system

Abstract

Provide a system. [Solution] a terminal for a user to input legal questions or issues; a server that receives input from the terminal; means for analyzing the input using natural language processing; A means to search the complete collection of laws and past case law databases, means for generating a legal response based on the search results; means for transmitting the generated answer to the terminal.

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, individuals and corporations had to consult directly with a law firm to resolve legal issues quickly and at low cost, which was time-consuming and costly. Furthermore, because legal expertise was required, it was difficult for ordinary people to find appropriate solutions on their own. There is a need to provide a system that can solve these issues and enable individuals and corporations to more easily resolve legal issues. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system including a terminal for a user to input a legal question or problem, a server that receives the input from the terminal, means for analyzing the input using natural language processing, means for searching the Six Codes and a database of past case law, means for generating a legal answer based on the search results, and means for transmitting the generated answer to the terminal, thereby enabling users to receive appropriate legal advice quickly and at low cost, even if they do not have specialized legal knowledge.

[0006] A "terminal" is a device through which a user enters legal questions or issues and receives information, and specifically includes a computer, smartphone, tablet, etc.

[0007] A "server" is a central processing unit that receives input from terminals, analyzes data, searches, generates and transmits answers.

[0008] "Natural language processing" is a technology for analyzing natural human language and understanding its meaning, and includes keyword extraction, context analysis, and syntactic analysis.

[0009] The "Roppo Zensho" is a book containing the six basic codes of Japanese law (Constitution, Civil Code, Criminal Code, Commercial Code, Code of Civil Procedure, and Code of Criminal Procedure), and is used for legal interpretation and application.

[0010] A "past case database" is a database that compiles past judgments and opinions issued by courts and is used as reference material for legal decisions.

[0011] "Searching" is the process of locating and extracting specific information from a designated database.

[0012] "Answer generation" is the process of creating a specific answer to a user's question or problem based on search results and analysis results.

[0013] "Transmission" is the process of delivering generated information or data from a source (server) to a recipient (terminal) via telecommunications equipment. [Brief explanation of the drawings]

[0014] [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

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] The present invention provides a system including a terminal for a user to input a legal question or problem, a server that receives input from the terminal, means for analyzing the input using natural language processing, means for searching the Six Codes and a database of past case law, means for generating a legal answer based on the search results, and means for transmitting the generated answer to the terminal.

[0036] System configuration

[0037] 1. Terminal

[0038] A device that allows users to enter legal questions or issues and receive answers.

[0039] Specifically, this includes computers, smartphones, tablets, etc.

[0040] 2. Server

[0041] It acts as a central processing unit, receiving input from the terminals, analyzing the data, searching, generating and sending answers.

[0042] 3. Natural Language Processing (NLP) Module

[0043] It uses technology to analyze input text data and understand its meaning.

[0044] This includes processes such as keyword extraction, contextual analysis, and syntax analysis.

[0045] 4. Legal Information Database

[0046] This is a database that includes the complete collection of laws and past court cases.

[0047] The server searches this database to obtain the appropriate legal information.

[0048] 5. Answer Generation Module

[0049] Based on the search results, legal answers to the user's questions are generated.

[0050] 6. Means of communication

[0051] Provides a means for sending and receiving data between the server and the terminal.

[0052] Specifically, HTTP requests and responses are used.

[0053] Program processing

[0054] Example: From user input to answer generation

[0055] 1. User Input

[0056] The user uses the terminal to enter a specific legal question.

[0057] For example: "What should I do if I get fired and I didn't sign a contract?"

[0058] 2. Sending a request from the device to the server

[0059] The terminal that receives the user's input sends an API request to the server.

[0060] Example: Send an HTTP POST request containing the user's question.

[0061] 3. Data reception and analysis on the server

[0062] The server parses the received request and extracts the user's input text.

[0063] The NLP module analyzes the text and understands keywords and context.

[0064] For example, extract keywords such as "contract," "signature," and "dismissal."

[0065] 4. Legal Information Search

[0066] The server searches the complete collection of laws and a database of past legal precedents.

[0067] Use search algorithms to extract relevant legal information.

[0068] For example, obtain Article 15 of the Labor Contract Act and past legal precedents (Heisei XX year XX judgment).

[0069] 5. Answer Generation

[0070] Based on the search results, the answer generation module constructs an answer.

[0071] The server generates a response containing specific legal advice.

[0072] Example: "Even if you have not signed a contract, a labor contract may still be in place. You may be able to sue for unfair dismissal under Article 15 of the Labor Contract Act."

[0073] 6. Sending a response from the server to the device

[0074] The server generates a response and returns it to the terminal.

[0075] Example: Sending an HTTP response containing the generated answer to the terminal.

[0076] 7. Displaying answers on your device

[0077] The terminal displays the received response to the user.

[0078] The user will refer to the displayed answer to decide on the next action.

[0079] Example: Specific legal advice and relevant legal information displayed on screen.

[0080] In this way, the system of the present invention allows users to receive appropriate legal advice quickly and at low cost, even if they do not have specialized legal knowledge.

[0081] The processing flow will be explained below.

[0082] Step 1:

[0083] A user enters a legal question or issue.

[0084] For example, a user might use a terminal to type, "What should I do if I am fired but haven't signed a contract?"

[0085] Step 2:

[0086] The device generates an API request to send the user's input to the server.

[0087] For example, the device sends the following HTTP POST request to the server:

[0088] json

[0089] {

[0090] "question": "What should I do if I get fired without signing a contract?"

[0091] }

[0092] Step 3:

[0093] The server parses the received request and extracts the entered text.

[0094] It uses a natural language processing (NLP) module to analyze the meaning of the input text and identify relevant keywords and context.

[0095] Step 4:

[0096] The server searches the complete collection of laws and past case law databases based on the extracted keywords.

[0097] For example, extract information about "Article 15 of the Labor Contract Act" and "Past precedents (Heisei XX year XX judgment)."

[0098] Step 5:

[0099] Based on the data acquired by the server, an AI algorithm is used to generate specific answers to the user's questions.

[0100] For example, it will generate an answer like this:

[0101] Even if a written contract has not been signed, a labor contract may be deemed to have been established through an oral agreement or the actual performance of work. Pursuant to Article 15 of the Labor Contract Act, it is possible to sue for unfair dismissal. Furthermore, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei).

[0102] Step 6:

[0103] The server generates an API response to return the generated answer to the device.

[0104] For example, send the following HTTP response to the device:

[0105] json

[0106] {

[0107] "answer": "Even if you have not signed a contract, a labor contract may be deemed to have been established by an oral agreement or the actual performance of work. Under Article 15 of the Labor Contract Act, you can file a lawsuit for unfair dismissal. In addition, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei)."

[0108] }

[0109] Step 7:

[0110] The terminal analyzes the response received from the server and displays it in a format that is easy for the user to understand.

[0111] For example, display the answer on the terminal screen in the following format:

[0112] answer:

[0113] Even if a contract has not been signed, a labor contract may be deemed to have been established through an oral agreement or the actual performance of work. Under Article 15 of the Labor Contract Act, it is possible to sue for unfair dismissal. There have also been cases in the past where employees have won lawsuits (such as the XX judgment in 2015).

[0114] Step 8:

[0115] The user decides on the next action based on the displayed answer.

[0116] For example, you can choose to consult the Labor Standards Inspection Office or contact a lawyer.

[0117] Example 1

[0118] 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."

[0119] Legal problems and questions require specialized knowledge, making it difficult for many people to obtain appropriate legal advice quickly and at low cost. Understanding the complex legal context and extracting appropriate information from past precedents and legal documents requires specialized skills and time. Therefore, there is a need for a legal advice system that is easily accessible to ordinary users.

[0120] 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.

[0121] In this invention, the server includes an information terminal for a user to input a legal question or problem, a processing device for receiving the input from the information terminal, means for analyzing the input using natural language processing, means for searching a database of legal documents and past precedents, means for generating a legal answer based on the search results, means for transmitting the generated answer to the information terminal, and means for displaying the answer received by the information terminal to the user, thereby enabling users to receive appropriate legal advice quickly and at low cost even without specialized knowledge.

[0122] "User" refers to a person who enters a legal question or issue into the system.

[0123] An "information terminal" is a device through which a user can input legal questions or issues and receive answers, and specifically includes computers, smartphones, tablets, etc.

[0124] "Processor" refers to a central processing unit that receives input from an information terminal, analyzes, searches, generates and transmits a response.

[0125] "Natural language processing" refers to the technology that enables computers to understand, interpret, and generate human language (natural language), and includes text analysis, keyword extraction, context understanding, etc.

[0126] "Legal Document" means any official document, including any law, rule, regulation, or decree.

[0127] A "past case database" refers to a database that records previous court decisions and legal interpretations.

[0128] "Search tools" refers to techniques and methods for searching for relevant information in legal documents and databases of past cases.

[0129] "Answer generation means" refers to a technique or method for generating legal answers to users' questions based on search results.

[0130] "Transmission means" refers to the technology or method for transmitting the response generated by the server to the information terminal.

[0131] "Display means" refers to a technique or method for visually presenting the answer received by the information terminal to the user.

[0132] This invention relates to a system that allows users to input legal questions or problems and receive prompt and accurate legal advice. The system includes an information terminal, a processing device, natural language processing, a database of legal documents and past cases, search means, answer generation means, transmission means, and display means.

[0133] First, the information terminals used by users are devices such as computers, smartphones, tablets, etc. Users use these terminals to input legal questions and issues.

[0134] The input question or problem is then sent from the information terminal to the processing device. This is done using a communication method such as an HTTP POST request. The processing device receives the input from the information terminal and analyzes the text data using natural language processing. Specific natural language processing technologies used include NLP libraries such as spaCy and NLTK. This allows for keyword extraction and contextual analysis of the input text.

[0135] For example, if a user enters "What should I do if I am fired without signing a contract?", keywords such as "contract," "signature," and "fire" will be extracted from this text.

[0136] The processing device searches a database of legal documents and past legal precedents based on the extracted keywords. SQL queries and specific search algorithms are used as search methods. For example, Article 15 of the Labor Contract Act and past legal precedents (decision in XX year of Heisei) can be retrieved from the database.

[0137] Next, based on the search results, the answer generator generates a legal answer. This uses a generative AI model (e.g., GPT-3 (registered trademark) or BERT). The generated answer includes specific legal advice. For example, "Even if you have not signed a contract, a labor contract may have been established. You can sue for wrongful dismissal under Article 15 of the Labor Contract Act."

[0138] The generated legal advice is sent to the information terminal as a response. HTTP responses or similar methods are again used as the means of communication. The terminal renders the received response on the screen to display it to the user. This allows the user to decide on their next course of action based on the displayed legal advice.

[0139] As a concrete example, the following prompt sentences can be used to input the generative AI model in the system:

[0140] Prompt: I have a question about employment contracts. "What should I do if I get fired even though I didn't sign a contract?"

[0141] In this way, users can receive appropriate legal advice quickly and at low cost, even if they do not have specialized legal knowledge.This system offers a new way to solve legal problems by making full use of computer technology and natural language processing techniques.

[0142] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0143] Step 1: The user enters a legal question or issue into an information terminal.

[0144] Input: A user uses an information device (computer, smartphone, tablet, etc.) to input text via a keyboard or touchscreen.

[0145] What happens: User types, "What should I do if I get fired and I didn't sign a contract?"

[0146] Output: The input text data.

[0147] Step 2: The terminal transmits the input question to the processing device.

[0148] Input: Text data entered by the user.

[0149] Specific operation: The device packs the entered text data into an HTTP POST request and sends it to the specified API endpoint.

[0150] Output: The HTTP POST request sent to the server.

[0151] Step 3: The server parses the received request and extracts the text data.

[0152] Input: HTTP POST request from the terminal.

[0153] What happens: The server parses the request and extracts the text data.

[0154] Output: The extracted text data.

[0155] Step 4: The server's natural language processing module analyzes the text data and extracts keywords and context.

[0156] Input: Extracted text data.

[0157] Specific behavior: Using an NLP library (e.g., spaCy or NLTK), extract keywords from the text and perform contextual analysis. For example, extract keywords such as "contract," "signature," and "dismissal."

[0158] Output: Extracted keywords and context information.

[0159] Step 5: The server searches legal documents and case law databases to retrieve relevant legal information.

[0160] Input: Extracted keywords and context information.

[0161] What it does: Searches a database based on keywords using SQL queries or specific search algorithms.

[0162] Output: Retrieved legal information (e.g. Article 15 of the Labor Contract Act and past court decisions).

[0163] Step 6: The server's answer generation module generates a legal answer based on the search results.

[0164] Input: The legal information searched.

[0165] Specific operation: Using a generative AI model (e.g., GPT-3 or BERT), generate a legal response. For example, "Even if you have not signed a contract, a labor contract may have been established. You can sue for wrongful dismissal under Article 15 of the Labor Contract Act."

[0166] Output: The generated legal answer.

[0167] Step 7: The server sends the generated response to the terminal.

[0168] Input: The generated legal answer.

[0169] Specific operation: The generated answer is packed in JSON format and sent to the terminal as an HTTP response.

[0170] Output: The HTTP response sent to the device.

[0171] Step 8: The terminal displays the received answer to the user.

[0172] Input: The HTTP response sent to the device.

[0173] Specific behavior: Render the answer text on the screen and display it to the user. For example, display the following on the user's screen: "Even if you have not signed the contract, a labor contract may have been established. You may be able to sue for wrongful dismissal under Article 15 of the Labor Contract Act."

[0174] Output: The legal answer displayed to the user.

[0175] (Application example 1)

[0176] 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."

[0177] In recent years, there has been a demand for systems that provide legal advice to quickly and accurately resolve legal issues. However, conventional systems have had the problem that it is difficult for users without specialized knowledge to obtain appropriate answers to legal questions and issues. Furthermore, it is still not possible to provide instant legal advice using smart devices.

[0178] 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.

[0179] In this invention, the server includes a terminal for a user to input a legal question or problem, means for receiving input from the terminal, means for analyzing the input using natural language processing, means for searching the Six Codes and a database of past case law, means for generating a legal answer based on the search results, means for transmitting the generated answer to the terminal, and a smart device that executes a program for providing legal advice, thereby enabling users to receive fast and accurate legal advice without having specialized knowledge.

[0180] A "terminal" is a device through which a user can enter legal questions or issues and receive answers.

[0181] A "server" is a device that acts as a central processing unit, receives input from terminals, analyzes data, searches, generates and transmits answers.

[0182] "Natural language processing" is a technology for analyzing text data entered by a user, understanding its content, and extracting keywords and context.

[0183] The "Roppo Zensho" is a book or database that compiles major laws and their explanations, such as Japan's Civil Code, Criminal Code, Commercial Code, and Constitution.

[0184] A "case law database" is a database that contains past court cases and their detailed information, stored in a searchable format.

[0185] A "means for generating legal answers" is a means for generating legal advice or information in response to a user's question based on natural language processing and database search results.

[0186] "Communication means" refers to the infrastructure and protocols for sending and receiving data between a server and a terminal, specifically using HTTP requests and responses.

[0187] A "smart device running a program for providing legal advice" is a mobile device on which an application is installed that generates appropriate answers to legal questions and provides the results to the user.

[0188] The present invention is a system that combines a terminal where users can input legal questions or problems and a server that receives the input, analyzes, searches, and generates answers. The system of the present invention is installed on a smart device and can provide instant legal advice. Specifically, it consists of the following components:

[0189] 1. Terminal

[0190] A device that allows users to input legal questions or issues. The device can be a computer, smartphone, tablet, etc., and allows users to receive legal advice quickly.

[0191] 2. Server

[0192] It functions as a central processing unit and receives input from terminals. The server is the main component for data analysis, search, and answer generation. It analyzes the input information using a natural language processing (NLP) module and searches the Roppo Zensho and past case law databases.

[0193] 3. Natural Language Processing (NLP) Module

[0194] It uses techniques to analyze input text data and understand its meaning. NLP can be performed using software such as SpaCy or NLTK. This module includes processes such as keyword extraction, contextual analysis, and syntax analysis.

[0195] 4. Legal Information Database

[0196] This is a database that includes the complete collection of laws and past legal precedents. The server searches this database to obtain the appropriate legal information. Search engines such as ElasticSearch (registered trademark) and Solr are used to search the database.

[0197] 5. Answer Generation Module

[0198] The search results are used to generate legal answers to users' questions, leveraging generative AI models (e.g., GPT-4®) to provide specific legal advice.

[0199] 6. Means of communication

[0200] It provides a means of sending and receiving data between a server and a device, specifically using HTTP requests and responses, allowing users to receive instant legal advice on their device.

[0201] Specific implementation examples of the program

[0202] Hardware / Software Used

[0203] Device: A device such as a smartphone, tablet, or computer where a user enters a question.

[0204] Server: The central processing unit that analyzes data and generates answers.

[0205] Natural Language Processing module: Uses SpaCy and NLTK to analyze the meaning of text data.

[0206] Legal information database: Complete collection of laws and past case law database.

[0207] Communication method: HTTP request and response.

[0208] Implementation example

[0209] A user opens an app on their smartphone and enters a question like this:

[0210] Example: "What should I pay attention to when buying real estate?"

[0211] 1. Receiving input: The smartphone app receives the user's question and generates an API request to send to the server (HTTP POST request).

[0212] 2. Data analysis: The server analyzes the received request and uses the NLP module to analyze the text, thereby extracting keywords and context.

[0213] 3. Database search: Based on the extracted keywords, the legal information database is searched to obtain relevant legal information.

[0214] 4. Answer generation: Based on the information obtained, a generative AI model (e.g., GPT-4) generates specific legal advice.

[0215] 5. Sending results: The generated answer is sent from the server to the device and displayed on the user's smartphone.

[0216] Prompt Sentence Examples

[0217] Prompt statement:

[0218] A user has asked a legal question: "What should I be careful of when purchasing real estate?" Please generate specific legal advice for this question based on the Six Codes and past legal precedents.

[0219] In this way, the system of the present invention allows users to receive appropriate legal advice quickly and at low cost, even if they do not have specialized legal knowledge.

[0220] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0221] Step 1:

[0222] The user enters a legal question or problem using a device. The user opens the application screen on their smartphone or tablet and enters the question in a text box. For example, they enter a question such as, "What should I pay attention to when purchasing real estate?" The input data is sent in text format from the device to the server.

[0223] Step 2:

[0224] The device sends the entered legal question to the server. The device generates an HTTP POST request and sends the request data, including the user's question, to the server. The request data format is typically JSON.

[0225] Step 3:

[0226] The server analyzes the received request. The server receives a POST request and extracts the user's input text from the request body. This extracted text data is sent to the Natural Language Processing (NLP) module.

[0227] Step 4:

[0228] The server's natural language processing (NLP) module analyzes the received input text. The NLP module uses tools such as SpaCy or NLTK to analyze and extract keywords and context from the text data. For example, it extracts keywords such as "real estate," "purchase," and "points to note." The results of this analysis are used as input for the next search step.

[0229] Step 5:

[0230] The server searches a legal information database based on the extracted keywords. The server uses a search engine such as Elasticsearch or Solr to retrieve relevant information from the Six Codes and past case law database. For example, it retrieves laws and past case law related to real estate purchases. The search results are sent to the answer generation module.

[0231] Step 6:

[0232] The server's answer generation module generates legal answers based on the search results. It uses a generative AI model (e.g., GPT-4) to construct specific legal advice for the user's question. For example, it generates an answer such as, "When purchasing real estate, we recommend that you carefully review the sales contract, register the property, and understand the mortgage terms." The generated answers are stored in JSON format.

[0233] Step 7:

[0234] The server sends the generated answer to the device. An HTTP response containing the generated legal advice is formed and sent to the device. The response data is formatted in JSON for easy user understanding.

[0235] Step 8:

[0236] The device displays the received response to the user. The received JSON format response data is analyzed and displayed on the application screen. The user can then check the legal advice on the device screen. For example, the following message may be displayed: "When purchasing real estate, it is recommended that you carefully review the sales contract, register the property, and understand the terms of the mortgage."

[0237] 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.

[0238] The present invention is a system that includes a terminal for a user to input a legal question or problem, a server that receives input from the terminal, means for analyzing the input using natural language processing, means for searching the Six Codes and a database of past case law, means for generating a legal answer based on the search results, and means for transmitting the generated answer to the terminal, and further combines it with an emotion engine that recognizes the user's emotions.

[0239] System configuration

[0240] 1. Terminal

[0241] A device that allows users to enter legal questions or issues and receive answers.

[0242] Specifically, this includes computers, smartphones, tablets, etc.

[0243] 2. Server

[0244] It acts as a central processing unit, receiving input from the terminals, analyzing the data, searching, generating and sending answers.

[0245] 3. Natural Language Processing (NLP) Module

[0246] It uses technology to analyze input text data and understand its meaning.

[0247] This includes processes such as keyword extraction, contextual analysis, and syntax analysis.

[0248] 4. Legal Information Database

[0249] This is a database that includes the complete collection of laws and past court cases.

[0250] The server searches this database to obtain the appropriate legal information.

[0251] 5. Emotion Engine

[0252] This module identifies the emotion contained in the user's input text.

[0253] It uses natural language processing technology to identify sentiment categories and tailor responses based on those sentiments.

[0254] 6. Answer Generation Module

[0255] Based on the search results and the output of the emotion engine, specific and emotionally sensitive answers to the user's questions are generated.

[0256] 7. Means of communication

[0257] Provides a means for sending and receiving data between the server and the terminal.

[0258] Specifically, HTTP requests and responses are used.

[0259] Program processing

[0260] Example: From user input to emotion recognition and answer generation

[0261] 1. User Input

[0262] The user uses the terminal to enter a specific legal question.

[0263] For example: "What should I do if I get fired and I didn't sign a contract?"

[0264] 2. Sending a request from the device to the server

[0265] The terminal that receives the user's input sends an API request to the server.

[0266] Example: Send an HTTP POST request containing the user's question.

[0267] 3. Data reception and analysis on the server

[0268] The server parses the received request and extracts the user's input text.

[0269] The NLP module analyzes the text and understands keywords and context.

[0270] For example, extract keywords such as "contract," "signature," and "dismissal."

[0271] 4. Emotion Recognition by Emotion Engine

[0272] The server uses an emotion engine to identify emotions contained in the user's input text.

[0273] Example: Detecting emotions such as "anxiety" or "anger" from user text.

[0274] 5. Legal Information Search

[0275] The server searches the complete collection of laws and a database of past legal precedents.

[0276] Use search algorithms to extract relevant legal information.

[0277] For example, obtain Article 15 of the Labor Contract Act and past legal precedents (Heisei XX year XX judgment).

[0278] 6. Answer Generation

[0279] Based on the search results and the output of the emotion engine, the answer generation module generates specific and emotion-sensitive answers.

[0280] Example: "Even if you haven't signed a contract, a labor contract may still be in place. Please don't worry. In cases like this, you can sue for unfair dismissal under Article 15 of the Labor Contract Act. In addition, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei)."

[0281] 7. Sending a response from the server to the device

[0282] The server generates an API response to return the generated answer to the terminal.

[0283] Example: Sending an HTTP response containing the generated answer to the terminal.

[0284] 8. Displaying answers on your device

[0285] The terminal analyzes the received response and displays it in a user-friendly format.

[0286] Example: Specific legal advice and relevant legal information displayed on the device screen, with a stable emotional expression.

[0287] 9. User Reference and Action Selection

[0288] The user decides on the next action based on the displayed answer.

[0289] Example: Choose whether to consult the Labor Standards Inspection Office or contact a lawyer.

[0290] In this way, the system of the present invention allows users to receive appropriate legal advice quickly and at low cost, even if they do not have specialized legal knowledge, and provides support that takes into consideration the user's feelings.

[0291] The processing flow will be explained below.

[0292] Step 1:

[0293] A user enters a legal question or issue.

[0294] For example, a user might use a terminal to type, "What should I do if I am fired but haven't signed a contract?"

[0295] Step 2:

[0296] The device generates an API request to send the user's input to the server.

[0297] For example, the device sends the following HTTP POST request to the server:

[0298] json

[0299] {

[0300] "question": "What should I do if I get fired without signing a contract?"

[0301] }

[0302] Step 3:

[0303] The server parses the received request and extracts the entered text.

[0304] It uses a natural language processing (NLP) module to analyze the meaning of the input text and identify relevant keywords and context.

[0305] For example, extract keywords such as "contract," "signature," and "dismissal."

[0306] Step 4:

[0307] The server uses an emotion engine to identify emotions contained in the user's input text.

[0308] Natural language processing technology is used to analyze emotions and identify emotion categories.

[0309] Example: Detecting emotions such as "anxiety" or "anger" from input text.

[0310] Step 5:

[0311] The server searches the complete collection of laws and a database of past legal precedents based on the extracted keywords and the identified emotions.

[0312] Using a search algorithm, relevant information such as "Article 15 of the Labor Contract Act" and "Past legal precedents (Heisei XX year XX judgment)" is extracted.

[0313] Step 6:

[0314] The server uses AI algorithms to generate answers to users' questions based on search results and sentiment data.

[0315] The generated responses include a tone and expression that takes into consideration the user's feelings.

[0316] Example: "Even if you haven't signed a contract, a labor contract may still be in place. Please don't worry. In cases like this, you can sue for unfair dismissal under Article 15 of the Labor Contract Act. In addition, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei)."

[0317] Step 7:

[0318] The server generates an API response to return the generated answer to the device.

[0319] Example: Send an HTTP response containing the generated answer to the terminal:

[0320] json

[0321] {

[0322] "answer": "Even if you haven't signed a contract, a labor contract may still be in place. Please don't worry. In such cases, you can file a lawsuit for unfair dismissal under Article 15 of the Labor Contract Act. In addition, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei)."

[0323] }

[0324] Step 8:

[0325] The terminal analyzes the response received from the server and displays it in a format that is easy for the user to understand.

[0326] Specific legal advice and relevant legal information are displayed on the device screen, along with a stable emotional response.

[0327] Example: "Even if you haven't signed a contract, a labor contract may still be in place. Please don't worry. In cases like this, you can sue for unfair dismissal under Article 15 of the Labor Contract Act. In addition, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei)."

[0328] Step 9:

[0329] The user decides on the next action based on the displayed answer.

[0330] For example, you can choose to consult the Labor Standards Inspection Office or contact a lawyer.

[0331] Example 2

[0332] 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."

[0333] While conventional legal question-answering systems can provide appropriate legal answers based on the user's input text, they often find it difficult to provide answers that take the user's emotions into consideration, which can lead to anxiety and stress. Furthermore, the accuracy of legal information searches and the specificity of answers are often insufficient, and these systems often fail to help users decide on their next course of action.

[0334] 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.

[0335] In this invention, the server includes emotion recognition means for identifying emotions contained in the user's input text, means for adjusting a response based on the emotions identified by the emotion recognition means, and means for searching the Six Codes and a database of past legal precedents, thereby making it possible to propose specific actions to address legal issues while taking the user's emotions into consideration.

[0336] A "terminal" is an information processing device such as a computer, smartphone, or tablet that a user uses to enter input and receive responses.

[0337] A "server" is a central processing unit that receives input from terminals, analyzes data, searches, generates and transmits answers.

[0338] "Natural language processing" is a technology that analyzes text data entered by a user and understands its meaning, and includes keyword extraction and context analysis.

[0339] The "Roppo Zensho and Past Case Law Database" is a database that stores legal information, including the Roppo Zensho and past case law.

[0340] "Emotion recognition means" is a technology that identifies the user's emotions contained in the input text and identifies emotion categories such as anxiety or anger.

[0341] The "means for adjusting an answer" is a technology for adjusting the content and expression of an answer that is generated based on the emotion identified by the emotion recognition means.

[0342] The "answer generation means" is a technology that creates specific and emotion-sensitive responses to user questions based on search results and emotion recognition results.

[0343] "Communication means" refers to the technology for sending and receiving data between the server and the terminal, specifically using HTTP requests and responses.

[0344] An "API request" is a data request sent from a terminal to a server, and is sent in a format that includes the user's input.

[0345] An "HTTP response" is a data response sent from a server to a terminal, and is sent in a format that includes a generated answer.

[0346] MODE FOR CARRYING OUT THE INVENTION

[0347] The present invention is a system that includes a terminal for a user to input a legal question or problem, a server that receives input from the terminal, means for analyzing the input using natural language processing, means for searching the Six Codes and a database of past case law, means for generating a legal answer based on the search results, and means for transmitting the generated answer to the terminal, and further combines it with an emotion engine that recognizes the user's emotions.

[0348] The configuration for implementing this is as follows.

[0349] 1. Terminal

[0350] A device that allows a user to enter legal questions or issues and receive answers, such as a computer, smartphone, or tablet.

[0351] 2. Server

[0352] It acts as a central processing unit, receiving input from the terminals, analyzing the data, searching, generating and sending answers.

[0353] 3. Natural Language Processing (NLP) Module

[0354] It uses technology to analyze input text data and understand its meaning, including processes such as keyword extraction, contextual analysis, and syntax analysis.

[0355] 4. Legal Information Database

[0356] This is a database containing the complete collection of laws and past legal precedents. The server searches this database to retrieve the appropriate legal information.

[0357] 5. Emotion Engine

[0358] This module identifies the sentiment contained in the user's input text, using natural language processing techniques to identify sentiment categories and tailor responses based on those sentiments.

[0359] 6. Answer Generation Module

[0360] Based on the search results and the output of the emotion engine, specific and emotionally sensitive answers to the user's questions are generated.

[0361] 7. Means of communication

[0362] It provides a means to send and receive data between the server and the terminal, specifically using HTTP requests and responses.

[0363] Specific examples

[0364] The user uses the device to input a legal question, such as "What should I do if I'm fired without signing a contract?" The device receives this input and sends an HTTP POST request to the server. The server analyzes the received request and uses an NLP module to analyze the text data. At the same time, an emotion engine detects emotions such as "anxiety" or "anger" from the user's input.

[0365] The server then searches the Six Codes and a database of past legal precedents to obtain relevant legal information. For example, it references Article 15 of the Labor Contract Act and past legal precedents (Heisei XX Year XX Judgment). Based on the search results and the output of the emotion engine, the answer generation module generates specific legal advice. The server sends the generated answer to the terminal as an HTTP response, and the terminal displays it to the user.

[0366] Prompt Sentence Examples

[0367] An example of a user-provided prompt is, "What should I do if I'm fired without signing a contract? Emotion: Anxiety." This prompt allows the generative AI model to provide specific, emotionally sensitive advice on a particular legal issue.

[0368] According to the above embodiment, users can obtain appropriate legal advice quickly and at low cost even if they do not have specialized legal knowledge, and can also receive support that takes into consideration the feelings of the users.

[0369] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0370] Program processing flow

[0371] Step 1: User enters legal question into terminal

[0372] The user enters a legal question or problem into the terminal.

[0373] Specific behavior:

[0374] A user types a question into an input field on a terminal, such as "What should I do if I am fired but have not signed a contract?"

[0375] input:

[0376] The text of the user's legal question.

[0377] output:

[0378] The entered question text.

[0379] Step 2: Sending a request from the device to the server

[0380] The terminal generates an HTTP POST request to send the user's question to the server.

[0381] Specific behavior:

[0382] The device converts the entered question text into JSON format and sends an HTTP POST request to the API endpoint.

[0383] input:

[0384] The text of the user's legal question.

[0385] output:

[0386] An HTTP POST request in JSON format.

[0387] Step 3: Receiving and analyzing data on the server

[0388] The server receives requests from the device, extracts text data, and passes the extracted text data to a natural language processing (NLP) module for analysis.

[0389] Specific behavior:

[0390] The server extracts the JSON payload from the HTTP request, and the NLP module extracts keywords such as "contract," "signature," and "dismissal."

[0391] input:

[0392] HTTP POST request.

[0393] output:

[0394] Extracted keywords and contextual information.

[0395] Step 4: Emotion Recognition with the Emotion Engine

[0396] The server passes the text analyzed by the NLP module to the emotion engine to identify the user's emotion.

[0397] Specific behavior:

[0398] The server uses an emotion engine to identify emotions such as "anxiety" or "anger."

[0399] input:

[0400] Text data analyzed by the NLP module.

[0401] output:

[0402] Identified emotional information (e.g., anxiety).

[0403] Step 5: Find legal information

[0404] The server searches the complete collection of laws and a database of past court cases to obtain relevant legal information.

[0405] Specific behavior:

[0406] The server executes a database query to search for legal provisions and precedents related to "contract" and "dismissal," and retrieves Article 15 of the Labor Contract Act and the XX judgment of Heisei XX year.

[0407] input:

[0408] Extracted keywords and contextual information.

[0409] output:

[0410] Legal information obtained (e.g., legal texts, case law).

[0411] Step 6: Generate an answer

[0412] The server uses the answer generation module to generate a specific answer for the user based on the acquired legal information and the results of the emotion engine.

[0413] Specific behavior:

[0414] The server generates a response such as, "Even if you haven't signed the contract, a labor contract may still be in place. Please don't worry. In such cases, you can sue for wrongful dismissal under Article 15 of the Labor Contract Act. In addition, there have been cases in the past where employees have won the case (such as the XX judgment in XX year of Heisei)."

[0415] input:

[0416] Legal information obtained, emotional information identified.

[0417] output:

[0418] The specific answer text generated.

[0419] Step 7: Sending the response from the server to the device

[0420] The server sends an HTTP response containing the generated answer to the terminal.

[0421] Specific behavior:

[0422] The server converts the generated answer into JSON format and sends it back to the device as an HTTP response.

[0423] input:

[0424] The generated answer text.

[0425] output:

[0426] The HTTP response in JSON format.

[0427] Step 8: View your answers on your device

[0428] The terminal analyzes the received response and displays it in a user-friendly format.

[0429] Specific behavior:

[0430] The terminal parses the JSON response and displays the following message: "Even if you have not signed the contract, an employment contract may still be in place. Please do not worry. In such cases, you can sue for wrongful dismissal under Article 15 of the Labor Contract Act. In addition, there have been past court cases (Heisei XX year XX judgment) in which employees have won the case."

[0431] input:

[0432] JSON response.

[0433] output:

[0434] The specific answer that is displayed to the user.

[0435] Step 9: Viewing Users and Selecting Actions

[0436] The user will refer to the displayed answer to decide on the next action.

[0437] Specific behavior:

[0438] The user reads the displayed legal advice and selects a next action, such as consulting the Labor Standards Inspection Office or contacting a lawyer.

[0439] input:

[0440] The displayed answer.

[0441] output:

[0442] The user's next action (e.g., consult the Labor Standards Inspection Office, contact a lawyer).

[0443] (Application example 2)

[0444] 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."

[0445] Conventional legal support systems make it difficult for users to receive prompt and appropriate legal advice when they face legal problems, and one of the challenges is that they do not take emotions into consideration. Furthermore, because the user's mental state is often an important factor in security-related legal issues, insufficient recognition and response to emotions can further exacerbate anxiety and confusion. Therefore, to solve these problems, a legal support system that can also provide emotional support is needed.

[0446] 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 analyzing a user's input using natural language processing, means for searching the Six Codes Collection and a database of past case law, means for generating a legal answer based on the search results, means including an emotion engine for recognizing the user's emotions, and means for adjusting the answer based on the user's emotions. This not only enables a user to receive prompt and appropriate legal advice when faced with a legal problem, but also makes it possible to provide support that takes the user's emotions into consideration.

[0447] A "terminal" is a device through which a user can enter legal questions or issues and receive answers.

[0448] A "server" is a central processing unit that receives input from terminals, analyzes data, searches, generates and transmits answers.

[0449] "Natural language processing" is a technology that analyzes input text data and understands its meaning.

[0450] The "Roppo Zensho" is a legal book that compiles the six basic laws of Japan.

[0451] A "case law database" is a database that stores past court decisions in a searchable format.

[0452] The "emotion engine" is a module that identifies emotions contained in the user's input text.

[0453] "Answer generation" is the process of creating specific and emotionally sensitive answers to users' questions based on search results and the output of the emotion engine.

[0454] "Search results" are relevant legal information obtained from the Six Codes and case law databases.

[0455] "Communication means" refers to the means for sending and receiving data between the server and the terminal.

[0456] The present invention is a system including a terminal for a user to input a legal question or problem, a server that receives input from the terminal, means for analyzing the input using natural language processing (NLP), means for searching the Six Codes and a database of past case law, means for generating a legal answer based on the search results, and means for transmitting the generated answer to the terminal. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions, and also includes means for adjusting the answer based on the user's emotions.

[0457] System Overview

[0458] 1. Device:

[0459] A device that allows a user to enter legal questions or issues and receive answers, including smartphones, tablets, and personal computers.

[0460] 2. Server:

[0461] It acts as a central processing unit, receiving input from the terminals, analyzing the data, searching, generating and sending answers.

[0462] 3. Natural Language Processing (NLP) Module:

[0463] It is a technology that analyzes input text data and understands its meaning. For example, it uses libraries such as spaCy and NLTK to extract keywords and context from the text.

[0464] 4. Legal Information Database:

[0465] This is a database containing the complete collection of laws and past legal precedents. The server searches this database to obtain the appropriate legal information. Database management systems such as MySQL (registered trademark) and PostgreSQL can be used.

[0466] 5. Emotion Engine:

[0467] This module identifies the sentiment contained in the user's input text. It includes a sentiment analysis model built using TENSORFLOW (registered trademark) and PyTorch.

[0468] 6. Answer Generation Module:

[0469] Generate specific, sentiment-sensitive answers based on search results and the output of the sentiment engine. Use generative AI models to create the best legal advice for your question.

[0470] 7. Means of communication:

[0471] It is a means for sending and receiving data between a server and a terminal. Specifically, API communication is performed using HTTP requests and responses.

[0472] System details process

[0473] User Input

[0474] A user uses a terminal to enter a specific legal question, such as "How do I handle a security breach?" into a text field.

[0475] Data processing on the server

[0476] When data is sent from a device to a server, a natural language processing module first analyzes the input text, extracts keywords and context, and generates data that can be used as a search criteria.

[0477] emotion recognition

[0478] The analyzed text data is processed by an emotion engine to identify the user's emotions, such as "anxiety" or "anger."

[0479] Search for legal information and generate answers

[0480] The system searches for relevant information in the complete collection of laws and case law databases, and the answer generation module generates specific, emotion-sensitive answers based on the output of the emotion engine.

[0481] Submitting and viewing responses

[0482] The generated answer is sent from the server to the terminal and displayed on the user's terminal, allowing the user to refer to the answer and select the next action.

[0483] Prompt Sentence Examples

[0484] A user opens a smartphone app and types, "How do I handle a security-related breach of contract?" This question is sent to the server, where the NLP module extracts the keywords "security" and "breach of contract." At the same time, the emotion engine detects "anxiety" from the user's text. Relevant information is searched for in the legal database, and an appropriate, emotion-sensitive answer is generated based on that information and the detected emotion.

[0485] Example prompt sentence:

[0486] The user asked, "How do I handle a security breach?" This question contains the emotion "anxiety." Use this information to generate appropriate legal advice. Include specific laws and legal precedents in your answer.

[0487] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0488] Step 1:

[0489] The user inputs a question into a terminal for inputting legal questions or issues. For example, the user might input, "Please tell me how to deal with a security-related contract violation." The terminal collects this text data and prepares it for transmission to the server.

[0490] Input: The question text that the user types into the terminal.

[0491] Output: JSON formatted data to send to the server.

[0492] Step 2:

[0493] The device receives the user's input and sends the data as an HTTP POST request to a specific API endpoint, which includes the user's question.

[0494] Input: JSON data containing the user's question.

[0495] Output: The HTTP POST request received by the server.

[0496] Step 3:

[0497] The server receives the HTTP POST request and begins data analysis. It uses a natural language processing (NLP) module to extract keywords and context from the question text.

[0498] Input: The user's question text.

[0499] Output: Extracted keywords and contextual data.

[0500] Step 4:

[0501] The server uses the extracted data to run an emotion engine to identify emotions from the user's text, such as "anxiety" or "anger."

[0502] Input: Keywords and contextual data.

[0503] Output: The detected emotion.

[0504] Step 5:

[0505] The server searches a legal information database based on keywords. The database contains the complete collection of laws and past legal precedents. The server extracts relevant legal information.

[0506] Input: Keyword data.

[0507] Output: The legal information search results.

[0508] Step 6:

[0509] The server uses the answer generation module to generate appropriate legal answers based on the extracted legal information and the output of the emotion engine, and uses the generative AI model to provide specific advice that takes the user's emotions into consideration.

[0510] Input: Search results and sentiment data.

[0511] Output: The generated legal answer.

[0512] Step 7:

[0513] The server sends the generated answer to the device as an API response, which contains specific legal advice in response to the user's question.

[0514] Input: The generated legal response.

[0515] Output: The API response received by the device.

[0516] Step 8:

[0517] The device analyzes the received answers and displays them in a user-friendly format, for example, using text or visual aids to help the user select the next action.

[0518] Input: Legal Answer received as API response.

[0519] Output: Specific legal advice and related information displayed to the user.

[0520] 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.

[0521] 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.

[0522] 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.

[0523] [Second embodiment]

[0524] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0525] 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.

[0526] 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).

[0527] 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.

[0528] 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.

[0529] 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).

[0530] 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.

[0531] 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.

[0532] 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.

[0533] 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.

[0534] 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.

[0535] 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."

[0536] The present invention provides a system including a terminal for a user to input a legal question or problem, a server that receives input from the terminal, means for analyzing the input using natural language processing, means for searching the Six Codes and a database of past case law, means for generating a legal answer based on the search results, and means for transmitting the generated answer to the terminal.

[0537] System configuration

[0538] 1. Terminal

[0539] A device that allows users to enter legal questions or issues and receive answers.

[0540] Specifically, this includes computers, smartphones, tablets, etc.

[0541] 2. Server

[0542] It acts as a central processing unit, receiving input from the terminals, analyzing the data, searching, generating and sending answers.

[0543] 3. Natural Language Processing (NLP) Module

[0544] It uses technology to analyze input text data and understand its meaning.

[0545] This includes processes such as keyword extraction, contextual analysis, and syntax analysis.

[0546] 4. Legal Information Database

[0547] This is a database that includes the complete collection of laws and past court cases.

[0548] The server searches this database to obtain the appropriate legal information.

[0549] 5. Answer Generation Module

[0550] Based on the search results, legal answers to the user's questions are generated.

[0551] 6. Means of communication

[0552] Provides a means for sending and receiving data between the server and the terminal.

[0553] Specifically, HTTP requests and responses are used.

[0554] Program processing

[0555] Example: From user input to answer generation

[0556] 1. User Input

[0557] The user uses the terminal to enter a specific legal question.

[0558] For example: "What should I do if I get fired and I didn't sign a contract?"

[0559] 2. Sending a request from the device to the server

[0560] The terminal that receives the user's input sends an API request to the server.

[0561] Example: Send an HTTP POST request containing the user's question.

[0562] 3. Data reception and analysis on the server

[0563] The server parses the received request and extracts the user's input text.

[0564] The NLP module analyzes the text and understands keywords and context.

[0565] For example, extract keywords such as "contract," "signature," and "dismissal."

[0566] 4. Legal Information Search

[0567] The server searches the complete collection of laws and a database of past legal precedents.

[0568] Use search algorithms to extract relevant legal information.

[0569] For example, obtain Article 15 of the Labor Contract Act and past legal precedents (Heisei XX year XX judgment).

[0570] 5. Answer Generation

[0571] Based on the search results, the answer generation module constructs an answer.

[0572] The server generates a response containing specific legal advice.

[0573] Example: "Even if you have not signed a contract, a labor contract may still be in place. You may be able to sue for unfair dismissal under Article 15 of the Labor Contract Act."

[0574] 6. Sending a response from the server to the device

[0575] The server generates a response and returns it to the terminal.

[0576] Example: Sending an HTTP response containing the generated answer to the terminal.

[0577] 7. Displaying answers on your device

[0578] The terminal displays the received response to the user.

[0579] The user will refer to the displayed answer to decide on the next action.

[0580] Example: Specific legal advice and relevant legal information displayed on screen.

[0581] In this way, the system of the present invention allows users to receive appropriate legal advice quickly and at low cost, even if they do not have specialized legal knowledge.

[0582] The processing flow will be explained below.

[0583] Step 1:

[0584] A user enters a legal question or issue.

[0585] For example, a user might use a terminal to type, "What should I do if I am fired but haven't signed a contract?"

[0586] Step 2:

[0587] The device generates an API request to send the user's input to the server.

[0588] For example, the device sends the following HTTP POST request to the server:

[0589] json

[0590] {

[0591] "question": "What should I do if I get fired without signing a contract?"

[0592] }

[0593] Step 3:

[0594] The server parses the received request and extracts the entered text.

[0595] It uses a natural language processing (NLP) module to analyze the meaning of the input text and identify relevant keywords and context.

[0596] Step 4:

[0597] The server searches the complete collection of laws and past case law databases based on the extracted keywords.

[0598] For example, extract information about "Article 15 of the Labor Contract Act" and "Past precedents (Heisei XX year XX judgment)."

[0599] Step 5:

[0600] Based on the data acquired by the server, an AI algorithm is used to generate specific answers to the user's questions.

[0601] For example, it will generate an answer like this:

[0602] Even if a written contract has not been signed, a labor contract may be deemed to have been established through an oral agreement or the actual performance of work. Pursuant to Article 15 of the Labor Contract Act, it is possible to sue for unfair dismissal. Furthermore, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei).

[0603] Step 6:

[0604] The server generates an API response to return the generated answer to the device.

[0605] For example, send the following HTTP response to the device:

[0606] json

[0607] {

[0608] "answer": "Even if you have not signed a contract, a labor contract may be deemed to have been established by an oral agreement or the actual performance of work. Under Article 15 of the Labor Contract Act, you can file a lawsuit for unfair dismissal. In addition, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei)."

[0609] }

[0610] Step 7:

[0611] The terminal analyzes the response received from the server and displays it in a format that is easy for the user to understand.

[0612] For example, display the answer on the terminal screen in the following format:

[0613] answer:

[0614] Even if a contract has not been signed, a labor contract may be deemed to have been established through an oral agreement or the actual performance of work. Under Article 15 of the Labor Contract Act, it is possible to sue for unfair dismissal. There have also been cases in the past where employees have won lawsuits (such as the XX judgment in 2015).

[0615] Step 8:

[0616] The user decides on the next action based on the displayed answer.

[0617] For example, you can choose to consult the Labor Standards Inspection Office or contact a lawyer.

[0618] Example 1

[0619] 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."

[0620] Legal problems and questions require specialized knowledge, making it difficult for many people to obtain appropriate legal advice quickly and at low cost. Understanding the complex legal context and extracting appropriate information from past precedents and legal documents requires specialized skills and time. Therefore, there is a need for a legal advice system that is easily accessible to ordinary users.

[0621] 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.

[0622] In this invention, the server includes an information terminal for a user to input a legal question or problem, a processing device for receiving the input from the information terminal, means for analyzing the input using natural language processing, means for searching a database of legal documents and past precedents, means for generating a legal answer based on the search results, means for transmitting the generated answer to the information terminal, and means for displaying the answer received by the information terminal to the user, thereby enabling users to receive appropriate legal advice quickly and at low cost even without specialized knowledge.

[0623] "User" refers to a person who enters a legal question or issue into the system.

[0624] An "information terminal" is a device through which a user can input legal questions or issues and receive answers, and specifically includes computers, smartphones, tablets, etc.

[0625] "Processor" refers to a central processing unit that receives input from an information terminal, analyzes, searches, generates and transmits a response.

[0626] "Natural language processing" refers to the technology that enables computers to understand, interpret, and generate human language (natural language), and includes text analysis, keyword extraction, context understanding, etc.

[0627] "Legal Document" means any official document, including any law, rule, regulation, or decree.

[0628] A "past case database" refers to a database that records previous court decisions and legal interpretations.

[0629] "Search tools" refers to techniques and methods for searching for relevant information in legal documents and databases of past cases.

[0630] "Answer generation means" refers to a technique or method for generating legal answers to users' questions based on search results.

[0631] "Transmission means" refers to the technology or method for transmitting the response generated by the server to the information terminal.

[0632] "Display means" refers to a technique or method for visually presenting the answer received by the information terminal to the user.

[0633] This invention relates to a system that allows users to input legal questions or problems and receive prompt and accurate legal advice. The system includes an information terminal, a processing device, natural language processing, a database of legal documents and past cases, search means, answer generation means, transmission means, and display means.

[0634] First, the information terminals used by users are devices such as computers, smartphones, tablets, etc. Users use these terminals to input legal questions and issues.

[0635] The input question or problem is then sent from the information terminal to the processing device. This is done using a communication method such as an HTTP POST request. The processing device receives the input from the information terminal and analyzes the text data using natural language processing. Specific natural language processing technologies used include NLP libraries such as spaCy and NLTK. This allows for keyword extraction and contextual analysis of the input text.

[0636] For example, if a user enters "What should I do if I am fired without signing a contract?", keywords such as "contract," "signature," and "fire" will be extracted from this text.

[0637] The processing device searches a database of legal documents and past legal precedents based on the extracted keywords. SQL queries and specific search algorithms are used as search methods. For example, Article 15 of the Labor Contract Act and past legal precedents (decision in XX year of Heisei) can be retrieved from the database.

[0638] Next, based on the search results, the answer generator generates a legal answer. This uses a generative AI model (e.g., GPT-3 or BERT). The generated answer includes specific legal advice. For example, "Even if you have not signed a contract, a labor contract may have been established. You can sue for wrongful dismissal under Article 15 of the Labor Contract Act."

[0639] The generated legal advice is sent to the information terminal as a response. HTTP responses or similar methods are again used as the means of communication. The terminal renders the received response on the screen to display it to the user. This allows the user to decide on their next course of action based on the displayed legal advice.

[0640] As a concrete example, the following prompt sentences can be used to input the generative AI model in the system:

[0641] Prompt: I have a question about employment contracts. "What should I do if I get fired even though I didn't sign a contract?"

[0642] In this way, users can receive appropriate legal advice quickly and at low cost, even if they do not have specialized legal knowledge.This system offers a new way to solve legal problems by making full use of computer technology and natural language processing techniques.

[0643] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0644] Step 1: The user enters a legal question or issue into an information terminal.

[0645] Input: A user uses an information device (computer, smartphone, tablet, etc.) to input text via a keyboard or touchscreen.

[0646] What happens: User types, "What should I do if I get fired and I didn't sign a contract?"

[0647] Output: The input text data.

[0648] Step 2: The terminal transmits the input question to the processing device.

[0649] Input: Text data entered by the user.

[0650] Specific operation: The device packs the entered text data into an HTTP POST request and sends it to the specified API endpoint.

[0651] Output: The HTTP POST request sent to the server.

[0652] Step 3: The server parses the received request and extracts the text data.

[0653] Input: HTTP POST request from the terminal.

[0654] What happens: The server parses the request and extracts the text data.

[0655] Output: The extracted text data.

[0656] Step 4: The server's natural language processing module analyzes the text data and extracts keywords and context.

[0657] Input: Extracted text data.

[0658] Specific behavior: Using an NLP library (e.g., spaCy or NLTK), extract keywords from the text and perform contextual analysis. For example, extract keywords such as "contract," "signature," and "dismissal."

[0659] Output: Extracted keywords and context information.

[0660] Step 5: The server searches legal documents and case law databases to retrieve relevant legal information.

[0661] Input: Extracted keywords and context information.

[0662] What it does: Searches a database based on keywords using SQL queries or specific search algorithms.

[0663] Output: Retrieved legal information (e.g. Article 15 of the Labor Contract Act and past court decisions).

[0664] Step 6: The server's answer generation module generates a legal answer based on the search results.

[0665] Input: The legal information searched.

[0666] Specific operation: Using a generative AI model (e.g., GPT-3 or BERT), generate a legal response. For example, "Even if you have not signed a contract, a labor contract may have been established. You can sue for wrongful dismissal under Article 15 of the Labor Contract Act."

[0667] Output: The generated legal answer.

[0668] Step 7: The server sends the generated response to the terminal.

[0669] Input: The generated legal answer.

[0670] Specific operation: The generated answer is packed in JSON format and sent to the terminal as an HTTP response.

[0671] Output: The HTTP response sent to the device.

[0672] Step 8: The terminal displays the received answer to the user.

[0673] Input: The HTTP response sent to the device.

[0674] Specific behavior: Render the answer text on the screen and display it to the user. For example, display the following on the user's screen: "Even if you have not signed the contract, a labor contract may have been established. You may be able to sue for wrongful dismissal under Article 15 of the Labor Contract Act."

[0675] Output: The legal answer displayed to the user.

[0676] (Application example 1)

[0677] 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."

[0678] In recent years, there has been a demand for systems that provide legal advice to quickly and accurately resolve legal issues. However, conventional systems have had the problem that it is difficult for users without specialized knowledge to obtain appropriate answers to legal questions and issues. Furthermore, it is still not possible to provide instant legal advice using smart devices.

[0679] 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.

[0680] In this invention, the server includes a terminal for a user to input a legal question or problem, means for receiving input from the terminal, means for analyzing the input using natural language processing, means for searching the Six Codes and a database of past case law, means for generating a legal answer based on the search results, means for transmitting the generated answer to the terminal, and a smart device that executes a program for providing legal advice, thereby enabling users to receive fast and accurate legal advice without having specialized knowledge.

[0681] A "terminal" is a device through which a user can enter legal questions or issues and receive answers.

[0682] A "server" is a device that acts as a central processing unit, receives input from terminals, analyzes data, searches, generates and transmits answers.

[0683] "Natural language processing" is a technology for analyzing text data entered by a user, understanding its content, and extracting keywords and context.

[0684] The "Roppo Zensho" is a book or database that compiles major laws and their explanations, such as Japan's Civil Code, Criminal Code, Commercial Code, and Constitution.

[0685] A "case law database" is a database that contains past court cases and their detailed information, stored in a searchable format.

[0686] A "means for generating legal answers" is a means for generating legal advice or information in response to a user's question based on natural language processing and database search results.

[0687] "Communication means" refers to the infrastructure and protocols for sending and receiving data between a server and a terminal, specifically using HTTP requests and responses.

[0688] A "smart device running a program for providing legal advice" is a mobile device on which an application is installed that generates appropriate answers to legal questions and provides the results to the user.

[0689] The present invention is a system that combines a terminal where users can input legal questions or problems and a server that receives the input, analyzes, searches, and generates answers. The system of the present invention is installed on a smart device and can provide instant legal advice. Specifically, it consists of the following components:

[0690] 1. Terminal

[0691] A device that allows users to input legal questions or issues. The device can be a computer, smartphone, tablet, etc., and allows users to receive legal advice quickly.

[0692] 2. Server

[0693] It functions as a central processing unit and receives input from terminals. The server is the main component for data analysis, search, and answer generation. It analyzes the input information using a natural language processing (NLP) module and searches the Roppo Zensho and past case law databases.

[0694] 3. Natural Language Processing (NLP) Module

[0695] It uses techniques to analyze input text data and understand its meaning. NLP can be performed using software such as SpaCy or NLTK. This module includes processes such as keyword extraction, contextual analysis, and syntax analysis.

[0696] 4. Legal Information Database

[0697] This is a database containing the complete collection of Japanese laws and past legal precedents. The server searches this database to obtain the appropriate legal information. Search engines such as Elasticsearch and Solr are used to search the database.

[0698] 5. Answer Generation Module

[0699] The search results are used to generate legal answers to users' questions, leveraging generative AI models (e.g., GPT-4) to provide specific legal advice.

[0700] 6. Means of communication

[0701] It provides a means of sending and receiving data between a server and a device, specifically using HTTP requests and responses, allowing users to receive instant legal advice on their device.

[0702] Specific implementation examples of the program

[0703] Hardware / Software Used

[0704] Device: A device such as a smartphone, tablet, or computer where a user enters a question.

[0705] Server: The central processing unit that analyzes data and generates answers.

[0706] Natural Language Processing module: Uses SpaCy and NLTK to analyze the meaning of text data.

[0707] Legal information database: Complete collection of laws and past case law database.

[0708] Communication method: HTTP request and response.

[0709] Implementation example

[0710] A user opens an app on their smartphone and enters a question like this:

[0711] Example: "What should I pay attention to when buying real estate?"

[0712] 1. Receiving input: The smartphone app receives the user's question and generates an API request to send to the server (HTTP POST request).

[0713] 2. Data analysis: The server analyzes the received request and uses the NLP module to analyze the text, thereby extracting keywords and context.

[0714] 3. Database search: Based on the extracted keywords, the legal information database is searched to obtain relevant legal information.

[0715] 4. Answer generation: Based on the information obtained, a generative AI model (e.g., GPT-4) generates specific legal advice.

[0716] 5. Sending results: The generated answer is sent from the server to the device and displayed on the user's smartphone.

[0717] Prompt Sentence Examples

[0718] Prompt statement:

[0719] A user has asked a legal question: "What should I be careful of when purchasing real estate?" Please generate specific legal advice for this question based on the Six Codes and past legal precedents.

[0720] In this way, the system of the present invention allows users to receive appropriate legal advice quickly and at low cost, even if they do not have specialized legal knowledge.

[0721] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0722] Step 1:

[0723] The user enters a legal question or problem using a device. The user opens the application screen on their smartphone or tablet and enters the question in a text box. For example, they enter a question such as, "What should I pay attention to when purchasing real estate?" The input data is sent in text format from the device to the server.

[0724] Step 2:

[0725] The device sends the entered legal question to the server. The device generates an HTTP POST request and sends the request data, including the user's question, to the server. The request data format is typically JSON.

[0726] Step 3:

[0727] The server analyzes the received request. The server receives a POST request and extracts the user's input text from the request body. This extracted text data is sent to the Natural Language Processing (NLP) module.

[0728] Step 4:

[0729] The server's natural language processing (NLP) module analyzes the received input text. The NLP module uses tools such as SpaCy or NLTK to analyze and extract keywords and context from the text data. For example, it extracts keywords such as "real estate," "purchase," and "points to note." The results of this analysis are used as input for the next search step.

[0730] Step 5:

[0731] The server searches a legal information database based on the extracted keywords. The server uses a search engine such as Elasticsearch or Solr to retrieve relevant information from the Six Codes and past case law database. For example, it retrieves laws and past case law related to real estate purchases. The search results are sent to the answer generation module.

[0732] Step 6:

[0733] The server's answer generation module generates legal answers based on the search results. It uses a generative AI model (e.g., GPT-4) to construct specific legal advice for the user's question. For example, it generates an answer such as, "When purchasing real estate, we recommend that you carefully review the sales contract, register the property, and understand the mortgage terms." The generated answers are stored in JSON format.

[0734] Step 7:

[0735] The server sends the generated answer to the device. An HTTP response containing the generated legal advice is formed and sent to the device. The response data is formatted in JSON for easy user understanding.

[0736] Step 8:

[0737] The device displays the received response to the user. The received JSON format response data is analyzed and displayed on the application screen. The user can then check the legal advice on the device screen. For example, the following message may be displayed: "When purchasing real estate, it is recommended that you carefully review the sales contract, register the property, and understand the terms of the mortgage."

[0738] 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.

[0739] The present invention is a system that includes a terminal for a user to input a legal question or problem, a server that receives input from the terminal, means for analyzing the input using natural language processing, means for searching the Six Codes and a database of past case law, means for generating a legal answer based on the search results, and means for transmitting the generated answer to the terminal, and further combines it with an emotion engine that recognizes the user's emotions.

[0740] System configuration

[0741] 1. Terminal

[0742] A device that allows users to enter legal questions or issues and receive answers.

[0743] Specifically, this includes computers, smartphones, tablets, etc.

[0744] 2. Server

[0745] It acts as a central processing unit, receiving input from the terminals, analyzing the data, searching, generating and sending answers.

[0746] 3. Natural Language Processing (NLP) Module

[0747] It uses technology to analyze input text data and understand its meaning.

[0748] This includes processes such as keyword extraction, contextual analysis, and syntax analysis.

[0749] 4. Legal Information Database

[0750] This is a database that includes the complete collection of laws and past court cases.

[0751] The server searches this database to obtain the appropriate legal information.

[0752] 5. Emotion Engine

[0753] This module identifies the emotion contained in the user's input text.

[0754] It uses natural language processing technology to identify sentiment categories and tailor responses based on those sentiments.

[0755] 6. Answer Generation Module

[0756] Based on the search results and the output of the emotion engine, specific and emotionally sensitive answers to the user's questions are generated.

[0757] 7. Means of communication

[0758] Provides a means for sending and receiving data between the server and the terminal.

[0759] Specifically, HTTP requests and responses are used.

[0760] Program processing

[0761] Example: From user input to emotion recognition and answer generation

[0762] 1. User Input

[0763] The user uses the terminal to enter a specific legal question.

[0764] For example: "What should I do if I get fired and I didn't sign a contract?"

[0765] 2. Sending a request from the device to the server

[0766] The terminal that receives the user's input sends an API request to the server.

[0767] Example: Send an HTTP POST request containing the user's question.

[0768] 3. Data reception and analysis on the server

[0769] The server parses the received request and extracts the user's input text.

[0770] The NLP module analyzes the text and understands keywords and context.

[0771] For example, extract keywords such as "contract," "signature," and "dismissal."

[0772] 4. Emotion Recognition by Emotion Engine

[0773] The server uses an emotion engine to identify emotions contained in the user's input text.

[0774] Example: Detecting emotions such as "anxiety" or "anger" from user text.

[0775] 5. Legal Information Search

[0776] The server searches the complete collection of laws and a database of past legal precedents.

[0777] Use search algorithms to extract relevant legal information.

[0778] For example, obtain Article 15 of the Labor Contract Act and past legal precedents (Heisei XX year XX judgment).

[0779] 6. Answer Generation

[0780] Based on the search results and the output of the emotion engine, the answer generation module generates specific and emotion-sensitive answers.

[0781] Example: "Even if you haven't signed a contract, a labor contract may still be in place. Please don't worry. In cases like this, you can sue for unfair dismissal under Article 15 of the Labor Contract Act. In addition, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei)."

[0782] 7. Sending a response from the server to the device

[0783] The server generates an API response to return the generated answer to the terminal.

[0784] Example: Sending an HTTP response containing the generated answer to the terminal.

[0785] 8. Displaying answers on your device

[0786] The terminal analyzes the received response and displays it in a user-friendly format.

[0787] Example: Specific legal advice and relevant legal information displayed on the device screen, with a stable emotional expression.

[0788] 9. User Reference and Action Selection

[0789] The user decides on the next action based on the displayed answer.

[0790] Example: Choose whether to consult the Labor Standards Inspection Office or contact a lawyer.

[0791] In this way, the system of the present invention allows users to receive appropriate legal advice quickly and at low cost, even if they do not have specialized legal knowledge, and provides support that takes into consideration the user's feelings.

[0792] The processing flow will be explained below.

[0793] Step 1:

[0794] A user enters a legal question or issue.

[0795] For example, a user might use a terminal to type, "What should I do if I am fired but haven't signed a contract?"

[0796] Step 2:

[0797] The device generates an API request to send the user's input to the server.

[0798] For example, the device sends the following HTTP POST request to the server:

[0799] json

[0800] {

[0801] "question": "What should I do if I get fired without signing a contract?"

[0802] }

[0803] Step 3:

[0804] The server parses the received request and extracts the entered text.

[0805] It uses a natural language processing (NLP) module to analyze the meaning of the input text and identify relevant keywords and context.

[0806] For example, extract keywords such as "contract," "signature," and "dismissal."

[0807] Step 4:

[0808] The server uses an emotion engine to identify emotions contained in the user's input text.

[0809] Natural language processing technology is used to analyze emotions and identify emotion categories.

[0810] Example: Detecting emotions such as "anxiety" or "anger" from input text.

[0811] Step 5:

[0812] The server searches the complete collection of laws and a database of past legal precedents based on the extracted keywords and the identified emotions.

[0813] Using a search algorithm, relevant information such as "Article 15 of the Labor Contract Act" and "Past legal precedents (Heisei XX year XX judgment)" is extracted.

[0814] Step 6:

[0815] The server uses AI algorithms to generate answers to users' questions based on search results and sentiment data.

[0816] The generated responses include a tone and expression that takes into consideration the user's feelings.

[0817] Example: "Even if you haven't signed a contract, a labor contract may still be in place. Please don't worry. In cases like this, you can sue for unfair dismissal under Article 15 of the Labor Contract Act. In addition, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei)."

[0818] Step 7:

[0819] The server generates an API response to return the generated answer to the device.

[0820] Example: Send an HTTP response containing the generated answer to the terminal:

[0821] json

[0822] {

[0823] "answer": "Even if you haven't signed a contract, a labor contract may still be in place. Please don't worry. In such cases, you can file a lawsuit for unfair dismissal under Article 15 of the Labor Contract Act. In addition, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei)."

[0824] }

[0825] Step 8:

[0826] The terminal analyzes the response received from the server and displays it in a format that is easy for the user to understand.

[0827] Specific legal advice and relevant legal information are displayed on the device screen, along with a stable emotional response.

[0828] Example: "Even if you haven't signed a contract, a labor contract may still be in place. Please don't worry. In cases like this, you can sue for unfair dismissal under Article 15 of the Labor Contract Act. In addition, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei)."

[0829] Step 9:

[0830] The user decides on the next action based on the displayed answer.

[0831] For example, you can choose to consult the Labor Standards Inspection Office or contact a lawyer.

[0832] Example 2

[0833] 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."

[0834] While conventional legal question-answering systems can provide appropriate legal answers based on the user's input text, they often find it difficult to provide answers that take the user's emotions into consideration, which can lead to anxiety and stress. Furthermore, the accuracy of legal information searches and the specificity of answers are often insufficient, and these systems often fail to help users decide on their next course of action.

[0835] 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.

[0836] In this invention, the server includes emotion recognition means for identifying emotions contained in the user's input text, means for adjusting a response based on the emotions identified by the emotion recognition means, and means for searching the Six Codes and a database of past legal precedents, thereby making it possible to propose specific actions to address legal issues while taking the user's emotions into consideration.

[0837] A "terminal" is an information processing device such as a computer, smartphone, or tablet that a user uses to enter input and receive responses.

[0838] A "server" is a central processing unit that receives input from terminals, analyzes data, searches, generates and transmits answers.

[0839] "Natural language processing" is a technology that analyzes text data entered by a user and understands its meaning, and includes keyword extraction and context analysis.

[0840] The "Roppo Zensho and Past Case Law Database" is a database that stores legal information, including the Roppo Zensho and past case law.

[0841] "Emotion recognition means" is a technology that identifies the user's emotions contained in the input text and identifies emotion categories such as anxiety or anger.

[0842] The "means for adjusting an answer" is a technology for adjusting the content and expression of an answer that is generated based on the emotion identified by the emotion recognition means.

[0843] The "answer generation means" is a technology that creates specific and emotion-sensitive responses to user questions based on search results and emotion recognition results.

[0844] "Communication means" refers to the technology for sending and receiving data between the server and the terminal, specifically using HTTP requests and responses.

[0845] An "API request" is a data request sent from a terminal to a server, and is sent in a format that includes the user's input.

[0846] An "HTTP response" is a data response sent from a server to a terminal, and is sent in a format that includes a generated answer.

[0847] MODE FOR CARRYING OUT THE INVENTION

[0848] The present invention is a system that includes a terminal for a user to input a legal question or problem, a server that receives input from the terminal, means for analyzing the input using natural language processing, means for searching the Six Codes and a database of past case law, means for generating a legal answer based on the search results, and means for transmitting the generated answer to the terminal, and further combines it with an emotion engine that recognizes the user's emotions.

[0849] The configuration for implementing this is as follows.

[0850] 1. Terminal

[0851] A device that allows a user to enter legal questions or issues and receive answers, such as a computer, smartphone, or tablet.

[0852] 2. Server

[0853] It acts as a central processing unit, receiving input from the terminals, analyzing the data, searching, generating and sending answers.

[0854] 3. Natural Language Processing (NLP) Module

[0855] It uses technology to analyze input text data and understand its meaning, including processes such as keyword extraction, contextual analysis, and syntax analysis.

[0856] 4. Legal Information Database

[0857] This is a database containing the complete collection of laws and past legal precedents. The server searches this database to retrieve the appropriate legal information.

[0858] 5. Emotion Engine

[0859] This module identifies the sentiment contained in the user's input text, using natural language processing techniques to identify sentiment categories and tailor responses based on those sentiments.

[0860] 6. Answer Generation Module

[0861] Based on the search results and the output of the emotion engine, specific and emotionally sensitive answers to the user's questions are generated.

[0862] 7. Means of communication

[0863] It provides a means to send and receive data between the server and the terminal, specifically using HTTP requests and responses.

[0864] Specific examples

[0865] The user uses the device to input a legal question, such as "What should I do if I'm fired without signing a contract?" The device receives this input and sends an HTTP POST request to the server. The server analyzes the received request and uses an NLP module to analyze the text data. At the same time, an emotion engine detects emotions such as "anxiety" or "anger" from the user's input.

[0866] The server then searches the Six Codes and a database of past legal precedents to obtain relevant legal information. For example, it references Article 15 of the Labor Contract Act and past legal precedents (Heisei XX Year XX Judgment). Based on the search results and the output of the emotion engine, the answer generation module generates specific legal advice. The server sends the generated answer to the terminal as an HTTP response, and the terminal displays it to the user.

[0867] Prompt Sentence Examples

[0868] An example of a user-provided prompt is, "What should I do if I'm fired without signing a contract? Emotion: Anxiety." This prompt allows the generative AI model to provide specific, emotionally sensitive advice on a particular legal issue.

[0869] According to the above embodiment, users can obtain appropriate legal advice quickly and at low cost even if they do not have specialized legal knowledge, and can also receive support that takes into consideration the feelings of the users.

[0870] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0871] Program processing flow

[0872] Step 1: User enters legal question into terminal

[0873] The user enters a legal question or problem into the terminal.

[0874] Specific behavior:

[0875] A user types a question into an input field on a terminal, such as "What should I do if I am fired but have not signed a contract?"

[0876] input:

[0877] The text of the user's legal question.

[0878] output:

[0879] The entered question text.

[0880] Step 2: Sending a request from the device to the server

[0881] The terminal generates an HTTP POST request to send the user's question to the server.

[0882] Specific behavior:

[0883] The device converts the entered question text into JSON format and sends an HTTP POST request to the API endpoint.

[0884] input:

[0885] The text of the user's legal question.

[0886] output:

[0887] An HTTP POST request in JSON format.

[0888] Step 3: Receiving and analyzing data on the server

[0889] The server receives requests from the device, extracts text data, and passes the extracted text data to a natural language processing (NLP) module for analysis.

[0890] Specific behavior:

[0891] The server extracts the JSON payload from the HTTP request, and the NLP module extracts keywords such as "contract," "signature," and "dismissal."

[0892] input:

[0893] HTTP POST request.

[0894] output:

[0895] Extracted keywords and contextual information.

[0896] Step 4: Emotion Recognition with the Emotion Engine

[0897] The server passes the text analyzed by the NLP module to the emotion engine to identify the user's emotion.

[0898] Specific behavior:

[0899] The server uses an emotion engine to identify emotions such as "anxiety" or "anger."

[0900] input:

[0901] Text data analyzed by the NLP module.

[0902] output:

[0903] Identified emotional information (e.g., anxiety).

[0904] Step 5: Find legal information

[0905] The server searches the complete collection of laws and a database of past court cases to obtain relevant legal information.

[0906] Specific behavior:

[0907] The server executes a database query to search for legal provisions and precedents related to "contract" and "dismissal," and retrieves Article 15 of the Labor Contract Act and the XX judgment of Heisei XX year.

[0908] input:

[0909] Extracted keywords and contextual information.

[0910] output:

[0911] Legal information obtained (e.g., legal texts, case law).

[0912] Step 6: Generate an answer

[0913] The server uses the answer generation module to generate a specific answer for the user based on the acquired legal information and the results of the emotion engine.

[0914] Specific behavior:

[0915] The server generates a response such as, "Even if you haven't signed the contract, a labor contract may still be in place. Please don't worry. In such cases, you can sue for wrongful dismissal under Article 15 of the Labor Contract Act. In addition, there have been cases in the past where employees have won the case (such as the XX judgment in XX year of Heisei)."

[0916] input:

[0917] Legal information obtained, emotional information identified.

[0918] output:

[0919] The specific answer text generated.

[0920] Step 7: Sending the response from the server to the device

[0921] The server sends an HTTP response containing the generated answer to the terminal.

[0922] Specific behavior:

[0923] The server converts the generated answer into JSON format and sends it back to the device as an HTTP response.

[0924] input:

[0925] The generated answer text.

[0926] output:

[0927] The HTTP response in JSON format.

[0928] Step 8: View your answers on your device

[0929] The terminal analyzes the received response and displays it in a user-friendly format.

[0930] Specific behavior:

[0931] The terminal parses the JSON response and displays the following message: "Even if you have not signed the contract, an employment contract may still be in place. Please do not worry. In such cases, you can sue for wrongful dismissal under Article 15 of the Labor Contract Act. In addition, there have been past court cases (Heisei XX year XX judgment) in which employees have won the case."

[0932] input:

[0933] JSON response.

[0934] output:

[0935] The specific answer that is displayed to the user.

[0936] Step 9: Viewing Users and Selecting Actions

[0937] The user will refer to the displayed answer to decide on the next action.

[0938] Specific behavior:

[0939] The user reads the displayed legal advice and selects a next action, such as consulting the Labor Standards Inspection Office or contacting a lawyer.

[0940] input:

[0941] The displayed answer.

[0942] output:

[0943] The user's next action (e.g., consult the Labor Standards Inspection Office, contact a lawyer).

[0944] (Application example 2)

[0945] 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."

[0946] Conventional legal support systems make it difficult for users to receive prompt and appropriate legal advice when they face legal problems, and one of the challenges is that they do not take emotions into consideration. Furthermore, because the user's mental state is often an important factor in security-related legal issues, insufficient recognition and response to emotions can further exacerbate anxiety and confusion. Therefore, to solve these problems, a legal support system that can also provide emotional support is needed.

[0947] 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 analyzing a user's input using natural language processing, means for searching the Six Codes Collection and a database of past case law, means for generating a legal answer based on the search results, means including an emotion engine for recognizing the user's emotions, and means for adjusting the answer based on the user's emotions. This not only enables a user to receive prompt and appropriate legal advice when faced with a legal problem, but also makes it possible to provide support that takes the user's emotions into consideration.

[0948] A "terminal" is a device through which a user can enter legal questions or issues and receive answers.

[0949] A "server" is a central processing unit that receives input from terminals, analyzes data, searches, generates and transmits answers.

[0950] "Natural language processing" is a technology that analyzes input text data and understands its meaning.

[0951] The "Roppo Zensho" is a legal book that compiles the six basic laws of Japan.

[0952] A "case law database" is a database that stores past court decisions in a searchable format.

[0953] The "emotion engine" is a module that identifies emotions contained in the user's input text.

[0954] "Answer generation" is the process of creating specific and emotionally sensitive answers to users' questions based on search results and the output of the emotion engine.

[0955] "Search results" are relevant legal information obtained from the Six Codes and case law databases.

[0956] "Communication means" refers to the means for sending and receiving data between the server and the terminal.

[0957] The present invention is a system including a terminal for a user to input a legal question or problem, a server that receives input from the terminal, means for analyzing the input using natural language processing (NLP), means for searching the Six Codes and a database of past case law, means for generating a legal answer based on the search results, and means for transmitting the generated answer to the terminal. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions, and also includes means for adjusting the answer based on the user's emotions.

[0958] System Overview

[0959] 1. Device:

[0960] A device that allows a user to enter legal questions or issues and receive answers, including smartphones, tablets, and personal computers.

[0961] 2. Server:

[0962] It acts as a central processing unit, receiving input from the terminals, analyzing the data, searching, generating and sending answers.

[0963] 3. Natural Language Processing (NLP) Module:

[0964] It is a technology that analyzes input text data and understands its meaning. For example, it uses libraries such as spaCy and NLTK to extract keywords and context from the text.

[0965] 4. Legal Information Database:

[0966] This is a database containing the complete collection of laws and past legal precedents. The server searches this database to retrieve the appropriate legal information. Database management systems such as MySQL and PostgreSQL can be used.

[0967] 5. Emotion Engine:

[0968] This module identifies the sentiment contained in the user's input text and includes a sentiment analysis model built using TensorFlow and PyTorch.

[0969] 6. Answer Generation Module:

[0970] Generate specific, sentiment-sensitive answers based on search results and the output of the sentiment engine. Use generative AI models to create the best legal advice for your question.

[0971] 7. Means of communication:

[0972] It is a means for sending and receiving data between a server and a terminal. Specifically, API communication is performed using HTTP requests and responses.

[0973] System details process

[0974] User Input

[0975] A user uses a terminal to enter a specific legal question, such as "How do I handle a security breach?" into a text field.

[0976] Data processing on the server

[0977] When data is sent from a device to a server, a natural language processing module first analyzes the input text, extracts keywords and context, and generates data that can be used as a search criteria.

[0978] emotion recognition

[0979] The analyzed text data is processed by an emotion engine to identify the user's emotions, such as "anxiety" or "anger."

[0980] Search for legal information and generate answers

[0981] The system searches for relevant information in the complete collection of laws and case law databases, and the answer generation module generates specific, emotion-sensitive answers based on the output of the emotion engine.

[0982] Submitting and viewing responses

[0983] The generated answer is sent from the server to the terminal and displayed on the user's terminal, allowing the user to refer to the answer and select the next action.

[0984] Prompt Sentence Examples

[0985] A user opens a smartphone app and types, "How do I handle a security-related breach of contract?" This question is sent to the server, where the NLP module extracts the keywords "security" and "breach of contract." At the same time, the emotion engine detects "anxiety" from the user's text. Relevant information is searched for in the legal database, and an appropriate, emotion-sensitive answer is generated based on that information and the detected emotion.

[0986] Example prompt sentence:

[0987] The user asked, "How do I handle a security breach?" This question contains the emotion "anxiety." Use this information to generate appropriate legal advice. Include specific laws and legal precedents in your answer.

[0988] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0989] Step 1:

[0990] The user inputs a question into a terminal for inputting legal questions or issues. For example, the user might input, "Please tell me how to deal with a security-related contract violation." The terminal collects this text data and prepares it for transmission to the server.

[0991] Input: The question text that the user types into the terminal.

[0992] Output: JSON formatted data to send to the server.

[0993] Step 2:

[0994] The device receives the user's input and sends the data as an HTTP POST request to a specific API endpoint, which includes the user's question.

[0995] Input: JSON data containing the user's question.

[0996] Output: The HTTP POST request received by the server.

[0997] Step 3:

[0998] The server receives the HTTP POST request and begins data analysis. It uses a natural language processing (NLP) module to extract keywords and context from the question text.

[0999] Input: The user's question text.

[1000] Output: Extracted keywords and contextual data.

[1001] Step 4:

[1002] The server uses the extracted data to run an emotion engine to identify emotions from the user's text, such as "anxiety" or "anger."

[1003] Input: Keywords and contextual data.

[1004] Output: The detected emotion.

[1005] Step 5:

[1006] The server searches a legal information database based on keywords. The database contains the complete collection of laws and past legal precedents. The server extracts relevant legal information.

[1007] Input: Keyword data.

[1008] Output: The legal information search results.

[1009] Step 6:

[1010] The server uses the answer generation module to generate appropriate legal answers based on the extracted legal information and the output of the emotion engine, and uses the generative AI model to provide specific advice that takes the user's emotions into consideration.

[1011] Input: Search results and sentiment data.

[1012] Output: The generated legal answer.

[1013] Step 7:

[1014] The server sends the generated answer to the device as an API response, which contains specific legal advice in response to the user's question.

[1015] Input: The generated legal response.

[1016] Output: The API response received by the device.

[1017] Step 8:

[1018] The device analyzes the received answers and displays them in a user-friendly format, for example, using text or visual aids to help the user select the next action.

[1019] Input: Legal Answer received as API response.

[1020] Output: Specific legal advice and related information displayed to the user.

[1021] 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.

[1022] 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.

[1023] 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.

[1024] [Third embodiment]

[1025] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1026] 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.

[1027] 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).

[1028] 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.

[1029] 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.

[1030] 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).

[1031] 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.

[1032] 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.

[1033] 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.

[1034] 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.

[1035] 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.

[1036] 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."

[1037] The present invention provides a system including a terminal for a user to input a legal question or problem, a server that receives input from the terminal, means for analyzing the input using natural language processing, means for searching the Six Codes and a database of past case law, means for generating a legal answer based on the search results, and means for transmitting the generated answer to the terminal.

[1038] System configuration

[1039] 1. Terminal

[1040] A device that allows users to enter legal questions or issues and receive answers.

[1041] Specifically, this includes computers, smartphones, tablets, etc.

[1042] 2. Server

[1043] It acts as a central processing unit, receiving input from the terminals, analyzing the data, searching, generating and sending answers.

[1044] 3. Natural Language Processing (NLP) Module

[1045] It uses technology to analyze input text data and understand its meaning.

[1046] This includes processes such as keyword extraction, contextual analysis, and syntax analysis.

[1047] 4. Legal Information Database

[1048] This is a database that includes the complete collection of laws and past court cases.

[1049] The server searches this database to obtain the appropriate legal information.

[1050] 5. Answer Generation Module

[1051] Based on the search results, legal answers to the user's questions are generated.

[1052] 6. Means of communication

[1053] Provides a means for sending and receiving data between the server and the terminal.

[1054] Specifically, HTTP requests and responses are used.

[1055] Program processing

[1056] Example: From user input to answer generation

[1057] 1. User Input

[1058] The user uses the terminal to enter a specific legal question.

[1059] For example: "What should I do if I get fired and I didn't sign a contract?"

[1060] 2. Sending a request from the device to the server

[1061] The terminal that receives the user's input sends an API request to the server.

[1062] Example: Send an HTTP POST request containing the user's question.

[1063] 3. Data reception and analysis on the server

[1064] The server parses the received request and extracts the user's input text.

[1065] The NLP module analyzes the text and understands keywords and context.

[1066] For example, extract keywords such as "contract," "signature," and "dismissal."

[1067] 4. Legal Information Search

[1068] The server searches the complete collection of laws and a database of past legal precedents.

[1069] Use search algorithms to extract relevant legal information.

[1070] For example, obtain Article 15 of the Labor Contract Act and past legal precedents (Heisei XX year XX judgment).

[1071] 5. Answer Generation

[1072] Based on the search results, the answer generation module constructs an answer.

[1073] The server generates a response containing specific legal advice.

[1074] Example: "Even if you have not signed a contract, a labor contract may still be in place. You may be able to sue for unfair dismissal under Article 15 of the Labor Contract Act."

[1075] 6. Sending a response from the server to the device

[1076] The server generates a response and returns it to the terminal.

[1077] Example: Sending an HTTP response containing the generated answer to the terminal.

[1078] 7. Displaying answers on your device

[1079] The terminal displays the received response to the user.

[1080] The user will refer to the displayed answer to decide on the next action.

[1081] Example: Specific legal advice and relevant legal information displayed on screen.

[1082] In this way, the system of the present invention allows users to receive appropriate legal advice quickly and at low cost, even if they do not have specialized legal knowledge.

[1083] The processing flow will be explained below.

[1084] Step 1:

[1085] A user enters a legal question or issue.

[1086] For example, a user might use a terminal to type, "What should I do if I am fired but haven't signed a contract?"

[1087] Step 2:

[1088] The device generates an API request to send the user's input to the server.

[1089] For example, the device sends the following HTTP POST request to the server:

[1090] json

[1091] {

[1092] "question": "What should I do if I get fired without signing a contract?"

[1093] }

[1094] Step 3:

[1095] The server parses the received request and extracts the entered text.

[1096] It uses a natural language processing (NLP) module to analyze the meaning of the input text and identify relevant keywords and context.

[1097] Step 4:

[1098] The server searches the complete collection of laws and past case law databases based on the extracted keywords.

[1099] For example, extract information about "Article 15 of the Labor Contract Act" and "Past precedents (Heisei XX year XX judgment)."

[1100] Step 5:

[1101] Based on the data acquired by the server, an AI algorithm is used to generate specific answers to the user's questions.

[1102] For example, it will generate an answer like this:

[1103] Even if a written contract has not been signed, a labor contract may be deemed to have been established through an oral agreement or the actual performance of work. Pursuant to Article 15 of the Labor Contract Act, it is possible to sue for unfair dismissal. Furthermore, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei).

[1104] Step 6:

[1105] The server generates an API response to return the generated answer to the device.

[1106] For example, send the following HTTP response to the device:

[1107] json

[1108] {

[1109] "answer": "Even if you have not signed a contract, a labor contract may be deemed to have been established by an oral agreement or the actual performance of work. Under Article 15 of the Labor Contract Act, you can file a lawsuit for unfair dismissal. In addition, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei)."

[1110] }

[1111] Step 7:

[1112] The terminal analyzes the response received from the server and displays it in a format that is easy for the user to understand.

[1113] For example, display the answer on the terminal screen in the following format:

[1114] answer:

[1115] Even if a contract has not been signed, a labor contract may be deemed to have been established through an oral agreement or the actual performance of work. Under Article 15 of the Labor Contract Act, it is possible to sue for unfair dismissal. There have also been cases in the past where employees have won lawsuits (such as the XX judgment in 2015).

[1116] Step 8:

[1117] The user decides on the next action based on the displayed answer.

[1118] For example, you can choose to consult the Labor Standards Inspection Office or contact a lawyer.

[1119] Example 1

[1120] 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."

[1121] Legal problems and questions require specialized knowledge, making it difficult for many people to obtain appropriate legal advice quickly and at low cost. Understanding the complex legal context and extracting appropriate information from past precedents and legal documents requires specialized skills and time. Therefore, there is a need for a legal advice system that is easily accessible to ordinary users.

[1122] 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.

[1123] In this invention, the server includes an information terminal for a user to input a legal question or problem, a processing device for receiving the input from the information terminal, means for analyzing the input using natural language processing, means for searching a database of legal documents and past precedents, means for generating a legal answer based on the search results, means for transmitting the generated answer to the information terminal, and means for displaying the answer received by the information terminal to the user, thereby enabling users to receive appropriate legal advice quickly and at low cost even without specialized knowledge.

[1124] "User" refers to a person who enters a legal question or issue into the system.

[1125] An "information terminal" is a device through which a user can input legal questions or issues and receive answers, and specifically includes computers, smartphones, tablets, etc.

[1126] "Processor" refers to a central processing unit that receives input from an information terminal, analyzes, searches, generates and transmits a response.

[1127] "Natural language processing" refers to the technology that enables computers to understand, interpret, and generate human language (natural language), and includes text analysis, keyword extraction, context understanding, etc.

[1128] "Legal Document" means any official document, including any law, rule, regulation, or decree.

[1129] A "past case database" refers to a database that records previous court decisions and legal interpretations.

[1130] "Search tools" refers to techniques and methods for searching for relevant information in legal documents and databases of past cases.

[1131] "Answer generation means" refers to a technique or method for generating legal answers to users' questions based on search results.

[1132] "Transmission means" refers to the technology or method for transmitting the response generated by the server to the information terminal.

[1133] "Display means" refers to a technique or method for visually presenting the answer received by the information terminal to the user.

[1134] This invention relates to a system that allows users to input legal questions or problems and receive prompt and accurate legal advice. The system includes an information terminal, a processing device, natural language processing, a database of legal documents and past cases, search means, answer generation means, transmission means, and display means.

[1135] First, the information terminals used by users are devices such as computers, smartphones, tablets, etc. Users use these terminals to input legal questions and issues.

[1136] The input question or problem is then sent from the information terminal to the processing device. This is done using a communication method such as an HTTP POST request. The processing device receives the input from the information terminal and analyzes the text data using natural language processing. Specific natural language processing technologies used include NLP libraries such as spaCy and NLTK. This allows for keyword extraction and contextual analysis of the input text.

[1137] For example, if a user enters "What should I do if I am fired without signing a contract?", keywords such as "contract," "signature," and "fire" will be extracted from this text.

[1138] The processing device searches a database of legal documents and past legal precedents based on the extracted keywords. SQL queries and specific search algorithms are used as search methods. For example, Article 15 of the Labor Contract Act and past legal precedents (decision in XX year of Heisei) can be retrieved from the database.

[1139] Next, based on the search results, the answer generator generates a legal answer. This uses a generative AI model (e.g., GPT-3 or BERT). The generated answer includes specific legal advice. For example, "Even if you have not signed a contract, a labor contract may have been established. You can sue for wrongful dismissal under Article 15 of the Labor Contract Act."

[1140] The generated legal advice is sent to the information terminal as a response. HTTP responses or similar methods are again used as the means of communication. The terminal renders the received response on the screen to display it to the user. This allows the user to decide on their next course of action based on the displayed legal advice.

[1141] As a concrete example, the following prompt sentences can be used to input the generative AI model in the system:

[1142] Prompt: I have a question about employment contracts. "What should I do if I get fired even though I didn't sign a contract?"

[1143] In this way, users can receive appropriate legal advice quickly and at low cost, even if they do not have specialized legal knowledge.This system offers a new way to solve legal problems by making full use of computer technology and natural language processing techniques.

[1144] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1145] Step 1: The user enters a legal question or issue into an information terminal.

[1146] Input: A user uses an information device (computer, smartphone, tablet, etc.) to input text via a keyboard or touchscreen.

[1147] What happens: User types, "What should I do if I get fired and I didn't sign a contract?"

[1148] Output: The input text data.

[1149] Step 2: The terminal transmits the input question to the processing device.

[1150] Input: Text data entered by the user.

[1151] Specific operation: The device packs the entered text data into an HTTP POST request and sends it to the specified API endpoint.

[1152] Output: The HTTP POST request sent to the server.

[1153] Step 3: The server parses the received request and extracts the text data.

[1154] Input: HTTP POST request from the terminal.

[1155] What happens: The server parses the request and extracts the text data.

[1156] Output: The extracted text data.

[1157] Step 4: The server's natural language processing module analyzes the text data and extracts keywords and context.

[1158] Input: Extracted text data.

[1159] Specific behavior: Using an NLP library (e.g., spaCy or NLTK), extract keywords from the text and perform contextual analysis. For example, extract keywords such as "contract," "signature," and "dismissal."

[1160] Output: Extracted keywords and context information.

[1161] Step 5: The server searches legal documents and case law databases to retrieve relevant legal information.

[1162] Input: Extracted keywords and context information.

[1163] What it does: Searches a database based on keywords using SQL queries or specific search algorithms.

[1164] Output: Retrieved legal information (e.g. Article 15 of the Labor Contract Act and past court decisions).

[1165] Step 6: The server's answer generation module generates a legal answer based on the search results.

[1166] Input: The legal information searched.

[1167] Specific operation: Using a generative AI model (e.g., GPT-3 or BERT), generate a legal response. For example, "Even if you have not signed a contract, a labor contract may have been established. You can sue for wrongful dismissal under Article 15 of the Labor Contract Act."

[1168] Output: The generated legal answer.

[1169] Step 7: The server sends the generated response to the terminal.

[1170] Input: The generated legal answer.

[1171] Specific operation: The generated answer is packed in JSON format and sent to the terminal as an HTTP response.

[1172] Output: The HTTP response sent to the device.

[1173] Step 8: The terminal displays the received answer to the user.

[1174] Input: The HTTP response sent to the device.

[1175] Specific behavior: Render the answer text on the screen and display it to the user. For example, display the following on the user's screen: "Even if you have not signed the contract, a labor contract may have been established. You may be able to sue for wrongful dismissal under Article 15 of the Labor Contract Act."

[1176] Output: The legal answer displayed to the user.

[1177] (Application example 1)

[1178] 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."

[1179] In recent years, there has been a demand for systems that provide legal advice to quickly and accurately resolve legal issues. However, conventional systems have had the problem that it is difficult for users without specialized knowledge to obtain appropriate answers to legal questions and issues. Furthermore, it is still not possible to provide instant legal advice using smart devices.

[1180] 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.

[1181] In this invention, the server includes a terminal for a user to input a legal question or problem, means for receiving input from the terminal, means for analyzing the input using natural language processing, means for searching the Six Codes and a database of past case law, means for generating a legal answer based on the search results, means for transmitting the generated answer to the terminal, and a smart device that executes a program for providing legal advice, thereby enabling users to receive fast and accurate legal advice without having specialized knowledge.

[1182] A "terminal" is a device through which a user can enter legal questions or issues and receive answers.

[1183] A "server" is a device that acts as a central processing unit, receives input from terminals, analyzes data, searches, generates and transmits answers.

[1184] "Natural language processing" is a technology for analyzing text data entered by a user, understanding its content, and extracting keywords and context.

[1185] The "Roppo Zensho" is a book or database that compiles major laws and their explanations, such as Japan's Civil Code, Criminal Code, Commercial Code, and Constitution.

[1186] A "case law database" is a database that contains past court cases and their detailed information, stored in a searchable format.

[1187] A "means for generating legal answers" is a means for generating legal advice or information in response to a user's question based on natural language processing and database search results.

[1188] "Communication means" refers to the infrastructure and protocols for sending and receiving data between a server and a terminal, specifically using HTTP requests and responses.

[1189] A "smart device running a program for providing legal advice" is a mobile device on which an application is installed that generates appropriate answers to legal questions and provides the results to the user.

[1190] The present invention is a system that combines a terminal where users can input legal questions or problems and a server that receives the input, analyzes, searches, and generates answers. The system of the present invention is installed on a smart device and can provide instant legal advice. Specifically, it consists of the following components:

[1191] 1. Terminal

[1192] A device that allows users to input legal questions or issues. The device can be a computer, smartphone, tablet, etc., and allows users to receive legal advice quickly.

[1193] 2. Server

[1194] It functions as a central processing unit and receives input from terminals. The server is the main component for data analysis, search, and answer generation. It analyzes the input information using a natural language processing (NLP) module and searches the Roppo Zensho and past case law databases.

[1195] 3. Natural Language Processing (NLP) Module

[1196] It uses techniques to analyze input text data and understand its meaning. NLP can be performed using software such as SpaCy or NLTK. This module includes processes such as keyword extraction, contextual analysis, and syntax analysis.

[1197] 4. Legal Information Database

[1198] This is a database containing the complete collection of Japanese laws and past legal precedents. The server searches this database to obtain the appropriate legal information. Search engines such as Elasticsearch and Solr are used to search the database.

[1199] 5. Answer Generation Module

[1200] The search results are used to generate legal answers to users' questions, leveraging generative AI models (e.g., GPT-4) to provide specific legal advice.

[1201] 6. Means of communication

[1202] It provides a means of sending and receiving data between a server and a device, specifically using HTTP requests and responses, allowing users to receive instant legal advice on their device.

[1203] Specific implementation examples of the program

[1204] Hardware / Software Used

[1205] Device: A device such as a smartphone, tablet, or computer where a user enters a question.

[1206] Server: The central processing unit that analyzes data and generates answers.

[1207] Natural Language Processing module: Uses SpaCy and NLTK to analyze the meaning of text data.

[1208] Legal information database: Complete collection of laws and past case law database.

[1209] Communication method: HTTP request and response.

[1210] Implementation example

[1211] A user opens an app on their smartphone and enters a question like this:

[1212] Example: "What should I pay attention to when buying real estate?"

[1213] 1. Receiving input: The smartphone app receives the user's question and generates an API request to send to the server (HTTP POST request).

[1214] 2. Data analysis: The server analyzes the received request and uses the NLP module to analyze the text, thereby extracting keywords and context.

[1215] 3. Database search: Based on the extracted keywords, the legal information database is searched to obtain relevant legal information.

[1216] 4. Answer generation: Based on the information obtained, a generative AI model (e.g., GPT-4) generates specific legal advice.

[1217] 5. Sending results: The generated answer is sent from the server to the device and displayed on the user's smartphone.

[1218] Prompt Sentence Examples

[1219] Prompt statement:

[1220] A user has asked a legal question: "What should I be careful of when purchasing real estate?" Please generate specific legal advice for this question based on the Six Codes and past legal precedents.

[1221] In this way, the system of the present invention allows users to receive appropriate legal advice quickly and at low cost, even if they do not have specialized legal knowledge.

[1222] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1223] Step 1:

[1224] The user enters a legal question or problem using a device. The user opens the application screen on their smartphone or tablet and enters the question in a text box. For example, they enter a question such as, "What should I pay attention to when purchasing real estate?" The input data is sent in text format from the device to the server.

[1225] Step 2:

[1226] The device sends the entered legal question to the server. The device generates an HTTP POST request and sends the request data, including the user's question, to the server. The request data format is typically JSON.

[1227] Step 3:

[1228] The server analyzes the received request. The server receives a POST request and extracts the user's input text from the request body. This extracted text data is sent to the Natural Language Processing (NLP) module.

[1229] Step 4:

[1230] The server's natural language processing (NLP) module analyzes the received input text. The NLP module uses tools such as SpaCy or NLTK to analyze and extract keywords and context from the text data. For example, it extracts keywords such as "real estate," "purchase," and "points to note." The results of this analysis are used as input for the next search step.

[1231] Step 5:

[1232] The server searches a legal information database based on the extracted keywords. The server uses a search engine such as Elasticsearch or Solr to retrieve relevant information from the Six Codes and past case law database. For example, it retrieves laws and past case law related to real estate purchases. The search results are sent to the answer generation module.

[1233] Step 6:

[1234] The server's answer generation module generates legal answers based on the search results. It uses a generative AI model (e.g., GPT-4) to construct specific legal advice for the user's question. For example, it generates an answer such as, "When purchasing real estate, we recommend that you carefully review the sales contract, register the property, and understand the mortgage terms." The generated answers are stored in JSON format.

[1235] Step 7:

[1236] The server sends the generated answer to the device. An HTTP response containing the generated legal advice is formed and sent to the device. The response data is formatted in JSON for easy user understanding.

[1237] Step 8:

[1238] The device displays the received response to the user. The received JSON format response data is analyzed and displayed on the application screen. The user can then check the legal advice on the device screen. For example, the following message may be displayed: "When purchasing real estate, it is recommended that you carefully review the sales contract, register the property, and understand the terms of the mortgage."

[1239] 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.

[1240] The present invention is a system that includes a terminal for a user to input a legal question or problem, a server that receives input from the terminal, means for analyzing the input using natural language processing, means for searching the Six Codes and a database of past case law, means for generating a legal answer based on the search results, and means for transmitting the generated answer to the terminal, and further combines it with an emotion engine that recognizes the user's emotions.

[1241] System configuration

[1242] 1. Terminal

[1243] A device that allows users to enter legal questions or issues and receive answers.

[1244] Specifically, this includes computers, smartphones, tablets, etc.

[1245] 2. Server

[1246] It acts as a central processing unit, receiving input from the terminals, analyzing the data, searching, generating and sending answers.

[1247] 3. Natural Language Processing (NLP) Module

[1248] It uses technology to analyze input text data and understand its meaning.

[1249] This includes processes such as keyword extraction, contextual analysis, and syntax analysis.

[1250] 4. Legal Information Database

[1251] This is a database that includes the complete collection of laws and past court cases.

[1252] The server searches this database to obtain the appropriate legal information.

[1253] 5. Emotion Engine

[1254] This module identifies the emotion contained in the user's input text.

[1255] It uses natural language processing technology to identify sentiment categories and tailor responses based on those sentiments.

[1256] 6. Answer Generation Module

[1257] Based on the search results and the output of the emotion engine, specific and emotionally sensitive answers to the user's questions are generated.

[1258] 7. Means of communication

[1259] Provides a means for sending and receiving data between the server and the terminal.

[1260] Specifically, HTTP requests and responses are used.

[1261] Program processing

[1262] Example: From user input to emotion recognition and answer generation

[1263] 1. User Input

[1264] The user uses the terminal to enter a specific legal question.

[1265] For example: "What should I do if I get fired and I didn't sign a contract?"

[1266] 2. Sending a request from the device to the server

[1267] The terminal that receives the user's input sends an API request to the server.

[1268] Example: Send an HTTP POST request containing the user's question.

[1269] 3. Data reception and analysis on the server

[1270] The server parses the received request and extracts the user's input text.

[1271] The NLP module analyzes the text and understands keywords and context.

[1272] For example, extract keywords such as "contract," "signature," and "dismissal."

[1273] 4. Emotion Recognition by Emotion Engine

[1274] The server uses an emotion engine to identify emotions contained in the user's input text.

[1275] Example: Detecting emotions such as "anxiety" or "anger" from user text.

[1276] 5. Legal Information Search

[1277] The server searches the complete collection of laws and a database of past legal precedents.

[1278] Use search algorithms to extract relevant legal information.

[1279] For example, obtain Article 15 of the Labor Contract Act and past legal precedents (Heisei XX year XX judgment).

[1280] 6. Answer Generation

[1281] Based on the search results and the output of the emotion engine, the answer generation module generates specific and emotion-sensitive answers.

[1282] Example: "Even if you haven't signed a contract, a labor contract may still be in place. Please don't worry. In cases like this, you can sue for unfair dismissal under Article 15 of the Labor Contract Act. In addition, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei)."

[1283] 7. Sending a response from the server to the device

[1284] The server generates an API response to return the generated answer to the terminal.

[1285] Example: Sending an HTTP response containing the generated answer to the terminal.

[1286] 8. Displaying answers on your device

[1287] The terminal analyzes the received response and displays it in a user-friendly format.

[1288] Example: Specific legal advice and relevant legal information displayed on the device screen, with a stable emotional expression.

[1289] 9. User Reference and Action Selection

[1290] The user decides on the next action based on the displayed answer.

[1291] Example: Choose whether to consult the Labor Standards Inspection Office or contact a lawyer.

[1292] In this way, the system of the present invention allows users to receive appropriate legal advice quickly and at low cost, even if they do not have specialized legal knowledge, and provides support that takes into consideration the user's feelings.

[1293] The processing flow will be explained below.

[1294] Step 1:

[1295] A user enters a legal question or issue.

[1296] For example, a user might use a terminal to type, "What should I do if I am fired but haven't signed a contract?"

[1297] Step 2:

[1298] The device generates an API request to send the user's input to the server.

[1299] For example, the device sends the following HTTP POST request to the server:

[1300] json

[1301] {

[1302] "question": "What should I do if I get fired without signing a contract?"

[1303] }

[1304] Step 3:

[1305] The server parses the received request and extracts the entered text.

[1306] It uses a natural language processing (NLP) module to analyze the meaning of the input text and identify relevant keywords and context.

[1307] For example, extract keywords such as "contract," "signature," and "dismissal."

[1308] Step 4:

[1309] The server uses an emotion engine to identify emotions contained in the user's input text.

[1310] Natural language processing technology is used to analyze emotions and identify emotion categories.

[1311] Example: Detecting emotions such as "anxiety" or "anger" from input text.

[1312] Step 5:

[1313] The server searches the complete collection of laws and a database of past legal precedents based on the extracted keywords and the identified emotions.

[1314] Using a search algorithm, relevant information such as "Article 15 of the Labor Contract Act" and "Past legal precedents (Heisei XX year XX judgment)" is extracted.

[1315] Step 6:

[1316] The server uses AI algorithms to generate answers to users' questions based on search results and sentiment data.

[1317] The generated responses include a tone and expression that takes into consideration the user's feelings.

[1318] Example: "Even if you haven't signed a contract, a labor contract may still be in place. Please don't worry. In cases like this, you can sue for unfair dismissal under Article 15 of the Labor Contract Act. In addition, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei)."

[1319] Step 7:

[1320] The server generates an API response to return the generated answer to the device.

[1321] Example: Send an HTTP response containing the generated answer to the terminal:

[1322] json

[1323] {

[1324] "answer": "Even if you haven't signed a contract, a labor contract may still be in place. Please don't worry. In such cases, you can file a lawsuit for unfair dismissal under Article 15 of the Labor Contract Act. In addition, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei)."

[1325] }

[1326] Step 8:

[1327] The terminal analyzes the response received from the server and displays it in a format that is easy for the user to understand.

[1328] Specific legal advice and relevant legal information are displayed on the device screen, along with a stable emotional response.

[1329] Example: "Even if you haven't signed a contract, a labor contract may still be in place. Please don't worry. In cases like this, you can sue for unfair dismissal under Article 15 of the Labor Contract Act. In addition, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei)."

[1330] Step 9:

[1331] The user decides on the next action based on the displayed answer.

[1332] For example, you can choose to consult the Labor Standards Inspection Office or contact a lawyer.

[1333] Example 2

[1334] 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."

[1335] While conventional legal question-answering systems can provide appropriate legal answers based on the user's input text, they often find it difficult to provide answers that take the user's emotions into consideration, which can lead to anxiety and stress. Furthermore, the accuracy of legal information searches and the specificity of answers are often insufficient, and these systems often fail to help users decide on their next course of action.

[1336] 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.

[1337] In this invention, the server includes emotion recognition means for identifying emotions contained in the user's input text, means for adjusting a response based on the emotions identified by the emotion recognition means, and means for searching the Six Codes and a database of past legal precedents, thereby making it possible to propose specific actions to address legal issues while taking the user's emotions into consideration.

[1338] A "terminal" is an information processing device such as a computer, smartphone, or tablet that a user uses to enter input and receive responses.

[1339] A "server" is a central processing unit that receives input from terminals, analyzes data, searches, generates and transmits answers.

[1340] "Natural language processing" is a technology that analyzes text data entered by a user and understands its meaning, and includes keyword extraction and context analysis.

[1341] The "Roppo Zensho and Past Case Law Database" is a database that stores legal information, including the Roppo Zensho and past case law.

[1342] "Emotion recognition means" is a technology that identifies the user's emotions contained in the input text and identifies emotion categories such as anxiety or anger.

[1343] The "means for adjusting an answer" is a technology for adjusting the content and expression of an answer that is generated based on the emotion identified by the emotion recognition means.

[1344] The "answer generation means" is a technology that creates specific and emotion-sensitive responses to user questions based on search results and emotion recognition results.

[1345] "Communication means" refers to the technology for sending and receiving data between the server and the terminal, specifically using HTTP requests and responses.

[1346] An "API request" is a data request sent from a terminal to a server, and is sent in a format that includes the user's input.

[1347] An "HTTP response" is a data response sent from a server to a terminal, and is sent in a format that includes a generated answer.

[1348] MODE FOR CARRYING OUT THE INVENTION

[1349] The present invention is a system that includes a terminal for a user to input a legal question or problem, a server that receives input from the terminal, means for analyzing the input using natural language processing, means for searching the Six Codes and a database of past case law, means for generating a legal answer based on the search results, and means for transmitting the generated answer to the terminal, and further combines it with an emotion engine that recognizes the user's emotions.

[1350] The configuration for implementing this is as follows.

[1351] 1. Terminal

[1352] A device that allows a user to enter legal questions or issues and receive answers, such as a computer, smartphone, or tablet.

[1353] 2. Server

[1354] It acts as a central processing unit, receiving input from the terminals, analyzing the data, searching, generating and sending answers.

[1355] 3. Natural Language Processing (NLP) Module

[1356] It uses technology to analyze input text data and understand its meaning, including processes such as keyword extraction, contextual analysis, and syntax analysis.

[1357] 4. Legal Information Database

[1358] This is a database containing the complete collection of laws and past legal precedents. The server searches this database to retrieve the appropriate legal information.

[1359] 5. Emotion Engine

[1360] This module identifies the sentiment contained in the user's input text, using natural language processing techniques to identify sentiment categories and tailor responses based on those sentiments.

[1361] 6. Answer Generation Module

[1362] Based on the search results and the output of the emotion engine, specific and emotionally sensitive answers to the user's questions are generated.

[1363] 7. Means of communication

[1364] It provides a means to send and receive data between the server and the terminal, specifically using HTTP requests and responses.

[1365] Specific examples

[1366] The user uses the device to input a legal question, such as "What should I do if I'm fired without signing a contract?" The device receives this input and sends an HTTP POST request to the server. The server analyzes the received request and uses an NLP module to analyze the text data. At the same time, an emotion engine detects emotions such as "anxiety" or "anger" from the user's input.

[1367] The server then searches the Six Codes and a database of past legal precedents to obtain relevant legal information. For example, it references Article 15 of the Labor Contract Act and past legal precedents (Heisei XX Year XX Judgment). Based on the search results and the output of the emotion engine, the answer generation module generates specific legal advice. The server sends the generated answer to the terminal as an HTTP response, and the terminal displays it to the user.

[1368] Prompt Sentence Examples

[1369] An example of a user-provided prompt is, "What should I do if I'm fired without signing a contract? Emotion: Anxiety." This prompt allows the generative AI model to provide specific, emotionally sensitive advice on a particular legal issue.

[1370] According to the above embodiment, users can obtain appropriate legal advice quickly and at low cost even if they do not have specialized legal knowledge, and can also receive support that takes into consideration the feelings of the users.

[1371] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1372] Program processing flow

[1373] Step 1: User enters legal question into terminal

[1374] The user enters a legal question or problem into the terminal.

[1375] Specific behavior:

[1376] A user types a question into an input field on a terminal, such as "What should I do if I am fired but have not signed a contract?"

[1377] input:

[1378] The text of the user's legal question.

[1379] output:

[1380] The entered question text.

[1381] Step 2: Sending a request from the device to the server

[1382] The terminal generates an HTTP POST request to send the user's question to the server.

[1383] Specific behavior:

[1384] The device converts the entered question text into JSON format and sends an HTTP POST request to the API endpoint.

[1385] input:

[1386] The text of the user's legal question.

[1387] output:

[1388] An HTTP POST request in JSON format.

[1389] Step 3: Receiving and analyzing data on the server

[1390] The server receives requests from the device, extracts text data, and passes the extracted text data to a natural language processing (NLP) module for analysis.

[1391] Specific behavior:

[1392] The server extracts the JSON payload from the HTTP request, and the NLP module extracts keywords such as "contract," "signature," and "dismissal."

[1393] input:

[1394] HTTP POST request.

[1395] output:

[1396] Extracted keywords and contextual information.

[1397] Step 4: Emotion Recognition with the Emotion Engine

[1398] The server passes the text analyzed by the NLP module to the emotion engine to identify the user's emotion.

[1399] Specific behavior:

[1400] The server uses an emotion engine to identify emotions such as "anxiety" or "anger."

[1401] input:

[1402] Text data analyzed by the NLP module.

[1403] output:

[1404] Identified emotional information (e.g., anxiety).

[1405] Step 5: Find legal information

[1406] The server searches the complete collection of laws and a database of past court cases to obtain relevant legal information.

[1407] Specific behavior:

[1408] The server executes a database query to search for legal provisions and precedents related to "contract" and "dismissal," and retrieves Article 15 of the Labor Contract Act and the XX judgment of Heisei XX year.

[1409] input:

[1410] Extracted keywords and contextual information.

[1411] output:

[1412] Legal information obtained (e.g., legal texts, case law).

[1413] Step 6: Generate an answer

[1414] The server uses the answer generation module to generate a specific answer for the user based on the acquired legal information and the results of the emotion engine.

[1415] Specific behavior:

[1416] The server generates a response such as, "Even if you haven't signed the contract, a labor contract may still be in place. Please don't worry. In such cases, you can sue for wrongful dismissal under Article 15 of the Labor Contract Act. In addition, there have been cases in the past where employees have won the case (such as the XX judgment in XX year of Heisei)."

[1417] input:

[1418] Legal information obtained, emotional information identified.

[1419] output:

[1420] The specific answer text generated.

[1421] Step 7: Sending the response from the server to the device

[1422] The server sends an HTTP response containing the generated answer to the terminal.

[1423] Specific behavior:

[1424] The server converts the generated answer into JSON format and sends it back to the device as an HTTP response.

[1425] input:

[1426] The generated answer text.

[1427] output:

[1428] The HTTP response in JSON format.

[1429] Step 8: View your answers on your device

[1430] The terminal analyzes the received response and displays it in a user-friendly format.

[1431] Specific behavior:

[1432] The terminal parses the JSON response and displays the following message: "Even if you have not signed the contract, an employment contract may still be in place. Please do not worry. In such cases, you can sue for wrongful dismissal under Article 15 of the Labor Contract Act. In addition, there have been past court cases (Heisei XX year XX judgment) in which employees have won the case."

[1433] input:

[1434] JSON response.

[1435] output:

[1436] The specific answer that is displayed to the user.

[1437] Step 9: Viewing Users and Selecting Actions

[1438] The user will refer to the displayed answer to decide on the next action.

[1439] Specific behavior:

[1440] The user reads the displayed legal advice and selects a next action, such as consulting the Labor Standards Inspection Office or contacting a lawyer.

[1441] input:

[1442] The displayed answer.

[1443] output:

[1444] The user's next action (e.g., consult the Labor Standards Inspection Office, contact a lawyer).

[1445] (Application example 2)

[1446] 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."

[1447] Conventional legal support systems make it difficult for users to receive prompt and appropriate legal advice when they face legal problems, and one of the challenges is that they do not take emotions into consideration. Furthermore, because the user's mental state is often an important factor in security-related legal issues, insufficient recognition and response to emotions can further exacerbate anxiety and confusion. Therefore, to solve these problems, a legal support system that can also provide emotional support is needed.

[1448] 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 analyzing a user's input using natural language processing, means for searching the Six Codes Collection and a database of past case law, means for generating a legal answer based on the search results, means including an emotion engine for recognizing the user's emotions, and means for adjusting the answer based on the user's emotions. This not only enables a user to receive prompt and appropriate legal advice when faced with a legal problem, but also makes it possible to provide support that takes the user's emotions into consideration.

[1449] A "terminal" is a device through which a user can enter legal questions or issues and receive answers.

[1450] A "server" is a central processing unit that receives input from terminals, analyzes data, searches, generates and transmits answers.

[1451] "Natural language processing" is a technology that analyzes input text data and understands its meaning.

[1452] The "Roppo Zensho" is a legal book that compiles the six basic laws of Japan.

[1453] A "case law database" is a database that stores past court decisions in a searchable format.

[1454] The "emotion engine" is a module that identifies emotions contained in the user's input text.

[1455] "Answer generation" is the process of creating specific and emotionally sensitive answers to users' questions based on search results and the output of the emotion engine.

[1456] "Search results" are relevant legal information obtained from the Six Codes and case law databases.

[1457] "Communication means" refers to the means for sending and receiving data between the server and the terminal.

[1458] The present invention is a system including a terminal for a user to input a legal question or problem, a server that receives input from the terminal, means for analyzing the input using natural language processing (NLP), means for searching the Six Codes and a database of past case law, means for generating a legal answer based on the search results, and means for transmitting the generated answer to the terminal. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions, and also includes means for adjusting the answer based on the user's emotions.

[1459] System Overview

[1460] 1. Device:

[1461] A device that allows a user to enter legal questions or issues and receive answers, including smartphones, tablets, and personal computers.

[1462] 2. Server:

[1463] It acts as a central processing unit, receiving input from the terminals, analyzing the data, searching, generating and sending answers.

[1464] 3. Natural Language Processing (NLP) Module:

[1465] It is a technology that analyzes input text data and understands its meaning. For example, it uses libraries such as spaCy and NLTK to extract keywords and context from the text.

[1466] 4. Legal Information Database:

[1467] This is a database containing the complete collection of laws and past legal precedents. The server searches this database to retrieve the appropriate legal information. Database management systems such as MySQL and PostgreSQL can be used.

[1468] 5. Emotion Engine:

[1469] This module identifies the sentiment contained in the user's input text and includes a sentiment analysis model built using TensorFlow and PyTorch.

[1470] 6. Answer Generation Module:

[1471] Generate specific, sentiment-sensitive answers based on search results and the output of the sentiment engine. Use generative AI models to create the best legal advice for your question.

[1472] 7. Means of communication:

[1473] It is a means for sending and receiving data between a server and a terminal. Specifically, API communication is performed using HTTP requests and responses.

[1474] System details process

[1475] User Input

[1476] A user uses a terminal to enter a specific legal question, such as "How do I handle a security breach?" into a text field.

[1477] Data processing on the server

[1478] When data is sent from a device to a server, a natural language processing module first analyzes the input text, extracts keywords and context, and generates data that can be used as a search criteria.

[1479] emotion recognition

[1480] The analyzed text data is processed by an emotion engine to identify the user's emotions, such as "anxiety" or "anger."

[1481] Search for legal information and generate answers

[1482] The system searches for relevant information in the complete collection of laws and case law databases, and the answer generation module generates specific, emotion-sensitive answers based on the output of the emotion engine.

[1483] Submitting and viewing responses

[1484] The generated answer is sent from the server to the terminal and displayed on the user's terminal, allowing the user to refer to the answer and select the next action.

[1485] Prompt Sentence Examples

[1486] A user opens a smartphone app and types, "How do I handle a security-related breach of contract?" This question is sent to the server, where the NLP module extracts the keywords "security" and "breach of contract." At the same time, the emotion engine detects "anxiety" from the user's text. Relevant information is searched for in the legal database, and an appropriate, emotion-sensitive answer is generated based on that information and the detected emotion.

[1487] Example prompt sentence:

[1488] The user asked, "How do I handle a security breach?" This question contains the emotion "anxiety." Use this information to generate appropriate legal advice. Include specific laws and legal precedents in your answer.

[1489] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1490] Step 1:

[1491] The user inputs a question into a terminal for inputting legal questions or issues. For example, the user might input, "Please tell me how to deal with a security-related contract violation." The terminal collects this text data and prepares it for transmission to the server.

[1492] Input: The question text that the user types into the terminal.

[1493] Output: JSON formatted data to send to the server.

[1494] Step 2:

[1495] The device receives the user's input and sends the data as an HTTP POST request to a specific API endpoint, which includes the user's question.

[1496] Input: JSON data containing the user's question.

[1497] Output: The HTTP POST request received by the server.

[1498] Step 3:

[1499] The server receives the HTTP POST request and begins data analysis. It uses a natural language processing (NLP) module to extract keywords and context from the question text.

[1500] Input: The user's question text.

[1501] Output: Extracted keywords and contextual data.

[1502] Step 4:

[1503] The server uses the extracted data to run an emotion engine to identify emotions from the user's text, such as "anxiety" or "anger."

[1504] Input: Keywords and contextual data.

[1505] Output: The detected emotion.

[1506] Step 5:

[1507] The server searches a legal information database based on keywords. The database contains the complete collection of laws and past legal precedents. The server extracts relevant legal information.

[1508] Input: Keyword data.

[1509] Output: The legal information search results.

[1510] Step 6:

[1511] The server uses the answer generation module to generate appropriate legal answers based on the extracted legal information and the output of the emotion engine, and uses the generative AI model to provide specific advice that takes the user's emotions into consideration.

[1512] Input: Search results and sentiment data.

[1513] Output: The generated legal answer.

[1514] Step 7:

[1515] The server sends the generated answer to the device as an API response, which contains specific legal advice in response to the user's question.

[1516] Input: The generated legal response.

[1517] Output: The API response received by the device.

[1518] Step 8:

[1519] The device analyzes the received answers and displays them in a user-friendly format, for example, using text or visual aids to help the user select the next action.

[1520] Input: Legal Answer received as API response.

[1521] Output: Specific legal advice and related information displayed to the user.

[1522] 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.

[1523] 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.

[1524] 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.

[1525] [Fourth embodiment]

[1526] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1527] 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.

[1528] 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).

[1529] 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.

[1530] 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.

[1531] 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).

[1532] 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.

[1533] 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.

[1534] 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.

[1535] 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.

[1536] 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.

[1537] 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.

[1538] 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."

[1539] The present invention provides a system including a terminal for a user to input a legal question or problem, a server that receives input from the terminal, means for analyzing the input using natural language processing, means for searching the Six Codes and a database of past case law, means for generating a legal answer based on the search results, and means for transmitting the generated answer to the terminal.

[1540] System configuration

[1541] 1. Terminal

[1542] A device that allows users to enter legal questions or issues and receive answers.

[1543] Specifically, this includes computers, smartphones, tablets, etc.

[1544] 2. Server

[1545] It acts as a central processing unit, receiving input from the terminals, analyzing the data, searching, generating and sending answers.

[1546] 3. Natural Language Processing (NLP) Module

[1547] It uses technology to analyze input text data and understand its meaning.

[1548] This includes processes such as keyword extraction, contextual analysis, and syntax analysis.

[1549] 4. Legal Information Database

[1550] This is a database that includes the complete collection of laws and past court cases.

[1551] The server searches this database to obtain the appropriate legal information.

[1552] 5. Answer Generation Module

[1553] Based on the search results, legal answers to the user's questions are generated.

[1554] 6. Means of communication

[1555] Provides a means for sending and receiving data between the server and the terminal.

[1556] Specifically, HTTP requests and responses are used.

[1557] Program processing

[1558] Example: From user input to answer generation

[1559] 1. User Input

[1560] The user uses the terminal to enter a specific legal question.

[1561] For example: "What should I do if I get fired and I didn't sign a contract?"

[1562] 2. Sending a request from the device to the server

[1563] The terminal that receives the user's input sends an API request to the server.

[1564] Example: Send an HTTP POST request containing the user's question.

[1565] 3. Data reception and analysis on the server

[1566] The server parses the received request and extracts the user's input text.

[1567] The NLP module analyzes the text and understands keywords and context.

[1568] For example, extract keywords such as "contract," "signature," and "dismissal."

[1569] 4. Legal Information Search

[1570] The server searches the complete collection of laws and a database of past legal precedents.

[1571] Use search algorithms to extract relevant legal information.

[1572] For example, obtain Article 15 of the Labor Contract Act and past legal precedents (Heisei XX year XX judgment).

[1573] 5. Answer Generation

[1574] Based on the search results, the answer generation module constructs an answer.

[1575] The server generates a response containing specific legal advice.

[1576] Example: "Even if you have not signed a contract, a labor contract may still be in place. You may be able to sue for unfair dismissal under Article 15 of the Labor Contract Act."

[1577] 6. Sending a response from the server to the device

[1578] The server generates a response and returns it to the terminal.

[1579] Example: Sending an HTTP response containing the generated answer to the terminal.

[1580] 7. Displaying answers on your device

[1581] The terminal displays the received response to the user.

[1582] The user will refer to the displayed answer to decide on the next action.

[1583] Example: Specific legal advice and relevant legal information displayed on screen.

[1584] In this way, the system of the present invention allows users to receive appropriate legal advice quickly and at low cost, even if they do not have specialized legal knowledge.

[1585] The processing flow will be explained below.

[1586] Step 1:

[1587] A user enters a legal question or issue.

[1588] For example, a user might use a terminal to type, "What should I do if I am fired but haven't signed a contract?"

[1589] Step 2:

[1590] The device generates an API request to send the user's input to the server.

[1591] For example, the device sends the following HTTP POST request to the server:

[1592] json

[1593] {

[1594] "question": "What should I do if I get fired without signing a contract?"

[1595] }

[1596] Step 3:

[1597] The server parses the received request and extracts the entered text.

[1598] It uses a natural language processing (NLP) module to analyze the meaning of the input text and identify relevant keywords and context.

[1599] Step 4:

[1600] The server searches the complete collection of laws and past case law databases based on the extracted keywords.

[1601] For example, extract information about "Article 15 of the Labor Contract Act" and "Past precedents (Heisei XX year XX judgment)."

[1602] Step 5:

[1603] Based on the data acquired by the server, an AI algorithm is used to generate specific answers to the user's questions.

[1604] For example, it will generate an answer like this:

[1605] Even if a written contract has not been signed, a labor contract may be deemed to have been established through an oral agreement or the actual performance of work. Pursuant to Article 15 of the Labor Contract Act, it is possible to sue for unfair dismissal. Furthermore, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei).

[1606] Step 6:

[1607] The server generates an API response to return the generated answer to the device.

[1608] For example, send the following HTTP response to the device:

[1609] json

[1610] {

[1611] "answer": "Even if you have not signed a contract, a labor contract may be deemed to have been established by an oral agreement or the actual performance of work. Under Article 15 of the Labor Contract Act, you can file a lawsuit for unfair dismissal. In addition, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei)."

[1612] }

[1613] Step 7:

[1614] The terminal analyzes the response received from the server and displays it in a format that is easy for the user to understand.

[1615] For example, display the answer on the terminal screen in the following format:

[1616] answer:

[1617] Even if a contract has not been signed, a labor contract may be deemed to have been established through an oral agreement or the actual performance of work. Under Article 15 of the Labor Contract Act, it is possible to sue for unfair dismissal. There have also been cases in the past where employees have won lawsuits (such as the XX judgment in 2015).

[1618] Step 8:

[1619] The user decides on the next action based on the displayed answer.

[1620] For example, you can choose to consult the Labor Standards Inspection Office or contact a lawyer.

[1621] Example 1

[1622] 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."

[1623] Legal problems and questions require specialized knowledge, making it difficult for many people to obtain appropriate legal advice quickly and at low cost. Understanding the complex legal context and extracting appropriate information from past precedents and legal documents requires specialized skills and time. Therefore, there is a need for a legal advice system that is easily accessible to ordinary users.

[1624] 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.

[1625] In this invention, the server includes an information terminal for a user to input a legal question or problem, a processing device for receiving the input from the information terminal, means for analyzing the input using natural language processing, means for searching a database of legal documents and past precedents, means for generating a legal answer based on the search results, means for transmitting the generated answer to the information terminal, and means for displaying the answer received by the information terminal to the user, thereby enabling users to receive appropriate legal advice quickly and at low cost even without specialized knowledge.

[1626] "User" refers to a person who enters a legal question or issue into the system.

[1627] An "information terminal" is a device through which a user can input legal questions or issues and receive answers, and specifically includes computers, smartphones, tablets, etc.

[1628] "Processor" refers to a central processing unit that receives input from an information terminal, analyzes, searches, generates and transmits a response.

[1629] "Natural language processing" refers to the technology that enables computers to understand, interpret, and generate human language (natural language), and includes text analysis, keyword extraction, context understanding, etc.

[1630] "Legal Document" means any official document, including any law, rule, regulation, or decree.

[1631] A "past case database" refers to a database that records previous court decisions and legal interpretations.

[1632] "Search tools" refers to techniques and methods for searching for relevant information in legal documents and databases of past cases.

[1633] "Answer generation means" refers to a technique or method for generating legal answers to users' questions based on search results.

[1634] "Transmission means" refers to the technology or method for transmitting the response generated by the server to the information terminal.

[1635] "Display means" refers to a technique or method for visually presenting the answer received by the information terminal to the user.

[1636] This invention relates to a system that allows users to input legal questions or problems and receive prompt and accurate legal advice. The system includes an information terminal, a processing device, natural language processing, a database of legal documents and past cases, search means, answer generation means, transmission means, and display means.

[1637] First, the information terminals used by users are devices such as computers, smartphones, tablets, etc. Users use these terminals to input legal questions and issues.

[1638] The input question or problem is then sent from the information terminal to the processing device. This is done using a communication method such as an HTTP POST request. The processing device receives the input from the information terminal and analyzes the text data using natural language processing. Specific natural language processing technologies used include NLP libraries such as spaCy and NLTK. This allows for keyword extraction and contextual analysis of the input text.

[1639] For example, if a user enters "What should I do if I am fired without signing a contract?", keywords such as "contract," "signature," and "fire" will be extracted from this text.

[1640] The processing device searches a database of legal documents and past legal precedents based on the extracted keywords. SQL queries and specific search algorithms are used as search methods. For example, Article 15 of the Labor Contract Act and past legal precedents (decision in XX year of Heisei) can be retrieved from the database.

[1641] Next, based on the search results, the answer generator generates a legal answer. This uses a generative AI model (e.g., GPT-3 or BERT). The generated answer includes specific legal advice. For example, "Even if you have not signed a contract, a labor contract may have been established. You can sue for wrongful dismissal under Article 15 of the Labor Contract Act."

[1642] The generated legal advice is sent to the information terminal as a response. HTTP responses or similar methods are again used as the means of communication. The terminal renders the received response on the screen to display it to the user. This allows the user to decide on their next course of action based on the displayed legal advice.

[1643] As a concrete example, the following prompt sentences can be used to input the generative AI model in the system:

[1644] Prompt: I have a question about employment contracts. "What should I do if I get fired even though I didn't sign a contract?"

[1645] In this way, users can receive appropriate legal advice quickly and at low cost, even if they do not have specialized legal knowledge.This system offers a new way to solve legal problems by making full use of computer technology and natural language processing techniques.

[1646] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1647] Step 1: The user enters a legal question or issue into an information terminal.

[1648] Input: A user uses an information device (computer, smartphone, tablet, etc.) to input text via a keyboard or touchscreen.

[1649] What happens: User types, "What should I do if I get fired and I didn't sign a contract?"

[1650] Output: The input text data.

[1651] Step 2: The terminal transmits the input question to the processing device.

[1652] Input: Text data entered by the user.

[1653] Specific operation: The device packs the entered text data into an HTTP POST request and sends it to the specified API endpoint.

[1654] Output: The HTTP POST request sent to the server.

[1655] Step 3: The server parses the received request and extracts the text data.

[1656] Input: HTTP POST request from the terminal.

[1657] What happens: The server parses the request and extracts the text data.

[1658] Output: The extracted text data.

[1659] Step 4: The server's natural language processing module analyzes the text data and extracts keywords and context.

[1660] Input: Extracted text data.

[1661] Specific behavior: Using an NLP library (e.g., spaCy or NLTK), extract keywords from the text and perform contextual analysis. For example, extract keywords such as "contract," "signature," and "dismissal."

[1662] Output: Extracted keywords and context information.

[1663] Step 5: The server searches legal documents and case law databases to retrieve relevant legal information.

[1664] Input: Extracted keywords and context information.

[1665] What it does: Searches a database based on keywords using SQL queries or specific search algorithms.

[1666] Output: Retrieved legal information (e.g. Article 15 of the Labor Contract Act and past court decisions).

[1667] Step 6: The server's answer generation module generates a legal answer based on the search results.

[1668] Input: The legal information searched.

[1669] Specific operation: Using a generative AI model (e.g., GPT-3 or BERT), generate a legal response. For example, "Even if you have not signed a contract, a labor contract may have been established. You can sue for wrongful dismissal under Article 15 of the Labor Contract Act."

[1670] Output: The generated legal answer.

[1671] Step 7: The server sends the generated response to the terminal.

[1672] Input: The generated legal answer.

[1673] Specific operation: The generated answer is packed in JSON format and sent to the terminal as an HTTP response.

[1674] Output: The HTTP response sent to the device.

[1675] Step 8: The terminal displays the received answer to the user.

[1676] Input: The HTTP response sent to the device.

[1677] Specific behavior: Render the answer text on the screen and display it to the user. For example, display the following on the user's screen: "Even if you have not signed the contract, a labor contract may have been established. You may be able to sue for wrongful dismissal under Article 15 of the Labor Contract Act."

[1678] Output: The legal answer displayed to the user.

[1679] (Application example 1)

[1680] 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."

[1681] In recent years, there has been a demand for systems that provide legal advice to quickly and accurately resolve legal issues. However, conventional systems have had the problem that it is difficult for users without specialized knowledge to obtain appropriate answers to legal questions and issues. Furthermore, it is still not possible to provide instant legal advice using smart devices.

[1682] 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.

[1683] In this invention, the server includes a terminal for a user to input a legal question or problem, means for receiving input from the terminal, means for analyzing the input using natural language processing, means for searching the Six Codes and a database of past case law, means for generating a legal answer based on the search results, means for transmitting the generated answer to the terminal, and a smart device that executes a program for providing legal advice, thereby enabling users to receive fast and accurate legal advice without having specialized knowledge.

[1684] A "terminal" is a device through which a user can enter legal questions or issues and receive answers.

[1685] A "server" is a device that acts as a central processing unit, receives input from terminals, analyzes data, searches, generates and transmits answers.

[1686] "Natural language processing" is a technology for analyzing text data entered by a user, understanding its content, and extracting keywords and context.

[1687] The "Roppo Zensho" is a book or database that compiles major laws and their explanations, such as Japan's Civil Code, Criminal Code, Commercial Code, and Constitution.

[1688] A "case law database" is a database that contains past court cases and their detailed information, stored in a searchable format.

[1689] A "means for generating legal answers" is a means for generating legal advice or information in response to a user's question based on natural language processing and database search results.

[1690] "Communication means" refers to the infrastructure and protocols for sending and receiving data between a server and a terminal, specifically using HTTP requests and responses.

[1691] A "smart device running a program for providing legal advice" is a mobile device on which an application is installed that generates appropriate answers to legal questions and provides the results to the user.

[1692] The present invention is a system that combines a terminal where users can input legal questions or problems and a server that receives the input, analyzes, searches, and generates answers. The system of the present invention is installed on a smart device and can provide instant legal advice. Specifically, it consists of the following components:

[1693] 1. Terminal

[1694] A device that allows users to input legal questions or issues. The device can be a computer, smartphone, tablet, etc., and allows users to receive legal advice quickly.

[1695] 2. Server

[1696] It functions as a central processing unit and receives input from terminals. The server is the main component for data analysis, search, and answer generation. It analyzes the input information using a natural language processing (NLP) module and searches the Roppo Zensho and past case law databases.

[1697] 3. Natural Language Processing (NLP) Module

[1698] It uses techniques to analyze input text data and understand its meaning. NLP can be performed using software such as SpaCy or NLTK. This module includes processes such as keyword extraction, contextual analysis, and syntax analysis.

[1699] 4. Legal Information Database

[1700] This is a database containing the complete collection of Japanese laws and past legal precedents. The server searches this database to obtain the appropriate legal information. Search engines such as Elasticsearch and Solr are used to search the database.

[1701] 5. Answer Generation Module

[1702] The search results are used to generate legal answers to users' questions, leveraging generative AI models (e.g., GPT-4) to provide specific legal advice.

[1703] 6. Means of communication

[1704] It provides a means of sending and receiving data between a server and a device, specifically using HTTP requests and responses, allowing users to receive instant legal advice on their device.

[1705] Specific implementation examples of the program

[1706] Hardware / Software Used

[1707] Device: A device such as a smartphone, tablet, or computer where a user enters a question.

[1708] Server: The central processing unit that analyzes data and generates answers.

[1709] Natural Language Processing module: Uses SpaCy and NLTK to analyze the meaning of text data.

[1710] Legal information database: Complete collection of laws and past case law database.

[1711] Communication method: HTTP request and response.

[1712] Implementation example

[1713] A user opens an app on their smartphone and enters a question like this:

[1714] Example: "What should I pay attention to when buying real estate?"

[1715] 1. Receiving input: The smartphone app receives the user's question and generates an API request to send to the server (HTTP POST request).

[1716] 2. Data analysis: The server analyzes the received request and uses the NLP module to analyze the text, thereby extracting keywords and context.

[1717] 3. Database search: Based on the extracted keywords, the legal information database is searched to obtain relevant legal information.

[1718] 4. Answer generation: Based on the information obtained, a generative AI model (e.g., GPT-4) generates specific legal advice.

[1719] 5. Sending results: The generated answer is sent from the server to the device and displayed on the user's smartphone.

[1720] Prompt Sentence Examples

[1721] Prompt statement:

[1722] A user has asked a legal question: "What should I be careful of when purchasing real estate?" Please generate specific legal advice for this question based on the Six Codes and past legal precedents.

[1723] In this way, the system of the present invention allows users to receive appropriate legal advice quickly and at low cost, even if they do not have specialized legal knowledge.

[1724] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1725] Step 1:

[1726] The user enters a legal question or problem using a device. The user opens the application screen on their smartphone or tablet and enters the question in a text box. For example, they enter a question such as, "What should I pay attention to when purchasing real estate?" The input data is sent in text format from the device to the server.

[1727] Step 2:

[1728] The device sends the entered legal question to the server. The device generates an HTTP POST request and sends the request data, including the user's question, to the server. The request data format is typically JSON.

[1729] Step 3:

[1730] The server analyzes the received request. The server receives a POST request and extracts the user's input text from the request body. This extracted text data is sent to the Natural Language Processing (NLP) module.

[1731] Step 4:

[1732] The server's natural language processing (NLP) module analyzes the received input text. The NLP module uses tools such as SpaCy or NLTK to analyze and extract keywords and context from the text data. For example, it extracts keywords such as "real estate," "purchase," and "points to note." The results of this analysis are used as input for the next search step.

[1733] Step 5:

[1734] The server searches a legal information database based on the extracted keywords. The server uses a search engine such as Elasticsearch or Solr to retrieve relevant information from the Six Codes and past case law database. For example, it retrieves laws and past case law related to real estate purchases. The search results are sent to the answer generation module.

[1735] Step 6:

[1736] The server's answer generation module generates legal answers based on the search results. It uses a generative AI model (e.g., GPT-4) to construct specific legal advice for the user's question. For example, it generates an answer such as, "When purchasing real estate, we recommend that you carefully review the sales contract, register the property, and understand the mortgage terms." The generated answers are stored in JSON format.

[1737] Step 7:

[1738] The server sends the generated answer to the device. An HTTP response containing the generated legal advice is formed and sent to the device. The response data is formatted in JSON for easy user understanding.

[1739] Step 8:

[1740] The device displays the received response to the user. The received JSON format response data is analyzed and displayed on the application screen. The user can then check the legal advice on the device screen. For example, the following message may be displayed: "When purchasing real estate, it is recommended that you carefully review the sales contract, register the property, and understand the terms of the mortgage."

[1741] 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.

[1742] The present invention is a system that includes a terminal for a user to input a legal question or problem, a server that receives input from the terminal, means for analyzing the input using natural language processing, means for searching the Six Codes and a database of past case law, means for generating a legal answer based on the search results, and means for transmitting the generated answer to the terminal, and further combines it with an emotion engine that recognizes the user's emotions.

[1743] System configuration

[1744] 1. Terminal

[1745] A device that allows users to enter legal questions or issues and receive answers.

[1746] Specifically, this includes computers, smartphones, tablets, etc.

[1747] 2. Server

[1748] It acts as a central processing unit, receiving input from the terminals, analyzing the data, searching, generating and sending answers.

[1749] 3. Natural Language Processing (NLP) Module

[1750] It uses technology to analyze input text data and understand its meaning.

[1751] This includes processes such as keyword extraction, contextual analysis, and syntax analysis.

[1752] 4. Legal Information Database

[1753] This is a database that includes the complete collection of laws and past court cases.

[1754] The server searches this database to obtain the appropriate legal information.

[1755] 5. Emotion Engine

[1756] This module identifies the emotion contained in the user's input text.

[1757] It uses natural language processing technology to identify sentiment categories and tailor responses based on those sentiments.

[1758] 6. Answer Generation Module

[1759] Based on the search results and the output of the emotion engine, specific and emotionally sensitive answers to the user's questions are generated.

[1760] 7. Means of communication

[1761] Provides a means for sending and receiving data between the server and the terminal.

[1762] Specifically, HTTP requests and responses are used.

[1763] Program processing

[1764] Example: From user input to emotion recognition and answer generation

[1765] 1. User Input

[1766] The user uses the terminal to enter a specific legal question.

[1767] For example: "What should I do if I get fired and I didn't sign a contract?"

[1768] 2. Sending a request from the device to the server

[1769] The terminal that receives the user's input sends an API request to the server.

[1770] Example: Send an HTTP POST request containing the user's question.

[1771] 3. Data reception and analysis on the server

[1772] The server parses the received request and extracts the user's input text.

[1773] The NLP module analyzes the text and understands keywords and context.

[1774] For example, extract keywords such as "contract," "signature," and "dismissal."

[1775] 4. Emotion Recognition by Emotion Engine

[1776] The server uses an emotion engine to identify emotions contained in the user's input text.

[1777] Example: Detecting emotions such as "anxiety" or "anger" from user text.

[1778] 5. Legal Information Search

[1779] The server searches the complete collection of laws and a database of past legal precedents.

[1780] Use search algorithms to extract relevant legal information.

[1781] For example, obtain Article 15 of the Labor Contract Act and past legal precedents (Heisei XX year XX judgment).

[1782] 6. Answer Generation

[1783] Based on the search results and the output of the emotion engine, the answer generation module generates specific and emotion-sensitive answers.

[1784] Example: "Even if you haven't signed a contract, a labor contract may still be in place. Please don't worry. In cases like this, you can sue for unfair dismissal under Article 15 of the Labor Contract Act. In addition, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei)."

[1785] 7. Sending a response from the server to the device

[1786] The server generates an API response to return the generated answer to the terminal.

[1787] Example: Sending an HTTP response containing the generated answer to the terminal.

[1788] 8. Displaying answers on your device

[1789] The terminal analyzes the received response and displays it in a user-friendly format.

[1790] Example: Specific legal advice and relevant legal information displayed on the device screen, with a stable emotional expression.

[1791] 9. User Reference and Action Selection

[1792] The user decides on the next action based on the displayed answer.

[1793] Example: Choose whether to consult the Labor Standards Inspection Office or contact a lawyer.

[1794] In this way, the system of the present invention allows users to receive appropriate legal advice quickly and at low cost, even if they do not have specialized legal knowledge, and provides support that takes into consideration the user's feelings.

[1795] The processing flow will be explained below.

[1796] Step 1:

[1797] A user enters a legal question or issue.

[1798] For example, a user might use a terminal to type, "What should I do if I am fired but haven't signed a contract?"

[1799] Step 2:

[1800] The device generates an API request to send the user's input to the server.

[1801] For example, the device sends the following HTTP POST request to the server:

[1802] json

[1803] {

[1804] "question": "What should I do if I get fired without signing a contract?"

[1805] }

[1806] Step 3:

[1807] The server parses the received request and extracts the entered text.

[1808] It uses a natural language processing (NLP) module to analyze the meaning of the input text and identify relevant keywords and context.

[1809] For example, extract keywords such as "contract," "signature," and "dismissal."

[1810] Step 4:

[1811] The server uses an emotion engine to identify emotions contained in the user's input text.

[1812] Natural language processing technology is used to analyze emotions and identify emotion categories.

[1813] Example: Detecting emotions such as "anxiety" or "anger" from input text.

[1814] Step 5:

[1815] The server searches the complete collection of laws and a database of past legal precedents based on the extracted keywords and the identified emotions.

[1816] Using a search algorithm, relevant information such as "Article 15 of the Labor Contract Act" and "Past legal precedents (Heisei XX year XX judgment)" is extracted.

[1817] Step 6:

[1818] The server uses AI algorithms to generate answers to users' questions based on search results and sentiment data.

[1819] The generated responses include a tone and expression that takes into consideration the user's feelings.

[1820] Example: "Even if you haven't signed a contract, a labor contract may still be in place. Please don't worry. In cases like this, you can sue for unfair dismissal under Article 15 of the Labor Contract Act. In addition, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei)."

[1821] Step 7:

[1822] The server generates an API response to return the generated answer to the device.

[1823] Example: Send an HTTP response containing the generated answer to the terminal:

[1824] json

[1825] {

[1826] "answer": "Even if you haven't signed a contract, a labor contract may still be in place. Please don't worry. In such cases, you can file a lawsuit for unfair dismissal under Article 15 of the Labor Contract Act. In addition, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei)."

[1827] }

[1828] Step 8:

[1829] The terminal analyzes the response received from the server and displays it in a format that is easy for the user to understand.

[1830] Specific legal advice and relevant legal information are displayed on the device screen, along with a stable emotional response.

[1831] Example: "Even if you haven't signed a contract, a labor contract may still be in place. Please don't worry. In cases like this, you can sue for unfair dismissal under Article 15 of the Labor Contract Act. In addition, there have been cases in the past where employees have won lawsuits (such as the XX judgment in XX year of Heisei)."

[1832] Step 9:

[1833] The user decides on the next action based on the displayed answer.

[1834] For example, you can choose to consult the Labor Standards Inspection Office or contact a lawyer.

[1835] Example 2

[1836] 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."

[1837] While conventional legal question-answering systems can provide appropriate legal answers based on the user's input text, they often find it difficult to provide answers that take the user's emotions into consideration, which can lead to anxiety and stress. Furthermore, the accuracy of legal information searches and the specificity of answers are often insufficient, and these systems often fail to help users decide on their next course of action.

[1838] 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.

[1839] In this invention, the server includes emotion recognition means for identifying emotions contained in the user's input text, means for adjusting a response based on the emotions identified by the emotion recognition means, and means for searching the Six Codes and a database of past legal precedents, thereby making it possible to propose specific actions to address legal issues while taking the user's emotions into consideration.

[1840] A "terminal" is an information processing device such as a computer, smartphone, or tablet that a user uses to enter input and receive responses.

[1841] A "server" is a central processing unit that receives input from terminals, analyzes data, searches, generates and transmits answers.

[1842] "Natural language processing" is a technology that analyzes text data entered by a user and understands its meaning, and includes keyword extraction and context analysis.

[1843] The "Roppo Zensho and Past Case Law Database" is a database that stores legal information, including the Roppo Zensho and past case law.

[1844] "Emotion recognition means" is a technology that identifies the user's emotions contained in the input text and identifies emotion categories such as anxiety or anger.

[1845] The "means for adjusting an answer" is a technology for adjusting the content and expression of an answer that is generated based on the emotion identified by the emotion recognition means.

[1846] The "answer generation means" is a technology that creates specific and emotion-sensitive responses to user questions based on search results and emotion recognition results.

[1847] "Communication means" refers to the technology for sending and receiving data between the server and the terminal, specifically using HTTP requests and responses.

[1848] An "API request" is a data request sent from a terminal to a server, and is sent in a format that includes the user's input.

[1849] An "HTTP response" is a data response sent from a server to a terminal, and is sent in a format that includes a generated answer.

[1850] MODE FOR CARRYING OUT THE INVENTION

[1851] The present invention is a system that includes a terminal for a user to input a legal question or problem, a server that receives input from the terminal, means for analyzing the input using natural language processing, means for searching the Six Codes and a database of past case law, means for generating a legal answer based on the search results, and means for transmitting the generated answer to the terminal, and further combines it with an emotion engine that recognizes the user's emotions.

[1852] The configuration for implementing this is as follows.

[1853] 1. Terminal

[1854] A device that allows a user to enter legal questions or issues and receive answers, such as a computer, smartphone, or tablet.

[1855] 2. Server

[1856] It acts as a central processing unit, receiving input from the terminals, analyzing the data, searching, generating and sending answers.

[1857] 3. Natural Language Processing (NLP) Module

[1858] It uses technology to analyze input text data and understand its meaning, including processes such as keyword extraction, contextual analysis, and syntax analysis.

[1859] 4. Legal Information Database

[1860] This is a database containing the complete collection of laws and past legal precedents. The server searches this database to retrieve the appropriate legal information.

[1861] 5. Emotion Engine

[1862] This module identifies the sentiment contained in the user's input text, using natural language processing techniques to identify sentiment categories and tailor responses based on those sentiments.

[1863] 6. Answer Generation Module

[1864] Based on the search results and the output of the emotion engine, specific and emotionally sensitive answers to the user's questions are generated.

[1865] 7. Means of communication

[1866] It provides a means to send and receive data between the server and the terminal, specifically using HTTP requests and responses.

[1867] Specific examples

[1868] The user uses the device to input a legal question, such as "What should I do if I'm fired without signing a contract?" The device receives this input and sends an HTTP POST request to the server. The server analyzes the received request and uses an NLP module to analyze the text data. At the same time, an emotion engine detects emotions such as "anxiety" or "anger" from the user's input.

[1869] The server then searches the Six Codes and a database of past legal precedents to obtain relevant legal information. For example, it references Article 15 of the Labor Contract Act and past legal precedents (Heisei XX Year XX Judgment). Based on the search results and the output of the emotion engine, the answer generation module generates specific legal advice. The server sends the generated answer to the terminal as an HTTP response, and the terminal displays it to the user.

[1870] Prompt Sentence Examples

[1871] An example of a user-provided prompt is, "What should I do if I'm fired without signing a contract? Emotion: Anxiety." This prompt allows the generative AI model to provide specific, emotionally sensitive advice on a particular legal issue.

[1872] According to the above embodiment, users can obtain appropriate legal advice quickly and at low cost even if they do not have specialized legal knowledge, and can also receive support that takes into consideration the feelings of the users.

[1873] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1874] Program processing flow

[1875] Step 1: User enters legal question into terminal

[1876] The user enters a legal question or problem into the terminal.

[1877] Specific behavior:

[1878] A user types a question into an input field on a terminal, such as "What should I do if I am fired but have not signed a contract?"

[1879] input:

[1880] The text of the user's legal question.

[1881] output:

[1882] The entered question text.

[1883] Step 2: Sending a request from the device to the server

[1884] The terminal generates an HTTP POST request to send the user's question to the server.

[1885] Specific behavior:

[1886] The device converts the entered question text into JSON format and sends an HTTP POST request to the API endpoint.

[1887] input:

[1888] The text of the user's legal question.

[1889] output:

[1890] An HTTP POST request in JSON format.

[1891] Step 3: Receiving and analyzing data on the server

[1892] The server receives requests from the device, extracts text data, and passes the extracted text data to a natural language processing (NLP) module for analysis.

[1893] Specific behavior:

[1894] The server extracts the JSON payload from the HTTP request, and the NLP module extracts keywords such as "contract," "signature," and "dismissal."

[1895] input:

[1896] HTTP POST request.

[1897] output:

[1898] Extracted keywords and contextual information.

[1899] Step 4: Emotion Recognition with the Emotion Engine

[1900] The server passes the text analyzed by the NLP module to the emotion engine to identify the user's emotion.

[1901] Specific behavior:

[1902] The server uses an emotion engine to identify emotions such as "anxiety" or "anger."

[1903] input:

[1904] Text data analyzed by the NLP module.

[1905] output:

[1906] Identified emotional information (e.g., anxiety).

[1907] Step 5: Find legal information

[1908] The server searches the complete collection of laws and a database of past court cases to obtain relevant legal information.

[1909] Specific behavior:

[1910] The server executes a database query to search for legal provisions and precedents related to "contract" and "dismissal," and retrieves Article 15 of the Labor Contract Act and the XX judgment of Heisei XX year.

[1911] input:

[1912] Extracted keywords and contextual information.

[1913] output:

[1914] Legal information obtained (e.g., legal texts, case law).

[1915] Step 6: Generate an answer

[1916] The server uses the answer generation module to generate a specific answer for the user based on the acquired legal information and the results of the emotion engine.

[1917] Specific behavior:

[1918] The server generates a response such as, "Even if you haven't signed the contract, a labor contract may still be in place. Please don't worry. In such cases, you can sue for wrongful dismissal under Article 15 of the Labor Contract Act. In addition, there have been cases in the past where employees have won the case (such as the XX judgment in XX year of Heisei)."

[1919] input:

[1920] Legal information obtained, emotional information identified.

[1921] output:

[1922] The specific answer text generated.

[1923] Step 7: Sending the response from the server to the device

[1924] The server sends an HTTP response containing the generated answer to the terminal.

[1925] Specific behavior:

[1926] The server converts the generated answer into JSON format and sends it back to the device as an HTTP response.

[1927] input:

[1928] The generated answer text.

[1929] output:

[1930] The HTTP response in JSON format.

[1931] Step 8: View your answers on your device

[1932] The terminal analyzes the received response and displays it in a user-friendly format.

[1933] Specific behavior:

[1934] The terminal parses the JSON response and displays the following message: "Even if you have not signed the contract, an employment contract may still be in place. Please do not worry. In such cases, you can sue for wrongful dismissal under Article 15 of the Labor Contract Act. In addition, there have been past court cases (Heisei XX year XX judgment) in which employees have won the case."

[1935] input:

[1936] JSON response.

[1937] output:

[1938] The specific answer that is displayed to the user.

[1939] Step 9: Viewing Users and Selecting Actions

[1940] The user will refer to the displayed answer to decide on the next action.

[1941] Specific behavior:

[1942] The user reads the displayed legal advice and selects a next action, such as consulting the Labor Standards Inspection Office or contacting a lawyer.

[1943] input:

[1944] The displayed answer.

[1945] output:

[1946] The user's next action (e.g., consult the Labor Standards Inspection Office, contact a lawyer).

[1947] (Application example 2)

[1948] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1949] Conventional legal support systems make it difficult for users to receive prompt and appropriate legal advice when they face legal problems, and one of the challenges is that they do not take emotions into consideration. Furthermore, because the user's mental state is often an important factor in security-related legal issues, insufficient recognition and response to emotions can further exacerbate anxiety and confusion. Therefore, to solve these problems, a legal support system that can also provide emotional support is needed.

[1950] 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 analyzing a user's input using natural language processing, means for searching the Six Codes Collection and a database of past case law, means for generating a legal answer based on the search results, means including an emotion engine for recognizing the user's emotions, and means for adjusting the answer based on the user's emotions. This not only enables a user to receive prompt and appropriate legal advice when faced with a legal problem, but also makes it possible to provide support that takes the user's emotions into consideration.

[1951] A "terminal" is a device through which a user can enter legal questions or issues and receive answers.

[1952] A "server" is a central processing unit that receives input from terminals, analyzes data, searches, generates and transmits answers.

[1953] "Natural language processing" is a technology that analyzes input text data and understands its meaning.

[1954] The "Roppo Zensho" is a legal book that compiles the six basic laws of Japan.

[1955] A "case law database" is a database that stores past court decisions in a searchable format.

[1956] The "emotion engine" is a module that identifies emotions contained in the user's input text.

[1957] "Answer generation" is the process of creating specific and emotionally sensitive answers to users' questions based on search results and the output of the emotion engine.

[1958] "Search results" are relevant legal information obtained from the Six Codes and case law databases.

[1959] "Communication means" refers to the means for sending and receiving data between the server and the terminal.

[1960] The present invention is a system including a terminal for a user to input a legal question or problem, a server that receives input from the terminal, means for analyzing the input using natural language processing (NLP), means for searching the Six Codes and a database of past case law, means for generating a legal answer based on the search results, and means for transmitting the generated answer to the terminal. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions, and also includes means for adjusting the answer based on the user's emotions.

[1961] System Overview

[1962] 1. Device:

[1963] A device that allows a user to enter legal questions or issues and receive answers, including smartphones, tablets, and personal computers.

[1964] 2. Server:

[1965] It acts as a central processing unit, receiving input from the terminals, analyzing the data, searching, generating and sending answers.

[1966] 3. Natural Language Processing (NLP) Module:

[1967] It is a technology that analyzes input text data and understands its meaning. For example, it uses libraries such as spaCy and NLTK to extract keywords and context from the text.

[1968] 4. Legal Information Database:

[1969] This is a database containing the complete collection of laws and past legal precedents. The server searches this database to retrieve the appropriate legal information. Database management systems such as MySQL and PostgreSQL can be used.

[1970] 5. Emotion Engine:

[1971] This module identifies the sentiment contained in the user's input text and includes a sentiment analysis model built using TensorFlow and PyTorch.

[1972] 6. Answer Generation Module:

[1973] Generate specific, sentiment-sensitive answers based on search results and the output of the sentiment engine. Use generative AI models to create the best legal advice for your question.

[1974] 7. Means of communication:

[1975] It is a means for sending and receiving data between a server and a terminal. Specifically, API communication is performed using HTTP requests and responses.

[1976] System details process

[1977] User Input

[1978] A user uses a terminal to enter a specific legal question, such as "How do I handle a security breach?" into a text field.

[1979] Data processing on the server

[1980] When data is sent from a device to a server, a natural language processing module first analyzes the input text, extracts keywords and context, and generates data that can be used as a search criteria.

[1981] emotion recognition

[1982] The analyzed text data is processed by an emotion engine to identify the user's emotions, such as "anxiety" or "anger."

[1983] Search for legal information and generate answers

[1984] The system searches for relevant information in the complete collection of laws and case law databases, and the answer generation module generates specific, emotion-sensitive answers based on the output of the emotion engine.

[1985] Submitting and viewing responses

[1986] The generated answer is sent from the server to the terminal and displayed on the user's terminal, allowing the user to refer to the answer and select the next action.

[1987] Prompt Sentence Examples

[1988] A user opens a smartphone app and types, "How do I handle a security-related breach of contract?" This question is sent to the server, where the NLP module extracts the keywords "security" and "breach of contract." At the same time, the emotion engine detects "anxiety" from the user's text. Relevant information is searched for in the legal database, and an appropriate, emotion-sensitive answer is generated based on that information and the detected emotion.

[1989] Example prompt sentence:

[1990] The user asked, "How do I handle a security breach?" This question contains the emotion "anxiety." Use this information to generate appropriate legal advice. Include specific laws and legal precedents in your answer.

[1991] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1992] Step 1:

[1993] The user inputs a question into a terminal for inputting legal questions or issues. For example, the user might input, "Please tell me how to deal with a security-related contract violation." The terminal collects this text data and prepares it for transmission to the server.

[1994] Input: The question text that the user types into the terminal.

[1995] Output: JSON formatted data to send to the server.

[1996] Step 2:

[1997] The device receives the user's input and sends the data as an HTTP POST request to a specific API endpoint, which includes the user's question.

[1998] Input: JSON data containing the user's question.

[1999] Output: The HTTP POST request received by the server.

[2000] Step 3:

[2001] The server receives the HTTP POST request and begins data analysis. It uses a natural language processing (NLP) module to extract keywords and context from the question text.

[2002] Input: The user's question text.

[2003] Output: Extracted keywords and contextual data.

[2004] Step 4:

[2005] The server uses the extracted data to run an emotion engine to identify emotions from the user's text, such as "anxiety" or "anger."

[2006] Input: Keywords and contextual data.

[2007] Output: The detected emotion.

[2008] Step 5:

[2009] The server searches a legal information database based on keywords. The database contains the complete collection of laws and past legal precedents. The server extracts relevant legal information.

[2010] Input: Keyword data.

[2011] Output: The legal information search results.

[2012] Step 6:

[2013] The server uses the answer generation module to generate appropriate legal answers based on the extracted legal information and the output of the emotion engine, and uses the generative AI model to provide specific advice that takes the user's emotions into consideration.

[2014] Input: Search results and sentiment data.

[2015] Output: The generated legal answer.

[2016] Step 7:

[2017] The server sends the generated answer to the device as an API response, which contains specific legal advice in response to the user's question.

[2018] Input: The generated legal response.

[2019] Output: The API response received by the device.

[2020] Step 8:

[2021] The device analyzes the received answers and displays them in a user-friendly format, for example, using text or visual aids to help the user select the next action.

[2022] Input: Legal Answer received as API response.

[2023] Output: Specific legal advice and related information displayed to the user.

[2024] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2025] 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.

[2026] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2027] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2028] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2029] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2030] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2031] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2032] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2033] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2034] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2035] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2036] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2037] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2038] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2039] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2040] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2041] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2042] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2043] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2044] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2045] The following is further disclosed regarding the above embodiment.

[2046] (Claim 1)

[2047] a terminal for a user to input legal questions or issues;

[2048] a server that receives input from the terminal;

[2049] means for analyzing the input using natural language processing;

[2050] A means to search the complete collection of laws and past case law databases,

[2051] means for generating a legal response based on the search results;

[2052] means for transmitting the generated answer to the terminal.

[2053] (Claim 2)

[2054] 2. The system of claim 1, wherein the natural language processing comprises analyzing the meaning of input text and extracting keywords.

[2055] (Claim 3)

[2056] 10. The system of claim 1, wherein the server further comprises means for suggesting specific actions regarding the user's legal issue based on the search results.

[2057] "Example 1"

[2058] (Claim 1)

[2059] an information terminal for a user to input legal questions or issues;

[2060] a processing device that receives input from the information terminal;

[2061] means for analyzing the input using natural language processing;

[2062] a means of searching legal documents and case law databases;

[2063] means for generating a legal response based on the search results;

[2064] means for transmitting the generated response to the information terminal;

[2065] The system further includes means for displaying the answer received by the information terminal to the user.

[2066] (Claim 2)

[2067] 2. The system of claim 1, wherein the natural language processing comprises analyzing the meaning of input text and extracting keywords.

[2068] (Claim 3)

[2069] 10. The system of claim 1, wherein the processing unit further comprises means for suggesting specific actions regarding the user's legal matter based on the search results.

[2070] "Application Example 1"

[2071] (Claim 1)

[2072] a terminal for a user to input legal questions or issues;

[2073] a server that receives input from the terminal;

[2074] means for analyzing the input using natural language processing;

[2075] A means to search the complete collection of laws and past case law databases,

[2076] means for generating a legal response based on the search results;

[2077] means for transmitting the generated response to the terminal;

[2078] A system including a smart device running a program for providing legal advice.

[2079] (Claim 2)

[2080] 2. The system of claim 1, wherein the natural language processing comprises analyzing the meaning of input text and extracting keywords.

[2081] (Claim 3)

[2082] 10. The system of claim 1, wherein the server further comprises means for suggesting specific actions regarding the user's legal issue based on the search results.

[2083] "Example 2: Combining Emotion Engines"

[2084] (Claim 1)

[2085] a terminal for a user to input legal questions or issues;

[2086] a server that receives input from the terminal;

[2087] means for analyzing the input using natural language processing;

[2088] A means to search the complete collection of laws and past case law databases,

[2089] means for generating a legal response based on the search results;

[2090] means for transmitting the generated response to the terminal;

[2091] an emotion recognition means for identifying emotions contained in a user's input text;

[2092] The system includes means for tailoring a response based on the emotion identified by the emotion recognition means.

[2093] (Claim 2)

[2094] 2. The system of claim 1, wherein the natural language processing comprises analyzing the meaning of input text and extracting keywords.

[2095] (Claim 3)

[2096] 10. The system of claim 1, wherein the server further comprises means for suggesting specific actions regarding the user's legal issue based on the search results.

[2097] "Application example 2 when combining emotion engines"

[2098] (Claim 1)

[2099] a terminal for a user to input legal questions or issues;

[2100] a server that receives input from the terminal;

[2101] means for analyzing the input using natural language processing;

[2102] A means to search the complete collection of laws and past case law databases,

[2103] means for generating a legal response based on the search results;

[2104] means for transmitting the generated response to the terminal;

[2105] means including an emotion engine for recognizing the emotion of the user;

[2106] The system includes means for adjusting responses based on the user's emotions.

[2107] (Claim 2)

[2108] 2. The system of claim 1, wherein the natural language processing comprises analyzing the meaning of input text and extracting keywords.

[2109] (Claim 3)

[2110] 2. The system of claim 1, wherein the server further comprises means for suggesting specific actions regarding the user's legal issue based on the search results, and means for adjusting the content of the suggestions based on the user's emotions detected by the emotion engine. [Explanation of symbols]

[2111] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a terminal for a user to input a legal question or problem; a server that receives input from the terminal; means for analyzing the input using natural language processing; A means to search the complete collection of laws and past case law databases, means for generating a legal response based on the search results; means for transmitting the generated answer to the terminal.

2. The system of claim 1 , wherein the natural language processing includes analyzing the meaning of input text and extracting keywords.

3. The system of claim 1 , wherein the server further comprises means for suggesting specific actions regarding the user's legal issue based on the search results.

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