System

Abstract

A system is provided.SOLUTION: A system comprising: means for a user to input a legal question using a device; means for the device to send the user's question to a server; means for the server to parse the question and extract key keywords; means for the server to generate relevant legal information based on the extracted keywords using a generative AI; means for the server to format the generated legal information for the user; and means for the device to display the formatted answer to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Japanese law is extremely difficult for the average person to understand, making it difficult to obtain accurate legal advice on everyday issues. For this reason, people usually need to consult a lawyer, but consultations are costly and many people don't know how to get help. Furthermore, legal information available on the Internet can sometimes be unreliable, making it difficult for users to make appropriate decisions. To solve these issues, there is a need for an efficient and economical way to provide legal advice. [Means for solving the problem]

[0005] In order to solve the above-mentioned problems, the system of the present invention includes the following means: a means for a user to input a legal question using a terminal, a means for the terminal to transmit the user's question to a server, a means for the server to analyze the content of the question and extract important keywords, a means for the server to generate relevant legal information using a generation AI based on the extracted keywords, a means for the server to format the generated legal information for the user, and a means for the terminal to display the formatted answer to the user. Furthermore, the system also includes a means for the server to add related links and reference materials to the generated legal information, and a means for transmitting the content of the question transmitted by the terminal to the server using a secure communication protocol, thereby providing a system that allows users to easily and quickly obtain reliable legal information.

[0006] "User" refers to an individual or legal entity that enters legal questions through a terminal and receives answers.

[0007] A "terminal" is a device used by a user to input legal questions and communicate with the server, and includes smartphones, personal computers, etc.

[0008] A "question" refers to a sentence or phrase entered by a user regarding a legal question or problem.

[0009] "Send" refers to the act of sending data from the user's terminal to the server.

[0010] "Server" refers to the central system that receives and analyzes the user's query and generates the appropriate legal information.

[0011] "Analysis" refers to the process of extracting and understanding important keywords from the question entered by the user.

[0012] "Keywords" refer to important words and phrases that are extracted when analyzing the content of a question and are used to generate legal information.

[0013] "Generative AI" refers to algorithms or programs that use artificial intelligence technology to generate legal information and answers to user questions.

[0014] "Legal information" refers to information such as relevant laws, precedents, and advice provided in response to a user's question.

[0015] "Formatting" refers to arranging the generated legal information into a form that is easy for the user to understand.

[0016] "Link" refers to a URL that provides reference information to related laws, regulations, precedents, etc.

[0017] "References" refers to additional documents or resources where the user can find more information.

[0018] A "secure communication protocol" is a communication protocol for safely sending and receiving data, and generally includes HTTPS. [Brief explanation of the drawings]

[0019] [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

[0020] 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.

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

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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."

[0027] [First embodiment]

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

[0029] 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.

[0030] 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).

[0031] 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.

[0032] 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.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0034] 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.

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

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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."

[0040] The present invention relates to a system in which a user inputs legal questions via a terminal, and a server provides appropriate legal information using a generation AI. A specific example of the system is described below.

[0041] System Overview

[0042] The overall system consists of a user's device, a server, and a generation AI. The user inputs a legal question using the device, which is then sent to the server. The server analyzes the question and generates appropriate legal information using the generation AI. The generated information is then formatted in an easy-to-understand format and provided to the user via the device.

[0043] Program processing overview

[0044] User Input

[0045] Users access the interface on their device (e.g., a smartphone or PC) and enter a legal question into a text box, such as "What should I do if my neighbors are making noise late at night?"

[0046] Submit a Question

[0047] When the user clicks the "Submit" button, the device sends the entered question to the server as an HTTP request. The communication is carried out using a secure protocol (e.g., HTTPS).

[0048] Question Analysis

[0049] The server analyzes the received question and extracts important keywords, such as "neighbor," "late night," "noise," and "how to respond," which are used for subsequent processing.

[0050] Legal information generation

[0051] The server passes the extracted keywords to the generation AI, which uses its internal legal dataset to search for and generate appropriate legal information and past precedents for the user's question. For example, it generates information such as "Under Article 709 of the Civil Code, it is possible to claim compensation for noise disturbances."

[0052] Information Format

[0053] The generated legal information is then formatted for the user by the server, which formats the information in an easy-to-understand format and adds relevant links and references as needed.

[0054] Show Answers

[0055] Finally, a formatted response is sent to the device and displayed to the user, such as "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. Please see the link below for more information."

[0056] Specific examples

[0057] As a specific example, let's consider the case where a user inputs the question, "What should I do if my company doesn't pay me my overtime wages?" In this case, the device sends the question to the server, which extracts keywords such as "overtime wages" and "not paid." The generation AI generates information related to the Labor Standards Act, which the server then formats appropriately and provides to the user. Finally, the user's device displays the following message: "According to Article 37 of the Labor Standards Act, overtime wages should be paid. We recommend that you consult with the Labor Standards Inspection Office as a specific procedure."

[0058] As described above, the system of the present invention provides an efficient method for users to easily and quickly obtain legal advice and appropriate legal information.

[0059] The processing flow will be explained below.

[0060] Step 1:

[0061] A user accesses the interface on their device and types a legal question into a text box, such as "What should I do if my neighbors are making noise late at night?"

[0062] Step 2:

[0063] When the user clicks the "Submit" button, the device sends the entered question to the server as an HTTP request. The communication is carried out using a secure protocol (e.g., HTTPS).

[0064] Step 3:

[0065] The server receives the question in JSON format and starts a text analysis engine to analyze the received data.

[0066] Step 4:

[0067] The server's text analysis engine analyzes the question and extracts important keywords, such as "neighbors," "late night," "noise," and "how to deal with it."

[0068] Step 5:

[0069] The server passes the extracted keywords to the generation AI, which uses its internal legal dataset to search for the most relevant legal information and past precedents and generate appropriate legal information. For example, it generates information such as, "Under Article 709 of the Civil Code, it is possible to claim compensation for noise disturbances."

[0070] Step 6:

[0071] The server receives the legal information returned by the generation AI and formats it for the user. The server formats the generated information in an easy-to-understand format, adding relevant links and references as needed.

[0072] Step 7:

[0073] The server sends the formatted answer to the device as an HTTP response in JSON format, and the user's device receives the response.

[0074] Step 8:

[0075] The device displays the answer to the user. For example, information is displayed on the device screen in the form of "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. Please refer to the link below for more information."

[0076] The above is a series of steps for processing legal questions from users. This flow is important for the system as a whole to respond quickly and accurately to user questions.

[0077] Example 1

[0078] 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."

[0079] In modern society, many people have legal problems and questions, but accessing legal experts is time-consuming. Furthermore, information on the Internet is often unreliable, making it difficult to quickly obtain accurate legal information. To address these issues, a system is needed that allows users to easily obtain reliable legal information.

[0080] 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.

[0081] In this invention, the server includes: a means for a user to input a legal question; a means for a terminal to transmit the user's question to the server using a secure communication protocol; a means for the server to analyze the received question using a natural language processing algorithm and extract important keywords; a means for the server to pass a prompt sentence for generating related legal information using a generation AI based on the extracted keywords; a means for the server to format the generated legal information for the user; a means for the server to add related links and reference materials to the generated legal information; and a means for the terminal to display the formatted answer to the user. This allows the user to easily and quickly obtain reliable legal information.

[0082] "User" means any person or entity that uses the System to enter legal questions and receive answers.

[0083] "Terminal" refers to an electronic device used by a user for input and display. Specifically, it includes smartphones, personal computers, tablets, etc.

[0084] "Server" refers to the central computer that receives, analyzes, processes, and generates answers to user questions.

[0085] "Question content" refers to text data of legal questions or inquiries entered by the user using the terminal.

[0086] A "secure communication protocol" refers to a communication method that prevents unauthorized access by third parties when sending and receiving data. Specifically, HTTPS is one example.

[0087] "Natural language processing algorithm" refers to a technical means for analyzing human language and extracting information.

[0088] "Keywords" refer to words and phrases extracted from the query that are important for generating legal information.

[0089] "Generative AI" refers to a model that uses artificial intelligence technology to generate relevant legal information based on a given prompt.

[0090] "Prompt sentence" refers to the input sentence that the generative AI uses to generate an appropriate response.

[0091] "Format" refers to the means by which the generated legal information is arranged in a form that is easy for users to understand.

[0092] "Reference links and additional resources" refers to supplementary information provided to help users understand more.

[0093] "Answer" refers to the legal information generated by the AI ​​in response to a user's question and formatted and provided by the server.

[0094] The present invention is a system in which a user inputs a legal question through a terminal, and a server provides appropriate legal information using a generation AI. This system is composed of a user's terminal, a server, and a generation AI. Specific embodiments of the system are described in detail below.

[0095] System Overview

[0096] A user accesses the interface on their device (e.g., a smartphone or PC) and enters a legal question into a text box. For example, they can enter a question such as, "What should I do if my neighbors are making noise late at night?" After entering the question, the user clicks the "Submit" button, and the device sends the entered question to the server using the HTTPS protocol. This communication uses a secure protocol, so the data is encrypted before being sent.

[0097] The server uses a natural language processing (NLP) algorithm to analyze the received question. This algorithm extracts important keywords from the question, such as "neighbors," "late night," "noise," and "how to respond." The server then passes the extracted keywords to the generation AI. The generation AI model generates appropriate legal information for the user's question based on its internal legal dataset and past case law. The following prompt is used for the generation AI:

[0098] Please provide relevant legal information in response to the question, "What should I do if my neighbor is making noise late at night?"

[0099] The generated legal information might include, for example, "Under Article 709 of the Civil Code, it is possible to claim compensation for noise."

[0100] The server formats the generated legal information in a way that is easy for the user to understand. The server formats the information and inserts relevant links and additional references as needed. Finally, the formatted answer is sent to the device and displayed in the user's browser. For example, it might look something like this:

[0101] According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. Please refer to the link below for more information.

[0102] This system allows users to quickly obtain reliable legal information. Specifically, let's consider the case where a user inputs a question such as, "What should I do if my company doesn't pay me my overtime wages?" In this case, the device sends the question to the server, which extracts keywords such as "overtime wages" and "not paid." The generation AI generates information related to the Labor Standards Act, which the server then formats appropriately and provides to the user. Finally, the user's device displays the following message: "According to Article 37 of the Labor Standards Act, overtime wages should be paid. We recommend that you consult with the Labor Standards Inspection Office for specific procedures."

[0103] Thus, the system of the present invention provides an efficient method for users to easily and quickly obtain legal advice and appropriate legal information.

[0104] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0105] Step 1:

[0106] The user uses a terminal to enter a legal question. For example, the user types "What should I do if my neighbors are making noise late at night?" into a text box. This is done using the system's web interface.

[0107] Input: The question text entered by the user

[0108] Output: None (user input is temporarily stored in a database or memory)

[0109] Step 2:

[0110] When the user clicks the "Submit" button, the device sends the question to the server using the HTTPS protocol, where the device validates the input and ensures that the question is in the correct format.

[0111] Input: The question text entered by the user and validated

[0112] Output: Question as HTTPS request

[0113] Step 3:

[0114] The server uses a natural language processing (NLP) algorithm to analyze the received question. The server extracts important keywords from the question. In this step, keywords such as "neighbors," "late night," "noise," and "how to deal with it" are extracted.

[0115] Input: Question text sent to the server

[0116] Output: List of extracted keywords (e.g., "neighbor," "late night," "noise," "how to respond")

[0117] Step 4:

[0118] The server passes the extracted keywords to the generation AI model. The server then creates a prompt for the generation AI, and generates legal information based on this prompt. For example, the prompt passed to the generation AI is as follows:

[0119] Please provide relevant legal information in response to the question, "What should I do if my neighbor is making noise late at night?"

[0120] Input: Extracted keyword list, generated prompt sentence

[0121] Output: Legal information generated by the AI ​​(e.g., "Article 709 of the Civil Code allows for the claim of compensation for noise pollution.")

[0122] Step 5:

[0123] The server formats the generated legal information in a user-friendly format. The server formats the information and inserts relevant links and additional references as needed.

[0124] Input: Legal information generated by the generative AI

[0125] Output: Formatted legal information (e.g., "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. Please see the link below for more information.")

[0126] Step 6:

[0127] Finally, the server sends the formatted response to the device, which displays the received information in the user's web browser.

[0128] Input: Formatted legal information

[0129] Output: The final answer that is displayed in the user's browser

[0130] Through the above specific processing steps, users can efficiently obtain reliable legal information.

[0131] (Application example 1)

[0132] 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."

[0133] In conventional legal consultation systems, it has been difficult for users to receive prompt and accurate legal information in real time when asking legal questions. Furthermore, users have been unable to immediately consult about security-related legal issues and obtain appropriate solutions, significantly impairing user convenience. The present invention aims to solve these problems by providing a system that allows users to consult about security-related legal issues in real time and quickly provides accurate legal information.

[0134] 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.

[0135] In this invention, the server includes means for a user to input a legal question using an electronic device, means for the electronic device to transmit the user's question to a data processing device, means for the data processing device to analyze the content of the question and extract important information, means for the data processing device to generate relevant legal information using a generation AI based on the extracted information, means for the data processing device to format the generated legal information for the user, means for the electronic device to display the formatted answer to the user, and means for the electronic device to display the legal information in real time. This allows users to quickly and accurately consult on legal issues related to security on the spot and learn appropriate responses in real time.

[0136] "User" means a person who uses the system to enter legal questions and obtain answers.

[0137] "Electronics" refers to the terminal where the user inputs, sends questions, and displays answers.

[0138] A "legal question" is a question posed to the system by a user regarding laws, regulations, or legal issues.

[0139] A "data processing device" is a computer system that analyzes a user's question, generates legal information using generative AI, and provides a formatted answer.

[0140] "Question content" refers to the text of a legal inquiry entered by a user through an electronic device.

[0141] "Important information" refers to keywords and themes extracted from the user's question for generating legal information.

[0142] "Generative AI" refers to an artificial intelligence model that generates relevant information based on input data.

[0143] "Legal information" refers to laws, precedents, and advice provided in response to users' questions.

[0144] "Formatting" refers to arranging the generated legal information in a form that is easy for the user to view and understand.

[0145] An "answer" is legal information that the system generates in response to a question and provides to the user.

[0146] "Real time" refers to near-instant processing and response.

[0147] This invention is a system that allows users to receive real-time consultations on legal issues related to security. Specifically, users input questions using electronic devices, and a data processing device analyzes and answers the questions.

[0148] System Configuration

[0149] The system consists of the following main components:

[0150] User terminals (electronic devices)

[0151] Data processing device (server)

[0152] Generative AI Models

[0153] Hardware and Software

[0154] The hardware and software used are as follows:

[0155] Electronics: Smart glasses (e.g. Google Glass, Vuzix Blade)

[0156] Data processing equipment: Cloud server (e.g. AWS, Azure)

[0157] Generative AI model: GPT-3

[0158] Program processing flow

[0159] The system proceeds as follows:

[0160] 1. User Input

[0161] Users use the smart glasses to input legal questions, such as "What should I do if I have a suspicious person in my neighborhood?"

[0162] 2. Submit a question

[0163] Once the user enters a question, the smart glasses send it to the server using the secure HTTPS protocol.

[0164] 3. Question analysis

[0165] The server analyzes the received question and extracts important information (keywords), such as "suspicious person" and "how to deal with it."

[0166] 4. Legal information generation

[0167] The server queries a generative AI model (GPT-3) based on the extracted information to generate relevant legal information. The generative AI model then references an internal dataset to generate appropriate legal information for the user's question.

[0168] 5. Information Format

[0169] The server formats the generated legal information for the user, making it easier to read and adding relevant links and references where necessary.

[0170] 6. Answer display

[0171] The final formatted answer is sent to the user terminal and displayed to the user in real time through the smart glasses.

[0172] Specific examples

[0173] The user explains the question in a flow: "What should I do if my company doesn't pay me my overtime wages?" In this case, the smart glasses send the question to the server, which extracts keywords such as "overtime wages" and "not paid." The generative AI model generates information related to Article 37 of the Labor Standards Act, which the server formats and provides to the user. Finally, the smart glasses display the message: "According to Article 37 of the Labor Standards Act, overtime wages should be paid. We recommend that you consult with the Labor Standards Inspection Office for specific procedures."

[0174] Prompt Sentence Examples

[0175] Examples of prompts are:

[0176] text

[0177] What should I do if there are suspicious people in my neighborhood?

[0178] This allows users to consult on security-related legal issues in real time on the spot and quickly obtain appropriate countermeasures.

[0179] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0180] Step 1:

[0181] The user uses the smart glasses to input a legal question, which is stored in the smart glasses as text data. The input of this step is the text data entered by the user, and the output is the text data stored in the smart glasses.

[0182] Step 2:

[0183] The device (smart glasses) sends the entered question to the server using the secure HTTPS protocol. The input for this step is the question data in text format, and the output is the question data sent to the server as an HTTPS request.

[0184] Step 3:

[0185] The server analyzes the received question and extracts important information (keywords). For example, words such as "suspicious person" and "how to deal with it" are extracted. The input for this step is the text data sent in the HTTPS request, and the output is a list of extracted keywords.

[0186] Step 4:

[0187] The server uses a generative AI model (GPT-3) to generate relevant legal information based on the extracted keywords. The generative AI model references an internal dataset to provide appropriate legal information for a specific question. The input for this step is a list of keywords, and the output is the generated legal information text.

[0188] Step 5:

[0189] The server formats the generated legal information for the user, making it easier to read and adding relevant links and references as needed. The input to this step is the generated legal text and the output is the formatted answer text.

[0190] Step 6:

[0191] The server then sends the formatted response to the terminal, again using a secure communication protocol. The input to this step is the formatted response data, and the output is the response data sent to the terminal as an HTTPS response.

[0192] Step 7:

[0193] The terminal (smart glasses) displays the formatted answer received from the server to the user in real time. The user checks the answer through the smart glasses display and decides the next action. The input of this step is the formatted answer data received in the HTTPS response, and the output is the user's visual confirmation.

[0194] 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.

[0195] The present invention relates to a system in which a user inputs a legal question through a terminal, and a server provides appropriate legal information using a generative AI and an emotion engine. A specific example of the system is described below.

[0196] System Overview

[0197] The overall system consists of a user's device, a server, a generation AI, and an emotion engine. The user inputs a legal question using the device, which is then sent to the server. The server analyzes the question and generates appropriate legal information using the generation AI and emotion engine. The generated information is then formatted in an easy-to-understand format and provided to the user via the device.

[0198] Program processing overview

[0199] User Input

[0200] Users access the interface on their device (e.g., a smartphone or computer) and enter a legal question into a text box, such as "What should I do if my neighbors are making noise late at night?"

[0201] Submit a Question

[0202] When the user clicks the "Submit" button, the device sends the entered question to the server as an HTTP request. The communication is carried out using a secure protocol (e.g., HTTPS).

[0203] Question Analysis

[0204] The server receives the question in JSON format and starts a text analysis engine to analyze the received data.

[0205] Keyword extraction

[0206] The server's text analysis engine analyzes the question and extracts important keywords, such as "neighbors," "late night," "noise," and "how to deal with it."

[0207] Emotion Analysis

[0208] The server uses an emotion engine to analyze the user's emotional state from the input question. For example, emotions such as "confusion" or "anger" can be detected from the context of the question.

[0209] Legal information generation

[0210] The server passes the extracted keywords and the results of the sentiment analysis to the generation AI. The generation AI then uses its internal legal dataset to search for and generate appropriate legal information and past precedents for the user's question. For example, it may generate information such as, "Under Article 709 of the Civil Code, it is possible to claim compensation for noise pollution." Based on the results of the sentiment analysis, the information is generated in an appropriate tone.

[0211] Information Format

[0212] The generated legal information is then formatted for the user by the server, which formats the generated information in an easy-to-understand format and adds relevant links and references as needed, thereby providing information that takes into account the user's emotional state.

[0213] Show Answers

[0214] Finally, a formatted response is sent to the device and displayed to the user. For example, it may say, "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. Please see the link below for more information." The tone of the response is adjusted based on the results of sentiment analysis.

[0215] Specific examples

[0216] As a specific example, let's consider a case where a user inputs a question such as, "What should I do if my company doesn't pay my overtime wages?" and an emotion of anxiety is detected from the question. In this case, the device sends the question to the server, which extracts keywords such as "overtime wages" and "not paid." The emotion engine detects the user's emotion of anxiety and feeds the results back to the generation AI. The generation AI generates information related to the Labor Standards Act in a tone that alleviates anxiety. For example, it provides information such as, "According to Article 37 of the Labor Standards Act, overtime wages should be paid without fail. If you are worried, we recommend that you consult the Labor Standards Inspection Office."

[0217] As described above, the system of the present invention allows users to easily and quickly seek legal advice and obtain appropriate legal information, and furthermore, is capable of providing information that takes into consideration the user's feelings.

[0218] The processing flow will be explained below.

[0219] Step 1:

[0220] A user accesses the interface on their device and types a legal question into a text box, such as "What should I do if my neighbors are making noise late at night?"

[0221] Step 2:

[0222] When the user clicks the "Submit" button, the device sends the entered question to the server as an HTTP request. The communication is carried out using a secure protocol (e.g., HTTPS).

[0223] Step 3:

[0224] The server receives the question in JSON format and starts a text analysis engine to analyze the received data.

[0225] Step 4:

[0226] The server's text analysis engine analyzes the question and extracts important keywords, such as "neighbors," "late night," "noise," and "how to deal with it."

[0227] Step 5:

[0228] The server uses an emotion engine to analyze the user's emotional state from the input question. For example, emotions such as "confusion" or "anger" can be detected from the context of the question.

[0229] Step 6:

[0230] The server passes the extracted keywords and sentiment analysis results to the generation AI. The generation AI then uses its internal legal dataset to search for and generate appropriate legal information and past precedents for the user's question. For example, it generates information such as, "Under Article 709 of the Civil Code, it is possible to claim compensation for noise disturbances."

[0231] Step 7:

[0232] The emotion engine analyzes the user's emotional state and adjusts the tone of the generated legal information based on that state. For example, if the user is "confused," the information is presented in a more reassuring tone.

[0233] Step 8:

[0234] The server receives the legal information returned by the generation AI and formats it for the user. The server formats the generated information in an easy-to-understand format, adding relevant links and references as needed. The tone of the information is adjusted based on feedback from the emotion engine.

[0235] Step 9:

[0236] The server sends the formatted answer to the device as an HTTP response in JSON format, and the user's device receives the response.

[0237] Step 10:

[0238] The device displays the answer to the user. For example, the device displays information in a reassuring tone on the screen, such as, "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. If you have any questions, please refer to the link below."

[0239] As a specific example, let's consider a case where a user inputs a question such as "What should I do if my company doesn't pay my overtime wages?" and an emotion of anxiety is detected from the question. In this case, the device sends the question to the server. The server extracts keywords such as "overtime wages" and "not paid," and the emotion engine detects the user's emotion of anxiety. The results are fed back to the generation AI, which then generates information related to the Labor Standards Act in a tone that alleviates the anxiety. For example, the information provided may be something like, "According to Article 37 of the Labor Standards Act, overtime wages should be paid without fail. If you are worried, we recommend that you consult the Labor Standards Inspection Office."

[0240] The above are the specific processing steps of the system of the present invention that combines an emotion engine. This system allows users to easily receive legal advice that takes emotional considerations into account, and enables them to quickly obtain accurate and reliable legal information.

[0241] Example 2

[0242] 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."

[0243] Conventional legal consultation systems have difficulty providing appropriate legal information in response to user-entered questions, and are particularly unable to generate answers that take into account the user's emotional state. Furthermore, generating appropriate legal information requires manual search and legal knowledge, making it extremely difficult for non-experts. To solve this problem, a system was needed that could analyze the content of a user's question, extract important keywords, and automatically provide appropriate legal information.

[0244] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for analyzing the content of the question and extracting important keywords, a sentiment analysis means, and a means for generating relevant legal information using a generation AI. This makes it possible to provide prompt and appropriate legal information that takes into consideration the user's sentiments.

[0245] A "computing device" is an electronic device, such as a personal computer, smartphone, or tablet, that allows a user to connect to the Internet and input or receive data.

[0246] A "network" is a communications infrastructure for data communication, such as the Internet or an intranet.

[0247] A "server" is a computer system that can process data in response to a user's request via a network and return the results.

[0248] "Means for analyzing the question content and extracting important keywords" refers to the process of analyzing the text entered by the user using natural language processing technology to extract key words and phrases that clarify the subject and purpose of the question.

[0249] "Emotion analysis means" is a technology for analyzing emotions (anger, joy, sadness, etc.) contained in input text and understanding the user's emotional state.

[0250] "Generative AI" is an artificial intelligence system that automatically generates legal information appropriate to input keywords and context based on large amounts of legal data.

[0251] "User formatting" refers to the process of providing generated legal information in a format that is easy for users to understand, and providing relevant links and references where necessary.

[0252] "Means for adjusting tone" refers to technology that appropriately adjusts the wording and expression of generated responses based on the results of sentiment analysis.

[0253] A "secure communication protocol" is a protocol that prevents communication content from being eavesdropped on or tampered with by third parties, such as an encryption method such as HTTPS.

[0254] The present invention relates to a system in which a user inputs a legal question through a terminal, and a server provides appropriate legal information using a generative AI and an emotion engine. A specific example of this system is described below.

[0255] Overall system configuration

[0256] This system consists of a terminal, a server, a generation AI, and an emotion engine to respond quickly and appropriately to user questions. Users input legal questions using a computer device (e.g., a smartphone or PC), and the questions are sent to the server via a network. The server analyzes the content of the question, extracts important keywords, and then analyzes the user's emotional state using the emotion engine. The generation AI then generates appropriate legal information based on the extracted keywords and the results of the emotion analysis. The generated legal information is formatted by the server and ultimately provided to the user via the terminal.

[0257] User input and question submission

[0258] The user opens a web browser or other interface on their device and enters a legal question, such as "What should I do if my neighbors are making noise late at night?". When the user clicks the "Submit" button, the device securely sends the question to the server using the HTTPS protocol.

[0259] Question analysis and keyword extraction

[0260] The server receives the question in JSON format via HTTPS and first launches a text analysis engine to analyze the data. At this stage, the server's text analysis engine extracts important keywords from the question, such as "neighbors," "late night," "noise," and "how to respond."

[0261] Sentiment analysis and legal information generation

[0262] Next, the server uses an emotion engine to analyze the user's emotional state from the entered question. For example, emotions such as "confusion" or "anger" can be detected from the context of the question. The extracted keywords and the results of the emotion analysis are passed to the generation AI, which then searches for appropriate legal information and past precedents based on an internal legal dataset to generate an answer. For example, legal information such as "Under Article 709 of the Civil Code, it is possible to claim compensation for noise disturbances" is generated. At this time, the tone is also adjusted based on the results of the emotion analysis.

[0263] Formatting and Presenting Legal Information

[0264] The generated legal information is then formatted for the user by the server, making it easy to understand. In some cases, relevant links and references are also added. For example, the information might be something like, "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbors. Please see the link below for more information." Finally, the formatted answer is sent to the terminal and displayed on the user's device.

[0265] Specific examples

[0266] As a specific example, let's consider a case where a user inputs a question such as, "What should I do if my company doesn't pay my overtime wages?" and an emotion of anxiety is detected from the question. In this case, the device sends the question to the server, which extracts keywords such as "overtime wages" and "not paid." The emotion engine detects the user's emotion of anxiety and feeds the results back to the generation AI. The generation AI generates information related to the Labor Standards Act in a tone that alleviates anxiety. For example, it provides information such as, "According to Article 37 of the Labor Standards Act, overtime wages should be paid without fail. If you are concerned, we recommend that you consult the Labor Standards Inspection Office."

[0267] In this way, the system allows users to ask legal questions easily and quickly, and also provides information that takes into consideration the user's feelings.

[0268] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0269] Step 1: User enters question

[0270] A user uses a computing device (such as a smartphone or PC) to enter a legal question into the system's web interface. The question is entered in natural language and is specific, such as "What should I do if my neighbors are making noise late at night?" This input is stored in a data field and passed on to the next processing step.

[0271] Step 2: Send the question to the server

[0272] When the user clicks the "Submit" button, the device sends the entered question to the server as a secure HTTP POST request using the HTTPS protocol, with the data encoded in JSON format.

[0273] Step 3: The server receives and parses the query

[0274] The server parses the received HTTP POST request and extracts the JSON format data. Then, the server's built-in text analysis engine is activated and analyzes the grammatical structure of the question. Specifically, the question text is broken down into tokens and the main and subordinate sentences are identified through grammatical analysis.

[0275] Step 4: Extract keywords

[0276] The text analysis engine extracts important keywords from the analyzed sentences. For example, keywords such as "neighbor," "late night," "noise," and "how to deal with it" are extracted. The algorithm used for this is a natural language processing technique such as TF-IDF (Term Frequency-Inverse Document Frequency). The extracted keywords are passed on to the next processing step.

[0277] Step 5: Conduct sentiment analysis

[0278] The server then launches an emotion engine to analyze the emotional state of the input question. For example, it can detect emotions such as "confusion" or "anger" from the context of the text. Specifically, it uses a pre-trained emotion model to calculate an emotion score for the document and saves it as the analysis result.

[0279] Step 6: Pass legal information to the generative AI

[0280] The server passes the extracted keywords and sentiment analysis results to the generation AI as input. The generation AI then uses its internal legal dataset to search for legal information and past precedents related to the keywords and generates an answer to the question. For example, it might generate something like, "Under Article 709 of the Civil Code, it is possible to claim compensation for noise pollution."

[0281] Step 7: Format the generated legal information

[0282] The server formats the legal information output by the generative AI for the user, making the answer text easier to understand and adding relevant links and references. This process uses technologies such as template engines.

[0283] Step 8: Display the Answer to the User

[0284] The server then sends the formatted response back to the terminal and displays it on the user's computing device, for example, "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbors. Please see the link below for more information."

[0285] In this way, the system can properly parse the user's input and provide relevant legal information, as well as respond in a way that takes into account the user's emotional state.

[0286] (Application example 2)

[0287] 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."

[0288] Modern self-driving vehicles and their users often have questions and doubts about complex traffic laws. Furthermore, traffic laws often vary by region, making it difficult to obtain prompt and appropriate information. Furthermore, failure to respond appropriately to a user's questions can increase the user's anxiety and confusion. The present invention aims to address these issues and provide self-driving vehicle users with prompt and appropriate information about traffic laws.

[0289] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0290] In this invention, the server includes: means for a user to input a legal question using a terminal; means for the terminal to transmit the user's question to the server; means for the server to analyze the content of the question and extract important keywords; means for the server to generate relevant legal information using a generation AI based on the extracted keywords; means for the server to format the generated legal information for the user; means for the terminal to display the formatted answer to the user; means for analyzing the question about traffic laws and generating appropriate legal information; and means for analyzing the user's emotional state using an emotion engine to generate the legal information. This allows the user to quickly obtain accurate information about traffic laws even while using an autonomous vehicle, and further enables the information to be provided in a form that takes the user's emotional state into consideration.

[0291] A "terminal" is a device used by a user for input and display, and includes smartphones, tablets, personal computers, etc.

[0292] A "server" is a computer system that receives, analyzes, processes, and generates data entered by a user.

[0293] The "question content" is text information of a question or inquiry about a law or traffic regulation that is input by the user using the terminal.

[0294] "Generative AI" is an artificial intelligence engine that generates relevant legal information based on text data.

[0295] The "emotion engine" is an engine for analyzing the user's emotional state from the text information of the question entered by the user.

[0296] "Keywords" refer to important words and phrases extracted from the question content and are used for information generation by generative AI and analysis by emotion engines.

[0297] "Legal information" is data that includes specific legal information and guidelines regarding traffic laws.

[0298] "Formatting" is the process of arranging the generated legal and regulatory information into a form that is easy for users to understand.

[0299] "Emotional state" indicates the psychological state or feelings of the user when they input the question, and includes, for example, confusion, anger, anxiety, and the like.

[0300] The present invention relates to a system in which a user inputs questions about traffic regulations and other laws through a terminal, and a server provides appropriate legal information using a generative AI and an emotion engine. A specific example of the system is described below.

[0301] System Overview

[0302] The entire system consists of a user's device, a server, a generation AI, and an emotion engine. The user inputs a question about traffic laws using the device, and the question is sent to the server. The server analyzes the question and generates appropriate legal information using the generation AI and emotion engine. The generated information is then formatted in an easy-to-understand format and provided to the user via the device.

[0303] Specific program processing overview

[0304] 1. User Input

[0305] A user accesses the interface on their device (e.g., a smartphone or PC) and types a question about traffic laws into a text box, for example, "Is a U-turn legal in this area?"

[0306] 2. Submit your question

[0307] The user clicks the "Submit" button, and the device sends the entered question to the server as an HTTPS request.

[0308] 3. Question Analysis

[0309] The server receives the question in JSON format and launches a text analysis engine (e.g., spaCy or NLTK) to analyze the question.

[0310] 4. Keyword extraction

[0311] The server's text analysis engine analyzes the question and extracts important keywords, such as "area," "U-turn," and "legal."

[0312] 5. Emotion Analysis

[0313] The server uses an emotion engine (for example, Microsoft Azure's Text Analytics API) to analyze the user's emotional state from the entered question. For example, emotions such as "confusion" or "urgency" can be detected from the context of the question.

[0314] 6. Generating legal information

[0315] The server passes the extracted keywords and sentiment analysis results to a generation AI (for example, OpenAI's GPT-4). The generation AI uses its internal traffic law dataset to generate appropriate legal information in response to the user's question. For example, it generates information such as, "U-turns are prohibited in this area. Fines may be imposed." Based on the sentiment analysis results, the information is generated in an appropriate tone.

[0316] 7. Information Format

[0317] The generated legal information is then formatted for the user by the server, which formats the generated information into an easy-to-understand format and adds relevant links and references as needed, thereby providing information in a way that takes into account the user's emotional state.

[0318] 8. View Answers

[0319] Finally, a formatted response is sent to the device and displayed to the user, such as "According to local traffic laws, making a U-turn is illegal and may result in a fine." The tone of the response is adjusted based on the results of sentiment analysis.

[0320] Specific examples

[0321] As a specific example, let's consider a case where a user inputs the question, "Is a U-turn legal in this area?" and a confused emotion is detected from the question. In this case, the device sends the question to the server, which extracts keywords such as "area," "U-turn," and "legal." The emotion engine detects the user's confused emotion and feeds the result back to the generation AI. The generation AI generates information related to local traffic laws in a tone that will alleviate the user's confusion. For example, information is provided such as, "U-turns are prohibited in this area. Fines may be imposed. See the link below for details."

[0322] An example of a prompt to input to a generative AI model is as follows:

[0323] Keywords: local area, U-turn, legal

[0324] Emotion: Confused

[0325] Please provide information on relevant traffic laws.

[0326] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0327] Step 1:

[0328] User Input

[0329] A user uses a device (smartphone or PC) to enter a question about traffic laws into a text box. The question (e.g., "Is a U-turn legal in this area?") is captured within the application and prepared for passing to the next processing step.

[0330] Step 2:

[0331] Submit a Question

[0332] When the user clicks the "Submit" button, the device sends the entered question to the server as an HTTPS request, and the data is serialized in JSON format and sent to the server via a secure communication protocol.

[0333] Step 3:

[0334] Question Analysis

[0335] The server deserializes the received question in JSON format. Next, it invokes a text analysis engine (e.g., spaCy or NLTK) to analyze the question and extract important keywords. Keywords such as "area," "U-turn," and "legal" are extracted from the input question text.

[0336] Step 4:

[0337] Emotion Analysis

[0338] The server uses an emotion engine (for example, Microsoft Azure's Text Analytics API) to analyze the user's emotional state from the received question. As a result of the analysis, emotions such as "confusion" or "urgency" are output based on the context of the question.

[0339] Step 5:

[0340] Generating legal information using generative AI

[0341] The server converts the extracted keywords and sentiment analysis results into prompt format and passes them to a generation AI (e.g., OpenAI's GPT-4). The generation AI generates appropriate legal information based on an internal traffic law dataset. The output information might be something like, "U-turns are prohibited in this area. Fines may be imposed."

[0342] Step 6:

[0343] Information Format

[0344] The server receives the legal information output by the generation AI and formats it for the user, formatting the information in a way that is easy for the user to understand and adding related links and references as needed.

[0345] Step 7:

[0346] Show Answers

[0347] The formatted answer is then serialized back into JSON and sent over HTTPS to the user's device, where it is deserialized and displayed in a user-friendly format, such as "According to local traffic laws, U-turns are illegal and may result in fines."

[0348] 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.

[0349] 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.

[0350] 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.

[0351] [Second embodiment]

[0352] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0353] 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.

[0354] 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).

[0355] 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.

[0356] 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.

[0357] 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).

[0358] 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.

[0359] 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.

[0360] 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.

[0361] 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.

[0362] 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.

[0363] 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."

[0364] The present invention relates to a system in which a user inputs legal questions via a terminal, and a server provides appropriate legal information using a generation AI. A specific example of the system is described below.

[0365] System Overview

[0366] The overall system consists of a user's device, a server, and a generation AI. The user inputs a legal question using the device, which is then sent to the server. The server analyzes the question and generates appropriate legal information using the generation AI. The generated information is then formatted in an easy-to-understand format and provided to the user via the device.

[0367] Program processing overview

[0368] User Input

[0369] Users access the interface on their device (e.g., a smartphone or PC) and enter a legal question into a text box, such as "What should I do if my neighbors are making noise late at night?"

[0370] Submit a Question

[0371] When the user clicks the "Submit" button, the device sends the entered question to the server as an HTTP request. The communication is carried out using a secure protocol (e.g., HTTPS).

[0372] Question Analysis

[0373] The server analyzes the received question and extracts important keywords, such as "neighbor," "late night," "noise," and "how to respond," which are used for subsequent processing.

[0374] Legal information generation

[0375] The server passes the extracted keywords to the generation AI, which uses its internal legal dataset to search for and generate appropriate legal information and past precedents for the user's question. For example, it generates information such as "Under Article 709 of the Civil Code, it is possible to claim compensation for noise disturbances."

[0376] Information Format

[0377] The generated legal information is then formatted for the user by the server, which formats the information in an easy-to-understand format and adds relevant links and references as needed.

[0378] Show Answers

[0379] Finally, a formatted response is sent to the device and displayed to the user, such as "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. Please see the link below for more information."

[0380] Specific examples

[0381] As a specific example, let's consider the case where a user inputs the question, "What should I do if my company doesn't pay me my overtime wages?" In this case, the device sends the question to the server, which extracts keywords such as "overtime wages" and "not paid." The generation AI generates information related to the Labor Standards Act, which the server then formats appropriately and provides to the user. Finally, the user's device displays the following message: "According to Article 37 of the Labor Standards Act, overtime wages should be paid. We recommend that you consult with the Labor Standards Inspection Office as a specific procedure."

[0382] As described above, the system of the present invention provides an efficient method for users to easily and quickly obtain legal advice and appropriate legal information.

[0383] The processing flow will be explained below.

[0384] Step 1:

[0385] A user accesses the interface on their device and types a legal question into a text box, such as "What should I do if my neighbors are making noise late at night?"

[0386] Step 2:

[0387] When the user clicks the "Submit" button, the device sends the entered question to the server as an HTTP request. The communication is carried out using a secure protocol (e.g., HTTPS).

[0388] Step 3:

[0389] The server receives the question in JSON format and starts a text analysis engine to analyze the received data.

[0390] Step 4:

[0391] The server's text analysis engine analyzes the question and extracts important keywords, such as "neighbors," "late night," "noise," and "how to deal with it."

[0392] Step 5:

[0393] The server passes the extracted keywords to the generation AI, which uses its internal legal dataset to search for the most relevant legal information and past precedents and generate appropriate legal information. For example, it generates information such as, "Under Article 709 of the Civil Code, it is possible to claim compensation for noise disturbances."

[0394] Step 6:

[0395] The server receives the legal information returned by the generation AI and formats it for the user. The server formats the generated information in an easy-to-understand format, adding relevant links and references as needed.

[0396] Step 7:

[0397] The server sends the formatted answer to the device as an HTTP response in JSON format, and the user's device receives the response.

[0398] Step 8:

[0399] The device displays the answer to the user. For example, information is displayed on the device screen in the form of "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. Please refer to the link below for more information."

[0400] The above is a series of steps for processing legal questions from users. This flow is important for the system as a whole to respond quickly and accurately to user questions.

[0401] Example 1

[0402] 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."

[0403] In modern society, many people have legal problems and questions, but accessing legal experts is time-consuming. Furthermore, information on the Internet is often unreliable, making it difficult to quickly obtain accurate legal information. To address these issues, a system is needed that allows users to easily obtain reliable legal information.

[0404] 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.

[0405] In this invention, the server includes: a means for a user to input a legal question; a means for a terminal to transmit the user's question to the server using a secure communication protocol; a means for the server to analyze the received question using a natural language processing algorithm and extract important keywords; a means for the server to pass a prompt sentence for generating related legal information using a generation AI based on the extracted keywords; a means for the server to format the generated legal information for the user; a means for the server to add related links and reference materials to the generated legal information; and a means for the terminal to display the formatted answer to the user. This allows the user to easily and quickly obtain reliable legal information.

[0406] "User" means any person or entity that uses the System to enter legal questions and receive answers.

[0407] "Terminal" refers to an electronic device used by a user for input and display. Specifically, it includes smartphones, personal computers, tablets, etc.

[0408] "Server" refers to the central computer that receives, analyzes, processes, and generates answers to user questions.

[0409] "Question content" refers to text data of legal questions or inquiries entered by the user using the terminal.

[0410] A "secure communication protocol" refers to a communication method that prevents unauthorized access by third parties when sending and receiving data. Specifically, HTTPS is one example.

[0411] "Natural language processing algorithm" refers to a technical means for analyzing human language and extracting information.

[0412] "Keywords" refer to words and phrases extracted from the query that are important for generating legal information.

[0413] "Generative AI" refers to a model that uses artificial intelligence technology to generate relevant legal information based on a given prompt.

[0414] "Prompt sentence" refers to the input sentence that the generative AI uses to generate an appropriate response.

[0415] "Format" refers to the means by which the generated legal information is arranged in a form that is easy for users to understand.

[0416] "Reference links and additional resources" refers to supplementary information provided to help users understand more.

[0417] "Answer" refers to the legal information generated by the AI ​​in response to a user's question and formatted and provided by the server.

[0418] The present invention is a system in which a user inputs a legal question through a terminal, and a server provides appropriate legal information using a generation AI. This system is composed of a user's terminal, a server, and a generation AI. Specific embodiments of the system are described in detail below.

[0419] System Overview

[0420] A user accesses the interface on their device (e.g., a smartphone or PC) and enters a legal question into a text box. For example, they can enter a question such as, "What should I do if my neighbors are making noise late at night?" After entering the question, the user clicks the "Submit" button, and the device sends the entered question to the server using the HTTPS protocol. This communication uses a secure protocol, so the data is encrypted before being sent.

[0421] The server uses a natural language processing (NLP) algorithm to analyze the received question. This algorithm extracts important keywords from the question, such as "neighbors," "late night," "noise," and "how to respond." The server then passes the extracted keywords to the generation AI. The generation AI model generates appropriate legal information for the user's question based on its internal legal dataset and past case law. The following prompt is used for the generation AI:

[0422] Please provide relevant legal information in response to the question, "What should I do if my neighbor is making noise late at night?"

[0423] The generated legal information might include, for example, "Under Article 709 of the Civil Code, it is possible to claim compensation for noise."

[0424] The server formats the generated legal information in a way that is easy for the user to understand. The server formats the information and inserts relevant links and additional references as needed. Finally, the formatted answer is sent to the device and displayed in the user's browser. For example, it might look something like this:

[0425] According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. Please refer to the link below for more information.

[0426] This system allows users to quickly obtain reliable legal information. Specifically, let's consider the case where a user inputs a question such as, "What should I do if my company doesn't pay me my overtime wages?" In this case, the device sends the question to the server, which extracts keywords such as "overtime wages" and "not paid." The generation AI generates information related to the Labor Standards Act, which the server then formats appropriately and provides to the user. Finally, the user's device displays the following message: "According to Article 37 of the Labor Standards Act, overtime wages should be paid. We recommend that you consult with the Labor Standards Inspection Office for specific procedures."

[0427] Thus, the system of the present invention provides an efficient method for users to easily and quickly obtain legal advice and appropriate legal information.

[0428] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0429] Step 1:

[0430] The user uses a terminal to enter a legal question. For example, the user types "What should I do if my neighbors are making noise late at night?" into a text box. This is done using the system's web interface.

[0431] Input: The question text entered by the user

[0432] Output: None (user input is temporarily stored in a database or memory)

[0433] Step 2:

[0434] When the user clicks the "Submit" button, the device sends the question to the server using the HTTPS protocol, where the device validates the input and ensures that the question is in the correct format.

[0435] Input: The question text entered by the user and validated

[0436] Output: Question as HTTPS request

[0437] Step 3:

[0438] The server uses a natural language processing (NLP) algorithm to analyze the received question. The server extracts important keywords from the question. In this step, keywords such as "neighbors," "late night," "noise," and "how to deal with it" are extracted.

[0439] Input: Question text sent to the server

[0440] Output: List of extracted keywords (e.g., "neighbor," "late night," "noise," "how to respond")

[0441] Step 4:

[0442] The server passes the extracted keywords to the generation AI model. The server then creates a prompt for the generation AI, and generates legal information based on this prompt. For example, the prompt passed to the generation AI is as follows:

[0443] Please provide relevant legal information in response to the question, "What should I do if my neighbor is making noise late at night?"

[0444] Input: Extracted keyword list, generated prompt sentence

[0445] Output: Legal information generated by the AI ​​(e.g., "Article 709 of the Civil Code allows for the claim of compensation for noise pollution.")

[0446] Step 5:

[0447] The server formats the generated legal information in a user-friendly format. The server formats the information and inserts relevant links and additional references as needed.

[0448] Input: Legal information generated by the generative AI

[0449] Output: Formatted legal information (e.g., "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. Please see the link below for more information.")

[0450] Step 6:

[0451] Finally, the server sends the formatted response to the device, which displays the received information in the user's web browser.

[0452] Input: Formatted legal information

[0453] Output: The final answer that is displayed in the user's browser

[0454] Through the above specific processing steps, users can efficiently obtain reliable legal information.

[0455] (Application example 1)

[0456] 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."

[0457] In conventional legal consultation systems, it has been difficult for users to receive prompt and accurate legal information in real time when asking legal questions. Furthermore, users have been unable to immediately consult about security-related legal issues and obtain appropriate solutions, significantly impairing user convenience. The present invention aims to solve these problems by providing a system that allows users to consult about security-related legal issues in real time and quickly provides accurate legal information.

[0458] 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.

[0459] In this invention, the server includes means for a user to input a legal question using an electronic device, means for the electronic device to transmit the user's question to a data processing device, means for the data processing device to analyze the content of the question and extract important information, means for the data processing device to generate relevant legal information using a generation AI based on the extracted information, means for the data processing device to format the generated legal information for the user, means for the electronic device to display the formatted answer to the user, and means for the electronic device to display the legal information in real time. This allows users to quickly and accurately consult on legal issues related to security on the spot and learn appropriate responses in real time.

[0460] "User" means a person who uses the system to enter legal questions and obtain answers.

[0461] "Electronics" refers to the terminal where the user inputs, sends questions, and displays answers.

[0462] A "legal question" is a question posed to the system by a user regarding laws, regulations, or legal issues.

[0463] A "data processing device" is a computer system that analyzes a user's question, generates legal information using generative AI, and provides a formatted answer.

[0464] "Question content" refers to the text of a legal inquiry entered by a user through an electronic device.

[0465] "Important information" refers to keywords and themes extracted from the user's question for generating legal information.

[0466] "Generative AI" refers to an artificial intelligence model that generates relevant information based on input data.

[0467] "Legal information" refers to laws, precedents, and advice provided in response to users' questions.

[0468] "Formatting" refers to arranging the generated legal information in a form that is easy for the user to view and understand.

[0469] An "answer" is legal information that the system generates in response to a question and provides to the user.

[0470] "Real time" refers to near-instant processing and response.

[0471] This invention is a system that allows users to receive real-time consultations on legal issues related to security. Specifically, users input questions using electronic devices, and a data processing device analyzes and answers the questions.

[0472] System Configuration

[0473] The system consists of the following main components:

[0474] User terminals (electronic devices)

[0475] Data processing device (server)

[0476] Generative AI Models

[0477] Hardware and Software

[0478] The hardware and software used are as follows:

[0479] Electronics: Smart glasses (e.g. Google Glass, Vuzix Blade)

[0480] Data processing equipment: Cloud server (e.g. AWS, Azure)

[0481] Generative AI model: GPT-3

[0482] Program processing flow

[0483] The system proceeds as follows:

[0484] 1. User Input

[0485] Users use the smart glasses to input legal questions, such as "What should I do if I have a suspicious person in my neighborhood?"

[0486] 2. Submit a question

[0487] Once the user enters a question, the smart glasses send it to the server using the secure HTTPS protocol.

[0488] 3. Question analysis

[0489] The server analyzes the received question and extracts important information (keywords), such as "suspicious person" and "how to deal with it."

[0490] 4. Legal information generation

[0491] The server queries a generative AI model (GPT-3) based on the extracted information to generate relevant legal information. The generative AI model then references an internal dataset to generate appropriate legal information for the user's question.

[0492] 5. Information Format

[0493] The server formats the generated legal information for the user, making it easier to read and adding relevant links and references where necessary.

[0494] 6. Answer display

[0495] The final formatted answer is sent to the user terminal and displayed to the user in real time through the smart glasses.

[0496] Specific examples

[0497] The user explains the question in a flow: "What should I do if my company doesn't pay me my overtime wages?" In this case, the smart glasses send the question to the server, which extracts keywords such as "overtime wages" and "not paid." The generative AI model generates information related to Article 37 of the Labor Standards Act, which the server formats and provides to the user. Finally, the smart glasses display the message: "According to Article 37 of the Labor Standards Act, overtime wages should be paid. We recommend that you consult with the Labor Standards Inspection Office for specific procedures."

[0498] Prompt Sentence Examples

[0499] Examples of prompts are:

[0500] text

[0501] What should I do if there are suspicious people in my neighborhood?

[0502] This allows users to consult on security-related legal issues in real time on the spot and quickly obtain appropriate countermeasures.

[0503] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0504] Step 1:

[0505] The user uses the smart glasses to input a legal question, which is stored in the smart glasses as text data. The input of this step is the text data entered by the user, and the output is the text data stored in the smart glasses.

[0506] Step 2:

[0507] The device (smart glasses) sends the entered question to the server using the secure HTTPS protocol. The input for this step is the question data in text format, and the output is the question data sent to the server as an HTTPS request.

[0508] Step 3:

[0509] The server analyzes the received question and extracts important information (keywords). For example, words such as "suspicious person" and "how to deal with it" are extracted. The input for this step is the text data sent in the HTTPS request, and the output is a list of extracted keywords.

[0510] Step 4:

[0511] The server uses a generative AI model (GPT-3) to generate relevant legal information based on the extracted keywords. The generative AI model references an internal dataset to provide appropriate legal information for a specific question. The input for this step is a list of keywords, and the output is the generated legal information text.

[0512] Step 5:

[0513] The server formats the generated legal information for the user, making it easier to read and adding relevant links and references as needed. The input to this step is the generated legal text and the output is the formatted answer text.

[0514] Step 6:

[0515] The server then sends the formatted response to the terminal, again using a secure communication protocol. The input to this step is the formatted response data, and the output is the response data sent to the terminal as an HTTPS response.

[0516] Step 7:

[0517] The terminal (smart glasses) displays the formatted answer received from the server to the user in real time. The user checks the answer through the smart glasses display and decides the next action. The input of this step is the formatted answer data received in the HTTPS response, and the output is the user's visual confirmation.

[0518] 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.

[0519] The present invention relates to a system in which a user inputs a legal question through a terminal, and a server provides appropriate legal information using a generative AI and an emotion engine. A specific example of the system is described below.

[0520] System Overview

[0521] The overall system consists of a user's device, a server, a generation AI, and an emotion engine. The user inputs a legal question using the device, which is then sent to the server. The server analyzes the question and generates appropriate legal information using the generation AI and emotion engine. The generated information is then formatted in an easy-to-understand format and provided to the user via the device.

[0522] Program processing overview

[0523] User Input

[0524] Users access the interface on their device (e.g., a smartphone or computer) and enter a legal question into a text box, such as "What should I do if my neighbors are making noise late at night?"

[0525] Submit a Question

[0526] When the user clicks the "Submit" button, the device sends the entered question to the server as an HTTP request. The communication is carried out using a secure protocol (e.g., HTTPS).

[0527] Question Analysis

[0528] The server receives the question in JSON format and starts a text analysis engine to analyze the received data.

[0529] Keyword extraction

[0530] The server's text analysis engine analyzes the question and extracts important keywords, such as "neighbors," "late night," "noise," and "how to deal with it."

[0531] Emotion Analysis

[0532] The server uses an emotion engine to analyze the user's emotional state from the input question. For example, emotions such as "confusion" or "anger" can be detected from the context of the question.

[0533] Legal information generation

[0534] The server passes the extracted keywords and the results of the sentiment analysis to the generation AI. The generation AI then uses its internal legal dataset to search for and generate appropriate legal information and past precedents for the user's question. For example, it may generate information such as, "Under Article 709 of the Civil Code, it is possible to claim compensation for noise pollution." Based on the results of the sentiment analysis, the information is generated in an appropriate tone.

[0535] Information Format

[0536] The generated legal information is then formatted for the user by the server, which formats the generated information in an easy-to-understand format and adds relevant links and references as needed, thereby providing information that takes into account the user's emotional state.

[0537] Show Answers

[0538] Finally, a formatted response is sent to the device and displayed to the user. For example, it may say, "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. Please see the link below for more information." The tone of the response is adjusted based on the results of sentiment analysis.

[0539] Specific examples

[0540] As a specific example, let's consider a case where a user inputs a question such as, "What should I do if my company doesn't pay my overtime wages?" and an emotion of anxiety is detected from the question. In this case, the device sends the question to the server, which extracts keywords such as "overtime wages" and "not paid." The emotion engine detects the user's emotion of anxiety and feeds the results back to the generation AI. The generation AI generates information related to the Labor Standards Act in a tone that alleviates anxiety. For example, it provides information such as, "According to Article 37 of the Labor Standards Act, overtime wages should be paid without fail. If you are worried, we recommend that you consult the Labor Standards Inspection Office."

[0541] As described above, the system of the present invention allows users to easily and quickly seek legal advice and obtain appropriate legal information, and furthermore, is capable of providing information that takes into consideration the user's feelings.

[0542] The processing flow will be explained below.

[0543] Step 1:

[0544] A user accesses the interface on their device and types a legal question into a text box, such as "What should I do if my neighbors are making noise late at night?"

[0545] Step 2:

[0546] When the user clicks the "Submit" button, the device sends the entered question to the server as an HTTP request. The communication is carried out using a secure protocol (e.g., HTTPS).

[0547] Step 3:

[0548] The server receives the question in JSON format and starts a text analysis engine to analyze the received data.

[0549] Step 4:

[0550] The server's text analysis engine analyzes the question and extracts important keywords, such as "neighbors," "late night," "noise," and "how to deal with it."

[0551] Step 5:

[0552] The server uses an emotion engine to analyze the user's emotional state from the input question. For example, emotions such as "confusion" or "anger" can be detected from the context of the question.

[0553] Step 6:

[0554] The server passes the extracted keywords and sentiment analysis results to the generation AI. The generation AI then uses its internal legal dataset to search for and generate appropriate legal information and past precedents for the user's question. For example, it generates information such as, "Under Article 709 of the Civil Code, it is possible to claim compensation for noise disturbances."

[0555] Step 7:

[0556] The emotion engine analyzes the user's emotional state and adjusts the tone of the generated legal information based on that state. For example, if the user is "confused," the information is presented in a more reassuring tone.

[0557] Step 8:

[0558] The server receives the legal information returned by the generation AI and formats it for the user. The server formats the generated information in an easy-to-understand format, adding relevant links and references as needed. The tone of the information is adjusted based on feedback from the emotion engine.

[0559] Step 9:

[0560] The server sends the formatted answer to the device as an HTTP response in JSON format, and the user's device receives the response.

[0561] Step 10:

[0562] The device displays the answer to the user. For example, the device displays information in a reassuring tone on the screen, such as, "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. If you have any questions, please refer to the link below."

[0563] As a specific example, let's consider a case where a user inputs a question such as "What should I do if my company doesn't pay my overtime wages?" and an emotion of anxiety is detected from the question. In this case, the device sends the question to the server. The server extracts keywords such as "overtime wages" and "not paid," and the emotion engine detects the user's emotion of anxiety. The results are fed back to the generation AI, which then generates information related to the Labor Standards Act in a tone that alleviates the anxiety. For example, the information provided may be something like, "According to Article 37 of the Labor Standards Act, overtime wages should be paid without fail. If you are worried, we recommend that you consult the Labor Standards Inspection Office."

[0564] The above are the specific processing steps of the system of the present invention that combines an emotion engine. This system allows users to easily receive legal advice that takes emotional considerations into account, and enables them to quickly obtain accurate and reliable legal information.

[0565] Example 2

[0566] 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."

[0567] Conventional legal consultation systems have difficulty providing appropriate legal information in response to user-entered questions, and are particularly unable to generate answers that take into account the user's emotional state. Furthermore, generating appropriate legal information requires manual search and legal knowledge, making it extremely difficult for non-experts. To solve this problem, a system was needed that could analyze the content of a user's question, extract important keywords, and automatically provide appropriate legal information.

[0568] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for analyzing the content of the question and extracting important keywords, a sentiment analysis means, and a means for generating relevant legal information using a generation AI. This makes it possible to provide prompt and appropriate legal information that takes into consideration the user's sentiments.

[0569] A "computing device" is an electronic device, such as a personal computer, smartphone, or tablet, that allows a user to connect to the Internet and input or receive data.

[0570] A "network" is a communications infrastructure for data communication, such as the Internet or an intranet.

[0571] A "server" is a computer system that can process data in response to a user's request via a network and return the results.

[0572] "Means for analyzing the question content and extracting important keywords" refers to the process of analyzing the text entered by the user using natural language processing technology to extract key words and phrases that clarify the subject and purpose of the question.

[0573] "Emotion analysis means" is a technology for analyzing emotions (anger, joy, sadness, etc.) contained in input text and understanding the user's emotional state.

[0574] "Generative AI" is an artificial intelligence system that automatically generates legal information appropriate to input keywords and context based on large amounts of legal data.

[0575] "User formatting" refers to the process of providing generated legal information in a format that is easy for users to understand, and providing relevant links and references where necessary.

[0576] "Means for adjusting tone" refers to technology that appropriately adjusts the wording and expression of generated responses based on the results of sentiment analysis.

[0577] A "secure communication protocol" is a protocol that prevents communication content from being eavesdropped on or tampered with by third parties, such as an encryption method such as HTTPS.

[0578] The present invention relates to a system in which a user inputs a legal question through a terminal, and a server provides appropriate legal information using a generative AI and an emotion engine. A specific example of this system is described below.

[0579] Overall system configuration

[0580] This system consists of a terminal, a server, a generation AI, and an emotion engine to respond quickly and appropriately to user questions. Users input legal questions using a computer device (e.g., a smartphone or PC), and the questions are sent to the server via a network. The server analyzes the content of the question, extracts important keywords, and then analyzes the user's emotional state using the emotion engine. The generation AI then generates appropriate legal information based on the extracted keywords and the results of the emotion analysis. The generated legal information is formatted by the server and ultimately provided to the user via the terminal.

[0581] User input and question submission

[0582] The user opens a web browser or other interface on their device and enters a legal question, such as "What should I do if my neighbors are making noise late at night?". When the user clicks the "Submit" button, the device securely sends the question to the server using the HTTPS protocol.

[0583] Question analysis and keyword extraction

[0584] The server receives the question in JSON format via HTTPS and first launches a text analysis engine to analyze the data. At this stage, the server's text analysis engine extracts important keywords from the question, such as "neighbors," "late night," "noise," and "how to respond."

[0585] Sentiment analysis and legal information generation

[0586] Next, the server uses an emotion engine to analyze the user's emotional state from the entered question. For example, emotions such as "confusion" or "anger" can be detected from the context of the question. The extracted keywords and the results of the emotion analysis are passed to the generation AI, which then searches for appropriate legal information and past precedents based on an internal legal dataset to generate an answer. For example, legal information such as "Under Article 709 of the Civil Code, it is possible to claim compensation for noise disturbances" is generated. At this time, the tone is also adjusted based on the results of the emotion analysis.

[0587] Formatting and Presenting Legal Information

[0588] The generated legal information is then formatted for the user by the server, making it easy to understand. In some cases, relevant links and references are also added. For example, the information might be something like, "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbors. Please see the link below for more information." Finally, the formatted answer is sent to the terminal and displayed on the user's device.

[0589] Specific examples

[0590] As a specific example, let's consider a case where a user inputs a question such as, "What should I do if my company doesn't pay my overtime wages?" and an emotion of anxiety is detected from the question. In this case, the device sends the question to the server, which extracts keywords such as "overtime wages" and "not paid." The emotion engine detects the user's emotion of anxiety and feeds the results back to the generation AI. The generation AI generates information related to the Labor Standards Act in a tone that alleviates anxiety. For example, it provides information such as, "According to Article 37 of the Labor Standards Act, overtime wages should be paid without fail. If you are concerned, we recommend that you consult the Labor Standards Inspection Office."

[0591] In this way, the system allows users to ask legal questions easily and quickly, and also provides information that takes into consideration the user's feelings.

[0592] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0593] Step 1: User enters question

[0594] A user uses a computing device (such as a smartphone or PC) to enter a legal question into the system's web interface. The question is entered in natural language and is specific, such as "What should I do if my neighbors are making noise late at night?" This input is stored in a data field and passed on to the next processing step.

[0595] Step 2: Send the question to the server

[0596] When the user clicks the "Submit" button, the device sends the entered question to the server as a secure HTTP POST request using the HTTPS protocol, with the data encoded in JSON format.

[0597] Step 3: The server receives and parses the query

[0598] The server parses the received HTTP POST request and extracts the JSON format data. Then, the server's built-in text analysis engine is activated and analyzes the grammatical structure of the question. Specifically, the question text is broken down into tokens and the main and subordinate sentences are identified through grammatical analysis.

[0599] Step 4: Extract keywords

[0600] The text analysis engine extracts important keywords from the analyzed sentences. For example, keywords such as "neighbor," "late night," "noise," and "how to deal with it" are extracted. The algorithm used for this is a natural language processing technique such as TF-IDF (Term Frequency-Inverse Document Frequency). The extracted keywords are passed on to the next processing step.

[0601] Step 5: Conduct sentiment analysis

[0602] The server then launches an emotion engine to analyze the emotional state of the input question. For example, it can detect emotions such as "confusion" or "anger" from the context of the text. Specifically, it uses a pre-trained emotion model to calculate an emotion score for the document and saves it as the analysis result.

[0603] Step 6: Pass legal information to the generative AI

[0604] The server passes the extracted keywords and sentiment analysis results to the generation AI as input. The generation AI then uses its internal legal dataset to search for legal information and past precedents related to the keywords and generates an answer to the question. For example, it might generate something like, "Under Article 709 of the Civil Code, it is possible to claim compensation for noise pollution."

[0605] Step 7: Format the generated legal information

[0606] The server formats the legal information output by the generative AI for the user, making the answer text easier to understand and adding relevant links and references. This process uses technologies such as template engines.

[0607] Step 8: Display the Answer to the User

[0608] The server then sends the formatted response back to the terminal and displays it on the user's computing device, for example, "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbors. Please see the link below for more information."

[0609] In this way, the system can properly parse the user's input and provide relevant legal information, as well as respond in a way that takes into account the user's emotional state.

[0610] (Application example 2)

[0611] 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."

[0612] Modern self-driving vehicles and their users often have questions and doubts about complex traffic laws. Furthermore, traffic laws often vary by region, making it difficult to obtain prompt and appropriate information. Furthermore, failure to respond appropriately to a user's questions can increase the user's anxiety and confusion. The present invention aims to address these issues and provide self-driving vehicle users with prompt and appropriate information about traffic laws.

[0613] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0614] In this invention, the server includes: means for a user to input a legal question using a terminal; means for the terminal to transmit the user's question to the server; means for the server to analyze the content of the question and extract important keywords; means for the server to generate relevant legal information using a generation AI based on the extracted keywords; means for the server to format the generated legal information for the user; means for the terminal to display the formatted answer to the user; means for analyzing the question about traffic laws and generating appropriate legal information; and means for analyzing the user's emotional state using an emotion engine to generate the legal information. This allows the user to quickly obtain accurate information about traffic laws even while using an autonomous vehicle, and further enables the information to be provided in a form that takes the user's emotional state into consideration.

[0615] A "terminal" is a device used by a user for input and display, and includes smartphones, tablets, personal computers, etc.

[0616] A "server" is a computer system that receives, analyzes, processes, and generates data entered by a user.

[0617] The "question content" is text information of a question or inquiry about a law or traffic regulation that is input by the user using the terminal.

[0618] "Generative AI" is an artificial intelligence engine that generates relevant legal information based on text data.

[0619] The "emotion engine" is an engine for analyzing the user's emotional state from the text information of the question entered by the user.

[0620] "Keywords" refer to important words and phrases extracted from the question content and are used for information generation by generative AI and analysis by emotion engines.

[0621] "Legal information" is data that includes specific legal information and guidelines regarding traffic laws.

[0622] "Formatting" is the process of arranging the generated legal and regulatory information into a form that is easy for users to understand.

[0623] "Emotional state" indicates the psychological state or feelings of the user when they input the question, and includes, for example, confusion, anger, anxiety, and the like.

[0624] The present invention relates to a system in which a user inputs questions about traffic regulations and other laws through a terminal, and a server provides appropriate legal information using a generative AI and an emotion engine. A specific example of the system is described below.

[0625] System Overview

[0626] The entire system consists of a user's device, a server, a generation AI, and an emotion engine. The user inputs a question about traffic laws using the device, and the question is sent to the server. The server analyzes the question and generates appropriate legal information using the generation AI and emotion engine. The generated information is then formatted in an easy-to-understand format and provided to the user via the device.

[0627] Specific program processing overview

[0628] 1. User Input

[0629] A user accesses the interface on their device (e.g., a smartphone or PC) and types a question about traffic laws into a text box, for example, "Is a U-turn legal in this area?"

[0630] 2. Submit your question

[0631] The user clicks the "Submit" button, and the device sends the entered question to the server as an HTTPS request.

[0632] 3. Question Analysis

[0633] The server receives the question in JSON format and launches a text analysis engine (e.g., spaCy or NLTK) to analyze the question.

[0634] 4. Keyword extraction

[0635] The server's text analysis engine analyzes the question and extracts important keywords, such as "area," "U-turn," and "legal."

[0636] 5. Emotion Analysis

[0637] The server uses an emotion engine (for example, Microsoft Azure's Text Analytics API) to analyze the user's emotional state from the entered question. For example, emotions such as "confusion" or "urgency" can be detected from the context of the question.

[0638] 6. Generating legal information

[0639] The server passes the extracted keywords and sentiment analysis results to a generation AI (for example, OpenAI's GPT-4). The generation AI uses its internal traffic law dataset to generate appropriate legal information in response to the user's question. For example, it generates information such as, "U-turns are prohibited in this area. Fines may be imposed." Based on the sentiment analysis results, the information is generated in an appropriate tone.

[0640] 7. Information Format

[0641] The generated legal information is then formatted for the user by the server, which formats the generated information into an easy-to-understand format and adds relevant links and references as needed, thereby providing information in a way that takes into account the user's emotional state.

[0642] 8. View Answers

[0643] Finally, a formatted response is sent to the device and displayed to the user, such as "According to local traffic laws, making a U-turn is illegal and may result in a fine." The tone of the response is adjusted based on the results of sentiment analysis.

[0644] Specific examples

[0645] As a specific example, let's consider a case where a user inputs the question, "Is a U-turn legal in this area?" and a confused emotion is detected from the question. In this case, the device sends the question to the server, which extracts keywords such as "area," "U-turn," and "legal." The emotion engine detects the user's confused emotion and feeds the result back to the generation AI. The generation AI generates information related to local traffic laws in a tone that will alleviate the user's confusion. For example, information is provided such as, "U-turns are prohibited in this area. Fines may be imposed. See the link below for details."

[0646] An example of a prompt to input to a generative AI model is as follows:

[0647] Keywords: local area, U-turn, legal

[0648] Emotion: Confused

[0649] Please provide information on relevant traffic laws.

[0650] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0651] Step 1:

[0652] User Input

[0653] A user uses a device (smartphone or PC) to enter a question about traffic laws into a text box. The question (e.g., "Is a U-turn legal in this area?") is captured within the application and prepared for passing to the next processing step.

[0654] Step 2:

[0655] Submit a Question

[0656] When the user clicks the "Submit" button, the device sends the entered question to the server as an HTTPS request, and the data is serialized in JSON format and sent to the server via a secure communication protocol.

[0657] Step 3:

[0658] Question Analysis

[0659] The server deserializes the received question in JSON format. Next, it invokes a text analysis engine (e.g., spaCy or NLTK) to analyze the question and extract important keywords. Keywords such as "area," "U-turn," and "legal" are extracted from the input question text.

[0660] Step 4:

[0661] Emotion Analysis

[0662] The server uses an emotion engine (for example, Microsoft Azure's Text Analytics API) to analyze the user's emotional state from the received question. As a result of the analysis, emotions such as "confusion" or "urgency" are output based on the context of the question.

[0663] Step 5:

[0664] Generating legal information using generative AI

[0665] The server converts the extracted keywords and sentiment analysis results into prompt format and passes them to a generation AI (e.g., OpenAI's GPT-4). The generation AI generates appropriate legal information based on an internal traffic law dataset. The output information might be something like, "U-turns are prohibited in this area. Fines may be imposed."

[0666] Step 6:

[0667] Information Format

[0668] The server receives the legal information output by the generation AI and formats it for the user, formatting the information in a way that is easy for the user to understand and adding related links and references as needed.

[0669] Step 7:

[0670] Show Answers

[0671] The formatted answer is then serialized back into JSON and sent over HTTPS to the user's device, where it is deserialized and displayed in a user-friendly format, such as "According to local traffic laws, U-turns are illegal and may result in fines."

[0672] 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.

[0673] 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.

[0674] 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.

[0675] [Third embodiment]

[0676] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0677] 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.

[0678] 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).

[0679] 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.

[0680] 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.

[0681] 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).

[0682] 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.

[0683] 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.

[0684] 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.

[0685] 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.

[0686] 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.

[0687] 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."

[0688] The present invention relates to a system in which a user inputs legal questions via a terminal, and a server provides appropriate legal information using a generation AI. A specific example of the system is described below.

[0689] System Overview

[0690] The overall system consists of a user's device, a server, and a generation AI. The user inputs a legal question using the device, which is then sent to the server. The server analyzes the question and generates appropriate legal information using the generation AI. The generated information is then formatted in an easy-to-understand format and provided to the user via the device.

[0691] Program processing overview

[0692] User Input

[0693] Users access the interface on their device (e.g., a smartphone or PC) and enter a legal question into a text box, such as "What should I do if my neighbors are making noise late at night?"

[0694] Submit a Question

[0695] When the user clicks the "Submit" button, the device sends the entered question to the server as an HTTP request. The communication is carried out using a secure protocol (e.g., HTTPS).

[0696] Question Analysis

[0697] The server analyzes the received question and extracts important keywords, such as "neighbor," "late night," "noise," and "how to respond," which are used for subsequent processing.

[0698] Legal information generation

[0699] The server passes the extracted keywords to the generation AI, which uses its internal legal dataset to search for and generate appropriate legal information and past precedents for the user's question. For example, it generates information such as "Under Article 709 of the Civil Code, it is possible to claim compensation for noise disturbances."

[0700] Information Format

[0701] The generated legal information is then formatted for the user by the server, which formats the information in an easy-to-understand format and adds relevant links and references as needed.

[0702] Show Answers

[0703] Finally, a formatted response is sent to the device and displayed to the user, such as "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. Please see the link below for more information."

[0704] Specific examples

[0705] As a specific example, let's consider the case where a user inputs the question, "What should I do if my company doesn't pay me my overtime wages?" In this case, the device sends the question to the server, which extracts keywords such as "overtime wages" and "not paid." The generation AI generates information related to the Labor Standards Act, which the server then formats appropriately and provides to the user. Finally, the user's device displays the following message: "According to Article 37 of the Labor Standards Act, overtime wages should be paid. We recommend that you consult with the Labor Standards Inspection Office as a specific procedure."

[0706] As described above, the system of the present invention provides an efficient method for users to easily and quickly obtain legal advice and appropriate legal information.

[0707] The processing flow will be explained below.

[0708] Step 1:

[0709] A user accesses the interface on their device and types a legal question into a text box, such as "What should I do if my neighbors are making noise late at night?"

[0710] Step 2:

[0711] When the user clicks the "Submit" button, the device sends the entered question to the server as an HTTP request. The communication is carried out using a secure protocol (e.g., HTTPS).

[0712] Step 3:

[0713] The server receives the question in JSON format and starts a text analysis engine to analyze the received data.

[0714] Step 4:

[0715] The server's text analysis engine analyzes the question and extracts important keywords, such as "neighbors," "late night," "noise," and "how to deal with it."

[0716] Step 5:

[0717] The server passes the extracted keywords to the generation AI, which uses its internal legal dataset to search for the most relevant legal information and past precedents and generate appropriate legal information. For example, it generates information such as, "Under Article 709 of the Civil Code, it is possible to claim compensation for noise disturbances."

[0718] Step 6:

[0719] The server receives the legal information returned by the generation AI and formats it for the user. The server formats the generated information in an easy-to-understand format, adding relevant links and references as needed.

[0720] Step 7:

[0721] The server sends the formatted answer to the device as an HTTP response in JSON format, and the user's device receives the response.

[0722] Step 8:

[0723] The device displays the answer to the user. For example, information is displayed on the device screen in the form of "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. Please refer to the link below for more information."

[0724] The above is a series of steps for processing legal questions from users. This flow is important for the system as a whole to respond quickly and accurately to user questions.

[0725] Example 1

[0726] 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."

[0727] In modern society, many people have legal problems and questions, but accessing legal experts is time-consuming. Furthermore, information on the Internet is often unreliable, making it difficult to quickly obtain accurate legal information. To address these issues, a system is needed that allows users to easily obtain reliable legal information.

[0728] 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.

[0729] In this invention, the server includes: a means for a user to input a legal question; a means for a terminal to transmit the user's question to the server using a secure communication protocol; a means for the server to analyze the received question using a natural language processing algorithm and extract important keywords; a means for the server to pass a prompt sentence for generating related legal information using a generation AI based on the extracted keywords; a means for the server to format the generated legal information for the user; a means for the server to add related links and reference materials to the generated legal information; and a means for the terminal to display the formatted answer to the user. This allows the user to easily and quickly obtain reliable legal information.

[0730] "User" means any person or entity that uses the System to enter legal questions and receive answers.

[0731] "Terminal" refers to an electronic device used by a user for input and display. Specifically, it includes smartphones, personal computers, tablets, etc.

[0732] "Server" refers to the central computer that receives, analyzes, processes, and generates answers to user questions.

[0733] "Question content" refers to text data of legal questions or inquiries entered by the user using the terminal.

[0734] A "secure communication protocol" refers to a communication method that prevents unauthorized access by third parties when sending and receiving data. Specifically, HTTPS is one example.

[0735] "Natural language processing algorithm" refers to a technical means for analyzing human language and extracting information.

[0736] "Keywords" refer to words and phrases extracted from the query that are important for generating legal information.

[0737] "Generative AI" refers to a model that uses artificial intelligence technology to generate relevant legal information based on a given prompt.

[0738] "Prompt sentence" refers to the input sentence that the generative AI uses to generate an appropriate response.

[0739] "Format" refers to the means by which the generated legal information is arranged in a form that is easy for users to understand.

[0740] "Reference links and additional resources" refers to supplementary information provided to help users understand more.

[0741] "Answer" refers to the legal information generated by the AI ​​in response to a user's question and formatted and provided by the server.

[0742] The present invention is a system in which a user inputs a legal question through a terminal, and a server provides appropriate legal information using a generation AI. This system is composed of a user's terminal, a server, and a generation AI. Specific embodiments of the system are described in detail below.

[0743] System Overview

[0744] A user accesses the interface on their device (e.g., a smartphone or PC) and enters a legal question into a text box. For example, they can enter a question such as, "What should I do if my neighbors are making noise late at night?" After entering the question, the user clicks the "Submit" button, and the device sends the entered question to the server using the HTTPS protocol. This communication uses a secure protocol, so the data is encrypted before being sent.

[0745] The server uses a natural language processing (NLP) algorithm to analyze the received question. This algorithm extracts important keywords from the question, such as "neighbors," "late night," "noise," and "how to respond." The server then passes the extracted keywords to the generation AI. The generation AI model generates appropriate legal information for the user's question based on its internal legal dataset and past case law. The following prompt is used for the generation AI:

[0746] Please provide relevant legal information in response to the question, "What should I do if my neighbor is making noise late at night?"

[0747] The generated legal information might include, for example, "Under Article 709 of the Civil Code, it is possible to claim compensation for noise."

[0748] The server formats the generated legal information in a way that is easy for the user to understand. The server formats the information and inserts relevant links and additional references as needed. Finally, the formatted answer is sent to the device and displayed in the user's browser. For example, it might look something like this:

[0749] According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. Please refer to the link below for more information.

[0750] This system allows users to quickly obtain reliable legal information. Specifically, let's consider the case where a user inputs a question such as, "What should I do if my company doesn't pay me my overtime wages?" In this case, the device sends the question to the server, which extracts keywords such as "overtime wages" and "not paid." The generation AI generates information related to the Labor Standards Act, which the server then formats appropriately and provides to the user. Finally, the user's device displays the following message: "According to Article 37 of the Labor Standards Act, overtime wages should be paid. We recommend that you consult with the Labor Standards Inspection Office for specific procedures."

[0751] Thus, the system of the present invention provides an efficient method for users to easily and quickly obtain legal advice and appropriate legal information.

[0752] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0753] Step 1:

[0754] The user uses a terminal to enter a legal question. For example, the user types "What should I do if my neighbors are making noise late at night?" into a text box. This is done using the system's web interface.

[0755] Input: The question text entered by the user

[0756] Output: None (user input is temporarily stored in a database or memory)

[0757] Step 2:

[0758] When the user clicks the "Submit" button, the device sends the question to the server using the HTTPS protocol, where the device validates the input and ensures that the question is in the correct format.

[0759] Input: The question text entered by the user and validated

[0760] Output: Question as HTTPS request

[0761] Step 3:

[0762] The server uses a natural language processing (NLP) algorithm to analyze the received question. The server extracts important keywords from the question. In this step, keywords such as "neighbors," "late night," "noise," and "how to deal with it" are extracted.

[0763] Input: Question text sent to the server

[0764] Output: List of extracted keywords (e.g., "neighbor," "late night," "noise," "how to respond")

[0765] Step 4:

[0766] The server passes the extracted keywords to the generation AI model. The server then creates a prompt for the generation AI, and generates legal information based on this prompt. For example, the prompt passed to the generation AI is as follows:

[0767] Please provide relevant legal information in response to the question, "What should I do if my neighbor is making noise late at night?"

[0768] Input: Extracted keyword list, generated prompt sentence

[0769] Output: Legal information generated by the AI ​​(e.g., "Article 709 of the Civil Code allows for the claim of compensation for noise pollution.")

[0770] Step 5:

[0771] The server formats the generated legal information in a user-friendly format. The server formats the information and inserts relevant links and additional references as needed.

[0772] Input: Legal information generated by the generative AI

[0773] Output: Formatted legal information (e.g., "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. Please see the link below for more information.")

[0774] Step 6:

[0775] Finally, the server sends the formatted response to the device, which displays the received information in the user's web browser.

[0776] Input: Formatted legal information

[0777] Output: The final answer that is displayed in the user's browser

[0778] Through the above specific processing steps, users can efficiently obtain reliable legal information.

[0779] (Application example 1)

[0780] 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."

[0781] In conventional legal consultation systems, it has been difficult for users to receive prompt and accurate legal information in real time when asking legal questions. Furthermore, users have been unable to immediately consult about security-related legal issues and obtain appropriate solutions, significantly impairing user convenience. The present invention aims to solve these problems by providing a system that allows users to consult about security-related legal issues in real time and quickly provides accurate legal information.

[0782] 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.

[0783] In this invention, the server includes means for a user to input a legal question using an electronic device, means for the electronic device to transmit the user's question to a data processing device, means for the data processing device to analyze the content of the question and extract important information, means for the data processing device to generate relevant legal information using a generation AI based on the extracted information, means for the data processing device to format the generated legal information for the user, means for the electronic device to display the formatted answer to the user, and means for the electronic device to display the legal information in real time. This allows users to quickly and accurately consult on legal issues related to security on the spot and learn appropriate responses in real time.

[0784] "User" means a person who uses the system to enter legal questions and obtain answers.

[0785] "Electronics" refers to the terminal where the user inputs, sends questions, and displays answers.

[0786] A "legal question" is a question posed to the system by a user regarding laws, regulations, or legal issues.

[0787] A "data processing device" is a computer system that analyzes a user's question, generates legal information using generative AI, and provides a formatted answer.

[0788] "Question content" refers to the text of a legal inquiry entered by a user through an electronic device.

[0789] "Important information" refers to keywords and themes extracted from the user's question for generating legal information.

[0790] "Generative AI" refers to an artificial intelligence model that generates relevant information based on input data.

[0791] "Legal information" refers to laws, precedents, and advice provided in response to users' questions.

[0792] "Formatting" refers to arranging the generated legal information in a form that is easy for the user to view and understand.

[0793] An "answer" is legal information that the system generates in response to a question and provides to the user.

[0794] "Real time" refers to near-instant processing and response.

[0795] This invention is a system that allows users to receive real-time consultations on legal issues related to security. Specifically, users input questions using electronic devices, and a data processing device analyzes and answers the questions.

[0796] System Configuration

[0797] The system consists of the following main components:

[0798] User terminals (electronic devices)

[0799] Data processing device (server)

[0800] Generative AI Models

[0801] Hardware and Software

[0802] The hardware and software used are as follows:

[0803] Electronics: Smart glasses (e.g. Google Glass, Vuzix Blade)

[0804] Data processing equipment: Cloud server (e.g. AWS, Azure)

[0805] Generative AI model: GPT-3

[0806] Program processing flow

[0807] The system proceeds as follows:

[0808] 1. User Input

[0809] Users use the smart glasses to input legal questions, such as "What should I do if I have a suspicious person in my neighborhood?"

[0810] 2. Submit a question

[0811] Once the user enters a question, the smart glasses send it to the server using the secure HTTPS protocol.

[0812] 3. Question analysis

[0813] The server analyzes the received question and extracts important information (keywords), such as "suspicious person" and "how to deal with it."

[0814] 4. Legal information generation

[0815] The server queries a generative AI model (GPT-3) based on the extracted information to generate relevant legal information. The generative AI model then references an internal dataset to generate appropriate legal information for the user's question.

[0816] 5. Information Format

[0817] The server formats the generated legal information for the user, making it easier to read and adding relevant links and references where necessary.

[0818] 6. Answer display

[0819] The final formatted answer is sent to the user terminal and displayed to the user in real time through the smart glasses.

[0820] Specific examples

[0821] The user explains the question in a flow: "What should I do if my company doesn't pay me my overtime wages?" In this case, the smart glasses send the question to the server, which extracts keywords such as "overtime wages" and "not paid." The generative AI model generates information related to Article 37 of the Labor Standards Act, which the server formats and provides to the user. Finally, the smart glasses display the message: "According to Article 37 of the Labor Standards Act, overtime wages should be paid. We recommend that you consult with the Labor Standards Inspection Office for specific procedures."

[0822] Prompt Sentence Examples

[0823] Examples of prompts are:

[0824] text

[0825] What should I do if there are suspicious people in my neighborhood?

[0826] This allows users to consult on security-related legal issues in real time on the spot and quickly obtain appropriate countermeasures.

[0827] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0828] Step 1:

[0829] The user uses the smart glasses to input a legal question, which is stored in the smart glasses as text data. The input of this step is the text data entered by the user, and the output is the text data stored in the smart glasses.

[0830] Step 2:

[0831] The device (smart glasses) sends the entered question to the server using the secure HTTPS protocol. The input for this step is the question data in text format, and the output is the question data sent to the server as an HTTPS request.

[0832] Step 3:

[0833] The server analyzes the received question and extracts important information (keywords). For example, words such as "suspicious person" and "how to deal with it" are extracted. The input for this step is the text data sent in the HTTPS request, and the output is a list of extracted keywords.

[0834] Step 4:

[0835] The server uses a generative AI model (GPT-3) to generate relevant legal information based on the extracted keywords. The generative AI model references an internal dataset to provide appropriate legal information for a specific question. The input for this step is a list of keywords, and the output is the generated legal information text.

[0836] Step 5:

[0837] The server formats the generated legal information for the user, making it easier to read and adding relevant links and references as needed. The input to this step is the generated legal text and the output is the formatted answer text.

[0838] Step 6:

[0839] The server then sends the formatted response to the terminal, again using a secure communication protocol. The input to this step is the formatted response data, and the output is the response data sent to the terminal as an HTTPS response.

[0840] Step 7:

[0841] The terminal (smart glasses) displays the formatted answer received from the server to the user in real time. The user checks the answer through the smart glasses display and decides the next action. The input of this step is the formatted answer data received in the HTTPS response, and the output is the user's visual confirmation.

[0842] 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.

[0843] The present invention relates to a system in which a user inputs a legal question through a terminal, and a server provides appropriate legal information using a generative AI and an emotion engine. A specific example of the system is described below.

[0844] System Overview

[0845] The overall system consists of a user's device, a server, a generation AI, and an emotion engine. The user inputs a legal question using the device, which is then sent to the server. The server analyzes the question and generates appropriate legal information using the generation AI and emotion engine. The generated information is then formatted in an easy-to-understand format and provided to the user via the device.

[0846] Program processing overview

[0847] User Input

[0848] Users access the interface on their device (e.g., a smartphone or computer) and enter a legal question into a text box, such as "What should I do if my neighbors are making noise late at night?"

[0849] Submit a Question

[0850] When the user clicks the "Submit" button, the device sends the entered question to the server as an HTTP request. The communication is carried out using a secure protocol (e.g., HTTPS).

[0851] Question Analysis

[0852] The server receives the question in JSON format and starts a text analysis engine to analyze the received data.

[0853] Keyword extraction

[0854] The server's text analysis engine analyzes the question and extracts important keywords, such as "neighbors," "late night," "noise," and "how to deal with it."

[0855] Emotion Analysis

[0856] The server uses an emotion engine to analyze the user's emotional state from the input question. For example, emotions such as "confusion" or "anger" can be detected from the context of the question.

[0857] Legal information generation

[0858] The server passes the extracted keywords and the results of the sentiment analysis to the generation AI. The generation AI then uses its internal legal dataset to search for and generate appropriate legal information and past precedents for the user's question. For example, it may generate information such as, "Under Article 709 of the Civil Code, it is possible to claim compensation for noise pollution." Based on the results of the sentiment analysis, the information is generated in an appropriate tone.

[0859] Information Format

[0860] The generated legal information is then formatted for the user by the server, which formats the generated information in an easy-to-understand format and adds relevant links and references as needed, thereby providing information that takes into account the user's emotional state.

[0861] Show Answers

[0862] Finally, a formatted response is sent to the device and displayed to the user. For example, it may say, "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. Please see the link below for more information." The tone of the response is adjusted based on the results of sentiment analysis.

[0863] Specific examples

[0864] As a specific example, let's consider a case where a user inputs a question such as, "What should I do if my company doesn't pay my overtime wages?" and an emotion of anxiety is detected from the question. In this case, the device sends the question to the server, which extracts keywords such as "overtime wages" and "not paid." The emotion engine detects the user's emotion of anxiety and feeds the results back to the generation AI. The generation AI generates information related to the Labor Standards Act in a tone that alleviates anxiety. For example, it provides information such as, "According to Article 37 of the Labor Standards Act, overtime wages should be paid without fail. If you are worried, we recommend that you consult the Labor Standards Inspection Office."

[0865] As described above, the system of the present invention allows users to easily and quickly seek legal advice and obtain appropriate legal information, and furthermore, is capable of providing information that takes into consideration the user's feelings.

[0866] The processing flow will be explained below.

[0867] Step 1:

[0868] A user accesses the interface on their device and types a legal question into a text box, such as "What should I do if my neighbors are making noise late at night?"

[0869] Step 2:

[0870] When the user clicks the "Submit" button, the device sends the entered question to the server as an HTTP request. The communication is carried out using a secure protocol (e.g., HTTPS).

[0871] Step 3:

[0872] The server receives the question in JSON format and starts a text analysis engine to analyze the received data.

[0873] Step 4:

[0874] The server's text analysis engine analyzes the question and extracts important keywords, such as "neighbors," "late night," "noise," and "how to deal with it."

[0875] Step 5:

[0876] The server uses an emotion engine to analyze the user's emotional state from the input question. For example, emotions such as "confusion" or "anger" can be detected from the context of the question.

[0877] Step 6:

[0878] The server passes the extracted keywords and sentiment analysis results to the generation AI. The generation AI then uses its internal legal dataset to search for and generate appropriate legal information and past precedents for the user's question. For example, it generates information such as, "Under Article 709 of the Civil Code, it is possible to claim compensation for noise disturbances."

[0879] Step 7:

[0880] The emotion engine analyzes the user's emotional state and adjusts the tone of the generated legal information based on that state. For example, if the user is "confused," the information is presented in a more reassuring tone.

[0881] Step 8:

[0882] The server receives the legal information returned by the generation AI and formats it for the user. The server formats the generated information in an easy-to-understand format, adding relevant links and references as needed. The tone of the information is adjusted based on feedback from the emotion engine.

[0883] Step 9:

[0884] The server sends the formatted answer to the device as an HTTP response in JSON format, and the user's device receives the response.

[0885] Step 10:

[0886] The device displays the answer to the user. For example, the device displays information in a reassuring tone on the screen, such as, "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. If you have any questions, please refer to the link below."

[0887] As a specific example, let's consider a case where a user inputs a question such as "What should I do if my company doesn't pay my overtime wages?" and an emotion of anxiety is detected from the question. In this case, the device sends the question to the server. The server extracts keywords such as "overtime wages" and "not paid," and the emotion engine detects the user's emotion of anxiety. The results are fed back to the generation AI, which then generates information related to the Labor Standards Act in a tone that alleviates the anxiety. For example, the information provided may be something like, "According to Article 37 of the Labor Standards Act, overtime wages should be paid without fail. If you are worried, we recommend that you consult the Labor Standards Inspection Office."

[0888] The above are the specific processing steps of the system of the present invention that combines an emotion engine. This system allows users to easily receive legal advice that takes emotional considerations into account, and enables them to quickly obtain accurate and reliable legal information.

[0889] Example 2

[0890] 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."

[0891] Conventional legal consultation systems have difficulty providing appropriate legal information in response to user-entered questions, and are particularly unable to generate answers that take into account the user's emotional state. Furthermore, generating appropriate legal information requires manual search and legal knowledge, making it extremely difficult for non-experts. To solve this problem, a system was needed that could analyze the content of a user's question, extract important keywords, and automatically provide appropriate legal information.

[0892] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for analyzing the content of the question and extracting important keywords, a sentiment analysis means, and a means for generating relevant legal information using a generation AI. This makes it possible to provide prompt and appropriate legal information that takes into consideration the user's sentiments.

[0893] A "computing device" is an electronic device, such as a personal computer, smartphone, or tablet, that allows a user to connect to the Internet and input or receive data.

[0894] A "network" is a communications infrastructure for data communication, such as the Internet or an intranet.

[0895] A "server" is a computer system that can process data in response to a user's request via a network and return the results.

[0896] "Means for analyzing the question content and extracting important keywords" refers to the process of analyzing the text entered by the user using natural language processing technology to extract key words and phrases that clarify the subject and purpose of the question.

[0897] "Emotion analysis means" is a technology for analyzing emotions (anger, joy, sadness, etc.) contained in input text and understanding the user's emotional state.

[0898] "Generative AI" is an artificial intelligence system that automatically generates legal information appropriate to input keywords and context based on large amounts of legal data.

[0899] "User formatting" refers to the process of providing generated legal information in a format that is easy for users to understand, and providing relevant links and references where necessary.

[0900] "Means for adjusting tone" refers to technology that appropriately adjusts the wording and expression of generated responses based on the results of sentiment analysis.

[0901] A "secure communication protocol" is a protocol that prevents communication content from being eavesdropped on or tampered with by third parties, such as an encryption method such as HTTPS.

[0902] The present invention relates to a system in which a user inputs a legal question through a terminal, and a server provides appropriate legal information using a generative AI and an emotion engine. A specific example of this system is described below.

[0903] Overall system configuration

[0904] This system consists of a terminal, a server, a generation AI, and an emotion engine to respond quickly and appropriately to user questions. Users input legal questions using a computer device (e.g., a smartphone or PC), and the questions are sent to the server via a network. The server analyzes the content of the question, extracts important keywords, and then analyzes the user's emotional state using the emotion engine. The generation AI then generates appropriate legal information based on the extracted keywords and the results of the emotion analysis. The generated legal information is formatted by the server and ultimately provided to the user via the terminal.

[0905] User input and question submission

[0906] The user opens a web browser or other interface on their device and enters a legal question, such as "What should I do if my neighbors are making noise late at night?". When the user clicks the "Submit" button, the device securely sends the question to the server using the HTTPS protocol.

[0907] Question analysis and keyword extraction

[0908] The server receives the question in JSON format via HTTPS and first launches a text analysis engine to analyze the data. At this stage, the server's text analysis engine extracts important keywords from the question, such as "neighbors," "late night," "noise," and "how to respond."

[0909] Sentiment analysis and legal information generation

[0910] Next, the server uses an emotion engine to analyze the user's emotional state from the entered question. For example, emotions such as "confusion" or "anger" can be detected from the context of the question. The extracted keywords and the results of the emotion analysis are passed to the generation AI, which then searches for appropriate legal information and past precedents based on an internal legal dataset to generate an answer. For example, legal information such as "Under Article 709 of the Civil Code, it is possible to claim compensation for noise disturbances" is generated. At this time, the tone is also adjusted based on the results of the emotion analysis.

[0911] Formatting and Presenting Legal Information

[0912] The generated legal information is then formatted for the user by the server, making it easy to understand. In some cases, relevant links and references are also added. For example, the information might be something like, "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbors. Please see the link below for more information." Finally, the formatted answer is sent to the terminal and displayed on the user's device.

[0913] Specific examples

[0914] As a specific example, let's consider a case where a user inputs a question such as, "What should I do if my company doesn't pay my overtime wages?" and an emotion of anxiety is detected from the question. In this case, the device sends the question to the server, which extracts keywords such as "overtime wages" and "not paid." The emotion engine detects the user's emotion of anxiety and feeds the results back to the generation AI. The generation AI generates information related to the Labor Standards Act in a tone that alleviates anxiety. For example, it provides information such as, "According to Article 37 of the Labor Standards Act, overtime wages should be paid without fail. If you are concerned, we recommend that you consult the Labor Standards Inspection Office."

[0915] In this way, the system allows users to ask legal questions easily and quickly, and also provides information that takes into consideration the user's feelings.

[0916] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0917] Step 1: User enters question

[0918] A user uses a computing device (such as a smartphone or PC) to enter a legal question into the system's web interface. The question is entered in natural language and is specific, such as "What should I do if my neighbors are making noise late at night?" This input is stored in a data field and passed on to the next processing step.

[0919] Step 2: Send the question to the server

[0920] When the user clicks the "Submit" button, the device sends the entered question to the server as a secure HTTP POST request using the HTTPS protocol, with the data encoded in JSON format.

[0921] Step 3: The server receives and parses the query

[0922] The server parses the received HTTP POST request and extracts the JSON format data. Then, the server's built-in text analysis engine is activated and analyzes the grammatical structure of the question. Specifically, the question text is broken down into tokens and the main and subordinate sentences are identified through grammatical analysis.

[0923] Step 4: Extract keywords

[0924] The text analysis engine extracts important keywords from the analyzed sentences. For example, keywords such as "neighbor," "late night," "noise," and "how to deal with it" are extracted. The algorithm used for this is a natural language processing technique such as TF-IDF (Term Frequency-Inverse Document Frequency). The extracted keywords are passed on to the next processing step.

[0925] Step 5: Conduct sentiment analysis

[0926] The server then launches an emotion engine to analyze the emotional state of the input question. For example, it can detect emotions such as "confusion" or "anger" from the context of the text. Specifically, it uses a pre-trained emotion model to calculate an emotion score for the document and saves it as the analysis result.

[0927] Step 6: Pass legal information to the generative AI

[0928] The server passes the extracted keywords and sentiment analysis results to the generation AI as input. The generation AI then uses its internal legal dataset to search for legal information and past precedents related to the keywords and generates an answer to the question. For example, it might generate something like, "Under Article 709 of the Civil Code, it is possible to claim compensation for noise pollution."

[0929] Step 7: Format the generated legal information

[0930] The server formats the legal information output by the generative AI for the user, making the answer text easier to understand and adding relevant links and references. This process uses technologies such as template engines.

[0931] Step 8: Display the Answer to the User

[0932] The server then sends the formatted response back to the terminal and displays it on the user's computing device, for example, "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbors. Please see the link below for more information."

[0933] In this way, the system can properly parse the user's input and provide relevant legal information, as well as respond in a way that takes into account the user's emotional state.

[0934] (Application example 2)

[0935] 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."

[0936] Modern self-driving vehicles and their users often have questions and doubts about complex traffic laws. Furthermore, traffic laws often vary by region, making it difficult to obtain prompt and appropriate information. Furthermore, failure to respond appropriately to a user's questions can increase the user's anxiety and confusion. The present invention aims to address these issues and provide self-driving vehicle users with prompt and appropriate information about traffic laws.

[0937] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0938] In this invention, the server includes: means for a user to input a legal question using a terminal; means for the terminal to transmit the user's question to the server; means for the server to analyze the content of the question and extract important keywords; means for the server to generate relevant legal information using a generation AI based on the extracted keywords; means for the server to format the generated legal information for the user; means for the terminal to display the formatted answer to the user; means for analyzing the question about traffic laws and generating appropriate legal information; and means for analyzing the user's emotional state using an emotion engine to generate the legal information. This allows the user to quickly obtain accurate information about traffic laws even while using an autonomous vehicle, and further enables the information to be provided in a form that takes the user's emotional state into consideration.

[0939] A "terminal" is a device used by a user for input and display, and includes smartphones, tablets, personal computers, etc.

[0940] A "server" is a computer system that receives, analyzes, processes, and generates data entered by a user.

[0941] The "question content" is text information of a question or inquiry about a law or traffic regulation that is input by the user using the terminal.

[0942] "Generative AI" is an artificial intelligence engine that generates relevant legal information based on text data.

[0943] The "emotion engine" is an engine for analyzing the user's emotional state from the text information of the question entered by the user.

[0944] "Keywords" refer to important words and phrases extracted from the question content and are used for information generation by generative AI and analysis by emotion engines.

[0945] "Legal information" is data that includes specific legal information and guidelines regarding traffic laws.

[0946] "Formatting" is the process of arranging the generated legal and regulatory information into a form that is easy for users to understand.

[0947] "Emotional state" indicates the psychological state or feelings of the user when they input the question, and includes, for example, confusion, anger, anxiety, and the like.

[0948] The present invention relates to a system in which a user inputs questions about traffic regulations and other laws through a terminal, and a server provides appropriate legal information using a generative AI and an emotion engine. A specific example of the system is described below.

[0949] System Overview

[0950] The entire system consists of a user's device, a server, a generation AI, and an emotion engine. The user inputs a question about traffic laws using the device, and the question is sent to the server. The server analyzes the question and generates appropriate legal information using the generation AI and emotion engine. The generated information is then formatted in an easy-to-understand format and provided to the user via the device.

[0951] Specific program processing overview

[0952] 1. User Input

[0953] A user accesses the interface on their device (e.g., a smartphone or PC) and types a question about traffic laws into a text box, for example, "Is a U-turn legal in this area?"

[0954] 2. Submit your question

[0955] The user clicks the "Submit" button, and the device sends the entered question to the server as an HTTPS request.

[0956] 3. Question Analysis

[0957] The server receives the question in JSON format and launches a text analysis engine (e.g., spaCy or NLTK) to analyze the question.

[0958] 4. Keyword extraction

[0959] The server's text analysis engine analyzes the question and extracts important keywords, such as "area," "U-turn," and "legal."

[0960] 5. Emotion Analysis

[0961] The server uses an emotion engine (for example, Microsoft Azure's Text Analytics API) to analyze the user's emotional state from the entered question. For example, emotions such as "confusion" or "urgency" can be detected from the context of the question.

[0962] 6. Generating legal information

[0963] The server passes the extracted keywords and sentiment analysis results to a generation AI (for example, OpenAI's GPT-4). The generation AI uses its internal traffic law dataset to generate appropriate legal information in response to the user's question. For example, it generates information such as, "U-turns are prohibited in this area. Fines may be imposed." Based on the sentiment analysis results, the information is generated in an appropriate tone.

[0964] 7. Information Format

[0965] The generated legal information is then formatted for the user by the server, which formats the generated information into an easy-to-understand format and adds relevant links and references as needed, thereby providing information in a way that takes into account the user's emotional state.

[0966] 8. View Answers

[0967] Finally, a formatted response is sent to the device and displayed to the user, such as "According to local traffic laws, making a U-turn is illegal and may result in a fine." The tone of the response is adjusted based on the results of sentiment analysis.

[0968] Specific examples

[0969] As a specific example, let's consider a case where a user inputs the question, "Is a U-turn legal in this area?" and a confused emotion is detected from the question. In this case, the device sends the question to the server, which extracts keywords such as "area," "U-turn," and "legal." The emotion engine detects the user's confused emotion and feeds the result back to the generation AI. The generation AI generates information related to local traffic laws in a tone that will alleviate the user's confusion. For example, information is provided such as, "U-turns are prohibited in this area. Fines may be imposed. See the link below for details."

[0970] An example of a prompt to input to a generative AI model is as follows:

[0971] Keywords: local area, U-turn, legal

[0972] Emotion: Confused

[0973] Please provide information on relevant traffic laws.

[0974] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0975] Step 1:

[0976] User Input

[0977] A user uses a device (smartphone or PC) to enter a question about traffic laws into a text box. The question (e.g., "Is a U-turn legal in this area?") is captured within the application and prepared for passing to the next processing step.

[0978] Step 2:

[0979] Submit a Question

[0980] When the user clicks the "Submit" button, the device sends the entered question to the server as an HTTPS request, and the data is serialized in JSON format and sent to the server via a secure communication protocol.

[0981] Step 3:

[0982] Question Analysis

[0983] The server deserializes the received question in JSON format. Next, it invokes a text analysis engine (e.g., spaCy or NLTK) to analyze the question and extract important keywords. Keywords such as "area," "U-turn," and "legal" are extracted from the input question text.

[0984] Step 4:

[0985] Emotion Analysis

[0986] The server uses an emotion engine (for example, Microsoft Azure's Text Analytics API) to analyze the user's emotional state from the received question. As a result of the analysis, emotions such as "confusion" or "urgency" are output based on the context of the question.

[0987] Step 5:

[0988] Generating legal information using generative AI

[0989] The server converts the extracted keywords and sentiment analysis results into prompt format and passes them to a generation AI (e.g., OpenAI's GPT-4). The generation AI generates appropriate legal information based on an internal traffic law dataset. The output information might be something like, "U-turns are prohibited in this area. Fines may be imposed."

[0990] Step 6:

[0991] Information Format

[0992] The server receives the legal information output by the generation AI and formats it for the user, formatting the information in a way that is easy for the user to understand and adding related links and references as needed.

[0993] Step 7:

[0994] Show Answers

[0995] The formatted answer is then serialized back into JSON and sent over HTTPS to the user's device, where it is deserialized and displayed in a user-friendly format, such as "According to local traffic laws, U-turns are illegal and may result in fines."

[0996] 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.

[0997] 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.

[0998] 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.

[0999] [Fourth embodiment]

[1000] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1001] 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.

[1002] 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).

[1003] 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.

[1004] 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.

[1005] 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).

[1006] 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.

[1007] 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.

[1008] 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.

[1009] 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.

[1010] 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.

[1011] 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.

[1012] 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."

[1013] The present invention relates to a system in which a user inputs legal questions via a terminal, and a server provides appropriate legal information using a generation AI. A specific example of the system is described below.

[1014] System Overview

[1015] The overall system consists of a user's device, a server, and a generation AI. The user inputs a legal question using the device, which is then sent to the server. The server analyzes the question and generates appropriate legal information using the generation AI. The generated information is then formatted in an easy-to-understand format and provided to the user via the device.

[1016] Program processing overview

[1017] User Input

[1018] Users access the interface on their device (e.g., a smartphone or PC) and enter a legal question into a text box, such as "What should I do if my neighbors are making noise late at night?"

[1019] Submit a Question

[1020] When the user clicks the "Submit" button, the device sends the entered question to the server as an HTTP request. The communication is carried out using a secure protocol (e.g., HTTPS).

[1021] Question Analysis

[1022] The server analyzes the received question and extracts important keywords, such as "neighbor," "late night," "noise," and "how to respond," which are used for subsequent processing.

[1023] Legal information generation

[1024] The server passes the extracted keywords to the generation AI, which uses its internal legal dataset to search for and generate appropriate legal information and past precedents for the user's question. For example, it generates information such as "Under Article 709 of the Civil Code, it is possible to claim compensation for noise disturbances."

[1025] Information Format

[1026] The generated legal information is then formatted for the user by the server, which formats the information in an easy-to-understand format and adds relevant links and references as needed.

[1027] Show Answers

[1028] Finally, a formatted response is sent to the device and displayed to the user, such as "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. Please see the link below for more information."

[1029] Specific examples

[1030] As a specific example, let's consider the case where a user inputs the question, "What should I do if my company doesn't pay me my overtime wages?" In this case, the device sends the question to the server, which extracts keywords such as "overtime wages" and "not paid." The generation AI generates information related to the Labor Standards Act, which the server then formats appropriately and provides to the user. Finally, the user's device displays the following message: "According to Article 37 of the Labor Standards Act, overtime wages should be paid. We recommend that you consult with the Labor Standards Inspection Office as a specific procedure."

[1031] As described above, the system of the present invention provides an efficient method for users to easily and quickly obtain legal advice and appropriate legal information.

[1032] The processing flow will be explained below.

[1033] Step 1:

[1034] A user accesses the interface on their device and types a legal question into a text box, such as "What should I do if my neighbors are making noise late at night?"

[1035] Step 2:

[1036] When the user clicks the "Submit" button, the device sends the entered question to the server as an HTTP request. The communication is carried out using a secure protocol (e.g., HTTPS).

[1037] Step 3:

[1038] The server receives the question in JSON format and starts a text analysis engine to analyze the received data.

[1039] Step 4:

[1040] The server's text analysis engine analyzes the question and extracts important keywords, such as "neighbors," "late night," "noise," and "how to deal with it."

[1041] Step 5:

[1042] The server passes the extracted keywords to the generation AI, which uses its internal legal dataset to search for the most relevant legal information and past precedents and generate appropriate legal information. For example, it generates information such as, "Under Article 709 of the Civil Code, it is possible to claim compensation for noise disturbances."

[1043] Step 6:

[1044] The server receives the legal information returned by the generation AI and formats it for the user. The server formats the generated information in an easy-to-understand format, adding relevant links and references as needed.

[1045] Step 7:

[1046] The server sends the formatted answer to the device as an HTTP response in JSON format, and the user's device receives the response.

[1047] Step 8:

[1048] The device displays the answer to the user. For example, information is displayed on the device screen in the form of "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. Please refer to the link below for more information."

[1049] The above is a series of steps for processing legal questions from users. This flow is important for the system as a whole to respond quickly and accurately to user questions.

[1050] Example 1

[1051] 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."

[1052] In modern society, many people have legal problems and questions, but accessing legal experts is time-consuming. Furthermore, information on the Internet is often unreliable, making it difficult to quickly obtain accurate legal information. To address these issues, a system is needed that allows users to easily obtain reliable legal information.

[1053] 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.

[1054] In this invention, the server includes: a means for a user to input a legal question; a means for a terminal to transmit the user's question to the server using a secure communication protocol; a means for the server to analyze the received question using a natural language processing algorithm and extract important keywords; a means for the server to pass a prompt sentence for generating related legal information using a generation AI based on the extracted keywords; a means for the server to format the generated legal information for the user; a means for the server to add related links and reference materials to the generated legal information; and a means for the terminal to display the formatted answer to the user. This allows the user to easily and quickly obtain reliable legal information.

[1055] "User" means any person or entity that uses the System to enter legal questions and receive answers.

[1056] "Terminal" refers to an electronic device used by a user for input and display. Specifically, it includes smartphones, personal computers, tablets, etc.

[1057] "Server" refers to the central computer that receives, analyzes, processes, and generates answers to user questions.

[1058] "Question content" refers to text data of legal questions or inquiries entered by the user using the terminal.

[1059] A "secure communication protocol" refers to a communication method that prevents unauthorized access by third parties when sending and receiving data. Specifically, HTTPS is one example.

[1060] "Natural language processing algorithm" refers to a technical means for analyzing human language and extracting information.

[1061] "Keywords" refer to words and phrases extracted from the query that are important for generating legal information.

[1062] "Generative AI" refers to a model that uses artificial intelligence technology to generate relevant legal information based on a given prompt.

[1063] "Prompt sentence" refers to the input sentence that the generative AI uses to generate an appropriate response.

[1064] "Format" refers to the means by which the generated legal information is arranged in a form that is easy for users to understand.

[1065] "Reference links and additional resources" refers to supplementary information provided to help users understand more.

[1066] "Answer" refers to the legal information generated by the AI ​​in response to a user's question and formatted and provided by the server.

[1067] The present invention is a system in which a user inputs a legal question through a terminal, and a server provides appropriate legal information using a generation AI. This system is composed of a user's terminal, a server, and a generation AI. Specific embodiments of the system are described in detail below.

[1068] System Overview

[1069] A user accesses the interface on their device (e.g., a smartphone or PC) and enters a legal question into a text box. For example, they can enter a question such as, "What should I do if my neighbors are making noise late at night?" After entering the question, the user clicks the "Submit" button, and the device sends the entered question to the server using the HTTPS protocol. This communication uses a secure protocol, so the data is encrypted before being sent.

[1070] The server uses a natural language processing (NLP) algorithm to analyze the received question. This algorithm extracts important keywords from the question, such as "neighbors," "late night," "noise," and "how to respond." The server then passes the extracted keywords to the generation AI. The generation AI model generates appropriate legal information for the user's question based on its internal legal dataset and past case law. The following prompt is used for the generation AI:

[1071] Please provide relevant legal information in response to the question, "What should I do if my neighbor is making noise late at night?"

[1072] The generated legal information might include, for example, "Under Article 709 of the Civil Code, it is possible to claim compensation for noise."

[1073] The server formats the generated legal information in a way that is easy for the user to understand. The server formats the information and inserts relevant links and additional references as needed. Finally, the formatted answer is sent to the device and displayed in the user's browser. For example, it might look something like this:

[1074] According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. Please refer to the link below for more information.

[1075] This system allows users to quickly obtain reliable legal information. Specifically, let's consider the case where a user inputs a question such as, "What should I do if my company doesn't pay me my overtime wages?" In this case, the device sends the question to the server, which extracts keywords such as "overtime wages" and "not paid." The generation AI generates information related to the Labor Standards Act, which the server then formats appropriately and provides to the user. Finally, the user's device displays the following message: "According to Article 37 of the Labor Standards Act, overtime wages should be paid. We recommend that you consult with the Labor Standards Inspection Office for specific procedures."

[1076] Thus, the system of the present invention provides an efficient method for users to easily and quickly obtain legal advice and appropriate legal information.

[1077] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1078] Step 1:

[1079] The user uses a terminal to enter a legal question. For example, the user types "What should I do if my neighbors are making noise late at night?" into a text box. This is done using the system's web interface.

[1080] Input: The question text entered by the user

[1081] Output: None (user input is temporarily stored in a database or memory)

[1082] Step 2:

[1083] When the user clicks the "Submit" button, the device sends the question to the server using the HTTPS protocol, where the device validates the input and ensures that the question is in the correct format.

[1084] Input: The question text entered by the user and validated

[1085] Output: Question as HTTPS request

[1086] Step 3:

[1087] The server uses a natural language processing (NLP) algorithm to analyze the received question. The server extracts important keywords from the question. In this step, keywords such as "neighbors," "late night," "noise," and "how to deal with it" are extracted.

[1088] Input: Question text sent to the server

[1089] Output: List of extracted keywords (e.g., "neighbor," "late night," "noise," "how to respond")

[1090] Step 4:

[1091] The server passes the extracted keywords to the generation AI model. The server then creates a prompt for the generation AI, and generates legal information based on this prompt. For example, the prompt passed to the generation AI is as follows:

[1092] Please provide relevant legal information in response to the question, "What should I do if my neighbor is making noise late at night?"

[1093] Input: Extracted keyword list, generated prompt sentence

[1094] Output: Legal information generated by the AI ​​(e.g., "Article 709 of the Civil Code allows for the claim of compensation for noise pollution.")

[1095] Step 5:

[1096] The server formats the generated legal information in a user-friendly format. The server formats the information and inserts relevant links and additional references as needed.

[1097] Input: Legal information generated by the generative AI

[1098] Output: Formatted legal information (e.g., "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. Please see the link below for more information.")

[1099] Step 6:

[1100] Finally, the server sends the formatted response to the device, which displays the received information in the user's web browser.

[1101] Input: Formatted legal information

[1102] Output: The final answer that is displayed in the user's browser

[1103] Through the above specific processing steps, users can efficiently obtain reliable legal information.

[1104] (Application example 1)

[1105] 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."

[1106] In conventional legal consultation systems, it has been difficult for users to receive prompt and accurate legal information in real time when asking legal questions. Furthermore, users have been unable to immediately consult about security-related legal issues and obtain appropriate solutions, significantly impairing user convenience. The present invention aims to solve these problems by providing a system that allows users to consult about security-related legal issues in real time and quickly provides accurate legal information.

[1107] 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.

[1108] In this invention, the server includes means for a user to input a legal question using an electronic device, means for the electronic device to transmit the user's question to a data processing device, means for the data processing device to analyze the content of the question and extract important information, means for the data processing device to generate relevant legal information using a generation AI based on the extracted information, means for the data processing device to format the generated legal information for the user, means for the electronic device to display the formatted answer to the user, and means for the electronic device to display the legal information in real time. This allows users to quickly and accurately consult on legal issues related to security on the spot and learn appropriate responses in real time.

[1109] "User" means a person who uses the system to enter legal questions and obtain answers.

[1110] "Electronics" refers to the terminal where the user inputs, sends questions, and displays answers.

[1111] A "legal question" is a question posed to the system by a user regarding laws, regulations, or legal issues.

[1112] A "data processing device" is a computer system that analyzes a user's question, generates legal information using generative AI, and provides a formatted answer.

[1113] "Question content" refers to the text of a legal inquiry entered by a user through an electronic device.

[1114] "Important information" refers to keywords and themes extracted from the user's question for generating legal information.

[1115] "Generative AI" refers to an artificial intelligence model that generates relevant information based on input data.

[1116] "Legal information" refers to laws, precedents, and advice provided in response to users' questions.

[1117] "Formatting" refers to arranging the generated legal information in a form that is easy for the user to view and understand.

[1118] An "answer" is legal information that the system generates in response to a question and provides to the user.

[1119] "Real time" refers to near-instant processing and response.

[1120] This invention is a system that allows users to receive real-time consultations on legal issues related to security. Specifically, users input questions using electronic devices, and a data processing device analyzes and answers the questions.

[1121] System Configuration

[1122] The system consists of the following main components:

[1123] User terminals (electronic devices)

[1124] Data processing device (server)

[1125] Generative AI Models

[1126] Hardware and Software

[1127] The hardware and software used are as follows:

[1128] Electronics: Smart glasses (e.g. Google Glass, Vuzix Blade)

[1129] Data processing equipment: Cloud server (e.g. AWS, Azure)

[1130] Generative AI model: GPT-3

[1131] Program processing flow

[1132] The system proceeds as follows:

[1133] 1. User Input

[1134] Users use the smart glasses to input legal questions, such as "What should I do if I have a suspicious person in my neighborhood?"

[1135] 2. Submit a question

[1136] Once the user enters a question, the smart glasses send it to the server using the secure HTTPS protocol.

[1137] 3. Question analysis

[1138] The server analyzes the received question and extracts important information (keywords), such as "suspicious person" and "how to deal with it."

[1139] 4. Legal information generation

[1140] The server queries a generative AI model (GPT-3) based on the extracted information to generate relevant legal information. The generative AI model then references an internal dataset to generate appropriate legal information for the user's question.

[1141] 5. Information Format

[1142] The server formats the generated legal information for the user, making it easier to read and adding relevant links and references where necessary.

[1143] 6. Answer display

[1144] The final formatted answer is sent to the user terminal and displayed to the user in real time through the smart glasses.

[1145] Specific examples

[1146] The user explains the question in a flow: "What should I do if my company doesn't pay me my overtime wages?" In this case, the smart glasses send the question to the server, which extracts keywords such as "overtime wages" and "not paid." The generative AI model generates information related to Article 37 of the Labor Standards Act, which the server formats and provides to the user. Finally, the smart glasses display the message: "According to Article 37 of the Labor Standards Act, overtime wages should be paid. We recommend that you consult with the Labor Standards Inspection Office for specific procedures."

[1147] Prompt Sentence Examples

[1148] Examples of prompts are:

[1149] text

[1150] What should I do if there are suspicious people in my neighborhood?

[1151] This allows users to consult on security-related legal issues in real time on the spot and quickly obtain appropriate countermeasures.

[1152] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1153] Step 1:

[1154] The user uses the smart glasses to input a legal question, which is stored in the smart glasses as text data. The input of this step is the text data entered by the user, and the output is the text data stored in the smart glasses.

[1155] Step 2:

[1156] The device (smart glasses) sends the entered question to the server using the secure HTTPS protocol. The input for this step is the question data in text format, and the output is the question data sent to the server as an HTTPS request.

[1157] Step 3:

[1158] The server analyzes the received question and extracts important information (keywords). For example, words such as "suspicious person" and "how to deal with it" are extracted. The input for this step is the text data sent in the HTTPS request, and the output is a list of extracted keywords.

[1159] Step 4:

[1160] The server uses a generative AI model (GPT-3) to generate relevant legal information based on the extracted keywords. The generative AI model references an internal dataset to provide appropriate legal information for a specific question. The input for this step is a list of keywords, and the output is the generated legal information text.

[1161] Step 5:

[1162] The server formats the generated legal information for the user, making it easier to read and adding relevant links and references as needed. The input to this step is the generated legal text and the output is the formatted answer text.

[1163] Step 6:

[1164] The server then sends the formatted response to the terminal, again using a secure communication protocol. The input to this step is the formatted response data, and the output is the response data sent to the terminal as an HTTPS response.

[1165] Step 7:

[1166] The terminal (smart glasses) displays the formatted answer received from the server to the user in real time. The user checks the answer through the smart glasses display and decides the next action. The input of this step is the formatted answer data received in the HTTPS response, and the output is the user's visual confirmation.

[1167] 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.

[1168] The present invention relates to a system in which a user inputs a legal question through a terminal, and a server provides appropriate legal information using a generative AI and an emotion engine. A specific example of the system is described below.

[1169] System Overview

[1170] The overall system consists of a user's device, a server, a generation AI, and an emotion engine. The user inputs a legal question using the device, which is then sent to the server. The server analyzes the question and generates appropriate legal information using the generation AI and emotion engine. The generated information is then formatted in an easy-to-understand format and provided to the user via the device.

[1171] Program processing overview

[1172] User Input

[1173] Users access the interface on their device (e.g., a smartphone or computer) and enter a legal question into a text box, such as "What should I do if my neighbors are making noise late at night?"

[1174] Submit a Question

[1175] When the user clicks the "Submit" button, the device sends the entered question to the server as an HTTP request. The communication is carried out using a secure protocol (e.g., HTTPS).

[1176] Question Analysis

[1177] The server receives the question in JSON format and starts a text analysis engine to analyze the received data.

[1178] Keyword extraction

[1179] The server's text analysis engine analyzes the question and extracts important keywords, such as "neighbors," "late night," "noise," and "how to deal with it."

[1180] Emotion Analysis

[1181] The server uses an emotion engine to analyze the user's emotional state from the input question. For example, emotions such as "confusion" or "anger" can be detected from the context of the question.

[1182] Legal information generation

[1183] The server passes the extracted keywords and the results of the sentiment analysis to the generation AI. The generation AI then uses its internal legal dataset to search for and generate appropriate legal information and past precedents for the user's question. For example, it may generate information such as, "Under Article 709 of the Civil Code, it is possible to claim compensation for noise pollution." Based on the results of the sentiment analysis, the information is generated in an appropriate tone.

[1184] Information Format

[1185] The generated legal information is then formatted for the user by the server, which formats the generated information in an easy-to-understand format and adds relevant links and references as needed, thereby providing information that takes into account the user's emotional state.

[1186] Show Answers

[1187] Finally, a formatted response is sent to the device and displayed to the user. For example, it may say, "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. Please see the link below for more information." The tone of the response is adjusted based on the results of sentiment analysis.

[1188] Specific examples

[1189] As a specific example, let's consider a case where a user inputs a question such as, "What should I do if my company doesn't pay my overtime wages?" and an emotion of anxiety is detected from the question. In this case, the device sends the question to the server, which extracts keywords such as "overtime wages" and "not paid." The emotion engine detects the user's emotion of anxiety and feeds the results back to the generation AI. The generation AI generates information related to the Labor Standards Act in a tone that alleviates anxiety. For example, it provides information such as, "According to Article 37 of the Labor Standards Act, overtime wages should be paid without fail. If you are worried, we recommend that you consult the Labor Standards Inspection Office."

[1190] As described above, the system of the present invention allows users to easily and quickly seek legal advice and obtain appropriate legal information, and furthermore, is capable of providing information that takes into consideration the user's feelings.

[1191] The processing flow will be explained below.

[1192] Step 1:

[1193] A user accesses the interface on their device and types a legal question into a text box, such as "What should I do if my neighbors are making noise late at night?"

[1194] Step 2:

[1195] When the user clicks the "Submit" button, the device sends the entered question to the server as an HTTP request. The communication is carried out using a secure protocol (e.g., HTTPS).

[1196] Step 3:

[1197] The server receives the question in JSON format and starts a text analysis engine to analyze the received data.

[1198] Step 4:

[1199] The server's text analysis engine analyzes the question and extracts important keywords, such as "neighbors," "late night," "noise," and "how to deal with it."

[1200] Step 5:

[1201] The server uses an emotion engine to analyze the user's emotional state from the input question. For example, emotions such as "confusion" or "anger" can be detected from the context of the question.

[1202] Step 6:

[1203] The server passes the extracted keywords and sentiment analysis results to the generation AI. The generation AI then uses its internal legal dataset to search for and generate appropriate legal information and past precedents for the user's question. For example, it generates information such as, "Under Article 709 of the Civil Code, it is possible to claim compensation for noise disturbances."

[1204] Step 7:

[1205] The emotion engine analyzes the user's emotional state and adjusts the tone of the generated legal information based on that state. For example, if the user is "confused," the information is presented in a more reassuring tone.

[1206] Step 8:

[1207] The server receives the legal information returned by the generation AI and formats it for the user. The server formats the generated information in an easy-to-understand format, adding relevant links and references as needed. The tone of the information is adjusted based on feedback from the emotion engine.

[1208] Step 9:

[1209] The server sends the formatted answer to the device as an HTTP response in JSON format, and the user's device receives the response.

[1210] Step 10:

[1211] The device displays the answer to the user. For example, the device displays information in a reassuring tone on the screen, such as, "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbor. If you have any questions, please refer to the link below."

[1212] As a specific example, let's consider a case where a user inputs a question such as "What should I do if my company doesn't pay my overtime wages?" and an emotion of anxiety is detected from the question. In this case, the device sends the question to the server. The server extracts keywords such as "overtime wages" and "not paid," and the emotion engine detects the user's emotion of anxiety. The results are fed back to the generation AI, which then generates information related to the Labor Standards Act in a tone that alleviates the anxiety. For example, the information provided may be something like, "According to Article 37 of the Labor Standards Act, overtime wages should be paid without fail. If you are worried, we recommend that you consult the Labor Standards Inspection Office."

[1213] The above are the specific processing steps of the system of the present invention that combines an emotion engine. This system allows users to easily receive legal advice that takes emotional considerations into account, and enables them to quickly obtain accurate and reliable legal information.

[1214] Example 2

[1215] 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."

[1216] Conventional legal consultation systems have difficulty providing appropriate legal information in response to user-entered questions, and are particularly unable to generate answers that take into account the user's emotional state. Furthermore, generating appropriate legal information requires manual search and legal knowledge, making it extremely difficult for non-experts. To solve this problem, a system was needed that could analyze the content of a user's question, extract important keywords, and automatically provide appropriate legal information.

[1217] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for analyzing the content of the question and extracting important keywords, a sentiment analysis means, and a means for generating relevant legal information using a generation AI. This makes it possible to provide prompt and appropriate legal information that takes into consideration the user's sentiments.

[1218] A "computing device" is an electronic device, such as a personal computer, smartphone, or tablet, that allows a user to connect to the Internet and input or receive data.

[1219] A "network" is a communications infrastructure for data communication, such as the Internet or an intranet.

[1220] A "server" is a computer system that can process data in response to a user's request via a network and return the results.

[1221] "Means for analyzing the question content and extracting important keywords" refers to the process of analyzing the text entered by the user using natural language processing technology to extract key words and phrases that clarify the subject and purpose of the question.

[1222] "Emotion analysis means" is a technology for analyzing emotions (anger, joy, sadness, etc.) contained in input text and understanding the user's emotional state.

[1223] "Generative AI" is an artificial intelligence system that automatically generates legal information appropriate to input keywords and context based on large amounts of legal data.

[1224] "User formatting" refers to the process of providing generated legal information in a format that is easy for users to understand, and providing relevant links and references where necessary.

[1225] "Means for adjusting tone" refers to technology that appropriately adjusts the wording and expression of generated responses based on the results of sentiment analysis.

[1226] A "secure communication protocol" is a protocol that prevents communication content from being eavesdropped on or tampered with by third parties, such as an encryption method such as HTTPS.

[1227] The present invention relates to a system in which a user inputs a legal question through a terminal, and a server provides appropriate legal information using a generative AI and an emotion engine. A specific example of this system is described below.

[1228] Overall system configuration

[1229] This system consists of a terminal, a server, a generation AI, and an emotion engine to respond quickly and appropriately to user questions. Users input legal questions using a computer device (e.g., a smartphone or PC), and the questions are sent to the server via a network. The server analyzes the content of the question, extracts important keywords, and then analyzes the user's emotional state using the emotion engine. The generation AI then generates appropriate legal information based on the extracted keywords and the results of the emotion analysis. The generated legal information is formatted by the server and ultimately provided to the user via the terminal.

[1230] User input and question submission

[1231] The user opens a web browser or other interface on their device and enters a legal question, such as "What should I do if my neighbors are making noise late at night?". When the user clicks the "Submit" button, the device securely sends the question to the server using the HTTPS protocol.

[1232] Question analysis and keyword extraction

[1233] The server receives the question in JSON format via HTTPS and first launches a text analysis engine to analyze the data. At this stage, the server's text analysis engine extracts important keywords from the question, such as "neighbors," "late night," "noise," and "how to respond."

[1234] Sentiment analysis and legal information generation

[1235] Next, the server uses an emotion engine to analyze the user's emotional state from the entered question. For example, emotions such as "confusion" or "anger" can be detected from the context of the question. The extracted keywords and the results of the emotion analysis are passed to the generation AI, which then searches for appropriate legal information and past precedents based on an internal legal dataset to generate an answer. For example, legal information such as "Under Article 709 of the Civil Code, it is possible to claim compensation for noise disturbances" is generated. At this time, the tone is also adjusted based on the results of the emotion analysis.

[1236] Formatting and Presenting Legal Information

[1237] The generated legal information is then formatted for the user by the server, making it easy to understand. In some cases, relevant links and references are also added. For example, the information might be something like, "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbors. Please see the link below for more information." Finally, the formatted answer is sent to the terminal and displayed on the user's device.

[1238] Specific examples

[1239] As a specific example, let's consider a case where a user inputs a question such as, "What should I do if my company doesn't pay my overtime wages?" and an emotion of anxiety is detected from the question. In this case, the device sends the question to the server, which extracts keywords such as "overtime wages" and "not paid." The emotion engine detects the user's emotion of anxiety and feeds the results back to the generation AI. The generation AI generates information related to the Labor Standards Act in a tone that alleviates anxiety. For example, it provides information such as, "According to Article 37 of the Labor Standards Act, overtime wages should be paid without fail. If you are concerned, we recommend that you consult the Labor Standards Inspection Office."

[1240] In this way, the system allows users to ask legal questions easily and quickly, and also provides information that takes into consideration the user's feelings.

[1241] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1242] Step 1: User enters question

[1243] A user uses a computing device (such as a smartphone or PC) to enter a legal question into the system's web interface. The question is entered in natural language and is specific, such as "What should I do if my neighbors are making noise late at night?" This input is stored in a data field and passed on to the next processing step.

[1244] Step 2: Send the question to the server

[1245] When the user clicks the "Submit" button, the device sends the entered question to the server as a secure HTTP POST request using the HTTPS protocol, with the data encoded in JSON format.

[1246] Step 3: The server receives and parses the query

[1247] The server parses the received HTTP POST request and extracts the JSON format data. Then, the server's built-in text analysis engine is activated and analyzes the grammatical structure of the question. Specifically, the question text is broken down into tokens and the main and subordinate sentences are identified through grammatical analysis.

[1248] Step 4: Extract keywords

[1249] The text analysis engine extracts important keywords from the analyzed sentences. For example, keywords such as "neighbor," "late night," "noise," and "how to deal with it" are extracted. The algorithm used for this is a natural language processing technique such as TF-IDF (Term Frequency-Inverse Document Frequency). The extracted keywords are passed on to the next processing step.

[1250] Step 5: Conduct sentiment analysis

[1251] The server then launches an emotion engine to analyze the emotional state of the input question. For example, it can detect emotions such as "confusion" or "anger" from the context of the text. Specifically, it uses a pre-trained emotion model to calculate an emotion score for the document and saves it as the analysis result.

[1252] Step 6: Pass legal information to the generative AI

[1253] The server passes the extracted keywords and sentiment analysis results to the generation AI as input. The generation AI then uses its internal legal dataset to search for legal information and past precedents related to the keywords and generates an answer to the question. For example, it might generate something like, "Under Article 709 of the Civil Code, it is possible to claim compensation for noise pollution."

[1254] Step 7: Format the generated legal information

[1255] The server formats the legal information output by the generative AI for the user, making the answer text easier to understand and adding relevant links and references. This process uses technologies such as template engines.

[1256] Step 8: Display the Answer to the User

[1257] The server then sends the formatted response back to the terminal and displays it on the user's computing device, for example, "According to Article 709 of the Japanese Civil Code, you can claim compensation for noise problems caused by your neighbors. Please see the link below for more information."

[1258] In this way, the system can properly parse the user's input and provide relevant legal information, as well as respond in a way that takes into account the user's emotional state.

[1259] (Application example 2)

[1260] 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."

[1261] Modern self-driving vehicles and their users often have questions and doubts about complex traffic laws. Furthermore, traffic laws often vary by region, making it difficult to obtain prompt and appropriate information. Furthermore, failure to respond appropriately to a user's questions can increase the user's anxiety and confusion. The present invention aims to address these issues and provide self-driving vehicle users with prompt and appropriate information about traffic laws.

[1262] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1263] In this invention, the server includes: means for a user to input a legal question using a terminal; means for the terminal to transmit the user's question to the server; means for the server to analyze the content of the question and extract important keywords; means for the server to generate relevant legal information using a generation AI based on the extracted keywords; means for the server to format the generated legal information for the user; means for the terminal to display the formatted answer to the user; means for analyzing the question about traffic laws and generating appropriate legal information; and means for analyzing the user's emotional state using an emotion engine to generate the legal information. This allows the user to quickly obtain accurate information about traffic laws even while using an autonomous vehicle, and further enables the information to be provided in a form that takes the user's emotional state into consideration.

[1264] A "terminal" is a device used by a user for input and display, and includes smartphones, tablets, personal computers, etc.

[1265] A "server" is a computer system that receives, analyzes, processes, and generates data entered by a user.

[1266] The "question content" is text information of a question or inquiry about a law or traffic regulation that is input by the user using the terminal.

[1267] "Generative AI" is an artificial intelligence engine that generates relevant legal information based on text data.

[1268] The "emotion engine" is an engine for analyzing the user's emotional state from the text information of the question entered by the user.

[1269] "Keywords" refer to important words and phrases extracted from the question content and are used for information generation by generative AI and analysis by emotion engines.

[1270] "Legal information" is data that includes specific legal information and guidelines regarding traffic laws.

[1271] "Formatting" is the process of arranging the generated legal and regulatory information into a form that is easy for users to understand.

[1272] "Emotional state" indicates the psychological state or feelings of the user when they input the question, and includes, for example, confusion, anger, anxiety, and the like.

[1273] The present invention relates to a system in which a user inputs questions about traffic regulations and other laws through a terminal, and a server provides appropriate legal information using a generative AI and an emotion engine. A specific example of the system is described below.

[1274] System Overview

[1275] The entire system consists of a user's device, a server, a generation AI, and an emotion engine. The user inputs a question about traffic laws using the device, and the question is sent to the server. The server analyzes the question and generates appropriate legal information using the generation AI and emotion engine. The generated information is then formatted in an easy-to-understand format and provided to the user via the device.

[1276] Specific program processing overview

[1277] 1. User Input

[1278] A user accesses the interface on their device (e.g., a smartphone or PC) and types a question about traffic laws into a text box, for example, "Is a U-turn legal in this area?"

[1279] 2. Submit your question

[1280] The user clicks the "Submit" button, and the device sends the entered question to the server as an HTTPS request.

[1281] 3. Question Analysis

[1282] The server receives the question in JSON format and launches a text analysis engine (e.g., spaCy or NLTK) to analyze the question.

[1283] 4. Keyword extraction

[1284] The server's text analysis engine analyzes the question and extracts important keywords, such as "area," "U-turn," and "legal."

[1285] 5. Emotion Analysis

[1286] The server uses an emotion engine (for example, Microsoft Azure's Text Analytics API) to analyze the user's emotional state from the entered question. For example, emotions such as "confusion" or "urgency" can be detected from the context of the question.

[1287] 6. Generating legal information

[1288] The server passes the extracted keywords and sentiment analysis results to a generation AI (for example, OpenAI's GPT-4). The generation AI uses its internal traffic law dataset to generate appropriate legal information in response to the user's question. For example, it generates information such as, "U-turns are prohibited in this area. Fines may be imposed." Based on the sentiment analysis results, the information is generated in an appropriate tone.

[1289] 7. Information Format

[1290] The generated legal information is then formatted for the user by the server, which formats the generated information into an easy-to-understand format and adds relevant links and references as needed, thereby providing information in a way that takes into account the user's emotional state.

[1291] 8. View Answers

[1292] Finally, a formatted response is sent to the device and displayed to the user, such as "According to local traffic laws, making a U-turn is illegal and may result in a fine." The tone of the response is adjusted based on the results of sentiment analysis.

[1293] Specific examples

[1294] As a specific example, let's consider a case where a user inputs the question, "Is a U-turn legal in this area?" and a confused emotion is detected from the question. In this case, the device sends the question to the server, which extracts keywords such as "area," "U-turn," and "legal." The emotion engine detects the user's confused emotion and feeds the result back to the generation AI. The generation AI generates information related to local traffic laws in a tone that will alleviate the user's confusion. For example, information is provided such as, "U-turns are prohibited in this area. Fines may be imposed. See the link below for details."

[1295] An example of a prompt to input to a generative AI model is as follows:

[1296] Keywords: local area, U-turn, legal

[1297] Emotion: Confused

[1298] Please provide information on relevant traffic laws.

[1299] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1300] Step 1:

[1301] User Input

[1302] A user uses a device (smartphone or PC) to enter a question about traffic laws into a text box. The question (e.g., "Is a U-turn legal in this area?") is captured within the application and prepared for passing to the next processing step.

[1303] Step 2:

[1304] Submit a Question

[1305] When the user clicks the "Submit" button, the device sends the entered question to the server as an HTTPS request, and the data is serialized in JSON format and sent to the server via a secure communication protocol.

[1306] Step 3:

[1307] Question Analysis

[1308] The server deserializes the received question in JSON format. Next, it invokes a text analysis engine (e.g., spaCy or NLTK) to analyze the question and extract important keywords. Keywords such as "area," "U-turn," and "legal" are extracted from the input question text.

[1309] Step 4:

[1310] Emotion Analysis

[1311] The server uses an emotion engine (for example, Microsoft Azure's Text Analytics API) to analyze the user's emotional state from the received question. As a result of the analysis, emotions such as "confusion" or "urgency" are output based on the context of the question.

[1312] Step 5:

[1313] Generating legal information using generative AI

[1314] The server converts the extracted keywords and sentiment analysis results into prompt format and passes them to a generation AI (e.g., OpenAI's GPT-4). The generation AI generates appropriate legal information based on an internal traffic law dataset. The output information might be something like, "U-turns are prohibited in this area. Fines may be imposed."

[1315] Step 6:

[1316] Information Format

[1317] The server receives the legal information output by the generation AI and formats it for the user, formatting the information in a way that is easy for the user to understand and adding related links and references as needed.

[1318] Step 7:

[1319] Show Answers

[1320] The formatted answer is then serialized back into JSON and sent over HTTPS to the user's device, where it is deserialized and displayed in a user-friendly format, such as "According to local traffic laws, U-turns are illegal and may result in fines."

[1321] 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.

[1322] 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.

[1323] 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.

[1324] 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.

[1325] 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.

[1326] 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.

[1327] 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).

[1328] 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.

[1329] 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."

[1330] 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.

[1331] 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).

[1332] 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.

[1333] 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.

[1334] 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.

[1335] 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.

[1336] 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.

[1337] 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.

[1338] 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.

[1339] 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.

[1340] 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.

[1341] 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.

[1342] The following is further disclosed regarding the above embodiment.

[1343] (Claim 1)

[1344] means for a user to input legal questions using a terminal;

[1345] means for the terminal to transmit a user's question to a server;

[1346] A means for the server to analyze the content of the question and extract important keywords;

[1347] A means for the server to generate related legal information using a generation AI based on the extracted keywords;

[1348] means for the server to format the generated legal information for a user;

[1349] means for the terminal to display the formatted answer to the user;

[1350] A system including:

[1351] (Claim 2)

[1352] 10. The system of claim 1, wherein the server comprises means for adding links and references related to the generated legal information.

[1353] (Claim 3)

[1354] 2. The system according to claim 1, further comprising means for transmitting the content of the question sent by said terminal to a server using a secure communication protocol.

[1355] "Example 1"

[1356] (Claim 1)

[1357] means for a user to input legal questions using a terminal;

[1358] means for the terminal to transmit a user's question to a server;

[1359] A means for the server to analyze the content of the question and extract important keywords;

[1360] A means for the server to generate related legal information using a generation AI based on the extracted keywords;

[1361] means for the server to format the generated legal information for a user;

[1362] means for the terminal to display the formatted answer to the user;

[1363] a means for the server to analyze the content of the question using a natural language processing algorithm;

[1364] a means for the server to pass a prompt sentence for generating legal information to the generation AI;

[1365] means for the server to insert relevant reference links and additional material into the formatted response;

[1366] A system including:

[1367] (Claim 2)

[1368] 10. The system of claim 1, wherein the server comprises means for adding links and references related to the generated legal information.

[1369] (Claim 3)

[1370] 2. The system according to claim 1, further comprising means for transmitting the content of the question sent by said terminal to a server using a secure communication protocol.

[1371] "Application Example 1"

[1372] (Claim 1)

[1373] means for a user to input a legal question using an electronic device;

[1374] means for the electronic device to transmit a user's query to a data processing device;

[1375] means for the data processing device to analyze the content of the question and extract important information;

[1376] A means for generating relevant legal information using a generation AI based on the extracted information by the data processing device;

[1377] means for formatting the legal information generated by said data processing device for a user;

[1378] means for the electronic device to display the formatted answer to the user;

[1379] means for the electronic device to display legal information in real time;

[1380] A system including:

[1381] (Claim 2)

[1382] 2. The system of claim 1, wherein said data processing device comprises means for adding links and references related to the generated legal information.

[1383] (Claim 3)

[1384] 2. The system according to claim 1, further comprising means for transmitting the content of the query sent by the electronic device to the data processing device using a secure communication protocol.

[1385] "Example 2: Combining Emotion Engines"

[1386] (Claim 1)

[1387] means for a user to input a legal question using a computing device;

[1388] means for the computer device to transmit the user's query to a server via a network;

[1389] A means for the server to analyze the content of the question and extract important keywords;

[1390] A means for the server to generate related legal information using a generation AI based on the extracted keywords;

[1391] means for the server to format the generated legal information for a user;

[1392] an emotion analysis means for analyzing an emotion state from the input question by the server;

[1393] means for adjusting the tone of the generated legal information based on the sentiment analysis result by the server;

[1394] means for said computing device to display the formatted answers to a user;

[1395] A system including:

[1396] (Claim 2)

[1397] 10. The system of claim 1, wherein the server comprises means for adding links and references related to the generated legal information.

[1398] (Claim 3)

[1399] 2. The system according to claim 1, further comprising means for transmitting the content of the query sent by the computer device to a server using a secure communication protocol.

[1400] "Application example 2 when combining emotion engines"

[1401] (Claim 1)

[1402] means for a user to input legal questions using a terminal;

[1403] means for the terminal to transmit a user's question to a server;

[1404] A means for the server to analyze the content of the question and extract important keywords;

[1405] A means for the server to generate related legal information using a generation AI based on the extracted keywords;

[1406] means for the server to format the generated legal information for a user;

[1407] means for the terminal to display the formatted answer to the user;

[1408] means for parsing traffic law questions and generating appropriate law information;

[1409] means for analyzing a user's emotional state using an emotion engine to generate said legal information;

[1410] A system including:

[1411] (Claim 2)

[1412] 10. The system of claim 1, wherein the server comprises means for adding links and references related to the generated legal information.

[1413] (Claim 3)

[1414] 2. The system according to claim 1, further comprising means for transmitting the content of the question sent by said terminal to a server using a secure communication protocol. [Explanation of symbols]

[1415] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for a user to input legal questions using a terminal; means for the terminal to transmit a user's question to a server; A means for the server to analyze the content of the question and extract important keywords; A means for the server to generate related legal information using a generation AI based on the extracted keywords; means for the server to format the generated legal information for a user; means for the terminal to display the formatted answer to the user; A system including:

2. 2. The system of claim 1, wherein said server includes means for adding links and references related to the generated legal information.

3. 2. The system according to claim 1, further comprising means for transmitting the content of the question sent by said terminal to a server using a secure communication protocol.

Images