System

Abstract

A system is provided.SOLUTION: This system includes a means for receiving a problem input by a user, a means for analyzing the problem, a means for retrieving related legal knowledge and past trial case data on the basis of the analyzed problem, a means for generating proper advice on the basis of a retrieved result, and a means for presenting the generated advice to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In modern society, legal issues arising in everyday life are on the rise, but many users lack basic legal knowledge and tend to leave minor legal issues unattended because they are unsure of the cost of consulting a lawyer or how to proceed with the consultation. This situation poses a challenge as users may not receive appropriate legal support, which could worsen the problem. [Means for solving the problem]

[0005] The present invention provides a system that receives and analyzes a problem entered by a user, searches for related legal knowledge and past court case data, and generates advice. Specifically, the system includes a means for receiving a problem entered by a user, a means for analyzing the problem, a means for searching for related legal knowledge and past court case data based on the analyzed problem, a means for generating appropriate advice based on the search results, and a means for presenting the generated advice to the user. The system also includes a means for recommending consultation with an expert if the generated advice is difficult to resolve. This allows users to receive legal advice at an affordable cost and receive prompt expert assistance when necessary.

[0006] "User" means any person who uses the System to enter legal issues or questions and obtain answers.

[0007] "Problems" are legal questions or problems that users enter into the system.

[0008] "Means for receiving" refers to the technical components that allow the system to capture questions entered by users.

[0009] The "means of analysis" refers to the technical components that allow the user to understand the problem entered and relate it to relevant legal knowledge and past court cases.

[0010] "Search means" refers to the technical components for retrieving relevant legal knowledge and past case data from a database based on the analyzed problem.

[0011] "Means for generating" refers to the technical components that generate appropriate advice for users based on the retrieved data.

[0012] "Presentation means" refers to the technical components for providing the generated advice to the user visually or audibly.

[0013] A "generative artificial intelligence model" is a machine learning model that learns legal knowledge and past court case data and generates appropriate advice for users' problems.

[0014] "Experts" are lawyers and other legal professionals who have legal expertise and can provide advanced assistance to users in resolving their problems.

[0015] "Legal knowledge" is the collection of information and knowledge relating to the interpretation and application of law.

[0016] "Case law data" refers to records of information relating to judgments and decisions in past court cases. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0022] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

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

[0027] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0034] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] This invention is a system that allows users to easily and quickly resolve legal problems. The system receives and analyzes the problem entered by the user, searches for relevant legal knowledge and past court case data, and generates and presents appropriate advice. It also has a function that recommends consulting an expert if necessary.

[0039] Overall system configuration

[0040] The system mainly consists of the following elements:

[0041] A terminal where users access the system and enter questions

[0042] A server that receives and analyzes input problems, searches for necessary data, and generates advice

[0043] A device that provides advice to users and recommends consulting a specialist

[0044] Program processing explanation

[0045] In the system of the present invention, the program performs the following processing.

[0046] 1. User registration and login process

[0047] A user accesses the system and performs new registration or logs in. The terminal sends the entered user information to the server, which then collates the received information with a database and returns the authentication result.

[0048] 2. Question input and analysis processing

[0049] Users enter legal issues or questions in text format, and their devices send the questions to a server, which uses a generative AI model to analyze the issues and search for relevant legal knowledge and past court cases.

[0050] 3. Providing answers and user assistance

[0051] The server generates advice based on the search results and sends it to the device, which then displays it to the user. The user can review the displayed answers and enter follow-up questions if they require more information. The server also responds to follow-up questions.

[0052] 4. Recommendation for consultation with a specialist

[0053] If the server determines that the generative AI model has difficulty answering a question, it recommends consulting an expert. The device then presents the user with information such as the expert's contact details and how to make a reservation, and the user can then contact the expert directly based on the information provided.

[0054] Specific examples

[0055] For example, suppose a user inputs a question such as, "There is a dispute about the boundary between my land and my neighbor's land. How should I resolve it?" The device sends this question to the server, which analyzes it using a generative AI model. As a result of the analysis, specific advice is generated, such as, "Boundary disputes are generally resolved through mutual discussion, but if that does not work, we recommend that you have the exact boundary measured by a land surveyor." The server sends this advice to the device, which displays it to the user. If the user wants to act on this advice but needs more information, they can input a follow-up question to receive further assistance. If the server answers this follow-up question appropriately but is unable to resolve the issue, information recommending consultation with an expert is displayed.

[0056] Thus, the present invention is a system that allows users to receive prompt and appropriate responses to minor legal issues and, if necessary, receive expert assistance.

[0057] The processing flow will be explained below.

[0058] Step 1: The user accesses the system.

[0059] Users access the system using terminals.

[0060] Step 2: User registers or logs in.

[0061] The device receives the email address and password entered by the user and sends that information to the server.

[0062] Step 3: The server authenticates the user information.

[0063] The server checks the received user information against a database and returns the authentication result to the terminal.

[0064] Step 4: The user enters the legal issue.

[0065] Users enter legal questions or problems into the terminal in text format.

[0066] Step 5: The device sends the entered question to the server.

[0067] The terminal transmits the questions entered by the user to the server as text data.

[0068] Step 6: The server analyzes the input problem.

[0069] The server passes the received problem to the generative AI model, which analyzes the problem.

[0070] Step 7: The server searches for relevant legal knowledge and case law data.

[0071] Based on the analysis results, the server searches a database for relevant legal knowledge and past court case data.

[0072] Step 8: The server generates the appropriate advice.

[0073] The server generates appropriate advice for the user based on the search results.

[0074] Step 9: The server sends the generated advice to the terminal.

[0075] The server transmits the generated advice to the terminal.

[0076] Step 10: The terminal displays the advice to the user.

[0077] The terminal visually displays the received advice to the user.

[0078] Step 11: The user reviews the advice and enters any further questions.

[0079] The user checks the displayed advice and, if they have any additional questions, they enter them again into the terminal.

[0080] Step 12: The terminal sends a follow-up question to the server.

[0081] The terminal sends a follow-up question to the server.

[0082] Step 13: The server again generates analysis and advice for the additional question.

[0083] The server analyzes the additional question, generates advice again, and sends it to the terminal.

[0084] Step 14: If the server determines that the problem is difficult to resolve, it recommends consulting an expert.

[0085] If the server determines through its analysis that the problem is difficult to solve, it generates information recommending that the user consult with an expert.

[0086] Step 15: The terminal displays the expert consultation information to the user.

[0087] The device visually displays to the user contact information for the specialist and how to schedule a consultation.

[0088] Step 16: The user contacts the expert.

[0089] The user can then contact the expert directly based on the displayed information.

[0090] In this way, the system provides users with appropriate solutions to their legal problems and allows them to access expert help if necessary.

[0091] Example 1

[0092] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0093] To provide a system that enables users with legal problems to easily obtain appropriate advice even without specialized knowledge, and to ensure that if the problem is not resolved, the users can quickly seek advice from an expert.

[0094] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0095] In this invention, the server includes means for receiving a problem entered by a user, means for analyzing the problem, means for searching related legal knowledge and past court case data based on the analyzed problem, means for generating appropriate advice based on the search results using a generative AI model, and means for presenting the generated advice to the user. This allows users to easily obtain appropriate advice on legal problems. In addition, if the problem is difficult to solve, the server can recommend consulting an expert, allowing users to quickly receive expert support.

[0096] "User" means any person or entity seeking to resolve a legal matter using the System.

[0097] "Means for receiving questions" refers to the function of sending legal questions or doubts entered by the user to the server through the interface.

[0098] "Means for analyzing the problem" refers to the analytical function used to understand and appropriately handle received legal questions and doubts.

[0099] "Means for searching legal knowledge and past court case data" refers to the function of searching for necessary information from a database of related legal knowledge and past court cases based on the analyzed problem.

[0100] A "generative artificial intelligence model" refers to a model that uses technologies such as natural language processing and machine learning to analyze input text data and generate appropriate advice.

[0101] "Means for generating advice" refers to the function of creating appropriate solutions and advice for users' problems based on searched legal knowledge and case law data.

[0102] "Means for presenting advice" refers to a function for displaying generated advice in an easy-to-understand manner for the user.

[0103] "Means to recommend consulting an expert" refers to a function that provides users with ways to contact or consult with relevant experts when the generative AI model determines that a problem is difficult to solve.

[0104] This invention is a system that allows users to easily and quickly resolve legal problems. The system receives and analyzes the problem entered by the user, searches for relevant legal knowledge and past court case data, and generates and presents appropriate advice. It also has a function that recommends consulting an expert if necessary.

[0105] Overall system configuration

[0106] The system mainly consists of the following components:

[0107] A terminal where users access the system and enter questions

[0108] A server that receives and analyzes input problems, searches for necessary data, and generates advice

[0109] A device that provides advice to users and recommends consulting a specialist

[0110] Program processing overview

[0111] The core of the system is the server, where most data processing and calculations are performed. Specifically, the server uses generative AI models such as "OpenAI GPT-4" and "Google BERT" to analyze legal questions entered by users. The analyzed data is queried against legal knowledge bases and databases of past court cases (e.g., MySQL, PostgreSQL) to search for relevant information. Based on the searched information, the generative AI model creates appropriate advice and sends the results back to the device.

[0112] Hardware and Software Examples

[0113] Processor: For example, the server uses a high-performance processor (e.g., Intel Xeon processor).

[0114] Database: For example, MySQL or PostgreSQL

[0115] AI models: OpenAI GPT-4 and Google BERT

[0116] Communication protocol: HTTP / HTTPS is used to exchange data between the terminal and the server.

[0117] Specific examples

[0118] For example, suppose a user inputs a question such as, "There is a dispute about the boundary between my land and the neighbor's land. How should I resolve it?" The device sends this question to the server, which analyzes it using a generative AI model. As a result of the analysis, specific advice is generated, such as, "It is common for boundary disputes to be resolved through mutual discussion, but if this cannot be resolved, it is recommended that the exact boundary be measured by a land surveyor." The server sends this advice to the device, which then displays it to the user.

[0119] Prompt Sentence Examples

[0120] An example of a prompt for a generative AI model is, "There is a problem regarding the boundary line between my land and my neighbor's land. What should I do if we can't resolve it through discussion?"

[0121] Thus, the present invention is a system that can quickly and appropriately respond to minor legal issues that users have, and can provide expert support as needed.

[0122] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0123] Step 1:

[0124] A user accesses the system and performs new registration or login. The terminal receives the user information entered by the user (e.g., username, password). The terminal sends this information to the server as an HTTP POST request. The server compares the received information with a database (e.g., MySQL, PostgreSQL), generates an authentication result, and returns the result to the terminal. The terminal displays the authentication result to the user, and if successful, transitions to a question input screen. The input is user information, and the output is the authentication result.

[0125] Step 2:

[0126] The user inputs a legal problem or question in text format. This input text is received by the device and sent to the server in JSON format. The input is the text of the legal problem, and the output is the analysis result.

[0127] Step 3:

[0128] The server passes the received text to the generative AI model as a prompt. The generative AI model (e.g., OpenAI GPT-4) analyzes the input problem and understands its content. It then searches for relevant legal knowledge and past court case data. These data are stored in a database. The input is the prompt, and the output is the relevant data.

[0129] Step 4:

[0130] The server generates appropriate advice based on the relevant data analyzed by the generative AI model. This advice is created using data analysis and sentence generation functions by the generative AI model. The generated advice is sent to the device in JSON format. The input is the analysis result, and the output is the generated advice.

[0131] Step 5:

[0132] The terminal displays the received advice on the user interface. The user can confirm the presented advice and, if they have any further questions, they can enter them in an additional text box. The input is the presentation of advice to the user, and the output is user confirmation.

[0133] Step 6:

[0134] The user enters a follow-up question, and the device sends it back to the server. The server then uses the generative AI model to analyze the follow-up question and generate appropriate advice in the same way. The input is the follow-up question, and the output is the follow-up advice.

[0135] Step 7:

[0136] If the server determines that analysis using the generative AI model is difficult, it recommends consulting an expert. In this case, the server sends the expert's contact information and consultation method to the device. The device displays this information on the user interface. The user can contact the expert directly based on the presented information. The input is the expert's recommended information, and the output is a recommendation presented to the user.

[0137] (Application example 1)

[0138] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0139] When conducting electronic transactions, there is a need for a method to quickly and efficiently resolve legal risks and doubts. However, many users lack legal expertise and are often unable to make appropriate decisions when faced with legal issues. Furthermore, when consultation with an expert is necessary, there is a need for a method to smoothly proceed with the procedure. The present invention aims to provide a method for solving these problems.

[0140] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0141] In this invention, the server includes means for receiving a problem entered by a user, means for analyzing the problem, means for searching related legal knowledge and past court case data based on the analyzed problem, means for generating appropriate advice based on the search results, means for presenting the generated advice to the user, means for analyzing legal risks and doubts related to electronic transactions and providing appropriate advice, and means for recommending consultation with an expert when a significant legal issue is detected. This enables users to quickly and appropriately resolve legal issues in electronic transactions and to receive expert help as needed.

[0142] "User" means any person or entity seeking to resolve a legal matter using the System.

[0143] "Means for receiving questions" refers to an interface for sending legal questions entered by a user to a server.

[0144] "Means of problem analysis" refers to the process used to understand the received legal problem and extract the necessary data.

[0145] "Means of searching relevant legal knowledge and past case law data" refers to the process of searching legal databases to gather the necessary information.

[0146] "Means of generating appropriate advice" refers to the process of constructing a solution to a problem based on retrieved legal knowledge and case law data.

[0147] "Means for presenting to the user" refers to an interface for displaying the generated advice on the user's terminal.

[0148] "Electronic commerce" refers to the buying and selling of goods and services conducted over the Internet.

[0149] "Legal risks and doubts" refers to legal issues and uncertainties that arise in connection with electronic transactions.

[0150] "Means for recommending consultation with an expert" refers to the process of referring a user to an appropriate legal expert if the system determines that the problem is difficult to resolve.

[0151] "Server" refers to a central processing unit that receives input data from users, analyzes it, and generates advice.

[0152] MODE FOR CARRYING OUT THE INVENTION

[0153] The present invention is a system for quickly resolving legal risks and doubts in electronic transactions, and is composed of the following elements: The system receives problems entered by users, analyzes them using a generative AI model, and aims to provide appropriate advice and expert recommendations.

[0154] System Configuration

[0155] 1. User's Device

[0156] Hardware: Smartphone (e.g. iPhone, Android device)

[0157] Software: React Native (cross-platform mobile app development)

[0158] 2. Server

[0159] Hardware: Central Processing Unit (e.g. AWS EC2 server)

[0160] software:

[0161] Server-side frameworks: Node.js, Express.js

[0162] Database: MySQL, MongoDB

[0163] Generative AI model: GPT-4 (OpenAI)

[0164] Program processing explanation

[0165] The server solves legal problems through the following series of steps: First, it receives the problem sent from the terminal and analyzes it. Based on the analyzed problem, it searches the database for relevant legal knowledge and past court case data.

[0166] Based on the search results, appropriate advice is generated using a generative AI model (GPT-4) and sent to the device. The user can review the advice on the device and enter a question again if additional information is needed. The server also analyzes the additional questions and generates advice.

[0167] If the generated advice is difficult to resolve, the system will display the contact information of an expert along with a message recommending that the user consult with an expert, allowing the user to quickly and appropriately resolve legal risks and doubts.

[0168] Specific examples

[0169] For example, if a user types a question like "Is the reason for this transaction's decline legitimate?", we generate the following prompt and ask the GPT-4 model:

[0170] Example prompt:

[0171] A user is asking about the legality of reasons for payment denial in an electronic payment transaction. Analyze the user's question, refer to relevant laws and court cases, and generate an answer. If the answer is difficult, include a message recommending that the user seek professional advice.

[0172] The server then sends the generated advice to the terminal, which then displays the advice to the user. In this way, the system provides a means for users to efficiently resolve legal issues related to electronic transactions.

[0173] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0174] Step 1:

[0175] The user inputs a legal problem in text format from a smartphone terminal. The input problem is sent to the server by the terminal. The input of this step is the text data of the user's legal problem, and the output is that the data is sent to the server.

[0176] Step 2:

[0177] The server analyzes the received text data. It uses a generative AI model (GPT-4) to understand the input problem and identify the necessary legal information. The input for this step is the text data of the user's legal problem, and the output is the structured data of the analyzed problem.

[0178] Step 3:

[0179] Based on the analyzed problem, the server searches a database for relevant legal knowledge and past court case data. The database uses MySQL or MongoDB. The input for this step is structured data, and the output is the search results for relevant legal knowledge and court case data.

[0180] Step 4:

[0181] The server generates appropriate advice based on the search results. Using a generative AI model (GPT-4), it derives the optimal solution from the searched legal knowledge and case law data. The input for this step is the search result data, and the output is the generated advice text data.

[0182] Step 5:

[0183] The server sends the generated advice to the terminal, which then displays the advice to the user. The input of this step is the text data of the generated advice, and the output is that the advice is displayed to the user.

[0184] Step 6:

[0185] If the user has additional questions or doubts, they enter the question again and the process is repeated from step 1. The input of this step is the text data of the user's additional question, and the output is sent to the server again.

[0186] Step 7:

[0187] If the server determines that the problem is difficult to solve as a result of analysis using the generative AI model, it recommends consulting an expert. The server generates the expert's contact information and sends it to the device. The device then presents this information to the user. The input to this step is the analysis result of the generative AI model, and the output is a message recommending consultation with an expert.

[0188] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0189] The present invention is a system for easily and quickly resolving legal problems faced by users, and enables the provision of more appropriate advice by taking the user's emotional state into consideration. The system includes means for receiving and analyzing problems entered by the user, means for searching for and generating relevant legal knowledge and past court case data based on the analysis, means for presenting the generated advice to the user, and an emotion engine that recognizes the user's emotions. The system also includes means for using the emotion engine to tailor advice according to the user's emotional state and means for evaluating the user's emotional state and recommending consultation with an expert.

[0190] Overall system configuration

[0191] The system consists of the following components:

[0192] A terminal where users access the system and enter questions

[0193] A server that receives input questions, analyzes them, searches for them, and generates them

[0194] A device that provides advice to users and recognizes their emotional state

[0195] An emotion engine that analyzes the user's emotional state

[0196] Program processing explanation

[0197] In the system of the present invention, the program performs the following processing.

[0198] 1. User registration and login process

[0199] A user accesses the system and registers or logs in. The terminal receives the email address and password entered by the user and sends them to the server. The server checks the database and returns the authentication result.

[0200] 2. Question input and analysis processing

[0201] Users enter legal issues or questions in text format and their devices send the questions to a server, which uses a generative AI model to analyze the issues and search for relevant legal knowledge and past court cases.

[0202] 3. Recognizing emotional states

[0203] The server uses an emotion engine to recognize the user's emotional state through input, facial expression analysis, and voice recognition. Specifically, the emotion engine analyzes the user's input text and voice message and evaluates the user's emotional state.

[0204] 4. Advice Generation and Adjustment

[0205] The server generates appropriate advice based on the analysis results and the user's emotional state. The server adjusts the wording and content of the advice depending on the user's emotional state recognized by the emotion engine.

[0206] 5. Providing answers and user assistance

[0207] The server sends the generated advice to the terminal, which then displays it to the user. The user checks the displayed answer and enters additional questions if more information is needed. The server responds to the additional questions in the same way.

[0208] 6. Recommendation for consultation with a specialist

[0209] If the server determines that the problem is difficult to solve or the user's emotional state is worsening based on the analysis results of the generative AI model and emotion engine, it will recommend consulting an expert. The device will then provide the user with information such as the expert's contact details and how to make an appointment, and the user can then contact the expert directly based on that information.

[0210] Specific examples

[0211] For example, if a user inputs a question such as "There's a problem with the boundary between my land and my neighbor's. How should we resolve it?" and is feeling a strong emotion (e.g., anxiety or anger) at the time, the emotion engine will recognize that emotion. Taking this emotional state into consideration, the server generates advice in a slightly more moderate language, such as "First, try to discuss the matter calmly. If that doesn't resolve the issue, we recommend that you have a land surveyor measure the exact boundary." The server then sends this advice to the device, which then displays it to the user. Furthermore, if the user's emotional state worsens and the problem cannot be resolved, the server will automatically provide information recommending that the user consult an expert.

[0212] In this way, the present invention is a system that provides appropriate solutions to minor legal problems that users have while taking into account their emotional state, and allows them to receive expert support if necessary.

[0213] The processing flow will be explained below.

[0214] Step 1: The user accesses the system.

[0215] Users access the system using terminals.

[0216] Step 2: User registers or logs in.

[0217] The terminal receives the email address and password entered by the user and sends them to the server.

[0218] Step 3: The server authenticates the user information.

[0219] The server checks the received user information against a database and returns the authentication result to the terminal.

[0220] Step 4: The user enters the legal issue.

[0221] Users enter legal questions or problems into the terminal in text format.

[0222] Step 5: The device sends the entered question to the server.

[0223] The terminal transmits the questions entered by the user to the server as text data.

[0224] Step 6: The server analyzes the input problem.

[0225] The server passes the received problem to the generative AI model, which analyzes the problem.

[0226] Step 7: The server searches for relevant legal knowledge and case law data.

[0227] Based on the analysis results, the server searches a database for relevant legal knowledge and past court case data.

[0228] Step 8: The server recognizes the user's emotional state.

[0229] The server uses an emotion engine to analyze the user's emotional state from their input text and voice.

[0230] Step 9: The server generates advice according to the emotional state.

[0231] The server generates appropriate advice based on the search results and the user's emotional state, adjusting the wording and content of the advice.

[0232] Step 10: The server sends the generated advice to the terminal.

[0233] The server transmits the generated advice to the terminal.

[0234] Step 11: The terminal displays the advice to the user.

[0235] The terminal visually displays the received advice to the user.

[0236] Step 12: The user reviews the advice and enters any further questions.

[0237] The user checks the displayed advice and, if they have any additional questions, they enter them again into the terminal.

[0238] Step 13: The terminal sends a follow-up question to the server.

[0239] The terminal sends a follow-up question to the server.

[0240] Step 14: The server again generates analysis and advice for the additional question.

[0241] The server analyzes the additional question, generates advice again, and sends it to the terminal.

[0242] Step 15: If the server determines that the problem is difficult to resolve, it recommends consulting an expert.

[0243] If the server determines through its analysis that the problem is difficult to solve, it generates information recommending that the user consult with an expert.

[0244] Step 16: The terminal displays the expert consultation information to the user.

[0245] The device visually displays to the user contact information for the specialist and how to schedule a consultation.

[0246] Step 17: The user contacts the expert.

[0247] The user can then contact the expert directly based on the displayed information.

[0248] In this way, the system can provide users with appropriate solutions to their legal problems, increase their satisfaction while taking into account their emotional state, and provide them with access to expert assistance when necessary.

[0249] Example 2

[0250] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0251] Users with legal problems need accurate information and appropriate advice to effectively resolve them. However, users' emotional state often gets in the way of resolving the problem, and conventional systems do not provide support that takes their emotional state into account. Furthermore, when a problem is difficult to resolve, it is necessary to seek expert help, but this decision is often left up to the user. This can delay timely expert intervention and further complicate the problem.

[0252] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving a problem input by a user, means for analyzing the problem, means for searching for related legal knowledge and past court case data based on the analyzed problem, means for generating appropriate advice based on the search results, means for presenting the generated advice to the user, means for recognizing the user's emotional state, and means for adjusting the generated advice based on the recognized emotional state. This makes it possible to provide appropriate advice that takes the user's emotional state into consideration, thereby making problem-solving support more effective. Furthermore, if the user's emotional state worsens and the problem becomes difficult to solve, the server recommends consulting an expert, allowing the expert to intervene at an appropriate time.

[0253] "User" means any person or organization seeking to resolve a legal matter using the System.

[0254] "Problems" refer to legal questions, troubles, disputes, and other issues that require resolution and are entered into the system by users.

[0255] "Means of receiving" refers to the functions and devices used to incorporate information entered by users into the system.

[0256] "Means for analyzing" refers to algorithms or programs for understanding the received question and analyzing its content.

[0257] "Searching means" refers to the function for finding relevant legal knowledge and past case law data based on the analyzed problem.

[0258] "Means for generating" refers to the function of creating specific advice to be provided to users based on the analysis results and search results.

[0259] "Presentation means" refers to a device or software feature that displays the generated advice in a user-readable form.

[0260] "Means for recognizing emotional state" refers to technologies and systems that can identify a user's current emotional state from their input, voice, facial expressions, etc.

[0261] "Adjustment" refers to the ability to adaptively change the content and wording of generated advice based on the perceived emotional state.

[0262] "Means to encourage consultation with an expert" refers to a function that encourages users to seek expert help if their problem is deemed difficult to solve.

[0263] This invention is a system for quickly and appropriately resolving legal problems faced by users, and has the function of providing advice that takes into account the user's emotional state. The system receives and analyzes the problem entered by the user, generates and presents advice based on relevant legal knowledge and past court case data, and can also recognize the user's emotional state using an emotion engine and adjust advice accordingly.

[0264] The overall system configuration is as follows:

[0265] 1. The terminal where users access the system and enter questions

[0266] 2. A server that receives input questions, analyzes them, searches for them, and generates them.

[0267] 3. A device that provides advice to users and recognizes their emotional state

[0268] 4. Emotion engine that analyzes the user's emotional state

[0269] When the server receives a legal problem or question in text form entered by the user, it analyzes the problem using a generative AI model (e.g., OpenAI's GPT-4). Based on the analyzed problem, the server searches relevant legal knowledge and past court case data. Next, it generates appropriate advice based on the search results. At this time, the generated advice is adjusted according to the user's emotional state, as recognized by an emotion engine (e.g., IBM Watson's Tone Analyzer).

[0270] As a concrete example, suppose a user inputs the question, "There's a problem regarding the boundary between my land and my neighbor's. How should we resolve it?" In this case, the server uses a generative AI model to analyze the problem and search for relevant legal knowledge and past court cases. At the same time, an emotion engine recognizes emotions such as anxiety or anger from the user's text. The server takes this emotional state into consideration and generates soft-spoken advice such as, "First, try to discuss the matter calmly. If that doesn't resolve the issue, I recommend having a land surveyor measure the exact boundary." The server sends this advice to the device, which then displays it to the user.

[0271] Furthermore, if the user's emotional state worsens and the problem remains unresolved, the server will automatically recommend consulting a specialist. In this case, the server will generate information such as the specialist's contact details and how to make an appointment, and the device will present this information to the user. This allows the user to smoothly contact the specialist.

[0272] This system responds quickly to even minor legal issues users may have, provides appropriate solutions that take into account their emotional state, and provides comprehensive support for users in resolving legal issues by providing expert assistance as needed.

[0273] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0274] Step 1:

[0275] A user accesses the system. The user enters an email address, password, and other necessary personal information into a new registration form. The device receives this information and sends it to the server. The server stores the received information in a database. The user enters an email address and password into a login form. The device receives the login information and sends it to the server. The server compares it with the database and returns the authentication result to the device. If authentication is successful, the user can proceed to the next step. Specifically, a database search and comparison operation are performed.

[0276] Step 2:

[0277] The user inputs a legal problem or question in text format. The input text is sent by the device to the server. The server receives this text. The server passes the input problem to a generative AI model (for example, OpenAI's GPT-4) as a prompt. The generative AI model analyzes the text. The input here is the user's text question, which is converted into a prompt and then sent to the generative AI model. The output is the analysis result, which may include relevant legal knowledge or past court case data. As a specific example, the question "There is a problem regarding the boundary between my land and the neighbor's land. How should we resolve this?" is sent to the generative AI model as a prompt.

[0278] Step 3:

[0279] The server receives the analysis results and searches for related legal knowledge and past court case data. The server then queries the database and extracts the required data. The input here is the analysis results from the generative AI model, and the output is legal knowledge and past court case data. Specific operations include searching and filtering the database.

[0280] Step 4:

[0281] The server generates appropriate advice based on the search results. The server creates advice according to the guidelines of the generative AI model. In addition, it uses an emotion engine (for example, IBM Watson's Tone Analyzer) to recognize the emotional state from the user's input text or voice message. The input here is the search results and the user's emotional state, and the output is tailored advice. Operations include natural language processing and style adjustment.

[0282] Step 5:

[0283] The server sends the generated advice to the terminal. The terminal displays the advice to the user. The user reviews the advice and enters an additional question if more information is needed. The additional question entered is also sent to the server, where it is parsed and searched again. The input here is the advice from the server, and the output is the advice displayed on the terminal. Operations include sending, receiving, and displaying data.

[0284] Step 6:

[0285] If the server determines that the problem is difficult to solve or the emotional state is worsening based on the analysis results of the generated AI model and the emotion engine, it recommends consulting an expert. The server generates information such as the expert's contact details and reservation methods, and the device presents this to the user. The user then directly contacts the expert based on this information. The input here is the analysis results of the emotion engine and the generated advice, and the output is the expert consultation information. Specific operations include analyzing the emotional state and generating information.

[0286] The above are the processing steps of the program of this system, and each step has detailed inputs and outputs, and specific operations are performed.

[0287] (Application example 2)

[0288] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0289] Conventional legal consultation systems often provide cold advice without taking into account the user's emotional state, further increasing the user's anxiety. Furthermore, they often fail to promptly introduce appropriate experts to difficult problems, resulting in a long wait for users to receive appropriate support. The present invention aims to solve these problems and quickly provide appropriate advice that takes into account the user's emotional state.

[0290] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0291] In this invention, the server includes a means for receiving questions entered by the user, a means for analyzing the questions, and a means for searching relevant legal knowledge and past court case data, thereby enabling the generation of appropriate advice that takes into account the emotional state of the user.

[0292] "User" means any person or entity that uses the System to enter legal issues and seek solutions.

[0293] "Means for receiving questions" is a function that allows users to input legal questions and doubts into the system.

[0294] A "means for analyzing a problem" is a program or algorithm that analyzes the received legal problem and understands its content and intent.

[0295] "Means for searching relevant legal knowledge and past court cases" refers to a function that searches for relevant legal knowledge and past court cases from databases and external information sources based on the analyzed problem.

[0296] A "means for generating appropriate advice" is a program that provides users with specific solutions and guidelines for action based on the retrieved legal knowledge and case law data.

[0297] The "means for presenting advice to the user" is a function for displaying the generated advice on the user's terminal.

[0298] "Emotion analysis means" is a technology for analyzing a user's emotional state from input text, voice, facial expressions, etc.

[0299] The "means for adjusting advice" is a function for adjusting the wording and expression depending on the emotional state of the user recognized by the emotion analysis means.

[0300] A "means for training a generative artificial intelligence model" is a process for training an artificial intelligence model with the data necessary to generate appropriate advice.

[0301] The "means for recommending consultation with an expert" is a function for introducing an appropriate expert to the user when the generated advice is judged to be difficult to resolve.

[0302] The present invention is a system for easily and quickly resolving legal problems that users have, and aims to provide more appropriate advice by taking into account the user's emotional state. Specific embodiments for carrying out the invention are described below.

[0303] Overall system overview

[0304] The system consists of the following main components:

[0305] A terminal for users to input questions

[0306] A server that analyzes input problems, searches for related information, and generates advice

[0307] Emotion engine that recognizes and analyzes emotional states

[0308] Generative AI Model

[0309] System processing overview

[0310] 1. User Registration and Login

[0311] The user accesses the system from a terminal and performs new registration or login. The terminal sends the email address and password entered by the user to the server. The server checks the database and returns the authentication result.

[0312] 2. Problem entry and analysis

[0313] Users input legal questions in text format, and their devices send the questions to a server, which then uses a generative AI model (e.g., GPT-4) to analyze the questions and search for relevant legal knowledge and past court cases.

[0314] 3. Recognizing emotional states

[0315] The server uses an emotion engine (e.g., Google Cloud Natural Language or NVidia Clara) to analyze the user's input text or voice message and recognize their emotional state.

[0316] 4. Advice Generation and Adjustment

[0317] The server generates appropriate advice based on the analysis results and the user's emotional state. The server adjusts the wording and content of the advice depending on the user's emotional state recognized by the emotion engine.

[0318] 5. Providing advice and responding to follow-up questions

[0319] The generated advice is sent to the terminal and displayed to the user. The user can review the displayed answer and enter follow-up questions if they require more information. The server responds to follow-up questions in the same way.

[0320] 6. Recommendation for consultation with a specialist

[0321] If the server determines that the problem is difficult to solve or the user's emotional state is worsening based on the analysis results of the generative AI model and emotion engine, it will recommend consulting an expert. The device will then provide the user with information such as the expert's contact details and how to make an appointment, allowing the user to contact the expert directly.

[0322] Hardware and software used

[0323] Front-end: Smartphone app, smart glasses app

[0324] Backend: Server (using AWS or Google Cloud Platform)

[0325] Sentiment engine: Google Cloud Natural Language, NVidia Clara

[0326] Generative AI model: GPT-4

[0327] Legal database: legal data held in cloud storage

[0328] Specific examples

[0329] For example, if a user types the question "I've been the victim of an internet scam, what should I do?", the emotion analysis method can detect that the user is feeling frustrated. Based on this information, the server generates soft-spoken advice such as "I recommend that you first contact your card company to report the fraud, and then file a police report." This advice is sent to the terminal and displayed to the user.

[0330] Prompt Sentence Examples

[0331] "A legal advice app for smartphones should assess the user's emotional state and generate appropriate advice for questions about internet fraud. If the user is feeling frustrated, examples of advice should include how to contact their credit card company or how to file a police report."

[0332] In this way, the present invention is a system that provides users with quick and appropriate solutions to legal problems while taking into account their emotional state.

[0333] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0334] Step 1:

[0335] User Registration and Login

[0336] A user accesses the system and registers or logs in. The terminal receives the email address and password entered by the user and sends them to the server. The server checks the database and returns the authentication result. This step takes the email address and password as input and returns the authentication result (success or failure) as output.

[0337] Step 2:

[0338] Entering the Question

[0339] The user inputs a legal question in text format, and the terminal sends the question to the server. In this step, the question entered by the user is transferred to the server as is.

[0340] Step 3:

[0341] Problem Analysis

[0342] The server inputs the received problem into a generative AI model (e.g., GPT-4) and analyzes the problem. In this step, the input text data (problem) is analyzed and processed to understand its meaning and intent. The output is the analysis result (what the problem is asking).

[0343] Step 4:

[0344] Search for related information

[0345] Based on the analysis results, the server searches the database for relevant legal knowledge and past court case data. In this step, a search query is generated based on the analysis results and used to filter the legal-related data in the database. The output is a set of relevant information.

[0346] Step 5:

[0347] Recognition of emotional states

[0348] The server uses an emotion engine to analyze the user's emotional state based on the input text. In this step, the input text data is passed through the emotion engine to evaluate the user's emotional state (e.g., anxiety, anger, impatience). The output is the emotion analysis result.

[0349] Step 6:

[0350] Advice generation and adjustment

[0351] The server generates appropriate advice based on the analysis results and the user's emotional state. At this stage, the generative AI model is again used to create specific advice that takes into account the searched information and the user's emotional state. The output is advice text, with the wording and content adjusted depending on the user's emotional state.

[0352] Step 7:

[0353] Providing advice

[0354] The generated advice is sent to the terminal and displayed to the user. In this step, the advice text is sent from the server to the terminal and displayed on the user's screen. The advice generated by the system is received as input and displayed on the user's screen as output.

[0355] Step 8:

[0356] Responding to additional questions

[0357] The user checks the displayed answer and enters an additional question if they have one. This additional question is also sent from the device to the server and processed again. In this step, the user enters the answer again, and the process from step 3 onwards is repeated.

[0358] Step 9:

[0359] Recommendation for consultation with a specialist

[0360] Based on the analysis results of the generative AI model and emotion engine, the server determines that the problem is difficult to solve or the user's emotional state is deteriorating, and recommends consulting an expert. In this step, information on the expert's contact details and how to make an appointment is generated and sent to the device. The user can then contact the expert directly using this information.

[0361] In this way, a system is realized that efficiently and effectively supports legal problem solving, taking into account in detail the specific actions performed at each step and the input and output data.

[0362] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0363] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0364] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0365] [Second embodiment]

[0366] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0367] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0368] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0369] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0370] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0371] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0372] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0373] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0374] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0375] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0376] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0377] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0378] This invention is a system that allows users to easily and quickly resolve legal problems. The system receives and analyzes the problem entered by the user, searches for relevant legal knowledge and past court case data, and generates and presents appropriate advice. It also has a function that recommends consulting an expert if necessary.

[0379] Overall system configuration

[0380] The system mainly consists of the following elements:

[0381] A terminal where users access the system and enter questions

[0382] A server that receives and analyzes input problems, searches for necessary data, and generates advice

[0383] A device that provides advice to users and recommends consulting a specialist

[0384] Program processing explanation

[0385] In the system of the present invention, the program performs the following processing.

[0386] 1. User registration and login process

[0387] A user accesses the system and performs new registration or logs in. The terminal sends the entered user information to the server, which then collates the received information with a database and returns the authentication result.

[0388] 2. Question input and analysis processing

[0389] Users enter legal issues or questions in text format, and their devices send the questions to a server, which uses a generative AI model to analyze the issues and search for relevant legal knowledge and past court cases.

[0390] 3. Providing answers and user assistance

[0391] The server generates advice based on the search results and sends it to the device, which then displays it to the user. The user can review the displayed answers and enter follow-up questions if they require more information. The server also responds to follow-up questions.

[0392] 4. Recommendation for consultation with a specialist

[0393] If the server determines that the generative AI model has difficulty answering a question, it recommends consulting an expert. The device then presents the user with information such as the expert's contact details and how to make a reservation, and the user can then contact the expert directly based on the information provided.

[0394] Specific examples

[0395] For example, suppose a user inputs a question such as, "There is a dispute about the boundary between my land and my neighbor's land. How should I resolve it?" The device sends this question to the server, which analyzes it using a generative AI model. As a result of the analysis, specific advice is generated, such as, "Boundary disputes are generally resolved through mutual discussion, but if that does not work, we recommend that you have the exact boundary measured by a land surveyor." The server sends this advice to the device, which displays it to the user. If the user wants to act on this advice but needs more information, they can input a follow-up question to receive further assistance. If the server answers this follow-up question appropriately but is unable to resolve the issue, information recommending consultation with an expert is displayed.

[0396] Thus, the present invention is a system that allows users to receive prompt and appropriate responses to minor legal issues and, if necessary, receive expert assistance.

[0397] The processing flow will be explained below.

[0398] Step 1: The user accesses the system.

[0399] Users access the system using terminals.

[0400] Step 2: User registers or logs in.

[0401] The device receives the email address and password entered by the user and sends that information to the server.

[0402] Step 3: The server authenticates the user information.

[0403] The server checks the received user information against a database and returns the authentication result to the terminal.

[0404] Step 4: The user enters the legal issue.

[0405] Users enter legal questions or problems into the terminal in text format.

[0406] Step 5: The device sends the entered question to the server.

[0407] The terminal transmits the questions entered by the user to the server as text data.

[0408] Step 6: The server analyzes the input problem.

[0409] The server passes the received problem to the generative AI model, which analyzes the problem.

[0410] Step 7: The server searches for relevant legal knowledge and case law data.

[0411] Based on the analysis results, the server searches a database for relevant legal knowledge and past court case data.

[0412] Step 8: The server generates the appropriate advice.

[0413] The server generates appropriate advice for the user based on the search results.

[0414] Step 9: The server sends the generated advice to the terminal.

[0415] The server transmits the generated advice to the terminal.

[0416] Step 10: The terminal displays the advice to the user.

[0417] The terminal visually displays the received advice to the user.

[0418] Step 11: The user reviews the advice and enters any further questions.

[0419] The user checks the displayed advice and, if they have any additional questions, they enter them again into the terminal.

[0420] Step 12: The terminal sends a follow-up question to the server.

[0421] The terminal sends a follow-up question to the server.

[0422] Step 13: The server again generates analysis and advice for the additional question.

[0423] The server analyzes the additional question, generates advice again, and sends it to the terminal.

[0424] Step 14: If the server determines that the problem is difficult to resolve, it recommends consulting an expert.

[0425] If the server determines through its analysis that the problem is difficult to solve, it generates information recommending that the user consult with an expert.

[0426] Step 15: The terminal displays the expert consultation information to the user.

[0427] The device visually displays to the user contact information for the specialist and how to schedule a consultation.

[0428] Step 16: The user contacts the expert.

[0429] The user can then contact the expert directly based on the displayed information.

[0430] In this way, the system provides users with appropriate solutions to their legal problems and allows them to access expert help if necessary.

[0431] Example 1

[0432] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0433] To provide a system that enables users with legal problems to easily obtain appropriate advice even without specialized knowledge, and to ensure that if the problem is not resolved, the users can quickly seek advice from an expert.

[0434] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0435] In this invention, the server includes means for receiving a problem entered by a user, means for analyzing the problem, means for searching related legal knowledge and past court case data based on the analyzed problem, means for generating appropriate advice based on the search results using a generative AI model, and means for presenting the generated advice to the user. This allows users to easily obtain appropriate advice on legal problems. In addition, if the problem is difficult to solve, the server can recommend consulting an expert, allowing users to quickly receive expert support.

[0436] "User" means any person or entity seeking to resolve a legal matter using the System.

[0437] "Means for receiving questions" refers to the function of sending legal questions or doubts entered by the user to the server through the interface.

[0438] "Means for analyzing the problem" refers to the analytical function used to understand and appropriately handle received legal questions and doubts.

[0439] "Means for searching legal knowledge and past court case data" refers to the function of searching for necessary information from a database of related legal knowledge and past court cases based on the analyzed problem.

[0440] A "generative artificial intelligence model" refers to a model that uses technologies such as natural language processing and machine learning to analyze input text data and generate appropriate advice.

[0441] "Means for generating advice" refers to the function of creating appropriate solutions and advice for users' problems based on searched legal knowledge and case law data.

[0442] "Means for presenting advice" refers to a function for displaying generated advice in an easy-to-understand manner for the user.

[0443] "Means to recommend consulting an expert" refers to a function that provides users with ways to contact or consult with relevant experts when the generative AI model determines that a problem is difficult to solve.

[0444] This invention is a system that allows users to easily and quickly resolve legal problems. The system receives and analyzes the problem entered by the user, searches for relevant legal knowledge and past court case data, and generates and presents appropriate advice. It also has a function that recommends consulting an expert if necessary.

[0445] Overall system configuration

[0446] The system mainly consists of the following components:

[0447] A terminal where users access the system and enter questions

[0448] A server that receives and analyzes input problems, searches for necessary data, and generates advice

[0449] A device that provides advice to users and recommends consulting a specialist

[0450] Program processing overview

[0451] The core of the system is the server, where most data processing and calculations are performed. Specifically, the server uses generative AI models such as "OpenAI GPT-4" and "Google BERT" to analyze legal questions entered by users. The analyzed data is queried against legal knowledge bases and databases of past court cases (e.g., MySQL, PostgreSQL) to search for relevant information. Based on the searched information, the generative AI model creates appropriate advice and sends the results back to the device.

[0452] Hardware and Software Examples

[0453] Processor: For example, the server uses a high-performance processor (e.g., Intel Xeon processor).

[0454] Database: For example, MySQL or PostgreSQL

[0455] AI models: OpenAI GPT-4 and Google BERT

[0456] Communication protocol: HTTP / HTTPS is used to exchange data between the terminal and the server.

[0457] Specific examples

[0458] For example, suppose a user inputs a question such as, "There is a dispute about the boundary between my land and the neighbor's land. How should I resolve it?" The device sends this question to the server, which analyzes it using a generative AI model. As a result of the analysis, specific advice is generated, such as, "It is common for boundary disputes to be resolved through mutual discussion, but if this cannot be resolved, it is recommended that the exact boundary be measured by a land surveyor." The server sends this advice to the device, which then displays it to the user.

[0459] Prompt Sentence Examples

[0460] An example of a prompt for a generative AI model is, "There is a problem regarding the boundary line between my land and my neighbor's land. What should I do if we can't resolve it through discussion?"

[0461] Thus, the present invention is a system that can quickly and appropriately respond to minor legal issues that users have, and can provide expert support as needed.

[0462] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0463] Step 1:

[0464] A user accesses the system and performs new registration or login. The terminal receives the user information entered by the user (e.g., username, password). The terminal sends this information to the server as an HTTP POST request. The server compares the received information with a database (e.g., MySQL, PostgreSQL), generates an authentication result, and returns the result to the terminal. The terminal displays the authentication result to the user, and if successful, transitions to a question input screen. The input is user information, and the output is the authentication result.

[0465] Step 2:

[0466] The user inputs a legal problem or question in text format. This input text is received by the device and sent to the server in JSON format. The input is the text of the legal problem, and the output is the analysis result.

[0467] Step 3:

[0468] The server passes the received text to the generative AI model as a prompt. The generative AI model (e.g., OpenAI GPT-4) analyzes the input problem and understands its content. It then searches for relevant legal knowledge and past court case data. These data are stored in a database. The input is the prompt, and the output is the relevant data.

[0469] Step 4:

[0470] The server generates appropriate advice based on the relevant data analyzed by the generative AI model. This advice is created using data analysis and sentence generation functions by the generative AI model. The generated advice is sent to the device in JSON format. The input is the analysis result, and the output is the generated advice.

[0471] Step 5:

[0472] The terminal displays the received advice on the user interface. The user can confirm the presented advice and, if they have any further questions, they can enter them in an additional text box. The input is the presentation of advice to the user, and the output is user confirmation.

[0473] Step 6:

[0474] The user enters a follow-up question, and the device sends it back to the server. The server then uses the generative AI model to analyze the follow-up question and generate appropriate advice in the same way. The input is the follow-up question, and the output is the follow-up advice.

[0475] Step 7:

[0476] If the server determines that analysis using the generative AI model is difficult, it recommends consulting an expert. In this case, the server sends the expert's contact information and consultation method to the device. The device displays this information on the user interface. The user can contact the expert directly based on the presented information. The input is the expert's recommended information, and the output is a recommendation presented to the user.

[0477] (Application example 1)

[0478] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0479] When conducting electronic transactions, there is a need for a method to quickly and efficiently resolve legal risks and doubts. However, many users lack legal expertise and are often unable to make appropriate decisions when faced with legal issues. Furthermore, when consultation with an expert is necessary, there is a need for a method to smoothly proceed with the procedure. The present invention aims to provide a method for solving these problems.

[0480] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0481] In this invention, the server includes means for receiving a problem entered by a user, means for analyzing the problem, means for searching related legal knowledge and past court case data based on the analyzed problem, means for generating appropriate advice based on the search results, means for presenting the generated advice to the user, means for analyzing legal risks and doubts related to electronic transactions and providing appropriate advice, and means for recommending consultation with an expert when a significant legal issue is detected. This enables users to quickly and appropriately resolve legal issues in electronic transactions and to receive expert help as needed.

[0482] "User" means any person or entity seeking to resolve a legal matter using the System.

[0483] "Means for receiving questions" refers to an interface for sending legal questions entered by a user to a server.

[0484] "Means of problem analysis" refers to the process used to understand the received legal problem and extract the necessary data.

[0485] "Means of searching relevant legal knowledge and past case law data" refers to the process of searching legal databases to gather the necessary information.

[0486] "Means of generating appropriate advice" refers to the process of constructing a solution to a problem based on retrieved legal knowledge and case law data.

[0487] "Means for presenting to the user" refers to an interface for displaying the generated advice on the user's terminal.

[0488] "Electronic commerce" refers to the buying and selling of goods and services conducted over the Internet.

[0489] "Legal risks and doubts" refers to legal issues and uncertainties that arise in connection with electronic transactions.

[0490] "Means for recommending consultation with an expert" refers to the process of referring a user to an appropriate legal expert if the system determines that the problem is difficult to resolve.

[0491] "Server" refers to a central processing unit that receives input data from users, analyzes it, and generates advice.

[0492] MODE FOR CARRYING OUT THE INVENTION

[0493] The present invention is a system for quickly resolving legal risks and doubts in electronic transactions, and is composed of the following elements: The system receives problems entered by users, analyzes them using a generative AI model, and aims to provide appropriate advice and expert recommendations.

[0494] System Configuration

[0495] 1. User's Device

[0496] Hardware: Smartphone (e.g. iPhone, Android device)

[0497] Software: React Native (cross-platform mobile app development)

[0498] 2. Server

[0499] Hardware: Central Processing Unit (e.g. AWS EC2 server)

[0500] software:

[0501] Server-side frameworks: Node.js, Express.js

[0502] Database: MySQL, MongoDB

[0503] Generative AI model: GPT-4 (OpenAI)

[0504] Program processing explanation

[0505] The server solves legal problems through the following series of steps: First, it receives the problem sent from the terminal and analyzes it. Based on the analyzed problem, it searches the database for relevant legal knowledge and past court case data.

[0506] Based on the search results, appropriate advice is generated using a generative AI model (GPT-4) and sent to the device. The user can review the advice on the device and enter a question again if additional information is needed. The server also analyzes the additional questions and generates advice.

[0507] If the generated advice is difficult to resolve, the system will display the contact information of an expert along with a message recommending that the user consult with an expert, allowing the user to quickly and appropriately resolve legal risks and doubts.

[0508] Specific examples

[0509] For example, if a user types a question like "Is the reason for this transaction's decline legitimate?", we generate the following prompt and ask the GPT-4 model:

[0510] Example prompt:

[0511] A user is asking about the legality of reasons for payment denial in an electronic payment transaction. Analyze the user's question, refer to relevant laws and court cases, and generate an answer. If the answer is difficult, include a message recommending that the user seek professional advice.

[0512] The server then sends the generated advice to the terminal, which then displays the advice to the user. In this way, the system provides a means for users to efficiently resolve legal issues related to electronic transactions.

[0513] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0514] Step 1:

[0515] The user inputs a legal problem in text format from a smartphone terminal. The input problem is sent to the server by the terminal. The input of this step is the text data of the user's legal problem, and the output is that the data is sent to the server.

[0516] Step 2:

[0517] The server analyzes the received text data. It uses a generative AI model (GPT-4) to understand the input problem and identify the necessary legal information. The input for this step is the text data of the user's legal problem, and the output is the structured data of the analyzed problem.

[0518] Step 3:

[0519] Based on the analyzed problem, the server searches a database for relevant legal knowledge and past court case data. The database uses MySQL or MongoDB. The input for this step is structured data, and the output is the search results for relevant legal knowledge and court case data.

[0520] Step 4:

[0521] The server generates appropriate advice based on the search results. Using a generative AI model (GPT-4), it derives the optimal solution from the searched legal knowledge and case law data. The input for this step is the search result data, and the output is the generated advice text data.

[0522] Step 5:

[0523] The server sends the generated advice to the terminal, which then displays the advice to the user. The input of this step is the text data of the generated advice, and the output is that the advice is displayed to the user.

[0524] Step 6:

[0525] If the user has additional questions or doubts, they enter the question again and the process is repeated from step 1. The input of this step is the text data of the user's additional question, and the output is sent to the server again.

[0526] Step 7:

[0527] If the server determines that the problem is difficult to solve as a result of analysis using the generative AI model, it recommends consulting an expert. The server generates the expert's contact information and sends it to the device. The device then presents this information to the user. The input to this step is the analysis result of the generative AI model, and the output is a message recommending consultation with an expert.

[0528] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0529] The present invention is a system for easily and quickly resolving legal problems faced by users, and enables the provision of more appropriate advice by taking the user's emotional state into consideration. The system includes means for receiving and analyzing problems entered by the user, means for searching for and generating relevant legal knowledge and past court case data based on the analysis, means for presenting the generated advice to the user, and an emotion engine that recognizes the user's emotions. The system also includes means for using the emotion engine to tailor advice according to the user's emotional state and means for evaluating the user's emotional state and recommending consultation with an expert.

[0530] Overall system configuration

[0531] The system consists of the following components:

[0532] A terminal where users access the system and enter questions

[0533] A server that receives input questions, analyzes them, searches for them, and generates them

[0534] A device that provides advice to users and recognizes their emotional state

[0535] An emotion engine that analyzes the user's emotional state

[0536] Program processing explanation

[0537] In the system of the present invention, the program performs the following processing.

[0538] 1. User registration and login process

[0539] A user accesses the system and registers or logs in. The terminal receives the email address and password entered by the user and sends them to the server. The server checks the database and returns the authentication result.

[0540] 2. Question input and analysis processing

[0541] Users enter legal issues or questions in text format and their devices send the questions to a server, which uses a generative AI model to analyze the issues and search for relevant legal knowledge and past court cases.

[0542] 3. Recognizing emotional states

[0543] The server uses an emotion engine to recognize the user's emotional state through input, facial expression analysis, and voice recognition. Specifically, the emotion engine analyzes the user's input text and voice message and evaluates the user's emotional state.

[0544] 4. Advice Generation and Adjustment

[0545] The server generates appropriate advice based on the analysis results and the user's emotional state. The server adjusts the wording and content of the advice depending on the user's emotional state recognized by the emotion engine.

[0546] 5. Providing answers and user assistance

[0547] The server sends the generated advice to the terminal, which then displays it to the user. The user checks the displayed answer and enters additional questions if more information is needed. The server responds to the additional questions in the same way.

[0548] 6. Recommendation for consultation with a specialist

[0549] If the server determines that the problem is difficult to solve or the user's emotional state is worsening based on the analysis results of the generative AI model and emotion engine, it will recommend consulting an expert. The device will then provide the user with information such as the expert's contact details and how to make an appointment, and the user can then contact the expert directly based on that information.

[0550] Specific examples

[0551] For example, if a user inputs a question such as "There's a problem with the boundary between my land and my neighbor's. How should we resolve it?" and is feeling a strong emotion (e.g., anxiety or anger) at the time, the emotion engine will recognize that emotion. Taking this emotional state into consideration, the server generates advice in a slightly more moderate language, such as "First, try to discuss the matter calmly. If that doesn't resolve the issue, we recommend that you have a land surveyor measure the exact boundary." The server then sends this advice to the device, which then displays it to the user. Furthermore, if the user's emotional state worsens and the problem cannot be resolved, the server will automatically provide information recommending that the user consult an expert.

[0552] In this way, the present invention is a system that provides appropriate solutions to minor legal problems that users have while taking into account their emotional state, and allows them to receive expert support if necessary.

[0553] The processing flow will be explained below.

[0554] Step 1: The user accesses the system.

[0555] Users access the system using terminals.

[0556] Step 2: User registers or logs in.

[0557] The terminal receives the email address and password entered by the user and sends them to the server.

[0558] Step 3: The server authenticates the user information.

[0559] The server checks the received user information against a database and returns the authentication result to the terminal.

[0560] Step 4: The user enters the legal issue.

[0561] Users enter legal questions or problems into the terminal in text format.

[0562] Step 5: The device sends the entered question to the server.

[0563] The terminal transmits the questions entered by the user to the server as text data.

[0564] Step 6: The server analyzes the input problem.

[0565] The server passes the received problem to the generative AI model, which analyzes the problem.

[0566] Step 7: The server searches for relevant legal knowledge and case law data.

[0567] Based on the analysis results, the server searches a database for relevant legal knowledge and past court case data.

[0568] Step 8: The server recognizes the user's emotional state.

[0569] The server uses an emotion engine to analyze the user's emotional state from their input text and voice.

[0570] Step 9: The server generates advice according to the emotional state.

[0571] The server generates appropriate advice based on the search results and the user's emotional state, adjusting the wording and content of the advice.

[0572] Step 10: The server sends the generated advice to the terminal.

[0573] The server transmits the generated advice to the terminal.

[0574] Step 11: The terminal displays the advice to the user.

[0575] The terminal visually displays the received advice to the user.

[0576] Step 12: The user reviews the advice and enters any further questions.

[0577] The user checks the displayed advice and, if they have any additional questions, they enter them again into the terminal.

[0578] Step 13: The terminal sends a follow-up question to the server.

[0579] The terminal sends a follow-up question to the server.

[0580] Step 14: The server again generates analysis and advice for the additional question.

[0581] The server analyzes the additional question, generates advice again, and sends it to the terminal.

[0582] Step 15: If the server determines that the problem is difficult to resolve, it recommends consulting an expert.

[0583] If the server determines through its analysis that the problem is difficult to solve, it generates information recommending that the user consult with an expert.

[0584] Step 16: The terminal displays the expert consultation information to the user.

[0585] The device visually displays to the user contact information for the specialist and how to schedule a consultation.

[0586] Step 17: The user contacts the expert.

[0587] The user can then contact the expert directly based on the displayed information.

[0588] In this way, the system can provide users with appropriate solutions to their legal problems, increase their satisfaction while taking into account their emotional state, and provide them with access to expert assistance when necessary.

[0589] Example 2

[0590] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0591] Users with legal problems need accurate information and appropriate advice to effectively resolve them. However, users' emotional state often gets in the way of resolving the problem, and conventional systems do not provide support that takes their emotional state into account. Furthermore, when a problem is difficult to resolve, it is necessary to seek expert help, but this decision is often left up to the user. This can delay timely expert intervention and further complicate the problem.

[0592] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving a problem input by a user, means for analyzing the problem, means for searching for related legal knowledge and past court case data based on the analyzed problem, means for generating appropriate advice based on the search results, means for presenting the generated advice to the user, means for recognizing the user's emotional state, and means for adjusting the generated advice based on the recognized emotional state. This makes it possible to provide appropriate advice that takes the user's emotional state into consideration, thereby making problem-solving support more effective. Furthermore, if the user's emotional state worsens and the problem becomes difficult to solve, the server recommends consulting an expert, allowing the expert to intervene at an appropriate time.

[0593] "User" means any person or organization seeking to resolve a legal matter using the System.

[0594] "Problems" refer to legal questions, troubles, disputes, and other issues that require resolution and are entered into the system by users.

[0595] "Means of receiving" refers to the functions and devices used to incorporate information entered by users into the system.

[0596] "Means for analyzing" refers to algorithms or programs for understanding the received question and analyzing its content.

[0597] "Searching means" refers to the function for finding relevant legal knowledge and past case law data based on the analyzed problem.

[0598] "Means for generating" refers to the function of creating specific advice to be provided to users based on the analysis results and search results.

[0599] "Presentation means" refers to a device or software feature that displays the generated advice in a user-readable form.

[0600] "Means for recognizing emotional state" refers to technologies and systems that can identify a user's current emotional state from their input, voice, facial expressions, etc.

[0601] "Adjustment" refers to the ability to adaptively change the content and wording of generated advice based on the perceived emotional state.

[0602] "Means to encourage consultation with an expert" refers to a function that encourages users to seek expert help if their problem is deemed difficult to solve.

[0603] This invention is a system for quickly and appropriately resolving legal problems faced by users, and has the function of providing advice that takes into account the user's emotional state. The system receives and analyzes the problem entered by the user, generates and presents advice based on relevant legal knowledge and past court case data, and can also recognize the user's emotional state using an emotion engine and adjust advice accordingly.

[0604] The overall system configuration is as follows:

[0605] 1. The terminal where users access the system and enter questions

[0606] 2. A server that receives input questions, analyzes them, searches for them, and generates them.

[0607] 3. A device that provides advice to users and recognizes their emotional state

[0608] 4. Emotion engine that analyzes the user's emotional state

[0609] When the server receives a legal problem or question in text form entered by the user, it analyzes the problem using a generative AI model (e.g., OpenAI's GPT-4). Based on the analyzed problem, the server searches relevant legal knowledge and past court case data. Next, it generates appropriate advice based on the search results. At this time, the generated advice is adjusted according to the user's emotional state, as recognized by an emotion engine (e.g., IBM Watson's Tone Analyzer).

[0610] As a concrete example, suppose a user inputs the question, "There's a problem regarding the boundary between my land and my neighbor's. How should we resolve it?" In this case, the server uses a generative AI model to analyze the problem and search for relevant legal knowledge and past court cases. At the same time, an emotion engine recognizes emotions such as anxiety or anger from the user's text. The server takes this emotional state into consideration and generates soft-spoken advice such as, "First, try to discuss the matter calmly. If that doesn't resolve the issue, I recommend having a land surveyor measure the exact boundary." The server sends this advice to the device, which then displays it to the user.

[0611] Furthermore, if the user's emotional state worsens and the problem remains unresolved, the server will automatically recommend consulting a specialist. In this case, the server will generate information such as the specialist's contact details and how to make an appointment, and the device will present this information to the user. This allows the user to smoothly contact the specialist.

[0612] This system responds quickly to even minor legal issues users may have, provides appropriate solutions that take into account their emotional state, and provides comprehensive support for users in resolving legal issues by providing expert assistance as needed.

[0613] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0614] Step 1:

[0615] A user accesses the system. The user enters an email address, password, and other necessary personal information into a new registration form. The device receives this information and sends it to the server. The server stores the received information in a database. The user enters an email address and password into a login form. The device receives the login information and sends it to the server. The server compares it with the database and returns the authentication result to the device. If authentication is successful, the user can proceed to the next step. Specifically, a database search and comparison operation are performed.

[0616] Step 2:

[0617] The user inputs a legal problem or question in text format. The input text is sent by the device to the server. The server receives this text. The server passes the input problem to a generative AI model (for example, OpenAI's GPT-4) as a prompt. The generative AI model analyzes the text. The input here is the user's text question, which is converted into a prompt and then sent to the generative AI model. The output is the analysis result, which may include relevant legal knowledge or past court case data. As a specific example, the question "There is a problem regarding the boundary between my land and the neighbor's land. How should we resolve this?" is sent to the generative AI model as a prompt.

[0618] Step 3:

[0619] The server receives the analysis results and searches for related legal knowledge and past court case data. The server then queries the database and extracts the required data. The input here is the analysis results from the generative AI model, and the output is legal knowledge and past court case data. Specific operations include searching and filtering the database.

[0620] Step 4:

[0621] The server generates appropriate advice based on the search results. The server creates advice according to the guidelines of the generative AI model. In addition, it uses an emotion engine (for example, IBM Watson's Tone Analyzer) to recognize the emotional state from the user's input text or voice message. The input here is the search results and the user's emotional state, and the output is tailored advice. Operations include natural language processing and style adjustment.

[0622] Step 5:

[0623] The server sends the generated advice to the terminal. The terminal displays the advice to the user. The user reviews the advice and enters an additional question if more information is needed. The additional question entered is also sent to the server, where it is parsed and searched again. The input here is the advice from the server, and the output is the advice displayed on the terminal. Operations include sending, receiving, and displaying data.

[0624] Step 6:

[0625] If the server determines that the problem is difficult to solve or the emotional state is worsening based on the analysis results of the generated AI model and the emotion engine, it recommends consulting an expert. The server generates information such as the expert's contact details and reservation methods, and the device presents this to the user. The user then directly contacts the expert based on this information. The input here is the analysis results of the emotion engine and the generated advice, and the output is the expert consultation information. Specific operations include analyzing the emotional state and generating information.

[0626] The above are the processing steps of the program of this system, and each step has detailed inputs and outputs, and specific operations are performed.

[0627] (Application example 2)

[0628] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0629] Conventional legal consultation systems often provide cold advice without taking into account the user's emotional state, further increasing the user's anxiety. Furthermore, they often fail to promptly introduce appropriate experts to difficult problems, resulting in a long wait for users to receive appropriate support. The present invention aims to solve these problems and quickly provide appropriate advice that takes into account the user's emotional state.

[0630] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0631] In this invention, the server includes a means for receiving questions entered by the user, a means for analyzing the questions, and a means for searching relevant legal knowledge and past court case data, thereby enabling the generation of appropriate advice that takes into account the emotional state of the user.

[0632] "User" means any person or entity that uses the System to enter legal issues and seek solutions.

[0633] "Means for receiving questions" is a function that allows users to input legal questions and doubts into the system.

[0634] A "means for analyzing a problem" is a program or algorithm that analyzes the received legal problem and understands its content and intent.

[0635] "Means for searching relevant legal knowledge and past court cases" refers to a function that searches for relevant legal knowledge and past court cases from databases and external information sources based on the analyzed problem.

[0636] A "means for generating appropriate advice" is a program that provides users with specific solutions and guidelines for action based on the retrieved legal knowledge and case law data.

[0637] The "means for presenting advice to the user" is a function for displaying the generated advice on the user's terminal.

[0638] "Emotion analysis means" is a technology for analyzing a user's emotional state from input text, voice, facial expressions, etc.

[0639] The "means for adjusting advice" is a function for adjusting the wording and expression depending on the emotional state of the user recognized by the emotion analysis means.

[0640] A "means for training a generative artificial intelligence model" is a process for training an artificial intelligence model with the data necessary to generate appropriate advice.

[0641] The "means for recommending consultation with an expert" is a function for introducing an appropriate expert to the user when the generated advice is judged to be difficult to resolve.

[0642] The present invention is a system for easily and quickly resolving legal problems that users have, and aims to provide more appropriate advice by taking into account the user's emotional state. Specific embodiments for carrying out the invention are described below.

[0643] Overall system overview

[0644] The system consists of the following main components:

[0645] A terminal for users to input questions

[0646] A server that analyzes input problems, searches for related information, and generates advice

[0647] Emotion engine that recognizes and analyzes emotional states

[0648] Generative AI Model

[0649] System processing overview

[0650] 1. User Registration and Login

[0651] The user accesses the system from a terminal and performs new registration or login. The terminal sends the email address and password entered by the user to the server. The server checks the database and returns the authentication result.

[0652] 2. Problem entry and analysis

[0653] Users input legal questions in text format, and their devices send the questions to a server, which then uses a generative AI model (e.g., GPT-4) to analyze the questions and search for relevant legal knowledge and past court cases.

[0654] 3. Recognizing emotional states

[0655] The server uses an emotion engine (e.g., Google Cloud Natural Language or NVidia Clara) to analyze the user's input text or voice message and recognize their emotional state.

[0656] 4. Advice Generation and Adjustment

[0657] The server generates appropriate advice based on the analysis results and the user's emotional state. The server adjusts the wording and content of the advice depending on the user's emotional state recognized by the emotion engine.

[0658] 5. Providing advice and responding to follow-up questions

[0659] The generated advice is sent to the terminal and displayed to the user. The user can review the displayed answer and enter follow-up questions if they require more information. The server responds to follow-up questions in the same way.

[0660] 6. Recommendation for consultation with a specialist

[0661] If the server determines that the problem is difficult to solve or the user's emotional state is worsening based on the analysis results of the generative AI model and emotion engine, it will recommend consulting an expert. The device will then provide the user with information such as the expert's contact details and how to make an appointment, allowing the user to contact the expert directly.

[0662] Hardware and software used

[0663] Front-end: Smartphone app, smart glasses app

[0664] Backend: Server (using AWS or Google Cloud Platform)

[0665] Sentiment engine: Google Cloud Natural Language, NVidia Clara

[0666] Generative AI model: GPT-4

[0667] Legal database: legal data held in cloud storage

[0668] Specific examples

[0669] For example, if a user types the question "I've been the victim of an internet scam, what should I do?", the emotion analysis method can detect that the user is feeling frustrated. Based on this information, the server generates soft-spoken advice such as "I recommend that you first contact your card company to report the fraud, and then file a police report." This advice is sent to the terminal and displayed to the user.

[0670] Prompt Sentence Examples

[0671] "A legal advice app for smartphones should assess the user's emotional state and generate appropriate advice for questions about internet fraud. If the user is feeling frustrated, examples of advice should include how to contact their credit card company or how to file a police report."

[0672] In this way, the present invention is a system that provides users with quick and appropriate solutions to legal problems while taking into account their emotional state.

[0673] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0674] Step 1:

[0675] User Registration and Login

[0676] A user accesses the system and registers or logs in. The terminal receives the email address and password entered by the user and sends them to the server. The server checks the database and returns the authentication result. This step takes the email address and password as input and returns the authentication result (success or failure) as output.

[0677] Step 2:

[0678] Entering the Question

[0679] The user inputs a legal question in text format, and the terminal sends the question to the server. In this step, the question entered by the user is transferred to the server as is.

[0680] Step 3:

[0681] Problem Analysis

[0682] The server inputs the received problem into a generative AI model (e.g., GPT-4) and analyzes the problem. In this step, the input text data (problem) is analyzed and processed to understand its meaning and intent. The output is the analysis result (what the problem is asking).

[0683] Step 4:

[0684] Search for related information

[0685] Based on the analysis results, the server searches the database for relevant legal knowledge and past court case data. In this step, a search query is generated based on the analysis results and used to filter the legal-related data in the database. The output is a set of relevant information.

[0686] Step 5:

[0687] Recognition of emotional states

[0688] The server uses an emotion engine to analyze the user's emotional state based on the input text. In this step, the input text data is passed through the emotion engine to evaluate the user's emotional state (e.g., anxiety, anger, impatience). The output is the emotion analysis result.

[0689] Step 6:

[0690] Advice generation and adjustment

[0691] The server generates appropriate advice based on the analysis results and the user's emotional state. At this stage, the generative AI model is again used to create specific advice that takes into account the searched information and the user's emotional state. The output is advice text, with the wording and content adjusted depending on the user's emotional state.

[0692] Step 7:

[0693] Providing advice

[0694] The generated advice is sent to the terminal and displayed to the user. In this step, the advice text is sent from the server to the terminal and displayed on the user's screen. The advice generated by the system is received as input and displayed on the user's screen as output.

[0695] Step 8:

[0696] Responding to additional questions

[0697] The user checks the displayed answer and enters an additional question if they have one. This additional question is also sent from the device to the server and processed again. In this step, the user enters the answer again, and the process from step 3 onwards is repeated.

[0698] Step 9:

[0699] Recommendation for consultation with a specialist

[0700] Based on the analysis results of the generative AI model and emotion engine, the server determines that the problem is difficult to solve or the user's emotional state is deteriorating, and recommends consulting an expert. In this step, information on the expert's contact details and how to make an appointment is generated and sent to the device. The user can then contact the expert directly using this information.

[0701] In this way, a system is realized that efficiently and effectively supports legal problem solving, taking into account in detail the specific actions performed at each step and the input and output data.

[0702] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0703] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0704] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0705] [Third embodiment]

[0706] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0707] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0708] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0709] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0710] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0711] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0712] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0713] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0714] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0715] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0716] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0717] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0718] This invention is a system that allows users to easily and quickly resolve legal problems. The system receives and analyzes the problem entered by the user, searches for relevant legal knowledge and past court case data, and generates and presents appropriate advice. It also has a function that recommends consulting an expert if necessary.

[0719] Overall system configuration

[0720] The system mainly consists of the following elements:

[0721] A terminal where users access the system and enter questions

[0722] A server that receives and analyzes input problems, searches for necessary data, and generates advice

[0723] A device that provides advice to users and recommends consulting a specialist

[0724] Program processing explanation

[0725] In the system of the present invention, the program performs the following processing.

[0726] 1. User registration and login process

[0727] A user accesses the system and performs new registration or logs in. The terminal sends the entered user information to the server, which then collates the received information with a database and returns the authentication result.

[0728] 2. Question input and analysis processing

[0729] Users enter legal issues or questions in text format, and their devices send the questions to a server, which uses a generative AI model to analyze the issues and search for relevant legal knowledge and past court cases.

[0730] 3. Providing answers and user assistance

[0731] The server generates advice based on the search results and sends it to the device, which then displays it to the user. The user can review the displayed answers and enter follow-up questions if they require more information. The server also responds to follow-up questions.

[0732] 4. Recommendation for consultation with a specialist

[0733] If the server determines that the generative AI model has difficulty answering a question, it recommends consulting an expert. The device then presents the user with information such as the expert's contact details and how to make a reservation, and the user can then contact the expert directly based on the information provided.

[0734] Specific examples

[0735] For example, suppose a user inputs a question such as, "There is a dispute about the boundary between my land and my neighbor's land. How should I resolve it?" The device sends this question to the server, which analyzes it using a generative AI model. As a result of the analysis, specific advice is generated, such as, "Boundary disputes are generally resolved through mutual discussion, but if that does not work, we recommend that you have the exact boundary measured by a land surveyor." The server sends this advice to the device, which displays it to the user. If the user wants to act on this advice but needs more information, they can input a follow-up question to receive further assistance. If the server answers this follow-up question appropriately but is unable to resolve the issue, information recommending consultation with an expert is displayed.

[0736] Thus, the present invention is a system that allows users to receive prompt and appropriate responses to minor legal issues and, if necessary, receive expert assistance.

[0737] The processing flow will be explained below.

[0738] Step 1: The user accesses the system.

[0739] Users access the system using terminals.

[0740] Step 2: User registers or logs in.

[0741] The device receives the email address and password entered by the user and sends that information to the server.

[0742] Step 3: The server authenticates the user information.

[0743] The server checks the received user information against a database and returns the authentication result to the terminal.

[0744] Step 4: The user enters the legal issue.

[0745] Users enter legal questions or problems into the terminal in text format.

[0746] Step 5: The device sends the entered question to the server.

[0747] The terminal transmits the questions entered by the user to the server as text data.

[0748] Step 6: The server analyzes the input problem.

[0749] The server passes the received problem to the generative AI model, which analyzes the problem.

[0750] Step 7: The server searches for relevant legal knowledge and case law data.

[0751] Based on the analysis results, the server searches a database for relevant legal knowledge and past court case data.

[0752] Step 8: The server generates the appropriate advice.

[0753] The server generates appropriate advice for the user based on the search results.

[0754] Step 9: The server sends the generated advice to the terminal.

[0755] The server transmits the generated advice to the terminal.

[0756] Step 10: The terminal displays the advice to the user.

[0757] The terminal visually displays the received advice to the user.

[0758] Step 11: The user reviews the advice and enters any further questions.

[0759] The user checks the displayed advice and, if they have any additional questions, they enter them again into the terminal.

[0760] Step 12: The terminal sends a follow-up question to the server.

[0761] The terminal sends a follow-up question to the server.

[0762] Step 13: The server again generates analysis and advice for the additional question.

[0763] The server analyzes the additional question, generates advice again, and sends it to the terminal.

[0764] Step 14: If the server determines that the problem is difficult to resolve, it recommends consulting an expert.

[0765] If the server determines through its analysis that the problem is difficult to solve, it generates information recommending that the user consult with an expert.

[0766] Step 15: The terminal displays the expert consultation information to the user.

[0767] The device visually displays to the user contact information for the specialist and how to schedule a consultation.

[0768] Step 16: The user contacts the expert.

[0769] The user can then contact the expert directly based on the displayed information.

[0770] In this way, the system provides users with appropriate solutions to their legal problems and allows them to access expert help if necessary.

[0771] Example 1

[0772] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0773] To provide a system that enables users with legal problems to easily obtain appropriate advice even without specialized knowledge, and to ensure that if the problem is not resolved, the users can quickly seek advice from an expert.

[0774] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0775] In this invention, the server includes means for receiving a problem entered by a user, means for analyzing the problem, means for searching related legal knowledge and past court case data based on the analyzed problem, means for generating appropriate advice based on the search results using a generative AI model, and means for presenting the generated advice to the user. This allows users to easily obtain appropriate advice on legal problems. In addition, if the problem is difficult to solve, the server can recommend consulting an expert, allowing users to quickly receive expert support.

[0776] "User" means any person or entity seeking to resolve a legal matter using the System.

[0777] "Means for receiving questions" refers to the function of sending legal questions or doubts entered by the user to the server through the interface.

[0778] "Means for analyzing the problem" refers to the analytical function used to understand and appropriately handle received legal questions and doubts.

[0779] "Means for searching legal knowledge and past court case data" refers to the function of searching for necessary information from a database of related legal knowledge and past court cases based on the analyzed problem.

[0780] A "generative artificial intelligence model" refers to a model that uses technologies such as natural language processing and machine learning to analyze input text data and generate appropriate advice.

[0781] "Means for generating advice" refers to the function of creating appropriate solutions and advice for users' problems based on searched legal knowledge and case law data.

[0782] "Means for presenting advice" refers to a function for displaying generated advice in an easy-to-understand manner for the user.

[0783] "Means to recommend consulting an expert" refers to a function that provides users with ways to contact or consult with relevant experts when the generative AI model determines that a problem is difficult to solve.

[0784] This invention is a system that allows users to easily and quickly resolve legal problems. The system receives and analyzes the problem entered by the user, searches for relevant legal knowledge and past court case data, and generates and presents appropriate advice. It also has a function that recommends consulting an expert if necessary.

[0785] Overall system configuration

[0786] The system mainly consists of the following components:

[0787] A terminal where users access the system and enter questions

[0788] A server that receives and analyzes input problems, searches for necessary data, and generates advice

[0789] A device that provides advice to users and recommends consulting a specialist

[0790] Program processing overview

[0791] The core of the system is the server, where most data processing and calculations are performed. Specifically, the server uses generative AI models such as "OpenAI GPT-4" and "Google BERT" to analyze legal questions entered by users. The analyzed data is queried against legal knowledge bases and databases of past court cases (e.g., MySQL, PostgreSQL) to search for relevant information. Based on the searched information, the generative AI model creates appropriate advice and sends the results back to the device.

[0792] Hardware and Software Examples

[0793] Processor: For example, the server uses a high-performance processor (e.g., Intel Xeon processor).

[0794] Database: For example, MySQL or PostgreSQL

[0795] AI models: OpenAI GPT-4 and Google BERT

[0796] Communication protocol: HTTP / HTTPS is used to exchange data between the terminal and the server.

[0797] Specific examples

[0798] For example, suppose a user inputs a question such as, "There is a dispute about the boundary between my land and the neighbor's land. How should I resolve it?" The device sends this question to the server, which analyzes it using a generative AI model. As a result of the analysis, specific advice is generated, such as, "It is common for boundary disputes to be resolved through mutual discussion, but if this cannot be resolved, it is recommended that the exact boundary be measured by a land surveyor." The server sends this advice to the device, which then displays it to the user.

[0799] Prompt Sentence Examples

[0800] An example of a prompt for a generative AI model is, "There is a problem regarding the boundary line between my land and my neighbor's land. What should I do if we can't resolve it through discussion?"

[0801] Thus, the present invention is a system that can quickly and appropriately respond to minor legal issues that users have, and can provide expert support as needed.

[0802] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0803] Step 1:

[0804] A user accesses the system and performs new registration or login. The terminal receives the user information entered by the user (e.g., username, password). The terminal sends this information to the server as an HTTP POST request. The server compares the received information with a database (e.g., MySQL, PostgreSQL), generates an authentication result, and returns the result to the terminal. The terminal displays the authentication result to the user, and if successful, transitions to a question input screen. The input is user information, and the output is the authentication result.

[0805] Step 2:

[0806] The user inputs a legal problem or question in text format. This input text is received by the device and sent to the server in JSON format. The input is the text of the legal problem, and the output is the analysis result.

[0807] Step 3:

[0808] The server passes the received text to the generative AI model as a prompt. The generative AI model (e.g., OpenAI GPT-4) analyzes the input problem and understands its content. It then searches for relevant legal knowledge and past court case data. These data are stored in a database. The input is the prompt, and the output is the relevant data.

[0809] Step 4:

[0810] The server generates appropriate advice based on the relevant data analyzed by the generative AI model. This advice is created using data analysis and sentence generation functions by the generative AI model. The generated advice is sent to the device in JSON format. The input is the analysis result, and the output is the generated advice.

[0811] Step 5:

[0812] The terminal displays the received advice on the user interface. The user can confirm the presented advice and, if they have any further questions, they can enter them in an additional text box. The input is the presentation of advice to the user, and the output is user confirmation.

[0813] Step 6:

[0814] The user enters a follow-up question, and the device sends it back to the server. The server then uses the generative AI model to analyze the follow-up question and generate appropriate advice in the same way. The input is the follow-up question, and the output is the follow-up advice.

[0815] Step 7:

[0816] If the server determines that analysis using the generative AI model is difficult, it recommends consulting an expert. In this case, the server sends the expert's contact information and consultation method to the device. The device displays this information on the user interface. The user can contact the expert directly based on the presented information. The input is the expert's recommended information, and the output is a recommendation presented to the user.

[0817] (Application example 1)

[0818] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0819] When conducting electronic transactions, there is a need for a method to quickly and efficiently resolve legal risks and doubts. However, many users lack legal expertise and are often unable to make appropriate decisions when faced with legal issues. Furthermore, when consultation with an expert is necessary, there is a need for a method to smoothly proceed with the procedure. The present invention aims to provide a method for solving these problems.

[0820] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0821] In this invention, the server includes means for receiving a problem entered by a user, means for analyzing the problem, means for searching related legal knowledge and past court case data based on the analyzed problem, means for generating appropriate advice based on the search results, means for presenting the generated advice to the user, means for analyzing legal risks and doubts related to electronic transactions and providing appropriate advice, and means for recommending consultation with an expert when a significant legal issue is detected. This enables users to quickly and appropriately resolve legal issues in electronic transactions and to receive expert help as needed.

[0822] "User" means any person or entity seeking to resolve a legal matter using the System.

[0823] "Means for receiving questions" refers to an interface for sending legal questions entered by a user to a server.

[0824] "Means of problem analysis" refers to the process used to understand the received legal problem and extract the necessary data.

[0825] "Means of searching relevant legal knowledge and past case law data" refers to the process of searching legal databases to gather the necessary information.

[0826] "Means of generating appropriate advice" refers to the process of constructing a solution to a problem based on retrieved legal knowledge and case law data.

[0827] "Means for presenting to the user" refers to an interface for displaying the generated advice on the user's terminal.

[0828] "Electronic commerce" refers to the buying and selling of goods and services conducted over the Internet.

[0829] "Legal risks and doubts" refers to legal issues and uncertainties that arise in connection with electronic transactions.

[0830] "Means for recommending consultation with an expert" refers to the process of referring a user to an appropriate legal expert if the system determines that the problem is difficult to resolve.

[0831] "Server" refers to a central processing unit that receives input data from users, analyzes it, and generates advice.

[0832] MODE FOR CARRYING OUT THE INVENTION

[0833] The present invention is a system for quickly resolving legal risks and doubts in electronic transactions, and is composed of the following elements: The system receives problems entered by users, analyzes them using a generative AI model, and aims to provide appropriate advice and expert recommendations.

[0834] System Configuration

[0835] 1. User's Device

[0836] Hardware: Smartphone (e.g. iPhone, Android device)

[0837] Software: React Native (cross-platform mobile app development)

[0838] 2. Server

[0839] Hardware: Central Processing Unit (e.g. AWS EC2 server)

[0840] software:

[0841] Server-side frameworks: Node.js, Express.js

[0842] Database: MySQL, MongoDB

[0843] Generative AI model: GPT-4 (OpenAI)

[0844] Program processing explanation

[0845] The server solves legal problems through the following series of steps: First, it receives the problem sent from the terminal and analyzes it. Based on the analyzed problem, it searches the database for relevant legal knowledge and past court case data.

[0846] Based on the search results, appropriate advice is generated using a generative AI model (GPT-4) and sent to the device. The user can review the advice on the device and enter a question again if additional information is needed. The server also analyzes the additional questions and generates advice.

[0847] If the generated advice is difficult to resolve, the system will display the contact information of an expert along with a message recommending that the user consult with an expert, allowing the user to quickly and appropriately resolve legal risks and doubts.

[0848] Specific examples

[0849] For example, if a user types a question like "Is the reason for this transaction's decline legitimate?", we generate the following prompt and ask the GPT-4 model:

[0850] Example prompt:

[0851] A user is asking about the legality of reasons for payment denial in an electronic payment transaction. Analyze the user's question, refer to relevant laws and court cases, and generate an answer. If the answer is difficult, include a message recommending that the user seek professional advice.

[0852] The server then sends the generated advice to the terminal, which then displays the advice to the user. In this way, the system provides a means for users to efficiently resolve legal issues related to electronic transactions.

[0853] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0854] Step 1:

[0855] The user inputs a legal problem in text format from a smartphone terminal. The input problem is sent to the server by the terminal. The input of this step is the text data of the user's legal problem, and the output is that the data is sent to the server.

[0856] Step 2:

[0857] The server analyzes the received text data. It uses a generative AI model (GPT-4) to understand the input problem and identify the necessary legal information. The input for this step is the text data of the user's legal problem, and the output is the structured data of the analyzed problem.

[0858] Step 3:

[0859] Based on the analyzed problem, the server searches a database for relevant legal knowledge and past court case data. The database uses MySQL or MongoDB. The input for this step is structured data, and the output is the search results for relevant legal knowledge and court case data.

[0860] Step 4:

[0861] The server generates appropriate advice based on the search results. Using a generative AI model (GPT-4), it derives the optimal solution from the searched legal knowledge and case law data. The input for this step is the search result data, and the output is the generated advice text data.

[0862] Step 5:

[0863] The server sends the generated advice to the terminal, which then displays the advice to the user. The input of this step is the text data of the generated advice, and the output is that the advice is displayed to the user.

[0864] Step 6:

[0865] If the user has additional questions or doubts, they enter the question again and the process is repeated from step 1. The input of this step is the text data of the user's additional question, and the output is sent to the server again.

[0866] Step 7:

[0867] If the server determines that the problem is difficult to solve as a result of analysis using the generative AI model, it recommends consulting an expert. The server generates the expert's contact information and sends it to the device. The device then presents this information to the user. The input to this step is the analysis result of the generative AI model, and the output is a message recommending consultation with an expert.

[0868] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0869] The present invention is a system for easily and quickly resolving legal problems faced by users, and enables the provision of more appropriate advice by taking the user's emotional state into consideration. The system includes means for receiving and analyzing problems entered by the user, means for searching for and generating relevant legal knowledge and past court case data based on the analysis, means for presenting the generated advice to the user, and an emotion engine that recognizes the user's emotions. The system also includes means for using the emotion engine to tailor advice according to the user's emotional state and means for evaluating the user's emotional state and recommending consultation with an expert.

[0870] Overall system configuration

[0871] The system consists of the following components:

[0872] A terminal where users access the system and enter questions

[0873] A server that receives input questions, analyzes them, searches for them, and generates them

[0874] A device that provides advice to users and recognizes their emotional state

[0875] An emotion engine that analyzes the user's emotional state

[0876] Program processing explanation

[0877] In the system of the present invention, the program performs the following processing.

[0878] 1. User registration and login process

[0879] A user accesses the system and registers or logs in. The terminal receives the email address and password entered by the user and sends them to the server. The server checks the database and returns the authentication result.

[0880] 2. Question input and analysis processing

[0881] Users enter legal issues or questions in text format and their devices send the questions to a server, which uses a generative AI model to analyze the issues and search for relevant legal knowledge and past court cases.

[0882] 3. Recognizing emotional states

[0883] The server uses an emotion engine to recognize the user's emotional state through input, facial expression analysis, and voice recognition. Specifically, the emotion engine analyzes the user's input text and voice message and evaluates the user's emotional state.

[0884] 4. Advice Generation and Adjustment

[0885] The server generates appropriate advice based on the analysis results and the user's emotional state. The server adjusts the wording and content of the advice depending on the user's emotional state recognized by the emotion engine.

[0886] 5. Providing answers and user assistance

[0887] The server sends the generated advice to the terminal, which then displays it to the user. The user checks the displayed answer and enters additional questions if more information is needed. The server responds to the additional questions in the same way.

[0888] 6. Recommendation for consultation with a specialist

[0889] If the server determines that the problem is difficult to solve or the user's emotional state is worsening based on the analysis results of the generative AI model and emotion engine, it will recommend consulting an expert. The device will then provide the user with information such as the expert's contact details and how to make an appointment, and the user can then contact the expert directly based on that information.

[0890] Specific examples

[0891] For example, if a user inputs a question such as "There's a problem with the boundary between my land and my neighbor's. How should we resolve it?" and is feeling a strong emotion (e.g., anxiety or anger) at the time, the emotion engine will recognize that emotion. Taking this emotional state into consideration, the server generates advice in a slightly more moderate language, such as "First, try to discuss the matter calmly. If that doesn't resolve the issue, we recommend that you have a land surveyor measure the exact boundary." The server then sends this advice to the device, which then displays it to the user. Furthermore, if the user's emotional state worsens and the problem cannot be resolved, the server will automatically provide information recommending that the user consult an expert.

[0892] In this way, the present invention is a system that provides appropriate solutions to minor legal problems that users have while taking into account their emotional state, and allows them to receive expert support if necessary.

[0893] The processing flow will be explained below.

[0894] Step 1: The user accesses the system.

[0895] Users access the system using terminals.

[0896] Step 2: User registers or logs in.

[0897] The terminal receives the email address and password entered by the user and sends them to the server.

[0898] Step 3: The server authenticates the user information.

[0899] The server checks the received user information against a database and returns the authentication result to the terminal.

[0900] Step 4: The user enters the legal issue.

[0901] Users enter legal questions or problems into the terminal in text format.

[0902] Step 5: The device sends the entered question to the server.

[0903] The terminal transmits the questions entered by the user to the server as text data.

[0904] Step 6: The server analyzes the input problem.

[0905] The server passes the received problem to the generative AI model, which analyzes the problem.

[0906] Step 7: The server searches for relevant legal knowledge and case law data.

[0907] Based on the analysis results, the server searches a database for relevant legal knowledge and past court case data.

[0908] Step 8: The server recognizes the user's emotional state.

[0909] The server uses an emotion engine to analyze the user's emotional state from their input text and voice.

[0910] Step 9: The server generates advice according to the emotional state.

[0911] The server generates appropriate advice based on the search results and the user's emotional state, adjusting the wording and content of the advice.

[0912] Step 10: The server sends the generated advice to the terminal.

[0913] The server transmits the generated advice to the terminal.

[0914] Step 11: The terminal displays the advice to the user.

[0915] The terminal visually displays the received advice to the user.

[0916] Step 12: The user reviews the advice and enters any further questions.

[0917] The user checks the displayed advice and, if they have any additional questions, they enter them again into the terminal.

[0918] Step 13: The terminal sends a follow-up question to the server.

[0919] The terminal sends a follow-up question to the server.

[0920] Step 14: The server again generates analysis and advice for the additional question.

[0921] The server analyzes the additional question, generates advice again, and sends it to the terminal.

[0922] Step 15: If the server determines that the problem is difficult to resolve, it recommends consulting an expert.

[0923] If the server determines through its analysis that the problem is difficult to solve, it generates information recommending that the user consult with an expert.

[0924] Step 16: The terminal displays the expert consultation information to the user.

[0925] The device visually displays to the user contact information for the specialist and how to schedule a consultation.

[0926] Step 17: The user contacts the expert.

[0927] The user can then contact the expert directly based on the displayed information.

[0928] In this way, the system can provide users with appropriate solutions to their legal problems, increase their satisfaction while taking into account their emotional state, and provide them with access to expert assistance when necessary.

[0929] Example 2

[0930] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0931] Users with legal problems need accurate information and appropriate advice to effectively resolve them. However, users' emotional state often gets in the way of resolving the problem, and conventional systems do not provide support that takes their emotional state into account. Furthermore, when a problem is difficult to resolve, it is necessary to seek expert help, but this decision is often left up to the user. This can delay timely expert intervention and further complicate the problem.

[0932] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving a problem input by a user, means for analyzing the problem, means for searching for related legal knowledge and past court case data based on the analyzed problem, means for generating appropriate advice based on the search results, means for presenting the generated advice to the user, means for recognizing the user's emotional state, and means for adjusting the generated advice based on the recognized emotional state. This makes it possible to provide appropriate advice that takes the user's emotional state into consideration, thereby making problem-solving support more effective. Furthermore, if the user's emotional state worsens and the problem becomes difficult to solve, the server recommends consulting an expert, allowing the expert to intervene at an appropriate time.

[0933] "User" means any person or organization seeking to resolve a legal matter using the System.

[0934] "Problems" refer to legal questions, troubles, disputes, and other issues that require resolution and are entered into the system by users.

[0935] "Means of receiving" refers to the functions and devices used to incorporate information entered by users into the system.

[0936] "Means for analyzing" refers to algorithms or programs for understanding the received question and analyzing its content.

[0937] "Searching means" refers to the function for finding relevant legal knowledge and past case law data based on the analyzed problem.

[0938] "Means for generating" refers to the function of creating specific advice to be provided to users based on the analysis results and search results.

[0939] "Presentation means" refers to a device or software feature that displays the generated advice in a user-readable form.

[0940] "Means for recognizing emotional state" refers to technologies and systems that can identify a user's current emotional state from their input, voice, facial expressions, etc.

[0941] "Adjustment" refers to the ability to adaptively change the content and wording of generated advice based on the perceived emotional state.

[0942] "Means to encourage consultation with an expert" refers to a function that encourages users to seek expert help if their problem is deemed difficult to solve.

[0943] This invention is a system for quickly and appropriately resolving legal problems faced by users, and has the function of providing advice that takes into account the user's emotional state. The system receives and analyzes the problem entered by the user, generates and presents advice based on relevant legal knowledge and past court case data, and can also recognize the user's emotional state using an emotion engine and adjust advice accordingly.

[0944] The overall system configuration is as follows:

[0945] 1. The terminal where users access the system and enter questions

[0946] 2. A server that receives input questions, analyzes them, searches for them, and generates them.

[0947] 3. A device that provides advice to users and recognizes their emotional state

[0948] 4. Emotion engine that analyzes the user's emotional state

[0949] When the server receives a legal problem or question in text form entered by the user, it analyzes the problem using a generative AI model (e.g., OpenAI's GPT-4). Based on the analyzed problem, the server searches relevant legal knowledge and past court case data. Next, it generates appropriate advice based on the search results. At this time, the generated advice is adjusted according to the user's emotional state, as recognized by an emotion engine (e.g., IBM Watson's Tone Analyzer).

[0950] As a concrete example, suppose a user inputs the question, "There's a problem regarding the boundary between my land and my neighbor's. How should we resolve it?" In this case, the server uses a generative AI model to analyze the problem and search for relevant legal knowledge and past court cases. At the same time, an emotion engine recognizes emotions such as anxiety or anger from the user's text. The server takes this emotional state into consideration and generates soft-spoken advice such as, "First, try to discuss the matter calmly. If that doesn't resolve the issue, I recommend having a land surveyor measure the exact boundary." The server sends this advice to the device, which then displays it to the user.

[0951] Furthermore, if the user's emotional state worsens and the problem remains unresolved, the server will automatically recommend consulting a specialist. In this case, the server will generate information such as the specialist's contact details and how to make an appointment, and the device will present this information to the user. This allows the user to smoothly contact the specialist.

[0952] This system responds quickly to even minor legal issues users may have, provides appropriate solutions that take into account their emotional state, and provides comprehensive support for users in resolving legal issues by providing expert assistance as needed.

[0953] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0954] Step 1:

[0955] A user accesses the system. The user enters an email address, password, and other necessary personal information into a new registration form. The device receives this information and sends it to the server. The server stores the received information in a database. The user enters an email address and password into a login form. The device receives the login information and sends it to the server. The server compares it with the database and returns the authentication result to the device. If authentication is successful, the user can proceed to the next step. Specifically, a database search and comparison operation are performed.

[0956] Step 2:

[0957] The user inputs a legal problem or question in text format. The input text is sent by the device to the server. The server receives this text. The server passes the input problem to a generative AI model (for example, OpenAI's GPT-4) as a prompt. The generative AI model analyzes the text. The input here is the user's text question, which is converted into a prompt and then sent to the generative AI model. The output is the analysis result, which may include relevant legal knowledge or past court case data. As a specific example, the question "There is a problem regarding the boundary between my land and the neighbor's land. How should we resolve this?" is sent to the generative AI model as a prompt.

[0958] Step 3:

[0959] The server receives the analysis results and searches for related legal knowledge and past court case data. The server then queries the database and extracts the required data. The input here is the analysis results from the generative AI model, and the output is legal knowledge and past court case data. Specific operations include searching and filtering the database.

[0960] Step 4:

[0961] The server generates appropriate advice based on the search results. The server creates advice according to the guidelines of the generative AI model. In addition, it uses an emotion engine (for example, IBM Watson's Tone Analyzer) to recognize the emotional state from the user's input text or voice message. The input here is the search results and the user's emotional state, and the output is tailored advice. Operations include natural language processing and style adjustment.

[0962] Step 5:

[0963] The server sends the generated advice to the terminal. The terminal displays the advice to the user. The user reviews the advice and enters an additional question if more information is needed. The additional question entered is also sent to the server, where it is parsed and searched again. The input here is the advice from the server, and the output is the advice displayed on the terminal. Operations include sending, receiving, and displaying data.

[0964] Step 6:

[0965] If the server determines that the problem is difficult to solve or the emotional state is worsening based on the analysis results of the generated AI model and the emotion engine, it recommends consulting an expert. The server generates information such as the expert's contact details and reservation methods, and the device presents this to the user. The user then directly contacts the expert based on this information. The input here is the analysis results of the emotion engine and the generated advice, and the output is the expert consultation information. Specific operations include analyzing the emotional state and generating information.

[0966] The above are the processing steps of the program of this system, and each step has detailed inputs and outputs, and specific operations are performed.

[0967] (Application example 2)

[0968] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0969] Conventional legal consultation systems often provide cold advice without taking into account the user's emotional state, further increasing the user's anxiety. Furthermore, they often fail to promptly introduce appropriate experts to difficult problems, resulting in a long wait for users to receive appropriate support. The present invention aims to solve these problems and quickly provide appropriate advice that takes into account the user's emotional state.

[0970] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0971] In this invention, the server includes a means for receiving questions entered by the user, a means for analyzing the questions, and a means for searching relevant legal knowledge and past court case data, thereby enabling the generation of appropriate advice that takes into account the emotional state of the user.

[0972] "User" means any person or entity that uses the System to enter legal issues and seek solutions.

[0973] "Means for receiving questions" is a function that allows users to input legal questions and doubts into the system.

[0974] A "means for analyzing a problem" is a program or algorithm that analyzes the received legal problem and understands its content and intent.

[0975] "Means for searching relevant legal knowledge and past court cases" refers to a function that searches for relevant legal knowledge and past court cases from databases and external information sources based on the analyzed problem.

[0976] A "means for generating appropriate advice" is a program that provides users with specific solutions and guidelines for action based on the retrieved legal knowledge and case law data.

[0977] The "means for presenting advice to the user" is a function for displaying the generated advice on the user's terminal.

[0978] "Emotion analysis means" is a technology for analyzing a user's emotional state from input text, voice, facial expressions, etc.

[0979] The "means for adjusting advice" is a function for adjusting the wording and expression depending on the emotional state of the user recognized by the emotion analysis means.

[0980] A "means for training a generative artificial intelligence model" is a process for training an artificial intelligence model with the data necessary to generate appropriate advice.

[0981] The "means for recommending consultation with an expert" is a function for introducing an appropriate expert to the user when the generated advice is judged to be difficult to resolve.

[0982] The present invention is a system for easily and quickly resolving legal problems that users have, and aims to provide more appropriate advice by taking into account the user's emotional state. Specific embodiments for carrying out the invention are described below.

[0983] Overall system overview

[0984] The system consists of the following main components:

[0985] A terminal for users to input questions

[0986] A server that analyzes input problems, searches for related information, and generates advice

[0987] Emotion engine that recognizes and analyzes emotional states

[0988] Generative AI Model

[0989] System processing overview

[0990] 1. User Registration and Login

[0991] The user accesses the system from a terminal and performs new registration or login. The terminal sends the email address and password entered by the user to the server. The server checks the database and returns the authentication result.

[0992] 2. Problem entry and analysis

[0993] Users input legal questions in text format, and their devices send the questions to a server, which then uses a generative AI model (e.g., GPT-4) to analyze the questions and search for relevant legal knowledge and past court cases.

[0994] 3. Recognizing emotional states

[0995] The server uses an emotion engine (e.g., Google Cloud Natural Language or NVidia Clara) to analyze the user's input text or voice message and recognize their emotional state.

[0996] 4. Advice Generation and Adjustment

[0997] The server generates appropriate advice based on the analysis results and the user's emotional state. The server adjusts the wording and content of the advice depending on the user's emotional state recognized by the emotion engine.

[0998] 5. Providing advice and responding to follow-up questions

[0999] The generated advice is sent to the terminal and displayed to the user. The user can review the displayed answer and enter follow-up questions if they require more information. The server responds to follow-up questions in the same way.

[1000] 6. Recommendation for consultation with a specialist

[1001] If the server determines that the problem is difficult to solve or the user's emotional state is worsening based on the analysis results of the generative AI model and emotion engine, it will recommend consulting an expert. The device will then provide the user with information such as the expert's contact details and how to make an appointment, allowing the user to contact the expert directly.

[1002] Hardware and software used

[1003] Front-end: Smartphone app, smart glasses app

[1004] Backend: Server (using AWS or Google Cloud Platform)

[1005] Sentiment engine: Google Cloud Natural Language, NVidia Clara

[1006] Generative AI model: GPT-4

[1007] Legal database: legal data held in cloud storage

[1008] Specific examples

[1009] For example, if a user types the question "I've been the victim of an internet scam, what should I do?", the emotion analysis method can detect that the user is feeling frustrated. Based on this information, the server generates soft-spoken advice such as "I recommend that you first contact your card company to report the fraud, and then file a police report." This advice is sent to the terminal and displayed to the user.

[1010] Prompt Sentence Examples

[1011] "A legal advice app for smartphones should assess the user's emotional state and generate appropriate advice for questions about internet fraud. If the user is feeling frustrated, examples of advice should include how to contact their credit card company or how to file a police report."

[1012] In this way, the present invention is a system that provides users with quick and appropriate solutions to legal problems while taking into account their emotional state.

[1013] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1014] Step 1:

[1015] User Registration and Login

[1016] A user accesses the system and registers or logs in. The terminal receives the email address and password entered by the user and sends them to the server. The server checks the database and returns the authentication result. This step takes the email address and password as input and returns the authentication result (success or failure) as output.

[1017] Step 2:

[1018] Entering the Question

[1019] The user inputs a legal question in text format, and the terminal sends the question to the server. In this step, the question entered by the user is transferred to the server as is.

[1020] Step 3:

[1021] Problem Analysis

[1022] The server inputs the received problem into a generative AI model (e.g., GPT-4) and analyzes the problem. In this step, the input text data (problem) is analyzed and processed to understand its meaning and intent. The output is the analysis result (what the problem is asking).

[1023] Step 4:

[1024] Search for related information

[1025] Based on the analysis results, the server searches the database for relevant legal knowledge and past court case data. In this step, a search query is generated based on the analysis results and used to filter the legal-related data in the database. The output is a set of relevant information.

[1026] Step 5:

[1027] Recognition of emotional states

[1028] The server uses an emotion engine to analyze the user's emotional state based on the input text. In this step, the input text data is passed through the emotion engine to evaluate the user's emotional state (e.g., anxiety, anger, impatience). The output is the emotion analysis result.

[1029] Step 6:

[1030] Advice generation and adjustment

[1031] The server generates appropriate advice based on the analysis results and the user's emotional state. At this stage, the generative AI model is again used to create specific advice that takes into account the searched information and the user's emotional state. The output is advice text, with the wording and content adjusted depending on the user's emotional state.

[1032] Step 7:

[1033] Providing advice

[1034] The generated advice is sent to the terminal and displayed to the user. In this step, the advice text is sent from the server to the terminal and displayed on the user's screen. The advice generated by the system is received as input and displayed on the user's screen as output.

[1035] Step 8:

[1036] Responding to additional questions

[1037] The user checks the displayed answer and enters an additional question if they have one. This additional question is also sent from the device to the server and processed again. In this step, the user enters the answer again, and the process from step 3 onwards is repeated.

[1038] Step 9:

[1039] Recommendation for consultation with a specialist

[1040] Based on the analysis results of the generative AI model and emotion engine, the server determines that the problem is difficult to solve or the user's emotional state is deteriorating, and recommends consulting an expert. In this step, information on the expert's contact details and how to make an appointment is generated and sent to the device. The user can then contact the expert directly using this information.

[1041] In this way, a system is realized that efficiently and effectively supports legal problem solving, taking into account in detail the specific actions performed at each step and the input and output data.

[1042] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1043] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1044] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1045] [Fourth embodiment]

[1046] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1047] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1048] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1049] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1050] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1051] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1052] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1053] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1054] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1055] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1056] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1057] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1058] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1059] This invention is a system that allows users to easily and quickly resolve legal problems. The system receives and analyzes the problem entered by the user, searches for relevant legal knowledge and past court case data, and generates and presents appropriate advice. It also has a function that recommends consulting an expert if necessary.

[1060] Overall system configuration

[1061] The system mainly consists of the following elements:

[1062] A terminal where users access the system and enter questions

[1063] A server that receives and analyzes input problems, searches for necessary data, and generates advice

[1064] A device that provides advice to users and recommends consulting a specialist

[1065] Program processing explanation

[1066] In the system of the present invention, the program performs the following processing.

[1067] 1. User registration and login process

[1068] A user accesses the system and performs new registration or logs in. The terminal sends the entered user information to the server, which then collates the received information with a database and returns the authentication result.

[1069] 2. Question input and analysis processing

[1070] Users enter legal issues or questions in text format, and their devices send the questions to a server, which uses a generative AI model to analyze the issues and search for relevant legal knowledge and past court cases.

[1071] 3. Providing answers and user assistance

[1072] The server generates advice based on the search results and sends it to the device, which then displays it to the user. The user can review the displayed answers and enter follow-up questions if they require more information. The server also responds to follow-up questions.

[1073] 4. Recommendation for consultation with a specialist

[1074] If the server determines that the generative AI model has difficulty answering a question, it recommends consulting an expert. The device then presents the user with information such as the expert's contact details and how to make a reservation, and the user can then contact the expert directly based on the information provided.

[1075] Specific examples

[1076] For example, suppose a user inputs a question such as, "There is a dispute about the boundary between my land and my neighbor's land. How should I resolve it?" The device sends this question to the server, which analyzes it using a generative AI model. As a result of the analysis, specific advice is generated, such as, "Boundary disputes are generally resolved through mutual discussion, but if that does not work, we recommend that you have the exact boundary measured by a land surveyor." The server sends this advice to the device, which displays it to the user. If the user wants to act on this advice but needs more information, they can input a follow-up question to receive further assistance. If the server answers this follow-up question appropriately but is unable to resolve the issue, information recommending consultation with an expert is displayed.

[1077] Thus, the present invention is a system that allows users to receive prompt and appropriate responses to minor legal issues and, if necessary, receive expert assistance.

[1078] The processing flow will be explained below.

[1079] Step 1: The user accesses the system.

[1080] Users access the system using terminals.

[1081] Step 2: User registers or logs in.

[1082] The device receives the email address and password entered by the user and sends that information to the server.

[1083] Step 3: The server authenticates the user information.

[1084] The server checks the received user information against a database and returns the authentication result to the terminal.

[1085] Step 4: The user enters the legal issue.

[1086] Users enter legal questions or problems into the terminal in text format.

[1087] Step 5: The device sends the entered question to the server.

[1088] The terminal transmits the questions entered by the user to the server as text data.

[1089] Step 6: The server analyzes the input problem.

[1090] The server passes the received problem to the generative AI model, which analyzes the problem.

[1091] Step 7: The server searches for relevant legal knowledge and case law data.

[1092] Based on the analysis results, the server searches a database for relevant legal knowledge and past court case data.

[1093] Step 8: The server generates the appropriate advice.

[1094] The server generates appropriate advice for the user based on the search results.

[1095] Step 9: The server sends the generated advice to the terminal.

[1096] The server transmits the generated advice to the terminal.

[1097] Step 10: The terminal displays the advice to the user.

[1098] The terminal visually displays the received advice to the user.

[1099] Step 11: The user reviews the advice and enters any further questions.

[1100] The user checks the displayed advice and, if they have any additional questions, they enter them again into the terminal.

[1101] Step 12: The terminal sends a follow-up question to the server.

[1102] The terminal sends a follow-up question to the server.

[1103] Step 13: The server again generates analysis and advice for the additional question.

[1104] The server analyzes the additional question, generates advice again, and sends it to the terminal.

[1105] Step 14: If the server determines that the problem is difficult to resolve, it recommends consulting an expert.

[1106] If the server determines through its analysis that the problem is difficult to solve, it generates information recommending that the user consult with an expert.

[1107] Step 15: The terminal displays the expert consultation information to the user.

[1108] The device visually displays to the user contact information for the specialist and how to schedule a consultation.

[1109] Step 16: The user contacts the expert.

[1110] The user can then contact the expert directly based on the displayed information.

[1111] In this way, the system provides users with appropriate solutions to their legal problems and allows them to access expert help if necessary.

[1112] Example 1

[1113] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1114] To provide a system that enables users with legal problems to easily obtain appropriate advice even without specialized knowledge, and to ensure that if the problem is not resolved, the users can quickly seek advice from an expert.

[1115] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1116] In this invention, the server includes means for receiving a problem entered by a user, means for analyzing the problem, means for searching related legal knowledge and past court case data based on the analyzed problem, means for generating appropriate advice based on the search results using a generative AI model, and means for presenting the generated advice to the user. This allows users to easily obtain appropriate advice on legal problems. In addition, if the problem is difficult to solve, the server can recommend consulting an expert, allowing users to quickly receive expert support.

[1117] "User" means any person or entity seeking to resolve a legal matter using the System.

[1118] "Means for receiving questions" refers to the function of sending legal questions or doubts entered by the user to the server through the interface.

[1119] "Means for analyzing the problem" refers to the analytical function used to understand and appropriately handle received legal questions and doubts.

[1120] "Means for searching legal knowledge and past court case data" refers to the function of searching for necessary information from a database of related legal knowledge and past court cases based on the analyzed problem.

[1121] A "generative artificial intelligence model" refers to a model that uses technologies such as natural language processing and machine learning to analyze input text data and generate appropriate advice.

[1122] "Means for generating advice" refers to the function of creating appropriate solutions and advice for users' problems based on searched legal knowledge and case law data.

[1123] "Means for presenting advice" refers to a function for displaying generated advice in an easy-to-understand manner for the user.

[1124] "Means to recommend consulting an expert" refers to a function that provides users with ways to contact or consult with relevant experts when the generative AI model determines that a problem is difficult to solve.

[1125] This invention is a system that allows users to easily and quickly resolve legal problems. The system receives and analyzes the problem entered by the user, searches for relevant legal knowledge and past court case data, and generates and presents appropriate advice. It also has a function that recommends consulting an expert if necessary.

[1126] Overall system configuration

[1127] The system mainly consists of the following components:

[1128] A terminal where users access the system and enter questions

[1129] A server that receives and analyzes input problems, searches for necessary data, and generates advice

[1130] A device that provides advice to users and recommends consulting a specialist

[1131] Program processing overview

[1132] The core of the system is the server, where most data processing and calculations are performed. Specifically, the server uses generative AI models such as "OpenAI GPT-4" and "Google BERT" to analyze legal questions entered by users. The analyzed data is queried against legal knowledge bases and databases of past court cases (e.g., MySQL, PostgreSQL) to search for relevant information. Based on the searched information, the generative AI model creates appropriate advice and sends the results back to the device.

[1133] Hardware and Software Examples

[1134] Processor: For example, the server uses a high-performance processor (e.g., Intel Xeon processor).

[1135] Database: For example, MySQL or PostgreSQL

[1136] AI models: OpenAI GPT-4 and Google BERT

[1137] Communication protocol: HTTP / HTTPS is used to exchange data between the terminal and the server.

[1138] Specific examples

[1139] For example, suppose a user inputs a question such as, "There is a dispute about the boundary between my land and the neighbor's land. How should I resolve it?" The device sends this question to the server, which analyzes it using a generative AI model. As a result of the analysis, specific advice is generated, such as, "It is common for boundary disputes to be resolved through mutual discussion, but if this cannot be resolved, it is recommended that the exact boundary be measured by a land surveyor." The server sends this advice to the device, which then displays it to the user.

[1140] Prompt Sentence Examples

[1141] An example of a prompt for a generative AI model is, "There is a problem regarding the boundary line between my land and my neighbor's land. What should I do if we can't resolve it through discussion?"

[1142] Thus, the present invention is a system that can quickly and appropriately respond to minor legal issues that users have, and can provide expert support as needed.

[1143] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1144] Step 1:

[1145] A user accesses the system and performs new registration or login. The terminal receives the user information entered by the user (e.g., username, password). The terminal sends this information to the server as an HTTP POST request. The server compares the received information with a database (e.g., MySQL, PostgreSQL), generates an authentication result, and returns the result to the terminal. The terminal displays the authentication result to the user, and if successful, transitions to a question input screen. The input is user information, and the output is the authentication result.

[1146] Step 2:

[1147] The user inputs a legal problem or question in text format. This input text is received by the device and sent to the server in JSON format. The input is the text of the legal problem, and the output is the analysis result.

[1148] Step 3:

[1149] The server passes the received text to the generative AI model as a prompt. The generative AI model (e.g., OpenAI GPT-4) analyzes the input problem and understands its content. It then searches for relevant legal knowledge and past court case data. These data are stored in a database. The input is the prompt, and the output is the relevant data.

[1150] Step 4:

[1151] The server generates appropriate advice based on the relevant data analyzed by the generative AI model. This advice is created using data analysis and sentence generation functions by the generative AI model. The generated advice is sent to the device in JSON format. The input is the analysis result, and the output is the generated advice.

[1152] Step 5:

[1153] The terminal displays the received advice on the user interface. The user can confirm the presented advice and, if they have any further questions, they can enter them in an additional text box. The input is the presentation of advice to the user, and the output is user confirmation.

[1154] Step 6:

[1155] The user enters a follow-up question, and the device sends it back to the server. The server then uses the generative AI model to analyze the follow-up question and generate appropriate advice in the same way. The input is the follow-up question, and the output is the follow-up advice.

[1156] Step 7:

[1157] If the server determines that analysis using the generative AI model is difficult, it recommends consulting an expert. In this case, the server sends the expert's contact information and consultation method to the device. The device displays this information on the user interface. The user can contact the expert directly based on the presented information. The input is the expert's recommended information, and the output is a recommendation presented to the user.

[1158] (Application example 1)

[1159] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1160] When conducting electronic transactions, there is a need for a method to quickly and efficiently resolve legal risks and doubts. However, many users lack legal expertise and are often unable to make appropriate decisions when faced with legal issues. Furthermore, when consultation with an expert is necessary, there is a need for a method to smoothly proceed with the procedure. The present invention aims to provide a method for solving these problems.

[1161] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1162] In this invention, the server includes means for receiving a problem entered by a user, means for analyzing the problem, means for searching related legal knowledge and past court case data based on the analyzed problem, means for generating appropriate advice based on the search results, means for presenting the generated advice to the user, means for analyzing legal risks and doubts related to electronic transactions and providing appropriate advice, and means for recommending consultation with an expert when a significant legal issue is detected. This enables users to quickly and appropriately resolve legal issues in electronic transactions and to receive expert help as needed.

[1163] "User" means any person or entity seeking to resolve a legal matter using the System.

[1164] "Means for receiving questions" refers to an interface for sending legal questions entered by a user to a server.

[1165] "Means of problem analysis" refers to the process used to understand the received legal problem and extract the necessary data.

[1166] "Means of searching relevant legal knowledge and past case law data" refers to the process of searching legal databases to gather the necessary information.

[1167] "Means of generating appropriate advice" refers to the process of constructing a solution to a problem based on retrieved legal knowledge and case law data.

[1168] "Means for presenting to the user" refers to an interface for displaying the generated advice on the user's terminal.

[1169] "Electronic commerce" refers to the buying and selling of goods and services conducted over the Internet.

[1170] "Legal risks and doubts" refers to legal issues and uncertainties that arise in connection with electronic transactions.

[1171] "Means for recommending consultation with an expert" refers to the process of referring a user to an appropriate legal expert if the system determines that the problem is difficult to resolve.

[1172] "Server" refers to a central processing unit that receives input data from users, analyzes it, and generates advice.

[1173] MODE FOR CARRYING OUT THE INVENTION

[1174] The present invention is a system for quickly resolving legal risks and doubts in electronic transactions, and is composed of the following elements: The system receives problems entered by users, analyzes them using a generative AI model, and aims to provide appropriate advice and expert recommendations.

[1175] System Configuration

[1176] 1. User's Device

[1177] Hardware: Smartphone (e.g. iPhone, Android device)

[1178] Software: React Native (cross-platform mobile app development)

[1179] 2. Server

[1180] Hardware: Central Processing Unit (e.g. AWS EC2 server)

[1181] software:

[1182] Server-side frameworks: Node.js, Express.js

[1183] Database: MySQL, MongoDB

[1184] Generative AI model: GPT-4 (OpenAI)

[1185] Program processing explanation

[1186] The server solves legal problems through the following series of steps: First, it receives the problem sent from the terminal and analyzes it. Based on the analyzed problem, it searches the database for relevant legal knowledge and past court case data.

[1187] Based on the search results, appropriate advice is generated using a generative AI model (GPT-4) and sent to the device. The user can review the advice on the device and enter a question again if additional information is needed. The server also analyzes the additional questions and generates advice.

[1188] If the generated advice is difficult to resolve, the system will display the contact information of an expert along with a message recommending that the user consult with an expert, allowing the user to quickly and appropriately resolve legal risks and doubts.

[1189] Specific examples

[1190] For example, if a user types a question like "Is the reason for this transaction's decline legitimate?", we generate the following prompt and ask the GPT-4 model:

[1191] Example prompt:

[1192] A user is asking about the legality of reasons for payment denial in an electronic payment transaction. Analyze the user's question, refer to relevant laws and court cases, and generate an answer. If the answer is difficult, include a message recommending that the user seek professional advice.

[1193] The server then sends the generated advice to the terminal, which then displays the advice to the user. In this way, the system provides a means for users to efficiently resolve legal issues related to electronic transactions.

[1194] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1195] Step 1:

[1196] The user inputs a legal problem in text format from a smartphone terminal. The input problem is sent to the server by the terminal. The input of this step is the text data of the user's legal problem, and the output is that the data is sent to the server.

[1197] Step 2:

[1198] The server analyzes the received text data. It uses a generative AI model (GPT-4) to understand the input problem and identify the necessary legal information. The input for this step is the text data of the user's legal problem, and the output is the structured data of the analyzed problem.

[1199] Step 3:

[1200] Based on the analyzed problem, the server searches a database for relevant legal knowledge and past court case data. The database uses MySQL or MongoDB. The input for this step is structured data, and the output is the search results for relevant legal knowledge and court case data.

[1201] Step 4:

[1202] The server generates appropriate advice based on the search results. Using a generative AI model (GPT-4), it derives the optimal solution from the searched legal knowledge and case law data. The input for this step is the search result data, and the output is the generated advice text data.

[1203] Step 5:

[1204] The server sends the generated advice to the terminal, which then displays the advice to the user. The input of this step is the text data of the generated advice, and the output is that the advice is displayed to the user.

[1205] Step 6:

[1206] If the user has additional questions or doubts, they enter the question again and the process is repeated from step 1. The input of this step is the text data of the user's additional question, and the output is sent to the server again.

[1207] Step 7:

[1208] If the server determines that the problem is difficult to solve as a result of analysis using the generative AI model, it recommends consulting an expert. The server generates the expert's contact information and sends it to the device. The device then presents this information to the user. The input to this step is the analysis result of the generative AI model, and the output is a message recommending consultation with an expert.

[1209] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1210] The present invention is a system for easily and quickly resolving legal problems faced by users, and enables the provision of more appropriate advice by taking the user's emotional state into consideration. The system includes means for receiving and analyzing problems entered by the user, means for searching for and generating relevant legal knowledge and past court case data based on the analysis, means for presenting the generated advice to the user, and an emotion engine that recognizes the user's emotions. The system also includes means for using the emotion engine to tailor advice according to the user's emotional state and means for evaluating the user's emotional state and recommending consultation with an expert.

[1211] Overall system configuration

[1212] The system consists of the following components:

[1213] A terminal where users access the system and enter questions

[1214] A server that receives input questions, analyzes them, searches for them, and generates them

[1215] A device that provides advice to users and recognizes their emotional state

[1216] An emotion engine that analyzes the user's emotional state

[1217] Program processing explanation

[1218] In the system of the present invention, the program performs the following processing.

[1219] 1. User registration and login process

[1220] A user accesses the system and registers or logs in. The terminal receives the email address and password entered by the user and sends them to the server. The server checks the database and returns the authentication result.

[1221] 2. Question input and analysis processing

[1222] Users enter legal issues or questions in text format and their devices send the questions to a server, which uses a generative AI model to analyze the issues and search for relevant legal knowledge and past court cases.

[1223] 3. Recognizing emotional states

[1224] The server uses an emotion engine to recognize the user's emotional state through input, facial expression analysis, and voice recognition. Specifically, the emotion engine analyzes the user's input text and voice message and evaluates the user's emotional state.

[1225] 4. Advice Generation and Adjustment

[1226] The server generates appropriate advice based on the analysis results and the user's emotional state. The server adjusts the wording and content of the advice depending on the user's emotional state recognized by the emotion engine.

[1227] 5. Providing answers and user assistance

[1228] The server sends the generated advice to the terminal, which then displays it to the user. The user checks the displayed answer and enters additional questions if more information is needed. The server responds to the additional questions in the same way.

[1229] 6. Recommendation for consultation with a specialist

[1230] If the server determines that the problem is difficult to solve or the user's emotional state is worsening based on the analysis results of the generative AI model and emotion engine, it will recommend consulting an expert. The device will then provide the user with information such as the expert's contact details and how to make an appointment, and the user can then contact the expert directly based on that information.

[1231] Specific examples

[1232] For example, if a user inputs a question such as "There's a problem with the boundary between my land and my neighbor's. How should we resolve it?" and is feeling a strong emotion (e.g., anxiety or anger) at the time, the emotion engine will recognize that emotion. Taking this emotional state into consideration, the server generates advice in a slightly more moderate language, such as "First, try to discuss the matter calmly. If that doesn't resolve the issue, we recommend that you have a land surveyor measure the exact boundary." The server then sends this advice to the device, which then displays it to the user. Furthermore, if the user's emotional state worsens and the problem cannot be resolved, the server will automatically provide information recommending that the user consult an expert.

[1233] In this way, the present invention is a system that provides appropriate solutions to minor legal problems that users have while taking into account their emotional state, and allows them to receive expert support if necessary.

[1234] The processing flow will be explained below.

[1235] Step 1: The user accesses the system.

[1236] Users access the system using terminals.

[1237] Step 2: User registers or logs in.

[1238] The terminal receives the email address and password entered by the user and sends them to the server.

[1239] Step 3: The server authenticates the user information.

[1240] The server checks the received user information against a database and returns the authentication result to the terminal.

[1241] Step 4: The user enters the legal issue.

[1242] Users enter legal questions or problems into the terminal in text format.

[1243] Step 5: The device sends the entered question to the server.

[1244] The terminal transmits the questions entered by the user to the server as text data.

[1245] Step 6: The server analyzes the input problem.

[1246] The server passes the received problem to the generative AI model, which analyzes the problem.

[1247] Step 7: The server searches for relevant legal knowledge and case law data.

[1248] Based on the analysis results, the server searches a database for relevant legal knowledge and past court case data.

[1249] Step 8: The server recognizes the user's emotional state.

[1250] The server uses an emotion engine to analyze the user's emotional state from their input text and voice.

[1251] Step 9: The server generates advice according to the emotional state.

[1252] The server generates appropriate advice based on the search results and the user's emotional state, adjusting the wording and content of the advice.

[1253] Step 10: The server sends the generated advice to the terminal.

[1254] The server transmits the generated advice to the terminal.

[1255] Step 11: The terminal displays the advice to the user.

[1256] The terminal visually displays the received advice to the user.

[1257] Step 12: The user reviews the advice and enters any further questions.

[1258] The user checks the displayed advice and, if they have any additional questions, they enter them again into the terminal.

[1259] Step 13: The terminal sends a follow-up question to the server.

[1260] The terminal sends a follow-up question to the server.

[1261] Step 14: The server again generates analysis and advice for the additional question.

[1262] The server analyzes the additional question, generates advice again, and sends it to the terminal.

[1263] Step 15: If the server determines that the problem is difficult to resolve, it recommends consulting an expert.

[1264] If the server determines through its analysis that the problem is difficult to solve, it generates information recommending that the user consult with an expert.

[1265] Step 16: The terminal displays the expert consultation information to the user.

[1266] The device visually displays to the user contact information for the specialist and how to schedule a consultation.

[1267] Step 17: The user contacts the expert.

[1268] The user can then contact the expert directly based on the displayed information.

[1269] In this way, the system can provide users with appropriate solutions to their legal problems, increase their satisfaction while taking into account their emotional state, and provide them with access to expert assistance when necessary.

[1270] Example 2

[1271] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1272] Users with legal problems need accurate information and appropriate advice to effectively resolve them. However, users' emotional state often gets in the way of resolving the problem, and conventional systems do not provide support that takes their emotional state into account. Furthermore, when a problem is difficult to resolve, it is necessary to seek expert help, but this decision is often left up to the user. This can delay timely expert intervention and further complicate the problem.

[1273] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving a problem input by a user, means for analyzing the problem, means for searching for related legal knowledge and past court case data based on the analyzed problem, means for generating appropriate advice based on the search results, means for presenting the generated advice to the user, means for recognizing the user's emotional state, and means for adjusting the generated advice based on the recognized emotional state. This makes it possible to provide appropriate advice that takes the user's emotional state into consideration, thereby making problem-solving support more effective. Furthermore, if the user's emotional state worsens and the problem becomes difficult to solve, the server recommends consulting an expert, allowing the expert to intervene at an appropriate time.

[1274] "User" means any person or organization seeking to resolve a legal matter using the System.

[1275] "Problems" refer to legal questions, troubles, disputes, and other issues that require resolution and are entered into the system by users.

[1276] "Means of receiving" refers to the functions and devices used to incorporate information entered by users into the system.

[1277] "Means for analyzing" refers to algorithms or programs for understanding the received question and analyzing its content.

[1278] "Searching means" refers to the function for finding relevant legal knowledge and past case law data based on the analyzed problem.

[1279] "Means for generating" refers to the function of creating specific advice to be provided to users based on the analysis results and search results.

[1280] "Presentation means" refers to a device or software feature that displays the generated advice in a user-readable form.

[1281] "Means for recognizing emotional state" refers to technologies and systems that can identify a user's current emotional state from their input, voice, facial expressions, etc.

[1282] "Adjustment" refers to the ability to adaptively change the content and wording of generated advice based on the perceived emotional state.

[1283] "Means to encourage consultation with an expert" refers to a function that encourages users to seek expert help if their problem is deemed difficult to solve.

[1284] This invention is a system for quickly and appropriately resolving legal problems faced by users, and has the function of providing advice that takes into account the user's emotional state. The system receives and analyzes the problem entered by the user, generates and presents advice based on relevant legal knowledge and past court case data, and can also recognize the user's emotional state using an emotion engine and adjust advice accordingly.

[1285] The overall system configuration is as follows:

[1286] 1. The terminal where users access the system and enter questions

[1287] 2. A server that receives input questions, analyzes them, searches for them, and generates them.

[1288] 3. A device that provides advice to users and recognizes their emotional state

[1289] 4. Emotion engine that analyzes the user's emotional state

[1290] When the server receives a legal problem or question in text form entered by the user, it analyzes the problem using a generative AI model (e.g., OpenAI's GPT-4). Based on the analyzed problem, the server searches relevant legal knowledge and past court case data. Next, it generates appropriate advice based on the search results. At this time, the generated advice is adjusted according to the user's emotional state, as recognized by an emotion engine (e.g., IBM Watson's Tone Analyzer).

[1291] As a concrete example, suppose a user inputs the question, "There's a problem regarding the boundary between my land and my neighbor's. How should we resolve it?" In this case, the server uses a generative AI model to analyze the problem and search for relevant legal knowledge and past court cases. At the same time, an emotion engine recognizes emotions such as anxiety or anger from the user's text. The server takes this emotional state into consideration and generates soft-spoken advice such as, "First, try to discuss the matter calmly. If that doesn't resolve the issue, I recommend having a land surveyor measure the exact boundary." The server sends this advice to the device, which then displays it to the user.

[1292] Furthermore, if the user's emotional state worsens and the problem remains unresolved, the server will automatically recommend consulting a specialist. In this case, the server will generate information such as the specialist's contact details and how to make an appointment, and the device will present this information to the user. This allows the user to smoothly contact the specialist.

[1293] This system responds quickly to even minor legal issues users may have, provides appropriate solutions that take into account their emotional state, and provides comprehensive support for users in resolving legal issues by providing expert assistance as needed.

[1294] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1295] Step 1:

[1296] A user accesses the system. The user enters an email address, password, and other necessary personal information into a new registration form. The device receives this information and sends it to the server. The server stores the received information in a database. The user enters an email address and password into a login form. The device receives the login information and sends it to the server. The server compares it with the database and returns the authentication result to the device. If authentication is successful, the user can proceed to the next step. Specifically, a database search and comparison operation are performed.

[1297] Step 2:

[1298] The user inputs a legal problem or question in text format. The input text is sent by the device to the server. The server receives this text. The server passes the input problem to a generative AI model (for example, OpenAI's GPT-4) as a prompt. The generative AI model analyzes the text. The input here is the user's text question, which is converted into a prompt and then sent to the generative AI model. The output is the analysis result, which may include relevant legal knowledge or past court case data. As a specific example, the question "There is a problem regarding the boundary between my land and the neighbor's land. How should we resolve this?" is sent to the generative AI model as a prompt.

[1299] Step 3:

[1300] The server receives the analysis results and searches for related legal knowledge and past court case data. The server then queries the database and extracts the required data. The input here is the analysis results from the generative AI model, and the output is legal knowledge and past court case data. Specific operations include searching and filtering the database.

[1301] Step 4:

[1302] The server generates appropriate advice based on the search results. The server creates advice according to the guidelines of the generative AI model. In addition, it uses an emotion engine (for example, IBM Watson's Tone Analyzer) to recognize the emotional state from the user's input text or voice message. The input here is the search results and the user's emotional state, and the output is tailored advice. Operations include natural language processing and style adjustment.

[1303] Step 5:

[1304] The server sends the generated advice to the terminal. The terminal displays the advice to the user. The user reviews the advice and enters an additional question if more information is needed. The additional question entered is also sent to the server, where it is parsed and searched again. The input here is the advice from the server, and the output is the advice displayed on the terminal. Operations include sending, receiving, and displaying data.

[1305] Step 6:

[1306] If the server determines that the problem is difficult to solve or the emotional state is worsening based on the analysis results of the generated AI model and the emotion engine, it recommends consulting an expert. The server generates information such as the expert's contact details and reservation methods, and the device presents this to the user. The user then directly contacts the expert based on this information. The input here is the analysis results of the emotion engine and the generated advice, and the output is the expert consultation information. Specific operations include analyzing the emotional state and generating information.

[1307] The above are the processing steps of the program of this system, and each step has detailed inputs and outputs, and specific operations are performed.

[1308] (Application example 2)

[1309] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1310] Conventional legal consultation systems often provide cold advice without taking into account the user's emotional state, further increasing the user's anxiety. Furthermore, they often fail to promptly introduce appropriate experts to difficult problems, resulting in a long wait for users to receive appropriate support. The present invention aims to solve these problems and quickly provide appropriate advice that takes into account the user's emotional state.

[1311] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1312] In this invention, the server includes a means for receiving questions entered by the user, a means for analyzing the questions, and a means for searching relevant legal knowledge and past court case data, thereby enabling the generation of appropriate advice that takes into account the emotional state of the user.

[1313] "User" means any person or entity that uses the System to enter legal issues and seek solutions.

[1314] "Means for receiving questions" is a function that allows users to input legal questions and doubts into the system.

[1315] A "means for analyzing a problem" is a program or algorithm that analyzes the received legal problem and understands its content and intent.

[1316] "Means for searching relevant legal knowledge and past court cases" refers to a function that searches for relevant legal knowledge and past court cases from databases and external information sources based on the analyzed problem.

[1317] A "means for generating appropriate advice" is a program that provides users with specific solutions and guidelines for action based on the retrieved legal knowledge and case law data.

[1318] The "means for presenting advice to the user" is a function for displaying the generated advice on the user's terminal.

[1319] "Emotion analysis means" is a technology for analyzing a user's emotional state from input text, voice, facial expressions, etc.

[1320] The "means for adjusting advice" is a function for adjusting the wording and expression depending on the emotional state of the user recognized by the emotion analysis means.

[1321] A "means for training a generative artificial intelligence model" is a process for training an artificial intelligence model with the data necessary to generate appropriate advice.

[1322] The "means for recommending consultation with an expert" is a function for introducing an appropriate expert to the user when the generated advice is judged to be difficult to resolve.

[1323] The present invention is a system for easily and quickly resolving legal problems that users have, and aims to provide more appropriate advice by taking into account the user's emotional state. Specific embodiments for carrying out the invention are described below.

[1324] Overall system overview

[1325] The system consists of the following main components:

[1326] A terminal for users to input questions

[1327] A server that analyzes input problems, searches for related information, and generates advice

[1328] Emotion engine that recognizes and analyzes emotional states

[1329] Generative AI Model

[1330] System processing overview

[1331] 1. User Registration and Login

[1332] The user accesses the system from a terminal and performs new registration or login. The terminal sends the email address and password entered by the user to the server. The server checks the database and returns the authentication result.

[1333] 2. Problem entry and analysis

[1334] Users input legal questions in text format, and their devices send the questions to a server, which then uses a generative AI model (e.g., GPT-4) to analyze the questions and search for relevant legal knowledge and past court cases.

[1335] 3. Recognizing emotional states

[1336] The server uses an emotion engine (e.g., Google Cloud Natural Language or NVidia Clara) to analyze the user's input text or voice message and recognize their emotional state.

[1337] 4. Advice Generation and Adjustment

[1338] The server generates appropriate advice based on the analysis results and the user's emotional state. The server adjusts the wording and content of the advice depending on the user's emotional state recognized by the emotion engine.

[1339] 5. Providing advice and responding to follow-up questions

[1340] The generated advice is sent to the terminal and displayed to the user. The user can review the displayed answer and enter follow-up questions if they require more information. The server responds to follow-up questions in the same way.

[1341] 6. Recommendation for consultation with a specialist

[1342] If the server determines that the problem is difficult to solve or the user's emotional state is worsening based on the analysis results of the generative AI model and emotion engine, it will recommend consulting an expert. The device will then provide the user with information such as the expert's contact details and how to make an appointment, allowing the user to contact the expert directly.

[1343] Hardware and software used

[1344] Front-end: Smartphone app, smart glasses app

[1345] Backend: Server (using AWS or Google Cloud Platform)

[1346] Sentiment engine: Google Cloud Natural Language, NVidia Clara

[1347] Generative AI model: GPT-4

[1348] Legal database: legal data held in cloud storage

[1349] Specific examples

[1350] For example, if a user types the question "I've been the victim of an internet scam, what should I do?", the emotion analysis method can detect that the user is feeling frustrated. Based on this information, the server generates soft-spoken advice such as "I recommend that you first contact your card company to report the fraud, and then file a police report." This advice is sent to the terminal and displayed to the user.

[1351] Prompt Sentence Examples

[1352] "A legal advice app for smartphones should assess the user's emotional state and generate appropriate advice for questions about internet fraud. If the user is feeling frustrated, examples of advice should include how to contact their credit card company or how to file a police report."

[1353] In this way, the present invention is a system that provides users with quick and appropriate solutions to legal problems while taking into account their emotional state.

[1354] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1355] Step 1:

[1356] User Registration and Login

[1357] A user accesses the system and registers or logs in. The terminal receives the email address and password entered by the user and sends them to the server. The server checks the database and returns the authentication result. This step takes the email address and password as input and returns the authentication result (success or failure) as output.

[1358] Step 2:

[1359] Entering the Question

[1360] The user inputs a legal question in text format, and the terminal sends the question to the server. In this step, the question entered by the user is transferred to the server as is.

[1361] Step 3:

[1362] Problem Analysis

[1363] The server inputs the received problem into a generative AI model (e.g., GPT-4) and analyzes the problem. In this step, the input text data (problem) is analyzed and processed to understand its meaning and intent. The output is the analysis result (what the problem is asking).

[1364] Step 4:

[1365] Search for related information

[1366] Based on the analysis results, the server searches the database for relevant legal knowledge and past court case data. In this step, a search query is generated based on the analysis results and used to filter the legal-related data in the database. The output is a set of relevant information.

[1367] Step 5:

[1368] Recognition of emotional states

[1369] The server uses an emotion engine to analyze the user's emotional state based on the input text. In this step, the input text data is passed through the emotion engine to evaluate the user's emotional state (e.g., anxiety, anger, impatience). The output is the emotion analysis result.

[1370] Step 6:

[1371] Advice generation and adjustment

[1372] The server generates appropriate advice based on the analysis results and the user's emotional state. At this stage, the generative AI model is again used to create specific advice that takes into account the searched information and the user's emotional state. The output is advice text, with the wording and content adjusted depending on the user's emotional state.

[1373] Step 7:

[1374] Providing advice

[1375] The generated advice is sent to the terminal and displayed to the user. In this step, the advice text is sent from the server to the terminal and displayed on the user's screen. The advice generated by the system is received as input and displayed on the user's screen as output.

[1376] Step 8:

[1377] Responding to additional questions

[1378] The user checks the displayed answer and enters an additional question if they have one. This additional question is also sent from the device to the server and processed again. In this step, the user enters the answer again, and the process from step 3 onwards is repeated.

[1379] Step 9:

[1380] Recommendation for consultation with a specialist

[1381] Based on the analysis results of the generative AI model and emotion engine, the server determines that the problem is difficult to solve or the user's emotional state is deteriorating, and recommends consulting an expert. In this step, information on the expert's contact details and how to make an appointment is generated and sent to the device. The user can then contact the expert directly using this information.

[1382] In this way, a system is realized that efficiently and effectively supports legal problem solving, taking into account in detail the specific actions performed at each step and the input and output data.

[1383] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1384] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1385] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1386] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1387] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1388] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1389] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1390] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1391] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1392] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1393] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1394] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1395] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1396] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1397] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1398] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1399] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1400] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1401] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1402] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1403] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1404] The following is further disclosed regarding the above embodiment.

[1405] (Claim 1)

[1406] means for receiving a question input by a user;

[1407] means for analyzing said problem;

[1408] A means of searching for relevant legal knowledge and past case data based on the analyzed problem;

[1409] A means for generating appropriate advice based on the searched results;

[1410] means for presenting the generated advice to a user;

[1411] A system including:

[1412] (Claim 2)

[1413] 10. The system of claim 1, further comprising means for training a generative artificial intelligence model to generate appropriate advice for a user-entered problem.

[1414] (Claim 3)

[1415] 10. The system of claim 1, further comprising: means for recommending consultation with an expert if the generated advice is difficult to resolve.

[1416] "Example 1"

[1417] (Claim 1)

[1418] means for receiving a question input by a user;

[1419] means for analyzing said problem;

[1420] A means of searching for relevant legal knowledge and past case data based on the analyzed problem;

[1421] means for generating appropriate advice based on the searched results using a generative artificial intelligence model;

[1422] means for presenting the generated advice to a user;

[1423] A system including:

[1424] (Claim 2)

[1425] 10. The system of claim 1, further comprising means for training a generative artificial intelligence model to generate appropriate advice for a user-entered problem.

[1426] (Claim 3)

[1427] 10. The system of claim 1, further comprising: means for recommending consultation with an expert if the generated advice is difficult to resolve.

[1428] "Application Example 1"

[1429] (Claim 1)

[1430] means for receiving a question input by a user;

[1431] means for analyzing said problem;

[1432] A means of searching for relevant legal knowledge and past case data based on the analyzed problem;

[1433] A means for generating appropriate advice based on the searched results;

[1434] means for presenting the generated advice to a user;

[1435] A means of analyzing legal risks and doubts regarding electronic transactions and providing appropriate advice;

[1436] A means of recommending expert consultation when significant legal issues are detected;

[1437] A system including:

[1438] (Claim 2)

[1439] 10. The system of claim 1, further comprising means for training the generative artificial intelligence model to include legal issues related to electronic commerce.

[1440] (Claim 3)

[1441] 10. The system of claim 1, further comprising means for recommending consultation with an expert if a transaction-related legal issue is difficult to resolve.

[1442] "Example 2: Combining Emotion Engines"

[1443] (Claim 1)

[1444] means for receiving a question input by a user;

[1445] means for analyzing said problem;

[1446] A means of searching for relevant legal knowledge and past case data based on the analyzed problem;

[1447] A means for generating appropriate advice based on the searched results;

[1448] means for presenting the generated advice to a user;

[1449] a means for recognizing the emotional state of a user;

[1450] means for adjusting the generated advice based on the perceived emotional state;

[1451] A system including:

[1452] (Claim 2)

[1453] 10. The system of claim 1, further comprising means for training a generative artificial intelligence model to generate appropriate advice for a user-entered problem.

[1454] (Claim 3)

[1455] 10. The system of claim 1, further comprising: means for recommending consultation with an expert if the generated advice is difficult to resolve.

[1456] "Application example 2 when combining emotion engines"

[1457] (Claim 1)

[1458] means for receiving a question input by a user;

[1459] means for analyzing said problem;

[1460] A means of searching for relevant legal knowledge and past case data based on the analyzed problem;

[1461] A means for generating appropriate advice based on the searched results;

[1462] means for presenting the generated advice to a user;

[1463] emotion analysis means for recognizing the emotional state of a user;

[1464] a means for tailoring advice in response to the perceived emotional state;

[1465] A system including:

[1466] (Claim 2)

[1467] 10. The system of claim 1, further comprising means for training a generative artificial intelligence model to generate appropriate advice for a user-entered problem.

[1468] (Claim 3)

[1469] 10. The system of claim 1, further comprising: means for recommending consultation with an expert if the generated advice is difficult to resolve. [Explanation of symbols]

[1470] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving a question input by a user; means for analyzing said problem; A means of searching for relevant legal knowledge and past case data based on the analyzed problem; A means for generating appropriate advice based on the searched results; means for presenting the generated advice to a user; A system including:

2. The system of claim 1 further comprising means for training a generative artificial intelligence model for generating appropriate advice for a problem input by a user.

3. The system of claim 1 , further comprising means for recommending consultation with an expert if the generated advice is difficult to resolve.

Images