative artificial intelligence, and means for determining the user's emotional state from the user's input using an emotion analysis engine. This makes it possible to analyze the user's problem in detail and provide customized advice based on their emotional state. The server also includes means for generating optimal advice based on the classified problem, means for presenting the generated advice to the user, means for selecting the services necessary to solve the problem, means for presenting the selected services to the user, means for receiving the user's selection results and transmitting user information to the selected services, and means for collecting and managing referral fees. This enables efficient problem solving by providing the information and services necessary to solve the user's problem in a centralized manner.

[1089] A "user" refers to a person who accesses the system and inputs their own concerns or requests.

[1090] "Generative artificial intelligence" refers to artificial intelligence technology that analyzes text data entered by users and performs categorization and generates customized advice.

[1091] An "emotion analysis engine" refers to a system that identifies and analyzes emotional states from text data entered by users.

[1092] "Means for receiving the content of concerns" refers to a function that receives text data entered by the user and securely transmits it to the server.

[1093] "Methods for analyzing and classifying the content of problems" refers to a function that uses generative artificial intelligence to analyze text data of problems entered by users and classify it into specific categories.

[1094] "Means for determining emotional state" refers to a function that uses an emotion analysis engine to determine the user's emotional state from their text data.

[1095] "Means for generating optimal advice" refers to a function that generates customized advice based on analyzed concerns and emotional states.

[1096] "Means of providing advice to the user" refers to a function that sends the generated advice to the user's device and displays it.

[1097] "A means of selecting services necessary for solving a problem" refers to a function that selects services or companies suitable for solving a problem from a database based on the analysis results.

[1098] "Means of presenting services to users" refers to functions that transmit and display information about selected services and companies to the user's device.

[1099] "Means of sending user information to a service" refers to a function that sends user information to a selected service based on the user's choices.

[1100] "Means of collecting and managing referral fees" refers to the function of collecting and managing referral fees from partnered services when a match with a selected service is successful.

[1101] This invention is a system that receives and analyzes users' problems, provides appropriate advice, and seamlessly connects them to the services necessary for resolving those problems. Specific embodiments are described below.

[1102] Basic System Configuration

[1103] This system consists of the following main components:

[1104] Terminal: A device that provides an interface for users to input their concerns. Specifically, this includes personal computers and smartphones.

[1105] Server: The central system that analyzes problems, recognizes emotions, generates advice, and selects services.

[1106] Generative artificial intelligence: AI models used for analyzing problems and generating advice. Specifically, OpenAI's GPT-3 falls into this category.

[1107] Sentiment analysis engine: A system that recognizes and analyzes emotions from text entered by the user. IBM Watson is an example of this type of system.

[1108] Database: Stores service information and is used for selection. Specifically, this refers to Microsoft Azure SQL Database.

[1109] System Operation Description

[1110] 1. The user accesses the device and enters their problem in text format. At this time, they open a browser, access the system's website, and enter "I've been feeling stressed lately because of childcare" into the input form.

[1111] 2. The terminal receives the entered problem content and sends the data to the server. Specifically, a JavaScript function is called, and the text data is sent to the server via an HTTPS request.

[1112] 3. The server passes the received data to a generative artificial intelligence and an emotion analysis engine for analysis. The server is built with Python, and at this stage, it sends the data to OpenAI's GPT-3 and IBM Watson via API.

[1113] 4. The emotion analysis engine determines the emotional state from the user's input and feeds the result back to the generative artificial intelligence. The server receives the emotion analysis results returned from IBM Watson and applies that data to the GPT-3 model.

[1114] 5. The server classifies the problem into a specific category based on the analysis results and sentiment analysis results. For example, based on the keyword "childcare," an algorithm is run to classify the problem as being related to childcare.

[1115] 6. Based on the analysis results, the server selects an appropriate advice template and generates customized advice using generative artificial intelligence.

[1116] Examples of prompt statements:

[1117] User-entered text about their problem: 'I've been feeling stressed lately because of childcare. What should I do?'

[1118] Analyze the emotional state of this text and generate advice on managing parenting stress.

[1119] 7. The server sends the generated advice to the terminal, and the terminal displays the advice to the user. The received advice text is rendered into a specified HTML element on the web page.

[1120] 8. Based on the analysis results, the server selects a service suitable for solving the user's problem. Specifically, it uses SQL queries to search the database for services related to the user's problem.

[1121] 9. The server generates a list of selected services and sends it to the terminal. The list is serialized in JSON format and sent as an HTTPS response.

[1122] 10. The device displays a list of services relevant to the user, and the user selects a service of interest from the presented list.

[1123] 11. The terminal sends the user's selection to the server, and the server sends the user information to the selected service. An HTTP POST request containing the user information is sent to the API endpoint of the selected service.

[1124] 12. When a match is successfully made with a selected service, the server collects and manages a referral fee from the partnered service. The management and billing processes will use a dedicated management system.

[1125] As described above, the present invention is a system that efficiently solves users' problems by comprehensively analyzing their concerns and providing customized advice and suitable services.

[1126] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1127] Specific processing steps of the system

[1128] Step 1:

[1129] The user accesses the device and enters their problem in text format.

[1130] Input: User's problem text (e.g., "I've been feeling stressed lately because of childcare")

[1131] Specific actions: Open a browser, access the system's website, and enter text into the input form.

[1132] Output: Text data of the entered problem

[1133] Step 2:

[1134] The terminal receives the entered problem details and sends the data to the server.

[1135] Input: Text data of the problem

[1136] Specific operation: A JavaScript function is called, and text data is sent to the server via an HTTPS request.

[1137] Output: Text data of the problem sent to the server

[1138] Step 3:

[1139] The server passes the received data to a generative artificial intelligence and an emotion analysis engine for analysis.

[1140] Input: Text data of the problem sent to the server

[1141] Specific operation: The server is built in Python and sends data via API to generative artificial intelligence (e.g., OpenAI's GPT-3) and sentiment analysis engines (e.g., IBM Watson).

[1142] Output: Analysis results from generative artificial intelligence and emotion analysis engine

[1143] Step 4:

[1144] The emotion analysis engine identifies the user's emotional state from their input and feeds the results back to the generative artificial intelligence.

[1145] Input: User's text data

[1146] Specific operation: An emotion analysis engine (e.g., IBM Watson) analyzes text data and determines the emotional state.

[1147] Output: Emotion analysis results

[1148] Step 5:

[1149] The server categorizes the problem into a specific category based on the analysis results and emotion analysis results.

[1150] Input: Analysis results and sentiment analysis results

[1151] Specific operation: Perform category classification using a keyword extraction algorithm or machine learning model (e.g., keyword extraction using natural language processing techniques).

[1152] Output: Category classification results

[1153] Step 6:

[1154] Based on the analysis results, the server selects an appropriate advice template and generates customized advice using generative artificial intelligence.

[1155] Input: Category classification results, sentiment analysis results

[1156] Specific operation: The server retrieves the necessary templates from the database and generates prompts using generative artificial intelligence (e.g., OpenAI's GPT-3).

[1157] Examples of prompt statements:

[1158] User-entered text about their problem: 'I've been feeling stressed lately because of childcare. What should I do?'

[1159] Analyze the emotional state of this text and generate advice on managing parenting stress.

[1160] Output: Generated customization advice

[1161] Step 7:

[1162] The server sends the generated advice to the terminal, and the terminal displays the advice to the user.

[1163] Input: Generated customization advice

[1164] Specific operation: The generated advice text is returned to the device as an HTTPS response, and the device renders the received data on a web page (e.g., (Display text).

[1165] Output: Advice displayed to the user

[1166] Step 8:

[1167] Based on the analysis results, the server selects the service best suited to solving the problem.

[1168] Input: Analysis results and generated customized advice results

[1169] Specific operation: Use SQL queries to search the database for service information related to solving the problem.

[1170] Output: List of selected services

[1171] Step 9:

[1172] The server generates a list of selected services and sends it to the terminal.

[1173] Input: List of service information

[1174] Specific operation: Serialize the list into JSON format and send it as an HTTPS response.

[1175] Output: Service list sent to the terminal

[1176] Step 10:

[1177] The device displays a list of services relevant to the user, and the user selects a service of interest from the presented list.

[1178] Input: Service List

[1179] Specific operation: The received list data is placed on a specified HTML element on a web page (e.g., Render it to ) and allow the user to select it.

[1180] Output: User service selection

[1181] Step 11:

[1182] The terminal sends the user's selection results to the server, and the server sends the user information to the selected service.

[1183] Input: User's selection result

[1184] Specific operation: An HTTP request containing the user's selection information is sent to the server, and the server sends an HTTP POST request containing the user information to the API endpoint of the selected service.

[1185] Output: User information sent to the service

[1186] Step 12:

[1187] When a match is successfully made with a selected service, the server collects a referral fee from the partnered service and manages the transaction.

[1188] Input: Matching success information

[1189] Specific operation: Upon successful matching, an API call for referral fee billing is automatically made and recorded in the management system.

[1190] Output: Management information for collected referral fees

[1191] The above outlines the specific processing steps of the system.

[1192] (Application Example 2)

[1193] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[1194] In modern industrial environments, there is a need to optimize the efficiency of factory robots and workers while also enabling flexible responses that take into account the emotional state of workers. However, there is no system that comprehensively understands the operating status and error information of factory robots along with the emotional state of workers and takes immediate, appropriate action. As a result, the risk of decreased efficiency and deterioration in work quality is increasing.

[1195] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for receiving the content of a problem input by the user, means for analyzing and classifying the content of the problem using generative artificial intelligence, means for generating optimal advice based on the classified problem, means for presenting the generated advice to the user, means for selecting companies and services necessary to solve the problem, means for presenting the selected companies and services to the user, means for receiving the user's selection results and transmitting user information to the selected companies, means for collecting and managing referral fees, means for collecting operational data from industrial machinery, means for collecting and analyzing worker emotion data, means for generating and presenting advice regarding the operation of industrial machinery based on the analysis results, and means for connecting to external technical support services as needed. This makes it possible to comprehensively manage the status of both factory robots and workers and to take appropriate action immediately.

[1196] A "user" is someone who works in a factory or someone who uses the system to input data about their worries and emotions.

[1197] "Generative artificial intelligence" is an artificial intelligence technology that analyzes and classifies input data and generates optimal advice.

[1198] "Problems" refer to the issues and challenges that users face, and are information provided to the system through input.

[1199] "Advice" refers to guidelines for solutions and improvements generated by generative artificial intelligence based on the analysis results.

[1200] "Industrial machinery" is a general term for robots and production equipment used in factories, and is the subject of operational data collection.

[1201] "Operational data" refers to data related to the operating status of industrial machinery, such as operating hours and error codes.

[1202] "Emotional data" refers to data about a user's emotional state, including information such as stress levels and fatigue levels.

[1203] A "server" is a central information processing device that performs tasks such as data analysis, advice generation, and selection of companies and services.

[1204] "Means" refers to the specific methods or devices used to realize each function of the system.

[1205] "External technical support services" refer to external companies or experts that provide problem-solving and technical support within the factory.

[1206] Modes for carrying out the invention

[1207] Basic System Configuration

[1208] The system that implements this application consists of the following main components.

[1209] 1. Terminal: A device that provides an interface for users to input data about their worries and emotions. Specifically, this includes tablet devices and smart glasses.

[1210] 2. Server: This is the central system that analyzes problems, recognizes emotions, generates advice, and selects companies and services. It is equipped with a database, generative artificial intelligence (AI), and an emotion engine.

[1211] 3. Industrial machinery: These are robots and production equipment used in factories, and are the subjects of operational data collection.

[1212] System operation

[1213] Data collection

[1214] The device collects data on worries and emotions entered by the user. This emotional data is entered by the user using a tablet or smart glasses. For example, the user receives the following prompt: "Please enter your current stress level on a scale of 1 to 5, with 1 being the lowest and 5 being the highest." The collected data is sent to the server.

[1215] Industrial machinery is equipped with operational sensors that collect operational data such as operating time, temperature, and error codes. This data is also periodically transmitted to a server.

[1216] Data Analysis

[1217] The server receives collected data on worries, emotions, and operational data. Generative artificial intelligence (using TensorFlow) analyzes the text data and classifies the worries. Simultaneously, an emotion engine analyzes the emotion data and recognizes the user's mental state and emotions.

[1218] Generating advice

[1219] Based on the analysis results and sentiment analysis results, the server generates advice on how to resolve problems and errors in industrial machinery. This advice is customized to the specific situation of the user and the industrial machinery. For example, it might generate specific advice such as, "The machine temperature is high. Please check the cooling system. Also, the worker's stress level is high. We recommend taking a break."

[1220] Providing advice and connecting

[1221] The terminal displays the generated advice to the user. Furthermore, if necessary, the server seamlessly connects with external technical support services to provide real-time support.

[1222] Hardware and software to use

[1223] Hardware:

[1224] Industrial machinery (with operation data collection sensors)

[1225] Tablet devices and smart glasses (for inputting emotional data)

[1226] software:

[1227] Python: Data Analysis and AI Model Building

[1228] TensorFlow: Implementing Generative Artificial Intelligence and Emotion Engines

[1229] MySQL: Storing and managing collected data

[1230] REST API: Data reception and transmission interface

[1231] Flask: Server construction and API development

[1232] Specific example

[1233] User A is working in a factory and inputs emotional data into a tablet device. For example, in response to the prompt, "Please enter your current stress level on a scale of 1 to 5. 1 is the lowest, and 5 is the highest," User A enters 3. The device sends this data to a server, which analyzes it and generates advice. Next, the advice is sent to the device, displaying to User A, "Your current stress level is high, so we recommend taking a break. Also, the machine temperature is high, so please check the cooling system." Furthermore, if necessary, the system can connect to external technical support services for additional assistance.

[1234] This system will improve efficiency within the factory and allow for flexible responses that take into account the health of the workers.

[1235] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1236] Step 1:

[1237] The user accesses the device and inputs emotional data. Specifically, the user receives a prompt message, "Please enter your current stress level on a scale of 1 to 5. 1 is the lowest, and 5 is the highest," and enters their stress level. The stress level (e.g., 3) is collected as input data.

[1238] Step 2:

[1239] The device sends collected emotional data to the server. The device converts the stress level value (e.g., 3) into JSON format and transfers it to the server via a REST API. The input is the user's emotional data, and the output is the data transmission to the server.

[1240] Step 3:

[1241] Industrial machinery collects operational data and sends it to a server. This operational data includes operating time, temperature, and error codes. For example, data might be collected showing an operating time of 500 minutes, a temperature of 75 degrees, and an error code of 0.

[1242] Step 4:

[1243] The server receives the collected sentiment and operational data and stores it in a database. The server uses MySQL to store the sentiment and operational data. Specific data inserted into the database includes stress levels, uptime, temperature, and error codes.

[1244] Step 5:

[1245] The server uses generative artificial intelligence to analyze emotional and operational data. During the analysis, the emotional engine assesses the user's stress level, and the generative AI model (using TensorFlow) comprehensively analyzes the operational and emotional data. As a result of the analysis, factors contributing to decreased work efficiency and machine error situations are identified.

[1246] Step 6:

[1247] The server generates advice based on the analysis results. The generated advice is specific, such as, "The machine temperature is high, please check the cooling system. Also, the worker's stress level is high; we recommend taking a break." The input is the analysis results, and the output is the generated advice.

[1248] Step 7:

[1249] The server sends the generated advice to the terminal. The server converts the generated advice into JSON format and sends it to the terminal via a REST API. The input is the generated advice, and the output is the data sent to the terminal.

[1250] Step 8:

[1251] The terminal displays advice to the user. For example, the tablet screen might display, "The machine temperature is high; please check the cooling system. Also, the worker's stress level is high; a break is recommended." The input is the advice received from the server, and the output is what is displayed to the user.

[1252] Step 9:

[1253] The server connects to an external technical support service as needed. If the user requests additional support, the server sends the user's status and the required support details to the external technical support service. This provides real-time technical support. The input is the user's support request, and the output is the connection to the external technical support service.

[1254] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1255] The data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One 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">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1256] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1257] [Third Embodiment]

[1258] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1259] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1260] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1261] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[1262] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1263] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1264] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1265] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1266] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1267] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1268] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1269] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1270] This invention provides a system for receiving and analyzing users' problems, providing appropriate advice, and seamlessly connecting them to the companies and services necessary for resolving those problems. Specific embodiments for carrying out this invention are described below.

[1271] 1. Basic System Configuration

[1272] This system consists of the following main components:

[1273] Terminal: A device that provides an interface for users to input their concerns.

[1274] Server: The central system that analyzes and classifies problems, generates advice, and selects companies and services.

[1275] Generative artificial intelligence: AI models for analyzing problems and generating advice.

[1276] Database: Stores information about companies and services and uses it for selection.

[1277] 2. System Operation

[1278] Receiving and analyzing problems

[1279] 1. The user accesses the device and enters their problem in text format.

[1280] 2. The terminal receives the entered content of the problem and sends the data to the server.

[1281] 3. The server passes the received data to a generative artificial intelligence (AI) for analysis. The generative AI extracts keywords from the text and performs sentiment analysis to analyze the content of the problem in detail.

[1282] 4. Based on the analysis results, the server classifies the problems into specific categories (e.g., inheritance, childcare, health issues, etc.).

[1283] Providing advice

[1284] 5. Based on the analysis results, the server selects an advice template appropriate to the category of the problem. Furthermore, it uses generative artificial intelligence to generate customized advice tailored to the user's specific problem.

[1285] 6. Once the server has finished generating the advice, it sends the generated results to the terminal.

[1286] 7. The device displays the received advice to the user. This allows the user to obtain guidance for specific solutions.

[1287] Proposal of solutions and connection

[1288] 8. The server accesses the database and selects relevant companies and services based on the analyzed problem category. For example, in the case of inheritance, it retrieves a list of reliable tax accounting firms.

[1289] 9. The server sends a list of selected companies and services to the terminal.

[1290] 10. The device displays a list of relevant companies and services to the user. The user can select the desired company or service from the list.

[1291] 11. When a user selects a company or service, the device sends the selection to the server.

[1292] 12. The server sends user information to the selected company and performs the matching process.

[1293] Crowdfunding proposal (optional)

[1294] 13. The server will suggest an appropriate crowdfunding platform if funding is needed to solve the user's problem.

[1295] 14. The server sends information from the crowdfunding platform to the device.

[1296] 15. The device displays crowdfunding platform proposals to the user, allowing them to receive further support as needed.

[1297] Management of referral fees

[1298] 16. The server operates a system to collect referral fees from partner companies when a match is successfully made with selected companies or services. The management and billing process for referral fees is entrusted to a dedicated management system.

[1299] Specific example

[1300] For example, if user A has concerns about inheritance, it would look like this:

[1301] 1. User A enters "I'm worried about inheritance" into the portal site.

[1302] 2. The terminal sends the input content to the server.

[1303] 3. The server uses generative artificial intelligence to analyze the text and categorize it under the "inheritance" category.

[1304] 4. The server generates advice regarding inheritance and sends it to the terminal.

[1305] 5. The device displays advice to user A (e.g., "Regarding inheritance procedures").

[1306] 6. The server selects a list of trusted tax accounting firms from its database and sends it to the terminal.

[1307] 7. The terminal displays the list to user A.

[1308] 8. User A selects a specific tax accounting firm.

[1309] 9. The terminal sends the selection result to the server.

[1310] 10. The server sends User A's information to the selected tax accounting firm and performs the matching process.

[1311] 11. The server collects referral fees from the tax accounting firm and records them in the management system.

[1312] In this way, the present invention provides a system for efficiently and effectively solving users' problems, and means for implementing the same.

[1313] The following describes the processing flow.

[1314] Step 1:

[1315] The user accesses the portal site using their device and enters the details of their problem as text.

[1316] Step 2:

[1317] The terminal receives user input and sends that information to the server.

[1318] Step 3:

[1319] The server receives text data about the problem and passes it to a generative artificial intelligence for analysis.

[1320] Step 4:

[1321] The generative artificial intelligence on the server analyzes the text, extracting keywords and performing sentiment analysis.

[1322] Step 5:

[1323] The server uses the analysis results to classify the problems into specific categories (e.g., inheritance, childcare, health issues, etc.).

[1324] Step 6:

[1325] Based on the analysis results, the server selects an advice template corresponding to the problem category.

[1326] Step 7:

[1327] The server uses generative artificial intelligence to generate customized advice tailored to the user's specific concerns.

[1328] Step 8:

[1329] The server sends the generated advice to the terminal.

[1330] Step 9:

[1331] The device displays generated advice to the user.

[1332] Step 10:

[1333] Based on the analysis results, the server selects companies and services from its database that are suitable for solving the problem.

[1334] Step 11:

[1335] The server generates a list of selected companies and services and sends it to the terminal.

[1336] Step 12:

[1337] The device displays a list of companies and services related to the user.

[1338] Step 13:

[1339] Users select companies or services that interest them from a presented list.

[1340] Step 14:

[1341] The terminal sends the user's selection results to the server.

[1342] Step 15:

[1343] The server sends user information to the selected companies based on the user's selection results.

[1344] Step 16:

[1345] The server waits for a response from the selected company, and if the matching is successful, it sends the result to the terminal.

[1346] Step 17:

[1347] The device notifies the user of the matching result.

[1348] Step 18:

[1349] Users will contact the selected companies and services directly and proceed with specific procedures to resolve their issues.

[1350] Step 19:

[1351] Once the server completes the matching process, it manages the referral fees from partner companies and initiates the billing process.

[1352] Step 20:

[1353] The server receives the referral fee and records it in the management system.

[1354] Step 21:

[1355] In some cases, the server will send appropriate platform information to the terminal to suggest a crowdfunding platform.

[1356] Step 22:

[1357] The device displays crowdfunding platform proposals to the user.

[1358] Step 23:

[1359] Users can utilize crowdfunding platforms as needed to receive further support.

[1360] (Example 1)

[1361] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1362] In modern society, individuals face a wide variety of problems and challenges, often requiring specialized knowledge and support to resolve. However, selecting the right company or service, and receiving prompt and accurate advice, is difficult. Existing systems require users to gather information and perform the necessary procedures themselves, which consumes considerable time and effort. Furthermore, if appropriate experts or services cannot be found, the problem may worsen. Therefore, there is a need for efficient and effective means to resolve users' problems.

[1363] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1364] In this invention, the server includes a device for receiving the content of a user's problem, a device for analyzing and classifying the content of the problem using generative artificial intelligence, a device for generating optimal advice based on the classified problem, a device for presenting the generated advice to the user, a device for selecting relevant businesses and services necessary for solving the problem, a device for presenting the selected businesses and services to the user, a device for receiving the user's selection results and transmitting user information to the selected businesses, and a device for collecting and managing referral fees. As a result, the user can efficiently analyze their problem, receive appropriate advice, quickly connect to the necessary businesses and services, and obtain support for problem solving.

[1365] A "user" refers to an individual who attempts to solve their own problems using this system.

[1366] A "device" refers to a device that provides an interface for users to input their concerns. Specifically, this includes computers, smartphones, tablets, and so on.

[1367] A "server" refers to a central computer system that analyzes, classifies, and provides advice on problems, as well as selecting and matching relevant businesses and services.

[1368] "Generative artificial intelligence" refers to an AI model that analyzes input text data, extracts keywords, and performs sentiment analysis to understand the user's concerns in detail and generate appropriate advice.

[1369] "Analyzing" refers to using generative artificial intelligence to extract keywords and perform sentiment analysis on input data, thereby gaining a detailed understanding of its content.

[1370] "Classifying" refers to categorizing users' concerns into specific categories (e.g., inheritance, childcare, health issues, etc.) based on the analysis results.

[1371] "Generating advice" refers to using generative artificial intelligence based on category-specific templates to create customized solutions or guidelines for a user's specific problems.

[1372] "Presenting" refers to displaying generated advice and information about related businesses and services to the user.

[1373] "Selecting" refers to extracting and choosing relevant businesses and services from a database based on the analyzed categories of problems.

[1374] "Transmitting user information" refers to sending necessary user information via the network to the business entity or service selected by the user.

[1375] A "business entity" refers to an organization or company that provides the specialized knowledge and services necessary to solve a problem.

[1376] "Referral fee" refers to the commission collected from a partnering business when a user and business are successfully matched.

[1377] A "crowdfunding platform" refers to a service that allows users to raise funds online to solve their problems.

[1378] This invention provides a system for receiving and analyzing users' problems, offering appropriate advice, and seamlessly connecting them to the necessary companies and services for resolving those problems. This system consists of the following main components:

[1379] 1. Terminal: A device that provides an interface for users to input their problems. Specifically, this includes computers, smartphones, and tablets. Users input their problems in text format via the terminal.

[1380] 2. Server: This is the central system that analyzes, classifies, and provides advice on problems, as well as selecting and matching relevant businesses and services. Specifically, generative artificial intelligence (e.g., GPT-3) is used as the software, and it is executed within the server to perform data analysis and advice generation.

[1381] 3. Generative Artificial Intelligence: This AI model analyzes text data entered by the user, extracts keywords, and performs sentiment analysis to understand the user's concerns in detail and generate appropriate advice. This AI model heavily relies on the analysis of text data and the generation of advice.

[1382] 4. Database: Used to store information about companies and services, and to search for and select appropriate businesses and services that meet users' needs. Detailed information about businesses and services is registered within the database.

[1383] System operation details

[1384] Receiving and analyzing problems

[1385] When a user enters their problem into their device, the device sends that text data to a server via an HTTP request. The server then passes the received data to a generative artificial intelligence (AI). This AI extracts keywords and performs sentiment analysis based on the input text data, providing a detailed analysis of the user's problem.

[1386] Generating and providing advice

[1387] The server categorizes the user's concerns into specific categories based on the analysis results from the generative artificial intelligence. It then selects an advice template corresponding to the category and uses the generative artificial intelligence again to generate customized advice tailored to the user's specific concerns. The generated advice is sent from the server to the terminal and displayed to the user.

[1388] Selection of companies and services

[1389] The server selects relevant businesses and services based on the problem categories analyzed from the database. This selection is sent to the terminal as a list of businesses and services and displayed to the user. The user can then select their desired business or service from the displayed list.

[1390] User information submission and matching

[1391] When a user selects their desired business entity or service, the selection is sent from the terminal to the server. The server then sends the user information to the selected business entity and performs a matching process. This allows the user to quickly access the appropriate service.

[1392] Specific example

[1393] For example, if user A has concerns about inheritance, it would look like this:

[1394] 1. User A enters "I'm worried about inheritance" into the terminal.

[1395] 2. The device sends the text data to the server.

[1396] 3. The server uses generative artificial intelligence to analyze the text and categorize it under the "inheritance" category.

[1397] 4. The server generates advice regarding inheritance and sends it to the terminal.

[1398] 5. The device displays advice to user A (e.g., "Regarding inheritance procedures").

[1399] 6. The server selects a trusted expert from the database and sends the list to the terminal.

[1400] 7. The terminal displays the list to user A.

[1401] 8. User A selects a specific expert.

[1402] 9. The terminal sends the selection result to the server.

[1403] 10. The server sends User A's information to the selected expert and performs the matching process.

[1404] In this way, the present invention provides a system and means for implementing it that efficiently and effectively solves users' problems.

[1405] Example of a prompt

[1406] An example of a prompt message might read: "Please enter your problem in text format and send it to the server. The server will pass the text data to a generative artificial intelligence system that will analyze and classify your problem. It will then provide appropriate advice and a list of relevant businesses and services."

[1407] This system is a powerful tool for efficiently analyzing users' problems and providing quick and appropriate solutions.

[1408] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1409] Step 1:

[1410] The user enters their problem in text format into the device.

[1411] Input: Text data of the user's problem

[1412] Output: Text data received by the terminal

[1413] Users access the input interface of a portal site or application and describe their problems in detail. This text data is received by the device.

[1414] Step 2:

[1415] The terminal sends the entered text data about the problem to the server.

[1416] Input: Text data received on the device

[1417] Output: Text data transferred to the server

[1418] The terminal receives text data and sends it to the server via a communication method such as an HTTP request. HTTPS is the recommended communication protocol.

[1419] Step 3:

[1420] The server receives text data and passes it to a generative artificial intelligence for analysis.

[1421] Input: Text data transferred to the server

[1422] Output: Analyzed problem data (keywords, emotions, categories)

[1423] The server passes text data to a generative artificial intelligence (e.g., GPT-3). The generative AI extracts keywords from the text and performs sentiment analysis to analyze the content of the problem. As a result, the category and keywords of the problem are extracted.

[1424] Step 4:

[1425] The server categorizes the problems based on the analysis results.

[1426] Input: Analyzed problem data

[1427] Output: Categorized problem data

[1428] The server uses the analysis results from the generative artificial intelligence to classify the problems into specific categories. For example, it might categorize them into "inheritance," "childcare," or "health problems."

[1429] Step 5:

[1430] The server selects an advice template based on the category and uses generative artificial intelligence to generate customized advice.

[1431] Input: Categorized problem data

[1432] Output: Customized advice data

[1433] The server selects a pre-prepared advice template and uses generative artificial intelligence to customize the advice to address the user's specific concerns. The generated advice is output in text format.

[1434] Step 6:

[1435] The server sends the generated advice data to the terminal.

[1436] Input: Customized advice data

[1437] Output: Advice data transferred to the terminal

[1438] The server sends the generated advice data back to the terminal via an HTTP request. HTTPS is recommended to ensure the reliability of the communication.

[1439] Step 7:

[1440] The device displays the advice it has received to the user.

[1441] Input: Advice data transferred to the device

[1442] Output: Advice displayed to the user

[1443] The device displays the received advice data in a user-friendly format, allowing the user to obtain concrete guidance for solutions.

[1444] Step 8:

[1445] The server accesses the database and selects the relevant entities and services.

[1446] Input: Categorized problem data

[1447] Output: List of selected entities and services

[1448] Based on the analyzed problem categories, the server selects relevant businesses and services from the database. This results in a list of the businesses and services best suited to the user's problem.

[1449] Step 9:

[1450] The server sends a list of selected entities and services to the terminal.

[1451] Input: List of selected entities or services

[1452] Output: List of entities and services transferred to the terminal

[1453] The server sends a list of selected entities and services to the terminal. This is also done via an HTTP request.

[1454] Step 10:

[1455] The device displays a list of businesses and services associated with the device to the user.

[1456] Input: List of entities and services transferred to the terminal

[1457] Output: A list of entities and services displayed to the user.

[1458] The terminal displays a list of received entities and services to the user. The user can select the desired entity or service from this list.

[1459] Step 11:

[1460] When a user selects a company or service, the device sends that selection to the server.

[1461] Input: Information about the business entity or service selected by the user.

[1462] Output: Selection results sent to the server

[1463] When a user selects a specific business entity or service, the selection result is sent from the terminal to the server.

[1464] Step 12:

[1465] The server sends user information to the selected business entity and performs the matching process.

[1466] Input: Selection results sent to the server

[1467] Output: User information sent to the selected entity

[1468] The server sends user information to the selected business entity and performs a matching process. This allows users to quickly receive the support they need.

[1469] Step 13 (Optional):

[1470] The server sends information from the crowdfunding platform to the device.

[1471] Input: Problem data indicating that a crowdfunding proposal is deemed necessary.

[1472] Output: Information about the crowdfunding platform sent to the device.

[1473] In some cases, the server may determine that the user needs funding to solve their problem and send information about an appropriate crowdfunding platform.

[1474] Step 14 (Optional):

[1475] The device displays crowdfunding platform proposals to the user.

[1476] Input: Information from the crowdfunding platform sent to the device.

[1477] Output: Information about the crowdfunding platform displayed to the user.

[1478] The device displays project information from crowdfunding platforms to the user. The user can then receive further funding as needed.

[1479] Step 15:

[1480] The server collects and manages referral fees.

[1481] Input: Information on businesses and users that have been successfully matched.

[1482] Output: Collected referral fees and records in the management system

[1483] When a match is successful, the server collects a referral fee from the partner company and records it in a dedicated management system. This process is automated and functions as part of the revenue model.

[1484] (Application Example 1)

[1485] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1486] Traditional problem-solving systems have a problem in that they cannot quickly provide appropriate advice or relevant store information to users who are having trouble choosing products in a physical store. Therefore, users have to search for information and find solutions themselves, which is time-consuming and requires effort. Furthermore, the system in question is required not only to analyze the user's problem and present a suitable solution, but also to provide users with a way to quickly and effectively resolve their problem in a physical store.

[1487] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1488] In this invention, the server includes means for receiving the content of a user's problem, means for analyzing and classifying the content of the problem using generative artificial intelligence, means for generating optimal advice based on the classified problem, means for presenting the generated advice to the user, means for selecting companies and services necessary to solve the problem, means for presenting the selected companies and services to the user, means for receiving the user's selection results and transmitting user information to the selected companies, means for collecting and managing referral fees, means for providing information on relevant stores to resolve difficulties when the user is having trouble choosing a product, means for presenting information on the relevant stores to the user, and means for accessing a database for providing information on the stores. As a result, when a user is having trouble choosing a product in a physical store, they can use their smartphone to input their problem, and the system will analyze the problem and quickly provide appropriate solutions and information on relevant stores.

[1489] Definitions of important words

[1490] "A means of receiving user input about their concerns" refers to a function that allows users to input their concerns in text format using a specific device, and for the system to receive that input.

[1491] "Means for analyzing and classifying the content of the aforementioned problems using generative artificial intelligence" refers to a system that uses a generative AI model to extract keywords and perform sentiment analysis from input text data, and has the function of classifying the content of the problems into specific categories.

[1492] "Means for generating optimal advice based on the classified problems" refers to a function that generates advice best suited to solving the user's problems based on the analyzed and classified data.

[1493] "Means for presenting the generated advice to the user" refers to a means that has the function of displaying the generated advice on a device accessible to the user.

[1494] "Means for selecting companies and services necessary to solve the aforementioned problems" refers to a function that searches a database for and selects companies and services suitable for solving the user's problems.

[1495] "Means for presenting the selected companies and services to the user" refers to a function that displays a list of selected companies and services on the user's device.

[1496] "Means for receiving user selection results and transmitting user information to selected companies" refers to a system that receives company information selected by the user and transmits the user's information to the selected companies.

[1497] "Means for collecting and managing referral fees" refers to a system that collects referral fees from companies when a match is successful and manages those fees.

[1498] "A means of providing information on relevant stores to resolve difficulties when a user has trouble choosing a product" refers to a function that provides information on suitable stores to resolve difficulties a user encounters when choosing a product.

[1499] "Means for presenting information about the relevant stores to the user" refers to a means that has the function of displaying information about the relevant stores on the user's device.

[1500] "Means for accessing a database to provide information about the store" refers to a means that has the function of accessing a database and obtaining information in order to provide information about the relevant store.

[1501] Modes for carrying out the invention

[1502] This invention provides a system that allows users to input their concerns using their smartphone when they are having trouble choosing products in a physical store. The system then analyzes these concerns and quickly provides appropriate solutions and information about relevant stores. The following describes in detail specific embodiments for carrying out this invention.

[1503] 1. Basic System Configuration

[1504] This system consists of the following main components:

[1505] Device: A smartphone that provides an interface for users to input their problems or concerns.

[1506] Server: The central system that analyzes and classifies problems, generates advice, and selects companies and services.

[1507] Generative artificial intelligence (AI model): An AI model designed to analyze problems and generate advice.

[1508] Database: Stores information about companies and related stores, and uses it for selection.

[1509] 2. System Operation

[1510] Receiving and analyzing problems

[1511] 1. The user uses their smartphone to enter a specific problem in text format. For example, they might type, "I don't know what to get my child for their birthday."

[1512] 2. The terminal receives the entered content of the problem and sends the data to the server.

[1513] 3. The server passes the received data to a generative artificial intelligence (e.g., OpenAI's GPT-4) for analysis. The AI ​​model extracts keywords from the text and performs sentiment analysis to analyze the content of the problem in detail.

[1514] 4. Based on the analysis results, the server classifies the problem into a specific category (e.g., birthday present).

[1515] Providing advice

[1516] 5. Based on the analysis results, the server selects an advice template appropriate to the category of the problem. Furthermore, it uses generative artificial intelligence to generate customized advice tailored to the user's specific problem.

[1517] 6. Once the server has finished generating the advice, it sends the generated results to the terminal.

[1518] 7. The device displays the received advice to the user. For example, it might display specific advice such as, "Toys, books, and games are suitable as birthday presents."

[1519] Providing store information

[1520] 8. The server accesses the database and selects relevant stores based on the analyzed problem categories. For example, it retrieves lists such as "toy stores" and "bookstores."

[1521] 9. The server sends a list of selected stores to the terminal.

[1522] 10. The terminal displays a list of relevant stores to the user. The user can select their desired store from the list.

[1523] 11. When a user selects a specific store, detailed information about that store (e.g., address, contact information, business hours) is displayed.

[1524] Crowdfunding proposal (optional)

[1525] 12. The server will suggest an appropriate crowdfunding platform if funding is needed to solve the user's problem.

[1526] 13. The server sends information from the crowdfunding platform to the device.

[1527] 14. The device displays crowdfunding platform proposals to the user, allowing them to receive further support as needed.

[1528] This system allows users to quickly obtain specific advice and relevant store information to effectively resolve the difficulties they face when choosing products in physical stores. An example of a prompt message is, "I don't know what would be a good birthday present for my child."

[1529] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1530] Program processing steps

[1531] Step 1:

[1532] The user enters their problem in text format using their smartphone.

[1533] Input: The user enters "I don't know what would be a good birthday present for my child" into a smartphone application.

[1534] Specific action: The user enters their problem into a text box and presses the "Submit" button.

[1535] Step 2:

[1536] The terminal receives the entered problem details and sends the data to the server.

[1537] Input: Text data entered by the user.

[1538] Data processing: The terminal converts the text data into JSON format and sends it to the server.

[1539] Output: Input data in JSON format is sent to the server.

[1540] Specific operation: The terminal formats the text data into JSON format and sends an HTTP request to the server's API endpoint.

[1541] Step 3:

[1542] The server passes the received data to a generative artificial intelligence for analysis. The AI ​​model extracts keywords from the text and performs sentiment analysis to analyze the content of the problem in detail.

[1543] Input: Input data in JSON format.

[1544] Data processing: An AI model (e.g., GPT-4) extracts keywords from text, performs sentiment analysis, and categorizes the data.

[1545] Output: The analysis results (categories and keywords) are returned to the server.

[1546] Specific operation: The server sends an API request to the AI ​​model, the model performs text analysis, and returns the analysis results to the server.

[1547] Step 4:

[1548] Based on the analysis results, the server categorizes the problem into a specific category (e.g., birthday present).

[1549] Input: Analysis results returned from the AI ​​model.

[1550] Data processing: Based on the analysis results, the data is classified into specific categories.

[1551] Output: Classified data is generated.

[1552] Specific operation: The server compares the analysis results with a preset category list to identify the corresponding category.

[1553] Step 5:

[1554] Based on the analysis results, the server selects an advice template appropriate to the problem category and uses generative artificial intelligence to generate personalized advice for the user.

[1555] Input: Categorized data and advice templates.

[1556] Data processing: AI models generate customized advice.

[1557] Output: Customized advice.

[1558] Specific operation: The server passes an advice template to the AI ​​model, which then generates advice that customizes the template based on categorical data.

[1559] Step 6:

[1560] Once the server has finished generating the advice, it sends the results to the terminal.

[1561] Input: Generated advice data.

[1562] Data processing: Convert the advice data to JSON format.

[1563] Output: Advice data in JSON format is sent to the terminal.

[1564] Specific operation: The server formats the generated advice into JSON format and sends an HTTP request to the terminal's API endpoint.

[1565] Step 7:

[1566] The device displays the received advice to the user.

[1567] Input: Advice data in JSON format received from the server.

[1568] Output: Advice displayed to the user.

[1569] Specific operation: The terminal parses the JSON data and displays advice in the user interface.

[1570] Step 8:

[1571] The server accesses the database and selects relevant stores based on the analyzed problem categories.

[1572] Input: Classified category data.

[1573] Data processing: Based on category data, relevant store information is searched and retrieved from the database.

[1574] Output: List of store information.

[1575] Specific operation: The server sends category data as a query to the database and retrieves related store information.

[1576] Step 9:

[1577] The server sends a list of selected stores to the terminal.

[1578] Input: List of store information.

[1579] Data processing: Convert store information to JSON format.

[1580] Output: A list of stores in JSON format is sent to the terminal.

[1581] Specific operation: The server formats the store information in JSON format and sends an HTTP request to the terminal's API endpoint.

[1582] Step 10:

[1583] The terminal displays a list of relevant stores to the user.

[1584] Input: A list of stores in JSON format received from the server.

[1585] Output: A list of stores displayed to the user.

[1586] Specific operation: The terminal parses the JSON data and displays the store information as a list in the user interface.

[1587] Step 11:

[1588] When a user selects a specific store, detailed information about that store is displayed.

[1589] Input: User's store selection action.

[1590] Output: Detailed information about the selected store.

[1591] Specific action: The device displays detailed information about the selected store (e.g., address, contact information, business hours).

[1592] Step 12:

[1593] The server will, in some cases, suggest an appropriate crowdfunding platform when funding is needed to solve a user's problem.

[1594] Input: User's problem and analysis results.

[1595] Data processing: AI analysis to propose crowdfunding platforms.

[1596] Output: Proposal for a crowdfunding platform.

[1597] Specific operation: The server proposes a crowdfunding campaign based on the analysis results and sends it to the terminal.

[1598] Step 13:

[1599] The device displays proposals from crowdfunding platforms to the user, allowing them to receive further support as needed.

[1600] Input: Crowdfunding proposal information received from the server.

[1601] Output: Crowdfunding information displayed to the user.

[1602] Specific action: The device displays crowdfunding proposals it has received in the user interface.

[1603] Through these steps, users can use their smartphones to get quick and effective advice and relevant store information when they have trouble choosing products in a physical store.

[1604] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1605] This invention provides a system that receives and analyzes users' concerns, provides appropriate advice, and seamlessly connects them to the necessary companies and services for resolution, in addition to an emotion engine that recognizes the user's emotions. Specific embodiments for carrying out this invention will be described below.

[1606] Basic System Configuration

[1607] This system consists of the following main components:

[1608] Terminal: A device that provides an interface for users to input their concerns.

[1609] Server: The central system that analyzes problems, recognizes emotions, generates advice, and selects companies and services.

[1610] Generative artificial intelligence: AI models for analyzing problems and generating advice.

[1611] Emotion engine: A system that recognizes and analyzes emotions from text entered by the user.

[1612] Database: Stores information about companies and services and uses it for selection.

[1613] System operation

[1614] Receiving and analyzing problems

[1615] 1. The user accesses the device and enters their problem in text format.

[1616] 2. The terminal receives the entered content of the problem and sends the data to the server.

[1617] 3. The server passes the received data to the generative artificial intelligence and the emotion engine for analysis. The generative artificial intelligence extracts keywords from the text and performs emotion analysis to analyze the content of the problem in detail.

[1618] 4. The emotion engine on the server determines the emotional state from the user's input and feeds the result back to the generative artificial intelligence.

[1619] 5. The server classifies the problem into a specific category (e.g., inheritance, childcare, health issues, etc.) based on the analysis results and sentiment analysis results.

[1620] Providing advice

[1621] 6. Based on the analysis results, the server selects an advice template appropriate to the category of the problem. Furthermore, it uses generative artificial intelligence to generate customized advice that is tailored to the user's specific problem and emotional state.

[1622] 7. The server sends the generated advice to the terminal.

[1623] 8. The device displays generated advice to the user. This allows the user to receive guidance on solutions that take their emotional state into consideration.

[1624] Proposal of solutions and connection

[1625] 9. Based on the analysis results, the server selects companies and services from the database that are suitable for solving the problem. The results of the sentiment analysis are also taken into consideration in the selection process.

[1626] 10. The server generates a list of selected companies and services and sends it to the terminal.

[1627] 11. The device displays a list of companies and services related to the user.

[1628] 12. The user selects companies or services of interest from the presented list.

[1629] 13. The terminal sends the user's selection results to the server.

[1630] 14. The server sends user information to the selected companies based on the user's selection results.

[1631] Crowdfunding proposal (optional)

[1632] 15. The server will suggest an appropriate crowdfunding platform if, in some cases, funding is needed to solve the user's problem.

[1633] 16. The server sends information from the crowdfunding platform to the device.

[1634] 17. The device displays crowdfunding platform proposals to the user, allowing them to receive further support as needed.

[1635] Management of referral fees

[1636] 18. The server operates a system to collect referral fees from partner companies when a match is successfully made with selected companies or services. The management and billing process for referral fees is entrusted to a dedicated management system.

[1637] Specific example

[1638] For example, if user B has concerns about childcare, it would look like this:

[1639] 1. User B enters their "childcare concerns" into the portal site.

[1640] 2. The terminal sends the input content to the server.

[1641] 3. The server uses generative artificial intelligence and an emotion engine to analyze the text and classify it into the "childcare" category. At the same time, the emotion engine recognizes user B's mental state and emotions.

[1642] 4. The server generates advice and creates customized advice that takes sentiment analysis results into account.

[1643] 5. The server sends the generated advice to the terminal, which then displays it to user B (e.g., "How to manage stress in childcare").

[1644] 6. The server selects suitable childcare support companies and services from the database and sends the list to the terminal.

[1645] 7. The device displays a list to User B, and User B selects a specific childcare support service.

[1646] 8. The device sends the selection results to the server.

[1647] 9. The server sends User B's information to the selected childcare support service and performs the matching process.

[1648] 10. The server collects referral fees from childcare support services and records them in the management system.

[1649] In this way, the present invention realizes a system that analyzes user concerns, including their emotions, provides solutions, and seamlessly connects to businesses and services.

[1650] The following describes the processing flow.

[1651] Step 1:

[1652] The user accesses the portal site using their device and enters the details of their problem as text.

[1653] Step 2:

[1654] The terminal receives user input and sends that information to the server.

[1655] Step 3:

[1656] The server receives the text data of the problem and passes it to a generative artificial intelligence to begin analysis.

[1657] Step 4:

[1658] The server passes user input data to the emotion engine, which then recognizes the user's emotional state.

[1659] Step 5:

[1660] Generative artificial intelligence analyzes text data, extracting keywords and performing sentiment analysis. Simultaneously, a sentiment engine determines the user's emotional state.

[1661] Step 6:

[1662] The server collects analysis results from generative artificial intelligence and emotion engines, and classifies the problems into specific categories (e.g., inheritance, childcare, health issues, etc.).

[1663] Step 7:

[1664] The server selects an advice template that corresponds to the problem category.

[1665] Step 8:

[1666] The server uses generative artificial intelligence to generate customized advice based on the user's specific concerns and emotional state.

[1667] Step 9:

[1668] The server sends the generated advice to the terminal.

[1669] Step 10:

[1670] The device displays generated advice to the user. This provides the user with specific solutions that take their emotional state into consideration.

[1671] Step 11:

[1672] Based on the analysis results, the server selects companies and services from its database that are necessary to solve the problem. The results of the emotional analysis are also taken into consideration in the selection process.

[1673] Step 12:

[1674] The server generates a list of selected companies and services and sends it to the terminal.

[1675] Step 13:

[1676] The device displays a list of companies and services related to the user.

[1677] Step 14:

[1678] Users select companies or services that interest them from a presented list.

[1679] Step 15:

[1680] The terminal sends the user's selection results to the server.

[1681] Step 16:

[1682] The server sends user information to the selected companies based on the user's selection results.

[1683] Step 17:

[1684] The server waits for a response from the selected company, and if the matching is successful, it sends the result to the terminal.

[1685] Step 18:

[1686] The device notifies the user of the matching result.

[1687] Step 19:

[1688] Users will contact the selected companies and services directly and proceed with specific procedures to resolve their issues.

[1689] Step 20:

[1690] Once the server completes the matching process, it manages the referral fees from partner companies and initiates the billing process.

[1691] Step 21:

[1692] The server receives the referral fee and records it in the management system.

[1693] Step 22:

[1694] In some cases, the server will send appropriate platform information to the terminal to suggest a crowdfunding platform.

[1695] Step 23:

[1696] The device displays crowdfunding platform proposals to the user.

[1697] Step 24:

[1698] Users can utilize crowdfunding platforms as needed to receive further support.

[1699] (Example 2)

[1700] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1701] Conventional problem-solving support systems lacked the technology to appropriately recognize users' emotions and customize advice based on them. Furthermore, they lacked the functionality to seamlessly suggest and connect users with suitable services and companies. As a result, users often failed to alleviate stress or find appropriate services. This invention aims to solve these problems and provide users with a more effective means of resolving their problems.

[1702] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1703] In this invention, the server includes means for receiving the content of the user's problem, means for analyzing and classifying the content of the problem using generative artificial intelligence, and means for determining the user's emotional state from the user's input using an emotion analysis engine. This makes it possible to analyze the user's problem in detail and provide customized advice based on their emotional state. The server also includes means for generating optimal advice based on the classified problem, means for presenting the generated advice to the user, means for selecting the services necessary to solve the problem, means for presenting the selected services to the user, means for receiving the user's selection results and transmitting user information to the selected services, and means for collecting and managing referral fees. This enables efficient problem solving by providing the information and services necessary to solve the user's problem in a centralized manner.

[1704] A "user" refers to a person who accesses the system and inputs their own concerns or requests.

[1705] "Generative artificial intelligence" refers to artificial intelligence technology that analyzes text data entered by users and performs categorization and generates customized advice.

[1706] An "emotion analysis engine" refers to a system that identifies and analyzes emotional states from text data entered by users.

[1707] "Means for receiving the content of concerns" refers to a function that receives text data entered by the user and securely transmits it to the server.

[1708] "Methods for analyzing and classifying the content of problems" refers to a function that uses generative artificial intelligence to analyze text data of problems entered by users and classify it into specific categories.

[1709] "Means for determining emotional state" refers to a function that uses an emotion analysis engine to determine the user's emotional state from their text data.

[1710] "Means for generating optimal advice" refers to a function that generates customized advice based on analyzed concerns and emotional states.

[1711] "Means of providing advice to the user" refers to a function that sends the generated advice to the user's device and displays it.

[1712] "A means of selecting services necessary for solving a problem" refers to a function that selects services or companies suitable for solving a problem from a database based on the analysis results.

[1713] "Means of presenting services to users" refers to functions that transmit and display information about selected services and companies to the user's device.

[1714] "Means of sending user information to a service" refers to a function that sends user information to a selected service based on the user's choices.

[1715] "Means of collecting and managing referral fees" refers to the function of collecting and managing referral fees from partnered services when a match with a selected service is successful.

[1716] This invention is a system that receives and analyzes users' problems, provides appropriate advice, and seamlessly connects them to the services necessary for resolving those problems. Specific embodiments are described below.

[1717] Basic System Configuration

[1718] This system consists of the following main components:

[1719] Terminal: A device that provides an interface for users to input their concerns. Specifically, this includes personal computers and smartphones.

[1720] Server: The central system that analyzes problems, recognizes emotions, generates advice, and selects services.

[1721] Generative artificial intelligence: AI models used for analyzing problems and generating advice. Specifically, OpenAI's GPT-3 falls into this category.

[1722] Sentiment analysis engine: A system that recognizes and analyzes emotions from text entered by the user. IBM Watson is an example of this type of system.

[1723] Database: Stores service information and is used for selection. Specifically, this refers to Microsoft Azure SQL Database.

[1724] System Operation Description

[1725] 1. The user accesses the device and enters their problem in text format. At this time, they open a browser, access the system's website, and enter "I've been feeling stressed lately because of childcare" into the input form.

[1726] 2. The terminal receives the entered problem content and sends the data to the server. Specifically, a JavaScript function is called, and the text data is sent to the server via an HTTPS request.

[1727] 3. The server passes the received data to a generative artificial intelligence and an emotion analysis engine for analysis. The server is built with Python, and at this stage, it sends the data to OpenAI's GPT-3 and IBM Watson via API.

[1728] 4. The emotion analysis engine determines the emotional state from the user's input and feeds the result back to the generative artificial intelligence. The server receives the emotion analysis results returned from IBM Watson and applies that data to the GPT-3 model.

[1729] 5. The server classifies the problem into a specific category based on the analysis results and sentiment analysis results. For example, based on the keyword "childcare," an algorithm is run to classify the problem as being related to childcare.

[1730] 6. Based on the analysis results, the server selects an appropriate advice template and generates customized advice using generative artificial intelligence.

[1731] Examples of prompt statements:

[1732] User-entered text about their problem: 'I've been feeling stressed lately because of childcare. What should I do?'

[1733] Analyze the emotional state of this text and generate advice on managing parenting stress.

[1734] 7. The server sends the generated advice to the terminal, and the terminal displays the advice to the user. The received advice text is rendered into a specified HTML element on the web page.

[1735] 8. Based on the analysis results, the server selects a service suitable for solving the user's problem. Specifically, it uses SQL queries to search the database for services related to the user's problem.

[1736] 9. The server generates a list of selected services and sends it to the terminal. The list is serialized in JSON format and sent as an HTTPS response.

[1737] 10. The device displays a list of services relevant to the user, and the user selects a service of interest from the presented list.

[1738] 11. The terminal sends the user's selection to the server, and the server sends the user information to the selected service. An HTTP POST request containing the user information is sent to the API endpoint of the selected service.

[1739] 12. When a match is successfully made with a selected service, the server collects and manages a referral fee from the partnered service. The management and billing processes will use a dedicated management system.

[1740] As described above, the present invention is a system that efficiently solves users' problems by comprehensively analyzing their concerns and providing customized advice and suitable services.

[1741] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1742] Specific processing steps of the system

[1743] Step 1:

[1744] The user accesses the device and enters their problem in text format.

[1745] Input: User's problem text (e.g., "I've been feeling stressed lately because of childcare")

[1746] Specific actions: Open a browser, access the system's website, and enter text into the input form.

[1747] Output: Text data of the entered problem

[1748] Step 2:

[1749] The terminal receives the entered problem details and sends the data to the server.

[1750] Input: Text data of the problem

[1751] Specific operation: A JavaScript function is called, and text data is sent to the server via an HTTPS request.

[1752] Output: Text data of the problem sent to the server

[1753] Step 3:

[1754] The server passes the received data to a generative artificial intelligence and an emotion analysis engine for analysis.

[1755] Input: Text data of the problem sent to the server

[1756] Specific operation: The server is built in Python and sends data via API to generative artificial intelligence (e.g., OpenAI's GPT-3) and sentiment analysis engines (e.g., IBM Watson).

[1757] Output: Analysis results from generative artificial intelligence and emotion analysis engine

[1758] Step 4:

[1759] The emotion analysis engine identifies the user's emotional state from their input and feeds the results back to the generative artificial intelligence.

[1760] Input: User's text data

[1761] Specific operation: An emotion analysis engine (e.g., IBM Watson) analyzes text data and determines the emotional state.

[1762] Output: Emotion analysis results

[1763] Step 5:

[1764] The server categorizes the problem into a specific category based on the analysis results and emotion analysis results.

[1765] Input: Analysis results and sentiment analysis results

[1766] Specific operation: Perform category classification using a keyword extraction algorithm or machine learning model (e.g., keyword extraction using natural language processing techniques).

[1767] Output: Category classification results

[1768] Step 6:

[1769] Based on the analysis results, the server selects an appropriate advice template and generates customized advice using generative artificial intelligence.

[1770] Input: Category classification results, sentiment analysis results

[1771] Specific operation: The server retrieves the necessary templates from the database and generates prompts using generative artificial intelligence (e.g., OpenAI's GPT-3).

[1772] Examples of prompt statements:

[1773] User-entered text about their problem: 'I've been feeling stressed lately because of childcare. What should I do?'

[1774] Analyze the emotional state of this text and generate advice on managing parenting stress.

[1775] Output: Generated customization advice

[1776] Step 7:

[1777] The server sends the generated advice to the terminal, and the terminal displays the advice to the user.

[1778] Input: Generated customization advice

[1779] Specific operation: The generated advice text is returned to the device as an HTTPS response, and the device renders the received data on a web page (e.g., (Display text).

[1780] Output: Advice displayed to the user

[1781] Step 8:

[1782] Based on the analysis results, the server selects the service best suited to solving the problem.

[1783] Input: Analysis results and generated customized advice results

[1784] Specific operation: Use SQL queries to search the database for service information related to solving the problem.

[1785] Output: List of selected services

[1786] Step 9:

[1787] The server generates a list of selected services and sends it to the terminal.

[1788] Input: List of service information

[1789] Specific operation: Serialize the list into JSON format and send it as an HTTPS response.

[1790] Output: Service list sent to the terminal

[1791] Step 10:

[1792] The device displays a list of services relevant to the user, and the user selects a service of interest from the presented list.

[1793] Input: Service List

[1794] Specific operation: The received list data is placed on a specified HTML element on a web page (e.g., Render it to ) and allow the user to select it.

[1795] Output: User service selection

[1796] Step 11:

[1797] The terminal sends the user's selection results to the server, and the server sends the user information to the selected service.

[1798] Input: User's selection result

[1799] Specific operation: An HTTP request containing the user's selection information is sent to the server, and the server sends an HTTP POST request containing the user information to the API endpoint of the selected service.

[1800] Output: User information sent to the service

[1801] Step 12:

[1802] When a match is successfully made with a selected service, the server collects a referral fee from the partnered service and manages the transaction.

[1803] Input: Matching success information

[1804] Specific operation: Upon successful matching, an API call for referral fee billing is automatically made and recorded in the management system.

[1805] Output: Management information for collected referral fees

[1806] The above outlines the specific processing steps of the system.

[1807] (Application Example 2)

[1808] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1809] In modern industrial environments, there is a need to optimize the efficiency of factory robots and workers while also enabling flexible responses that take into account the emotional state of workers. However, there is no system that comprehensively understands the operating status and error information of factory robots along with the emotional state of workers and takes immediate, appropriate action. As a result, the risk of decreased efficiency and deterioration in work quality is increasing.

[1810] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for receiving the content of a problem input by the user, means for analyzing and classifying the content of the problem using generative artificial intelligence, means for generating optimal advice based on the classified problem, means for presenting the generated advice to the user, means for selecting companies and services necessary to solve the problem, means for presenting the selected companies and services to the user, means for receiving the user's selection results and transmitting user information to the selected companies, means for collecting and managing referral fees, means for collecting operational data from industrial machinery, means for collecting and analyzing worker emotion data, means for generating and presenting advice regarding the operation of industrial machinery based on the analysis results, and means for connecting to external technical support services as needed. This makes it possible to comprehensively manage the status of both factory robots and workers and to take appropriate action immediately.

[1811] A "user" is someone who works in a factory or someone who uses the system to input data about their worries and emotions.

[1812] "Generative artificial intelligence" is an artificial intelligence technology that analyzes and classifies input data and generates optimal advice.

[1813] "Problems" refer to the issues and challenges that users face, and are information provided to the system through input.

[1814] "Advice" refers to guidelines for solutions and improvements generated by generative artificial intelligence based on the analysis results.

[1815] "Industrial machinery" is a general term for robots and production equipment used in factories, and is the subject of operational data collection.

[1816] "Operational data" refers to data related to the operating status of industrial machinery, such as operating hours and error codes.

[1817] "Emotional data" refers to data about a user's emotional state, including information such as stress levels and fatigue levels.

[1818] A "server" is a central information processing device that performs tasks such as data analysis, advice generation, and selection of companies and services.

[1819] "Means" refers to the specific methods or devices used to realize each function of the system.

[1820] "External technical support services" refer to external companies or experts that provide problem-solving and technical support within the factory.

[1821] Modes for carrying out the invention

[1822] Basic System Configuration

[1823] The system that implements this application consists of the following main components.

[1824] 1. Terminal: A device that provides an interface for users to input data about their worries and emotions. Specifically, this includes tablet devices and smart glasses.

[1825] 2. Server: This is the central system that analyzes problems, recognizes emotions, generates advice, and selects companies and services. It is equipped with a database, generative artificial intelligence (AI), and an emotion engine.

[1826] 3. Industrial machinery: These are robots and production equipment used in factories, and are the subjects of operational data collection.

[1827] System operation

[1828] Data collection

[1829] The device collects data on worries and emotions entered by the user. This emotional data is entered by the user using a tablet or smart glasses. For example, the user receives the following prompt: "Please enter your current stress level on a scale of 1 to 5, with 1 being the lowest and 5 being the highest." The collected data is sent to the server.

[1830] Industrial machinery is equipped with operational sensors that collect operational data such as operating time, temperature, and error codes. This data is also periodically transmitted to a server.

[1831] Data Analysis

[1832] The server receives collected data on worries, emotions, and operational data. Generative artificial intelligence (using TensorFlow) analyzes the text data and classifies the worries. Simultaneously, an emotion engine analyzes the emotion data and recognizes the user's mental state and emotions.

[1833] Generating advice

[1834] Based on the analysis results and sentiment analysis results, the server generates advice on how to resolve problems and errors in industrial machinery. This advice is customized to the specific situation of the user and the industrial machinery. For example, it might generate specific advice such as, "The machine temperature is high. Please check the cooling system. Also, the worker's stress level is high. We recommend taking a break."

[1835] Providing advice and connecting

[1836] The terminal displays the generated advice to the user. Furthermore, if necessary, the server seamlessly connects with external technical support services to provide real-time support.

[1837] Hardware and software to use

[1838] Hardware:

[1839] Industrial machinery (with operation data collection sensors)

[1840] Tablet devices and smart glasses (for inputting emotional data)

[1841] software:

[1842] Python: Data Analysis and AI Model Building

[1843] TensorFlow: Implementing Generative Artificial Intelligence and Emotion Engines

[1844] MySQL: Storing and managing collected data

[1845] REST API: Data reception and transmission interface

[1846] Flask: Server construction and API development

[1847] Specific example

[1848] User A is working in a factory and inputs emotional data into a tablet device. For example, in response to the prompt, "Please enter your current stress level on a scale of 1 to 5. 1 is the lowest, and 5 is the highest," User A enters 3. The device sends this data to a server, which analyzes it and generates advice. Next, the advice is sent to the device, displaying to User A, "Your current stress level is high, so we recommend taking a break. Also, the machine temperature is high, so please check the cooling system." Furthermore, if necessary, the system can connect to external technical support services for additional assistance.

[1849] This system will improve efficiency within the factory and allow for flexible responses that take into account the health of the workers.

[1850] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1851] Step 1:

[1852] The user accesses the device and inputs emotional data. Specifically, the user receives a prompt message, "Please enter your current stress level on a scale of 1 to 5. 1 is the lowest, and 5 is the highest," and enters their stress level. The stress level (e.g., 3) is collected as input data.

[1853] Step 2:

[1854] The device sends collected emotional data to the server. The device converts the stress level value (e.g., 3) into JSON format and transfers it to the server via a REST API. The input is the user's emotional data, and the output is the data transmission to the server.

[1855] Step 3:

[1856] Industrial machinery collects operational data and sends it to a server. This operational data includes operating time, temperature, and error codes. For example, data might be collected showing an operating time of 500 minutes, a temperature of 75 degrees, and an error code of 0.

[1857] Step 4:

[1858] The server receives the collected sentiment and operational data and stores it in a database. The server uses MySQL to store the sentiment and operational data. Specific data inserted into the database includes stress levels, uptime, temperature, and error codes.

[1859] Step 5:

[1860] The server uses generative artificial intelligence to analyze emotional and operational data. During the analysis, the emotional engine assesses the user's stress level, and the generative AI model (using TensorFlow) comprehensively analyzes the operational and emotional data. As a result of the analysis, factors contributing to decreased work efficiency and machine error situations are identified.

[1861] Step 6:

[1862] The server generates advice based on the analysis results. The generated advice is specific, such as, "The machine temperature is high, please check the cooling system. Also, the worker's stress level is high; we recommend taking a break." The input is the analysis results, and the output is the generated advice.

[1863] Step 7:

[1864] The server sends the generated advice to the terminal. The server converts the generated advice into JSON format and sends it to the terminal via a REST API. The input is the generated advice, and the output is the data sent to the terminal.

[1865] Step 8:

[1866] The terminal displays advice to the user. For example, the tablet screen might display, "The machine temperature is high; please check the cooling system. Also, the worker's stress level is high; a break is recommended." The input is the advice received from the server, and the output is what is displayed to the user.

[1867] Step 9:

[1868] The server connects to an external technical support service as needed. If the user requests additional support, the server sends the user's status and the required support details to the external technical support service. This provides real-time technical support. The input is the user's support request, and the output is the connection to the external technical support service.

[1869] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1870] The data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One 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">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1871] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1872] [Fourth Embodiment]

[1873] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1874] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1875] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1876] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1877] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1878] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1879] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1880] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1881] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1882] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1883] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1884] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1885] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1886] This invention provides a system for receiving and analyzing users' problems, providing appropriate advice, and seamlessly connecting them to the companies and services necessary for resolving those problems. Specific embodiments for carrying out this invention are described below.

[1887] 1. Basic System Configuration

[1888] This system consists of the following main components:

[1889] Terminal: A device that provides an interface for users to input their concerns.

[1890] Server: The central system that analyzes and classifies problems, generates advice, and selects companies and services.

[1891] Generative artificial intelligence: AI models for analyzing problems and generating advice.

[1892] Database: Stores information about companies and services and uses it for selection.

[1893] 2. System Operation

[1894] Receiving and analyzing problems

[1895] 1. The user accesses the device and enters their problem in text format.

[1896] 2. The terminal receives the entered content of the problem and sends the data to the server.

[1897] 3. The server passes the received data to a generative artificial intelligence (AI) for analysis. The generative AI extracts keywords from the text and performs sentiment analysis to analyze the content of the problem in detail.

[1898] 4. Based on the analysis results, the server classifies the problems into specific categories (e.g., inheritance, childcare, health issues, etc.).

[1899] Providing advice

[1900] 5. Based on the analysis results, the server selects an advice template appropriate to the category of the problem. Furthermore, it uses generative artificial intelligence to generate customized advice tailored to the user's specific problem.

[1901] 6. Once the server has finished generating the advice, it sends the generated results to the terminal.

[1902] 7. The device displays the received advice to the user. This allows the user to obtain guidance for specific solutions.

[1903] Proposal of solutions and connection

[1904] 8. The server accesses the database and selects relevant companies and services based on the analyzed problem category. For example, in the case of inheritance, it retrieves a list of reliable tax accounting firms.

[1905] 9. The server sends a list of selected companies and services to the terminal.

[1906] 10. The device displays a list of relevant companies and services to the user. The user can select the desired company or service from the list.

[1907] 11. When a user selects a company or service, the device sends the selection to the server.

[1908] 12. The server sends user information to the selected company and performs the matching process.

[1909] Crowdfunding proposal (optional)

[1910] 13. The server will suggest an appropriate crowdfunding platform if funding is needed to solve the user's problem.

[1911] 14. The server sends information from the crowdfunding platform to the device.

[1912] 15. The device displays crowdfunding platform proposals to the user, allowing them to receive further support as needed.

[1913] Management of referral fees

[1914] 16. The server operates a system to collect referral fees from partner companies when a match is successfully made with selected companies or services. The management and billing process for referral fees is entrusted to a dedicated management system.

[1915] Specific example

[1916] For example, if user A has concerns about inheritance, it would look like this:

[1917] 1. User A enters "I'm worried about inheritance" into the portal site.

[1918] 2. The terminal sends the input content to the server.

[1919] 3. The server uses generative artificial intelligence to analyze the text and categorize it under the "inheritance" category.

[1920] 4. The server generates advice regarding inheritance and sends it to the terminal.

[1921] 5. The device displays advice to user A (e.g., "Regarding inheritance procedures").

[1922] 6. The server selects a list of trusted tax accounting firms from its database and sends it to the terminal.

[1923] 7. The terminal displays the list to user A.

[1924] 8. User A selects a specific tax accounting firm.

[1925] 9. The terminal sends the selection result to the server.

[1926] 10. The server sends User A's information to the selected tax accounting firm and performs the matching process.

[1927] 11. The server collects referral fees from the tax accounting firm and records them in the management system.

[1928] In this way, the present invention provides a system for efficiently and effectively solving users' problems, and means for implementing the same.

[1929] The following describes the processing flow.

[1930] Step 1:

[1931] The user accesses the portal site using their device and enters the details of their problem as text.

[1932] Step 2:

[1933] The terminal receives user input and sends that information to the server.

[1934] Step 3:

[1935] The server receives text data about the problem and passes it to a generative artificial intelligence for analysis.

[1936] Step 4:

[1937] The generative artificial intelligence on the server analyzes the text, extracting keywords and performing sentiment analysis.

[1938] Step 5:

[1939] The server uses the analysis results to classify the problems into specific categories (e.g., inheritance, childcare, health issues, etc.).

[1940] Step 6:

[1941] Based on the analysis results, the server selects an advice template corresponding to the problem category.

[1942] Step 7:

[1943] The server uses generative artificial intelligence to generate customized advice tailored to the user's specific concerns.

[1944] Step 8:

[1945] The server sends the generated advice to the terminal.

[1946] Step 9:

[1947] The device displays generated advice to the user.

[1948] Step 10:

[1949] Based on the analysis results, the server selects companies and services from its database that are suitable for solving the problem.

[1950] Step 11:

[1951] The server generates a list of selected companies and services and sends it to the terminal.

[1952] Step 12:

[1953] The device displays a list of companies and services related to the user.

[1954] Step 13:

[1955] Users select companies or services that interest them from a presented list.

[1956] Step 14:

[1957] The terminal sends the user's selection results to the server.

[1958] Step 15:

[1959] The server sends user information to the selected companies based on the user's selection results.

[1960] Step 16:

[1961] The server waits for a response from the selected company, and if the matching is successful, it sends the result to the terminal.

[1962] Step 17:

[1963] The device notifies the user of the matching result.

[1964] Step 18:

[1965] Users will contact the selected companies and services directly and proceed with specific procedures to resolve their issues.

[1966] Step 19:

[1967] Once the server completes the matching process, it manages the referral fees from partner companies and initiates the billing process.

[1968] Step 20:

[1969] The server receives the referral fee and records it in the management system.

[1970] Step 21:

[1971] In some cases, the server will send appropriate platform information to the terminal to suggest a crowdfunding platform.

[1972] Step 22:

[1973] The device displays crowdfunding platform proposals to the user.

[1974] Step 23:

[1975] Users can utilize crowdfunding platforms as needed to receive further support.

[1976] (Example 1)

[1977] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1978] In modern society, individuals face a wide variety of problems and challenges, often requiring specialized knowledge and support to resolve. However, selecting the right company or service, and receiving prompt and accurate advice, is difficult. Existing systems require users to gather information and perform the necessary procedures themselves, which consumes considerable time and effort. Furthermore, if appropriate experts or services cannot be found, the problem may worsen. Therefore, there is a need for efficient and effective means to resolve users' problems.

[1979] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1980] In this invention, the server includes a device for receiving the content of a user's problem, a device for analyzing and classifying the content of the problem using generative artificial intelligence, a device for generating optimal advice based on the classified problem, a device for presenting the generated advice to the user, a device for selecting relevant businesses and services necessary for solving the problem, a device for presenting the selected businesses and services to the user, a device for receiving the user's selection results and transmitting user information to the selected businesses, and a device for collecting and managing referral fees. As a result, the user can efficiently analyze their problem, receive appropriate advice, quickly connect to the necessary businesses and services, and obtain support for problem solving.

[1981] A "user" refers to an individual who attempts to solve their own problems using this system.

[1982] A "device" refers to a device that provides an interface for users to input their concerns. Specifically, this includes computers, smartphones, tablets, and so on.

[1983] A "server" refers to a central computer system that analyzes, classifies, and provides advice on problems, as well as selecting and matching relevant businesses and services.

[1984] "Generative artificial intelligence" refers to an AI model that analyzes input text data, extracts keywords, and performs sentiment analysis to understand the user's concerns in detail and generate appropriate advice.

[1985] "Analyzing" refers to using generative artificial intelligence to extract keywords and perform sentiment analysis on input data, thereby gaining a detailed understanding of its content.

[1986] "Classifying" refers to categorizing users' concerns into specific categories (e.g., inheritance, childcare, health issues, etc.) based on the analysis results.

[1987] "Generating advice" refers to using generative artificial intelligence based on category-specific templates to create customized solutions or guidelines for a user's specific problems.

[1988] "Presenting" refers to displaying generated advice and information about related businesses and services to the user.

[1989] "Selecting" refers to extracting and choosing relevant businesses and services from a database based on the analyzed categories of problems.

[1990] "Transmitting user information" refers to sending necessary user information via the network to the business entity or service selected by the user.

[1991] A "business entity" refers to an organization or company that provides the specialized knowledge and services necessary to solve a problem.

[1992] "Referral fee" refers to the commission collected from a partnering business when a user and business are successfully matched.

[1993] A "crowdfunding platform" refers to a service that allows users to raise funds online to solve their problems.

[1994] This invention provides a system for receiving and analyzing users' problems, offering appropriate advice, and seamlessly connecting them to the necessary companies and services for resolving those problems. This system consists of the following main components:

[1995] 1. Terminal: A device that provides an interface for users to input their problems. Specifically, this includes computers, smartphones, and tablets. Users input their problems in text format via the terminal.

[1996] 2. Server: This is the central system that analyzes, classifies, and provides advice on problems, as well as selecting and matching relevant businesses and services. Specifically, generative artificial intelligence (e.g., GPT-3) is used as the software, and it is executed within the server to perform data analysis and advice generation.

[1997] 3. Generative Artificial Intelligence: This AI model analyzes text data entered by the user, extracts keywords, and performs sentiment analysis to understand the user's concerns in detail and generate appropriate advice. This AI model heavily relies on the analysis of text data and the generation of advice.

[1998] 4. Database: Used to store information about companies and services, and to search for and select appropriate businesses and services that meet users' needs. Detailed information about businesses and services is registered within the database.

[1999] System operation details

[2000] Receiving and analyzing problems

[2001] When a user enters their problem into their device, the device sends that text data to a server via an HTTP request. The server then passes the received data to a generative artificial intelligence (AI). This AI extracts keywords and performs sentiment analysis based on the input text data, providing a detailed analysis of the user's problem.

[2002] Generating and providing advice

[2003] The server categorizes the user's concerns into specific categories based on the analysis results from the generative artificial intelligence. It then selects an advice template corresponding to the category and uses the generative artificial intelligence again to generate customized advice tailored to the user's specific concerns. The generated advice is sent from the server to the terminal and displayed to the user.

[2004] Selection of companies and services

[2005] The server selects relevant businesses and services based on the problem categories analyzed from the database. This selection is sent to the terminal as a list of businesses and services and displayed to the user. The user can then select their desired business or service from the displayed list.

[2006] User information submission and matching

[2007] When a user selects their desired business entity or service, the selection is sent from the terminal to the server. The server then sends the user information to the selected business entity and performs a matching process. This allows the user to quickly access the appropriate service.

[2008] Specific example

[2009] For example, if user A has concerns about inheritance, it would look like this:

[2010] 1. User A enters "I'm worried about inheritance" into the terminal.

[2011] 2. The device sends the text data to the server.

[2012] 3. The server uses generative artificial intelligence to analyze the text and categorize it under the "inheritance" category.

[2013] 4. The server generates advice regarding inheritance and sends it to the terminal.

[2014] 5. The device displays advice to user A (e.g., "Regarding inheritance procedures").

[2015] 6. The server selects a trusted expert from the database and sends the list to the terminal.

[2016] 7. The terminal displays the list to user A.

[2017] 8. User A selects a specific expert.

[2018] 9. The terminal sends the selection result to the server.

[2019] 10. The server sends User A's information to the selected expert and performs the matching process.

[2020] In this way, the present invention provides a system and means for implementing it that efficiently and effectively solves users' problems.

[2021] Example of a prompt

[2022] An example of a prompt message might read: "Please enter your problem in text format and send it to the server. The server will pass the text data to a generative artificial intelligence system that will analyze and classify your problem. It will then provide appropriate advice and a list of relevant businesses and services."

[2023] This system is a powerful tool for efficiently analyzing users' problems and providing quick and appropriate solutions.

[2024] The flow of the specific processing in Example 1 will be explained using Figure 11.

[2025] Step 1:

[2026] The user enters their problem in text format into the device.

[2027] Input: Text data of the user's problem

[2028] Output: Text data received by the terminal

[2029] Users access the input interface of a portal site or application and describe their problems in detail. This text data is received by the device.

[2030] Step 2:

[2031] The terminal sends the entered text data about the problem to the server.

[2032] Input: Text data received on the device

[2033] Output: Text data transferred to the server

[2034] The terminal receives text data and sends it to the server via a communication method such as an HTTP request. HTTPS is the recommended communication protocol.

[2035] Step 3:

[2036] The server receives text data and passes it to a generative artificial intelligence for analysis.

[2037] Input: Text data transferred to the server

[2038] Output: Analyzed problem data (keywords, emotions, categories)

[2039] The server passes text data to a generative artificial intelligence (e.g., GPT-3). The generative AI extracts keywords from the text and performs sentiment analysis to analyze the content of the problem. As a result, the category and keywords of the problem are extracted.

[2040] Step 4:

[2041] The server categorizes the problems based on the analysis results.

[2042] Input: Analyzed problem data

[2043] Output: Categorized problem data

[2044] The server uses the analysis results from the generative artificial intelligence to classify the problems into specific categories. For example, it might categorize them into "inheritance," "childcare," or "health problems."

[2045] Step 5:

[2046] The server selects an advice template based on the category and uses generative artificial intelligence to generate customized advice.

[2047] Input: Categorized problem data

[2048] Output: Customized advice data

[2049] The server selects a pre-prepared advice template and uses generative artificial intelligence to customize the advice to address the user's specific concerns. The generated advice is output in text format.

[2050] Step 6:

[2051] The server sends the generated advice data to the terminal.

[2052] Input: Customized advice data

[2053] Output: Advice data transferred to the terminal

[2054] The server sends the generated advice data back to the terminal via an HTTP request. HTTPS is recommended to ensure the reliability of the communication.

[2055] Step 7:

[2056] The device displays the advice it has received to the user.

[2057] Input: Advice data transferred to the device

[2058] Output: Advice displayed to the user

[2059] The device displays the received advice data in a user-friendly format, allowing the user to obtain concrete guidance for solutions.

[2060] Step 8:

[2061] The server accesses the database and selects the relevant entities and services.

[2062] Input: Categorized problem data

[2063] Output: List of selected entities and services

[2064] Based on the analyzed problem categories, the server selects relevant businesses and services from the database. This results in a list of the businesses and services best suited to the user's problem.

[2065] Step 9:

[2066] The server sends a list of selected entities and services to the terminal.

[2067] Input: List of selected entities or services

[2068] Output: List of entities and services transferred to the terminal

[2069] The server sends a list of selected entities and services to the terminal. This is also done via an HTTP request.

[2070] Step 10:

[2071] The device displays a list of businesses and services associated with the device to the user.

[2072] Input: List of entities and services transferred to the terminal

[2073] Output: A list of entities and services displayed to the user.

[2074] The terminal displays a list of received entities and services to the user. The user can select the desired entity or service from this list.

[2075] Step 11:

[2076] When a user selects a company or service, the device sends that selection to the server.

[2077] Input: Information about the business entity or service selected by the user.

[2078] Output: Selection results sent to the server

[2079] When a user selects a specific business entity or service, the selection result is sent from the terminal to the server.

[2080] Step 12:

[2081] The server sends user information to the selected business entity and performs the matching process.

[2082] Input: Selection results sent to the server

[2083] Output: User information sent to the selected entity

[2084] The server sends user information to the selected business entity and performs a matching process. This allows users to quickly receive the support they need.

[2085] Step 13 (Optional):

[2086] The server sends information from the crowdfunding platform to the device.

[2087] Input: Problem data indicating that a crowdfunding proposal is deemed necessary.

[2088] Output: Information about the crowdfunding platform sent to the device.

[2089] In some cases, the server may determine that the user needs funding to solve their problem and send information about an appropriate crowdfunding platform.

[2090] Step 14 (Optional):

[2091] The device displays crowdfunding platform proposals to the user.

[2092] Input: Information from the crowdfunding platform sent to the device.

[2093] Output: Information about the crowdfunding platform displayed to the user.

[2094] The device displays project information from crowdfunding platforms to the user. The user can then receive further funding as needed.

[2095] Step 15:

[2096] The server collects and manages referral fees.

[2097] Input: Information on businesses and users that have been successfully matched.

[2098] Output: Collected referral fees and records in the management system

[2099] When a match is successful, the server collects a referral fee from the partner company and records it in a dedicated management system. This process is automated and functions as part of the revenue model.

[2100] (Application Example 1)

[2101] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2102] Traditional problem-solving systems have a problem in that they cannot quickly provide appropriate advice or relevant store information to users who are having trouble choosing products in a physical store. Therefore, users have to search for information and find solutions themselves, which is time-consuming and requires effort. Furthermore, the system in question is required not only to analyze the user's problem and present a suitable solution, but also to provide users with a way to quickly and effectively resolve their problem in a physical store.

[2103] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[2104] In this invention, the server includes means for receiving the content of a user's problem, means for analyzing and classifying the content of the problem using generative artificial intelligence, means for generating optimal advice based on the classified problem, means for presenting the generated advice to the user, means for selecting companies and services necessary to solve the problem, means for presenting the selected companies and services to the user, means for receiving the user's selection results and transmitting user information to the selected companies, means for collecting and managing referral fees, means for providing information on relevant stores to resolve difficulties when the user is having trouble choosing a product, means for presenting information on the relevant stores to the user, and means for accessing a database for providing information on the stores. As a result, when a user is having trouble choosing a product in a physical store, they can use their smartphone to input their problem, and the system will analyze the problem and quickly provide appropriate solutions and information on relevant stores.

[2105] Definitions of important words

[2106] "A means of receiving user input about their concerns" refers to a function that allows users to input their concerns in text format using a specific device, and for the system to receive that input.

[2107] "Means for analyzing and classifying the content of the aforementioned problems using generative artificial intelligence" refers to a system that uses a generative AI model to extract keywords and perform sentiment analysis from input text data, and has the function of classifying the content of the problems into specific categories.

[2108] "Means for generating optimal advice based on the classified problems" refers to a function that generates advice best suited to solving the user's problems based on the analyzed and classified data.

[2109] "Means for presenting the generated advice to the user" refers to a means that has the function of displaying the generated advice on a device accessible to the user.

[2110] "Means for selecting companies and services necessary to solve the aforementioned problems" refers to a function that searches a database for and selects companies and services suitable for solving the user's problems.

[2111] "Means for presenting the selected companies and services to the user" refers to a function that displays a list of selected companies and services on the user's device.

[2112] "Means for receiving user selection results and transmitting user information to selected companies" refers to a system that receives company information selected by the user and transmits the user's information to the selected companies.

[2113] "Means for collecting and managing referral fees" refers to a system that collects referral fees from companies when a match is successful and manages those fees.

[2114] "A means of providing information on relevant stores to resolve difficulties when a user has trouble choosing a product" refers to a function that provides information on suitable stores to resolve difficulties a user encounters when choosing a product.

[2115] "Means for presenting information about the relevant stores to the user" refers to a means that has the function of displaying information about the relevant stores on the user's device.

[2116] "Means for accessing a database to provide information about the store" refers to a means that has the function of accessing a database and obtaining information in order to provide information about the relevant store.

[2117] Modes for carrying out the invention

[2118] This invention provides a system that allows users to input their concerns using their smartphone when they are having trouble choosing products in a physical store. The system then analyzes these concerns and quickly provides appropriate solutions and information about relevant stores. The following describes in detail specific embodiments for carrying out this invention.

[2119] 1. Basic System Configuration

[2120] This system consists of the following main components:

[2121] Device: A smartphone that provides an interface for users to input their problems or concerns.

[2122] Server: The central system that analyzes and classifies problems, generates advice, and selects companies and services.

[2123] Generative artificial intelligence (AI model): An AI model designed to analyze problems and generate advice.

[2124] Database: Stores information about companies and related stores, and uses it for selection.

[2125] 2. System Operation

[2126] Receiving and analyzing problems

[2127] 1. The user uses their smartphone to enter a specific problem in text format. For example, they might type, "I don't know what to get my child for their birthday."

[2128] 2. The terminal receives the entered content of the problem and sends the data to the server.

[2129] 3. The server passes the received data to a generative artificial intelligence (e.g., OpenAI's GPT-4) for analysis. The AI ​​model extracts keywords from the text and performs sentiment analysis to analyze the content of the problem in detail.

[2130] 4. Based on the analysis results, the server classifies the problem into a specific category (e.g., birthday present).

[2131] Providing advice

[2132] 5. Based on the analysis results, the server selects an advice template appropriate to the category of the problem. Furthermore, it uses generative artificial intelligence to generate customized advice tailored to the user's specific problem.

[2133] 6. Once the server has finished generating the advice, it sends the generated results to the terminal.

[2134] 7. The device displays the received advice to the user. For example, it might display specific advice such as, "Toys, books, and games are suitable as birthday presents."

[2135] Providing store information

[2136] 8. The server accesses the database and selects relevant stores based on the analyzed problem categories. For example, it retrieves lists such as "toy stores" and "bookstores."

[2137] 9. The server sends a list of selected stores to the terminal.

[2138] 10. The terminal displays a list of relevant stores to the user. The user can select their desired store from the list.

[2139] 11. When a user selects a specific store, detailed information about that store (e.g., address, contact information, business hours) is displayed.

[2140] Crowdfunding proposal (optional)

[2141] 12. The server will suggest an appropriate crowdfunding platform if funding is needed to solve the user's problem.

[2142] 13. The server sends information from the crowdfunding platform to the device.

[2143] 14. The device displays crowdfunding platform proposals to the user, allowing them to receive further support as needed.

[2144] This system allows users to quickly obtain specific advice and relevant store information to effectively resolve the difficulties they face when choosing products in physical stores. An example of a prompt message is, "I don't know what would be a good birthday present for my child."

[2145] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[2146] Program processing steps

[2147] Step 1:

[2148] The user enters their problem in text format using their smartphone.

[2149] Input: The user enters "I don't know what would be a good birthday present for my child" into a smartphone application.

[2150] Specific action: The user enters their problem into a text box and presses the "Submit" button.

[2151] Step 2:

[2152] The terminal receives the entered problem details and sends the data to the server.

[2153] Input: Text data entered by the user.

[2154] Data processing: The terminal converts the text data into JSON format and sends it to the server.

[2155] Output: Input data in JSON format is sent to the server.

[2156] Specific operation: The terminal formats the text data into JSON format and sends an HTTP request to the server's API endpoint.

[2157] Step 3:

[2158] The server passes the received data to a generative artificial intelligence for analysis. The AI ​​model extracts keywords from the text and performs sentiment analysis to analyze the content of the problem in detail.

[2159] Input: Input data in JSON format.

[2160] Data processing: An AI model (e.g., GPT-4) extracts keywords from text, performs sentiment analysis, and categorizes the data.

[2161] Output: The analysis results (categories and keywords) are returned to the server.

[2162] Specific operation: The server sends an API request to the AI ​​model, the model performs text analysis, and returns the analysis results to the server.

[2163] Step 4:

[2164] Based on the analysis results, the server categorizes the problem into a specific category (e.g., birthday present).

[2165] Input: Analysis results returned from the AI ​​model.

[2166] Data processing: Based on the analysis results, the data is classified into specific categories.

[2167] Output: Classified data is generated.

[2168] Specific operation: The server compares the analysis results with a preset category list to identify the corresponding category.

[2169] Step 5:

[2170] Based on the analysis results, the server selects an advice template appropriate to the problem category and uses generative artificial intelligence to generate personalized advice for the user.

[2171] Input: Categorized data and advice templates.

[2172] Data processing: AI models generate customized advice.

[2173] Output: Customized advice.

[2174] Specific operation: The server passes an advice template to the AI ​​model, which then generates advice that customizes the template based on categorical data.

[2175] Step 6:

[2176] Once the server has finished generating the advice, it sends the results to the terminal.

[2177] Input: Generated advice data.

[2178] Data processing: Convert the advice data to JSON format.

[2179] Output: Advice data in JSON format is sent to the terminal.

[2180] Specific operation: The server formats the generated advice into JSON format and sends an HTTP request to the terminal's API endpoint.

[2181] Step 7:

[2182] The device displays the received advice to the user.

[2183] Input: Advice data in JSON format received from the server.

[2184] Output: Advice displayed to the user.

[2185] Specific operation: The terminal parses the JSON data and displays advice in the user interface.

[2186] Step 8:

[2187] The server accesses the database and selects relevant stores based on the analyzed problem categories.

[2188] Input: Classified category data.

[2189] Data processing: Based on category data, relevant store information is searched and retrieved from the database.

[2190] Output: List of store information.

[2191] Specific operation: The server sends category data as a query to the database and retrieves related store information.

[2192] Step 9:

[2193] The server sends a list of selected stores to the terminal.

[2194] Input: List of store information.

[2195] Data processing: Convert store information to JSON format.

[2196] Output: A list of stores in JSON format is sent to the terminal.

[2197] Specific operation: The server formats the store information in JSON format and sends an HTTP request to the terminal's API endpoint.

[2198] Step 10:

[2199] The terminal displays a list of relevant stores to the user.

[2200] Input: A list of stores in JSON format received from the server.

[2201] Output: A list of stores displayed to the user.

[2202] Specific operation: The terminal parses the JSON data and displays the store information as a list in the user interface.

[2203] Step 11:

[2204] When a user selects a specific store, detailed information about that store is displayed.

[2205] Input: User's store selection action.

[2206] Output: Detailed information about the selected store.

[2207] Specific action: The device displays detailed information about the selected store (e.g., address, contact information, business hours).

[2208] Step 12:

[2209] The server will, in some cases, suggest an appropriate crowdfunding platform when funding is needed to solve a user's problem.

[2210] Input: User's problem and analysis results.

[2211] Data processing: AI analysis to propose crowdfunding platforms.

[2212] Output: Proposal for a crowdfunding platform.

[2213] Specific operation: The server proposes a crowdfunding campaign based on the analysis results and sends it to the terminal.

[2214] Step 13:

[2215] The device displays proposals from crowdfunding platforms to the user, allowing them to receive further support as needed.

[2216] Input: Crowdfunding proposal information received from the server.

[2217] Output: Crowdfunding information displayed to the user.

[2218] Specific action: The device displays crowdfunding proposals it has received in the user interface.

[2219] Through these steps, users can use their smartphones to get quick and effective advice and relevant store information when they have trouble choosing products in a physical store.

[2220] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[2221] This invention provides a system that receives and analyzes users' concerns, provides appropriate advice, and seamlessly connects them to the necessary companies and services for resolution, in addition to an emotion engine that recognizes the user's emotions. Specific embodiments for carrying out this invention will be described below.

[2222] Basic System Configuration

[2223] This system consists of the following main components:

[2224] Terminal: A device that provides an interface for users to input their concerns.

[2225] Server: The central system that analyzes problems, recognizes emotions, generates advice, and selects companies and services.

[2226] Generative artificial intelligence: AI models for analyzing problems and generating advice.

[2227] Emotion engine: A system that recognizes and analyzes emotions from text entered by the user.

[2228] Database: Stores information about companies and services and uses it for selection.

[2229] System operation

[2230] Receiving and analyzing problems

[2231] 1. The user accesses the device and enters their problem in text format.

[2232] 2. The terminal receives the entered content of the problem and sends the data to the server.

[2233] 3. The server passes the received data to the generative artificial intelligence and the emotion engine for analysis. The generative artificial intelligence extracts keywords from the text and performs emotion analysis to analyze the content of the problem in detail.

[2234] 4. The emotion engine on the server determines the emotional state from the user's input and feeds the result back to the generative artificial intelligence.

[2235] 5. The server classifies the problem into a specific category (e.g., inheritance, childcare, health issues, etc.) based on the analysis results and sentiment analysis results.

[2236] Providing advice

[2237] 6. Based on the analysis results, the server selects an advice template appropriate to the category of the problem. Furthermore, it uses generative artificial intelligence to generate customized advice that is tailored to the user's specific problem and emotional state.

[2238] 7. The server sends the generated advice to the terminal.

[2239] 8. The device displays generated advice to the user. This allows the user to receive guidance on solutions that take their emotional state into consideration.

[2240] Proposal of solutions and connection

[2241] 9. Based on the analysis results, the server selects companies and services from the database that are suitable for solving the problem. The results of the sentiment analysis are also taken into consideration in the selection process.

[2242] 10. The server generates a list of selected companies and services and sends it to the terminal.

[2243] 11. The device displays a list of companies and services related to the user.

[2244] 12. The user selects companies or services of interest from the presented list.

[2245] 13. The terminal sends the user's selection results to the server.

[2246] 14. The server sends user information to the selected companies based on the user's selection results.

[2247] Crowdfunding proposal (optional)

[2248] 15. The server will suggest an appropriate crowdfunding platform if, in some cases, funding is needed to solve the user's problem.

[2249] 16. The server sends information from the crowdfunding platform to the device.

[2250] 17. The device displays crowdfunding platform proposals to the user, allowing them to receive further support as needed.

[2251] Management of referral fees

[2252] 18. The server operates a system to collect referral fees from partner companies when a match is successfully made with selected companies or services. The management and billing process for referral fees is entrusted to a dedicated management system.

[2253] Specific example

[2254] For example, if user B has concerns about childcare, it would look like this:

[2255] 1. User B enters their "childcare concerns" into the portal site.

[2256] 2. The terminal sends the input content to the server.

[2257] 3. The server uses generative artificial intelligence and an emotion engine to analyze the text and classify it into the "childcare" category. At the same time, the emotion engine recognizes user B's mental state and emotions.

[2258] 4. The server generates advice and creates customized advice that takes sentiment analysis results into account.

[2259] 5. The server sends the generated advice to the terminal, which then displays it to user B (e.g., "How to manage stress in childcare").

[2260] 6. The server selects suitable childcare support companies and services from the database and sends the list to the terminal.

[2261] 7. The device displays a list to User B, and User B selects a specific childcare support service.

[2262] 8. The device sends the selection results to the server.

[2263] 9. The server sends User B's information to the selected childcare support service and performs the matching process.

[2264] 10. The server collects referral fees from childcare support services and records them in the management system.

[2265] In this way, the present invention realizes a system that analyzes user concerns, including their emotions, provides solutions, and seamlessly connects to businesses and services.

[2266] The following describes the processing flow.

[2267] Step 1:

[2268] The user accesses the portal site using their device and enters the details of their problem as text.

[2269] Step 2:

[2270] The terminal receives user input and sends that information to the server.

[2271] Step 3:

[2272] The server receives the text data of the problem and passes it to a generative artificial intelligence to begin analysis.

[2273] Step 4:

[2274] The server passes user input data to the emotion engine, which then recognizes the user's emotional state.

[2275] Step 5:

[2276] Generative artificial intelligence analyzes text data, extracting keywords and performing sentiment analysis. Simultaneously, a sentiment engine determines the user's emotional state.

[2277] Step 6:

[2278] The server collects analysis results from generative artificial intelligence and emotion engines, and classifies the problems into specific categories (e.g., inheritance, childcare, health issues, etc.).

[2279] Step 7:

[2280] The server selects an advice template that corresponds to the problem category.

[2281] Step 8:

[2282] The server uses generative artificial intelligence to generate customized advice based on the user's specific concerns and emotional state.

[2283] Step 9:

[2284] The server sends the generated advice to the terminal.

[2285] Step 10:

[2286] The device displays generated advice to the user. This provides the user with specific solutions that take their emotional state into consideration.

[2287] Step 11:

[2288] Based on the analysis results, the server selects companies and services from its database that are necessary to solve the problem. The results of the emotional analysis are also taken into consideration in the selection process.

[2289] Step 12:

[2290] The server generates a list of selected companies and services and sends it to the terminal.

[2291] Step 13:

[2292] The device displays a list of companies and services related to the user.

[2293] Step 14:

[2294] Users select companies or services that interest them from a presented list.

[2295] Step 15:

[2296] The terminal sends the user's selection results to the server.

[2297] Step 16:

[2298] The server sends user information to the selected companies based on the user's selection results.

[2299] Step 17:

[2300] The server waits for a response from the selected company, and if the matching is successful, it sends the result to the terminal.

[2301] Step 18:

[2302] The device notifies the user of the matching result.

[2303] Step 19:

[2304] Users will contact the selected companies and services directly and proceed with specific procedures to resolve their issues.

[2305] Step 20:

[2306] Once the server completes the matching process, it manages the referral fees from partner companies and initiates the billing process.

[2307] Step 21:

[2308] The server receives the referral fee and records it in the management system.

[2309] Step 22:

[2310] In some cases, the server will send appropriate platform information to the terminal to suggest a crowdfunding platform.

[2311] Step 23:

[2312] The device displays crowdfunding platform proposals to the user.

[2313] Step 24:

[2314] Users can utilize crowdfunding platforms as needed to receive further support.

[2315] (Example 2)

[2316] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2317] Conventional problem-solving support systems lacked the technology to appropriately recognize users' emotions and customize advice based on them. Furthermore, they lacked the functionality to seamlessly suggest and connect users with suitable services and companies. As a result, users often failed to alleviate stress or find appropriate services. This invention aims to solve these problems and provide users with a more effective means of resolving their problems.

[2318] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[2319] In this invention, the server includes means for receiving the content of the user's problem, means for analyzing and classifying the content of the problem using generative artificial intelligence, and means for determining the user's emotional state from the user's input using an emotion analysis engine. This makes it possible to analyze the user's problem in detail and provide customized advice based on their emotional state. The server also includes means for generating optimal advice based on the classified problem, means for presenting the generated advice to the user, means for selecting the services necessary to solve the problem, means for presenting the selected services to the user, means for receiving the user's selection results and transmitting user information to the selected services, and means for collecting and managing referral fees. This enables efficient problem solving by providing the information and services necessary to solve the user's problem in a centralized manner.

[2320] A "user" refers to a person who accesses the system and inputs their own concerns or requests.

[2321] "Generative artificial intelligence" refers to artificial intelligence technology that analyzes text data entered by users and performs categorization and generates customized advice.

[2322] An "emotion analysis engine" refers to a system that identifies and analyzes emotional states from text data entered by users.

[2323] "Means for receiving the content of concerns" refers to a function that receives text data entered by the user and securely transmits it to the server.

[2324] "Methods for analyzing and classifying the content of problems" refers to a function that uses generative artificial intelligence to analyze text data of problems entered by users and classify it into specific categories.

[2325] "Means for determining emotional state" refers to a function that uses an emotion analysis engine to determine the user's emotional state from their text data.

[2326] "Means for generating optimal advice" refers to a function that generates customized advice based on analyzed concerns and emotional states.

[2327] "Means of providing advice to the user" refers to a function that sends the generated advice to the user's device and displays it.

[2328] "A means of selecting services necessary for solving a problem" refers to a function that selects services or companies suitable for solving a problem from a database based on the analysis results.

[2329] "Means of presenting services to users" refers to functions that transmit and display information about selected services and companies to the user's device.

[2330] "Means of sending user information to a service" refers to a function that sends user information to a selected service based on the user's choices.

[2331] "Means of collecting and managing referral fees" refers to the function of collecting and managing referral fees from partnered services when a match with a selected service is successful.

[2332] This invention is a system that receives and analyzes users' problems, provides appropriate advice, and seamlessly connects them to the services necessary for resolving those problems. Specific embodiments are described below.

[2333] Basic System Configuration

[2334] This...

Claims

1. A means of receiving the content of the user's problem, A means for analyzing and classifying the content of the aforementioned problems using generative artificial intelligence, A means for generating optimal advice based on the aforementioned classified problems, A means for presenting the generated advice to the user, A means of selecting companies and services necessary to solve the aforementioned problems, A means of presenting the selected companies and services to the user, A means of receiving the user's selection results and transmitting the user information to the selected company, A means of collecting and managing referral fees A system that includes this.

2. The system according to claim 1, further comprising means for proposing a crowdfunding platform.

3. The system according to claim 1, which includes means for extracting keywords and performing emotional analysis when classifying the content of the aforementioned problems.

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