system

Abstract

Provide a system. A means for collecting and storing legal data in a database; means for receiving user-entered trouble summary data; a means for analyzing the received summary data using natural language processing to generate an appropriate solution; a means of providing the user with information on the generated solution and the corresponding legal authority; a means of receiving user feedback and optimizing the system; A system including:

Description

[Technical Field]

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

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

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

[0004] In the past, it has been difficult to provide appropriate solutions to legal problems quickly and efficiently. In particular, finding an accurate solution based on reliable information requires a lot of time and effort. As a result, ordinary users have had trouble easily obtaining appropriate solutions when they face legal problems. Furthermore, due to a lack of means to properly utilize information from law firms and legal institutions, users have had difficulty receiving support from reliable experts. Therefore, there is a need for a system that allows users to efficiently obtain appropriate solutions to legal problems and access reliable legal support. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system that includes: means for collecting and storing legal-related data in a database; means for receiving summary data of the problem entered by the user; means for analyzing the received summary data using natural language processing to generate an appropriate solution; means for providing the generated solution and information on the corresponding legal agency to the user; and means for receiving user feedback and optimizing the system. Specifically, the system uses a server to collect reliable data from law firms and courts, and performs analysis using natural language processing technology based on the details of the problem entered by the user. Based on the analysis results, the system presents an appropriate solution and, if necessary, provides information on law firms and municipal consultation centers. Furthermore, user feedback is accumulated in the system, and the analysis accuracy and information are continuously updated. This enables users to obtain appropriate and efficient solutions and receive reliable legal support when they face legal problems.

[0006] "Legal data" refers to highly reliable information such as laws, precedents, contracts, court documents, and legal consultation cases obtained from law firms, courts, legal institutions, etc.

[0007] "Database" refers to a system or platform that systematically stores and manages collected legal-related data and facilitates its search and analysis.

[0008] "Trouble summary data" refers to detailed information entered by the user, such as the type of trouble, the circumstances, the people involved, and the date and time of the occurrence.

[0009] "Natural language processing" refers to the technology that enables computers to understand, analyze, and generate human language. Specifically, it includes morphological analysis, sentence analysis, and intent understanding.

[0010] "Analysis" refers to the process of classifying and analyzing the received summary data of the problem using natural language processing technology and deriving an appropriate solution.

[0011] "Solutions" refer to specific ways and means of dealing with problems, including legal advice, procedural procedures, and appropriate contact information.

[0012] "Legal institutions" refers to organizations and groups that provide legal support, such as law firms, courts, municipal helplines, and labor bureaus.

[0013] "Feedback" refers to information that a User reports to the System regarding their evaluation and results of the solution provided or the support of a legal authority.

[0014] "Server" refers to the computer system that receives and analyzes data from users and generates and provides solutions.

[0015] "System" refers to a comprehensive technological platform that combines multiple means to enable users to resolve legal disputes. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] System Overview

[0038] The present invention is a comprehensive system for providing appropriate solutions to legal problems quickly and efficiently. This system mainly operates in cooperation with a server, terminals, and users.

[0039] Server-side behavior

[0040] The server collects reliable data from law firms, courts, and other sources and stores it in a database. It also receives summary data about the problem entered by the user on their device and analyzes it using natural language processing technology. Based on the analysis results, it generates appropriate solutions and provides them to the user. It also collects feedback from users and reflects it in improving the system.

[0041] Data collection and storage

[0042] The server periodically collects the latest information from law firms and courts through web scraping, APIs, and manual entry, and the collected data is organized and stored in a database.

[0043] Analysis of trouble summary data

[0044] The server analyzes the trouble summary data received from the user using natural language processing (NLP) techniques, such as morphological analysis, topic modeling, and similar case search.

[0045] Solution generation and delivery

[0046] Based on the analysis results, the server generates an optimal solution, which includes legal advice and appropriate procedural instructions, and, if necessary, provides information on relevant law firms and local government consultation services.

[0047] Feedback collection and optimization

[0048] The server receives feedback from users after they have used the solutions and consultation services provided, and this feedback is stored in a database and used to improve the accuracy of the system's analytical model and database.

[0049] Operation on the terminal side

[0050] The terminal provides the interface through which users access the system. The terminal is used by users to create an account, enter a problem description, and receive a solution from the system. This can be a web browser or a mobile application.

[0051] User Registration and Login

[0052] Users create an account through a terminal and enter the necessary information. Existing users can access the system by logging in.

[0053] Enter a summary of the problem

[0054] The user enters detailed information about the problem through a terminal. The form includes items such as the type of problem, the date and time of the problem, the people involved, and specific details of the problem.

[0055] Receiving solutions and feedback

[0056] The user receives and views the solutions provided by the server through the terminal, and also inputs feedback on the results of using the proposed solutions and legal support.

[0057] Specific examples

[0058] Example 1: Labor-related issues

[0059] The user wishes to seek advice regarding unfair dismissal under a labor contract. Using the terminal, the user enters the following information:

[0060] Type of problem: Labor issues

[0061] Date of occurrence: August 15, 2023

[0062] Parties involved: Employee (user), Employer (company)

[0063] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[0064] The server receives this information, analyzes it, and makes the following suggestions:

[0065] Checklist for legality of dismissal under the Labor Standards Act

[0066] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[0067] Introduction to law firms that specialize in labor issues

[0068] The user acts on the presented solution and reports the results to the system as feedback.

[0069] Example 2: Consultation regarding contract disputes

[0070] The user wishes to consult about a problem regarding the renewal of a rental contract. The user enters the following information through the terminal:

[0071] Type of problem: Contract problem

[0072] Date of occurrence: September 10, 2023

[0073] Parties involved: Tenant (user), landlord (landlord)

[0074] Detailed background: The landlord added unfair conditions when renewing the contract.

[0075] The server receives this information, analyzes it, and makes the following suggestions:

[0076] Procedures for verifying the legality of renewal conditions in lease agreements

[0077] Local government rental housing trouble consultation desk

[0078] Introducing a law firm that specializes in real estate issues

[0079] The user takes specific action based on the presented solution and reports the results to the system as feedback.

[0080] In this way, the system of the present invention provides comprehensive support for quickly and appropriately responding to legal troubles.

[0081] The processing flow will be explained below.

[0082] Step 1:

[0083] The server collects reliable data from law firms and courts. It uses web scraping and APIs to obtain the latest laws, precedents, contracts, etc., and stores them in a database. Additionally, it uses OCR technology to digitize manually collected materials as needed and registers them in the database.

[0084] Step 2:

[0085] Users access the system using a terminal and create an account or log in. New users create an account by entering personal information such as their name, email address, and password. Existing users enter their email address and password, which are then verified by the server.

[0086] Step 3:

[0087] The user uses the terminal to input an outline of the problem. The input form includes items such as the type of problem, the date and time of occurrence, the people involved, and specific details. The user enters this information in detail.

[0088] Step 4:

[0089] The server receives the summary data of the problem sent by the user and stores it in a temporary database. At this point, a simple error check is performed to ensure that there are no problems with the format or content of the input data.

[0090] Step 5:

[0091] The server analyzes the received summary data of the problem using natural language processing (NLP) technology. It uses an NLP model (e.g., BERT or GPT) to classify the input data, extract important keywords, and understand the content of the problem.

[0092] Step 6:

[0093] The server searches the database for similar cases and related laws and regulations based on the analysis results, and generates the optimal solution based on the search results and determines which solution to provide to the user.

[0094] Step 7:

[0095] The server provides the generated solution to the user, and also lists and displays to the user information on law firms and details of local government consultation centers related to the solution.

[0096] Step 8:

[0097] The user can view the solutions provided by the server through their device and take action if necessary, including contacting the suggested law firm or counseling center.

[0098] Step 9:

[0099] Users enter their feedback on the solutions provided and the results of using the support service in a feedback form, including their evaluation of the effectiveness of the solutions and the quality of the support.

[0100] Step 10:

[0101] The server receives feedback from users and stores it in a database. The collected feedback is used to improve the accuracy of the system's analytical model and database, allowing the system to be continuously optimized.

[0102] Through these steps, this system provides users with efficient solutions to legal problems and creates an environment where they can easily access reliable legal support.

[0103] Example 1

[0104] 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."

[0105] In conventional legal systems, it took time and effort to manually analyze the outline of the problem and provide an appropriate solution. It was also difficult to effectively collect user feedback and reflect it in system optimization. Furthermore, the collection of updated information on related laws and past case data was not automated, which led to delays in system updates and accuracy improvements.

[0106] 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.

[0107] In this invention, the server includes means for collecting legal-related data and storing it in a database, means for receiving summary data of the problem entered by the user, means for analyzing the received summary data using natural language processing and generating an appropriate solution, means for providing the user with the generated solution and information on the corresponding legal agency, means for receiving user feedback and optimizing the system, means for performing morphological analysis, topic modeling, and similar case search using natural language processing technology on the summary data of the problem entered by the user, means for generating a solution including legally compliant advice and appropriate procedural methods based on the analysis results, and means for storing feedback data entered by the user in the database after providing the generated solution and using it to improve the accuracy of the analysis model and the database. This enables fast and efficient problem analysis and solution presentation, and enables effective collection of user feedback and continuous optimization of the system.

[0108] "Legal data" refers to highly reliable information provided by law firms and courts, including laws, court precedents, legal consultation cases, and other information.

[0109] "Trouble summary data" is data that details the legal problem the user has experienced, including the type of trouble, the date and time of occurrence, the people involved, and the specific circumstances.

[0110] The "database" is an information management system for organizing and storing collected legal-related data, trouble summary data from users, and feedback data.

[0111] "Natural language processing" is a technology that allows computers to understand and analyze natural language used by humans, and includes techniques such as morphological analysis, topic modeling, and similar case search.

[0112] "Morphological analysis" is a technique that breaks down a sentence into words or phrases and analyzes the part of speech and meaning of each word.

[0113] "Topic modeling" is a technology that automatically extracts themes from large amounts of document data and is used to identify major themes from users' problem summary data.

[0114] "Similar case search" is a technology that searches a database of past cases for cases similar to the current trouble summary data and provides reference information.

[0115] A "solution" is a solution that provides users with legal advice and appropriate procedures for dealing with legal issues they are experiencing.

[0116] "Feedback" is data, including ratings and comments entered by users regarding the usefulness and actual results of the solutions provided.

[0117] An "analysis model" is a set of programs based on statistical and machine learning algorithms for natural language processing, which are used to analyze problem summary data and generate solutions.

[0118] "Accuracy improvement" refers to continuous improvement activities to improve the performance of databases and analytical models and provide more accurate and appropriate solutions.

[0119] "Legal Institution" refers to an institution from which users can receive legal assistance or advice, such as a law firm, court, or local government helpline.

[0120] This invention is a comprehensive system for quickly and efficiently providing appropriate solutions to legal problems. This system realizes a series of processes from analyzing legal problems to providing solutions by linking together servers, terminals, and users.

[0121] Server-side behavior

[0122] The server operates primarily using the following hardware and software. The server collects reliable data from law firms, courts, etc. and stores it in a database. It also receives summary data of the problem entered by the user and analyzes it using natural language processing technology. Based on the results, it generates an appropriate solution and provides it to the user.

[0123] Hardware and software used

[0124] Database management system: MySQL (registered trademark), PostgreSQL

[0125] Natural language processing libraries: MeCab, Gensim, ElasticSearch (registered trademark)

[0126] Web scraping tools: Beautiful Soup, Scrapy

[0127] Data collection and storage

[0128] The server periodically collects the latest legal information through web scraping, APIs, and manual input, and then organizes and stores the collected data in a database.

[0129] Analysis of trouble summary data

[0130] The trouble summary data received from users is analyzed using natural language processing technology. Specifically, morphological analysis is performed with MeCab, topic modeling is performed with Gensim, and similar cases are searched for with ElasticSearch.

[0131] Solution generation and delivery

[0132] Based on the analysis results, solutions including legal advice and proper procedural methods are generated, and information on relevant law firms and consultation centers is also provided as needed.

[0133] Feedback collection and optimization

[0134] When users input the results of the solutions they used as feedback, the server stores the information in a database, which is used to improve the accuracy of the system's analytical models and databases.

[0135] Operation on the terminal side

[0136] The terminal provides an interface for users to access the system, through which they can create an account, enter a description of their problem, and receive a solution from the system.

[0137] Hardware and software used

[0138] Web browser: Chrome, Firefox

[0139] Mobile Applications: iOS App, ANDROID(R) App

[0140] User Registration and Login

[0141] Users can create an account through a terminal and enter the necessary information, and existing users can access the system by logging in.

[0142] Enter a summary of the problem

[0143] Users enter detailed information about the problem through a terminal. The form includes items such as the type of problem, the date and time it occurred, the people involved, and specific details of the incident.

[0144] Receiving solutions and feedback

[0145] The user receives and views the solutions provided by the server through the terminal, and also inputs feedback on the results of using the proposed solutions and legal support.

[0146] Specific examples

[0147] Example 1: Labor-related issues

[0148] The user wishes to seek advice regarding unfair dismissal under a labor contract. Using the terminal, the user enters the following information:

[0149] Type of problem: Labor issues

[0150] Date of occurrence: August 15, 2023

[0151] Parties involved: Employee (user), Employer (company)

[0152] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[0153] Then the following solutions are provided:

[0154] Checklist for legality of dismissal under the Labor Standards Act

[0155] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[0156] Introduction to law firms that specialize in labor issues

[0157] Example 2: Consultation regarding contract disputes

[0158] The user is consulting about a problem with renewing a rental contract. They enter the following information through the terminal:

[0159] Type of problem: Contract problem

[0160] Date of occurrence: September 10, 2023

[0161] Parties involved: Tenant (user), landlord (landlord)

[0162] Detailed background: The landlord added unfair conditions when renewing the contract.

[0163] Then the following solutions are provided:

[0164] Procedures for verifying the legality of renewal conditions in lease agreements

[0165] Local government rental housing trouble consultation desk

[0166] Introducing a law firm that specializes in real estate issues

[0167] This allows users to obtain solutions to legal problems quickly and appropriately.

[0168] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0169] Step 1:

[0170] User Registration and Login

[0171] Users access the system using a terminal and create an account. The data entered includes personal information such as name, email address, and password. Existing users log in using their email address and password.

[0172] Input data: Name, email address, password

[0173] Output data: User account information

[0174] Specific behavior:

[0175] User reaches registration / login screen.

[0176] The user enters the required information and clicks the submit button.

[0177] The server receives the input data and stores it in a database or performs authentication.

[0178] Step 2:

[0179] Entering trouble summary data

[0180] After registering or logging in to the system, users enter summary data about the problem. The input form includes items such as the type of problem, the date and time it occurred, the people involved, and specific details of the problem.

[0181] Input data: Type of trouble, date and time of occurrence, people involved, specific details

[0182] Output data: Trouble summary data

[0183] Specific behavior:

[0184] The user accesses the trouble summary input screen.

[0185] The user enters the information corresponding to each item and clicks the submit button.

[0186] The server receives the input data and stores it in a database.

[0187] Step 3:

[0188] Data collection and storage

[0189] The server periodically collects data from law firms and courts using web scraping and APIs, and stores it in a database using Python's Beautiful Soup and Scrapy.

[0190] Input data: Legal data obtained from websites and APIs

[0191] Output data: Legal data stored in a database

[0192] Specific behavior:

[0193] The server initiates web scraping or API calls on a schedule.

[0194] Beautiful Soup or Scrapy retrieves data from a specific website.

[0195] The acquired data is analyzed and stored in a database.

[0196] Step 4:

[0197] Analysis of trouble summary data

[0198] The server analyzes the received trouble summary data using natural language processing technology. Specifically, it performs morphological analysis with MeCab, topic modeling with Gensim, and searches for similar cases with ElasticSearch.

[0199] Input data: Trouble summary data received from the user

[0200] Output data: Morphological analysis results, topic models, search results for similar cases

[0201] Specific behavior:

[0202] The server passes the trouble summary data received from the user to the NLP processing pipeline.

[0203] Morphological analysis is performed using MeCab to decompose the data into grammatical parts.

[0204] Use topic modeling with Gensim to extract themes from the data.

[0205] Search for similar cases using ElasticSearch and evaluate their similarity.

[0206] Step 5:

[0207] Solution Generation

[0208] Based on the analysis results, the server generates an optimal solution, which includes legal advice and appropriate procedural instructions, and, if necessary, provides information on relevant law firms and consultation centers.

[0209] Input data: Analysis results (morphological analysis results, topic model, search results for similar cases)

[0210] Output data: Resolution and corresponding legal authority information

[0211] Specific behavior:

[0212] The server provides data to the solution generation algorithm based on the results of the NLP analysis.

[0213] The algorithm references a database of laws and regulations and past cases to construct an appropriate solution.

[0214] If necessary, include information on relevant law firms and counseling services.

[0215] Step 6:

[0216] Providing solutions

[0217] The user receives the generated solution through the terminal, where the solution is displayed and can be viewed by the user.

[0218] Input data: generated solutions and corresponding legal authority information

[0219] Output: The solution displayed on the user's device

[0220] Specific behavior:

[0221] The server sends the generated solution to the user's device.

[0222] The user receives a notification and is taken to a screen that displays the solution.

[0223] Browse the solutions provided by users.

[0224] Step 7:

[0225] Gathering feedback and optimizing the system

[0226] Users input feedback on the results of using the proposed solutions and legal support. The server receives this feedback data and stores it in a database. The collected feedback data is used to improve the accuracy of the system's analytical model and database.

[0227] Input data: Feedback data from users

[0228] Output data: Feedback data stored in database, updated analytical model and database

[0229] Specific behavior:

[0230] The user accesses the feedback input screen.

[0231] Users provide input on the usefulness of the solution and actual results.

[0232] The server receives the feedback data and stores it in a database.

[0233] The server analyzes the collected feedback and uses it to improve the accuracy of the model and update the database.

[0234] (Application example 1)

[0235] 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."

[0236] In modern society, legal issues are diverse, and problems faced by individuals in particular require prompt and appropriate resolution. However, because specialized knowledge and experience are required, it is difficult for individuals to find the optimal solution on their own. Another major issue is the lack of a way to quickly consult with a legal expert without being tied to a physical location. Furthermore, there is a lack of a mechanism for reflecting the effectiveness of the solution obtained as feedback into the system. In this situation, an efficient system is needed that allows users to easily resolve legal issues and receive expert support.

[0237] 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.

[0238] In this invention, the server includes means for collecting legal-related data and storing it in a database, means for receiving summary data of the problem entered by the user, means for analyzing the received summary data using natural language processing and generating an appropriate solution, means for providing the generated solution and information on the corresponding legal agency to the user, means for receiving user feedback and optimizing the system, and means for enabling communication with legal experts in a virtual environment using a smart device. This allows users to obtain quick and appropriate solutions to legal problems through their smart devices and also allows for real-time consultation with experts, thereby enabling efficient and effective resolution of legal problems.

[0239] "Legal data" refers to information such as laws, precedents, legal advice, and consultation cases collected from law firms, courts, the Ministry of Justice, etc.

[0240] A "database" is a collection of information that organizes and stores legal-related data so that it can be searched and used efficiently.

[0241] "Trouble summary data" refers to specific information about the case, such as the type of trouble entered by the user, the date and time of occurrence, the people involved, and detailed background information.

[0242] "Natural language processing" is a technology for analyzing summary data of a problem entered by a user and generating appropriate solutions, and includes morphological analysis, topic modeling, and similar case search.

[0243] "Solutions" refers to proposals generated by natural language processing that include legal advice, appropriate procedural steps, and information on relevant legal authorities.

[0244] "Legal institutions" refers to organizations that provide legal support, such as law firms, courts, labor bureaus, labor standards inspection offices, and municipal consultation centers.

[0245] "Feedback" refers to a user's evaluation or opinion of the results of using the provided solutions or legal support.

[0246] "Smart devices" refers to electronic devices with advanced functions such as smartphones, smart glasses, and head-mounted displays.

[0247] "Virtual environment" refers to a virtual space or online platform that users can access using smart devices.

[0248] "Communication" refers to the means by which legal professionals and users exchange information in real time through a virtual environment.

[0249] System Overview

[0250] The present invention is a comprehensive system for providing appropriate solutions to legal problems quickly and efficiently. This system mainly operates in cooperation with a server, terminals, and users.

[0251] Server-side behavior

[0252] The server collects reliable data from legal institutions and stores it in a database. It also receives summary data of the problem entered by the user on their device and analyzes it using natural language processing technology. Based on the analysis results, it generates appropriate solutions and provides them to the user. It also collects feedback from users and reflects it in improving the system.

[0253] Data collection and storage

[0254] The server periodically collects the latest information from legal agencies through web scraping, APIs, and manual entry, and the collected data is organized and stored in a database.

[0255] Analysis of trouble summary data

[0256] The server analyzes the trouble summary data received from the user using natural language processing (NLP) techniques, such as morphological analysis, topic modeling, and similar case search.

[0257] Solution generation and delivery

[0258] Based on the analysis results, the server generates an optimal solution, including legal advice and appropriate procedural instructions. It also provides information on relevant legal authorities, if necessary. It also allows users to communicate with legal experts in a virtual environment using their smart devices.

[0259] Feedback collection and optimization

[0260] The server receives feedback from users after they have used the solutions and legal support provided, which is stored in a database and used to improve the accuracy of the system's analytical models and database.

[0261] Operation on the terminal side

[0262] The terminal provides an interface for users to access the system. Users use the terminal to create an account, enter a problem description, and receive a solution from the system. This can be a web browser or a mobile application. Users can also use smart devices to communicate with legal experts in a virtual environment in real time.

[0263] User Registration and Login

[0264] Users create an account through a terminal and enter the necessary information. Existing users can access the system by logging in.

[0265] Enter a summary of the problem

[0266] The user enters detailed information about the problem through a terminal. The form includes items such as the type of problem, the date and time of the problem, the people involved, and specific details of the problem.

[0267] Receiving solutions and feedback

[0268] The user receives and views the solutions provided by the server through the terminal, and also inputs feedback on the results of using the proposed solutions and legal support.

[0269] Specific examples

[0270] Example 1: Labor-related issues

[0271] The user wishes to seek advice regarding unfair dismissal under a labor contract. Using the terminal, the user enters the following information:

[0272] Type of problem: Labor issues

[0273] Date of occurrence: August 15, 2023

[0274] Parties involved: Employee (user), Employer (company)

[0275] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[0276] The server receives this information, analyzes it, and makes the following suggestions:

[0277] Checklist for legality of dismissal under the Labor Standards Act

[0278] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[0279] Introduction to law firms that specialize in labor issues

[0280] The user acts on the presented solution and reports the results to the system as feedback.

[0281] Example 2: Consultation regarding contract disputes

[0282] The user wishes to consult about a problem regarding the renewal of a rental contract. The user enters the following information through the terminal:

[0283] Type of problem: Contract problem

[0284] Date of occurrence: September 10, 2023

[0285] Parties involved: Tenant (user), landlord (landlord)

[0286] Detailed background: The landlord added unfair conditions when renewing the contract.

[0287] The server receives this information, analyzes it, and makes the following suggestions:

[0288] Procedures for verifying the legality of renewal conditions in lease agreements

[0289] Local government rental housing trouble consultation desk

[0290] Introducing a law firm that specializes in real estate issues

[0291] The user takes specific action based on the presented solution and reports the results to the system as feedback.

[0292] Example prompts for generative AI models

[0293] "Unfair terms were presented during the contract renewal. Type of problem: Contract dispute, Date of occurrence: September 10, 2023, Parties involved: Tenant and Landlord."

[0294] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0295] Step 1:

[0296] The user creates an account using a terminal and enters the necessary information. The input for this step is the user's personal information and login information. The output is that the user account has been created and is ready to log in.

[0297] Step 2:

[0298] The user inputs detailed information about the problem through the terminal. Specifically, the type of problem, the date and time of occurrence, the people involved, and the specific details. The input of this step is detailed information about the problem, and the output is that this information is sent to the server.

[0299] Step 3:

[0300] The server analyzes the received problem summary data using natural language processing (NLP) technology. The input for this step is the problem summary data sent by the user, and the output is a set of analyzed topics and keywords. Specific operations include morphological analysis, topic modeling, and similar case search.

[0301] Step 4:

[0302] The server generates optimal solutions based on the analysis results. It searches the database for appropriate laws and cases based on the analyzed topics and keywords, and generates legal advice and appropriate procedural methods. The input for this step is the analysis results and related information in the database, and the output is the generated solution.

[0303] Step 5:

[0304] The generated solution and corresponding legal authority information are provided to the user. The server sends the generated solution to the terminal, where the user can view it. The input of this step is the generated solution, and the output is a display of the solution that can be viewed by the user.

[0305] Step 6:

[0306] The server enables real-time communication with a legal expert in a virtual environment using a smart device. The user then uses the smart device to video chat with the legal expert for further consultation. The input of this step is the user's communication request, and the output is the initiation of a real-time video chat session with the legal expert.

[0307] Step 7:

[0308] The user inputs the results of using the provided solutions and legal support as feedback. The feedback is sent to the server and stored in the database. The input of this step is the user's feedback, and the output is the accumulation of feedback in the database.

[0309] Step 8:

[0310] The server uses the collected feedback to refine the system's analytical model and database. The input for this step is the feedback data, and the output is an improved analytical model and a refined database. Specific operations include retraining the model using machine learning algorithms.

[0311] 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.

[0312] System Overview

[0313] This invention is a comprehensive system for quickly and efficiently providing appropriate solutions to legal disputes, and in particular, it incorporates an emotion engine that recognizes the user's emotional state and reflects it in the solution. This system mainly operates in cooperation with a server, terminals, and users.

[0314] Server-side behavior

[0315] The server collects reliable data from law firms and courts and stores it in a database. It also receives summary data of the problem entered by the user and analyzes it using natural language processing and an emotion engine. Based on the analysis results, it generates an appropriate solution and provides it to the user. It also collects feedback from users and reflects it in improving the system.

[0316] Data collection and storage

[0317] The server periodically collects the latest information from law firms and courts through web scraping, APIs, and manual entry, and the collected data is organized and stored in a database.

[0318] Analysis of trouble summary data

[0319] The server analyzes the trouble summary data received from the user using natural language processing (NLP) technology and an emotion engine. It uses an NLP model (e.g., BERT or GPT) to classify the input data, extract important keywords, and understand the details of the trouble. At the same time, it uses the emotion engine to analyze the user's emotional state from the input.

[0320] Solution generation and delivery

[0321] Based on the analysis results, the server generates an optimal solution, including legal advice and appropriate procedural instructions. The solution presentation is tailored to the user's emotional state. If necessary, information on relevant law firms or local government consultation services is also provided.

[0322] Feedback collection and optimization

[0323] The server receives feedback from users after they use the solutions and consultation services provided. This feedback is stored in a database and used to improve the accuracy of the system's analytical model and emotion engine, allowing the system to be continuously optimized.

[0324] Operation on the terminal side

[0325] The terminal provides the interface through which users access the system. The terminal is used by users to create an account, enter a problem description, and receive a solution from the system. This can be a web browser or a mobile application.

[0326] User Registration and Login

[0327] Users create an account through a terminal and enter the necessary information. Existing users can access the system by logging in.

[0328] Enter a summary of the problem

[0329] The user uses a terminal to enter detailed information about the problem. The form includes items such as the type of problem, the date and time of the problem, the people involved, and specific details. The data entered by the user is sent to the server.

[0330] Receiving solutions and feedback

[0331] The user can view the solutions provided by the server through their device and take action if necessary. They can contact the suggested law firms or counseling centers. They can also input feedback on the solutions provided and the results of using legal support.

[0332] Specific examples

[0333] Example 1: Labor-related issues

[0334] The user wishes to seek advice regarding unfair dismissal under a labor contract. Using the terminal, the user enters the following information:

[0335] Type of problem: Labor issues

[0336] Date of occurrence: August 15, 2023

[0337] Parties involved: Employee (user), Employer (company)

[0338] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[0339] As you type, the emotion engine recognizes your emotions, such as anger or anxiety.

[0340] The server receives this information, analyzes it, and makes the following suggestions:

[0341] Checklist for legality of dismissal under the Labor Standards Act

[0342] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[0343] Introduction to law firms that specialize in labor issues

[0344] In response to any concerns users may have, the message is presented in a reassuring manner, such as "verifying legality should be given priority."

[0345] The user acts on the presented solution and reports the results to the system as feedback.

[0346] Example 2: Consultation regarding contract disputes

[0347] The user wishes to consult about a problem regarding the renewal of a rental contract. The user enters the following information through the terminal:

[0348] Type of problem: Contract problem

[0349] Date of occurrence: September 10, 2023

[0350] Parties involved: Tenant (user), landlord (landlord)

[0351] Detailed background: The landlord added unfair conditions when renewing the contract.

[0352] Upon input, the emotion engine recognizes the user's confused emotion.

[0353] The server receives this information, analyzes it, and makes the following suggestions:

[0354] Procedures for verifying the legality of renewal conditions in lease agreements

[0355] Local government rental housing trouble consultation desk

[0356] Introducing a law firm that specializes in real estate issues

[0357] To reduce user confusion, encouraging statements such as "Follow the detailed verification steps and the problem will be resolved" are presented.

[0358] The user takes specific action based on the presented solution and reports the results to the system as feedback.

[0359] In this way, by combining emotion engines, it becomes possible to provide solutions that take into account the user's emotional state, thereby providing effective support for legal disputes.

[0360] The processing flow will be explained below.

[0361] Step 1:

[0362] The server collects reliable data from law firms and courts. It uses web scraping and APIs to obtain the latest laws, precedents, contracts, etc., and stores them in a database. Additionally, it uses OCR technology to digitize manually collected materials as needed and registers them in the database.

[0363] Step 2:

[0364] Users access the system using a terminal and create an account or log in. New users create an account by entering personal information such as their name, email address, and password. Existing users log in by entering their email address and password.

[0365] Step 3:

[0366] The user uses the terminal to enter an outline of the problem. The input form includes items such as the type of problem, the date and time of occurrence, the people involved, and specific details. The user enters this information in detail and presses the send button.

[0367] Step 4:

[0368] The server receives the summary data of the problem sent by the user and stores it in a temporary database. At this point, a simple error check is performed to ensure that there are no problems with the format or content of the input data.

[0369] Step 5:

[0370] The server analyzes the received summary data of the trouble using natural language processing (NLP) technology and an emotion engine. It uses an NLP model (e.g., BERT or GPT) to classify the input data, extract important keywords, and understand the content of the trouble. At the same time, it uses the emotion engine to analyze the emotional state from the user's input.

[0371] Step 6:

[0372] The server uses the analysis results to search for similar cases and related laws and regulations in its database. Based on the search results, it generates the optimal solution and determines its content. The solution includes legal advice and appropriate procedural methods.

[0373] Step 7:

[0374] The server adjusts the content of the solution presented to the user depending on the user's emotional state. For example, if the user is feeling strong emotions such as anxiety or anger, the server changes the presented solution to be more reassuring.

[0375] Step 8:

[0376] The server provides the generated solution to the user, and also lists and displays to the user information on law firms and details of local government consultation centers related to the solution.

[0377] Step 9:

[0378] The user can view the solutions provided by the server through their device and take action if necessary, including contacting the suggested law firm or counseling center.

[0379] Step 10:

[0380] Users enter their feedback on the solutions provided and the results of using the support service in a feedback form, including their evaluation of the effectiveness of the solutions and the quality of the support.

[0381] Step 11:

[0382] The server receives feedback from users and stores it in a database. The collected feedback is used to improve the accuracy of the system's analytical model and emotion engine, allowing the system to be continuously optimized.

[0383] Specific examples

[0384] Example 1: Labor-related issues

[0385] The user wishes to seek advice regarding unfair dismissal under a labor contract. Using the terminal, the user enters the following information:

[0386] Type of problem: Labor issues

[0387] Date of occurrence: August 15, 2023

[0388] Parties involved: Employee (user), Employer (company)

[0389] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[0390] As you type, the emotion engine recognizes your emotions, such as anger or anxiety.

[0391] The server receives this information, analyzes it, and makes the following suggestions:

[0392] Checklist for legality of dismissal under the Labor Standards Act

[0393] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[0394] Introduction to law firms that specialize in labor issues

[0395] In response to any concerns users may have, the message is presented in a reassuring manner, such as "verifying legality should be given priority."

[0396] The user acts on the presented solution and reports the results to the system as feedback.

[0397] Example 2: Consultation regarding contract disputes

[0398] The user wishes to consult about a problem regarding the renewal of a rental contract. The user enters the following information through the terminal:

[0399] Type of problem: Contract problem

[0400] Date of occurrence: September 10, 2023

[0401] Parties involved: Tenant (user), landlord (landlord)

[0402] Detailed background: The landlord added unfair conditions when renewing the contract.

[0403] Upon input, the emotion engine recognizes the user's confused emotion.

[0404] The server receives this information, analyzes it, and makes the following suggestions:

[0405] Procedures for verifying the legality of renewal conditions in lease agreements

[0406] Local government rental housing trouble consultation desk

[0407] Introducing a law firm that specializes in real estate issues

[0408] To reduce user confusion, encouraging statements such as "Follow the detailed verification steps and the problem will be resolved" are presented.

[0409] The user takes specific action based on the presented solution and reports the results to the system as feedback.

[0410] In this way, by combining emotion engines, it becomes possible to provide solutions that take into account the user's emotional state, thereby providing effective support for legal disputes.

[0411] Example 2

[0412] 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."

[0413] Conventional legal systems only provide solutions to legal disputes without taking into account the user's emotional state. This can lead to problems such as users finding it difficult to understand the solutions or lacking motivation to take appropriate action. Furthermore, they lack the ability to collect feedback and optimize the system to improve the effectiveness of the solutions provided.

[0414] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0415] In this invention, the server includes means for collecting legal-related data and storing it in a database, means for receiving summary data of the problem entered by the user, means for analyzing the received summary data using natural language processing and generating an appropriate solution, means for adjusting the way the solution is presented using an emotion engine that analyzes the user's emotional state, means for providing the user with the generated solution and information on the corresponding legal agency, and means for receiving user feedback and optimizing the system. This makes it possible to provide solutions that take the user's emotional state into consideration, thereby realizing more effective support for legal troubles.

[0416] "Legal data" refers to information such as laws, precedents, cases, and legal consultation results collected from law firms and courts.

[0417] A "database" is an information system that organizes and stores collected legal-related data, allowing it to be efficiently searched and accessed when needed.

[0418] "User" means an individual or organization that uses the system to seek legal advice.

[0419] "Summary data of the trouble" is detailed information entered by the user, such as the type of trouble, the date and time of occurrence, the people involved, and the specific details of the trouble.

[0420] "Natural language processing" is a technology that analyzes and processes text data entered by the user to understand and generate human language.

[0421] "Solutions" are specific advice or suggestions generated to solve a problem based on trouble data analyzed using natural language processing.

[0422] An "emotion engine" is a technology that analyzes a user's emotional state and adjusts the way solutions are presented to take those emotions into consideration.

[0423] "Feedback" refers to the user's opinions and evaluations of the solutions provided or the results of using the consultation service.

[0424] "System optimization" is the process of continuously improving the overall performance and accuracy of the system based on collected feedback.

[0425] "Legal institutions" are organizations that provide legal support, such as law firms, courts, and local government helplines.

[0426] A "natural language processing model" is a machine learning model, such as BERT or GPT, that is used to understand and analyze user input text and generate appropriate solutions.

[0427] "Solution presentation method" is a means of adjusting the content and presentation of the solution depending on the user's emotional state.

[0428] "Information provision" is the process of communicating generated solutions and relevant legal information to users.

[0429] MODE FOR CARRYING OUT THE INVENTION

[0430] System Overview

[0431] This invention is a system for quickly and efficiently providing appropriate solutions to legal problems, and in particular, it combines an emotion engine that recognizes the user's emotional state and reflects it in the solution. This system mainly operates in cooperation with a server, terminals, and users.

[0432] System configuration

[0433] The server collects reliable data from law firms and courts and stores it in a database. It also receives summary data of the problem entered by the user and analyzes it using natural language processing and an emotion engine. Based on the analysis results, it generates an appropriate solution and provides it to the user. It also collects feedback from users and reflects it in improving the system. Specifically, the following hardware and software are used:

[0434] Hardware: Servers, client devices (PCs, smartphones, tablets)

[0435] Software: Natural language processing models (BERT, GPT), sentiment engine, database management system, web server

[0436] Server-side behavior

[0437] 1. Data collection and storage:

[0438] The server periodically collects the latest legal information using web scraping, APIs, and manual input.

[0439] The collected data is organized and stored in a database.

[0440] 2. Analysis of Trouble Summary Data:

[0441] The server analyzes the summary data of the problem received from the user using natural language processing (NLP) techniques such as BERT and GPT.

[0442] Through analysis, the input data is classified, important keywords are extracted, and the nature of the problem is understood.

[0443] At the same time, an emotion engine is used to analyze the emotional state from the user's input.

[0444] 3. Solution generation and delivery:

[0445] Based on the analysis, the server generates an optimal solution, which may include legal advice and proper procedural instructions.

[0446] The system adjusts the way solutions are presented depending on the user's emotional state, and also provides information on relevant law firms and local government consultation services.

[0447] 4. Feedback collection and optimization:

[0448] The server receives feedback from the user after the user has used the provided solutions and helplines.

[0449] The feedback is stored in a database and used to improve the accuracy of the system's analytical models and emotion engine.

[0450] Operation on the terminal side

[0451] 1. User Registration and Login:

[0452] Users create an account through a terminal and enter the necessary information. Existing users can access the system by logging in.

[0453] 2. Enter a summary of the problem:

[0454] The user uses a terminal to input detailed information about the problem. The input format includes text boxes where the user can enter the type of problem, the date and time of occurrence, the people involved, and detailed information about the problem.

[0455] The user's input data is sent to the server.

[0456] 3. Receiving solutions and feedback:

[0457] The user can view the solutions provided by the server through the terminal and take action as necessary.

[0458] Provide feedback on the solutions provided and the results of using legal support.

[0459] Specific examples

[0460] Example 1: Labor-related issues

[0461] When a user wishes to consult about unfair dismissal under a labor contract, the user inputs the following information using a terminal.

[0462] Type of problem: Labor issues

[0463] Date of occurrence: August 15, 2023

[0464] Parties involved: Employee (user), Employer (company)

[0465] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[0466] As you type, the emotion engine recognizes your emotions, such as anger or anxiety.

[0467] The server receives this information, analyzes it, and makes the following suggestions:

[0468] Checklist for legality of dismissal under the Labor Standards Act

[0469] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[0470] Introduction to law firms that specialize in labor issues

[0471] The solution is presented in a way that gives the user a sense of security, such as "Confirming legality should be prioritized," in response to any concerns the user may have. The user then takes action based on the presented solution and reports the results to the system as feedback.

[0472] Example 2: Consultation regarding contract disputes

[0473] When consulting about a problem with renewing a rental contract, the user enters the following information:

[0474] Type of problem: Contract problem

[0475] Date of occurrence: September 10, 2023

[0476] Parties involved: Tenant (user), landlord (landlord)

[0477] Detailed background: The landlord added unfair conditions when renewing the contract.

[0478] Upon input, the emotion engine recognizes the user's confused emotion.

[0479] The server receives this information, analyzes it, and makes the following suggestions:

[0480] Procedures for verifying the legality of renewal conditions in lease agreements

[0481] Local government rental housing trouble consultation desk

[0482] Introducing a law firm that specializes in real estate issues

[0483] To alleviate user confusion, encouraging messages such as, "Follow the detailed confirmation steps and your problem will be solved." In this way, by combining the emotion engine, it is possible to provide solutions that take into account the user's emotional state, thereby achieving effective support for legal disputes.

[0484] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0485] Step 1: User registration and login

[0486] Users create an account using a device. They register by entering their username, email address, password, etc. Existing users can log in by entering their account information.

[0487] The device sends the entered information to the server, which receives it, stores it in a database, verifies the login information, and redirects the user to the dashboard if authentication is successful.

[0488] Input: User information (user name, email address, password)

[0489] Output: Authentication results, dashboard access

[0490] Step 2: Enter a description of the problem

[0491] The user uses the terminal to input detailed information about the problem, such as the type of problem, the date and time of occurrence, the people involved, and a detailed history of the problem, into an input form.

[0492] The terminal sends the entered data to the server, which stores the received data in a database. Once the data is stored, the analysis process is initiated.

[0493] Input: Detailed information about the problem (type, date and time of occurrence, people involved, detailed history)

[0494] Output: Saving data and launching analysis processes

[0495] Step 3: Analyze the trouble summary data

[0496] The server analyzes the received summary data of the trouble using natural language processing models such as BERT and GPT.

[0497] For analysis, the data is pre-processed (tokenized and normalized) and then input into the model. The NLP model analyzes the text data, extracts important keywords and phrases, and classifies the content of the problem.

[0498] Input: Summary of the problem

[0499] Output: Analysis results (keywords, classification results)

[0500] Step 4: Analyze emotional state

[0501] Based on the results of the natural language processing analysis, the server uses an emotion engine to analyze the user's emotional state.

[0502] The text data is input into an emotion model to identify the user's emotion (e.g., anger, anxiety, confusion), and the emotion model returns the result.

[0503] Input: Analysis results (keywords, classification results)

[0504] Output: Emotion analysis results (anger, anxiety, confusion, etc.)

[0505] Step 5: Generate a solution

[0506] The server generates an appropriate solution based on the content of the problem and the user's emotional state, and refers to a legal database to collect relevant information.

[0507] Solutions include legal advice and specific procedural steps, and are tailored to the user's emotional state.

[0508] Input: Sentiment analysis results, legal data

[0509] Output: Generated solution

[0510] Step 6: Propose a solution

[0511] The server sends the generated solution to the terminal.

[0512] The device displays a solution to the user. The solution is presented in a way that takes into consideration the user's emotions. For example, if the user is feeling anxious, the device uses reassuring language such as "First, confirming legality is a priority."

[0513] Input: Generated solution

[0514] Output: The solution that is displayed to the user

[0515] Step 7: Receiving feedback

[0516] The user acts on the provided solutions and provides feedback on the results.

[0517] The device receives the feedback and sends it to a server, which stores it in a database and uses it for analysis.

[0518] Input: User feedback

[0519] Output: feedback storage and system optimization

[0520] This series of steps not only provides users with a fast and appropriate solution, but also takes into account the user's emotional state. The system is continuously improved using collected feedback.

[0521] (Application example 2)

[0522] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0523] In modern society, the number of opportunities to face legal troubles and security issues is increasing, and resolving these issues requires providing prompt and accurate information. Furthermore, if individual responses are not given taking into account the user's emotional state, users' stress and anxiety will increase, which will become a barrier to problem resolution. Therefore, a system that provides legal and security advice combined with emotion recognition is needed.

[0524] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting legal-related data and storing it in a database, means for receiving summary data of the problem entered by the user, means for analyzing the received summary data using natural language processing and emotion recognition to generate an appropriate solution, means for providing the generated solution and information on corresponding related organizations to the user, and means for receiving user feedback and optimizing the system. This makes it possible to provide quick and emotion-sensitive solutions to legal and security issues.

[0525] "Legal data" is a general term for information about laws, precedents, legal advice, and procedures collected from law firms, courts, government agencies, etc.

[0526] A "database" is an information management system that systematically stores collected legal data, user input data, feedback information, etc., and uses them for search and analysis.

[0527] "Summary data of the trouble entered by the user" refers to detailed information provided by the user to the system, such as the type of trouble, the date and time of occurrence, the people involved, and the specific details of the trouble.

[0528] "Natural language processing" is a technology that analyzes summary data of problems and other text data to extract and classify important keywords, and is a method for computers to understand and process human language.

[0529] "Emotion recognition" is a technology that analyzes and recognizes a user's emotional state (e.g., anger, anxiety, confusion, etc.) from text and other data entered by the user.

[0530] "Appropriate solutions" are those that provide legally accurate and feasible advice and procedures for the problems users are facing, based on collected legal data and analysis results.

[0531] "Related institutions" is a general term for specialized institutions or organizations related to resolving user disputes, such as law firms, courts, and consultation centers.

[0532] "Feedback" means any evaluation or comment you make about the results or experience you have had implementing or using a solution or service provided.

[0533] "Optimization" is the process of improving models and algorithms based on feedback received from users in order to improve the overall performance and accuracy of the system.

[0534] System Overview

[0535] This invention is a system for providing quick and effective solutions to legal and security disputes. In particular, it incorporates an emotion recognition engine that recognizes the user's emotional state and reflects it in the solution. This system mainly operates in cooperation with a server, terminals, and users.

[0536] Server-side behavior

[0537] The server collects legal data and stores it in a database. Specifically, the server periodically collects data automatically from authorized data sources (e.g., law firms, courts, and government agencies). This data collection is done using web scraping, APIs, and manual entry. The collected data is then organized and stored in a database.

[0538] After receiving the user's summary of the problem, the server analyzes it using natural language processing (NLP) technology and an emotion recognition engine. NLP models used, such as BERT and GPT, classify the input data, extract important keywords, and understand the nature of the problem. At the same time, the emotion recognition engine analyzes the user's emotional state from the input.

[0539] Based on the analysis results, the server generates an optimal solution, including legal advice and appropriate procedural instructions. The solution presentation is tailored to the user's emotional state. It also provides information on relevant law firms and local government consultation services.

[0540] After users use the solutions and consultation services provided, the server receives feedback, which is stored in a database and used to improve the accuracy of the system's analytical models and emotion recognition engine, allowing the system to be continuously optimized.

[0541] Operation on the terminal side

[0542] The terminal provides an interface for users to access the system. Users can use the terminal to create an account, enter a summary of the problem, and receive a solution from the system. Specifically, this role is played by a web browser or a mobile application.

[0543] Users create an account through their device and enter the necessary information. Existing users can access the system by logging in. When entering detailed information about a problem using the device, the emotion recognition engine analyzes the user's emotions in real time and sends the analysis results to the server.

[0544] After receiving the solution provided by the server, the user can view the solution through the terminal and take action if necessary. The user can also contact the suggested law firm or consultation center through the terminal. In addition, the user can enter feedback on the results of using the provided solution.

[0545] Specific examples

[0546] Example 1: Labor-related issues

[0547] When a user wishes to consult about unfair dismissal under a labor contract, the user enters the following information using the terminal.

[0548] Type of problem: Labor issues

[0549] Date of occurrence: August 15, 2023

[0550] Parties involved: Employee (user), Employer (company)

[0551] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[0552] When inputting, the emotion recognition engine recognizes the user's emotions such as anger or anxiety. The server receives this information and analyzes it. As a result, it makes the following suggestions:

[0553] Checklist for legality of dismissal under the Labor Standards Act

[0554] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[0555] Introduction to law firms that specialize in labor issues

[0556] In response to users' concerns, solutions are presented in a reassuring manner, such as "verifying legality should be given priority."

[0557] Example 2: Consultation regarding contract disputes

[0558] When a user wishes to consult about a problem with renewing a rental contract, the user enters the following information through the terminal.

[0559] Type of problem: Contract problem

[0560] Date of occurrence: September 10, 2023

[0561] Parties involved: Tenant (user), landlord (landlord)

[0562] Detailed background: The landlord added unfair conditions when renewing the contract.

[0563] When inputting, the emotion recognition engine will recognize the user's confused emotion. The server will receive this information and analyze it. As a result, it will make the following suggestions:

[0564] Procedures for verifying the legality of renewal conditions in lease agreements

[0565] Local government rental housing trouble consultation desk

[0566] Introducing a law firm that specializes in real estate issues

[0567] To reduce user confusion, solutions are presented in encouraging language such as, "Follow our detailed verification steps and your problem will be resolved."

[0568] Prompt Sentence Examples

[0569] For example, a generative AI model operates using prompt statements such as the following:

[0570] Type of problem: Contract problem

[0571] Problem description: Last night I received an email that I suspected was a phishing scam.

[0572] Emotional state: Anxiety

[0573] Legal advice: Check if the link is from a trusted site, avoid opening suspicious emails, and contact the police or security agencies.

[0574] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0575] Step 1:

[0576] A user accesses a device and creates or logs in to an account. The input data is the user's authentication information (username, password, etc.). The device receives this and sends it to the server. The server performs authentication and, if successful, returns the user's profile information to the device.

[0577] Step 2:

[0578] The user uses a terminal to input summary data about the problem. The input data includes the type of problem, the date and time of occurrence, the people involved, and a detailed history. The terminal receives this data and sends it to the server.

[0579] Step 3:

[0580] The server analyzes the received summary data of the trouble using natural language processing (NLP). It uses an NLP model (e.g., BERT, GPT, etc.) to classify the input data and extract keywords. The input data is the trouble text, and the output data is the analyzed keyword list and classification results.

[0581] Step 4:

[0582] The server simultaneously uses an emotion recognition engine to analyze the user's emotional state. The input data is the summary of the problem, and the output data is the user's emotional state (e.g., anger, anxiety, confusion, etc.). The analysis results are combined with the results of natural language processing.

[0583] Step 5:

[0584] The server generates appropriate solutions based on the analysis results. The solution generation utilizes collected legal data and information from related agencies. The input data is the NLP and emotion recognition results, and the output data is the solution and information from related agencies.

[0585] Step 6:

[0586] The server sends the generated solution and related organization information to the terminal. The user uses the terminal to view the solution. The output data is the solution and related organization information.

[0587] Step 7:

[0588] The user takes action based on the provided solution and inputs the results as feedback into the device. The input data is the feedback content (e.g., satisfaction level, additional comments). The device receives this and sends it to the server.

[0589] Step 8:

[0590] The server receives the feedback and stores it in a database. The input data is the user's feedback. The server optimizes the analysis model and emotion recognition engine for future solution generation. This improves the accuracy and usefulness of the system.

[0591] 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.

[0592] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0593] 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.

[0594] [Second embodiment]

[0595] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0596] 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.

[0597] 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).

[0598] 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.

[0599] 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.

[0600] 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).

[0601] 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.

[0602] 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.

[0603] 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.

[0604] 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.

[0605] 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.

[0606] 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."

[0607] System Overview

[0608] The present invention is a comprehensive system for providing appropriate solutions to legal problems quickly and efficiently. This system mainly operates in cooperation with a server, terminals, and users.

[0609] Server-side behavior

[0610] The server collects reliable data from law firms, courts, and other sources and stores it in a database. It also receives summary data about the problem entered by the user on their device and analyzes it using natural language processing technology. Based on the analysis results, it generates appropriate solutions and provides them to the user. It also collects feedback from users and reflects it in improving the system.

[0611] Data collection and storage

[0612] The server periodically collects the latest information from law firms and courts through web scraping, APIs, and manual entry, and the collected data is organized and stored in a database.

[0613] Analysis of trouble summary data

[0614] The server analyzes the trouble summary data received from the user using natural language processing (NLP) techniques, such as morphological analysis, topic modeling, and similar case search.

[0615] Solution generation and delivery

[0616] Based on the analysis results, the server generates an optimal solution, which includes legal advice and appropriate procedural instructions, and, if necessary, provides information on relevant law firms and local government consultation services.

[0617] Feedback collection and optimization

[0618] The server receives feedback from users after they have used the solutions and consultation services provided, and this feedback is stored in a database and used to improve the accuracy of the system's analytical model and database.

[0619] Operation on the terminal side

[0620] The terminal provides the interface through which users access the system. The terminal is used by users to create an account, enter a problem description, and receive a solution from the system. This can be a web browser or a mobile application.

[0621] User Registration and Login

[0622] Users create an account through a terminal and enter the necessary information. Existing users can access the system by logging in.

[0623] Enter a summary of the problem

[0624] The user enters detailed information about the problem through a terminal. The form includes items such as the type of problem, the date and time of the problem, the people involved, and specific details of the problem.

[0625] Receiving solutions and feedback

[0626] The user receives and views the solutions provided by the server through the terminal, and also inputs feedback on the results of using the proposed solutions and legal support.

[0627] Specific examples

[0628] Example 1: Labor-related issues

[0629] The user wishes to seek advice regarding unfair dismissal under a labor contract. Using the terminal, the user enters the following information:

[0630] Type of problem: Labor issues

[0631] Date of occurrence: August 15, 2023

[0632] Parties involved: Employee (user), Employer (company)

[0633] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[0634] The server receives this information, analyzes it, and makes the following suggestions:

[0635] Checklist for legality of dismissal under the Labor Standards Act

[0636] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[0637] Introduction to law firms that specialize in labor issues

[0638] The user acts on the presented solution and reports the results to the system as feedback.

[0639] Example 2: Consultation regarding contract disputes

[0640] The user wishes to consult about a problem regarding the renewal of a rental contract. The user enters the following information through the terminal:

[0641] Type of problem: Contract problem

[0642] Date of occurrence: September 10, 2023

[0643] Parties involved: Tenant (user), landlord (landlord)

[0644] Detailed background: The landlord added unfair conditions when renewing the contract.

[0645] The server receives this information, analyzes it, and makes the following suggestions:

[0646] Procedures for verifying the legality of renewal conditions in lease agreements

[0647] Local government rental housing trouble consultation desk

[0648] Introducing a law firm that specializes in real estate issues

[0649] The user takes specific action based on the presented solution and reports the results to the system as feedback.

[0650] In this way, the system of the present invention provides comprehensive support for quickly and appropriately responding to legal troubles.

[0651] The processing flow will be explained below.

[0652] Step 1:

[0653] The server collects reliable data from law firms and courts. It uses web scraping and APIs to obtain the latest laws, precedents, contracts, etc., and stores them in a database. Additionally, it uses OCR technology to digitize manually collected materials as needed and registers them in the database.

[0654] Step 2:

[0655] Users access the system using a terminal and create an account or log in. New users create an account by entering personal information such as their name, email address, and password. Existing users enter their email address and password, which are then verified by the server.

[0656] Step 3:

[0657] The user uses the terminal to input an outline of the problem. The input form includes items such as the type of problem, the date and time of occurrence, the people involved, and specific details. The user enters this information in detail.

[0658] Step 4:

[0659] The server receives the summary data of the problem sent by the user and stores it in a temporary database. At this point, a simple error check is performed to ensure that there are no problems with the format or content of the input data.

[0660] Step 5:

[0661] The server analyzes the received summary data of the problem using natural language processing (NLP) technology. It uses an NLP model (e.g., BERT or GPT) to classify the input data, extract important keywords, and understand the content of the problem.

[0662] Step 6:

[0663] The server searches the database for similar cases and related laws and regulations based on the analysis results, and generates the optimal solution based on the search results and determines which solution to provide to the user.

[0664] Step 7:

[0665] The server provides the generated solution to the user, and also lists and displays to the user information on law firms and details of local government consultation centers related to the solution.

[0666] Step 8:

[0667] The user can view the solutions provided by the server through their device and take action if necessary, including contacting the suggested law firm or counseling center.

[0668] Step 9:

[0669] Users enter their feedback on the solutions provided and the results of using the support service in a feedback form, including their evaluation of the effectiveness of the solutions and the quality of the support.

[0670] Step 10:

[0671] The server receives feedback from users and stores it in a database. The collected feedback is used to improve the accuracy of the system's analytical model and database, allowing the system to be continuously optimized.

[0672] Through these steps, this system provides users with efficient solutions to legal problems and creates an environment where they can easily access reliable legal support.

[0673] Example 1

[0674] 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."

[0675] In conventional legal systems, it took time and effort to manually analyze the outline of the problem and provide an appropriate solution. It was also difficult to effectively collect user feedback and reflect it in system optimization. Furthermore, the collection of updated information on related laws and past case data was not automated, which led to delays in system updates and accuracy improvements.

[0676] 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.

[0677] In this invention, the server includes means for collecting legal-related data and storing it in a database, means for receiving summary data of the problem entered by the user, means for analyzing the received summary data using natural language processing and generating an appropriate solution, means for providing the user with the generated solution and information on the corresponding legal agency, means for receiving user feedback and optimizing the system, means for performing morphological analysis, topic modeling, and similar case search using natural language processing technology on the summary data of the problem entered by the user, means for generating a solution including legally compliant advice and appropriate procedural methods based on the analysis results, and means for storing feedback data entered by the user in the database after providing the generated solution and using it to improve the accuracy of the analysis model and the database. This enables fast and efficient problem analysis and solution presentation, and enables effective collection of user feedback and continuous optimization of the system.

[0678] "Legal data" refers to highly reliable information provided by law firms and courts, including laws, court precedents, legal consultation cases, and other information.

[0679] "Trouble summary data" is data that details the legal problem the user has experienced, including the type of trouble, the date and time of occurrence, the people involved, and the specific circumstances.

[0680] The "database" is an information management system for organizing and storing collected legal-related data, trouble summary data from users, and feedback data.

[0681] "Natural language processing" is a technology that allows computers to understand and analyze natural language used by humans, and includes techniques such as morphological analysis, topic modeling, and similar case search.

[0682] "Morphological analysis" is a technique that breaks down a sentence into words or phrases and analyzes the part of speech and meaning of each word.

[0683] "Topic modeling" is a technology that automatically extracts themes from large amounts of document data and is used to identify major themes from users' problem summary data.

[0684] "Similar case search" is a technology that searches a database of past cases for cases similar to the current trouble summary data and provides reference information.

[0685] A "solution" is a solution that provides users with legal advice and appropriate procedures for dealing with legal issues they are experiencing.

[0686] "Feedback" is data, including ratings and comments entered by users regarding the usefulness and actual results of the solutions provided.

[0687] An "analysis model" is a set of programs based on statistical and machine learning algorithms for natural language processing, which are used to analyze problem summary data and generate solutions.

[0688] "Accuracy improvement" refers to continuous improvement activities to improve the performance of databases and analytical models and provide more accurate and appropriate solutions.

[0689] "Legal Institution" refers to an institution from which users can receive legal assistance or advice, such as a law firm, court, or local government helpline.

[0690] This invention is a comprehensive system for quickly and efficiently providing appropriate solutions to legal problems. This system realizes a series of processes from analyzing legal problems to providing solutions by linking together servers, terminals, and users.

[0691] Server-side behavior

[0692] The server operates primarily using the following hardware and software. The server collects reliable data from law firms, courts, etc. and stores it in a database. It also receives summary data of the problem entered by the user and analyzes it using natural language processing technology. Based on the results, it generates an appropriate solution and provides it to the user.

[0693] Hardware and software used

[0694] Database management systems: MySQL, PostgreSQL

[0695] Natural Language Processing Libraries: MeCab, Gensim, ElasticSearch

[0696] Web scraping tools: Beautiful Soup, Scrapy

[0697] Data collection and storage

[0698] The server periodically collects the latest legal information through web scraping, APIs, and manual input, and then organizes and stores the collected data in a database.

[0699] Analysis of trouble summary data

[0700] The trouble summary data received from users is analyzed using natural language processing technology. Specifically, morphological analysis is performed with MeCab, topic modeling is performed with Gensim, and similar cases are searched for with ElasticSearch.

[0701] Solution generation and delivery

[0702] Based on the analysis results, solutions including legal advice and proper procedural methods are generated, and information on relevant law firms and consultation centers is also provided as needed.

[0703] Feedback collection and optimization

[0704] When users input the results of the solutions they used as feedback, the server stores the information in a database, which is used to improve the accuracy of the system's analytical models and databases.

[0705] Operation on the terminal side

[0706] The terminal provides an interface for users to access the system, through which they can create an account, enter a description of their problem, and receive a solution from the system.

[0707] Hardware and software used

[0708] Web browser: Chrome, Firefox

[0709] Mobile Applications: iOS App, Android App

[0710] User Registration and Login

[0711] Users can create an account through a terminal and enter the necessary information, and existing users can access the system by logging in.

[0712] Enter a summary of the problem

[0713] Users enter detailed information about the problem through a terminal. The form includes items such as the type of problem, the date and time it occurred, the people involved, and specific details of the incident.

[0714] Receiving solutions and feedback

[0715] The user receives and views the solutions provided by the server through the terminal, and also inputs feedback on the results of using the proposed solutions and legal support.

[0716] Specific examples

[0717] Example 1: Labor-related issues

[0718] The user wishes to seek advice regarding unfair dismissal under a labor contract. Using the terminal, the user enters the following information:

[0719] Type of problem: Labor issues

[0720] Date of occurrence: August 15, 2023

[0721] Parties involved: Employee (user), Employer (company)

[0722] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[0723] Then the following solutions are provided:

[0724] Checklist for legality of dismissal under the Labor Standards Act

[0725] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[0726] Introduction to law firms that specialize in labor issues

[0727] Example 2: Consultation regarding contract disputes

[0728] The user is consulting about a problem with renewing a rental contract. They enter the following information through the terminal:

[0729] Type of problem: Contract problem

[0730] Date of occurrence: September 10, 2023

[0731] Parties involved: Tenant (user), landlord (landlord)

[0732] Detailed background: The landlord added unfair conditions when renewing the contract.

[0733] Then the following solutions are provided:

[0734] Procedures for verifying the legality of renewal conditions in lease agreements

[0735] Local government rental housing trouble consultation desk

[0736] Introducing a law firm that specializes in real estate issues

[0737] This allows users to obtain solutions to legal problems quickly and appropriately.

[0738] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0739] Step 1:

[0740] User Registration and Login

[0741] Users access the system using a terminal and create an account. The data entered includes personal information such as name, email address, and password. Existing users log in using their email address and password.

[0742] Input data: Name, email address, password

[0743] Output data: User account information

[0744] Specific behavior:

[0745] User reaches registration / login screen.

[0746] The user enters the required information and clicks the submit button.

[0747] The server receives the input data and stores it in a database or performs authentication.

[0748] Step 2:

[0749] Entering trouble summary data

[0750] After registering or logging in to the system, users enter summary data about the problem. The input form includes items such as the type of problem, the date and time it occurred, the people involved, and specific details of the problem.

[0751] Input data: Type of trouble, date and time of occurrence, people involved, specific details

[0752] Output data: Trouble summary data

[0753] Specific behavior:

[0754] The user accesses the trouble summary input screen.

[0755] The user enters the information corresponding to each item and clicks the submit button.

[0756] The server receives the input data and stores it in a database.

[0757] Step 3:

[0758] Data collection and storage

[0759] The server periodically collects data from law firms and courts using web scraping and APIs, and stores it in a database using Python's Beautiful Soup and Scrapy.

[0760] Input data: Legal data obtained from websites and APIs

[0761] Output data: Legal data stored in a database

[0762] Specific behavior:

[0763] The server initiates web scraping or API calls on a schedule.

[0764] Beautiful Soup or Scrapy retrieves data from a specific website.

[0765] The acquired data is analyzed and stored in a database.

[0766] Step 4:

[0767] Analysis of trouble summary data

[0768] The server analyzes the received trouble summary data using natural language processing technology. Specifically, it performs morphological analysis with MeCab, topic modeling with Gensim, and searches for similar cases with ElasticSearch.

[0769] Input data: Trouble summary data received from the user

[0770] Output data: Morphological analysis results, topic models, search results for similar cases

[0771] Specific behavior:

[0772] The server passes the trouble summary data received from the user to the NLP processing pipeline.

[0773] Morphological analysis is performed using MeCab to decompose the data into grammatical parts.

[0774] Use topic modeling with Gensim to extract themes from the data.

[0775] Search for similar cases using ElasticSearch and evaluate their similarity.

[0776] Step 5:

[0777] Solution Generation

[0778] Based on the analysis results, the server generates an optimal solution, which includes legal advice and appropriate procedural instructions, and, if necessary, provides information on relevant law firms and consultation centers.

[0779] Input data: Analysis results (morphological analysis results, topic model, search results for similar cases)

[0780] Output data: Resolution and corresponding legal authority information

[0781] Specific behavior:

[0782] The server provides data to the solution generation algorithm based on the results of the NLP analysis.

[0783] The algorithm references a database of laws and regulations and past cases to construct an appropriate solution.

[0784] If necessary, include information on relevant law firms and counseling services.

[0785] Step 6:

[0786] Providing solutions

[0787] The user receives the generated solution through the terminal, where the solution is displayed and can be viewed by the user.

[0788] Input data: generated solutions and corresponding legal authority information

[0789] Output: The solution displayed on the user's device

[0790] Specific behavior:

[0791] The server sends the generated solution to the user's device.

[0792] The user receives a notification and is taken to a screen that displays the solution.

[0793] Browse the solutions provided by users.

[0794] Step 7:

[0795] Gathering feedback and optimizing the system

[0796] Users input feedback on the results of using the proposed solutions and legal support. The server receives this feedback data and stores it in a database. The collected feedback data is used to improve the accuracy of the system's analytical model and database.

[0797] Input data: Feedback data from users

[0798] Output data: Feedback data stored in database, updated analytical model and database

[0799] Specific behavior:

[0800] The user accesses the feedback input screen.

[0801] Users provide input on the usefulness of the solution and actual results.

[0802] The server receives the feedback data and stores it in a database.

[0803] The server analyzes the collected feedback and uses it to improve the accuracy of the model and update the database.

[0804] (Application example 1)

[0805] 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."

[0806] In modern society, legal issues are diverse, and problems faced by individuals in particular require prompt and appropriate resolution. However, because specialized knowledge and experience are required, it is difficult for individuals to find the optimal solution on their own. Another major issue is the lack of a way to quickly consult with a legal expert without being tied to a physical location. Furthermore, there is a lack of a mechanism for reflecting the effectiveness of the solution obtained as feedback into the system. In this situation, an efficient system is needed that allows users to easily resolve legal issues and receive expert support.

[0807] 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.

[0808] In this invention, the server includes means for collecting legal-related data and storing it in a database, means for receiving summary data of the problem entered by the user, means for analyzing the received summary data using natural language processing and generating an appropriate solution, means for providing the generated solution and information on the corresponding legal agency to the user, means for receiving user feedback and optimizing the system, and means for enabling communication with legal experts in a virtual environment using a smart device. This allows users to obtain quick and appropriate solutions to legal problems through their smart devices and also allows for real-time consultation with experts, thereby enabling efficient and effective resolution of legal problems.

[0809] "Legal data" refers to information such as laws, precedents, legal advice, and consultation cases collected from law firms, courts, the Ministry of Justice, etc.

[0810] A "database" is a collection of information that organizes and stores legal-related data so that it can be searched and used efficiently.

[0811] "Trouble summary data" refers to specific information about the case, such as the type of trouble entered by the user, the date and time of occurrence, the people involved, and detailed background information.

[0812] "Natural language processing" is a technology for analyzing summary data of a problem entered by a user and generating appropriate solutions, and includes morphological analysis, topic modeling, and similar case search.

[0813] "Solutions" refers to proposals generated by natural language processing that include legal advice, appropriate procedural steps, and information on relevant legal authorities.

[0814] "Legal institutions" refers to organizations that provide legal support, such as law firms, courts, labor bureaus, labor standards inspection offices, and municipal consultation centers.

[0815] "Feedback" refers to a user's evaluation or opinion of the results of using the provided solutions or legal support.

[0816] "Smart devices" refers to electronic devices with advanced functions such as smartphones, smart glasses, and head-mounted displays.

[0817] "Virtual environment" refers to a virtual space or online platform that users can access using smart devices.

[0818] "Communication" refers to the means by which legal professionals and users exchange information in real time through a virtual environment.

[0819] System Overview

[0820] The present invention is a comprehensive system for providing appropriate solutions to legal problems quickly and efficiently. This system mainly operates in cooperation with a server, terminals, and users.

[0821] Server-side behavior

[0822] The server collects reliable data from legal institutions and stores it in a database. It also receives summary data of the problem entered by the user on their device and analyzes it using natural language processing technology. Based on the analysis results, it generates appropriate solutions and provides them to the user. It also collects feedback from users and reflects it in improving the system.

[0823] Data collection and storage

[0824] The server periodically collects the latest information from legal agencies through web scraping, APIs, and manual entry, and the collected data is organized and stored in a database.

[0825] Analysis of trouble summary data

[0826] The server analyzes the trouble summary data received from the user using natural language processing (NLP) techniques, such as morphological analysis, topic modeling, and similar case search.

[0827] Solution generation and delivery

[0828] Based on the analysis results, the server generates an optimal solution, including legal advice and appropriate procedural instructions. It also provides information on relevant legal authorities, if necessary. It also allows users to communicate with legal experts in a virtual environment using their smart devices.

[0829] Feedback collection and optimization

[0830] The server receives feedback from users after they have used the solutions and legal support provided, which is stored in a database and used to improve the accuracy of the system's analytical models and database.

[0831] Operation on the terminal side

[0832] The terminal provides an interface for users to access the system. Users use the terminal to create an account, enter a problem description, and receive a solution from the system. This can be a web browser or a mobile application. Users can also use smart devices to communicate with legal experts in a virtual environment in real time.

[0833] User Registration and Login

[0834] Users create an account through a terminal and enter the necessary information. Existing users can access the system by logging in.

[0835] Enter a summary of the problem

[0836] The user enters detailed information about the problem through a terminal. The form includes items such as the type of problem, the date and time of the problem, the people involved, and specific details of the problem.

[0837] Receiving solutions and feedback

[0838] The user receives and views the solutions provided by the server through the terminal, and also inputs feedback on the results of using the proposed solutions and legal support.

[0839] Specific examples

[0840] Example 1: Labor-related issues

[0841] The user wishes to seek advice regarding unfair dismissal under a labor contract. Using the terminal, the user enters the following information:

[0842] Type of problem: Labor issues

[0843] Date of occurrence: August 15, 2023

[0844] Parties involved: Employee (user), Employer (company)

[0845] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[0846] The server receives this information, analyzes it, and makes the following suggestions:

[0847] Checklist for legality of dismissal under the Labor Standards Act

[0848] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[0849] Introduction to law firms that specialize in labor issues

[0850] The user acts on the presented solution and reports the results to the system as feedback.

[0851] Example 2: Consultation regarding contract disputes

[0852] The user wishes to consult about a problem regarding the renewal of a rental contract. The user enters the following information through the terminal:

[0853] Type of problem: Contract problem

[0854] Date of occurrence: September 10, 2023

[0855] Parties involved: Tenant (user), landlord (landlord)

[0856] Detailed background: The landlord added unfair conditions when renewing the contract.

[0857] The server receives this information, analyzes it, and makes the following suggestions:

[0858] Procedures for verifying the legality of renewal conditions in lease agreements

[0859] Local government rental housing trouble consultation desk

[0860] Introducing a law firm that specializes in real estate issues

[0861] The user takes specific action based on the presented solution and reports the results to the system as feedback.

[0862] Example prompts for generative AI models

[0863] "Unfair terms were presented during the contract renewal. Type of problem: Contract dispute, Date of occurrence: September 10, 2023, Parties involved: Tenant and Landlord."

[0864] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0865] Step 1:

[0866] The user creates an account using a terminal and enters the necessary information. The input for this step is the user's personal information and login information. The output is that the user account has been created and is ready to log in.

[0867] Step 2:

[0868] The user inputs detailed information about the problem through the terminal. Specifically, the type of problem, the date and time of occurrence, the people involved, and the specific details. The input of this step is detailed information about the problem, and the output is that this information is sent to the server.

[0869] Step 3:

[0870] The server analyzes the received problem summary data using natural language processing (NLP) technology. The input for this step is the problem summary data sent by the user, and the output is a set of analyzed topics and keywords. Specific operations include morphological analysis, topic modeling, and similar case search.

[0871] Step 4:

[0872] The server generates optimal solutions based on the analysis results. It searches the database for appropriate laws and cases based on the analyzed topics and keywords, and generates legal advice and appropriate procedural methods. The input for this step is the analysis results and related information in the database, and the output is the generated solution.

[0873] Step 5:

[0874] The generated solution and corresponding legal authority information are provided to the user. The server sends the generated solution to the terminal, where the user can view it. The input of this step is the generated solution, and the output is a display of the solution that can be viewed by the user.

[0875] Step 6:

[0876] The server enables real-time communication with a legal expert in a virtual environment using a smart device. The user then uses the smart device to video chat with the legal expert for further consultation. The input of this step is the user's communication request, and the output is the initiation of a real-time video chat session with the legal expert.

[0877] Step 7:

[0878] The user inputs the results of using the provided solutions and legal support as feedback. The feedback is sent to the server and stored in the database. The input of this step is the user's feedback, and the output is the accumulation of feedback in the database.

[0879] Step 8:

[0880] The server uses the collected feedback to refine the system's analytical model and database. The input for this step is the feedback data, and the output is an improved analytical model and a refined database. Specific operations include retraining the model using machine learning algorithms.

[0881] 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.

[0882] System Overview

[0883] This invention is a comprehensive system for quickly and efficiently providing appropriate solutions to legal disputes, and in particular, it incorporates an emotion engine that recognizes the user's emotional state and reflects it in the solution. This system mainly operates in cooperation with a server, terminals, and users.

[0884] Server-side behavior

[0885] The server collects reliable data from law firms and courts and stores it in a database. It also receives summary data of the problem entered by the user and analyzes it using natural language processing and an emotion engine. Based on the analysis results, it generates an appropriate solution and provides it to the user. It also collects feedback from users and reflects it in improving the system.

[0886] Data collection and storage

[0887] The server periodically collects the latest information from law firms and courts through web scraping, APIs, and manual entry, and the collected data is organized and stored in a database.

[0888] Analysis of trouble summary data

[0889] The server analyzes the trouble summary data received from the user using natural language processing (NLP) technology and an emotion engine. It uses an NLP model (e.g., BERT or GPT) to classify the input data, extract important keywords, and understand the details of the trouble. At the same time, it uses the emotion engine to analyze the user's emotional state from the input.

[0890] Solution generation and delivery

[0891] Based on the analysis results, the server generates an optimal solution, including legal advice and appropriate procedural instructions. The solution presentation is tailored to the user's emotional state. If necessary, information on relevant law firms or local government consultation services is also provided.

[0892] Feedback collection and optimization

[0893] The server receives feedback from users after they use the solutions and consultation services provided. This feedback is stored in a database and used to improve the accuracy of the system's analytical model and emotion engine, allowing the system to be continuously optimized.

[0894] Operation on the terminal side

[0895] The terminal provides the interface through which users access the system. The terminal is used by users to create an account, enter a problem description, and receive a solution from the system. This can be a web browser or a mobile application.

[0896] User Registration and Login

[0897] Users create an account through a terminal and enter the necessary information. Existing users can access the system by logging in.

[0898] Enter a summary of the problem

[0899] The user uses a terminal to enter detailed information about the problem. The form includes items such as the type of problem, the date and time of the problem, the people involved, and specific details. The data entered by the user is sent to the server.

[0900] Receiving solutions and feedback

[0901] The user can view the solutions provided by the server through their device and take action if necessary. They can contact the suggested law firms or counseling centers. They can also input feedback on the solutions provided and the results of using legal support.

[0902] Specific examples

[0903] Example 1: Labor-related issues

[0904] The user wishes to seek advice regarding unfair dismissal under a labor contract. Using the terminal, the user enters the following information:

[0905] Type of problem: Labor issues

[0906] Date of occurrence: August 15, 2023

[0907] Parties involved: Employee (user), Employer (company)

[0908] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[0909] As you type, the emotion engine recognizes your emotions, such as anger or anxiety.

[0910] The server receives this information, analyzes it, and makes the following suggestions:

[0911] Checklist for legality of dismissal under the Labor Standards Act

[0912] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[0913] Introduction to law firms that specialize in labor issues

[0914] In response to any concerns users may have, the message is presented in a reassuring manner, such as "verifying legality should be given priority."

[0915] The user acts on the presented solution and reports the results to the system as feedback.

[0916] Example 2: Consultation regarding contract disputes

[0917] The user wishes to consult about a problem regarding the renewal of a rental contract. The user enters the following information through the terminal:

[0918] Type of problem: Contract problem

[0919] Date of occurrence: September 10, 2023

[0920] Parties involved: Tenant (user), landlord (landlord)

[0921] Detailed background: The landlord added unfair conditions when renewing the contract.

[0922] Upon input, the emotion engine recognizes the user's confused emotion.

[0923] The server receives this information, analyzes it, and makes the following suggestions:

[0924] Procedures for verifying the legality of renewal conditions in lease agreements

[0925] Local government rental housing trouble consultation desk

[0926] Introducing a law firm that specializes in real estate issues

[0927] To reduce user confusion, encouraging statements such as "Follow the detailed verification steps and the problem will be resolved" are presented.

[0928] The user takes specific action based on the presented solution and reports the results to the system as feedback.

[0929] In this way, by combining emotion engines, it becomes possible to provide solutions that take into account the user's emotional state, thereby providing effective support for legal disputes.

[0930] The processing flow will be explained below.

[0931] Step 1:

[0932] The server collects reliable data from law firms and courts. It uses web scraping and APIs to obtain the latest laws, precedents, contracts, etc., and stores them in a database. Additionally, it uses OCR technology to digitize manually collected materials as needed and registers them in the database.

[0933] Step 2:

[0934] Users access the system using a terminal and create an account or log in. New users create an account by entering personal information such as their name, email address, and password. Existing users log in by entering their email address and password.

[0935] Step 3:

[0936] The user uses the terminal to enter an outline of the problem. The input form includes items such as the type of problem, the date and time of occurrence, the people involved, and specific details. The user enters this information in detail and presses the send button.

[0937] Step 4:

[0938] The server receives the summary data of the problem sent by the user and stores it in a temporary database. At this point, a simple error check is performed to ensure that there are no problems with the format or content of the input data.

[0939] Step 5:

[0940] The server analyzes the received summary data of the trouble using natural language processing (NLP) technology and an emotion engine. It uses an NLP model (e.g., BERT or GPT) to classify the input data, extract important keywords, and understand the content of the trouble. At the same time, it uses the emotion engine to analyze the emotional state from the user's input.

[0941] Step 6:

[0942] The server uses the analysis results to search for similar cases and related laws and regulations in its database. Based on the search results, it generates the optimal solution and determines its content. The solution includes legal advice and appropriate procedural methods.

[0943] Step 7:

[0944] The server adjusts the content of the solution presented to the user depending on the user's emotional state. For example, if the user is feeling strong emotions such as anxiety or anger, the server changes the presented solution to be more reassuring.

[0945] Step 8:

[0946] The server provides the generated solution to the user, and also lists and displays to the user information on law firms and details of local government consultation centers related to the solution.

[0947] Step 9:

[0948] The user can view the solutions provided by the server through their device and take action if necessary, including contacting the suggested law firm or counseling center.

[0949] Step 10:

[0950] Users enter their feedback on the solutions provided and the results of using the support service in a feedback form, including their evaluation of the effectiveness of the solutions and the quality of the support.

[0951] Step 11:

[0952] The server receives feedback from users and stores it in a database. The collected feedback is used to improve the accuracy of the system's analytical model and emotion engine, allowing the system to be continuously optimized.

[0953] Specific examples

[0954] Example 1: Labor-related issues

[0955] The user wishes to seek advice regarding unfair dismissal under a labor contract. Using the terminal, the user enters the following information:

[0956] Type of problem: Labor issues

[0957] Date of occurrence: August 15, 2023

[0958] Parties involved: Employee (user), Employer (company)

[0959] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[0960] As you type, the emotion engine recognizes your emotions, such as anger or anxiety.

[0961] The server receives this information, analyzes it, and makes the following suggestions:

[0962] Checklist for legality of dismissal under the Labor Standards Act

[0963] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[0964] Introduction to law firms that specialize in labor issues

[0965] In response to any concerns users may have, the message is presented in a reassuring manner, such as "verifying legality should be given priority."

[0966] The user acts on the presented solution and reports the results to the system as feedback.

[0967] Example 2: Consultation regarding contract disputes

[0968] The user wishes to consult about a problem regarding the renewal of a rental contract. The user enters the following information through the terminal:

[0969] Type of problem: Contract problem

[0970] Date of occurrence: September 10, 2023

[0971] Parties involved: Tenant (user), landlord (landlord)

[0972] Detailed background: The landlord added unfair conditions when renewing the contract.

[0973] Upon input, the emotion engine recognizes the user's confused emotion.

[0974] The server receives this information, analyzes it, and makes the following suggestions:

[0975] Procedures for verifying the legality of renewal conditions in lease agreements

[0976] Local government rental housing trouble consultation desk

[0977] Introducing a law firm that specializes in real estate issues

[0978] To reduce user confusion, encouraging statements such as "Follow the detailed verification steps and the problem will be resolved" are presented.

[0979] The user takes specific action based on the presented solution and reports the results to the system as feedback.

[0980] In this way, by combining emotion engines, it becomes possible to provide solutions that take into account the user's emotional state, thereby providing effective support for legal disputes.

[0981] Example 2

[0982] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0983] Conventional legal systems only provide solutions to legal disputes without taking into account the user's emotional state. This can lead to problems such as users finding it difficult to understand the solutions or lacking motivation to take appropriate action. Furthermore, they lack the ability to collect feedback and optimize the system to improve the effectiveness of the solutions provided.

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

[0985] In this invention, the server includes means for collecting legal-related data and storing it in a database, means for receiving summary data of the problem entered by the user, means for analyzing the received summary data using natural language processing and generating an appropriate solution, means for adjusting the way the solution is presented using an emotion engine that analyzes the user's emotional state, means for providing the user with the generated solution and information on the corresponding legal agency, and means for receiving user feedback and optimizing the system. This makes it possible to provide solutions that take the user's emotional state into consideration, thereby realizing more effective support for legal troubles.

[0986] "Legal data" refers to information such as laws, precedents, cases, and legal consultation results collected from law firms and courts.

[0987] A "database" is an information system that organizes and stores collected legal-related data, allowing it to be efficiently searched and accessed when needed.

[0988] "User" means an individual or organization that uses the system to seek legal advice.

[0989] "Summary data of the trouble" is detailed information entered by the user, such as the type of trouble, the date and time of occurrence, the people involved, and the specific details of the trouble.

[0990] "Natural language processing" is a technology that analyzes and processes text data entered by the user to understand and generate human language.

[0991] "Solutions" are specific advice or suggestions generated to solve a problem based on trouble data analyzed using natural language processing.

[0992] An "emotion engine" is a technology that analyzes a user's emotional state and adjusts the way solutions are presented to take those emotions into consideration.

[0993] "Feedback" refers to the user's opinions and evaluations of the solutions provided or the results of using the consultation service.

[0994] "System optimization" is the process of continuously improving the overall performance and accuracy of the system based on collected feedback.

[0995] "Legal institutions" are organizations that provide legal support, such as law firms, courts, and local government helplines.

[0996] A "natural language processing model" is a machine learning model, such as BERT or GPT, that is used to understand and analyze user input text and generate appropriate solutions.

[0997] "Solution presentation method" is a means of adjusting the content and presentation of the solution depending on the user's emotional state.

[0998] "Information provision" is the process of communicating generated solutions and relevant legal information to users.

[0999] MODE FOR CARRYING OUT THE INVENTION

[1000] System Overview

[1001] This invention is a system for quickly and efficiently providing appropriate solutions to legal problems, and in particular, it combines an emotion engine that recognizes the user's emotional state and reflects it in the solution. This system mainly operates in cooperation with a server, terminals, and users.

[1002] System configuration

[1003] The server collects reliable data from law firms and courts and stores it in a database. It also receives summary data of the problem entered by the user and analyzes it using natural language processing and an emotion engine. Based on the analysis results, it generates an appropriate solution and provides it to the user. It also collects feedback from users and reflects it in improving the system. Specifically, the following hardware and software are used:

[1004] Hardware: Servers, client devices (PCs, smartphones, tablets)

[1005] Software: Natural language processing models (BERT, GPT), sentiment engine, database management system, web server

[1006] Server-side behavior

[1007] 1. Data collection and storage:

[1008] The server periodically collects the latest legal information using web scraping, APIs, and manual input.

[1009] The collected data is organized and stored in a database.

[1010] 2. Analysis of Trouble Summary Data:

[1011] The server analyzes the summary data of the problem received from the user using natural language processing (NLP) techniques such as BERT and GPT.

[1012] Through analysis, the input data is classified, important keywords are extracted, and the nature of the problem is understood.

[1013] At the same time, an emotion engine is used to analyze the emotional state from the user's input.

[1014] 3. Solution generation and delivery:

[1015] Based on the analysis, the server generates an optimal solution, which may include legal advice and proper procedural instructions.

[1016] The system adjusts the way solutions are presented depending on the user's emotional state, and also provides information on relevant law firms and local government consultation services.

[1017] 4. Feedback collection and optimization:

[1018] The server receives feedback from the user after the user has used the provided solutions and helplines.

[1019] The feedback is stored in a database and used to improve the accuracy of the system's analytical models and emotion engine.

[1020] Operation on the terminal side

[1021] 1. User Registration and Login:

[1022] Users create an account through a terminal and enter the necessary information. Existing users can access the system by logging in.

[1023] 2. Enter a summary of the problem:

[1024] The user uses a terminal to input detailed information about the problem. The input format includes text boxes where the user can enter the type of problem, the date and time of occurrence, the people involved, and detailed information about the problem.

[1025] The user's input data is sent to the server.

[1026] 3. Receiving solutions and feedback:

[1027] The user can view the solutions provided by the server through the terminal and take action as necessary.

[1028] Provide feedback on the solutions provided and the results of using legal support.

[1029] Specific examples

[1030] Example 1: Labor-related issues

[1031] When a user wishes to consult about unfair dismissal under a labor contract, the user inputs the following information using a terminal.

[1032] Type of problem: Labor issues

[1033] Date of occurrence: August 15, 2023

[1034] Parties involved: Employee (user), Employer (company)

[1035] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[1036] As you type, the emotion engine recognizes your emotions, such as anger or anxiety.

[1037] The server receives this information, analyzes it, and makes the following suggestions:

[1038] Checklist for legality of dismissal under the Labor Standards Act

[1039] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[1040] Introduction to law firms that specialize in labor issues

[1041] The solution is presented in a way that gives the user a sense of security, such as "Confirming legality should be prioritized," in response to any concerns the user may have. The user then takes action based on the presented solution and reports the results to the system as feedback.

[1042] Example 2: Consultation regarding contract disputes

[1043] When consulting about a problem with renewing a rental contract, the user enters the following information:

[1044] Type of problem: Contract problem

[1045] Date of occurrence: September 10, 2023

[1046] Parties involved: Tenant (user), landlord (landlord)

[1047] Detailed background: The landlord added unfair conditions when renewing the contract.

[1048] Upon input, the emotion engine recognizes the user's confused emotion.

[1049] The server receives this information, analyzes it, and makes the following suggestions:

[1050] Procedures for verifying the legality of renewal conditions in lease agreements

[1051] Local government rental housing trouble consultation desk

[1052] Introducing a law firm that specializes in real estate issues

[1053] To alleviate user confusion, encouraging messages such as, "Follow the detailed confirmation steps and your problem will be solved." In this way, by combining the emotion engine, it is possible to provide solutions that take into account the user's emotional state, thereby achieving effective support for legal disputes.

[1054] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1055] Step 1: User registration and login

[1056] Users create an account using a device. They register by entering their username, email address, password, etc. Existing users can log in by entering their account information.

[1057] The device sends the entered information to the server, which receives it, stores it in a database, verifies the login information, and redirects the user to the dashboard if authentication is successful.

[1058] Input: User information (user name, email address, password)

[1059] Output: Authentication results, dashboard access

[1060] Step 2: Enter a description of the problem

[1061] The user uses the terminal to input detailed information about the problem, such as the type of problem, the date and time of occurrence, the people involved, and a detailed history of the problem, into an input form.

[1062] The terminal sends the entered data to the server, which stores the received data in a database. Once the data is stored, the analysis process is initiated.

[1063] Input: Detailed information about the problem (type, date and time of occurrence, people involved, detailed history)

[1064] Output: Saving data and launching analysis processes

[1065] Step 3: Analyze the trouble summary data

[1066] The server analyzes the received summary data of the trouble using natural language processing models such as BERT and GPT.

[1067] For analysis, the data is pre-processed (tokenized and normalized) and then input into the model. The NLP model analyzes the text data, extracts important keywords and phrases, and classifies the content of the problem.

[1068] Input: Summary of the problem

[1069] Output: Analysis results (keywords, classification results)

[1070] Step 4: Analyze emotional state

[1071] Based on the results of the natural language processing analysis, the server uses an emotion engine to analyze the user's emotional state.

[1072] The text data is input into an emotion model to identify the user's emotion (e.g., anger, anxiety, confusion), and the emotion model returns the result.

[1073] Input: Analysis results (keywords, classification results)

[1074] Output: Emotion analysis results (anger, anxiety, confusion, etc.)

[1075] Step 5: Generate a solution

[1076] The server generates an appropriate solution based on the content of the problem and the user's emotional state, and refers to a legal database to collect relevant information.

[1077] Solutions include legal advice and specific procedural steps, and are tailored to the user's emotional state.

[1078] Input: Sentiment analysis results, legal data

[1079] Output: Generated solution

[1080] Step 6: Propose a solution

[1081] The server sends the generated solution to the terminal.

[1082] The device displays a solution to the user. The solution is presented in a way that takes into consideration the user's emotions. For example, if the user is feeling anxious, the device uses reassuring language such as "First, confirming legality is a priority."

[1083] Input: Generated solution

[1084] Output: The solution that is displayed to the user

[1085] Step 7: Receiving feedback

[1086] The user acts on the provided solutions and provides feedback on the results.

[1087] The device receives the feedback and sends it to a server, which stores it in a database and uses it for analysis.

[1088] Input: User feedback

[1089] Output: feedback storage and system optimization

[1090] This series of steps not only provides users with a fast and appropriate solution, but also takes into account the user's emotional state. The system is continuously improved using collected feedback.

[1091] (Application example 2)

[1092] 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."

[1093] In modern society, the number of opportunities to face legal troubles and security issues is increasing, and resolving these issues requires providing prompt and accurate information. Furthermore, if individual responses are not given taking into account the user's emotional state, users' stress and anxiety will increase, which will become a barrier to problem resolution. Therefore, a system that provides legal and security advice combined with emotion recognition is needed.

[1094] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting legal-related data and storing it in a database, means for receiving summary data of the problem entered by the user, means for analyzing the received summary data using natural language processing and emotion recognition to generate an appropriate solution, means for providing the generated solution and information on corresponding related organizations to the user, and means for receiving user feedback and optimizing the system. This makes it possible to provide quick and emotion-sensitive solutions to legal and security issues.

[1095] "Legal data" is a general term for information about laws, precedents, legal advice, and procedures collected from law firms, courts, government agencies, etc.

[1096] A "database" is an information management system that systematically stores collected legal data, user input data, feedback information, etc., and uses them for search and analysis.

[1097] "Summary data of the trouble entered by the user" refers to detailed information provided by the user to the system, such as the type of trouble, the date and time of occurrence, the people involved, and the specific details of the trouble.

[1098] "Natural language processing" is a technology that analyzes summary data of problems and other text data to extract and classify important keywords, and is a method for computers to understand and process human language.

[1099] "Emotion recognition" is a technology that analyzes and recognizes a user's emotional state (e.g., anger, anxiety, confusion, etc.) from text and other data entered by the user.

[1100] "Appropriate solutions" are those that provide legally accurate and feasible advice and procedures for the problems users are facing, based on collected legal data and analysis results.

[1101] "Related institutions" is a general term for specialized institutions or organizations related to resolving user disputes, such as law firms, courts, and consultation centers.

[1102] "Feedback" means any evaluation or comment you make about the results or experience you have had implementing or using a solution or service provided.

[1103] "Optimization" is the process of improving models and algorithms based on feedback received from users in order to improve the overall performance and accuracy of the system.

[1104] System Overview

[1105] This invention is a system for providing quick and effective solutions to legal and security disputes. In particular, it incorporates an emotion recognition engine that recognizes the user's emotional state and reflects it in the solution. This system mainly operates in cooperation with a server, terminals, and users.

[1106] Server-side behavior

[1107] The server collects legal data and stores it in a database. Specifically, the server periodically collects data automatically from authorized data sources (e.g., law firms, courts, and government agencies). This data collection is done using web scraping, APIs, and manual entry. The collected data is then organized and stored in a database.

[1108] After receiving the user's summary of the problem, the server analyzes it using natural language processing (NLP) technology and an emotion recognition engine. NLP models used, such as BERT and GPT, classify the input data, extract important keywords, and understand the nature of the problem. At the same time, the emotion recognition engine analyzes the user's emotional state from the input.

[1109] Based on the analysis results, the server generates an optimal solution, including legal advice and appropriate procedural instructions. The solution presentation is tailored to the user's emotional state. It also provides information on relevant law firms and local government consultation services.

[1110] After users use the solutions and consultation services provided, the server receives feedback, which is stored in a database and used to improve the accuracy of the system's analytical models and emotion recognition engine, allowing the system to be continuously optimized.

[1111] Operation on the terminal side

[1112] The terminal provides an interface for users to access the system. Users can use the terminal to create an account, enter a summary of the problem, and receive a solution from the system. Specifically, this role is played by a web browser or a mobile application.

[1113] Users create an account through their device and enter the necessary information. Existing users can access the system by logging in. When entering detailed information about a problem using the device, the emotion recognition engine analyzes the user's emotions in real time and sends the analysis results to the server.

[1114] After receiving the solution provided by the server, the user can view the solution through the terminal and take action if necessary. The user can also contact the suggested law firm or consultation center through the terminal. In addition, the user can enter feedback on the results of using the provided solution.

[1115] Specific examples

[1116] Example 1: Labor-related issues

[1117] When a user wishes to consult about unfair dismissal under a labor contract, the user enters the following information using the terminal.

[1118] Type of problem: Labor issues

[1119] Date of occurrence: August 15, 2023

[1120] Parties involved: Employee (user), Employer (company)

[1121] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[1122] When inputting, the emotion recognition engine recognizes the user's emotions such as anger or anxiety. The server receives this information and analyzes it. As a result, it makes the following suggestions:

[1123] Checklist for legality of dismissal under the Labor Standards Act

[1124] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[1125] Introduction to law firms that specialize in labor issues

[1126] In response to users' concerns, solutions are presented in a reassuring manner, such as "verifying legality should be given priority."

[1127] Example 2: Consultation regarding contract disputes

[1128] When a user wishes to consult about a problem with renewing a rental contract, the user enters the following information through the terminal.

[1129] Type of problem: Contract problem

[1130] Date of occurrence: September 10, 2023

[1131] Parties involved: Tenant (user), landlord (landlord)

[1132] Detailed background: The landlord added unfair conditions when renewing the contract.

[1133] When inputting, the emotion recognition engine will recognize the user's confused emotion. The server will receive this information and analyze it. As a result, it will make the following suggestions:

[1134] Procedures for verifying the legality of renewal conditions in lease agreements

[1135] Local government rental housing trouble consultation desk

[1136] Introducing a law firm that specializes in real estate issues

[1137] To reduce user confusion, solutions are presented in encouraging language such as, "Follow our detailed verification steps and your problem will be resolved."

[1138] Prompt Sentence Examples

[1139] For example, a generative AI model operates using prompt statements such as the following:

[1140] Type of problem: Contract problem

[1141] Problem description: Last night I received an email that I suspected was a phishing scam.

[1142] Emotional state: Anxiety

[1143] Legal advice: Check if the link is from a trusted site, avoid opening suspicious emails, and contact the police or security agencies.

[1144] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1145] Step 1:

[1146] A user accesses a device and creates or logs in to an account. The input data is the user's authentication information (username, password, etc.). The device receives this and sends it to the server. The server performs authentication and, if successful, returns the user's profile information to the device.

[1147] Step 2:

[1148] The user uses a terminal to input summary data about the problem. The input data includes the type of problem, the date and time of occurrence, the people involved, and a detailed history. The terminal receives this data and sends it to the server.

[1149] Step 3:

[1150] The server analyzes the received summary data of the trouble using natural language processing (NLP). It uses an NLP model (e.g., BERT, GPT, etc.) to classify the input data and extract keywords. The input data is the trouble text, and the output data is the analyzed keyword list and classification results.

[1151] Step 4:

[1152] The server simultaneously uses an emotion recognition engine to analyze the user's emotional state. The input data is the summary of the problem, and the output data is the user's emotional state (e.g., anger, anxiety, confusion, etc.). The analysis results are combined with the results of natural language processing.

[1153] Step 5:

[1154] The server generates appropriate solutions based on the analysis results. The solution generation utilizes collected legal data and information from related agencies. The input data is the NLP and emotion recognition results, and the output data is the solution and information from related agencies.

[1155] Step 6:

[1156] The server sends the generated solution and related organization information to the terminal. The user uses the terminal to view the solution. The output data is the solution and related organization information.

[1157] Step 7:

[1158] The user takes action based on the provided solution and inputs the results as feedback into the device. The input data is the feedback content (e.g., satisfaction level, additional comments). The device receives this and sends it to the server.

[1159] Step 8:

[1160] The server receives the feedback and stores it in a database. The input data is the user's feedback. The server optimizes the analysis model and emotion recognition engine for future solution generation. This improves the accuracy and usefulness of the system.

[1161] 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.

[1162] 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.

[1163] 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.

[1164] [Third embodiment]

[1165] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1166] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1167] 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).

[1168] 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.

[1169] 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.

[1170] 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).

[1171] 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.

[1172] 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.

[1173] 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.

[1174] 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.

[1175] 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.

[1176] 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."

[1177] System Overview

[1178] The present invention is a comprehensive system for providing appropriate solutions to legal problems quickly and efficiently. This system mainly operates in cooperation with a server, terminals, and users.

[1179] Server-side behavior

[1180] The server collects reliable data from law firms, courts, and other sources and stores it in a database. It also receives summary data about the problem entered by the user on their device and analyzes it using natural language processing technology. Based on the analysis results, it generates appropriate solutions and provides them to the user. It also collects feedback from users and reflects it in improving the system.

[1181] Data collection and storage

[1182] The server periodically collects the latest information from law firms and courts through web scraping, APIs, and manual entry, and the collected data is organized and stored in a database.

[1183] Analysis of trouble summary data

[1184] The server analyzes the trouble summary data received from the user using natural language processing (NLP) techniques, such as morphological analysis, topic modeling, and similar case search.

[1185] Solution generation and delivery

[1186] Based on the analysis results, the server generates an optimal solution, which includes legal advice and appropriate procedural instructions, and, if necessary, provides information on relevant law firms and local government consultation services.

[1187] Feedback collection and optimization

[1188] The server receives feedback from users after they have used the solutions and consultation services provided, and this feedback is stored in a database and used to improve the accuracy of the system's analytical model and database.

[1189] Operation on the terminal side

[1190] The terminal provides the interface through which users access the system. The terminal is used by users to create an account, enter a problem description, and receive a solution from the system. This can be a web browser or a mobile application.

[1191] User Registration and Login

[1192] Users create an account through a terminal and enter the necessary information. Existing users can access the system by logging in.

[1193] Enter a summary of the problem

[1194] The user enters detailed information about the problem through a terminal. The form includes items such as the type of problem, the date and time of the problem, the people involved, and specific details of the problem.

[1195] Receiving solutions and feedback

[1196] The user receives and views the solutions provided by the server through the terminal, and also inputs feedback on the results of using the proposed solutions and legal support.

[1197] Specific examples

[1198] Example 1: Labor-related issues

[1199] The user wishes to seek advice regarding unfair dismissal under a labor contract. Using the terminal, the user enters the following information:

[1200] Type of problem: Labor issues

[1201] Date of occurrence: August 15, 2023

[1202] Parties involved: Employee (user), Employer (company)

[1203] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[1204] The server receives this information, analyzes it, and makes the following suggestions:

[1205] Checklist for legality of dismissal under the Labor Standards Act

[1206] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[1207] Introduction to law firms that specialize in labor issues

[1208] The user acts on the presented solution and reports the results to the system as feedback.

[1209] Example 2: Consultation regarding contract disputes

[1210] The user wishes to consult about a problem regarding the renewal of a rental contract. The user enters the following information through the terminal:

[1211] Type of problem: Contract problem

[1212] Date of occurrence: September 10, 2023

[1213] Parties involved: Tenant (user), landlord (landlord)

[1214] Detailed background: The landlord added unfair conditions when renewing the contract.

[1215] The server receives this information, analyzes it, and makes the following suggestions:

[1216] Procedures for verifying the legality of renewal conditions in lease agreements

[1217] Local government rental housing trouble consultation desk

[1218] Introducing a law firm that specializes in real estate issues

[1219] The user takes specific action based on the presented solution and reports the results to the system as feedback.

[1220] In this way, the system of the present invention provides comprehensive support for quickly and appropriately responding to legal troubles.

[1221] The processing flow will be explained below.

[1222] Step 1:

[1223] The server collects reliable data from law firms and courts. It uses web scraping and APIs to obtain the latest laws, precedents, contracts, etc., and stores them in a database. Additionally, it uses OCR technology to digitize manually collected materials as needed and registers them in the database.

[1224] Step 2:

[1225] Users access the system using a terminal and create an account or log in. New users create an account by entering personal information such as their name, email address, and password. Existing users enter their email address and password, which are then verified by the server.

[1226] Step 3:

[1227] The user uses the terminal to input an outline of the problem. The input form includes items such as the type of problem, the date and time of occurrence, the people involved, and specific details. The user enters this information in detail.

[1228] Step 4:

[1229] The server receives the summary data of the problem sent by the user and stores it in a temporary database. At this point, a simple error check is performed to ensure that there are no problems with the format or content of the input data.

[1230] Step 5:

[1231] The server analyzes the received summary data of the problem using natural language processing (NLP) technology. It uses an NLP model (e.g., BERT or GPT) to classify the input data, extract important keywords, and understand the content of the problem.

[1232] Step 6:

[1233] The server searches the database for similar cases and related laws and regulations based on the analysis results, and generates the optimal solution based on the search results and determines which solution to provide to the user.

[1234] Step 7:

[1235] The server provides the generated solution to the user, and also lists and displays to the user information on law firms and details of local government consultation centers related to the solution.

[1236] Step 8:

[1237] The user can view the solutions provided by the server through their device and take action if necessary, including contacting the suggested law firm or counseling center.

[1238] Step 9:

[1239] Users enter their feedback on the solutions provided and the results of using the support service in a feedback form, including their evaluation of the effectiveness of the solutions and the quality of the support.

[1240] Step 10:

[1241] The server receives feedback from users and stores it in a database. The collected feedback is used to improve the accuracy of the system's analytical model and database, allowing the system to be continuously optimized.

[1242] Through these steps, this system provides users with efficient solutions to legal problems and creates an environment where they can easily access reliable legal support.

[1243] Example 1

[1244] 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."

[1245] In conventional legal systems, it took time and effort to manually analyze the outline of the problem and provide an appropriate solution. It was also difficult to effectively collect user feedback and reflect it in system optimization. Furthermore, the collection of updated information on related laws and past case data was not automated, which led to delays in system updates and accuracy improvements.

[1246] 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.

[1247] In this invention, the server includes means for collecting legal-related data and storing it in a database, means for receiving summary data of the problem entered by the user, means for analyzing the received summary data using natural language processing and generating an appropriate solution, means for providing the user with the generated solution and information on the corresponding legal agency, means for receiving user feedback and optimizing the system, means for performing morphological analysis, topic modeling, and similar case search using natural language processing technology on the summary data of the problem entered by the user, means for generating a solution including legally compliant advice and appropriate procedural methods based on the analysis results, and means for storing feedback data entered by the user in the database after providing the generated solution and using it to improve the accuracy of the analysis model and the database. This enables fast and efficient problem analysis and solution presentation, and enables effective collection of user feedback and continuous optimization of the system.

[1248] "Legal data" refers to highly reliable information provided by law firms and courts, including laws, court precedents, legal consultation cases, and other information.

[1249] "Trouble summary data" is data that details the legal problem the user has experienced, including the type of trouble, the date and time of occurrence, the people involved, and the specific circumstances.

[1250] The "database" is an information management system for organizing and storing collected legal-related data, trouble summary data from users, and feedback data.

[1251] "Natural language processing" is a technology that allows computers to understand and analyze natural language used by humans, and includes techniques such as morphological analysis, topic modeling, and similar case search.

[1252] "Morphological analysis" is a technique that breaks down a sentence into words or phrases and analyzes the part of speech and meaning of each word.

[1253] "Topic modeling" is a technology that automatically extracts themes from large amounts of document data and is used to identify major themes from users' problem summary data.

[1254] "Similar case search" is a technology that searches a database of past cases for cases similar to the current trouble summary data and provides reference information.

[1255] A "solution" is a solution that provides users with legal advice and appropriate procedures for dealing with legal issues they are experiencing.

[1256] "Feedback" is data, including ratings and comments entered by users regarding the usefulness and actual results of the solutions provided.

[1257] An "analysis model" is a set of programs based on statistical and machine learning algorithms for natural language processing, which are used to analyze problem summary data and generate solutions.

[1258] "Accuracy improvement" refers to continuous improvement activities to improve the performance of databases and analytical models and provide more accurate and appropriate solutions.

[1259] "Legal Institution" refers to an institution from which users can receive legal assistance or advice, such as a law firm, court, or local government helpline.

[1260] This invention is a comprehensive system for quickly and efficiently providing appropriate solutions to legal problems. This system realizes a series of processes from analyzing legal problems to providing solutions by linking together servers, terminals, and users.

[1261] Server-side behavior

[1262] The server operates primarily using the following hardware and software. The server collects reliable data from law firms, courts, etc. and stores it in a database. It also receives summary data of the problem entered by the user and analyzes it using natural language processing technology. Based on the results, it generates an appropriate solution and provides it to the user.

[1263] Hardware and software used

[1264] Database management systems: MySQL, PostgreSQL

[1265] Natural Language Processing Libraries: MeCab, Gensim, ElasticSearch

[1266] Web scraping tools: Beautiful Soup, Scrapy

[1267] Data collection and storage

[1268] The server periodically collects the latest legal information through web scraping, APIs, and manual input, and then organizes and stores the collected data in a database.

[1269] Analysis of trouble summary data

[1270] The trouble summary data received from users is analyzed using natural language processing technology. Specifically, morphological analysis is performed with MeCab, topic modeling is performed with Gensim, and similar cases are searched for with ElasticSearch.

[1271] Solution generation and delivery

[1272] Based on the analysis results, solutions including legal advice and proper procedural methods are generated, and information on relevant law firms and consultation centers is also provided as needed.

[1273] Feedback collection and optimization

[1274] When users input the results of the solutions they used as feedback, the server stores the information in a database, which is used to improve the accuracy of the system's analytical models and databases.

[1275] Operation on the terminal side

[1276] The terminal provides an interface for users to access the system, through which they can create an account, enter a description of their problem, and receive a solution from the system.

[1277] Hardware and software used

[1278] Web browser: Chrome, Firefox

[1279] Mobile Applications: iOS App, Android App

[1280] User Registration and Login

[1281] Users can create an account through a terminal and enter the necessary information, and existing users can access the system by logging in.

[1282] Enter a summary of the problem

[1283] Users enter detailed information about the problem through a terminal. The form includes items such as the type of problem, the date and time it occurred, the people involved, and specific details of the incident.

[1284] Receiving solutions and feedback

[1285] The user receives and views the solutions provided by the server through the terminal, and also inputs feedback on the results of using the proposed solutions and legal support.

[1286] Specific examples

[1287] Example 1: Labor-related issues

[1288] The user wishes to seek advice regarding unfair dismissal under a labor contract. Using the terminal, the user enters the following information:

[1289] Type of problem: Labor issues

[1290] Date of occurrence: August 15, 2023

[1291] Parties involved: Employee (user), Employer (company)

[1292] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[1293] Then the following solutions are provided:

[1294] Checklist for legality of dismissal under the Labor Standards Act

[1295] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[1296] Introduction to law firms that specialize in labor issues

[1297] Example 2: Consultation regarding contract disputes

[1298] The user is consulting about a problem with renewing a rental contract. They enter the following information through the terminal:

[1299] Type of problem: Contract problem

[1300] Date of occurrence: September 10, 2023

[1301] Parties involved: Tenant (user), landlord (landlord)

[1302] Detailed background: The landlord added unfair conditions when renewing the contract.

[1303] Then the following solutions are provided:

[1304] Procedures for verifying the legality of renewal conditions in lease agreements

[1305] Local government rental housing trouble consultation desk

[1306] Introducing a law firm that specializes in real estate issues

[1307] This allows users to obtain solutions to legal problems quickly and appropriately.

[1308] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1309] Step 1:

[1310] User Registration and Login

[1311] Users access the system using a terminal and create an account. The data entered includes personal information such as name, email address, and password. Existing users log in using their email address and password.

[1312] Input data: Name, email address, password

[1313] Output data: User account information

[1314] Specific behavior:

[1315] User reaches registration / login screen.

[1316] The user enters the required information and clicks the submit button.

[1317] The server receives the input data and stores it in a database or performs authentication.

[1318] Step 2:

[1319] Entering trouble summary data

[1320] After registering or logging in to the system, users enter summary data about the problem. The input form includes items such as the type of problem, the date and time it occurred, the people involved, and specific details of the problem.

[1321] Input data: Type of trouble, date and time of occurrence, people involved, specific details

[1322] Output data: Trouble summary data

[1323] Specific behavior:

[1324] The user accesses the trouble summary input screen.

[1325] The user enters the information corresponding to each item and clicks the submit button.

[1326] The server receives the input data and stores it in a database.

[1327] Step 3:

[1328] Data collection and storage

[1329] The server periodically collects data from law firms and courts using web scraping and APIs, and stores it in a database using Python's Beautiful Soup and Scrapy.

[1330] Input data: Legal data obtained from websites and APIs

[1331] Output data: Legal data stored in a database

[1332] Specific behavior:

[1333] The server initiates web scraping or API calls on a schedule.

[1334] Beautiful Soup or Scrapy retrieves data from a specific website.

[1335] The acquired data is analyzed and stored in a database.

[1336] Step 4:

[1337] Analysis of trouble summary data

[1338] The server analyzes the received trouble summary data using natural language processing technology. Specifically, it performs morphological analysis with MeCab, topic modeling with Gensim, and searches for similar cases with ElasticSearch.

[1339] Input data: Trouble summary data received from the user

[1340] Output data: Morphological analysis results, topic models, search results for similar cases

[1341] Specific behavior:

[1342] The server passes the trouble summary data received from the user to the NLP processing pipeline.

[1343] Morphological analysis is performed using MeCab to decompose the data into grammatical parts.

[1344] Use topic modeling with Gensim to extract themes from the data.

[1345] Search for similar cases using ElasticSearch and evaluate their similarity.

[1346] Step 5:

[1347] Solution Generation

[1348] Based on the analysis results, the server generates an optimal solution, which includes legal advice and appropriate procedural instructions, and, if necessary, provides information on relevant law firms and consultation centers.

[1349] Input data: Analysis results (morphological analysis results, topic model, search results for similar cases)

[1350] Output data: Resolution and corresponding legal authority information

[1351] Specific behavior:

[1352] The server provides data to the solution generation algorithm based on the results of the NLP analysis.

[1353] The algorithm references a database of laws and regulations and past cases to construct an appropriate solution.

[1354] If necessary, include information on relevant law firms and counseling services.

[1355] Step 6:

[1356] Providing solutions

[1357] The user receives the generated solution through the terminal, where the solution is displayed and can be viewed by the user.

[1358] Input data: generated solutions and corresponding legal authority information

[1359] Output: The solution displayed on the user's device

[1360] Specific behavior:

[1361] The server sends the generated solution to the user's device.

[1362] The user receives a notification and is taken to a screen that displays the solution.

[1363] Browse the solutions provided by users.

[1364] Step 7:

[1365] Gathering feedback and optimizing the system

[1366] Users input feedback on the results of using the proposed solutions and legal support. The server receives this feedback data and stores it in a database. The collected feedback data is used to improve the accuracy of the system's analytical model and database.

[1367] Input data: Feedback data from users

[1368] Output data: Feedback data stored in database, updated analytical model and database

[1369] Specific behavior:

[1370] The user accesses the feedback input screen.

[1371] Users provide input on the usefulness of the solution and actual results.

[1372] The server receives the feedback data and stores it in a database.

[1373] The server analyzes the collected feedback and uses it to improve the accuracy of the model and update the database.

[1374] (Application example 1)

[1375] 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."

[1376] In modern society, legal issues are diverse, and problems faced by individuals in particular require prompt and appropriate resolution. However, because specialized knowledge and experience are required, it is difficult for individuals to find the optimal solution on their own. Another major issue is the lack of a way to quickly consult with a legal expert without being tied to a physical location. Furthermore, there is a lack of a mechanism for reflecting the effectiveness of the solution obtained as feedback into the system. In this situation, an efficient system is needed that allows users to easily resolve legal issues and receive expert support.

[1377] 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.

[1378] In this invention, the server includes means for collecting legal-related data and storing it in a database, means for receiving summary data of the problem entered by the user, means for analyzing the received summary data using natural language processing and generating an appropriate solution, means for providing the generated solution and information on the corresponding legal agency to the user, means for receiving user feedback and optimizing the system, and means for enabling communication with legal experts in a virtual environment using a smart device. This allows users to obtain quick and appropriate solutions to legal problems through their smart devices and also allows for real-time consultation with experts, thereby enabling efficient and effective resolution of legal problems.

[1379] "Legal data" refers to information such as laws, precedents, legal advice, and consultation cases collected from law firms, courts, the Ministry of Justice, etc.

[1380] A "database" is a collection of information that organizes and stores legal-related data so that it can be searched and used efficiently.

[1381] "Trouble summary data" refers to specific information about the case, such as the type of trouble entered by the user, the date and time of occurrence, the people involved, and detailed background information.

[1382] "Natural language processing" is a technology for analyzing summary data of a problem entered by a user and generating appropriate solutions, and includes morphological analysis, topic modeling, and similar case search.

[1383] "Solutions" refers to proposals generated by natural language processing that include legal advice, appropriate procedural steps, and information on relevant legal authorities.

[1384] "Legal institutions" refers to organizations that provide legal support, such as law firms, courts, labor bureaus, labor standards inspection offices, and municipal consultation centers.

[1385] "Feedback" refers to a user's evaluation or opinion of the results of using the provided solutions or legal support.

[1386] "Smart devices" refers to electronic devices with advanced functions such as smartphones, smart glasses, and head-mounted displays.

[1387] "Virtual environment" refers to a virtual space or online platform that users can access using smart devices.

[1388] "Communication" refers to the means by which legal professionals and users exchange information in real time through a virtual environment.

[1389] System Overview

[1390] The present invention is a comprehensive system for providing appropriate solutions to legal problems quickly and efficiently. This system mainly operates in cooperation with a server, terminals, and users.

[1391] Server-side behavior

[1392] The server collects reliable data from legal institutions and stores it in a database. It also receives summary data of the problem entered by the user on their device and analyzes it using natural language processing technology. Based on the analysis results, it generates appropriate solutions and provides them to the user. It also collects feedback from users and reflects it in improving the system.

[1393] Data collection and storage

[1394] The server periodically collects the latest information from legal agencies through web scraping, APIs, and manual entry, and the collected data is organized and stored in a database.

[1395] Analysis of trouble summary data

[1396] The server analyzes the trouble summary data received from the user using natural language processing (NLP) techniques, such as morphological analysis, topic modeling, and similar case search.

[1397] Solution generation and delivery

[1398] Based on the analysis results, the server generates an optimal solution, including legal advice and appropriate procedural instructions. It also provides information on relevant legal authorities, if necessary. It also allows users to communicate with legal experts in a virtual environment using their smart devices.

[1399] Feedback collection and optimization

[1400] The server receives feedback from users after they have used the solutions and legal support provided, which is stored in a database and used to improve the accuracy of the system's analytical models and database.

[1401] Operation on the terminal side

[1402] The terminal provides an interface for users to access the system. Users use the terminal to create an account, enter a problem description, and receive a solution from the system. This can be a web browser or a mobile application. Users can also use smart devices to communicate with legal experts in a virtual environment in real time.

[1403] User Registration and Login

[1404] Users create an account through a terminal and enter the necessary information. Existing users can access the system by logging in.

[1405] Enter a summary of the problem

[1406] The user enters detailed information about the problem through a terminal. The form includes items such as the type of problem, the date and time of the problem, the people involved, and specific details of the problem.

[1407] Receiving solutions and feedback

[1408] The user receives and views the solutions provided by the server through the terminal, and also inputs feedback on the results of using the proposed solutions and legal support.

[1409] Specific examples

[1410] Example 1: Labor-related issues

[1411] The user wishes to seek advice regarding unfair dismissal under a labor contract. Using the terminal, the user enters the following information:

[1412] Type of problem: Labor issues

[1413] Date of occurrence: August 15, 2023

[1414] Parties involved: Employee (user), Employer (company)

[1415] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[1416] The server receives this information, analyzes it, and makes the following suggestions:

[1417] Checklist for legality of dismissal under the Labor Standards Act

[1418] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[1419] Introduction to law firms that specialize in labor issues

[1420] The user acts on the presented solution and reports the results to the system as feedback.

[1421] Example 2: Consultation regarding contract disputes

[1422] The user wishes to consult about a problem regarding the renewal of a rental contract. The user enters the following information through the terminal:

[1423] Type of problem: Contract problem

[1424] Date of occurrence: September 10, 2023

[1425] Parties involved: Tenant (user), landlord (landlord)

[1426] Detailed background: The landlord added unfair conditions when renewing the contract.

[1427] The server receives this information, analyzes it, and makes the following suggestions:

[1428] Procedures for verifying the legality of renewal conditions in lease agreements

[1429] Local government rental housing trouble consultation desk

[1430] Introducing a law firm that specializes in real estate issues

[1431] The user takes specific action based on the presented solution and reports the results to the system as feedback.

[1432] Example prompts for generative AI models

[1433] "Unfair terms were presented during the contract renewal. Type of problem: Contract dispute, Date of occurrence: September 10, 2023, Parties involved: Tenant and Landlord."

[1434] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1435] Step 1:

[1436] The user creates an account using a terminal and enters the necessary information. The input for this step is the user's personal information and login information. The output is that the user account has been created and is ready to log in.

[1437] Step 2:

[1438] The user inputs detailed information about the problem through the terminal. Specifically, the type of problem, the date and time of occurrence, the people involved, and the specific details. The input of this step is detailed information about the problem, and the output is that this information is sent to the server.

[1439] Step 3:

[1440] The server analyzes the received problem summary data using natural language processing (NLP) technology. The input for this step is the problem summary data sent by the user, and the output is a set of analyzed topics and keywords. Specific operations include morphological analysis, topic modeling, and similar case search.

[1441] Step 4:

[1442] The server generates optimal solutions based on the analysis results. It searches the database for appropriate laws and cases based on the analyzed topics and keywords, and generates legal advice and appropriate procedural methods. The input for this step is the analysis results and related information in the database, and the output is the generated solution.

[1443] Step 5:

[1444] The generated solution and corresponding legal authority information are provided to the user. The server sends the generated solution to the terminal, where the user can view it. The input of this step is the generated solution, and the output is a display of the solution that can be viewed by the user.

[1445] Step 6:

[1446] The server enables real-time communication with a legal expert in a virtual environment using a smart device. The user then uses the smart device to video chat with the legal expert for further consultation. The input of this step is the user's communication request, and the output is the initiation of a real-time video chat session with the legal expert.

[1447] Step 7:

[1448] The user inputs the results of using the provided solutions and legal support as feedback. The feedback is sent to the server and stored in the database. The input of this step is the user's feedback, and the output is the accumulation of feedback in the database.

[1449] Step 8:

[1450] The server uses the collected feedback to refine the system's analytical model and database. The input for this step is the feedback data, and the output is an improved analytical model and a refined database. Specific operations include retraining the model using machine learning algorithms.

[1451] 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.

[1452] System Overview

[1453] This invention is a comprehensive system for quickly and efficiently providing appropriate solutions to legal disputes, and in particular, it incorporates an emotion engine that recognizes the user's emotional state and reflects it in the solution. This system mainly operates in cooperation with a server, terminals, and users.

[1454] Server-side behavior

[1455] The server collects reliable data from law firms and courts and stores it in a database. It also receives summary data of the problem entered by the user and analyzes it using natural language processing and an emotion engine. Based on the analysis results, it generates an appropriate solution and provides it to the user. It also collects feedback from users and reflects it in improving the system.

[1456] Data collection and storage

[1457] The server periodically collects the latest information from law firms and courts through web scraping, APIs, and manual entry, and the collected data is organized and stored in a database.

[1458] Analysis of trouble summary data

[1459] The server analyzes the trouble summary data received from the user using natural language processing (NLP) technology and an emotion engine. It uses an NLP model (e.g., BERT or GPT) to classify the input data, extract important keywords, and understand the details of the trouble. At the same time, it uses the emotion engine to analyze the user's emotional state from the input.

[1460] Solution generation and delivery

[1461] Based on the analysis results, the server generates an optimal solution, including legal advice and appropriate procedural instructions. The solution presentation is tailored to the user's emotional state. If necessary, information on relevant law firms or local government consultation services is also provided.

[1462] Feedback collection and optimization

[1463] The server receives feedback from users after they use the solutions and consultation services provided. This feedback is stored in a database and used to improve the accuracy of the system's analytical model and emotion engine, allowing the system to be continuously optimized.

[1464] Operation on the terminal side

[1465] The terminal provides the interface through which users access the system. The terminal is used by users to create an account, enter a problem description, and receive a solution from the system. This can be a web browser or a mobile application.

[1466] User Registration and Login

[1467] Users create an account through a terminal and enter the necessary information. Existing users can access the system by logging in.

[1468] Enter a summary of the problem

[1469] The user uses a terminal to enter detailed information about the problem. The form includes items such as the type of problem, the date and time of the problem, the people involved, and specific details. The data entered by the user is sent to the server.

[1470] Receiving solutions and feedback

[1471] The user can view the solutions provided by the server through their device and take action if necessary. They can contact the suggested law firms or counseling centers. They can also input feedback on the solutions provided and the results of using legal support.

[1472] Specific examples

[1473] Example 1: Labor-related issues

[1474] The user wishes to seek advice regarding unfair dismissal under a labor contract. Using the terminal, the user enters the following information:

[1475] Type of problem: Labor issues

[1476] Date of occurrence: August 15, 2023

[1477] Parties involved: Employee (user), Employer (company)

[1478] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[1479] As you type, the emotion engine recognizes your emotions, such as anger or anxiety.

[1480] The server receives this information, analyzes it, and makes the following suggestions:

[1481] Checklist for legality of dismissal under the Labor Standards Act

[1482] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[1483] Introduction to law firms that specialize in labor issues

[1484] In response to any concerns users may have, the message is presented in a reassuring manner, such as "verifying legality should be given priority."

[1485] The user acts on the presented solution and reports the results to the system as feedback.

[1486] Example 2: Consultation regarding contract disputes

[1487] The user wishes to consult about a problem regarding the renewal of a rental contract. The user enters the following information through the terminal:

[1488] Type of problem: Contract problem

[1489] Date of occurrence: September 10, 2023

[1490] Parties involved: Tenant (user), landlord (landlord)

[1491] Detailed background: The landlord added unfair conditions when renewing the contract.

[1492] Upon input, the emotion engine recognizes the user's confused emotion.

[1493] The server receives this information, analyzes it, and makes the following suggestions:

[1494] Procedures for verifying the legality of renewal conditions in lease agreements

[1495] Local government rental housing trouble consultation desk

[1496] Introducing a law firm that specializes in real estate issues

[1497] To reduce user confusion, encouraging statements such as "Follow the detailed verification steps and the problem will be resolved" are presented.

[1498] The user takes specific action based on the presented solution and reports the results to the system as feedback.

[1499] In this way, by combining emotion engines, it becomes possible to provide solutions that take into account the user's emotional state, thereby providing effective support for legal disputes.

[1500] The processing flow will be explained below.

[1501] Step 1:

[1502] The server collects reliable data from law firms and courts. It uses web scraping and APIs to obtain the latest laws, precedents, contracts, etc., and stores them in a database. Additionally, it uses OCR technology to digitize manually collected materials as needed and registers them in the database.

[1503] Step 2:

[1504] Users access the system using a terminal and create an account or log in. New users create an account by entering personal information such as their name, email address, and password. Existing users log in by entering their email address and password.

[1505] Step 3:

[1506] The user uses the terminal to enter an outline of the problem. The input form includes items such as the type of problem, the date and time of occurrence, the people involved, and specific details. The user enters this information in detail and presses the send button.

[1507] Step 4:

[1508] The server receives the summary data of the problem sent by the user and stores it in a temporary database. At this point, a simple error check is performed to ensure that there are no problems with the format or content of the input data.

[1509] Step 5:

[1510] The server analyzes the received summary data of the trouble using natural language processing (NLP) technology and an emotion engine. It uses an NLP model (e.g., BERT or GPT) to classify the input data, extract important keywords, and understand the content of the trouble. At the same time, it uses the emotion engine to analyze the emotional state from the user's input.

[1511] Step 6:

[1512] The server uses the analysis results to search for similar cases and related laws and regulations in its database. Based on the search results, it generates the optimal solution and determines its content. The solution includes legal advice and appropriate procedural methods.

[1513] Step 7:

[1514] The server adjusts the content of the solution presented to the user depending on the user's emotional state. For example, if the user is feeling strong emotions such as anxiety or anger, the server changes the presented solution to be more reassuring.

[1515] Step 8:

[1516] The server provides the generated solution to the user, and also lists and displays to the user information on law firms and details of local government consultation centers related to the solution.

[1517] Step 9:

[1518] The user can view the solutions provided by the server through their device and take action if necessary, including contacting the suggested law firm or counseling center.

[1519] Step 10:

[1520] Users enter their feedback on the solutions provided and the results of using the support service in a feedback form, including their evaluation of the effectiveness of the solutions and the quality of the support.

[1521] Step 11:

[1522] The server receives feedback from users and stores it in a database. The collected feedback is used to improve the accuracy of the system's analytical model and emotion engine, allowing the system to be continuously optimized.

[1523] Specific examples

[1524] Example 1: Labor-related issues

[1525] The user wishes to seek advice regarding unfair dismissal under a labor contract. Using the terminal, the user enters the following information:

[1526] Type of problem: Labor issues

[1527] Date of occurrence: August 15, 2023

[1528] Parties involved: Employee (user), Employer (company)

[1529] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[1530] As you type, the emotion engine recognizes your emotions, such as anger or anxiety.

[1531] The server receives this information, analyzes it, and makes the following suggestions:

[1532] Checklist for legality of dismissal under the Labor Standards Act

[1533] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[1534] Introduction to law firms that specialize in labor issues

[1535] In response to any concerns users may have, the message is presented in a reassuring manner, such as "verifying legality should be given priority."

[1536] The user acts on the presented solution and reports the results to the system as feedback.

[1537] Example 2: Consultation regarding contract disputes

[1538] The user wishes to consult about a problem regarding the renewal of a rental contract. The user enters the following information through the terminal:

[1539] Type of problem: Contract problem

[1540] Date of occurrence: September 10, 2023

[1541] Parties involved: Tenant (user), landlord (landlord)

[1542] Detailed background: The landlord added unfair conditions when renewing the contract.

[1543] Upon input, the emotion engine recognizes the user's confused emotion.

[1544] The server receives this information, analyzes it, and makes the following suggestions:

[1545] Procedures for verifying the legality of renewal conditions in lease agreements

[1546] Local government rental housing trouble consultation desk

[1547] Introducing a law firm that specializes in real estate issues

[1548] To reduce user confusion, encouraging statements such as "Follow the detailed verification steps and the problem will be resolved" are presented.

[1549] The user takes specific action based on the presented solution and reports the results to the system as feedback.

[1550] In this way, by combining emotion engines, it becomes possible to provide solutions that take into account the user's emotional state, thereby providing effective support for legal disputes.

[1551] Example 2

[1552] 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."

[1553] Conventional legal systems only provide solutions to legal disputes without taking into account the user's emotional state. This can lead to problems such as users finding it difficult to understand the solutions or lacking motivation to take appropriate action. Furthermore, they lack the ability to collect feedback and optimize the system to improve the effectiveness of the solutions provided.

[1554] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1555] In this invention, the server includes means for collecting legal-related data and storing it in a database, means for receiving summary data of the problem entered by the user, means for analyzing the received summary data using natural language processing and generating an appropriate solution, means for adjusting the way the solution is presented using an emotion engine that analyzes the user's emotional state, means for providing the user with the generated solution and information on the corresponding legal agency, and means for receiving user feedback and optimizing the system. This makes it possible to provide solutions that take the user's emotional state into consideration, thereby realizing more effective support for legal troubles.

[1556] "Legal data" refers to information such as laws, precedents, cases, and legal consultation results collected from law firms and courts.

[1557] A "database" is an information system that organizes and stores collected legal-related data, allowing it to be efficiently searched and accessed when needed.

[1558] "User" means an individual or organization that uses the system to seek legal advice.

[1559] "Summary data of the trouble" is detailed information entered by the user, such as the type of trouble, the date and time of occurrence, the people involved, and the specific details of the trouble.

[1560] "Natural language processing" is a technology that analyzes and processes text data entered by the user to understand and generate human language.

[1561] "Solutions" are specific advice or suggestions generated to solve a problem based on trouble data analyzed using natural language processing.

[1562] An "emotion engine" is a technology that analyzes a user's emotional state and adjusts the way solutions are presented to take those emotions into consideration.

[1563] "Feedback" refers to the user's opinions and evaluations of the solutions provided or the results of using the consultation service.

[1564] "System optimization" is the process of continuously improving the overall performance and accuracy of the system based on collected feedback.

[1565] "Legal institutions" are organizations that provide legal support, such as law firms, courts, and local government helplines.

[1566] A "natural language processing model" is a machine learning model, such as BERT or GPT, that is used to understand and analyze user input text and generate appropriate solutions.

[1567] "Solution presentation method" is a means of adjusting the content and presentation of the solution depending on the user's emotional state.

[1568] "Information provision" is the process of communicating generated solutions and relevant legal information to users.

[1569] MODE FOR CARRYING OUT THE INVENTION

[1570] System Overview

[1571] This invention is a system for quickly and efficiently providing appropriate solutions to legal problems, and in particular, it combines an emotion engine that recognizes the user's emotional state and reflects it in the solution. This system mainly operates in cooperation with a server, terminals, and users.

[1572] System configuration

[1573] The server collects reliable data from law firms and courts and stores it in a database. It also receives summary data of the problem entered by the user and analyzes it using natural language processing and an emotion engine. Based on the analysis results, it generates an appropriate solution and provides it to the user. It also collects feedback from users and reflects it in improving the system. Specifically, the following hardware and software are used:

[1574] Hardware: Servers, client devices (PCs, smartphones, tablets)

[1575] Software: Natural language processing models (BERT, GPT), sentiment engine, database management system, web server

[1576] Server-side behavior

[1577] 1. Data collection and storage:

[1578] The server periodically collects the latest legal information using web scraping, APIs, and manual input.

[1579] The collected data is organized and stored in a database.

[1580] 2. Analysis of Trouble Summary Data:

[1581] The server analyzes the summary data of the problem received from the user using natural language processing (NLP) techniques such as BERT and GPT.

[1582] Through analysis, the input data is classified, important keywords are extracted, and the nature of the problem is understood.

[1583] At the same time, an emotion engine is used to analyze the emotional state from the user's input.

[1584] 3. Solution generation and delivery:

[1585] Based on the analysis, the server generates an optimal solution, which may include legal advice and proper procedural instructions.

[1586] The system adjusts the way solutions are presented depending on the user's emotional state, and also provides information on relevant law firms and local government consultation services.

[1587] 4. Feedback collection and optimization:

[1588] The server receives feedback from the user after the user has used the provided solutions and helplines.

[1589] The feedback is stored in a database and used to improve the accuracy of the system's analytical models and emotion engine.

[1590] Operation on the terminal side

[1591] 1. User Registration and Login:

[1592] Users create an account through a terminal and enter the necessary information. Existing users can access the system by logging in.

[1593] 2. Enter a summary of the problem:

[1594] The user uses a terminal to input detailed information about the problem. The input format includes text boxes where the user can enter the type of problem, the date and time of occurrence, the people involved, and detailed information about the problem.

[1595] The user's input data is sent to the server.

[1596] 3. Receiving solutions and feedback:

[1597] The user can view the solutions provided by the server through the terminal and take action as necessary.

[1598] Provide feedback on the solutions provided and the results of using legal support.

[1599] Specific examples

[1600] Example 1: Labor-related issues

[1601] When a user wishes to consult about unfair dismissal under a labor contract, the user inputs the following information using a terminal.

[1602] Type of problem: Labor issues

[1603] Date of occurrence: August 15, 2023

[1604] Parties involved: Employee (user), Employer (company)

[1605] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[1606] As you type, the emotion engine recognizes your emotions, such as anger or anxiety.

[1607] The server receives this information, analyzes it, and makes the following suggestions:

[1608] Checklist for legality of dismissal under the Labor Standards Act

[1609] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[1610] Introduction to law firms that specialize in labor issues

[1611] The solution is presented in a way that gives the user a sense of security, such as "Confirming legality should be prioritized," in response to any concerns the user may have. The user then takes action based on the presented solution and reports the results to the system as feedback.

[1612] Example 2: Consultation regarding contract disputes

[1613] When consulting about a problem with renewing a rental contract, the user enters the following information:

[1614] Type of problem: Contract problem

[1615] Date of occurrence: September 10, 2023

[1616] Parties involved: Tenant (user), landlord (landlord)

[1617] Detailed background: The landlord added unfair conditions when renewing the contract.

[1618] Upon input, the emotion engine recognizes the user's confused emotion.

[1619] The server receives this information, analyzes it, and makes the following suggestions:

[1620] Procedures for verifying the legality of renewal conditions in lease agreements

[1621] Local government rental housing trouble consultation desk

[1622] Introducing a law firm that specializes in real estate issues

[1623] To alleviate user confusion, encouraging messages such as, "Follow the detailed confirmation steps and your problem will be solved." In this way, by combining the emotion engine, it is possible to provide solutions that take into account the user's emotional state, thereby achieving effective support for legal disputes.

[1624] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1625] Step 1: User registration and login

[1626] Users create an account using a device. They register by entering their username, email address, password, etc. Existing users can log in by entering their account information.

[1627] The device sends the entered information to the server, which receives it, stores it in a database, verifies the login information, and redirects the user to the dashboard if authentication is successful.

[1628] Input: User information (user name, email address, password)

[1629] Output: Authentication results, dashboard access

[1630] Step 2: Enter a description of the problem

[1631] The user uses the terminal to input detailed information about the problem, such as the type of problem, the date and time of occurrence, the people involved, and a detailed history of the problem, into an input form.

[1632] The terminal sends the entered data to the server, which stores the received data in a database. Once the data is stored, the analysis process is initiated.

[1633] Input: Detailed information about the problem (type, date and time of occurrence, people involved, detailed history)

[1634] Output: Saving data and launching analysis processes

[1635] Step 3: Analyze the trouble summary data

[1636] The server analyzes the received summary data of the trouble using natural language processing models such as BERT and GPT.

[1637] For analysis, the data is pre-processed (tokenized and normalized) and then input into the model. The NLP model analyzes the text data, extracts important keywords and phrases, and classifies the content of the problem.

[1638] Input: Summary of the problem

[1639] Output: Analysis results (keywords, classification results)

[1640] Step 4: Analyze emotional state

[1641] Based on the results of the natural language processing analysis, the server uses an emotion engine to analyze the user's emotional state.

[1642] The text data is input into an emotion model to identify the user's emotion (e.g., anger, anxiety, confusion), and the emotion model returns the result.

[1643] Input: Analysis results (keywords, classification results)

[1644] Output: Emotion analysis results (anger, anxiety, confusion, etc.)

[1645] Step 5: Generate a solution

[1646] The server generates an appropriate solution based on the content of the problem and the user's emotional state, and refers to a legal database to collect relevant information.

[1647] Solutions include legal advice and specific procedural steps, and are tailored to the user's emotional state.

[1648] Input: Sentiment analysis results, legal data

[1649] Output: Generated solution

[1650] Step 6: Propose a solution

[1651] The server sends the generated solution to the terminal.

[1652] The device displays a solution to the user. The solution is presented in a way that takes into consideration the user's emotions. For example, if the user is feeling anxious, the device uses reassuring language such as "First, confirming legality is a priority."

[1653] Input: Generated solution

[1654] Output: The solution that is displayed to the user

[1655] Step 7: Receiving feedback

[1656] The user acts on the provided solutions and provides feedback on the results.

[1657] The device receives the feedback and sends it to a server, which stores it in a database and uses it for analysis.

[1658] Input: User feedback

[1659] Output: feedback storage and system optimization

[1660] This series of steps not only provides users with a fast and appropriate solution, but also takes into account the user's emotional state. The system is continuously improved using collected feedback.

[1661] (Application example 2)

[1662] 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."

[1663] In modern society, the number of opportunities to face legal troubles and security issues is increasing, and resolving these issues requires providing prompt and accurate information. Furthermore, if individual responses are not given taking into account the user's emotional state, users' stress and anxiety will increase, which will become a barrier to problem resolution. Therefore, a system that provides legal and security advice combined with emotion recognition is needed.

[1664] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting legal-related data and storing it in a database, means for receiving summary data of the problem entered by the user, means for analyzing the received summary data using natural language processing and emotion recognition to generate an appropriate solution, means for providing the generated solution and information on corresponding related organizations to the user, and means for receiving user feedback and optimizing the system. This makes it possible to provide quick and emotion-sensitive solutions to legal and security issues.

[1665] "Legal data" is a general term for information about laws, precedents, legal advice, and procedures collected from law firms, courts, government agencies, etc.

[1666] A "database" is an information management system that systematically stores collected legal data, user input data, feedback information, etc., and uses them for search and analysis.

[1667] "Summary data of the trouble entered by the user" refers to detailed information provided by the user to the system, such as the type of trouble, the date and time of occurrence, the people involved, and the specific details of the trouble.

[1668] "Natural language processing" is a technology that analyzes summary data of problems and other text data to extract and classify important keywords, and is a method for computers to understand and process human language.

[1669] "Emotion recognition" is a technology that analyzes and recognizes a user's emotional state (e.g., anger, anxiety, confusion, etc.) from text and other data entered by the user.

[1670] "Appropriate solutions" are those that provide legally accurate and feasible advice and procedures for the problems users are facing, based on collected legal data and analysis results.

[1671] "Related institutions" is a general term for specialized institutions or organizations related to resolving user disputes, such as law firms, courts, and consultation centers.

[1672] "Feedback" means any evaluation or comment you make about the results or experience you have had implementing or using a solution or service provided.

[1673] "Optimization" is the process of improving models and algorithms based on feedback received from users in order to improve the overall performance and accuracy of the system.

[1674] System Overview

[1675] This invention is a system for providing quick and effective solutions to legal and security disputes. In particular, it incorporates an emotion recognition engine that recognizes the user's emotional state and reflects it in the solution. This system mainly operates in cooperation with a server, terminals, and users.

[1676] Server-side behavior

[1677] The server collects legal data and stores it in a database. Specifically, the server periodically collects data automatically from authorized data sources (e.g., law firms, courts, and government agencies). This data collection is done using web scraping, APIs, and manual entry. The collected data is then organized and stored in a database.

[1678] After receiving the user's summary of the problem, the server analyzes it using natural language processing (NLP) technology and an emotion recognition engine. NLP models used, such as BERT and GPT, classify the input data, extract important keywords, and understand the nature of the problem. At the same time, the emotion recognition engine analyzes the user's emotional state from the input.

[1679] Based on the analysis results, the server generates an optimal solution, including legal advice and appropriate procedural instructions. The solution presentation is tailored to the user's emotional state. It also provides information on relevant law firms and local government consultation services.

[1680] After users use the solutions and consultation services provided, the server receives feedback, which is stored in a database and used to improve the accuracy of the system's analytical models and emotion recognition engine, allowing the system to be continuously optimized.

[1681] Operation on the terminal side

[1682] The terminal provides an interface for users to access the system. Users can use the terminal to create an account, enter a summary of the problem, and receive a solution from the system. Specifically, this role is played by a web browser or a mobile application.

[1683] Users create an account through their device and enter the necessary information. Existing users can access the system by logging in. When entering detailed information about a problem using the device, the emotion recognition engine analyzes the user's emotions in real time and sends the analysis results to the server.

[1684] After receiving the solution provided by the server, the user can view the solution through the terminal and take action if necessary. The user can also contact the suggested law firm or consultation center through the terminal. In addition, the user can enter feedback on the results of using the provided solution.

[1685] Specific examples

[1686] Example 1: Labor-related issues

[1687] When a user wishes to consult about unfair dismissal under a labor contract, the user enters the following information using the terminal.

[1688] Type of problem: Labor issues

[1689] Date of occurrence: August 15, 2023

[1690] Parties involved: Employee (user), Employer (company)

[1691] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[1692] When inputting, the emotion recognition engine recognizes the user's emotions such as anger or anxiety. The server receives this information and analyzes it. As a result, it makes the following suggestions:

[1693] Checklist for legality of dismissal under the Labor Standards Act

[1694] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[1695] Introduction to law firms that specialize in labor issues

[1696] In response to users' concerns, solutions are presented in a reassuring manner, such as "verifying legality should be given priority."

[1697] Example 2: Consultation regarding contract disputes

[1698] When a user wishes to consult about a problem with renewing a rental contract, the user enters the following information through the terminal.

[1699] Type of problem: Contract problem

[1700] Date of occurrence: September 10, 2023

[1701] Parties involved: Tenant (user), landlord (landlord)

[1702] Detailed background: The landlord added unfair conditions when renewing the contract.

[1703] When inputting, the emotion recognition engine will recognize the user's confused emotion. The server will receive this information and analyze it. As a result, it will make the following suggestions:

[1704] Procedures for verifying the legality of renewal conditions in lease agreements

[1705] Local government rental housing trouble consultation desk

[1706] Introducing a law firm that specializes in real estate issues

[1707] To reduce user confusion, solutions are presented in encouraging language such as, "Follow our detailed verification steps and your problem will be resolved."

[1708] Prompt Sentence Examples

[1709] For example, a generative AI model operates using prompt statements such as the following:

[1710] Type of problem: Contract problem

[1711] Problem description: Last night I received an email that I suspected was a phishing scam.

[1712] Emotional state: Anxiety

[1713] Legal advice: Check if the link is from a trusted site, avoid opening suspicious emails, and contact the police or security agencies.

[1714] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1715] Step 1:

[1716] A user accesses a device and creates or logs in to an account. The input data is the user's authentication information (username, password, etc.). The device receives this and sends it to the server. The server performs authentication and, if successful, returns the user's profile information to the device.

[1717] Step 2:

[1718] The user uses a terminal to input summary data about the problem. The input data includes the type of problem, the date and time of occurrence, the people involved, and a detailed history. The terminal receives this data and sends it to the server.

[1719] Step 3:

[1720] The server analyzes the received summary data of the trouble using natural language processing (NLP). It uses an NLP model (e.g., BERT, GPT, etc.) to classify the input data and extract keywords. The input data is the trouble text, and the output data is the analyzed keyword list and classification results.

[1721] Step 4:

[1722] The server simultaneously uses an emotion recognition engine to analyze the user's emotional state. The input data is the summary of the problem, and the output data is the user's emotional state (e.g., anger, anxiety, confusion, etc.). The analysis results are combined with the results of natural language processing.

[1723] Step 5:

[1724] The server generates appropriate solutions based on the analysis results. The solution generation utilizes collected legal data and information from related agencies. The input data is the NLP and emotion recognition results, and the output data is the solution and information from related agencies.

[1725] Step 6:

[1726] The server sends the generated solution and related organization information to the terminal. The user uses the terminal to view the solution. The output data is the solution and related organization information.

[1727] Step 7:

[1728] The user takes action based on the provided solution and inputs the results as feedback into the device. The input data is the feedback content (e.g., satisfaction level, additional comments). The device receives this and sends it to the server.

[1729] Step 8:

[1730] The server receives the feedback and stores it in a database. The input data is the user's feedback. The server optimizes the analysis model and emotion recognition engine for future solution generation. This improves the accuracy and usefulness of the system.

[1731] 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.

[1732] 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.

[1733] 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.

[1734] [Fourth embodiment]

[1735] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1736] 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.

[1737] 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).

[1738] 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.

[1739] 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.

[1740] 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).

[1741] 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.

[1742] 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.

[1743] 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.

[1744] 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.

[1745] 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.

[1746] 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.

[1747] 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."

[1748] System Overview

[1749] The present invention is a comprehensive system for providing appropriate solutions to legal problems quickly and efficiently. This system mainly operates in cooperation with a server, terminals, and users.

[1750] Server-side behavior

[1751] The server collects reliable data from law firms, courts, and other sources and stores it in a database. It also receives summary data about the problem entered by the user on their device and analyzes it using natural language processing technology. Based on the analysis results, it generates appropriate solutions and provides them to the user. It also collects feedback from users and reflects it in improving the system.

[1752] Data collection and storage

[1753] The server periodically collects the latest information from law firms and courts through web scraping, APIs, and manual entry, and the collected data is organized and stored in a database.

[1754] Analysis of trouble summary data

[1755] The server analyzes the trouble summary data received from the user using natural language processing (NLP) techniques, such as morphological analysis, topic modeling, and similar case search.

[1756] Solution generation and delivery

[1757] Based on the analysis results, the server generates an optimal solution, which includes legal advice and appropriate procedural instructions, and, if necessary, provides information on relevant law firms and local government consultation services.

[1758] Feedback collection and optimization

[1759] The server receives feedback from users after they have used the solutions and consultation services provided, and this feedback is stored in a database and used to improve the accuracy of the system's analytical model and database.

[1760] Operation on the terminal side

[1761] The terminal provides the interface through which users access the system. The terminal is used by users to create an account, enter a problem description, and receive a solution from the system. This can be a web browser or a mobile application.

[1762] User Registration and Login

[1763] Users create an account through a terminal and enter the necessary information. Existing users can access the system by logging in.

[1764] Enter a summary of the problem

[1765] The user enters detailed information about the problem through a terminal. The form includes items such as the type of problem, the date and time of the problem, the people involved, and specific details of the problem.

[1766] Receiving solutions and feedback

[1767] The user receives and views the solutions provided by the server through the terminal, and also inputs feedback on the results of using the proposed solutions and legal support.

[1768] Specific examples

[1769] Example 1: Labor-related issues

[1770] The user wishes to seek advice regarding unfair dismissal under a labor contract. Using the terminal, the user enters the following information:

[1771] Type of problem: Labor issues

[1772] Date of occurrence: August 15, 2023

[1773] Parties involved: Employee (user), Employer (company)

[1774] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[1775] The server receives this information, analyzes it, and makes the following suggestions:

[1776] Checklist for legality of dismissal under the Labor Standards Act

[1777] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[1778] Introduction to law firms that specialize in labor issues

[1779] The user acts on the presented solution and reports the results to the system as feedback.

[1780] Example 2: Consultation regarding contract disputes

[1781] The user wishes to consult about a problem regarding the renewal of a rental contract. The user enters the following information through the terminal:

[1782] Type of problem: Contract problem

[1783] Date of occurrence: September 10, 2023

[1784] Parties involved: Tenant (user), landlord (landlord)

[1785] Detailed background: The landlord added unfair conditions when renewing the contract.

[1786] The server receives this information, analyzes it, and makes the following suggestions:

[1787] Procedures for verifying the legality of renewal conditions in lease agreements

[1788] Local government rental housing trouble consultation desk

[1789] Introducing a law firm that specializes in real estate issues

[1790] The user takes specific action based on the presented solution and reports the results to the system as feedback.

[1791] In this way, the system of the present invention provides comprehensive support for quickly and appropriately responding to legal troubles.

[1792] The processing flow will be explained below.

[1793] Step 1:

[1794] The server collects reliable data from law firms and courts. It uses web scraping and APIs to obtain the latest laws, precedents, contracts, etc., and stores them in a database. Additionally, it uses OCR technology to digitize manually collected materials as needed and registers them in the database.

[1795] Step 2:

[1796] Users access the system using a terminal and create an account or log in. New users create an account by entering personal information such as their name, email address, and password. Existing users enter their email address and password, which are then verified by the server.

[1797] Step 3:

[1798] The user uses the terminal to input an outline of the problem. The input form includes items such as the type of problem, the date and time of occurrence, the people involved, and specific details. The user enters this information in detail.

[1799] Step 4:

[1800] The server receives the summary data of the problem sent by the user and stores it in a temporary database. At this point, a simple error check is performed to ensure that there are no problems with the format or content of the input data.

[1801] Step 5:

[1802] The server analyzes the received summary data of the problem using natural language processing (NLP) technology. It uses an NLP model (e.g., BERT or GPT) to classify the input data, extract important keywords, and understand the content of the problem.

[1803] Step 6:

[1804] The server searches the database for similar cases and related laws and regulations based on the analysis results, and generates the optimal solution based on the search results and determines which solution to provide to the user.

[1805] Step 7:

[1806] The server provides the generated solution to the user, and also lists and displays to the user information on law firms and details of local government consultation centers related to the solution.

[1807] Step 8:

[1808] The user can view the solutions provided by the server through their device and take action if necessary, including contacting the suggested law firm or counseling center.

[1809] Step 9:

[1810] Users enter their feedback on the solutions provided and the results of using the support service in a feedback form, including their evaluation of the effectiveness of the solutions and the quality of the support.

[1811] Step 10:

[1812] The server receives feedback from users and stores it in a database. The collected feedback is used to improve the accuracy of the system's analytical model and database, allowing the system to be continuously optimized.

[1813] Through these steps, this system provides users with efficient solutions to legal problems and creates an environment where they can easily access reliable legal support.

[1814] Example 1

[1815] 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."

[1816] In conventional legal systems, it took time and effort to manually analyze the outline of the problem and provide an appropriate solution. It was also difficult to effectively collect user feedback and reflect it in system optimization. Furthermore, the collection of updated information on related laws and past case data was not automated, which led to delays in system updates and accuracy improvements.

[1817] 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.

[1818] In this invention, the server includes means for collecting legal-related data and storing it in a database, means for receiving summary data of the problem entered by the user, means for analyzing the received summary data using natural language processing and generating an appropriate solution, means for providing the user with the generated solution and information on the corresponding legal agency, means for receiving user feedback and optimizing the system, means for performing morphological analysis, topic modeling, and similar case search using natural language processing technology on the summary data of the problem entered by the user, means for generating a solution including legally compliant advice and appropriate procedural methods based on the analysis results, and means for storing feedback data entered by the user in the database after providing the generated solution and using it to improve the accuracy of the analysis model and the database. This enables fast and efficient problem analysis and solution presentation, and enables effective collection of user feedback and continuous optimization of the system.

[1819] "Legal data" refers to highly reliable information provided by law firms and courts, including laws, court precedents, legal consultation cases, and other information.

[1820] "Trouble summary data" is data that details the legal problem the user has experienced, including the type of trouble, the date and time of occurrence, the people involved, and the specific circumstances.

[1821] The "database" is an information management system for organizing and storing collected legal-related data, trouble summary data from users, and feedback data.

[1822] "Natural language processing" is a technology that allows computers to understand and analyze natural language used by humans, and includes techniques such as morphological analysis, topic modeling, and similar case search.

[1823] "Morphological analysis" is a technique that breaks down a sentence into words or phrases and analyzes the part of speech and meaning of each word.

[1824] "Topic modeling" is a technology that automatically extracts themes from large amounts of document data and is used to identify major themes from users' problem summary data.

[1825] "Similar case search" is a technology that searches a database of past cases for cases similar to the current trouble summary data and provides reference information.

[1826] A "solution" is a solution that provides users with legal advice and appropriate procedures for dealing with legal issues they are experiencing.

[1827] "Feedback" is data, including ratings and comments entered by users regarding the usefulness and actual results of the solutions provided.

[1828] An "analysis model" is a set of programs based on statistical and machine learning algorithms for natural language processing, which are used to analyze problem summary data and generate solutions.

[1829] "Accuracy improvement" refers to continuous improvement activities to improve the performance of databases and analytical models and provide more accurate and appropriate solutions.

[1830] "Legal Institution" refers to an institution from which users can receive legal assistance or advice, such as a law firm, court, or local government helpline.

[1831] This invention is a comprehensive system for quickly and efficiently providing appropriate solutions to legal problems. This system realizes a series of processes from analyzing legal problems to providing solutions by linking together servers, terminals, and users.

[1832] Server-side behavior

[1833] The server operates primarily using the following hardware and software. The server collects reliable data from law firms, courts, etc. and stores it in a database. It also receives summary data of the problem entered by the user and analyzes it using natural language processing technology. Based on the results, it generates an appropriate solution and provides it to the user.

[1834] Hardware and software used

[1835] Database management systems: MySQL, PostgreSQL

[1836] Natural Language Processing Libraries: MeCab, Gensim, ElasticSearch

[1837] Web scraping tools: Beautiful Soup, Scrapy

[1838] Data collection and storage

[1839] The server periodically collects the latest legal information through web scraping, APIs, and manual input, and then organizes and stores the collected data in a database.

[1840] Analysis of trouble summary data

[1841] The trouble summary data received from users is analyzed using natural language processing technology. Specifically, morphological analysis is performed with MeCab, topic modeling is performed with Gensim, and similar cases are searched for with ElasticSearch.

[1842] Solution generation and delivery

[1843] Based on the analysis results, solutions including legal advice and proper procedural methods are generated, and information on relevant law firms and consultation centers is also provided as needed.

[1844] Feedback collection and optimization

[1845] When users input the results of the solutions they used as feedback, the server stores the information in a database, which is used to improve the accuracy of the system's analytical models and databases.

[1846] Operation on the terminal side

[1847] The terminal provides an interface for users to access the system, through which they can create an account, enter a description of their problem, and receive a solution from the system.

[1848] Hardware and software used

[1849] Web browser: Chrome, Firefox

[1850] Mobile Applications: iOS App, Android App

[1851] User Registration and Login

[1852] Users can create an account through a terminal and enter the necessary information, and existing users can access the system by logging in.

[1853] Enter a summary of the problem

[1854] Users enter detailed information about the problem through a terminal. The form includes items such as the type of problem, the date and time it occurred, the people involved, and specific details of the incident.

[1855] Receiving solutions and feedback

[1856] The user receives and views the solutions provided by the server through the terminal, and also inputs feedback on the results of using the proposed solutions and legal support.

[1857] Specific examples

[1858] Example 1: Labor-related issues

[1859] The user wishes to seek advice regarding unfair dismissal under a labor contract. Using the terminal, the user enters the following information:

[1860] Type of problem: Labor issues

[1861] Date of occurrence: August 15, 2023

[1862] Parties involved: Employee (user), Employer (company)

[1863] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[1864] Then the following solutions are provided:

[1865] Checklist for legality of dismissal under the Labor Standards Act

[1866] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[1867] Introduction to law firms that specialize in labor issues

[1868] Example 2: Consultation regarding contract disputes

[1869] The user is consulting about a problem with renewing a rental contract. They enter the following information through the terminal:

[1870] Type of problem: Contract problem

[1871] Date of occurrence: September 10, 2023

[1872] Parties involved: Tenant (user), landlord (landlord)

[1873] Detailed background: The landlord added unfair conditions when renewing the contract.

[1874] Then the following solutions are provided:

[1875] Procedures for verifying the legality of renewal conditions in lease agreements

[1876] Local government rental housing trouble consultation desk

[1877] Introducing a law firm that specializes in real estate issues

[1878] This allows users to obtain solutions to legal problems quickly and appropriately.

[1879] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1880] Step 1:

[1881] User Registration and Login

[1882] Users access the system using a terminal and create an account. The data entered includes personal information such as name, email address, and password. Existing users log in using their email address and password.

[1883] Input data: Name, email address, password

[1884] Output data: User account information

[1885] Specific behavior:

[1886] User reaches registration / login screen.

[1887] The user enters the required information and clicks the submit button.

[1888] The server receives the input data and stores it in a database or performs authentication.

[1889] Step 2:

[1890] Entering trouble summary data

[1891] After registering or logging in to the system, users enter summary data about the problem. The input form includes items such as the type of problem, the date and time it occurred, the people involved, and specific details of the problem.

[1892] Input data: Type of trouble, date and time of occurrence, people involved, specific details

[1893] Output data: Trouble summary data

[1894] Specific behavior:

[1895] The user accesses the trouble summary input screen.

[1896] The user enters the information corresponding to each item and clicks the submit button.

[1897] The server receives the input data and stores it in a database.

[1898] Step 3:

[1899] Data collection and storage

[1900] The server periodically collects data from law firms and courts using web scraping and APIs, and stores it in a database using Python's Beautiful Soup and Scrapy.

[1901] Input data: Legal data obtained from websites and APIs

[1902] Output data: Legal data stored in a database

[1903] Specific behavior:

[1904] The server initiates web scraping or API calls on a schedule.

[1905] Beautiful Soup or Scrapy retrieves data from a specific website.

[1906] The acquired data is analyzed and stored in a database.

[1907] Step 4:

[1908] Analysis of trouble summary data

[1909] The server analyzes the received trouble summary data using natural language processing technology. Specifically, it performs morphological analysis with MeCab, topic modeling with Gensim, and searches for similar cases with ElasticSearch.

[1910] Input data: Trouble summary data received from the user

[1911] Output data: Morphological analysis results, topic models, search results for similar cases

[1912] Specific behavior:

[1913] The server passes the trouble summary data received from the user to the NLP processing pipeline.

[1914] Morphological analysis is performed using MeCab to decompose the data into grammatical parts.

[1915] Use topic modeling with Gensim to extract themes from the data.

[1916] Search for similar cases using ElasticSearch and evaluate their similarity.

[1917] Step 5:

[1918] Solution Generation

[1919] Based on the analysis results, the server generates an optimal solution, which includes legal advice and appropriate procedural instructions, and, if necessary, provides information on relevant law firms and consultation centers.

[1920] Input data: Analysis results (morphological analysis results, topic model, search results for similar cases)

[1921] Output data: Resolution and corresponding legal authority information

[1922] Specific behavior:

[1923] The server provides data to the solution generation algorithm based on the results of the NLP analysis.

[1924] The algorithm references a database of laws and regulations and past cases to construct an appropriate solution.

[1925] If necessary, include information on relevant law firms and counseling services.

[1926] Step 6:

[1927] Providing solutions

[1928] The user receives the generated solution through the terminal, where the solution is displayed and can be viewed by the user.

[1929] Input data: generated solutions and corresponding legal authority information

[1930] Output: The solution displayed on the user's device

[1931] Specific behavior:

[1932] The server sends the generated solution to the user's device.

[1933] The user receives a notification and is taken to a screen that displays the solution.

[1934] Browse the solutions provided by users.

[1935] Step 7:

[1936] Gathering feedback and optimizing the system

[1937] Users input feedback on the results of using the proposed solutions and legal support. The server receives this feedback data and stores it in a database. The collected feedback data is used to improve the accuracy of the system's analytical model and database.

[1938] Input data: Feedback data from users

[1939] Output data: Feedback data stored in database, updated analytical model and database

[1940] Specific behavior:

[1941] The user accesses the feedback input screen.

[1942] Users provide input on the usefulness of the solution and actual results.

[1943] The server receives the feedback data and stores it in a database.

[1944] The server analyzes the collected feedback and uses it to improve the accuracy of the model and update the database.

[1945] (Application example 1)

[1946] 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."

[1947] In modern society, legal issues are diverse, and problems faced by individuals in particular require prompt and appropriate resolution. However, because specialized knowledge and experience are required, it is difficult for individuals to find the optimal solution on their own. Another major issue is the lack of a way to quickly consult with a legal expert without being tied to a physical location. Furthermore, there is a lack of a mechanism for reflecting the effectiveness of the solution obtained as feedback into the system. In this situation, an efficient system is needed that allows users to easily resolve legal issues and receive expert support.

[1948] 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.

[1949] In this invention, the server includes means for collecting legal-related data and storing it in a database, means for receiving summary data of the problem entered by the user, means for analyzing the received summary data using natural language processing and generating an appropriate solution, means for providing the generated solution and information on the corresponding legal agency to the user, means for receiving user feedback and optimizing the system, and means for enabling communication with legal experts in a virtual environment using a smart device. This allows users to obtain quick and appropriate solutions to legal problems through their smart devices and also allows for real-time consultation with experts, thereby enabling efficient and effective resolution of legal problems.

[1950] "Legal data" refers to information such as laws, precedents, legal advice, and consultation cases collected from law firms, courts, the Ministry of Justice, etc.

[1951] A "database" is a collection of information that organizes and stores legal-related data so that it can be searched and used efficiently.

[1952] "Trouble summary data" refers to specific information about the case, such as the type of trouble entered by the user, the date and time of occurrence, the people involved, and detailed background information.

[1953] "Natural language processing" is a technology for analyzing summary data of a problem entered by a user and generating appropriate solutions, and includes morphological analysis, topic modeling, and similar case search.

[1954] "Solutions" refers to proposals generated by natural language processing that include legal advice, appropriate procedural steps, and information on relevant legal authorities.

[1955] "Legal institutions" refers to organizations that provide legal support, such as law firms, courts, labor bureaus, labor standards inspection offices, and municipal consultation centers.

[1956] "Feedback" refers to a user's evaluation or opinion of the results of using the provided solutions or legal support.

[1957] "Smart devices" refers to electronic devices with advanced functions such as smartphones, smart glasses, and head-mounted displays.

[1958] "Virtual environment" refers to a virtual space or online platform that users can access using smart devices.

[1959] "Communication" refers to the means by which legal professionals and users exchange information in real time through a virtual environment.

[1960] System Overview

[1961] The present invention is a comprehensive system for providing appropriate solutions to legal problems quickly and efficiently. This system mainly operates in cooperation with a server, terminals, and users.

[1962] Server-side behavior

[1963] The server collects reliable data from legal institutions and stores it in a database. It also receives summary data of the problem entered by the user on their device and analyzes it using natural language processing technology. Based on the analysis results, it generates appropriate solutions and provides them to the user. It also collects feedback from users and reflects it in improving the system.

[1964] Data collection and storage

[1965] The server periodically collects the latest information from legal agencies through web scraping, APIs, and manual entry, and the collected data is organized and stored in a database.

[1966] Analysis of trouble summary data

[1967] The server analyzes the trouble summary data received from the user using natural language processing (NLP) techniques, such as morphological analysis, topic modeling, and similar case search.

[1968] Solution generation and delivery

[1969] Based on the analysis results, the server generates an optimal solution, including legal advice and appropriate procedural instructions. It also provides information on relevant legal authorities, if necessary. It also allows users to communicate with legal experts in a virtual environment using their smart devices.

[1970] Feedback collection and optimization

[1971] The server receives feedback from users after they have used the solutions and legal support provided, which is stored in a database and used to improve the accuracy of the system's analytical models and database.

[1972] Operation on the terminal side

[1973] The terminal provides an interface for users to access the system. Users use the terminal to create an account, enter a problem description, and receive a solution from the system. This can be a web browser or a mobile application. Users can also use smart devices to communicate with legal experts in a virtual environment in real time.

[1974] User Registration and Login

[1975] Users create an account through a terminal and enter the necessary information. Existing users can access the system by logging in.

[1976] Enter a summary of the problem

[1977] The user enters detailed information about the problem through a terminal. The form includes items such as the type of problem, the date and time of the problem, the people involved, and specific details of the problem.

[1978] Receiving solutions and feedback

[1979] The user receives and views the solutions provided by the server through the terminal, and also inputs feedback on the results of using the proposed solutions and legal support.

[1980] Specific examples

[1981] Example 1: Labor-related issues

[1982] The user wishes to seek advice regarding unfair dismissal under a labor contract. Using the terminal, the user enters the following information:

[1983] Type of problem: Labor issues

[1984] Date of occurrence: August 15, 2023

[1985] Parties involved: Employee (user), Employer (company)

[1986] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[1987] The server receives this information, analyzes it, and makes the following suggestions:

[1988] Checklist for legality of dismissal under the Labor Standards Act

[1989] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[1990] Introduction to law firms that specialize in labor issues

[1991] The user acts on the presented solution and reports the results to the system as feedback.

[1992] Example 2: Consultation regarding contract disputes

[1993] The user wishes to consult about a problem regarding the renewal of a rental contract. The user enters the following information through the terminal:

[1994] Type of problem: Contract problem

[1995] Date of occurrence: September 10, 2023

[1996] Parties involved: Tenant (user), landlord (landlord)

[1997] Detailed background: The landlord added unfair conditions when renewing the contract.

[1998] The server receives this information, analyzes it, and makes the following suggestions:

[1999] Procedures for verifying the legality of renewal conditions in lease agreements

[2000] Local government rental housing trouble consultation desk

[2001] Introducing a law firm that specializes in real estate issues

[2002] The user takes specific action based on the presented solution and reports the results to the system as feedback.

[2003] Example prompts for generative AI models

[2004] "Unfair terms were presented during the contract renewal. Type of problem: Contract dispute, Date of occurrence: September 10, 2023, Parties involved: Tenant and Landlord."

[2005] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2006] Step 1:

[2007] The user creates an account using a terminal and enters the necessary information. The input for this step is the user's personal information and login information. The output is that the user account has been created and is ready to log in.

[2008] Step 2:

[2009] The user inputs detailed information about the problem through the terminal. Specifically, the type of problem, the date and time of occurrence, the people involved, and the specific details. The input of this step is detailed information about the problem, and the output is that this information is sent to the server.

[2010] Step 3:

[2011] The server analyzes the received problem summary data using natural language processing (NLP) technology. The input for this step is the problem summary data sent by the user, and the output is a set of analyzed topics and keywords. Specific operations include morphological analysis, topic modeling, and similar case search.

[2012] Step 4:

[2013] The server generates optimal solutions based on the analysis results. It searches the database for appropriate laws and cases based on the analyzed topics and keywords, and generates legal advice and appropriate procedural methods. The input for this step is the analysis results and related information in the database, and the output is the generated solution.

[2014] Step 5:

[2015] The generated solution and corresponding legal authority information are provided to the user. The server sends the generated solution to the terminal, where the user can view it. The input of this step is the generated solution, and the output is a display of the solution that can be viewed by the user.

[2016] Step 6:

[2017] The server enables real-time communication with a legal expert in a virtual environment using a smart device. The user then uses the smart device to video chat with the legal expert for further consultation. The input of this step is the user's communication request, and the output is the initiation of a real-time video chat session with the legal expert.

[2018] Step 7:

[2019] The user inputs the results of using the provided solutions and legal support as feedback. The feedback is sent to the server and stored in the database. The input of this step is the user's feedback, and the output is the accumulation of feedback in the database.

[2020] Step 8:

[2021] The server uses the collected feedback to refine the system's analytical model and database. The input for this step is the feedback data, and the output is an improved analytical model and a refined database. Specific operations include retraining the model using machine learning algorithms.

[2022] 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.

[2023] System Overview

[2024] This invention is a comprehensive system for quickly and efficiently providing appropriate solutions to legal disputes, and in particular, it incorporates an emotion engine that recognizes the user's emotional state and reflects it in the solution. This system mainly operates in cooperation with a server, terminals, and users.

[2025] Server-side behavior

[2026] The server collects reliable data from law firms and courts and stores it in a database. It also receives summary data of the problem entered by the user and analyzes it using natural language processing and an emotion engine. Based on the analysis results, it generates an appropriate solution and provides it to the user. It also collects feedback from users and reflects it in improving the system.

[2027] Data collection and storage

[2028] The server periodically collects the latest information from law firms and courts through web scraping, APIs, and manual entry, and the collected data is organized and stored in a database.

[2029] Analysis of trouble summary data

[2030] The server analyzes the trouble summary data received from the user using natural language processing (NLP) technology and an emotion engine. It uses an NLP model (e.g., BERT or GPT) to classify the input data, extract important keywords, and understand the details of the trouble. At the same time, it uses the emotion engine to analyze the user's emotional state from the input.

[2031] Solution generation and delivery

[2032] Based on the analysis results, the server generates an optimal solution, including legal advice and appropriate procedural instructions. The solution presentation is tailored to the user's emotional state. If necessary, information on relevant law firms or local government consultation services is also provided.

[2033] Feedback collection and optimization

[2034] The server receives feedback from users after they use the solutions and consultation services provided. This feedback is stored in a database and used to improve the accuracy of the system's analytical model and emotion engine, allowing the system to be continuously optimized.

[2035] Operation on the terminal side

[2036] The terminal provides the interface through which users access the system. The terminal is used by users to create an account, enter a problem description, and receive a solution from the system. This can be a web browser or a mobile application.

[2037] User Registration and Login

[2038] Users create an account through a terminal and enter the necessary information. Existing users can access the system by logging in.

[2039] Enter a summary of the problem

[2040] The user uses a terminal to enter detailed information about the problem. The form includes items such as the type of problem, the date and time of the problem, the people involved, and specific details. The data entered by the user is sent to the server.

[2041] Receiving solutions and feedback

[2042] The user can view the solutions provided by the server through their device and take action if necessary. They can contact the suggested law firms or counseling centers. They can also input feedback on the solutions provided and the results of using legal support.

[2043] Specific examples

[2044] Example 1: Labor-related issues

[2045] The user wishes to seek advice regarding unfair dismissal under a labor contract. Using the terminal, the user enters the following information:

[2046] Type of problem: Labor issues

[2047] Date of occurrence: August 15, 2023

[2048] Parties involved: Employee (user), Employer (company)

[2049] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[2050] As you type, the emotion engine recognizes your emotions, such as anger or anxiety.

[2051] The server receives this information, analyzes it, and makes the following suggestions:

[2052] Checklist for legality of dismissal under the Labor Standards Act

[2053] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[2054] Introduction to law firms that specialize in labor issues

[2055] In response to any concerns users may have, the message is presented in a reassuring manner, such as "verifying legality should be given priority."

[2056] The user acts on the presented solution and reports the results to the system as feedback.

[2057] Example 2: Consultation regarding contract disputes

[2058] The user wishes to consult about a problem regarding the renewal of a rental contract. The user enters the following information through the terminal:

[2059] Type of problem: Contract problem

[2060] Date of occurrence: September 10, 2023

[2061] Parties involved: Tenant (user), landlord (landlord)

[2062] Detailed background: The landlord added unfair conditions when renewing the contract.

[2063] Upon input, the emotion engine recognizes the user's confused emotion.

[2064] The server receives this information, analyzes it, and makes the following suggestions:

[2065] Procedures for verifying the legality of renewal conditions in lease agreements

[2066] Local government rental housing trouble consultation desk

[2067] Introducing a law firm that specializes in real estate issues

[2068] To reduce user confusion, encouraging statements such as "Follow the detailed verification steps and the problem will be resolved" are presented.

[2069] The user takes specific action based on the presented solution and reports the results to the system as feedback.

[2070] In this way, by combining emotion engines, it becomes possible to provide solutions that take into account the user's emotional state, thereby providing effective support for legal disputes.

[2071] The processing flow will be explained below.

[2072] Step 1:

[2073] The server collects reliable data from law firms and courts. It uses web scraping and APIs to obtain the latest laws, precedents, contracts, etc., and stores them in a database. Additionally, it uses OCR technology to digitize manually collected materials as needed and registers them in the database.

[2074] Step 2:

[2075] Users access the system using a terminal and create an account or log in. New users create an account by entering personal information such as their name, email address, and password. Existing users log in by entering their email address and password.

[2076] Step 3:

[2077] The user uses the terminal to enter an outline of the problem. The input form includes items such as the type of problem, the date and time of occurrence, the people involved, and specific details. The user enters this information in detail and presses the send button.

[2078] Step 4:

[2079] The server receives the summary data of the problem sent by the user and stores it in a temporary database. At this point, a simple error check is performed to ensure that there are no problems with the format or content of the input data.

[2080] Step 5:

[2081] The server analyzes the received summary data of the trouble using natural language processing (NLP) technology and an emotion engine. It uses an NLP model (e.g., BERT or GPT) to classify the input data, extract important keywords, and understand the content of the trouble. At the same time, it uses the emotion engine to analyze the emotional state from the user's input.

[2082] Step 6:

[2083] The server uses the analysis results to search for similar cases and related laws and regulations in its database. Based on the search results, it generates the optimal solution and determines its content. The solution includes legal advice and appropriate procedural methods.

[2084] Step 7:

[2085] The server adjusts the content of the solution presented to the user depending on the user's emotional state. For example, if the user is feeling strong emotions such as anxiety or anger, the server changes the presented solution to be more reassuring.

[2086] Step 8:

[2087] The server provides the generated solution to the user, and also lists and displays to the user information on law firms and details of local government consultation centers related to the solution.

[2088] Step 9:

[2089] The user can view the solutions provided by the server through their device and take action if necessary, including contacting the suggested law firm or counseling center.

[2090] Step 10:

[2091] Users enter their feedback on the solutions provided and the results of using the support service in a feedback form, including their evaluation of the effectiveness of the solutions and the quality of the support.

[2092] Step 11:

[2093] The server receives feedback from users and stores it in a database. The collected feedback is used to improve the accuracy of the system's analytical model and emotion engine, allowing the system to be continuously optimized.

[2094] Specific examples

[2095] Example 1: Labor-related issues

[2096] The user wishes to seek advice regarding unfair dismissal under a labor contract. Using the terminal, the user enters the following information:

[2097] Type of problem: Labor issues

[2098] Date of occurrence: August 15, 2023

[2099] Parties involved: Employee (user), Employer (company)

[2100] Details of the situation: I was suddenly notified by my company that I was being fired, and I don't understand the reason.

[2101] As you type, the emotion engine recognizes your emotions, such as anger or anxiety.

[2102] The server receives this information, analyzes it, and makes the following suggestions:

[2103] Checklist for legality of dismissal under the Labor Standards Act

[2104] Consultation desks at the Labor Bureau and Labor Standards Inspection Office

[2105] Introduction to law firms that specialize in labor issues

[2106] In response to any concerns users may have, the message is presented in a reassuring manner, such as "verifying legality should be given priority."

[2107] The user acts on the presented solution and reports the results to the system as feedback.

[2108] Example 2: Consultation regarding contract disputes

[2109] The user wishes to consult about a problem regarding the renewal of a rental contract. The user enters the following information through the terminal:

[2110] Type of problem: Contract problem

[2111] Date of occurrence: September 10, 2023

[2112] Parties involved: Tenant (user), landlord (landlord)

[2113] Detailed background: The landlord added unfair conditions when renewing the contract.

[2114] Upon input, the emotion engine recognizes the user's confused emotion.

[2115] The server receives this information, analyzes it, and makes the following suggestions:

[2116] Procedures for verifying the legality of renewal conditions in lease agreements

[2117] Local government rental housing trouble consultation desk

[2118] Introducing a law firm that specializes in real estate issues

[2119] To reduce user confusion, encouraging statements such as "Follow the detailed verification steps and the problem will be resolved" are presented.

[2120] The user takes specific action based on the presented solution and reports the results to the system as feedback.

[2121] In this way, by combining emotion engines, it becomes possible to provide solutions that take into account the user's emotional state, thereby providing effective support for legal disputes.

[2122] Example 2

[2123] 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."

[2124] Conventional legal systems only provide solutions to legal disputes without taking into account the user's emotional state. This can lead to problems such as users finding it difficult to understand the solutions or lacking motivation to take appropriate action. Furthermore, they lack the ability to collect feedback and optimize the system to improve the effectiveness of the solutions provided.

[2125] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2126] In this invention, the server includes means for collecting legal-related data and storing it in a database, means for receiving summary data of the problem entered by the user, means for analyzing the received summary data using natural language processing and generating an appropriate solution, means for adjusting the way the solution is presented using an emotion engine that analyzes the user's emotional state, means for providing the user with the generated solution and information on the corresponding legal agency, and means for receiving user feedback and optimizing the system. This makes it possible to provide solutions that take the user's emotional state into consideration, thereby realizing more effective support for legal troubles.

[2127] "Legal data" refers to information such as laws, precedents, cases, and legal consultation results collected from law firms and courts.

[2128] A "database" is an information system that organizes and stores collected legal-related data, allowing it to be efficiently searched and accessed when needed.

[2129] "User" means an individual or organization that uses the system to seek legal advice.

[2130] "Summary data of the trouble" is detailed information entered by the user, such as the type of trouble, the date and time of occurrence, the people involved, and the specific details of the trouble.

[2131] "Natural language processing" is a technology that analyzes and processes text data entered by the user to understand and generate human language.

[2132] "Solutions" are specific advice or suggestions generated to solve a problem based on trouble data analyzed using natural language processing.

[2133] An "emotion engine" is a technology that analyzes a user's emotional state and adjusts the way solutions are presented to take those emotions into consideration.

[2134] "Feedback" refers to the user's opinions and evaluations of the solutions provided or the results of using the consultation service.

[2135] "System optimization" is the process of continuously improving the overall performance and accuracy of the system based on collected feedback.

[2136] "Legal institutions" are organizations that provide legal support, such as law firms, courts, and local government helplines.

[2137] A "natural language processing model" is a machine learning model, such as BERT or GPT, that is used to understand and analyze user input text and generate appropriate solutions.

[2138] "Solution presentation method" is a means of adjusting the content and presentation of the solution depending on the user's emotional state.

[2139] "Information provision" is the process of communicating generated solutions and relevant legal information to users.

[2140] MODE FOR CARRYING OUT THE INVENTION

[2141] System Overview

[2142] This invention is a system for quickly and efficiently providing appropriate solutions to legal problems, and in particular, it combines an emotion engine that recognizes the user's emotional state and reflects it in the solution. This system mainly operates in cooperation with a server, terminals, and users.

[2143] System configuration

[2144] The server collects reliable data from law firms and courts and stores it in a database. It also receives summary data of the problem entered by the user and analyzes it using natural language processing and an emotion engine. Based on the analysis results, it generates an appropriate solution and provides it to the user. It also collects feedback from users and reflects it in improving the system. Specifically, the following hardware and software are used:

[2145] Hardware: Servers, client devices (PCs, smartphones, tablets)

[2146] Software: Natural language processing models (BERT, GPT), sentiment engine, database management system, web server

[2147] Server-side behavior

[2148] 1. Data collection and storage:

[2149] The server periodically collects the latest legal information using web scraping, APIs, and manual input.

[2150] The collected data is organized and stored in a database.

[2151] 2. Analysis of Trouble Summary Data:

[2152] The server analyzes the summary data of the problem received from the user using natural language processing (NLP) techniques such as BERT and GPT.

[2153] Through analysis, the input data is classified, important keywords are extracted, and the nature of the problem is understood.

[2154] At the same time, an emotion engine is used to analyze the emotional state from the user's input.

[2155] 3. Solution generation and delivery:

[2156] Based on the analysis, the server generates an optimal solution, which may include legal advice and proper procedural instructions.

[2157] The system adjusts the way solutions are presented depending on the user's emotional state, and also provides information on relevant law firms and local government consultation services.

[2158] 4. Feedback collection and optimization:

[2159] The server receives feedback from the user after the user has used the provided solutions and helplines.

[2160] The feedback is stored in a database and used to improve the accuracy of the system's analytical models and emotion engine.

[2161] Operation on the terminal side

[2162] 1. User Registration and Login:

[2163] Users create an account through a terminal and enter the necessary information. Existing users can access the system by logging in.

[2164] 2. Enter a summary of the problem:

[2165] The user uses a terminal to input detailed information about the problem. The input format includes text boxes where the user can enter the type of problem, the date and time of occurrence, the people involved, and detailed information about the problem.

[2166] The user's input data is sent to the server.

[2167] 3. Receiving solutions and feedback:

[2168] The user can view the solutions provided by the server through the terminal and take action as necessary.

[2169] Provide feedback on the solutions provided and the results of using legal support.

[2170] Specific examples

[2171] Example 1: Labor-related issues

[2172] When a user wishes t...

Claims

1. A means for collecting and storing legal data in a database; means for receiving user-entered trouble summary data; a means for analyzing the received summary data using natural language processing to generate an appropriate solution; a means of providing the user with information on the generated solution and the corresponding legal authority; a means of receiving user feedback and optimizing the system; A system including:

2. 10. The system of claim 1, further comprising means for analyzing input data utilizing a natural language processing model.

3. 10. The system of claim 1, including means for automatically collecting law firm and court data on a periodic basis.

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