System

Abstract

A system is provided.SOLUTION: A system, comprising: means for a user to input a legal question; means for a terminal to transmit the user's input data to a server; means for the server to analyze the received question and identify a legal category associated with a key keyword; means for the server to refer to a database storing legal information and past precedents and obtain specific legal information; means for the server to generate an answer to the user's question based on the obtained legal information; and means for the terminal to transmit the generated answer to the terminal.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In modern society, legal problems arise on a daily basis, but most of them are minor. Because consulting a legal expert is costly and time-consuming, many people try to resolve their problems themselves. However, because they lack general legal knowledge and prior legal precedents, it can be difficult to find an appropriate solution. Therefore, there is a need to provide a means for users to quickly and easily resolve familiar legal problems. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system including a means for a user to input a legal question, a means for a terminal to transmit the user's input data to a server, a means for the server to analyze the received question and identify legal categories associated with key keywords, a means for the server to obtain specific legal information by referencing a database storing legal information and past precedents, a means for the server to generate an answer to the user's question based on the obtained legal information, a means for the server to transmit the generated answer to the terminal, and a means for the terminal to display the answer from the server to the user. This system allows users to quickly and accurately obtain information on everyday legal issues without having to rely on experts.

[0006] "User" refers to a person who enters a legal question into the system and receives a response.

[0007] "Terminal" refers to a device (such as a smartphone or computer) through which a user enters legal questions and sends those questions to a server.

[0008] "Server" refers to a central management system that receives and analyzes user questions, obtains legal information, and generates and transmits answers.

[0009] A "question" refers to a specific legal question that a user enters into the system via a terminal.

[0010] "Keywords" refer to important words or phrases extracted by analyzing a user's question.

[0011] "Legal category" refers to the field or subject of law related to the extracted keywords.

[0012] "Database" refers to a collection of information that stores legal information and past case law information and that can be searched and referenced by the server.

[0013] "Legal information" refers to documented legal knowledge, such as legal provisions and legal principles, that solves specific problems.

[0014] "Past precedents" refer to cases of legal issues that have been resolved in court in the past and the content of the decisions made.

[0015] "Answer" refers to legal information or advice that the server generates in response to a user's question and provides to the user. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

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

[0026] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] The present invention provides a system for users to quickly and effectively resolve common legal issues. The system involves users inputting legal questions via a terminal, and a server providing appropriate answers to those questions.

[0038] Program processing overview

[0039] The user enters a question

[0040] The user enters a legal question into a form on the device. The user can enter a specific legal issue or question.

[0041] The device sends a question to the server

[0042] The terminal sends the entered question data to the server using a communication protocol (e.g., HTTP POST) over the Internet.

[0043] The server receives and analyzes the query.

[0044] The server receives the question data sent by the user and stores it in a database.

[0045] Next, natural language processing technology is used to analyze the question and identify key keywords and associated legal categories.

[0046] The server references legal information and past cases

[0047] The server accesses an internal database that searches for legal information and past cases based on the identified keywords and legal categories. This database contains legal provisions, legal commentary documents, and past court records.

[0048] The server generates the answer

[0049] The server uses the acquired legal information and case law to generate specific answers to the user's questions, written in a clear and easy-to-understand format.

[0050] The server sends the answer to the device

[0051] The server then sends the generated answer to the user's device, where it is converted into a format suitable for display on the user interface.

[0052] The device displays the answer

[0053] The device displays the answer received from the server on the screen, and the user can check the displayed answer and use it as a reference for solving the problem.

[0054] Specific examples

[0055] Below is a specific example of use based on the above processing flow.

[0056] 1. The user enters a question

[0057] The user operates a terminal (e.g., a smartphone) and enters, "Will there be a penalty if I terminate the rental contract midway?"

[0058] 2. The device sends a question to the server

[0059] The smartphone application sends the entered question data to the server via an HTTP POST request.

[0060] 3. The server receives and analyzes the query

[0061] The server receives the question data and uses natural language processing technology to extract important keywords such as "rental contract," "mid-term termination," and "penalty fee."

[0062] 4. The server references legal information and past cases

[0063] The server queries its internal database to search for relevant information based on the extracted keywords, resulting in the acquisition of legal provisions and past legal precedents related to rental contracts.

[0064] 5. The server generates the answer

[0065] Based on the information it has obtained, the server generates the following response: "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord's illegal activity is not involved."

[0066] 6. The server sends the answer to the device

[0067] The server sends the generated answer to the terminal as an HTTP response.

[0068] 7. The device will display the answer

[0069] The smartphone application receives the response and displays the following message on the screen: "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the termination does not involve illegal activity by the landlord."

[0070] This system allows users to easily and quickly obtain accurate information about legal issues without having to consult a legal professional, thus enabling users to deal with legal issues that arise in their daily lives.

[0071] The processing flow will be explained below.

[0072] Step 1:

[0073] A user uses a terminal to input a legal question into an input form. For example, the user inputs, "Are there any penalties if I terminate a rental contract early?"

[0074] Step 2:

[0075] The terminal sends the entered question data to the server using a communication protocol (e.g., HTTP POST) over the Internet.

[0076] Step 3:

[0077] The server receives the question data sent by the user and stores it in a database.

[0078] Step 4:

[0079] The server uses natural language processing (NLP) technology to analyze the received question, specifically extracting key keywords such as "rental contract," "mid-term termination," and "penalty."

[0080] Step 5:

[0081] Based on the extracted keywords, the server will refer to its internal database to identify relevant legal categories, for example, searching for laws and precedents related to "rental agreements."

[0082] Step 6:

[0083] The server searches an internal database of legal information and past case law data to retrieve specific information related to the user's question.

[0084] Step 7:

[0085] The server generates answers to user questions based on legal information and past precedents. Answers may include specific legal provisions and past precedents. For example, it may generate an answer such as, "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord's illegal actions are not included."

[0086] Step 8:

[0087] The server generates a response and sends it to the terminal, again using a communication protocol (e.g., HTTP response).

[0088] Step 9:

[0089] The terminal displays the answer received from the server to the user. The user interface is updated to display the answer in a format that is easy for the user to understand. For example, it may say, "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord's illegal activity is not involved."

[0090] Example 1

[0091] 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."

[0092] Conventional legal problem-solving systems have had issues such as delayed responses to user questions and the high cost of expert consultations. Furthermore, it is difficult for users without specialized legal knowledge to gather appropriate information on their own. This has led to a demand for a means for general users to quickly and effectively resolve legal problems.

[0093] 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.

[0094] In this invention, the server includes a means for storing received question data in a database, a means for analyzing the question using a natural language processing engine and extracting key keywords, and a means for generating answers using a generative AI model, thereby enabling the server to quickly and accurately generate and provide answers to user questions.

[0095] "User" means any person or entity that enters a legal question into the system.

[0096] "Terminal" refers to the electronic device used by the user to input questions and communicate with the server. Examples include smartphones, tablets, and personal computers.

[0097] "Server" refers to a central computing system that receives, analyzes, and generates answers to user-submitted question data.

[0098] "Question data" refers to legal inquiries entered by a user using a terminal.

[0099] "Database" refers to a collection of information accessed by a server that stores legal information and past court decisions.

[0100] A "natural language processing engine" refers to software technology for analyzing question data and extracting key keywords.

[0101] A "generative AI model" refers to an artificial intelligence technology that generates specific answers to users' questions based on acquired legal information.

[0102] "HTTPS" refers to a communication protocol for secure data communication between a terminal and a server.

[0103] "HTTP POST request" refers to a specific Internet protocol used to send query data from a terminal to a server.

[0104] "HTTP response" refers to a specific Internet protocol used to send response data from a server to a terminal.

[0105] "User interface" refers to an interactive display screen for interaction between a user and a terminal.

[0106] MODE FOR CARRYING OUT THE INVENTION

[0107] The present invention is a system for enabling users to quickly and effectively resolve common legal issues. The system is configured so that users input legal questions via a terminal, and a server provides appropriate answers to those questions. Specific embodiments for implementing the present invention are described below.

[0108] Hardware and software used

[0109] Devices: Electronic devices such as smartphones, tablets, and PCs

[0110] Server: A computing system equipped with a high-performance database and natural language processing engine.

[0111] Database: A collection of information containing legal documents and past court decisions

[0112] Natural language processing engine: Software technology for analyzing questions and extracting necessary information (e.g., SpaCy, BERT model)

[0113] Generative AI model: Artificial intelligence technology that generates specific answers based on acquired legal information

[0114] Processing flow

[0115] A user uses a device to input a legal question. The input data is sent from the device to a server via an HTTP POST request. The server stores the received question data in a database and analyzes it using a natural language processing engine. The server identifies key keywords and related legal categories and searches for relevant information in a database that contains legal provisions, legal commentaries, and past court records.

[0116] Based on the acquired information, the server uses a generative AI model to generate a specific answer to the user's question. The generated answer is sent from the server to the device as an HTTP response, and the device converts it into a format suitable for the user interface and displays it so that the user can check it.

[0117] Specific examples

[0118] Below is a specific example of use based on the above processing flow.

[0119] 1. The user enters a question

[0120] The user operates a terminal (e.g., a smartphone) and enters, "Will there be a penalty if I terminate the rental contract midway?"

[0121] 2. The device sends a question to the server

[0122] The smartphone application sends the entered question data to the server via an HTTP POST request, using the HTTPS protocol to ensure secure data transmission.

[0123] 3. The server parses the question

[0124] The server stores the received question data in a database and analyzes the question using a natural language processing engine (e.g., SpaCy, BERT model) to extract keywords such as "rental contract," "early termination," and "penalty fee."

[0125] 4. The server references legal information and past cases

[0126] The server accesses an internal database and searches for relevant legal documents and past cases based on the extracted keywords.

[0127] 5. The server generates the answer

[0128] The server uses a generative AI model to generate specific answers based on the information it receives.

[0129] For example: "In a rental agreement, if you terminate the agreement early, you may be subject to a penalty if it is clearly stated in the agreement. However, this only applies if the landlord's illegal actions are not involved."

[0130] 6. The server sends the answer to the device

[0131] The server generates an answer and sends it to the device as an HTTP response, which contains the answer formatted in the appropriate format.

[0132] 7. The device will display the answer

[0133] The smartphone application receives the response and displays the following message on the screen: "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the termination does not involve illegal activity by the landlord."

[0134] This system allows users to quickly and effectively obtain accurate information on legal issues without having to rely on a specialist, and also allows users to easily acquire knowledge to deal with legal issues that arise in their daily lives.

[0135] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0136] Step 1:

[0137] User enters legal question

[0138] The user opens a dedicated application or web interface on their device (e.g., smartphone, PC) and enters their question into the input form.

[0139] Input data: Legal questions entered by the user (e.g., "Are there any penalties for breaking a lease early?")

[0140] Output: Question data entered by the user

[0141] Step 2:

[0142] The device sends a question to the server

[0143] The device packages the entered question data in JSON format and sends it to the server via an HTTP POST request, using HTTPS to ensure secure communication.

[0144] Input data: Question data converted to JSON format

[0145] Output: HTTP POST request sent to the server

[0146] Step 3:

[0147] The server receives and analyzes the query.

[0148] The server parses the received HTTP POST request, extracts and saves the question data, and then uses a natural language processing engine (e.g., SpaCy, BERT model) to analyze the question and extract key keywords (e.g., "rental agreement," "early termination," "penalty fee").

[0149] Input data: Question data in an HTTP POST request

[0150] Data processing: Analysis of question data, extraction of important keywords

[0151] Output: Extracted keywords

[0152] Step 4:

[0153] The server references legal information and past cases

[0154] The server then uses the extracted keywords to query an internal database that contains legal provisions, legal commentaries, and past legal precedents to find relevant legal documents and past cases.

[0155] Input data: extracted keywords

[0156] Data processing: querying databases and searching for relevant information

[0157] Output: Relevant legal documents, provisions, and past cases

[0158] Step 5:

[0159] The server generates the answer

[0160] The server uses a generative AI model to generate specific answers based on the legal information it receives, and formats the answers in a way that is easy for users to understand.

[0161] Input data: relevant legal documents, statutes, and past precedents

[0162] Data processing: Generate answers and convert formats using AI models

[0163] Output: The specific answer generated

[0164] Step 6:

[0165] The server sends the answer to the device

[0166] The server packages the generated response in JSON format and sends it to the terminal as an HTTP response, again using the HTTPS protocol to ensure communication security.

[0167] Input data: Generated answers

[0168] Data processing: conversion to JSON format, generation of HTTP response

[0169] Output: HTTP response sent to the device

[0170] Step 7:

[0171] The device displays the answer

[0172] The device analyzes the received HTTP response and converts the response data into a format suitable for the user interface (e.g., HTML, in-app display format), and displays it. The user can check the response on the screen.

[0173] Input data: Response data in the HTTP response

[0174] Data processing: converting data into a format suitable for the user interface

[0175] Output: The answer displayed in the user interface

[0176] (Application example 1)

[0177] 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."

[0178] There is a need for fast and effective responses to legal issues in brick-and-mortar stores, but currently, it is difficult for store staff without legal expertise to provide appropriate answers. Furthermore, there is a lack of means to obtain immediate and accurate answers to customers' legal problems, so problems often take a long time to resolve. To solve these problems, a legal response system that can be easily used in stores is needed.

[0179] 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.

[0180] In this invention, the server includes: means for a user to input a legal question; means for a terminal to transmit the user's input data to the server; means for the server to analyze the received question and identify legal categories associated with major keywords; means for the server to reference a database storing legal information and past precedents and acquire specific legal information; means for the server to generate an answer to the user's question based on the acquired legal information; means for the server to transmit the generated answer to the terminal; means for the terminal to display or output the answer from the server as voice to the user; means for the tablet terminal, smartphone, or robot to input the legal question by voice or text; and means for the tablet terminal, smartphone, or robot to transmit the question data to the server. This enables users to ask legal questions using simple input means and receive accurate answers immediately.

[0181] A "User" is any person or entity that utilizes the System to enter legal questions and receive answers.

[0182] "Terminal" refers to a device that allows a user to input legal questions and transmit the input data to a server, including a tablet, smartphone, or robot.

[0183] A "server" is a computer system that analyzes questions received from users, generates answers based on legal information and past precedents, and sends them to terminals.

[0184] A "database" is a storage system that stores legal information and past precedents, which the server references to obtain the necessary information.

[0185] "Natural language processing technology" is a technology that allows the server to analyze the user's question and identify key keywords and related legal categories.

[0186] A "tablet" is a handheld computing device used by users to voice or text legal questions.

[0187] A "smartphone" is a mobile phone-type multifunction device used by users to voice or text legal questions.

[0188] A "robot" is a mechanical device used by users to voice or text legal questions.

[0189] "Voice input" is a method in which a user voices legal questions into a microphone.

[0190] "Text entry" is a method in which a user enters legal questions as text via a keyboard or touchscreen.

[0191] First, we will explain in detail the main components that make up the system for realizing this invention. The entire system utilizes terminals used by users, a server that processes data, and appropriate software to operate these in conjunction with each other.

[0192] Hardware used

[0193] The hardware used in this system is as follows:

[0194] Tablet devices: Used by users to dictate or text legal questions.

[0195] Smartphones: Used by users to dictate or text legal questions.

[0196] Interactive robots: used by users to voice or text legal questions.

[0197] Software used

[0198] The main software and technologies used in this system are as follows:

[0199] Flask: A Python web framework used to handle server-side HTTP requests and responses.

[0200] Transformers: A natural language processing library developed by Hugging Face that uses a question-answering (QnA) model to generate answers to questions.

[0201] Natural Language Processing Technology (NLP): Used by the server to analyze the questions received from the user and identify key keywords and relevant legal categories.

[0202] Data Flow and Processing

[0203] A user enters a legal question into a device (tablet, smartphone, or robot) using either voice or text input. The device then sends the user's input to a server. This communication typically occurs over the internet using an HTTP POST request.

[0204] The server analyzes the received query using NLP techniques to identify key keywords and associated legal categories, then accesses a database to search for legal information and past cases based on the specific keywords and legal categories.

[0205] Based on the legal information acquired by the server, a specific answer to the user's question is generated using a question-answering (QnA) model from the Transformers library.

[0206] The generated answer is sent from the server to the terminal, which displays or speaks the answer to the user, thereby providing the user with an immediate and accurate answer to their legal question.

[0207] Specific examples

[0208] For example, if a customer asks an interactive robot, "What should I do if my credit card is fraudulently used?", the question is entered as follows:

[0209] What to do if your credit card is fraudulently used?

[0210] The server receives and analyzes this question, retrieving relevant legal information and precedents from a database. For example, it extracts keywords such as "credit card," "fraudulent use," and "how to deal with it," and searches relevant legal provisions and past precedents. As a result, the server generates an answer like this:

[0211] If your credit card has been used fraudulently, first contact your card company and ask them to investigate the fraud. You should also file a police report and consider changing your password to prevent the leaking of personal information.

[0212] This generated answer is immediately provided to the user, allowing even store staff and customers who are not familiar with the law to quickly deal with legal issues.

[0213] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0214] Step 1:

[0215] The user inputs legal questions into a device (tablet, smartphone, or robot) by voice or text input. The input data is saved in the device as text data of the question.

[0216] Step 2:

[0217] The device sends the entered question data to the server using an HTTP POST request. This request includes the question text entered by the user. Specifically, the question data is embedded in the body of the request in JSON format.

[0218] Step 3:

[0219] The server analyzes the received question data. It takes the question text contained in the HTTP request body as input and uses natural language processing (NLP) techniques to identify key keywords and associated legal categories. Specifically, the NLP model tokenizes the text and extracts key keywords from it.

[0220] Step 4:

[0221] The server searches the database based on the analyzed keywords. The identified keywords are sent as input to the database in the form of an SQL query or similar to retrieve corresponding legal information and past precedents. As output, the relevant legal information and precedents are returned to the server.

[0222] Step 5:

[0223] The server generates a specific answer to the user's question based on the legal information it has acquired. In this step, it uses the acquired data to generate a text-based answer using the GEN AI model (a generative AI model). The acquired legal information and keywords are used as input, and a complete answer text is generated as output.

[0224] Step 6:

[0225] The server sends the generated response data to the terminal as an HTTP response. As output, the generated response text is included in the body of the HTTP response.

[0226] Step 7:

[0227] The device displays or audibly outputs the answer data received from the server to the user. It takes the answer text contained in the body of the HTTP response as input and displays it on the user interface or outputs it audibly using a text-to-speech (TTS) system. Specifically, it displays the answer text on the screen in an appropriate format or passes it to a speech synthesis engine and outputs it from the speaker.

[0228] 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.

[0229] The present invention is a system that allows users to quickly and effectively solve common legal problems, and by combining an emotion engine, provides appropriate answers according to the user's emotional state. This system is configured so that a user inputs a legal question via a terminal, a server provides an appropriate answer to the question, and the emotion engine analyzes the user's emotional state and provides the answer in an appropriate tone.

[0230] Program processing overview

[0231] The user enters a question

[0232] A user types a legal question into a form on a device, for example, "How do I start divorce proceedings?"

[0233] The device sends a question to the server

[0234] The terminal sends the user's input data to the server via the Internet using a communication protocol (e.g., HTTP POST).

[0235] The server receives and analyzes the query.

[0236] The server receives the query data submitted by the user, stores it in a database, and then uses natural language processing (NLP) technology to analyze the query and identify key keywords and related legal categories.

[0237] Emotion engine analyzes the user's emotional state

[0238] The server uses an emotion engine to analyze the user's emotional state from the input data, for example, determining whether the user is feeling anxious or angry based on the tone and keywords in the text.

[0239] The server references legal information and past cases

[0240] The server accesses an internal database containing legal texts, legal commentary documents, and past court records to retrieve the required legal information and past cases based on the identified keywords and legal categories.

[0241] The server generates the answer

[0242] The server generates answers to users' questions based on the acquired legal information and case law. The tone of the answer is adjusted based on the emotional data provided by the emotion engine. For example, if the user is feeling anxious, the answer will be written in a comforting tone.

[0243] The server sends the answer to the device

[0244] The server generates a response and sends it to the terminal, where it is converted into a format suitable for display on the user interface.

[0245] The device displays the answer

[0246] The device will display the answer received from the server on the screen. The answer will be adjusted to be displayed in a format that is easy for the user to understand. For example, it may say, "To begin divorce proceedings, you will need to go to city hall and submit the necessary documents. Specifically, you will need a divorce notification form and an extract of your family register. Please stay calm and proceed one step at a time."

[0247] Specific examples

[0248] Below is a specific example of use based on the above processing flow.

[0249] 1. The user enters a question

[0250] The user operates a terminal (e.g., a smartphone) and enters, "Will there be a penalty if I terminate the rental contract midway?"

[0251] 2. The device sends a question to the server

[0252] The smartphone application sends the entered question data to the server via an HTTP POST request.

[0253] 3. The server receives and analyzes the query

[0254] The server receives the question data and uses natural language processing technology to extract important keywords such as "rental contract," "mid-term termination," and "penalty fee."

[0255] 4. The emotion engine analyzes the user's emotional state

[0256] The server uses an emotion engine to analyze the user's emotional state and determine whether the user is feeling stressed from the tone of the questions.

[0257] 5. The server references legal information and past cases

[0258] The server queries its internal database to search for relevant information based on the extracted keywords, resulting in the acquisition of legal provisions and past legal precedents related to rental contracts.

[0259] 6. The server generates the answer

[0260] The server generates a response in an appropriate tone based on the acquired information and the data provided by the emotion engine. For example, it generates a response such as, "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord's illegal actions are not included. This may be worrying, but please take appropriate measures."

[0261] 7. The server sends the answer to the device

[0262] The server sends the generated answer to the terminal as an HTTP response.

[0263] 8. The device will display the answer

[0264] The smartphone application receives the response and displays the following message on the screen: "If you terminate a rental contract midway, you may be charged a penalty if it is clearly stated in the contract. However, this only applies if the landlord has not engaged in illegal activity. This may be worrying, but you should take appropriate measures."

[0265] This system allows users to easily and quickly obtain accurate information about legal issues without relying on a specialist, and to receive appropriate answers that take into account their own emotional state, thus enabling users to deal with legal issues that arise in their daily lives.

[0266] The processing flow will be explained below.

[0267] Step 1:

[0268] A user uses a terminal to input a legal question into an input form. For example, the user inputs, "Are there any penalties if I terminate a rental contract early?"

[0269] Step 2:

[0270] The terminal sends the entered question data to the server using a communication protocol (e.g., HTTP POST) over the Internet.

[0271] Step 3:

[0272] The server receives the question data sent by the user and stores it in a database.

[0273] Step 4:

[0274] The server uses natural language processing (NLP) technology to analyze the received question, specifically extracting key keywords such as "rental contract," "mid-term termination," and "penalty."

[0275] Step 5:

[0276] Based on the extracted keywords, the server will refer to its internal database to identify relevant legal categories, for example, searching for laws and precedents related to "rental agreements."

[0277] Step 6:

[0278] The emotion engine analyzes the user's emotional state from the input data, for example, determining whether the user is feeling anxious or angry based on the tone of the text and the keywords used.

[0279] Step 7:

[0280] The server adjusts the tone of the response based on the emotional data provided by the emotion engine: if the user is feeling anxious, the answer will be written in a comforting tone.

[0281] Step 8:

[0282] The server searches an internal database of legal information and past case law data to retrieve specific information related to the user's question.

[0283] Step 9:

[0284] The server generates answers to user questions based on legal information and past legal precedents. Answers may include specific legal provisions and past cases. For example, it might generate an answer like, "In the case of mid-term termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord has committed no illegal acts. This may be worrying, but you should take appropriate measures."

[0285] Step 10:

[0286] The server generates a response and sends it to the terminal, again using a communication protocol (e.g., HTTP response).

[0287] Step 11:

[0288] The device displays the response received from the server to the user. The user interface is updated to display the response in a format that is easy for the user to understand. For example, it might say, "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord's illegal activity is not involved. This may be worrying, but please take appropriate measures."

[0289] Example 2

[0290] 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."

[0291] In modern society, we often face legal problems, and it is difficult for ordinary citizens, especially those without specialized knowledge, to obtain legal information quickly and accurately. This requires time and money to consult with experts, and there is a need for a way to resolve these problems while also managing one's own emotions appropriately. However, existing systems lack the ability to provide appropriate advice that takes into account emotional states.

[0292] 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.

[0293] In this invention, the server includes means for using an emotion engine to analyze the emotional state of the user from input data, means for adjusting the tone of the response based on the emotional data provided by the emotion engine, and means for using natural language processing techniques to identify legal categories associated with key keywords, thereby enabling the user to quickly obtain accurate legal information that takes into account the user's emotional state.

[0294] A "user" is a person who utilizes the system to enter a legal question.

[0295] A "terminal" is a device that a user operates to input questions, and refers to electronic devices such as smartphones and personal computers.

[0296] A "server" is a computer system that analyzes the received data, generates a response based on legal information and past precedents, and sends it to the terminal.

[0297] "Natural language processing technology" is a technology that analyzes the content of questions entered by users to identify key keywords and related legal categories.

[0298] An "emotion engine" is software or a system for analyzing a user's emotional state from input data.

[0299] A "database" is a collection of data that stores legal information and past case law information and can be referenced as needed.

[0300] "Tone of response" refers to the emotional expression or tone of the generated response, which is adjusted according to the user's emotional state.

[0301] "Legal information" refers to all information related to the law, such as legal explanations, provisions, or past court decisions.

[0302] The present invention is a system that allows users to quickly and effectively solve common legal problems, and by combining an emotion engine, provides appropriate answers according to the user's emotional state. This system is composed of terminals, a server, a database, an emotion engine, and natural language processing technology.

[0303] First, the user enters a legal question through a device, such as a smartphone or PC. For example, a user might use a smartphone to enter "How do I start divorce proceedings?" into an application form.

[0304] Next, the terminal sends the user-entered question data to the server via the Internet using the HTTP POST request protocol, which sends the input data to the server and the system begins processing the question.

[0305] The server first stores the received question data in a database, which stores legal information and past legal precedents. A database system such as MongoDB is used. Next, the server analyzes the question using natural language processing technology (e.g., SpaCy, Gensim) to identify key keywords and related legal categories. This process allows the system to accurately understand the user's intent in the question.

[0306] Furthermore, the server analyzes the user's emotional state using an emotion engine, such as IBM Watson Tone Analyzer, which can analyze the user's emotional state, such as anxiety or anger, from the user's input data.

[0307] The server then queries its internal database to find relevant legal information and past cases based on the analyzed keywords and legal categories. The server generates a response based on the retrieved information, adjusting the tone of the response based on the emotional data provided by the emotion engine. For example, if the user is feeling anxious, the response will be written in a comforting tone. The response might be something like, "You need to go to city hall and submit the necessary documents. Specifically, you need a divorce notice and a copy of your family register. Please proceed with the process without worry."

[0308] The generated answers are sent from the server to the terminal and displayed on the terminal. The user interface is designed to provide answers in a format that is easy for the user to understand.

[0309] For example, consider the following prompt:

[0310] Are there any penalties if I cancel my lease early?

[0311] This system not only allows users to quickly obtain accurate legal information without relying on a specialist, but also provides answers that take into consideration their emotional state, enabling users to quickly respond to legal issues that arise in their daily lives.

[0312] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0313] Step 1:

[0314] The user enters a question

[0315] The user operates the terminal and inputs a question about a legal issue into the input form. The input question is prepared as text data. This text data is input in preparation for processing in the next step.

[0316] Input: User question (e.g., "How do I start divorce proceedings?")

[0317] Output: Text data entered in the input form

[0318] Step 2:

[0319] The device sends a question to the server

[0320] The terminal sends the text data entered by the user to the server using an HTTP POST request, and the sent data reaches the server via the Internet.

[0321] Input: Text data in the input form

[0322] Output: HTTP POST request sent to the server

[0323] Step 3:

[0324] The server receives and analyzes the query.

[0325] The server first stores the received text data in a database, then uses natural language processing (NLP) techniques to analyze the text data and identify key keywords (e.g., "divorce" and "procedure") and related legal categories.

[0326] Input: Text data of HTTP POST request

[0327] Output: Identified keywords and legal categories

[0328] Step 4:

[0329] Emotion engine analyzes the user's emotional state

[0330] The server passes the received text data to the emotion engine, which analyzes the user's emotional state. The emotion engine infers emotions from the tone of the text and specific keywords.

[0331] Input: Text data

[0332] Output: Emotional state data (e.g., anxiety, anger)

[0333] Step 5:

[0334] The server references legal information and past cases

[0335] The server uses the identified keywords and legal categories to access an internal database and search for relevant legal information and past cases.

[0336] Input: Identified keywords and legal categories

[0337] Output: Retrieved relevant legal information and past cases

[0338] Step 6:

[0339] The server generates the answer

[0340] The server generates an answer to the user's question based on the acquired legal information and emotional data, and the tone of the answer is adjusted based on the emotional data.

[0341] Input: Obtained legal information, past cases, and emotional state data

[0342] Output: Answer text with adjusted emotional tone

[0343] Step 7:

[0344] The server sends the answer to the device

[0345] The server sends the generated answer text to the terminal as an HTTP response.

[0346] Input: Answer text

[0347] Output: The answer text sent in the HTTP response

[0348] Step 8:

[0349] The device displays the answer

[0350] The terminal displays the answer text received as an HTTP response on the user interface, adjusted to a format that is easy for the user to view.

[0351] Input: HTTP response answer text

[0352] Output: Answer text displayed on the screen

[0353] Through these processing steps, users can obtain relevant and emotionally sensitive answers to their legal questions.

[0354] (Application example 2)

[0355] 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."

[0356] The problem to be solved by the present invention is to provide not only legal answers but also answers in an appropriate tone that takes into consideration the emotional state of the user when solving legal questions quickly and effectively. In particular, the present invention aims to provide a system that can respond to customers in a way that does not cause anxiety or stress in customer support situations where the tone of the answer is important.

[0357] The identification process by the identification 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 the emotional state of a user using an emotion analysis engine, means for referencing a database storing legal information and past precedents and acquiring specific legal information, and means for generating an answer to a user's question based on the acquired legal information and the emotion analysis results. This makes it possible, when a user asks a question, to quickly provide an answer in an appropriate tone that takes into account the user's emotional state.

[0358] Definition of Terms

[0359] A "user" is someone who utilizes the system to input a legal question.

[0360] A "question" is a request for legal information or a matter for consultation entered by a user.

[0361] A "terminal" is a device through which a user inputs legal questions and communicates with the server, and includes smartphones and personal computers.

[0362] A "server" is a device that receives legal questions sent by users, analyzes them, and generates answers.

[0363] An "emotion analysis engine" is software or hardware for analyzing a user's emotional state from input data.

[0364] "Natural language processing technology" is a technology that analyzes questions entered by users and identifies key keywords and related legal categories.

[0365] A "database" is a collection of information that stores legal information and past precedents and can be referenced by a server.

[0366] "Answers" are legal information and advice generated by the server based on the user's question.

[0367] "Means for analyzing the question" refers to the process by which the server uses natural language processing technology to analyze the content of the question entered by the user and extract key keywords and related legal categories.

[0368] The "means for generating an answer" is the process by which the server creates an answer to the user's question based on the legal information and sentiment analysis results it has obtained.

[0369] The "means for displaying the answer" is a function that visually presents the answer that the terminal receives from the server to the user.

[0370] MODE FOR CARRYING OUT THE INVENTION

[0371] This invention relates to a legal consultation system that incorporates an emotion engine, and is particularly applicable to customer support on online shopping sites. This system allows users to input legal questions and send the information to a server, which provides quick and emotionally sensitive answers.

[0372] Hardware and software used

[0373] To implement the system, the following hardware and software are used.

[0374] Hardware

[0375] Device: A smartphone used by a user, allowing the user to enter legal questions and receive answers.

[0376] Server: A powerful computing device that processes data sent by users and generates answers.

[0377] software

[0378] Natural Language Processing Technology (NLPProcessor): Technology that analyzes user questions and identifies key keywords and relevant legal categories.

[0379] Emotion Analysis Engine (EmotionEngine): A technology that analyzes the emotional state of a user from input data and determines their emotions based on the tone of the questions and keywords they enter.

[0380] Database: A collection of information for storing legal information and past precedents. The server references this database to obtain the necessary information.

[0381] Requests library: A library for HTTP communication. Used to send data between the terminal and the server.

[0382] Specific operation of the system

[0383] 1. Enter your question

[0384] Users use a smartphone application to input legal questions, such as, "I'm having trouble with the complicated return process. How should I proceed?"

[0385] 2. Submit your question

[0386] The smartphone application sends the entered question data to the server using an HTTP POST request, using the "requests" library.

[0387] 3. Question and Sentiment Analysis

[0388] The server analyzes the received inquiry data. First, it uses natural language processing technology (NLPProcessor) to analyze the content of the inquiry and identify key keywords and related legal categories.

[0389] Next, the "Emotion Engine" is used to analyze the user's emotional state and determine emotions such as anxiety or stress.

[0390] 4. Obtaining relevant information

[0391] The server accesses a "database" to search for legal information and past cases, and retrieves the required information based on the identified keywords and categories.

[0392] 5. Answer Generation

[0393] The server generates a response in an appropriate tone based on the acquired information and the results of sentiment analysis. For example, a user who is feeling anxious might receive a response such as, "Don't worry. Please follow the steps below to process your return."

[0394] 6. Submitting and Viewing Your Answers

[0395] The server generates an answer and sends it to the device as an HTTP response. The smartphone application receives the answer and presents it visually to the user.

[0396] Examples of specific examples and prompts

[0397] Specific examples

[0398] The user enters a question through a smartphone application, such as "The return procedure is complicated and I'm having trouble. How should I proceed?" The server analyzes the question and detects that the user is feeling anxious. The server retrieves information about the return procedure from the database, generates a response such as "Don't worry. Please follow the steps below to return the product," and provides it to the user.

[0399] Prompt Sentence Examples

[0400] "Use sentiment engines and natural language processing to answer customer questions about returns, like: 'I'm having trouble with the complicated returns process. How do I proceed?'"

[0401] The above is an embodiment of the present invention.

[0402] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0403] Program processing steps

[0404] Step 1:

[0405] Users input legal questions through a smartphone application. Data is generated by entering specific questions into this input form (e.g., "I'm having trouble with the complicated return procedure. How should I proceed?"). The input data includes the text information of the question.

[0406] Step 2:

[0407] The device (smartphone) sends the entered question data to the server using an HTTP POST request. At this time, the input data is sent as part of the HTTP request. The input data is sent to the server and received by the server.

[0408] Step 3:

[0409] The server analyzes the received question data. First, it uses natural language processing technology (NLPProcessor) to analyze the text data of the question and extract key keywords and related legal categories. The input data is analyzed, and the extracted keywords and categories are output (e.g., "return," "procedure," "complex," etc.).

[0410] Step 4:

[0411] The server uses an emotion analysis engine (EmotionEngine) to analyze the user's emotional state from the input data. Based on the linguistic features of the input data (e.g., tone and keywords), it determines the emotion the user is feeling (e.g., anxiety, confusion). The results of the emotion analysis are output and used in the next step.

[0412] Step 5:

[0413] The server references a database containing legal information and past precedents and retrieves relevant information based on the extracted keywords and categories. The input data is used as a database query, and the required legal information and past precedent data is output.

[0414] Step 6:

[0415] The server generates an answer to the user's question based on the legal information acquired and the results of sentiment analysis. Specifically, the answer is created based on the legal information and in a tone that takes into account the sentiment data. For example, the generated answer might be something like, "Don't worry. Please follow the steps below to process your return."

[0416] Step 7:

[0417] The server generates an answer and sends it to the terminal as an HTTP response. The generated answer is output in document format and sent as part of the HTTP response. The terminal receives this answer.

[0418] Step 8:

[0419] The device displays the answer received from the server to the user. The received data is visualized by the smartphone application, and the appropriate answer is displayed on the screen for the user.

[0420] The above is the specific processing flow of the program.

[0421] 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.

[0422] 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.

[0423] 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.

[0424] [Second embodiment]

[0425] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0426] 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.

[0427] 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).

[0428] 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.

[0429] 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.

[0430] 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).

[0431] 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.

[0432] 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.

[0433] 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.

[0434] 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.

[0435] 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.

[0436] 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."

[0437] The present invention provides a system for users to quickly and effectively resolve common legal issues. The system involves users inputting legal questions via a terminal, and a server providing appropriate answers to those questions.

[0438] Program processing overview

[0439] The user enters a question

[0440] The user enters a legal question into a form on the device. The user can enter a specific legal issue or question.

[0441] The device sends a question to the server

[0442] The terminal sends the entered question data to the server using a communication protocol (e.g., HTTP POST) over the Internet.

[0443] The server receives and analyzes the query.

[0444] The server receives the question data sent by the user and stores it in a database.

[0445] Next, natural language processing technology is used to analyze the question and identify key keywords and associated legal categories.

[0446] The server references legal information and past cases

[0447] The server accesses an internal database that searches for legal information and past cases based on the identified keywords and legal categories. This database contains legal provisions, legal commentary documents, and past court records.

[0448] The server generates the answer

[0449] The server uses the acquired legal information and case law to generate specific answers to the user's questions, written in a clear and easy-to-understand format.

[0450] The server sends the answer to the device

[0451] The server then sends the generated answer to the user's device, where it is converted into a format suitable for display on the user interface.

[0452] The device displays the answer

[0453] The device displays the answer received from the server on the screen, and the user can check the displayed answer and use it as a reference for solving the problem.

[0454] Specific examples

[0455] Below is a specific example of use based on the above processing flow.

[0456] 1. The user enters a question

[0457] The user operates a terminal (e.g., a smartphone) and enters, "Will there be a penalty if I terminate the rental contract midway?"

[0458] 2. The device sends a question to the server

[0459] The smartphone application sends the entered question data to the server via an HTTP POST request.

[0460] 3. The server receives and analyzes the query

[0461] The server receives the question data and uses natural language processing technology to extract important keywords such as "rental contract," "mid-term termination," and "penalty fee."

[0462] 4. The server references legal information and past cases

[0463] The server queries its internal database to search for relevant information based on the extracted keywords, resulting in the acquisition of legal provisions and past legal precedents related to rental contracts.

[0464] 5. The server generates the answer

[0465] Based on the information it has obtained, the server generates the following response: "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord's illegal activity is not involved."

[0466] 6. The server sends the answer to the device

[0467] The server sends the generated answer to the terminal as an HTTP response.

[0468] 7. The device will display the answer

[0469] The smartphone application receives the response and displays the following message on the screen: "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the termination does not involve illegal activity by the landlord."

[0470] This system allows users to easily and quickly obtain accurate information about legal issues without having to consult a legal professional, thus enabling users to deal with legal issues that arise in their daily lives.

[0471] The processing flow will be explained below.

[0472] Step 1:

[0473] A user uses a terminal to input a legal question into an input form. For example, the user inputs, "Are there any penalties if I terminate a rental contract early?"

[0474] Step 2:

[0475] The terminal sends the entered question data to the server using a communication protocol (e.g., HTTP POST) over the Internet.

[0476] Step 3:

[0477] The server receives the question data sent by the user and stores it in a database.

[0478] Step 4:

[0479] The server uses natural language processing (NLP) technology to analyze the received question, specifically extracting key keywords such as "rental contract," "mid-term termination," and "penalty."

[0480] Step 5:

[0481] Based on the extracted keywords, the server will refer to its internal database to identify relevant legal categories, for example, searching for laws and precedents related to "rental agreements."

[0482] Step 6:

[0483] The server searches an internal database of legal information and past case law data to retrieve specific information related to the user's question.

[0484] Step 7:

[0485] The server generates answers to user questions based on legal information and past precedents. Answers may include specific legal provisions and past precedents. For example, it may generate an answer such as, "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord's illegal actions are not included."

[0486] Step 8:

[0487] The server generates a response and sends it to the terminal, again using a communication protocol (e.g., HTTP response).

[0488] Step 9:

[0489] The terminal displays the answer received from the server to the user. The user interface is updated to display the answer in a format that is easy for the user to understand. For example, it may say, "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord's illegal activity is not involved."

[0490] Example 1

[0491] 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."

[0492] Conventional legal problem-solving systems have had issues such as delayed responses to user questions and the high cost of expert consultations. Furthermore, it is difficult for users without specialized legal knowledge to gather appropriate information on their own. This has led to a demand for a means for general users to quickly and effectively resolve legal problems.

[0493] 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.

[0494] In this invention, the server includes a means for storing received question data in a database, a means for analyzing the question using a natural language processing engine and extracting key keywords, and a means for generating answers using a generative AI model, thereby enabling the server to quickly and accurately generate and provide answers to user questions.

[0495] "User" means any person or entity that enters a legal question into the system.

[0496] "Terminal" refers to the electronic device used by the user to input questions and communicate with the server. Examples include smartphones, tablets, and personal computers.

[0497] "Server" refers to a central computing system that receives, analyzes, and generates answers to user-submitted question data.

[0498] "Question data" refers to legal inquiries entered by a user using a terminal.

[0499] "Database" refers to a collection of information accessed by a server that stores legal information and past court decisions.

[0500] A "natural language processing engine" refers to software technology for analyzing question data and extracting key keywords.

[0501] A "generative AI model" refers to an artificial intelligence technology that generates specific answers to users' questions based on acquired legal information.

[0502] "HTTPS" refers to a communication protocol for secure data communication between a terminal and a server.

[0503] "HTTP POST request" refers to a specific Internet protocol used to send query data from a terminal to a server.

[0504] "HTTP response" refers to a specific Internet protocol used to send response data from a server to a terminal.

[0505] "User interface" refers to an interactive display screen for interaction between a user and a terminal.

[0506] MODE FOR CARRYING OUT THE INVENTION

[0507] The present invention is a system for enabling users to quickly and effectively resolve common legal issues. The system is configured so that users input legal questions via a terminal, and a server provides appropriate answers to those questions. Specific embodiments for implementing the present invention are described below.

[0508] Hardware and software used

[0509] Devices: Electronic devices such as smartphones, tablets, and PCs

[0510] Server: A computing system equipped with a high-performance database and natural language processing engine.

[0511] Database: A collection of information containing legal documents and past court decisions

[0512] Natural language processing engine: Software technology for analyzing questions and extracting necessary information (e.g., SpaCy, BERT model)

[0513] Generative AI model: Artificial intelligence technology that generates specific answers based on acquired legal information

[0514] Processing flow

[0515] A user uses a device to input a legal question. The input data is sent from the device to a server via an HTTP POST request. The server stores the received question data in a database and analyzes it using a natural language processing engine. The server identifies key keywords and related legal categories and searches for relevant information in a database that contains legal provisions, legal commentaries, and past court records.

[0516] Based on the acquired information, the server uses a generative AI model to generate a specific answer to the user's question. The generated answer is sent from the server to the device as an HTTP response, and the device converts it into a format suitable for the user interface and displays it so that the user can check it.

[0517] Specific examples

[0518] Below is a specific example of use based on the above processing flow.

[0519] 1. The user enters a question

[0520] The user operates a terminal (e.g., a smartphone) and enters, "Will there be a penalty if I terminate the rental contract midway?"

[0521] 2. The device sends a question to the server

[0522] The smartphone application sends the entered question data to the server via an HTTP POST request, using the HTTPS protocol to ensure secure data transmission.

[0523] 3. The server parses the question

[0524] The server stores the received question data in a database and analyzes the question using a natural language processing engine (e.g., SpaCy, BERT model) to extract keywords such as "rental contract," "early termination," and "penalty fee."

[0525] 4. The server references legal information and past cases

[0526] The server accesses an internal database and searches for relevant legal documents and past cases based on the extracted keywords.

[0527] 5. The server generates the answer

[0528] The server uses a generative AI model to generate specific answers based on the information it receives.

[0529] For example: "In a rental agreement, if you terminate the agreement early, you may be subject to a penalty if it is clearly stated in the agreement. However, this only applies if the landlord's illegal actions are not involved."

[0530] 6. The server sends the answer to the device

[0531] The server generates an answer and sends it to the device as an HTTP response, which contains the answer formatted in the appropriate format.

[0532] 7. The device will display the answer

[0533] The smartphone application receives the response and displays the following message on the screen: "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the termination does not involve illegal activity by the landlord."

[0534] This system allows users to quickly and effectively obtain accurate information on legal issues without having to rely on a specialist, and also allows users to easily acquire knowledge to deal with legal issues that arise in their daily lives.

[0535] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0536] Step 1:

[0537] User enters legal question

[0538] The user opens a dedicated application or web interface on their device (e.g., smartphone, PC) and enters their question into the input form.

[0539] Input data: Legal questions entered by the user (e.g., "Are there any penalties for breaking a lease early?")

[0540] Output: Question data entered by the user

[0541] Step 2:

[0542] The device sends a question to the server

[0543] The device packages the entered question data in JSON format and sends it to the server via an HTTP POST request, using HTTPS to ensure secure communication.

[0544] Input data: Question data converted to JSON format

[0545] Output: HTTP POST request sent to the server

[0546] Step 3:

[0547] The server receives and analyzes the query.

[0548] The server parses the received HTTP POST request, extracts and saves the question data, and then uses a natural language processing engine (e.g., SpaCy, BERT model) to analyze the question and extract key keywords (e.g., "rental agreement," "early termination," "penalty fee").

[0549] Input data: Question data in an HTTP POST request

[0550] Data processing: Analysis of question data, extraction of important keywords

[0551] Output: Extracted keywords

[0552] Step 4:

[0553] The server references legal information and past cases

[0554] The server then uses the extracted keywords to query an internal database that contains legal provisions, legal commentaries, and past legal precedents to find relevant legal documents and past cases.

[0555] Input data: extracted keywords

[0556] Data processing: querying databases and searching for relevant information

[0557] Output: Relevant legal documents, provisions, and past cases

[0558] Step 5:

[0559] The server generates the answer

[0560] The server uses a generative AI model to generate specific answers based on the legal information it receives, and formats the answers in a way that is easy for users to understand.

[0561] Input data: relevant legal documents, statutes, and past precedents

[0562] Data processing: Generate answers and convert formats using AI models

[0563] Output: The specific answer generated

[0564] Step 6:

[0565] The server sends the answer to the device

[0566] The server packages the generated response in JSON format and sends it to the terminal as an HTTP response, again using the HTTPS protocol to ensure communication security.

[0567] Input data: Generated answers

[0568] Data processing: conversion to JSON format, generation of HTTP response

[0569] Output: HTTP response sent to the device

[0570] Step 7:

[0571] The device displays the answer

[0572] The device analyzes the received HTTP response and converts the response data into a format suitable for the user interface (e.g., HTML, in-app display format), and displays it. The user can check the response on the screen.

[0573] Input data: Response data in the HTTP response

[0574] Data processing: converting data into a format suitable for the user interface

[0575] Output: The answer displayed in the user interface

[0576] (Application example 1)

[0577] 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."

[0578] There is a need for fast and effective responses to legal issues in brick-and-mortar stores, but currently, it is difficult for store staff without legal expertise to provide appropriate answers. Furthermore, there is a lack of means to obtain immediate and accurate answers to customers' legal problems, so problems often take a long time to resolve. To solve these problems, a legal response system that can be easily used in stores is needed.

[0579] 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.

[0580] In this invention, the server includes: means for a user to input a legal question; means for a terminal to transmit the user's input data to the server; means for the server to analyze the received question and identify legal categories associated with major keywords; means for the server to reference a database storing legal information and past precedents and acquire specific legal information; means for the server to generate an answer to the user's question based on the acquired legal information; means for the server to transmit the generated answer to the terminal; means for the terminal to display or output the answer from the server as voice to the user; means for the tablet terminal, smartphone, or robot to input the legal question by voice or text; and means for the tablet terminal, smartphone, or robot to transmit the question data to the server. This enables users to ask legal questions using simple input means and receive accurate answers immediately.

[0581] A "User" is any person or entity that utilizes the System to enter legal questions and receive answers.

[0582] "Terminal" refers to a device that allows a user to input legal questions and transmit the input data to a server, including a tablet, smartphone, or robot.

[0583] A "server" is a computer system that analyzes questions received from users, generates answers based on legal information and past precedents, and sends them to terminals.

[0584] A "database" is a storage system that stores legal information and past precedents, which the server references to obtain the necessary information.

[0585] "Natural language processing technology" is a technology that allows the server to analyze the user's question and identify key keywords and related legal categories.

[0586] A "tablet" is a handheld computing device used by users to voice or text legal questions.

[0587] A "smartphone" is a mobile phone-type multifunction device used by users to voice or text legal questions.

[0588] A "robot" is a mechanical device used by users to voice or text legal questions.

[0589] "Voice input" is a method in which a user voices legal questions into a microphone.

[0590] "Text entry" is a method in which a user enters legal questions as text via a keyboard or touchscreen.

[0591] First, we will explain in detail the main components that make up the system for realizing this invention. The entire system utilizes terminals used by users, a server that processes data, and appropriate software to operate these in conjunction with each other.

[0592] Hardware used

[0593] The hardware used in this system is as follows:

[0594] Tablet devices: Used by users to dictate or text legal questions.

[0595] Smartphones: Used by users to dictate or text legal questions.

[0596] Interactive robots: used by users to voice or text legal questions.

[0597] Software used

[0598] The main software and technologies used in this system are as follows:

[0599] Flask: A Python web framework used to handle server-side HTTP requests and responses.

[0600] Transformers: A natural language processing library developed by Hugging Face that uses a question-answering (QnA) model to generate answers to questions.

[0601] Natural Language Processing Technology (NLP): Used by the server to analyze the questions received from the user and identify key keywords and relevant legal categories.

[0602] Data Flow and Processing

[0603] A user enters a legal question into a device (tablet, smartphone, or robot) using either voice or text input. The device then sends the user's input to a server. This communication typically occurs over the internet using an HTTP POST request.

[0604] The server analyzes the received query using NLP techniques to identify key keywords and associated legal categories, then accesses a database to search for legal information and past cases based on the specific keywords and legal categories.

[0605] Based on the legal information acquired by the server, a specific answer to the user's question is generated using a question-answering (QnA) model from the Transformers library.

[0606] The generated answer is sent from the server to the terminal, which displays or speaks the answer to the user, thereby providing the user with an immediate and accurate answer to their legal question.

[0607] Specific examples

[0608] For example, if a customer asks an interactive robot, "What should I do if my credit card is fraudulently used?", the question is entered as follows:

[0609] What to do if your credit card is fraudulently used?

[0610] The server receives and analyzes this question, retrieving relevant legal information and precedents from a database. For example, it extracts keywords such as "credit card," "fraudulent use," and "how to deal with it," and searches relevant legal provisions and past precedents. As a result, the server generates an answer like this:

[0611] If your credit card has been used fraudulently, first contact your card company and ask them to investigate the fraud. You should also file a police report and consider changing your password to prevent the leaking of personal information.

[0612] This generated answer is immediately provided to the user, allowing even store staff and customers who are not familiar with the law to quickly deal with legal issues.

[0613] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0614] Step 1:

[0615] The user inputs legal questions into a device (tablet, smartphone, or robot) by voice or text input. The input data is saved in the device as text data of the question.

[0616] Step 2:

[0617] The device sends the entered question data to the server using an HTTP POST request. This request includes the question text entered by the user. Specifically, the question data is embedded in the body of the request in JSON format.

[0618] Step 3:

[0619] The server analyzes the received question data. It takes the question text contained in the HTTP request body as input and uses natural language processing (NLP) techniques to identify key keywords and associated legal categories. Specifically, the NLP model tokenizes the text and extracts key keywords from it.

[0620] Step 4:

[0621] The server searches the database based on the analyzed keywords. The identified keywords are sent as input to the database in the form of an SQL query or similar to retrieve corresponding legal information and past precedents. As output, the relevant legal information and precedents are returned to the server.

[0622] Step 5:

[0623] The server generates a specific answer to the user's question based on the legal information it has acquired. In this step, it uses the acquired data to generate a text-based answer using the GEN AI model (a generative AI model). The acquired legal information and keywords are used as input, and a complete answer text is generated as output.

[0624] Step 6:

[0625] The server sends the generated response data to the terminal as an HTTP response. As output, the generated response text is included in the body of the HTTP response.

[0626] Step 7:

[0627] The device displays or audibly outputs the answer data received from the server to the user. It takes the answer text contained in the body of the HTTP response as input and displays it on the user interface or outputs it audibly using a text-to-speech (TTS) system. Specifically, it displays the answer text on the screen in an appropriate format or passes it to a speech synthesis engine and outputs it from the speaker.

[0628] 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.

[0629] The present invention is a system that allows users to quickly and effectively solve common legal problems, and by combining an emotion engine, provides appropriate answers according to the user's emotional state. This system is configured so that a user inputs a legal question via a terminal, a server provides an appropriate answer to the question, and the emotion engine analyzes the user's emotional state and provides the answer in an appropriate tone.

[0630] Program processing overview

[0631] The user enters a question

[0632] A user types a legal question into a form on a device, for example, "How do I start divorce proceedings?"

[0633] The device sends a question to the server

[0634] The terminal sends the user's input data to the server via the Internet using a communication protocol (e.g., HTTP POST).

[0635] The server receives and analyzes the query.

[0636] The server receives the query data submitted by the user, stores it in a database, and then uses natural language processing (NLP) technology to analyze the query and identify key keywords and related legal categories.

[0637] Emotion engine analyzes the user's emotional state

[0638] The server uses an emotion engine to analyze the user's emotional state from the input data, for example, determining whether the user is feeling anxious or angry based on the tone and keywords in the text.

[0639] The server references legal information and past cases

[0640] The server accesses an internal database containing legal texts, legal commentary documents, and past court records to retrieve the required legal information and past cases based on the identified keywords and legal categories.

[0641] The server generates the answer

[0642] The server generates answers to users' questions based on the acquired legal information and case law. The tone of the answer is adjusted based on the emotional data provided by the emotion engine. For example, if the user is feeling anxious, the answer will be written in a comforting tone.

[0643] The server sends the answer to the device

[0644] The server generates a response and sends it to the terminal, where it is converted into a format suitable for display on the user interface.

[0645] The device displays the answer

[0646] The device will display the answer received from the server on the screen. The answer will be adjusted to be displayed in a format that is easy for the user to understand. For example, it may say, "To begin divorce proceedings, you will need to go to city hall and submit the necessary documents. Specifically, you will need a divorce notification form and an extract of your family register. Please stay calm and proceed one step at a time."

[0647] Specific examples

[0648] Below is a specific example of use based on the above processing flow.

[0649] 1. The user enters a question

[0650] The user operates a terminal (e.g., a smartphone) and enters, "Will there be a penalty if I terminate the rental contract midway?"

[0651] 2. The device sends a question to the server

[0652] The smartphone application sends the entered question data to the server via an HTTP POST request.

[0653] 3. The server receives and analyzes the query

[0654] The server receives the question data and uses natural language processing technology to extract important keywords such as "rental contract," "mid-term termination," and "penalty fee."

[0655] 4. The emotion engine analyzes the user's emotional state

[0656] The server uses an emotion engine to analyze the user's emotional state and determine whether the user is feeling stressed from the tone of the questions.

[0657] 5. The server references legal information and past cases

[0658] The server queries its internal database to search for relevant information based on the extracted keywords, resulting in the acquisition of legal provisions and past legal precedents related to rental contracts.

[0659] 6. The server generates the answer

[0660] The server generates a response in an appropriate tone based on the acquired information and the data provided by the emotion engine. For example, it generates a response such as, "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord's illegal actions are not included. This may be worrying, but please take appropriate measures."

[0661] 7. The server sends the answer to the device

[0662] The server sends the generated answer to the terminal as an HTTP response.

[0663] 8. The device will display the answer

[0664] The smartphone application receives the response and displays the following message on the screen: "If you terminate a rental contract midway, you may be charged a penalty if it is clearly stated in the contract. However, this only applies if the landlord has not engaged in illegal activity. This may be worrying, but you should take appropriate measures."

[0665] This system allows users to easily and quickly obtain accurate information about legal issues without relying on a specialist, and to receive appropriate answers that take into account their own emotional state, thus enabling users to deal with legal issues that arise in their daily lives.

[0666] The processing flow will be explained below.

[0667] Step 1:

[0668] A user uses a terminal to input a legal question into an input form. For example, the user inputs, "Are there any penalties if I terminate a rental contract early?"

[0669] Step 2:

[0670] The terminal sends the entered question data to the server using a communication protocol (e.g., HTTP POST) over the Internet.

[0671] Step 3:

[0672] The server receives the question data sent by the user and stores it in a database.

[0673] Step 4:

[0674] The server uses natural language processing (NLP) technology to analyze the received question, specifically extracting key keywords such as "rental contract," "mid-term termination," and "penalty."

[0675] Step 5:

[0676] Based on the extracted keywords, the server will refer to its internal database to identify relevant legal categories, for example, searching for laws and precedents related to "rental agreements."

[0677] Step 6:

[0678] The emotion engine analyzes the user's emotional state from the input data, for example, determining whether the user is feeling anxious or angry based on the tone of the text and the keywords used.

[0679] Step 7:

[0680] The server adjusts the tone of the response based on the emotional data provided by the emotion engine: if the user is feeling anxious, the answer will be written in a comforting tone.

[0681] Step 8:

[0682] The server searches an internal database of legal information and past case law data to retrieve specific information related to the user's question.

[0683] Step 9:

[0684] The server generates answers to user questions based on legal information and past legal precedents. Answers may include specific legal provisions and past cases. For example, it might generate an answer like, "In the case of mid-term termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord has committed no illegal acts. This may be worrying, but you should take appropriate measures."

[0685] Step 10:

[0686] The server generates a response and sends it to the terminal, again using a communication protocol (e.g., HTTP response).

[0687] Step 11:

[0688] The device displays the response received from the server to the user. The user interface is updated to display the response in a format that is easy for the user to understand. For example, it might say, "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord's illegal activity is not involved. This may be worrying, but please take appropriate measures."

[0689] Example 2

[0690] 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."

[0691] In modern society, we often face legal problems, and it is difficult for ordinary citizens, especially those without specialized knowledge, to obtain legal information quickly and accurately. This requires time and money to consult with experts, and there is a need for a way to resolve these problems while also managing one's own emotions appropriately. However, existing systems lack the ability to provide appropriate advice that takes into account emotional states.

[0692] 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.

[0693] In this invention, the server includes means for using an emotion engine to analyze the emotional state of the user from input data, means for adjusting the tone of the response based on the emotional data provided by the emotion engine, and means for using natural language processing techniques to identify legal categories associated with key keywords, thereby enabling the user to quickly obtain accurate legal information that takes into account the user's emotional state.

[0694] A "user" is a person who utilizes the system to enter a legal question.

[0695] A "terminal" is a device that a user operates to input questions, and refers to electronic devices such as smartphones and personal computers.

[0696] A "server" is a computer system that analyzes the received data, generates a response based on legal information and past precedents, and sends it to the terminal.

[0697] "Natural language processing technology" is a technology that analyzes the content of questions entered by users to identify key keywords and related legal categories.

[0698] An "emotion engine" is software or a system for analyzing a user's emotional state from input data.

[0699] A "database" is a collection of data that stores legal information and past case law information and can be referenced as needed.

[0700] "Tone of response" refers to the emotional expression or tone of the generated response, which is adjusted according to the user's emotional state.

[0701] "Legal information" refers to all information related to the law, such as legal explanations, provisions, or past court decisions.

[0702] The present invention is a system that allows users to quickly and effectively solve common legal problems, and by combining an emotion engine, provides appropriate answers according to the user's emotional state. This system is composed of terminals, a server, a database, an emotion engine, and natural language processing technology.

[0703] First, the user enters a legal question through a device, such as a smartphone or PC. For example, a user might use a smartphone to enter "How do I start divorce proceedings?" into an application form.

[0704] Next, the terminal sends the user-entered question data to the server via the Internet using the HTTP POST request protocol, which sends the input data to the server and the system begins processing the question.

[0705] The server first stores the received question data in a database, which stores legal information and past legal precedents. A database system such as MongoDB is used. Next, the server analyzes the question using natural language processing technology (e.g., SpaCy, Gensim) to identify key keywords and related legal categories. This process allows the system to accurately understand the user's intent in the question.

[0706] Furthermore, the server analyzes the user's emotional state using an emotion engine, such as IBM Watson Tone Analyzer, which can analyze the user's emotional state, such as anxiety or anger, from the user's input data.

[0707] The server then queries its internal database to find relevant legal information and past cases based on the analyzed keywords and legal categories. The server generates a response based on the retrieved information, adjusting the tone of the response based on the emotional data provided by the emotion engine. For example, if the user is feeling anxious, the response will be written in a comforting tone. The response might be something like, "You need to go to city hall and submit the necessary documents. Specifically, you need a divorce notice and a copy of your family register. Please proceed with the process without worry."

[0708] The generated answers are sent from the server to the terminal and displayed on the terminal. The user interface is designed to provide answers in a format that is easy for the user to understand.

[0709] For example, consider the following prompt:

[0710] Are there any penalties if I cancel my lease early?

[0711] This system not only allows users to quickly obtain accurate legal information without relying on a specialist, but also provides answers that take into consideration their emotional state, enabling users to quickly respond to legal issues that arise in their daily lives.

[0712] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0713] Step 1:

[0714] The user enters a question

[0715] The user operates the terminal and inputs a question about a legal issue into the input form. The input question is prepared as text data. This text data is input in preparation for processing in the next step.

[0716] Input: User question (e.g., "How do I start divorce proceedings?")

[0717] Output: Text data entered in the input form

[0718] Step 2:

[0719] The device sends a question to the server

[0720] The terminal sends the text data entered by the user to the server using an HTTP POST request, and the sent data reaches the server via the Internet.

[0721] Input: Text data in the input form

[0722] Output: HTTP POST request sent to the server

[0723] Step 3:

[0724] The server receives and analyzes the query.

[0725] The server first stores the received text data in a database, then uses natural language processing (NLP) techniques to analyze the text data and identify key keywords (e.g., "divorce" and "procedure") and related legal categories.

[0726] Input: Text data of HTTP POST request

[0727] Output: Identified keywords and legal categories

[0728] Step 4:

[0729] Emotion engine analyzes the user's emotional state

[0730] The server passes the received text data to the emotion engine, which analyzes the user's emotional state. The emotion engine infers emotions from the tone of the text and specific keywords.

[0731] Input: Text data

[0732] Output: Emotional state data (e.g., anxiety, anger)

[0733] Step 5:

[0734] The server references legal information and past cases

[0735] The server uses the identified keywords and legal categories to access an internal database and search for relevant legal information and past cases.

[0736] Input: Identified keywords and legal categories

[0737] Output: Retrieved relevant legal information and past cases

[0738] Step 6:

[0739] The server generates the answer

[0740] The server generates an answer to the user's question based on the acquired legal information and emotional data, and the tone of the answer is adjusted based on the emotional data.

[0741] Input: Obtained legal information, past cases, and emotional state data

[0742] Output: Answer text with adjusted emotional tone

[0743] Step 7:

[0744] The server sends the answer to the device

[0745] The server sends the generated answer text to the terminal as an HTTP response.

[0746] Input: Answer text

[0747] Output: The answer text sent in the HTTP response

[0748] Step 8:

[0749] The device displays the answer

[0750] The terminal displays the answer text received as an HTTP response on the user interface, adjusted to a format that is easy for the user to view.

[0751] Input: HTTP response answer text

[0752] Output: Answer text displayed on the screen

[0753] Through these processing steps, users can obtain relevant and emotionally sensitive answers to their legal questions.

[0754] (Application example 2)

[0755] 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."

[0756] The problem to be solved by the present invention is to provide not only legal answers but also answers in an appropriate tone that takes into consideration the emotional state of the user when solving legal questions quickly and effectively. In particular, the present invention aims to provide a system that can respond to customers in a way that does not cause anxiety or stress in customer support situations where the tone of the answer is important.

[0757] The identification process by the identification 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 the emotional state of a user using an emotion analysis engine, means for referencing a database storing legal information and past precedents and acquiring specific legal information, and means for generating an answer to a user's question based on the acquired legal information and the emotion analysis results. This makes it possible, when a user asks a question, to quickly provide an answer in an appropriate tone that takes into account the user's emotional state.

[0758] Definition of Terms

[0759] A "user" is someone who utilizes the system to input a legal question.

[0760] A "question" is a request for legal information or a matter for consultation entered by a user.

[0761] A "terminal" is a device through which a user inputs legal questions and communicates with the server, and includes smartphones and personal computers.

[0762] A "server" is a device that receives legal questions sent by users, analyzes them, and generates answers.

[0763] An "emotion analysis engine" is software or hardware for analyzing a user's emotional state from input data.

[0764] "Natural language processing technology" is a technology that analyzes questions entered by users and identifies key keywords and related legal categories.

[0765] A "database" is a collection of information that stores legal information and past precedents and can be referenced by a server.

[0766] "Answers" are legal information and advice generated by the server based on the user's question.

[0767] "Means for analyzing the question" refers to the process by which the server uses natural language processing technology to analyze the content of the question entered by the user and extract key keywords and related legal categories.

[0768] The "means for generating an answer" is the process by which the server creates an answer to the user's question based on the legal information and sentiment analysis results it has obtained.

[0769] The "means for displaying the answer" is a function that visually presents the answer that the terminal receives from the server to the user.

[0770] MODE FOR CARRYING OUT THE INVENTION

[0771] This invention relates to a legal consultation system that incorporates an emotion engine, and is particularly applicable to customer support on online shopping sites. This system allows users to input legal questions and send the information to a server, which provides quick and emotionally sensitive answers.

[0772] Hardware and software used

[0773] To implement the system, the following hardware and software are used.

[0774] Hardware

[0775] Device: A smartphone used by a user, allowing the user to enter legal questions and receive answers.

[0776] Server: A powerful computing device that processes data sent by users and generates answers.

[0777] software

[0778] Natural Language Processing Technology (NLPProcessor): Technology that analyzes user questions and identifies key keywords and relevant legal categories.

[0779] Emotion Analysis Engine (EmotionEngine): A technology that analyzes the emotional state of a user from input data and determines their emotions based on the tone of the questions and keywords they enter.

[0780] Database: A collection of information for storing legal information and past precedents. The server references this database to obtain the necessary information.

[0781] Requests library: A library for HTTP communication. Used to send data between the terminal and the server.

[0782] Specific operation of the system

[0783] 1. Enter your question

[0784] Users use a smartphone application to input legal questions, such as, "I'm having trouble with the complicated return process. How should I proceed?"

[0785] 2. Submit your question

[0786] The smartphone application sends the entered question data to the server using an HTTP POST request, using the "requests" library.

[0787] 3. Question and Sentiment Analysis

[0788] The server analyzes the received inquiry data. First, it uses natural language processing technology (NLPProcessor) to analyze the content of the inquiry and identify key keywords and related legal categories.

[0789] Next, the "Emotion Engine" is used to analyze the user's emotional state and determine emotions such as anxiety or stress.

[0790] 4. Obtaining relevant information

[0791] The server accesses a "database" to search for legal information and past cases, and retrieves the required information based on the identified keywords and categories.

[0792] 5. Answer Generation

[0793] The server generates a response in an appropriate tone based on the acquired information and the results of sentiment analysis. For example, a user who is feeling anxious might receive a response such as, "Don't worry. Please follow the steps below to process your return."

[0794] 6. Submitting and Viewing Your Answers

[0795] The server generates an answer and sends it to the device as an HTTP response. The smartphone application receives the answer and presents it visually to the user.

[0796] Examples of specific examples and prompts

[0797] Specific examples

[0798] The user enters a question through a smartphone application, such as "The return procedure is complicated and I'm having trouble. How should I proceed?" The server analyzes the question and detects that the user is feeling anxious. The server retrieves information about the return procedure from the database, generates a response such as "Don't worry. Please follow the steps below to return the product," and provides it to the user.

[0799] Prompt Sentence Examples

[0800] "Use sentiment engines and natural language processing to answer customer questions about returns, like: 'I'm having trouble with the complicated returns process. How do I proceed?'"

[0801] The above is an embodiment of the present invention.

[0802] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0803] Program processing steps

[0804] Step 1:

[0805] Users input legal questions through a smartphone application. Data is generated by entering specific questions into this input form (e.g., "I'm having trouble with the complicated return procedure. How should I proceed?"). The input data includes the text information of the question.

[0806] Step 2:

[0807] The device (smartphone) sends the entered question data to the server using an HTTP POST request. At this time, the input data is sent as part of the HTTP request. The input data is sent to the server and received by the server.

[0808] Step 3:

[0809] The server analyzes the received question data. First, it uses natural language processing technology (NLPProcessor) to analyze the text data of the question and extract key keywords and related legal categories. The input data is analyzed, and the extracted keywords and categories are output (e.g., "return," "procedure," "complex," etc.).

[0810] Step 4:

[0811] The server uses an emotion analysis engine (EmotionEngine) to analyze the user's emotional state from the input data. Based on the linguistic features of the input data (e.g., tone and keywords), it determines the emotion the user is feeling (e.g., anxiety, confusion). The results of the emotion analysis are output and used in the next step.

[0812] Step 5:

[0813] The server references a database containing legal information and past precedents and retrieves relevant information based on the extracted keywords and categories. The input data is used as a database query, and the required legal information and past precedent data is output.

[0814] Step 6:

[0815] The server generates an answer to the user's question based on the legal information acquired and the results of sentiment analysis. Specifically, the answer is created based on the legal information and in a tone that takes into account the sentiment data. For example, the generated answer might be something like, "Don't worry. Please follow the steps below to process your return."

[0816] Step 7:

[0817] The server generates an answer and sends it to the terminal as an HTTP response. The generated answer is output in document format and sent as part of the HTTP response. The terminal receives this answer.

[0818] Step 8:

[0819] The device displays the answer received from the server to the user. The received data is visualized by the smartphone application, and the appropriate answer is displayed on the screen for the user.

[0820] The above is the specific processing flow of the program.

[0821] 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.

[0822] 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.

[0823] 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.

[0824] [Third embodiment]

[0825] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0826] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0827] 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).

[0828] 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.

[0829] 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.

[0830] 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).

[0831] 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.

[0832] 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.

[0833] 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.

[0834] 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.

[0835] 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.

[0836] 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."

[0837] The present invention provides a system for users to quickly and effectively resolve common legal issues. The system involves users inputting legal questions via a terminal, and a server providing appropriate answers to those questions.

[0838] Program processing overview

[0839] The user enters a question

[0840] The user enters a legal question into a form on the device. The user can enter a specific legal issue or question.

[0841] The device sends a question to the server

[0842] The terminal sends the entered question data to the server using a communication protocol (e.g., HTTP POST) over the Internet.

[0843] The server receives and analyzes the query.

[0844] The server receives the question data sent by the user and stores it in a database.

[0845] Next, natural language processing technology is used to analyze the question and identify key keywords and associated legal categories.

[0846] The server references legal information and past cases

[0847] The server accesses an internal database that searches for legal information and past cases based on the identified keywords and legal categories. This database contains legal provisions, legal commentary documents, and past court records.

[0848] The server generates the answer

[0849] The server uses the acquired legal information and case law to generate specific answers to the user's questions, written in a clear and easy-to-understand format.

[0850] The server sends the answer to the device

[0851] The server then sends the generated answer to the user's device, where it is converted into a format suitable for display on the user interface.

[0852] The device displays the answer

[0853] The device displays the answer received from the server on the screen, and the user can check the displayed answer and use it as a reference for solving the problem.

[0854] Specific examples

[0855] Below is a specific example of use based on the above processing flow.

[0856] 1. The user enters a question

[0857] The user operates a terminal (e.g., a smartphone) and enters, "Will there be a penalty if I terminate the rental contract midway?"

[0858] 2. The device sends a question to the server

[0859] The smartphone application sends the entered question data to the server via an HTTP POST request.

[0860] 3. The server receives and analyzes the query

[0861] The server receives the question data and uses natural language processing technology to extract important keywords such as "rental contract," "mid-term termination," and "penalty fee."

[0862] 4. The server references legal information and past cases

[0863] The server queries its internal database to search for relevant information based on the extracted keywords, resulting in the acquisition of legal provisions and past legal precedents related to rental contracts.

[0864] 5. The server generates the answer

[0865] Based on the information it has obtained, the server generates the following response: "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord's illegal activity is not involved."

[0866] 6. The server sends the answer to the device

[0867] The server sends the generated answer to the terminal as an HTTP response.

[0868] 7. The device will display the answer

[0869] The smartphone application receives the response and displays the following message on the screen: "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the termination does not involve illegal activity by the landlord."

[0870] This system allows users to easily and quickly obtain accurate information about legal issues without having to consult a legal professional, thus enabling users to deal with legal issues that arise in their daily lives.

[0871] The processing flow will be explained below.

[0872] Step 1:

[0873] A user uses a terminal to input a legal question into an input form. For example, the user inputs, "Are there any penalties if I terminate a rental contract early?"

[0874] Step 2:

[0875] The terminal sends the entered question data to the server using a communication protocol (e.g., HTTP POST) over the Internet.

[0876] Step 3:

[0877] The server receives the question data sent by the user and stores it in a database.

[0878] Step 4:

[0879] The server uses natural language processing (NLP) technology to analyze the received question, specifically extracting key keywords such as "rental contract," "mid-term termination," and "penalty."

[0880] Step 5:

[0881] Based on the extracted keywords, the server will refer to its internal database to identify relevant legal categories, for example, searching for laws and precedents related to "rental agreements."

[0882] Step 6:

[0883] The server searches an internal database of legal information and past case law data to retrieve specific information related to the user's question.

[0884] Step 7:

[0885] The server generates answers to user questions based on legal information and past precedents. Answers may include specific legal provisions and past precedents. For example, it may generate an answer such as, "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord's illegal actions are not included."

[0886] Step 8:

[0887] The server generates a response and sends it to the terminal, again using a communication protocol (e.g., HTTP response).

[0888] Step 9:

[0889] The terminal displays the answer received from the server to the user. The user interface is updated to display the answer in a format that is easy for the user to understand. For example, it may say, "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord's illegal activity is not involved."

[0890] Example 1

[0891] 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."

[0892] Conventional legal problem-solving systems have had issues such as delayed responses to user questions and the high cost of expert consultations. Furthermore, it is difficult for users without specialized legal knowledge to gather appropriate information on their own. This has led to a demand for a means for general users to quickly and effectively resolve legal problems.

[0893] 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.

[0894] In this invention, the server includes a means for storing received question data in a database, a means for analyzing the question using a natural language processing engine and extracting key keywords, and a means for generating answers using a generative AI model, thereby enabling the server to quickly and accurately generate and provide answers to user questions.

[0895] "User" means any person or entity that enters a legal question into the system.

[0896] "Terminal" refers to the electronic device used by the user to input questions and communicate with the server. Examples include smartphones, tablets, and personal computers.

[0897] "Server" refers to a central computing system that receives, analyzes, and generates answers to user-submitted question data.

[0898] "Question data" refers to legal inquiries entered by a user using a terminal.

[0899] "Database" refers to a collection of information accessed by a server that stores legal information and past court decisions.

[0900] A "natural language processing engine" refers to software technology for analyzing question data and extracting key keywords.

[0901] A "generative AI model" refers to an artificial intelligence technology that generates specific answers to users' questions based on acquired legal information.

[0902] "HTTPS" refers to a communication protocol for secure data communication between a terminal and a server.

[0903] "HTTP POST request" refers to a specific Internet protocol used to send query data from a terminal to a server.

[0904] "HTTP response" refers to a specific Internet protocol used to send response data from a server to a terminal.

[0905] "User interface" refers to an interactive display screen for interaction between a user and a terminal.

[0906] MODE FOR CARRYING OUT THE INVENTION

[0907] The present invention is a system for enabling users to quickly and effectively resolve common legal issues. The system is configured so that users input legal questions via a terminal, and a server provides appropriate answers to those questions. Specific embodiments for implementing the present invention are described below.

[0908] Hardware and software used

[0909] Devices: Electronic devices such as smartphones, tablets, and PCs

[0910] Server: A computing system equipped with a high-performance database and natural language processing engine.

[0911] Database: A collection of information containing legal documents and past court decisions

[0912] Natural language processing engine: Software technology for analyzing questions and extracting necessary information (e.g., SpaCy, BERT model)

[0913] Generative AI model: Artificial intelligence technology that generates specific answers based on acquired legal information

[0914] Processing flow

[0915] A user uses a device to input a legal question. The input data is sent from the device to a server via an HTTP POST request. The server stores the received question data in a database and analyzes it using a natural language processing engine. The server identifies key keywords and related legal categories and searches for relevant information in a database that contains legal provisions, legal commentaries, and past court records.

[0916] Based on the acquired information, the server uses a generative AI model to generate a specific answer to the user's question. The generated answer is sent from the server to the device as an HTTP response, and the device converts it into a format suitable for the user interface and displays it so that the user can check it.

[0917] Specific examples

[0918] Below is a specific example of use based on the above processing flow.

[0919] 1. The user enters a question

[0920] The user operates a terminal (e.g., a smartphone) and enters, "Will there be a penalty if I terminate the rental contract midway?"

[0921] 2. The device sends a question to the server

[0922] The smartphone application sends the entered question data to the server via an HTTP POST request, using the HTTPS protocol to ensure secure data transmission.

[0923] 3. The server parses the question

[0924] The server stores the received question data in a database and analyzes the question using a natural language processing engine (e.g., SpaCy, BERT model) to extract keywords such as "rental contract," "early termination," and "penalty fee."

[0925] 4. The server references legal information and past cases

[0926] The server accesses an internal database and searches for relevant legal documents and past cases based on the extracted keywords.

[0927] 5. The server generates the answer

[0928] The server uses a generative AI model to generate specific answers based on the information it receives.

[0929] For example: "In a rental agreement, if you terminate the agreement early, you may be subject to a penalty if it is clearly stated in the agreement. However, this only applies if the landlord's illegal actions are not involved."

[0930] 6. The server sends the answer to the device

[0931] The server generates an answer and sends it to the device as an HTTP response, which contains the answer formatted in the appropriate format.

[0932] 7. The device will display the answer

[0933] The smartphone application receives the response and displays the following message on the screen: "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the termination does not involve illegal activity by the landlord."

[0934] This system allows users to quickly and effectively obtain accurate information on legal issues without having to rely on a specialist, and also allows users to easily acquire knowledge to deal with legal issues that arise in their daily lives.

[0935] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0936] Step 1:

[0937] User enters legal question

[0938] The user opens a dedicated application or web interface on their device (e.g., smartphone, PC) and enters their question into the input form.

[0939] Input data: Legal questions entered by the user (e.g., "Are there any penalties for breaking a lease early?")

[0940] Output: Question data entered by the user

[0941] Step 2:

[0942] The device sends a question to the server

[0943] The device packages the entered question data in JSON format and sends it to the server via an HTTP POST request, using HTTPS to ensure secure communication.

[0944] Input data: Question data converted to JSON format

[0945] Output: HTTP POST request sent to the server

[0946] Step 3:

[0947] The server receives and analyzes the query.

[0948] The server parses the received HTTP POST request, extracts and saves the question data, and then uses a natural language processing engine (e.g., SpaCy, BERT model) to analyze the question and extract key keywords (e.g., "rental agreement," "early termination," "penalty fee").

[0949] Input data: Question data in an HTTP POST request

[0950] Data processing: Analysis of question data, extraction of important keywords

[0951] Output: Extracted keywords

[0952] Step 4:

[0953] The server references legal information and past cases

[0954] The server then uses the extracted keywords to query an internal database that contains legal provisions, legal commentaries, and past legal precedents to find relevant legal documents and past cases.

[0955] Input data: extracted keywords

[0956] Data processing: querying databases and searching for relevant information

[0957] Output: Relevant legal documents, provisions, and past cases

[0958] Step 5:

[0959] The server generates the answer

[0960] The server uses a generative AI model to generate specific answers based on the legal information it receives, and formats the answers in a way that is easy for users to understand.

[0961] Input data: relevant legal documents, statutes, and past precedents

[0962] Data processing: Generate answers and convert formats using AI models

[0963] Output: The specific answer generated

[0964] Step 6:

[0965] The server sends the answer to the device

[0966] The server packages the generated response in JSON format and sends it to the terminal as an HTTP response, again using the HTTPS protocol to ensure communication security.

[0967] Input data: Generated answers

[0968] Data processing: conversion to JSON format, generation of HTTP response

[0969] Output: HTTP response sent to the device

[0970] Step 7:

[0971] The device displays the answer

[0972] The device analyzes the received HTTP response and converts the response data into a format suitable for the user interface (e.g., HTML, in-app display format), and displays it. The user can check the response on the screen.

[0973] Input data: Response data in the HTTP response

[0974] Data processing: converting data into a format suitable for the user interface

[0975] Output: The answer displayed in the user interface

[0976] (Application example 1)

[0977] 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."

[0978] There is a need for fast and effective responses to legal issues in brick-and-mortar stores, but currently, it is difficult for store staff without legal expertise to provide appropriate answers. Furthermore, there is a lack of means to obtain immediate and accurate answers to customers' legal problems, so problems often take a long time to resolve. To solve these problems, a legal response system that can be easily used in stores is needed.

[0979] 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.

[0980] In this invention, the server includes: means for a user to input a legal question; means for a terminal to transmit the user's input data to the server; means for the server to analyze the received question and identify legal categories associated with major keywords; means for the server to reference a database storing legal information and past precedents and acquire specific legal information; means for the server to generate an answer to the user's question based on the acquired legal information; means for the server to transmit the generated answer to the terminal; means for the terminal to display or output the answer from the server as voice to the user; means for the tablet terminal, smartphone, or robot to input the legal question by voice or text; and means for the tablet terminal, smartphone, or robot to transmit the question data to the server. This enables users to ask legal questions using simple input means and receive accurate answers immediately.

[0981] A "User" is any person or entity that utilizes the System to enter legal questions and receive answers.

[0982] "Terminal" refers to a device that allows a user to input legal questions and transmit the input data to a server, including a tablet, smartphone, or robot.

[0983] A "server" is a computer system that analyzes questions received from users, generates answers based on legal information and past precedents, and sends them to terminals.

[0984] A "database" is a storage system that stores legal information and past precedents, which the server references to obtain the necessary information.

[0985] "Natural language processing technology" is a technology that allows the server to analyze the user's question and identify key keywords and related legal categories.

[0986] A "tablet" is a handheld computing device used by users to voice or text legal questions.

[0987] A "smartphone" is a mobile phone-type multifunction device used by users to voice or text legal questions.

[0988] A "robot" is a mechanical device used by users to voice or text legal questions.

[0989] "Voice input" is a method in which a user voices legal questions into a microphone.

[0990] "Text entry" is a method in which a user enters legal questions as text via a keyboard or touchscreen.

[0991] First, we will explain in detail the main components that make up the system for realizing this invention. The entire system utilizes terminals used by users, a server that processes data, and appropriate software to operate these in conjunction with each other.

[0992] Hardware used

[0993] The hardware used in this system is as follows:

[0994] Tablet devices: Used by users to dictate or text legal questions.

[0995] Smartphones: Used by users to dictate or text legal questions.

[0996] Interactive robots: used by users to voice or text legal questions.

[0997] Software used

[0998] The main software and technologies used in this system are as follows:

[0999] Flask: A Python web framework used to handle server-side HTTP requests and responses.

[1000] Transformers: A natural language processing library developed by Hugging Face that uses a question-answering (QnA) model to generate answers to questions.

[1001] Natural Language Processing Technology (NLP): Used by the server to analyze the questions received from the user and identify key keywords and relevant legal categories.

[1002] Data Flow and Processing

[1003] A user enters a legal question into a device (tablet, smartphone, or robot) using either voice or text input. The device then sends the user's input to a server. This communication typically occurs over the internet using an HTTP POST request.

[1004] The server analyzes the received query using NLP techniques to identify key keywords and associated legal categories, then accesses a database to search for legal information and past cases based on the specific keywords and legal categories.

[1005] Based on the legal information acquired by the server, a specific answer to the user's question is generated using a question-answering (QnA) model from the Transformers library.

[1006] The generated answer is sent from the server to the terminal, which displays or speaks the answer to the user, thereby providing the user with an immediate and accurate answer to their legal question.

[1007] Specific examples

[1008] For example, if a customer asks an interactive robot, "What should I do if my credit card is fraudulently used?", the question is entered as follows:

[1009] What to do if your credit card is fraudulently used?

[1010] The server receives and analyzes this question, retrieving relevant legal information and precedents from a database. For example, it extracts keywords such as "credit card," "fraudulent use," and "how to deal with it," and searches relevant legal provisions and past precedents. As a result, the server generates an answer like this:

[1011] If your credit card has been used fraudulently, first contact your card company and ask them to investigate the fraud. You should also file a police report and consider changing your password to prevent the leaking of personal information.

[1012] This generated answer is immediately provided to the user, allowing even store staff and customers who are not familiar with the law to quickly deal with legal issues.

[1013] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1014] Step 1:

[1015] The user inputs legal questions into a device (tablet, smartphone, or robot) by voice or text input. The input data is saved in the device as text data of the question.

[1016] Step 2:

[1017] The device sends the entered question data to the server using an HTTP POST request. This request includes the question text entered by the user. Specifically, the question data is embedded in the body of the request in JSON format.

[1018] Step 3:

[1019] The server analyzes the received question data. It takes the question text contained in the HTTP request body as input and uses natural language processing (NLP) techniques to identify key keywords and associated legal categories. Specifically, the NLP model tokenizes the text and extracts key keywords from it.

[1020] Step 4:

[1021] The server searches the database based on the analyzed keywords. The identified keywords are sent as input to the database in the form of an SQL query or similar to retrieve corresponding legal information and past precedents. As output, the relevant legal information and precedents are returned to the server.

[1022] Step 5:

[1023] The server generates a specific answer to the user's question based on the legal information it has acquired. In this step, it uses the acquired data to generate a text-based answer using the GEN AI model (a generative AI model). The acquired legal information and keywords are used as input, and a complete answer text is generated as output.

[1024] Step 6:

[1025] The server sends the generated response data to the terminal as an HTTP response. As output, the generated response text is included in the body of the HTTP response.

[1026] Step 7:

[1027] The device displays or audibly outputs the answer data received from the server to the user. It takes the answer text contained in the body of the HTTP response as input and displays it on the user interface or outputs it audibly using a text-to-speech (TTS) system. Specifically, it displays the answer text on the screen in an appropriate format or passes it to a speech synthesis engine and outputs it from the speaker.

[1028] 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.

[1029] The present invention is a system that allows users to quickly and effectively solve common legal problems, and by combining an emotion engine, provides appropriate answers according to the user's emotional state. This system is configured so that a user inputs a legal question via a terminal, a server provides an appropriate answer to the question, and the emotion engine analyzes the user's emotional state and provides the answer in an appropriate tone.

[1030] Program processing overview

[1031] The user enters a question

[1032] A user types a legal question into a form on a device, for example, "How do I start divorce proceedings?"

[1033] The device sends a question to the server

[1034] The terminal sends the user's input data to the server via the Internet using a communication protocol (e.g., HTTP POST).

[1035] The server receives and analyzes the query.

[1036] The server receives the query data submitted by the user, stores it in a database, and then uses natural language processing (NLP) technology to analyze the query and identify key keywords and related legal categories.

[1037] Emotion engine analyzes the user's emotional state

[1038] The server uses an emotion engine to analyze the user's emotional state from the input data, for example, determining whether the user is feeling anxious or angry based on the tone and keywords in the text.

[1039] The server references legal information and past cases

[1040] The server accesses an internal database containing legal texts, legal commentary documents, and past court records to retrieve the required legal information and past cases based on the identified keywords and legal categories.

[1041] The server generates the answer

[1042] The server generates answers to users' questions based on the acquired legal information and case law. The tone of the answer is adjusted based on the emotional data provided by the emotion engine. For example, if the user is feeling anxious, the answer will be written in a comforting tone.

[1043] The server sends the answer to the device

[1044] The server generates a response and sends it to the terminal, where it is converted into a format suitable for display on the user interface.

[1045] The device displays the answer

[1046] The device will display the answer received from the server on the screen. The answer will be adjusted to be displayed in a format that is easy for the user to understand. For example, it may say, "To begin divorce proceedings, you will need to go to city hall and submit the necessary documents. Specifically, you will need a divorce notification form and an extract of your family register. Please stay calm and proceed one step at a time."

[1047] Specific examples

[1048] Below is a specific example of use based on the above processing flow.

[1049] 1. The user enters a question

[1050] The user operates a terminal (e.g., a smartphone) and enters, "Will there be a penalty if I terminate the rental contract midway?"

[1051] 2. The device sends a question to the server

[1052] The smartphone application sends the entered question data to the server via an HTTP POST request.

[1053] 3. The server receives and analyzes the query

[1054] The server receives the question data and uses natural language processing technology to extract important keywords such as "rental contract," "mid-term termination," and "penalty fee."

[1055] 4. The emotion engine analyzes the user's emotional state

[1056] The server uses an emotion engine to analyze the user's emotional state and determine whether the user is feeling stressed from the tone of the questions.

[1057] 5. The server references legal information and past cases

[1058] The server queries its internal database to search for relevant information based on the extracted keywords, resulting in the acquisition of legal provisions and past legal precedents related to rental contracts.

[1059] 6. The server generates the answer

[1060] The server generates a response in an appropriate tone based on the acquired information and the data provided by the emotion engine. For example, it generates a response such as, "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord's illegal actions are not included. This may be worrying, but please take appropriate measures."

[1061] 7. The server sends the answer to the device

[1062] The server sends the generated answer to the terminal as an HTTP response.

[1063] 8. The device will display the answer

[1064] The smartphone application receives the response and displays the following message on the screen: "If you terminate a rental contract midway, you may be charged a penalty if it is clearly stated in the contract. However, this only applies if the landlord has not engaged in illegal activity. This may be worrying, but you should take appropriate measures."

[1065] This system allows users to easily and quickly obtain accurate information about legal issues without relying on a specialist, and to receive appropriate answers that take into account their own emotional state, thus enabling users to deal with legal issues that arise in their daily lives.

[1066] The processing flow will be explained below.

[1067] Step 1:

[1068] A user uses a terminal to input a legal question into an input form. For example, the user inputs, "Are there any penalties if I terminate a rental contract early?"

[1069] Step 2:

[1070] The terminal sends the entered question data to the server using a communication protocol (e.g., HTTP POST) over the Internet.

[1071] Step 3:

[1072] The server receives the question data sent by the user and stores it in a database.

[1073] Step 4:

[1074] The server uses natural language processing (NLP) technology to analyze the received question, specifically extracting key keywords such as "rental contract," "mid-term termination," and "penalty."

[1075] Step 5:

[1076] Based on the extracted keywords, the server will refer to its internal database to identify relevant legal categories, for example, searching for laws and precedents related to "rental agreements."

[1077] Step 6:

[1078] The emotion engine analyzes the user's emotional state from the input data, for example, determining whether the user is feeling anxious or angry based on the tone of the text and the keywords used.

[1079] Step 7:

[1080] The server adjusts the tone of the response based on the emotional data provided by the emotion engine: if the user is feeling anxious, the answer will be written in a comforting tone.

[1081] Step 8:

[1082] The server searches an internal database of legal information and past case law data to retrieve specific information related to the user's question.

[1083] Step 9:

[1084] The server generates answers to user questions based on legal information and past legal precedents. Answers may include specific legal provisions and past cases. For example, it might generate an answer like, "In the case of mid-term termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord has committed no illegal acts. This may be worrying, but you should take appropriate measures."

[1085] Step 10:

[1086] The server generates a response and sends it to the terminal, again using a communication protocol (e.g., HTTP response).

[1087] Step 11:

[1088] The device displays the response received from the server to the user. The user interface is updated to display the response in a format that is easy for the user to understand. For example, it might say, "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord's illegal activity is not involved. This may be worrying, but please take appropriate measures."

[1089] Example 2

[1090] 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."

[1091] In modern society, we often face legal problems, and it is difficult for ordinary citizens, especially those without specialized knowledge, to obtain legal information quickly and accurately. This requires time and money to consult with experts, and there is a need for a way to resolve these problems while also managing one's own emotions appropriately. However, existing systems lack the ability to provide appropriate advice that takes into account emotional states.

[1092] 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.

[1093] In this invention, the server includes means for using an emotion engine to analyze the emotional state of the user from input data, means for adjusting the tone of the response based on the emotional data provided by the emotion engine, and means for using natural language processing techniques to identify legal categories associated with key keywords, thereby enabling the user to quickly obtain accurate legal information that takes into account the user's emotional state.

[1094] A "user" is a person who utilizes the system to enter a legal question.

[1095] A "terminal" is a device that a user operates to input questions, and refers to electronic devices such as smartphones and personal computers.

[1096] A "server" is a computer system that analyzes the received data, generates a response based on legal information and past precedents, and sends it to the terminal.

[1097] "Natural language processing technology" is a technology that analyzes the content of questions entered by users to identify key keywords and related legal categories.

[1098] An "emotion engine" is software or a system for analyzing a user's emotional state from input data.

[1099] A "database" is a collection of data that stores legal information and past case law information and can be referenced as needed.

[1100] "Tone of response" refers to the emotional expression or tone of the generated response, which is adjusted according to the user's emotional state.

[1101] "Legal information" refers to all information related to the law, such as legal explanations, provisions, or past court decisions.

[1102] The present invention is a system that allows users to quickly and effectively solve common legal problems, and by combining an emotion engine, provides appropriate answers according to the user's emotional state. This system is composed of terminals, a server, a database, an emotion engine, and natural language processing technology.

[1103] First, the user enters a legal question through a device, such as a smartphone or PC. For example, a user might use a smartphone to enter "How do I start divorce proceedings?" into an application form.

[1104] Next, the terminal sends the user-entered question data to the server via the Internet using the HTTP POST request protocol, which sends the input data to the server and the system begins processing the question.

[1105] The server first stores the received question data in a database, which stores legal information and past legal precedents. A database system such as MongoDB is used. Next, the server analyzes the question using natural language processing technology (e.g., SpaCy, Gensim) to identify key keywords and related legal categories. This process allows the system to accurately understand the user's intent in the question.

[1106] Furthermore, the server analyzes the user's emotional state using an emotion engine, such as IBM Watson Tone Analyzer, which can analyze the user's emotional state, such as anxiety or anger, from the user's input data.

[1107] The server then queries its internal database to find relevant legal information and past cases based on the analyzed keywords and legal categories. The server generates a response based on the retrieved information, adjusting the tone of the response based on the emotional data provided by the emotion engine. For example, if the user is feeling anxious, the response will be written in a comforting tone. The response might be something like, "You need to go to city hall and submit the necessary documents. Specifically, you need a divorce notice and a copy of your family register. Please proceed with the process without worry."

[1108] The generated answers are sent from the server to the terminal and displayed on the terminal. The user interface is designed to provide answers in a format that is easy for the user to understand.

[1109] For example, consider the following prompt:

[1110] Are there any penalties if I cancel my lease early?

[1111] This system not only allows users to quickly obtain accurate legal information without relying on a specialist, but also provides answers that take into consideration their emotional state, enabling users to quickly respond to legal issues that arise in their daily lives.

[1112] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1113] Step 1:

[1114] The user enters a question

[1115] The user operates the terminal and inputs a question about a legal issue into the input form. The input question is prepared as text data. This text data is input in preparation for processing in the next step.

[1116] Input: User question (e.g., "How do I start divorce proceedings?")

[1117] Output: Text data entered in the input form

[1118] Step 2:

[1119] The device sends a question to the server

[1120] The terminal sends the text data entered by the user to the server using an HTTP POST request, and the sent data reaches the server via the Internet.

[1121] Input: Text data in the input form

[1122] Output: HTTP POST request sent to the server

[1123] Step 3:

[1124] The server receives and analyzes the query.

[1125] The server first stores the received text data in a database, then uses natural language processing (NLP) techniques to analyze the text data and identify key keywords (e.g., "divorce" and "procedure") and related legal categories.

[1126] Input: Text data of HTTP POST request

[1127] Output: Identified keywords and legal categories

[1128] Step 4:

[1129] Emotion engine analyzes the user's emotional state

[1130] The server passes the received text data to the emotion engine, which analyzes the user's emotional state. The emotion engine infers emotions from the tone of the text and specific keywords.

[1131] Input: Text data

[1132] Output: Emotional state data (e.g., anxiety, anger)

[1133] Step 5:

[1134] The server references legal information and past cases

[1135] The server uses the identified keywords and legal categories to access an internal database and search for relevant legal information and past cases.

[1136] Input: Identified keywords and legal categories

[1137] Output: Retrieved relevant legal information and past cases

[1138] Step 6:

[1139] The server generates the answer

[1140] The server generates an answer to the user's question based on the acquired legal information and emotional data, and the tone of the answer is adjusted based on the emotional data.

[1141] Input: Obtained legal information, past cases, and emotional state data

[1142] Output: Answer text with adjusted emotional tone

[1143] Step 7:

[1144] The server sends the answer to the device

[1145] The server sends the generated answer text to the terminal as an HTTP response.

[1146] Input: Answer text

[1147] Output: The answer text sent in the HTTP response

[1148] Step 8:

[1149] The device displays the answer

[1150] The terminal displays the answer text received as an HTTP response on the user interface, adjusted to a format that is easy for the user to view.

[1151] Input: HTTP response answer text

[1152] Output: Answer text displayed on the screen

[1153] Through these processing steps, users can obtain relevant and emotionally sensitive answers to their legal questions.

[1154] (Application example 2)

[1155] 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."

[1156] The problem to be solved by the present invention is to provide not only legal answers but also answers in an appropriate tone that takes into consideration the emotional state of the user when solving legal questions quickly and effectively. In particular, the present invention aims to provide a system that can respond to customers in a way that does not cause anxiety or stress in customer support situations where the tone of the answer is important.

[1157] The identification process by the identification 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 the emotional state of a user using an emotion analysis engine, means for referencing a database storing legal information and past precedents and acquiring specific legal information, and means for generating an answer to a user's question based on the acquired legal information and the emotion analysis results. This makes it possible, when a user asks a question, to quickly provide an answer in an appropriate tone that takes into account the user's emotional state.

[1158] Definition of Terms

[1159] A "user" is someone who utilizes the system to input a legal question.

[1160] A "question" is a request for legal information or a matter for consultation entered by a user.

[1161] A "terminal" is a device through which a user inputs legal questions and communicates with the server, and includes smartphones and personal computers.

[1162] A "server" is a device that receives legal questions sent by users, analyzes them, and generates answers.

[1163] An "emotion analysis engine" is software or hardware for analyzing a user's emotional state from input data.

[1164] "Natural language processing technology" is a technology that analyzes questions entered by users and identifies key keywords and related legal categories.

[1165] A "database" is a collection of information that stores legal information and past precedents and can be referenced by a server.

[1166] "Answers" are legal information and advice generated by the server based on the user's question.

[1167] "Means for analyzing the question" refers to the process by which the server uses natural language processing technology to analyze the content of the question entered by the user and extract key keywords and related legal categories.

[1168] The "means for generating an answer" is the process by which the server creates an answer to the user's question based on the legal information and sentiment analysis results it has obtained.

[1169] The "means for displaying the answer" is a function that visually presents the answer that the terminal receives from the server to the user.

[1170] MODE FOR CARRYING OUT THE INVENTION

[1171] This invention relates to a legal consultation system that incorporates an emotion engine, and is particularly applicable to customer support on online shopping sites. This system allows users to input legal questions and send the information to a server, which provides quick and emotionally sensitive answers.

[1172] Hardware and software used

[1173] To implement the system, the following hardware and software are used.

[1174] Hardware

[1175] Device: A smartphone used by a user, allowing the user to enter legal questions and receive answers.

[1176] Server: A powerful computing device that processes data sent by users and generates answers.

[1177] software

[1178] Natural Language Processing Technology (NLPProcessor): Technology that analyzes user questions and identifies key keywords and relevant legal categories.

[1179] Emotion Analysis Engine (EmotionEngine): A technology that analyzes the emotional state of a user from input data and determines their emotions based on the tone of the questions and keywords they enter.

[1180] Database: A collection of information for storing legal information and past precedents. The server references this database to obtain the necessary information.

[1181] Requests library: A library for HTTP communication. Used to send data between the terminal and the server.

[1182] Specific operation of the system

[1183] 1. Enter your question

[1184] Users use a smartphone application to input legal questions, such as, "I'm having trouble with the complicated return process. How should I proceed?"

[1185] 2. Submit your question

[1186] The smartphone application sends the entered question data to the server using an HTTP POST request, using the "requests" library.

[1187] 3. Question and Sentiment Analysis

[1188] The server analyzes the received inquiry data. First, it uses natural language processing technology (NLPProcessor) to analyze the content of the inquiry and identify key keywords and related legal categories.

[1189] Next, the "Emotion Engine" is used to analyze the user's emotional state and determine emotions such as anxiety or stress.

[1190] 4. Obtaining relevant information

[1191] The server accesses a "database" to search for legal information and past cases, and retrieves the required information based on the identified keywords and categories.

[1192] 5. Answer Generation

[1193] The server generates a response in an appropriate tone based on the acquired information and the results of sentiment analysis. For example, a user who is feeling anxious might receive a response such as, "Don't worry. Please follow the steps below to process your return."

[1194] 6. Submitting and Viewing Your Answers

[1195] The server generates an answer and sends it to the device as an HTTP response. The smartphone application receives the answer and presents it visually to the user.

[1196] Examples of specific examples and prompts

[1197] Specific examples

[1198] The user enters a question through a smartphone application, such as "The return procedure is complicated and I'm having trouble. How should I proceed?" The server analyzes the question and detects that the user is feeling anxious. The server retrieves information about the return procedure from the database, generates a response such as "Don't worry. Please follow the steps below to return the product," and provides it to the user.

[1199] Prompt Sentence Examples

[1200] "Use sentiment engines and natural language processing to answer customer questions about returns, like: 'I'm having trouble with the complicated returns process. How do I proceed?'"

[1201] The above is an embodiment of the present invention.

[1202] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1203] Program processing steps

[1204] Step 1:

[1205] Users input legal questions through a smartphone application. Data is generated by entering specific questions into this input form (e.g., "I'm having trouble with the complicated return procedure. How should I proceed?"). The input data includes the text information of the question.

[1206] Step 2:

[1207] The device (smartphone) sends the entered question data to the server using an HTTP POST request. At this time, the input data is sent as part of the HTTP request. The input data is sent to the server and received by the server.

[1208] Step 3:

[1209] The server analyzes the received question data. First, it uses natural language processing technology (NLPProcessor) to analyze the text data of the question and extract key keywords and related legal categories. The input data is analyzed, and the extracted keywords and categories are output (e.g., "return," "procedure," "complex," etc.).

[1210] Step 4:

[1211] The server uses an emotion analysis engine (EmotionEngine) to analyze the user's emotional state from the input data. Based on the linguistic features of the input data (e.g., tone and keywords), it determines the emotion the user is feeling (e.g., anxiety, confusion). The results of the emotion analysis are output and used in the next step.

[1212] Step 5:

[1213] The server references a database containing legal information and past precedents and retrieves relevant information based on the extracted keywords and categories. The input data is used as a database query, and the required legal information and past precedent data is output.

[1214] Step 6:

[1215] The server generates an answer to the user's question based on the legal information acquired and the results of sentiment analysis. Specifically, the answer is created based on the legal information and in a tone that takes into account the sentiment data. For example, the generated answer might be something like, "Don't worry. Please follow the steps below to process your return."

[1216] Step 7:

[1217] The server generates an answer and sends it to the terminal as an HTTP response. The generated answer is output in document format and sent as part of the HTTP response. The terminal receives this answer.

[1218] Step 8:

[1219] The device displays the answer received from the server to the user. The received data is visualized by the smartphone application, and the appropriate answer is displayed on the screen for the user.

[1220] The above is the specific processing flow of the program.

[1221] 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.

[1222] 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.

[1223] 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.

[1224] [Fourth embodiment]

[1225] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1226] 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.

[1227] 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).

[1228] 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.

[1229] 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.

[1230] 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).

[1231] 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.

[1232] 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.

[1233] 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.

[1234] 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.

[1235] 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.

[1236] 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.

[1237] 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."

[1238] The present invention provides a system for users to quickly and effectively resolve common legal issues. The system involves users inputting legal questions via a terminal, and a server providing appropriate answers to those questions.

[1239] Program processing overview

[1240] The user enters a question

[1241] The user enters a legal question into a form on the device. The user can enter a specific legal issue or question.

[1242] The device sends a question to the server

[1243] The terminal sends the entered question data to the server using a communication protocol (e.g., HTTP POST) over the Internet.

[1244] The server receives and analyzes the query.

[1245] The server receives the question data sent by the user and stores it in a database.

[1246] Next, natural language processing technology is used to analyze the question and identify key keywords and associated legal categories.

[1247] The server references legal information and past cases

[1248] The server accesses an internal database that searches for legal information and past cases based on the identified keywords and legal categories. This database contains legal provisions, legal commentary documents, and past court records.

[1249] The server generates the answer

[1250] The server uses the acquired legal information and case law to generate specific answers to the user's questions, written in a clear and easy-to-understand format.

[1251] The server sends the answer to the device

[1252] The server then sends the generated answer to the user's device, where it is converted into a format suitable for display on the user interface.

[1253] The device displays the answer

[1254] The device displays the answer received from the server on the screen, and the user can check the displayed answer and use it as a reference for solving the problem.

[1255] Specific examples

[1256] Below is a specific example of use based on the above processing flow.

[1257] 1. The user enters a question

[1258] The user operates a terminal (e.g., a smartphone) and enters, "Will there be a penalty if I terminate the rental contract midway?"

[1259] 2. The device sends a question to the server

[1260] The smartphone application sends the entered question data to the server via an HTTP POST request.

[1261] 3. The server receives and analyzes the query

[1262] The server receives the question data and uses natural language processing technology to extract important keywords such as "rental contract," "mid-term termination," and "penalty fee."

[1263] 4. The server references legal information and past cases

[1264] The server queries its internal database to search for relevant information based on the extracted keywords, resulting in the acquisition of legal provisions and past legal precedents related to rental contracts.

[1265] 5. The server generates the answer

[1266] Based on the information it has obtained, the server generates the following response: "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord's illegal activity is not involved."

[1267] 6. The server sends the answer to the device

[1268] The server sends the generated answer to the terminal as an HTTP response.

[1269] 7. The device will display the answer

[1270] The smartphone application receives the response and displays the following message on the screen: "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the termination does not involve illegal activity by the landlord."

[1271] This system allows users to easily and quickly obtain accurate information about legal issues without having to consult a legal professional, thus enabling users to deal with legal issues that arise in their daily lives.

[1272] The processing flow will be explained below.

[1273] Step 1:

[1274] A user uses a terminal to input a legal question into an input form. For example, the user inputs, "Are there any penalties if I terminate a rental contract early?"

[1275] Step 2:

[1276] The terminal sends the entered question data to the server using a communication protocol (e.g., HTTP POST) over the Internet.

[1277] Step 3:

[1278] The server receives the question data sent by the user and stores it in a database.

[1279] Step 4:

[1280] The server uses natural language processing (NLP) technology to analyze the received question, specifically extracting key keywords such as "rental contract," "mid-term termination," and "penalty."

[1281] Step 5:

[1282] Based on the extracted keywords, the server will refer to its internal database to identify relevant legal categories, for example, searching for laws and precedents related to "rental agreements."

[1283] Step 6:

[1284] The server searches an internal database of legal information and past case law data to retrieve specific information related to the user's question.

[1285] Step 7:

[1286] The server generates answers to user questions based on legal information and past precedents. Answers may include specific legal provisions and past precedents. For example, it may generate an answer such as, "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord's illegal actions are not included."

[1287] Step 8:

[1288] The server generates a response and sends it to the terminal, again using a communication protocol (e.g., HTTP response).

[1289] Step 9:

[1290] The terminal displays the answer received from the server to the user. The user interface is updated to display the answer in a format that is easy for the user to understand. For example, it may say, "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord's illegal activity is not involved."

[1291] Example 1

[1292] 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."

[1293] Conventional legal problem-solving systems have had issues such as delayed responses to user questions and the high cost of expert consultations. Furthermore, it is difficult for users without specialized legal knowledge to gather appropriate information on their own. This has led to a demand for a means for general users to quickly and effectively resolve legal problems.

[1294] 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.

[1295] In this invention, the server includes a means for storing received question data in a database, a means for analyzing the question using a natural language processing engine and extracting key keywords, and a means for generating answers using a generative AI model, thereby enabling the server to quickly and accurately generate and provide answers to user questions.

[1296] "User" means any person or entity that enters a legal question into the system.

[1297] "Terminal" refers to the electronic device used by the user to input questions and communicate with the server. Examples include smartphones, tablets, and personal computers.

[1298] "Server" refers to a central computing system that receives, analyzes, and generates answers to user-submitted question data.

[1299] "Question data" refers to legal inquiries entered by a user using a terminal.

[1300] "Database" refers to a collection of information accessed by a server that stores legal information and past court decisions.

[1301] A "natural language processing engine" refers to software technology for analyzing question data and extracting key keywords.

[1302] A "generative AI model" refers to an artificial intelligence technology that generates specific answers to users' questions based on acquired legal information.

[1303] "HTTPS" refers to a communication protocol for secure data communication between a terminal and a server.

[1304] "HTTP POST request" refers to a specific Internet protocol used to send query data from a terminal to a server.

[1305] "HTTP response" refers to a specific Internet protocol used to send response data from a server to a terminal.

[1306] "User interface" refers to an interactive display screen for interaction between a user and a terminal.

[1307] MODE FOR CARRYING OUT THE INVENTION

[1308] The present invention is a system for enabling users to quickly and effectively resolve common legal issues. The system is configured so that users input legal questions via a terminal, and a server provides appropriate answers to those questions. Specific embodiments for implementing the present invention are described below.

[1309] Hardware and software used

[1310] Devices: Electronic devices such as smartphones, tablets, and PCs

[1311] Server: A computing system equipped with a high-performance database and natural language processing engine.

[1312] Database: A collection of information containing legal documents and past court decisions

[1313] Natural language processing engine: Software technology for analyzing questions and extracting necessary information (e.g., SpaCy, BERT model)

[1314] Generative AI model: Artificial intelligence technology that generates specific answers based on acquired legal information

[1315] Processing flow

[1316] A user uses a device to input a legal question. The input data is sent from the device to a server via an HTTP POST request. The server stores the received question data in a database and analyzes it using a natural language processing engine. The server identifies key keywords and related legal categories and searches for relevant information in a database that contains legal provisions, legal commentaries, and past court records.

[1317] Based on the acquired information, the server uses a generative AI model to generate a specific answer to the user's question. The generated answer is sent from the server to the device as an HTTP response, and the device converts it into a format suitable for the user interface and displays it so that the user can check it.

[1318] Specific examples

[1319] Below is a specific example of use based on the above processing flow.

[1320] 1. The user enters a question

[1321] The user operates a terminal (e.g., a smartphone) and enters, "Will there be a penalty if I terminate the rental contract midway?"

[1322] 2. The device sends a question to the server

[1323] The smartphone application sends the entered question data to the server via an HTTP POST request, using the HTTPS protocol to ensure secure data transmission.

[1324] 3. The server parses the question

[1325] The server stores the received question data in a database and analyzes the question using a natural language processing engine (e.g., SpaCy, BERT model) to extract keywords such as "rental contract," "early termination," and "penalty fee."

[1326] 4. The server references legal information and past cases

[1327] The server accesses an internal database and searches for relevant legal documents and past cases based on the extracted keywords.

[1328] 5. The server generates the answer

[1329] The server uses a generative AI model to generate specific answers based on the information it receives.

[1330] For example: "In a rental agreement, if you terminate the agreement early, you may be subject to a penalty if it is clearly stated in the agreement. However, this only applies if the landlord's illegal actions are not involved."

[1331] 6. The server sends the answer to the device

[1332] The server generates an answer and sends it to the device as an HTTP response, which contains the answer formatted in the appropriate format.

[1333] 7. The device will display the answer

[1334] The smartphone application receives the response and displays the following message on the screen: "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the termination does not involve illegal activity by the landlord."

[1335] This system allows users to quickly and effectively obtain accurate information on legal issues without having to rely on a specialist, and also allows users to easily acquire knowledge to deal with legal issues that arise in their daily lives.

[1336] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1337] Step 1:

[1338] User enters legal question

[1339] The user opens a dedicated application or web interface on their device (e.g., smartphone, PC) and enters their question into the input form.

[1340] Input data: Legal questions entered by the user (e.g., "Are there any penalties for breaking a lease early?")

[1341] Output: Question data entered by the user

[1342] Step 2:

[1343] The device sends a question to the server

[1344] The device packages the entered question data in JSON format and sends it to the server via an HTTP POST request, using HTTPS to ensure secure communication.

[1345] Input data: Question data converted to JSON format

[1346] Output: HTTP POST request sent to the server

[1347] Step 3:

[1348] The server receives and analyzes the query.

[1349] The server parses the received HTTP POST request, extracts and saves the question data, and then uses a natural language processing engine (e.g., SpaCy, BERT model) to analyze the question and extract key keywords (e.g., "rental agreement," "early termination," "penalty fee").

[1350] Input data: Question data in an HTTP POST request

[1351] Data processing: Analysis of question data, extraction of important keywords

[1352] Output: Extracted keywords

[1353] Step 4:

[1354] The server references legal information and past cases

[1355] The server then uses the extracted keywords to query an internal database that contains legal provisions, legal commentaries, and past legal precedents to find relevant legal documents and past cases.

[1356] Input data: extracted keywords

[1357] Data processing: querying databases and searching for relevant information

[1358] Output: Relevant legal documents, provisions, and past cases

[1359] Step 5:

[1360] The server generates the answer

[1361] The server uses a generative AI model to generate specific answers based on the legal information it receives, and formats the answers in a way that is easy for users to understand.

[1362] Input data: relevant legal documents, statutes, and past precedents

[1363] Data processing: Generate answers and convert formats using AI models

[1364] Output: The specific answer generated

[1365] Step 6:

[1366] The server sends the answer to the device

[1367] The server packages the generated response in JSON format and sends it to the terminal as an HTTP response, again using the HTTPS protocol to ensure communication security.

[1368] Input data: Generated answers

[1369] Data processing: conversion to JSON format, generation of HTTP response

[1370] Output: HTTP response sent to the device

[1371] Step 7:

[1372] The device displays the answer

[1373] The device analyzes the received HTTP response and converts the response data into a format suitable for the user interface (e.g., HTML, in-app display format), and displays it. The user can check the response on the screen.

[1374] Input data: Response data in the HTTP response

[1375] Data processing: converting data into a format suitable for the user interface

[1376] Output: The answer displayed in the user interface

[1377] (Application example 1)

[1378] 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."

[1379] There is a need for fast and effective responses to legal issues in brick-and-mortar stores, but currently, it is difficult for store staff without legal expertise to provide appropriate answers. Furthermore, there is a lack of means to obtain immediate and accurate answers to customers' legal problems, so problems often take a long time to resolve. To solve these problems, a legal response system that can be easily used in stores is needed.

[1380] 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.

[1381] In this invention, the server includes: means for a user to input a legal question; means for a terminal to transmit the user's input data to the server; means for the server to analyze the received question and identify legal categories associated with major keywords; means for the server to reference a database storing legal information and past precedents and acquire specific legal information; means for the server to generate an answer to the user's question based on the acquired legal information; means for the server to transmit the generated answer to the terminal; means for the terminal to display or output the answer from the server as voice to the user; means for the tablet terminal, smartphone, or robot to input the legal question by voice or text; and means for the tablet terminal, smartphone, or robot to transmit the question data to the server. This enables users to ask legal questions using simple input means and receive accurate answers immediately.

[1382] A "User" is any person or entity that utilizes the System to enter legal questions and receive answers.

[1383] "Terminal" refers to a device that allows a user to input legal questions and transmit the input data to a server, including a tablet, smartphone, or robot.

[1384] A "server" is a computer system that analyzes questions received from users, generates answers based on legal information and past precedents, and sends them to terminals.

[1385] A "database" is a storage system that stores legal information and past precedents, which the server references to obtain the necessary information.

[1386] "Natural language processing technology" is a technology that allows the server to analyze the user's question and identify key keywords and related legal categories.

[1387] A "tablet" is a handheld computing device used by users to voice or text legal questions.

[1388] A "smartphone" is a mobile phone-type multifunction device used by users to voice or text legal questions.

[1389] A "robot" is a mechanical device used by users to voice or text legal questions.

[1390] "Voice input" is a method in which a user voices legal questions into a microphone.

[1391] "Text entry" is a method in which a user enters legal questions as text via a keyboard or touchscreen.

[1392] First, we will explain in detail the main components that make up the system for realizing this invention. The entire system utilizes terminals used by users, a server that processes data, and appropriate software to operate these in conjunction with each other.

[1393] Hardware used

[1394] The hardware used in this system is as follows:

[1395] Tablet devices: Used by users to dictate or text legal questions.

[1396] Smartphones: Used by users to dictate or text legal questions.

[1397] Interactive robots: used by users to voice or text legal questions.

[1398] Software used

[1399] The main software and technologies used in this system are as follows:

[1400] Flask: A Python web framework used to handle server-side HTTP requests and responses.

[1401] Transformers: A natural language processing library developed by Hugging Face that uses a question-answering (QnA) model to generate answers to questions.

[1402] Natural Language Processing Technology (NLP): Used by the server to analyze the questions received from the user and identify key keywords and relevant legal categories.

[1403] Data Flow and Processing

[1404] A user enters a legal question into a device (tablet, smartphone, or robot) using either voice or text input. The device then sends the user's input to a server. This communication typically occurs over the internet using an HTTP POST request.

[1405] The server analyzes the received query using NLP techniques to identify key keywords and associated legal categories, then accesses a database to search for legal information and past cases based on the specific keywords and legal categories.

[1406] Based on the legal information acquired by the server, a specific answer to the user's question is generated using a question-answering (QnA) model from the Transformers library.

[1407] The generated answer is sent from the server to the terminal, which displays or speaks the answer to the user, thereby providing the user with an immediate and accurate answer to their legal question.

[1408] Specific examples

[1409] For example, if a customer asks an interactive robot, "What should I do if my credit card is fraudulently used?", the question is entered as follows:

[1410] What to do if your credit card is fraudulently used?

[1411] The server receives and analyzes this question, retrieving relevant legal information and precedents from a database. For example, it extracts keywords such as "credit card," "fraudulent use," and "how to deal with it," and searches relevant legal provisions and past precedents. As a result, the server generates an answer like this:

[1412] If your credit card has been used fraudulently, first contact your card company and ask them to investigate the fraud. You should also file a police report and consider changing your password to prevent the leaking of personal information.

[1413] This generated answer is immediately provided to the user, allowing even store staff and customers who are not familiar with the law to quickly deal with legal issues.

[1414] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1415] Step 1:

[1416] The user inputs legal questions into a device (tablet, smartphone, or robot) by voice or text input. The input data is saved in the device as text data of the question.

[1417] Step 2:

[1418] The device sends the entered question data to the server using an HTTP POST request. This request includes the question text entered by the user. Specifically, the question data is embedded in the body of the request in JSON format.

[1419] Step 3:

[1420] The server analyzes the received question data. It takes the question text contained in the HTTP request body as input and uses natural language processing (NLP) techniques to identify key keywords and associated legal categories. Specifically, the NLP model tokenizes the text and extracts key keywords from it.

[1421] Step 4:

[1422] The server searches the database based on the analyzed keywords. The identified keywords are sent as input to the database in the form of an SQL query or similar to retrieve corresponding legal information and past precedents. As output, the relevant legal information and precedents are returned to the server.

[1423] Step 5:

[1424] The server generates a specific answer to the user's question based on the legal information it has acquired. In this step, it uses the acquired data to generate a text-based answer using the GEN AI model (a generative AI model). The acquired legal information and keywords are used as input, and a complete answer text is generated as output.

[1425] Step 6:

[1426] The server sends the generated response data to the terminal as an HTTP response. As output, the generated response text is included in the body of the HTTP response.

[1427] Step 7:

[1428] The device displays or audibly outputs the answer data received from the server to the user. It takes the answer text contained in the body of the HTTP response as input and displays it on the user interface or outputs it audibly using a text-to-speech (TTS) system. Specifically, it displays the answer text on the screen in an appropriate format or passes it to a speech synthesis engine and outputs it from the speaker.

[1429] 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.

[1430] The present invention is a system that allows users to quickly and effectively solve common legal problems, and by combining an emotion engine, provides appropriate answers according to the user's emotional state. This system is configured so that a user inputs a legal question via a terminal, a server provides an appropriate answer to the question, and the emotion engine analyzes the user's emotional state and provides the answer in an appropriate tone.

[1431] Program processing overview

[1432] The user enters a question

[1433] A user types a legal question into a form on a device, for example, "How do I start divorce proceedings?"

[1434] The device sends a question to the server

[1435] The terminal sends the user's input data to the server via the Internet using a communication protocol (e.g., HTTP POST).

[1436] The server receives and analyzes the query.

[1437] The server receives the query data submitted by the user, stores it in a database, and then uses natural language processing (NLP) technology to analyze the query and identify key keywords and related legal categories.

[1438] Emotion engine analyzes the user's emotional state

[1439] The server uses an emotion engine to analyze the user's emotional state from the input data, for example, determining whether the user is feeling anxious or angry based on the tone and keywords in the text.

[1440] The server references legal information and past cases

[1441] The server accesses an internal database containing legal texts, legal commentary documents, and past court records to retrieve the required legal information and past cases based on the identified keywords and legal categories.

[1442] The server generates the answer

[1443] The server generates answers to users' questions based on the acquired legal information and case law. The tone of the answer is adjusted based on the emotional data provided by the emotion engine. For example, if the user is feeling anxious, the answer will be written in a comforting tone.

[1444] The server sends the answer to the device

[1445] The server generates a response and sends it to the terminal, where it is converted into a format suitable for display on the user interface.

[1446] The device displays the answer

[1447] The device will display the answer received from the server on the screen. The answer will be adjusted to be displayed in a format that is easy for the user to understand. For example, it may say, "To begin divorce proceedings, you will need to go to city hall and submit the necessary documents. Specifically, you will need a divorce notification form and an extract of your family register. Please stay calm and proceed one step at a time."

[1448] Specific examples

[1449] Below is a specific example of use based on the above processing flow.

[1450] 1. The user enters a question

[1451] The user operates a terminal (e.g., a smartphone) and enters, "Will there be a penalty if I terminate the rental contract midway?"

[1452] 2. The device sends a question to the server

[1453] The smartphone application sends the entered question data to the server via an HTTP POST request.

[1454] 3. The server receives and analyzes the query

[1455] The server receives the question data and uses natural language processing technology to extract important keywords such as "rental contract," "mid-term termination," and "penalty fee."

[1456] 4. The emotion engine analyzes the user's emotional state

[1457] The server uses an emotion engine to analyze the user's emotional state and determine whether the user is feeling stressed from the tone of the questions.

[1458] 5. The server references legal information and past cases

[1459] The server queries its internal database to search for relevant information based on the extracted keywords, resulting in the acquisition of legal provisions and past legal precedents related to rental contracts.

[1460] 6. The server generates the answer

[1461] The server generates a response in an appropriate tone based on the acquired information and the data provided by the emotion engine. For example, it generates a response such as, "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord's illegal actions are not included. This may be worrying, but please take appropriate measures."

[1462] 7. The server sends the answer to the device

[1463] The server sends the generated answer to the terminal as an HTTP response.

[1464] 8. The device will display the answer

[1465] The smartphone application receives the response and displays the following message on the screen: "If you terminate a rental contract midway, you may be charged a penalty if it is clearly stated in the contract. However, this only applies if the landlord has not engaged in illegal activity. This may be worrying, but you should take appropriate measures."

[1466] This system allows users to easily and quickly obtain accurate information about legal issues without relying on a specialist, and to receive appropriate answers that take into account their own emotional state, thus enabling users to deal with legal issues that arise in their daily lives.

[1467] The processing flow will be explained below.

[1468] Step 1:

[1469] A user uses a terminal to input a legal question into an input form. For example, the user inputs, "Are there any penalties if I terminate a rental contract early?"

[1470] Step 2:

[1471] The terminal sends the entered question data to the server using a communication protocol (e.g., HTTP POST) over the Internet.

[1472] Step 3:

[1473] The server receives the question data sent by the user and stores it in a database.

[1474] Step 4:

[1475] The server uses natural language processing (NLP) technology to analyze the received question, specifically extracting key keywords such as "rental contract," "mid-term termination," and "penalty."

[1476] Step 5:

[1477] Based on the extracted keywords, the server will refer to its internal database to identify relevant legal categories, for example, searching for laws and precedents related to "rental agreements."

[1478] Step 6:

[1479] The emotion engine analyzes the user's emotional state from the input data, for example, determining whether the user is feeling anxious or angry based on the tone of the text and the keywords used.

[1480] Step 7:

[1481] The server adjusts the tone of the response based on the emotional data provided by the emotion engine: if the user is feeling anxious, the answer will be written in a comforting tone.

[1482] Step 8:

[1483] The server searches an internal database of legal information and past case law data to retrieve specific information related to the user's question.

[1484] Step 9:

[1485] The server generates answers to user questions based on legal information and past legal precedents. Answers may include specific legal provisions and past cases. For example, it might generate an answer like, "In the case of mid-term termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord has committed no illegal acts. This may be worrying, but you should take appropriate measures."

[1486] Step 10:

[1487] The server generates a response and sends it to the terminal, again using a communication protocol (e.g., HTTP response).

[1488] Step 11:

[1489] The device displays the response received from the server to the user. The user interface is updated to display the response in a format that is easy for the user to understand. For example, it might say, "In the case of early termination of a rental contract, a penalty may be incurred if it is clearly stated in the contract. However, this only applies if the landlord's illegal activity is not involved. This may be worrying, but please take appropriate measures."

[1490] Example 2

[1491] 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."

[1492] In modern society, we often face legal problems, and it is difficult for ordinary citizens, especially those without specialized knowledge, to obtain legal information quickly and accurately. This requires time and money to consult with experts, and there is a need for a way to resolve these problems while also managing one's own emotions appropriately. However, existing systems lack the ability to provide appropriate advice that takes into account emotional states.

[1493] 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.

[1494] In this invention, the server includes means for using an emotion engine to analyze the emotional state of the user from input data, means for adjusting the tone of the response based on the emotional data provided by the emotion engine, and means for using natural language processing techniques to identify legal categories associated with key keywords, thereby enabling the user to quickly obtain accurate legal information that takes into account the user's emotional state.

[1495] A "user" is a person who utilizes the system to enter a legal question.

[1496] A "terminal" is a device that a user operates to input questions, and refers to electronic devices such as smartphones and personal computers.

[1497] A "server" is a computer system that analyzes the received data, generates a response based on legal information and past precedents, and sends it to the terminal.

[1498] "Natural language processing technology" is a technology that analyzes the content of questions entered by users to identify key keywords and related legal categories.

[1499] An "emotion engine" is software or a system for analyzing a user's emotional state from input data.

[1500] A "database" is a collection of data that stores legal information and past case law information and can be referenced as needed.

[1501] "Tone of response" refers to the emotional expression or tone of the generated response, which is adjusted according to the user's emotional state.

[1502] "Legal information" refers to all information related to the law, such as legal explanations, provisions, or past court decisions.

[1503] The present invention is a system that allows users to quickly and effectively solve common legal problems, and by combining an emotion engine, provides appropriate answers according to the user's emotional state. This system is composed of terminals, a server, a database, an emotion engine, and natural language processing technology.

[1504] First, the user enters a legal question through a device, such as a smartphone or PC. For example, a user might use a smartphone to enter "How do I start divorce proceedings?" into an application form.

[1505] Next, the terminal sends the user-entered question data to the server via the Internet using the HTTP POST request protocol, which sends the input data to the server and the system begins processing the question.

[1506] The server first stores the received question data in a database, which stores legal information and past legal precedents. A database system such as MongoDB is used. Next, the server analyzes the question using natural language processing technology (e.g., SpaCy, Gensim) to identify key keywords and related legal categories. This process allows the system to accurately understand the user's intent in the question.

[1507] Furthermore, the server analyzes the user's emotional state using an emotion engine, such as IBM Watson Tone Analyzer, which can analyze the user's emotional state, such as anxiety or anger, from the user's input data.

[1508] The server then queries its internal database to find relevant legal information and past cases based on the analyzed keywords and legal categories. The server generates a response based on the retrieved information, adjusting the tone of the response based on the emotional data provided by the emotion engine. For example, if the user is feeling anxious, the response will be written in a comforting tone. The response might be something like, "You need to go to city hall and submit the necessary documents. Specifically, you need a divorce notice and a copy of your family register. Please proceed with the process without worry."

[1509] The generated answers are sent from the server to the terminal and displayed on the terminal. The user interface is designed to provide answers in a format that is easy for the user to understand.

[1510] For example, consider the following prompt:

[1511] Are there any penalties if I cancel my lease early?

[1512] This system not only allows users to quickly obtain accurate legal information without relying on a specialist, but also provides answers that take into consideration their emotional state, enabling users to quickly respond to legal issues that arise in their daily lives.

[1513] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1514] Step 1:

[1515] The user enters a question

[1516] The user operates the terminal and inputs a question about a legal issue into the input form. The input question is prepared as text data. This text data is input in preparation for processing in the next step.

[1517] Input: User question (e.g., "How do I start divorce proceedings?")

[1518] Output: Text data entered in the input form

[1519] Step 2:

[1520] The device sends a question to the server

[1521] The terminal sends the text data entered by the user to the server using an HTTP POST request, and the sent data reaches the server via the Internet.

[1522] Input: Text data in the input form

[1523] Output: HTTP POST request sent to the server

[1524] Step 3:

[1525] The server receives and analyzes the query.

[1526] The server first stores the received text data in a database, then uses natural language processing (NLP) techniques to analyze the text data and identify key keywords (e.g., "divorce" and "procedure") and related legal categories.

[1527] Input: Text data of HTTP POST request

[1528] Output: Identified keywords and legal categories

[1529] Step 4:

[1530] Emotion engine analyzes the user's emotional state

[1531] The server passes the received text data to the emotion engine, which analyzes the user's emotional state. The emotion engine infers emotions from the tone of the text and specific keywords.

[1532] Input: Text data

[1533] Output: Emotional state data (e.g., anxiety, anger)

[1534] Step 5:

[1535] The server references legal information and past cases

[1536] The server uses the identified keywords and legal categories to access an internal database and search for relevant legal information and past cases.

[1537] Input: Identified keywords and legal categories

[1538] Output: Retrieved relevant legal information and past cases

[1539] Step 6:

[1540] The server generates the answer

[1541] The server generates an answer to the user's question based on the acquired legal information and emotional data, and the tone of the answer is adjusted based on the emotional data.

[1542] Input: Obtained legal information, past cases, and emotional state data

[1543] Output: Answer text with adjusted emotional tone

[1544] Step 7:

[1545] The server sends the answer to the device

[1546] The server sends the generated answer text to the terminal as an HTTP response.

[1547] Input: Answer text

[1548] Output: The answer text sent in the HTTP response

[1549] Step 8:

[1550] The device displays the answer

[1551] The terminal displays the answer text received as an HTTP response on the user interface, adjusted to a format that is easy for the user to view.

[1552] Input: HTTP response answer text

[1553] Output: Answer text displayed on the screen

[1554] Through these processing steps, users can obtain relevant and emotionally sensitive answers to their legal questions.

[1555] (Application example 2)

[1556] 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."

[1557] The problem to be solved by the present invention is to provide not only legal answers but also answers in an appropriate tone that takes into consideration the emotional state of the user when solving legal questions quickly and effectively. In particular, the present invention aims to provide a system that can respond to customers in a way that does not cause anxiety or stress in customer support situations where the tone of the answer is important.

[1558] The identification process by the identification 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 the emotional state of a user using an emotion analysis engine, means for referencing a database storing legal information and past precedents and acquiring specific legal information, and means for generating an answer to a user's question based on the acquired legal information and the emotion analysis results. This makes it possible, when a user asks a question, to quickly provide an answer in an appropriate tone that takes into account the user's emotional state.

[1559] Definition of Terms

[1560] A "user" is someone who utilizes the system to input a legal question.

[1561] A "question" is a request for legal information or a matter for consultation entered by a user.

[1562] A "terminal" is a device through which a user inputs legal questions and communicates with the server, and includes smartphones and personal computers.

[1563] A "server" is a device that receives legal questions sent by users, analyzes them, and generates answers.

[1564] An "emotion analysis engine" is software or hardware for analyzing a user's emotional state from input data.

[1565] "Natural language processing technology" is a technology that analyzes questions entered by users and identifies key keywords and related legal categories.

[1566] A "database" is a collection of information that stores legal information and past precedents and can be referenced by a server.

[1567] "Answers" are legal information and advice generated by the server based on the user's question.

[1568] "Means for analyzing the question" refers to the process by which the server uses natural language processing technology to analyze the content of the question entered by the user and extract key keywords and related legal categories.

[1569] The "means for generating an answer" is the process by which the server creates an answer to the user's question based on the legal information and sentiment analysis results it has obtained.

[1570] The "means for displaying the answer" is a function that visually presents the answer that the terminal receives from the server to the user.

[1571] MODE FOR CARRYING OUT THE INVENTION

[1572] This invention relates to a legal consultation system that incorporates an emotion engine, and is particularly applicable to customer support on online shopping sites. This system allows users to input legal questions and send the information to a server, which provides quick and emotionally sensitive answers.

[1573] Hardware and software used

[1574] To implement the system, the following hardware and software are used.

[1575] Hardware

[1576] Device: A smartphone used by a user, allowing the user to enter legal questions and receive answers.

[1577] Server: A powerful computing device that processes data sent by users and generates answers.

[1578] software

[1579] Natural Language Processing Technology (NLPProcessor): Technology that analyzes user questions and identifies key keywords and relevant legal categories.

[1580] Emotion Analysis Engine (EmotionEngine): A technology that analyzes the emotional state of a user from input data and determines their emotions based on the tone of the questions and keywords they enter.

[1581] Database: A collection of information for storing legal information and past precedents. The server references this database to obtain the necessary information.

[1582] Requests library: A library for HTTP communication. Used to send data between the terminal and the server.

[1583] Specific operation of the system

[1584] 1. Enter your question

[1585] Users use a smartphone application to input legal questions, such as, "I'm having trouble with the complicated return process. How should I proceed?"

[1586] 2. Submit your question

[1587] The smartphone application sends the entered question data to the server using an HTTP POST request, using the "requests" library.

[1588] 3. Question and Sentiment Analysis

[1589] The server analyzes the received inquiry data. First, it uses natural language processing technology (NLPProcessor) to analyze the content of the inquiry and identify key keywords and related legal categories.

[1590] Next, the "Emotion Engine" is used to analyze the user's emotional state and determine emotions such as anxiety or stress.

[1591] 4. Obtaining relevant information

[1592] The server accesses a "database" to search for legal information and past cases, and retrieves the required information based on the identified keywords and categories.

[1593] 5. Answer Generation

[1594] The server generates a response in an appropriate tone based on the acquired information and the results of sentiment analysis. For example, a user who is feeling anxious might receive a response such as, "Don't worry. Please follow the steps below to process your return."

[1595] 6. Submitting and Viewing Your Answers

[1596] The server generates an answer and sends it to the device as an HTTP response. The smartphone application receives the answer and presents it visually to the user.

[1597] Examples of specific examples and prompts

[1598] Specific examples

[1599] The user enters a question through a smartphone application, such as "The return procedure is complicated and I'm having trouble. How should I proceed?" The server analyzes the question and detects that the user is feeling anxious. The server retrieves information about the return procedure from the database, generates a response such as "Don't worry. Please follow the steps below to return the product," and provides it to the user.

[1600] Prompt Sentence Examples

[1601] "Use sentiment engines and natural language processing to answer customer questions about returns, like: 'I'm having trouble with the complicated returns process. How do I proceed?'"

[1602] The above is an embodiment of the present invention.

[1603] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1604] Program processing steps

[1605] Step 1:

[1606] Users input legal questions through a smartphone application. Data is generated by entering specific questions into this input form (e.g., "I'm having trouble with the complicated return procedure. How should I proceed?"). The input data includes the text information of the question.

[1607] Step 2:

[1608] The device (smartphone) sends the entered question data to the server using an HTTP POST request. At this time, the input data is sent as part of the HTTP request. The input data is sent to the server and received by the server.

[1609] Step 3:

[1610] The server analyzes the received question data. First, it uses natural language processing technology (NLPProcessor) to analyze the text data of the question and extract key keywords and related legal categories. The input data is analyzed, and the extracted keywords and categories are output (e.g., "return," "procedure," "complex," etc.).

[1611] Step 4:

[1612] The server uses an emotion analysis engine (EmotionEngine) to analyze the user's emotional state from the input data. Based on the linguistic features of the input data (e.g., tone and keywords), it determines the emotion the user is feeling (e.g., anxiety, confusion). The results of the emotion analysis are output and used in the next step.

[1613] Step 5:

[1614] The server references a database containing legal information and past precedents and retrieves relevant information based on the extracted keywords and categories. The input data is used as a database query, and the required legal information and past precedent data is output.

[1615] Step 6:

[1616] The server generates an answer to the user's question based on the legal information acquired and the results of sentiment analysis. Specifically, the answer is created based on the legal information and in a tone that takes into account the sentiment data. For example, the generated answer might be something like, "Don't worry. Please follow the steps below to process your return."

[1617] Step 7:

[1618] The server generates an answer and sends it to the terminal as an HTTP response. The generated answer is output in document format and sent as part of the HTTP response. The terminal receives this answer.

[1619] Step 8:

[1620] The device displays the answer received from the server to the user. The received data is visualized by the smartphone application, and the appropriate answer is displayed on the screen for the user.

[1621] The above is the specific processing flow of the program.

[1622] 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.

[1623] 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.

[1624] 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.

[1625] 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.

[1626] 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.

[1627] 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.

[1628] 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).

[1629] 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.

[1630] 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."

[1631] 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.

[1632] 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).

[1633] 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.

[1634] 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.

[1635] 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.

[1636] 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.

[1637] 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.

[1638] 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.

[1639] 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.

[1640] 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.

[1641] 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.

[1642] 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.

[1643] The following is further disclosed regarding the above embodiment.

[1644] (Claim 1)

[1645] a means for a user to input a legal question;

[1646] A means for the terminal to transmit user input data to the server;

[1647] means for parsing the received query by the server to identify key keywords and associated legal categories;

[1648] A means for the server to refer to a database storing legal information and past precedents and acquire specific legal information;

[1649] means for generating answers to user questions based on the legal information obtained by the server;

[1650] means for transmitting the server-generated response to the terminal;

[1651] means for the terminal to display a response from the server to the user;

[1652] A system including:

[1653] (Claim 2)

[1654] 10. The system of claim 1, wherein natural language processing techniques are used to identify legal categories associated with key keywords in a user's query.

[1655] (Claim 3)

[1656] 2. The system according to claim 1, wherein the server refers to a database storing past case law information to obtain information related to the user's question.

[1657] "Example 1"

[1658] (Claim 1)

[1659] a means for a user to input a legal question;

[1660] A means for the terminal to transmit user input data to the server;

[1661] means for parsing the received query by the server to identify key keywords and associated legal categories;

[1662] A means for the server to refer to a database storing legal information and past precedents and acquire specific legal information;

[1663] means for generating answers to user questions based on the legal information obtained by the server;

[1664] means for transmitting the server-generated response to the terminal;

[1665] means for the terminal to display a response from the server to the user;

[1666] a means for storing the received question data in a database by the server;

[1667] A means of analyzing the question and extracting key keywords using a natural language processing engine;

[1668] A means for the server to generate an answer using the generative AI model;

[1669] means for converting the answer data received by the terminal into a format suitable for a user interface and displaying the converted answer data;

[1670] A system including:

[1671] (Claim 2)

[1672] 10. The system of claim 1, wherein natural language processing techniques are used to identify legal categories associated with key keywords in a user's query.

[1673] (Claim 3)

[1674] 2. The system according to claim 1, wherein the server refers to a database storing past case law information to obtain information related to the user's question.

[1675] "Application Example 1"

[1676] (Claim 1)

[1677] a means for a user to input a legal question;

[1678] A means for the terminal to transmit user input data to the server;

[1679] means for parsing the received query by the server to identify key keywords and associated legal categories;

[1680] A means for the server to refer to a database storing legal information and past precedents and acquire specific legal information;

[1681] means for generating answers to user questions based on the legal information obtained by the server;

[1682] means for transmitting the server-generated response to the terminal;

[1683] a means for the terminal to display or output a voice message to the user the answer from the server;

[1684] A means of voice or text input of legal questions into a tablet, smartphone, or robot;

[1685] A means for a tablet terminal, a smartphone, or a robot to transmit question data to a server;

[1686] A system including:

[1687] (Claim 2)

[1688] 10. The system of claim 1, wherein natural language processing techniques are used to identify legal categories associated with key keywords in a user's query.

[1689] (Claim 3)

[1690] 2. The system according to claim 1, wherein the server refers to a database storing past case law information and provides audio guidance on information related to the user's question.

[1691] "Example 2: Combining Emotion Engines"

[1692] (Claim 1)

[1693] a means for a user to input a legal question;

[1694] A means for the terminal to transmit user input data to the server;

[1695] means for parsing the received query by the server to identify key keywords and associated legal categories;

[1696] A means for the server to refer to a database storing legal information and past precedents and acquire specific legal information;

[1697] means for generating answers to user questions based on the legal information obtained by the server;

[1698] means for transmitting the server-generated response to the terminal;

[1699] means for the terminal to display a response from the server to the user;

[1700] a means for the server to use an emotion engine to analyze the user's emotional state from the input data;

[1701] means for the server to adjust the tone of the response based on the emotion data provided by the emotion engine;

[1702] A system including:

[1703] (Claim 2)

[1704] 10. The system of claim 1, wherein natural language processing techniques are used to identify legal categories associated with key keywords in a user's query.

[1705] (Claim 3)

[1706] 2. The system according to claim 1, wherein the server refers to a database storing past case law information to obtain information related to the user's question.

[1707] "Application example 2 when combining emotion engines"

[1708] New Claims

[1709] (Claim 1)

[1710] a means for a user to input a legal question;

[1711] A means for the terminal to transmit user input data to the server;

[1712] means for parsing the received query by the server to identify key keywords and associated legal categories;

[1713] A means for the server to analyze the emotional state of the user using an emotion analysis engine;

[1714] A means for the server to refer to a database storing legal information and past precedents and acquire specific legal information;

[1715] A means for generating answers to user questions based on the legal information and sentiment analysis results acquired by the server;

[1716] means for transmitting the server-generated response to the terminal;

[1717] means for the terminal to display a response from the server to the user;

[1718] A system including:

[1719] (Claim 2)

[1720] 10. The system of claim 1, wherein natural language processing techniques are used to identify legal categories associated with key keywords in a user's query.

[1721] (Claim 3)

[1722] 2. The system according to claim 1, wherein the server refers to a database storing past case law information to obtain information related to the user's question. [Explanation of symbols]

[1723] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for a user to input a legal question; A means for the terminal to transmit user input data to the server; means for parsing the received query by the server to identify key keywords and associated legal categories; A means for the server to refer to a database storing legal information and past precedents and acquire specific legal information; means for generating answers to user questions based on the legal information obtained by the server; means for transmitting the server-generated response to the terminal; means for the terminal to display a response from the server to the user; A system including:

2. The system of claim 1 , wherein natural language processing techniques are used to identify legal categories associated with key keywords in a user's query.

3. 2. The system according to claim 1, wherein the server refers to a database storing past case law information to obtain information related to the user's question.

Images