system

Abstract

We provide the system. [Solution] A means for receiving input information in various formats provided by the user, The means for analyzing the aforementioned input information using natural language processing technology, A means of generating contract reviews and legal advice based on analysis results, A means of providing the generated reviews and advice to the user, A system that includes this.

Description

【Technical Field】 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot's 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 Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 In legal services, there are problems such as variations in quality due to personalization, uneven workloads, and human errors. In addition, dealing with international legal issues requires high expertise and a great deal of effort, making it difficult to respond efficiently. There is a need to provide a unified, high-quality, and efficient system that can solve such problems. 【Means for Solving the Problems】 【0005】 This invention provides a system that receives input information in various formats from users and analyzes it using natural language processing technology. Furthermore, it can generate and provide contract reviews and legal advice to users based on the analysis results. This eliminates the reliance on individual expertise in legal work, ensures consistent quality and efficient operations, and enables the handling of international legal issues. In addition, continuous improvement can be achieved by receiving revised contracts from users, re-analyzing them, and re-reviewing them. 【0006】 A "user" refers to an individual or organization that uses this system to receive contract review or legal advice. 【0007】 "Input information" refers to contracts and related documents provided by the user, and includes various formats such as text, images, and audio. 【0008】 "Means of receiving" refers to the functions or devices that the system uses to acquire input information sent by the user. 【0009】 "Natural language processing technology" refers to the technology that systems use to analyze and understand human language, and this can be used to analyze the contents of contracts. 【0010】 "Means of analysis" refers to functions and devices that analyze received input information using natural language processing technology and extract important information. 【0011】 "Means for generating reviews and legal advice" refers to functions and devices for evaluating contracts and making improvement suggestions based on analysis results. 【0012】 "Means of delivery" refers to functions and devices for communicating generated reviews and advice to users. [Brief explanation of the drawing] 【0013】 [Figure 1]This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention] 【0014】 Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings. 【0015】 First, the terms used in the following description will be explained. 【0016】 In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0017】 In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0018】 In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc. 【0019】 In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and 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), or Bluetooth (registered trademark), etc. 【0020】 In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or." 【0021】 [First Embodiment] 【0022】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0023】 As shown in Figure 1, the 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. 【0024】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0025】 The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52. 【0026】 The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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. 【0027】 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor. 【0028】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54. 【0029】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0030】 As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30. 【0031】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0032】 In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0033】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0034】 This system utilizes AI technology to streamline legal operations. When users require contract review or legal advice, they can access this system and provide input information in various formats (e.g., text files, images, etc.). The terminal sends the user's input information to the server, which receives and begins processing it. 【0035】 The server analyzes the received information using natural language processing technology. Specifically, it identifies key clauses within the contract and extracts legal risks and issues. This process is based on advanced text analysis by an AI model. Furthermore, the AI ​​model generates contract reviews and legal advice based on the analysis results. This advice may include suggestions for revising contract clauses and warnings about ambiguous terminology. 【0036】 The generated advice and review results are sent from the server to the terminal and provided to the user. The user can refer to this and revise the contract as needed. By uploading the revised contract back to the system, it can undergo a more detailed review. 【0037】 As a concrete example, consider a case where a user uploads a contract in image format. In this case, the server uses OCR technology to extract text data from the image and performs analysis. As a result, warnings about ambiguous clauses and undefined legal terms are generated and provided to the user. If the user makes corrections based on these warnings, further review is possible, leading to continuous improvement. 【0038】 This system improves the accuracy and efficiency of contract reviews and facilitates responses to international legal issues. Through this process, it becomes possible to standardize legal work and reduce the burden on individual employees. 【0039】 The following describes the processing flow. 【0040】 Step 1: 【0041】 The user uploads the contract file to the system using a terminal. The terminal verifies the user's input information and sends this information to the server. 【0042】 Step 2: 【0043】 The server receives the uploaded file. It identifies the file format (text, PDF, image, etc.) and prepares it for analysis. 【0044】 Step 3: 【0045】 The server performs preprocessing based on the format of the received file. In the case of image files, text data is extracted using OCR technology and then standardized. 【0046】 Step 4: 【0047】 The server uses natural language processing (NLP) technology to analyze text data. It identifies clauses within the contract and extracts important legal terms and risk factors. 【0048】 Step 5: 【0049】 The server runs an AI model based on the analysis results, generating a contract review and legal advice. The AI ​​model consults legal databases to prepare relevant reference information and proposed revisions. 【0050】 Step 6: 【0051】 The server compiles the generated review results and advice into a report for the user. The report includes points of concern, recommended corrections, and reference materials. 【0052】 Step 7: 【0053】 The terminal receives reports from the server and displays them to the user in a visualized format. The user then reviews the reports and makes revisions to the contract. 【0054】 Step 8: 【0055】 The user uploads the revised contract to the system again. The server receives the revised information and performs re-analysis and re-review. 【0056】 Step 9: 【0057】 By repeating steps 3 through 8 as needed, the quality of the final contract will be improved. 【0058】 (Example 1) 【0059】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0060】 To efficiently review contracts and provide legal advice, it is necessary to process diverse contractual documents quickly and accurately, and to identify key clauses and risk factors. However, traditional methods become cumbersome and prone to inaccuracies when dealing with different document formats. Furthermore, expert reviews are time-consuming and costly. There is a need to improve this situation. 【0061】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0062】 In this invention, the server includes means for receiving input information in various formats provided by the user, means for extracting text data using optical character recognition technology, and means for analyzing the extracted text data using natural language processing technology. This makes it possible to automatically and accurately analyze contracts regardless of their format and to quickly identify important clauses and risk factors. 【0063】 "Input information" refers to various forms of data, such as contracts, provided by users. 【0064】 "Optical character recognition technology" is a technology for electronically reading text data from images, printed materials, and other sources. 【0065】 "Text data" refers to a collection of character information converted into a format that can be processed by a computer. 【0066】 "Natural language processing technology" is a technology that enables computers to understand and analyze human language. 【0067】 "Analysis" refers to the process of processing data and extracting necessary information. 【0068】 A "contract" refers to a document that formalizes a legal agreement, and is typically a document that contains clauses and terms. 【0069】 A "clause" is a section of a document that represents the conditions or provisions set forth within it. 【0070】 "Legal risk" refers to the legal uncertainties and potential problems that may arise in contracts and transactions. 【0071】 "Advice" refers to suggestions or recommendations given to achieve a specific objective. 【0072】 A "system" is a collection of interconnected components that work together to perform a specific function. 【0073】 This invention provides a system that efficiently offers legal document review and legal advice, and users access this system using a terminal during legal work. Users upload legal documents such as contracts as text files or image files. 【0074】 The terminal sends input information obtained from the user to the server. This server is a computer system that receives and processes the input information. The server uses optical character recognition technology to extract text data from the image-formatted input information. The extracted text data is analyzed using natural language processing technology. This process uses a generative AI model that executes advanced text analysis algorithms. 【0075】 Based on the analysis results, the server identifies key clauses within the contract and extracts legal risks and potential issues. This generates a contract review and legal advice. 【0076】 The generated reviews and advice are sent from the server to the terminal and provided to the user. The user can use this information to make necessary revisions to the contract, and then re-upload the results to the system for further analysis and review. This ensures that the contract is more accurate and less risky. 【0077】 As a concrete example, consider a scenario where a user uploads a contract in image format to the system. The server uses OCR technology to extract text information, and an AI model identifies ambiguous clauses and undefined legal terms. It then generates warnings and suggested revisions related to these issues and provides them to the user. 【0078】 An example of a prompt is the sentence, "Analyze the image of the contract to identify important clauses and legal risks." Based on this prompt, the AI ​​model performs the analysis and provides the necessary information to the user. 【0079】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0080】 Step 1: 【0081】 Users access the system via a terminal to receive contract review and legal advice. Users upload contract documents as text files or image files as input information. The terminal sends this input information to the server. Here, the input is the contract file uploaded by the user, and the output is the completion of the transmission to the server. 【0082】 Step 2: 【0083】 The server receives contract data sent from the terminal and stores it in storage. If the data includes image format, the server then uses optical character recognition (OCR) technology to convert it into text data. The input to this process is the image-format contract data, and the output is the extracted text data. Specifically, the server recognizes characters from the image and stores them as text in a database. 【0084】 Step 3: 【0085】 The server provides text data to a generating AI model, which analyzes the data using natural language processing techniques. This analysis extracts clauses from the contract and identifies risk factors and problems. The input is text data extracted by OCR, and the output is information generated based on the analysis, namely important clauses and warning items. The server also runs a text analysis algorithm to extract hidden risks. 【0086】 Step 4: 【0087】 The server uses a generative AI model to generate legal advice and contract review results based on the analysis. The input to this process is the information obtained through analysis, and the output is the review results and advice provided to the user. The AI ​​model is responsible for generating suggestions and warnings for specific clauses. 【0088】 Step 5: 【0089】 The server sends the generated reviews and advice to the user's device. The device displays and makes the provided information available to the user for review. The input is data provided by the server, and the output is reviews and advice that the user can view on the screen. The device notifies the user of any identified risks and prompts them to take further action. 【0090】 Step 6: 【0091】 Users can revise the contract based on the advice provided through the terminal. By uploading the revised contract back to the system, they can request re-analysis and re-review. In this step, the input is the user-updated contract, and the output is the new evaluation and improvement suggestions. Users then take specific actions to scrutinize the contract clauses and decide on revisions. 【0092】 (Application Example 1) 【0093】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0094】 Traditionally, reviewing contracts in legal practice has required significant time and expertise, and has been plagued by a heavy reliance on individual expertise, particularly in risk assessment and the identification of critical clauses. Furthermore, there is a growing need for efficient and timely legal advice utilizing smart devices to improve user convenience. 【0095】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0096】 In this invention, the server includes means for receiving input information in various forms provided by the user, means for analyzing the input information using natural language processing technology, means for generating contract reviews and legal advice based on the analysis results, means for providing the generated reviews and advice to the user, means for acquiring input data through photography of contract documents, means for using character recognition technology to extract character data from the captured images, and means for presenting immediate feedback and legal evaluations to the user. This enables increased efficiency in legal work and immediate improvements through rapid feedback on contract reviews. 【0097】 "Input information" refers to various types of data provided by the user, including text files and image files. 【0098】 "Natural language processing technology" refers to the technology used to analyze, understand, and generate human language using computers. 【0099】 "Review" refers to the act of evaluating the content of contracts and legal documents and pointing out problems and areas for improvement. 【0100】 "Advice" refers to suggestions that guide users on what actions they should take and what precautions they should take from a legal perspective. 【0101】 "Feedback" refers to the act of providing users with information that encourages improvement and correction by returning analysis results and evaluations. 【0102】 "Character recognition technology" is a technology that converts characters contained in an image into digital text data. 【0103】 "Photography" refers to the act of acquiring an image of a physical document using the camera of a smart device. 【0104】 A "risk factor" refers to a point in a contract where there are potential problems or uncertainties that could later lead to trouble. 【0105】 The system implementing this invention begins with the user using a smart device to input a contract as a photograph. The user takes a picture of the contract with the device and sends the image to the system. This device utilizes an internet connection. 【0106】 When the server receives an image of a contract, it first uses optical character recognition (OCR) technology to extract text data from the image. The OCR technology used includes Tesseract OCR. 【0107】 Next, the server analyzes the extracted text data using natural language processing techniques. This analysis utilizes natural language processing libraries such as spaCy and NLTK, as well as generative AI models such as BERT and GPT-3(registered trademark). This process identifies important clauses and risk factors within the contract. 【0108】 Based on the analysis results, the server generates a contract review and legal advice. This advice includes suggested revisions to contract clauses and warnings about ambiguous terminology. The generated information is immediately sent to the terminal and presented to the user. 【0109】 For example, when a user uploads a home purchase agreement, the server identifies unclear penalty clauses as risk factors and provides a more detailed legal assessment. This allows the user to quickly take appropriate action regarding the contract. 【0110】 A specific example of a prompt might be, "I have uploaded my home purchase agreement. Please assess the legal risks regarding the penalty clause." Through this prompt, the user can obtain the desired legal advice from the system. 【0111】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0112】 Step 1: 【0113】 The user takes a picture of the contract using a smart device. At this stage, the camera attached to the smart device acquires a physical image of the contract. The input is the actual image of the contract, and the output is the acquired image data. 【0114】 Step 2: 【0115】 The terminal sends the captured image of the contract to the server. Here, the terminal uploads the image data to the server via the internet connection. The input is the image data obtained in the previous step, and the output is the transfer of the image data to the server. 【0116】 Step 3: 【0117】 The server converts the received image data into text data using optical character recognition (OCR) technology. Here, Tesseract OCR is used to analyze the characters in the image and generate digital text data. The input is the received image data, and the output is the extracted text data. 【0118】 Step 4: 【0119】 The server analyzes the extracted text data using natural language processing techniques. Specifically, it uses spaCy and NLTK to perform grammatical analysis and identify important clauses and legal risks. The input is text data extracted by OCR, and the output is important clauses and risk information as a result of the analysis. 【0120】 Step 5: 【0121】 Based on the analysis results, the server uses a generative AI model (e.g., BERT or GPT-3) to generate a review of the contract and legal advice. At this stage, the AI ​​model uses the analysis results as prompts to generate specific revision suggestions and warnings. The input is the analysis results from step 4, and the output is the review and advice provided to the user. 【0122】 Step 6: 【0123】 The server sends the generated reviews and advice back to the terminal. Here, the server sends the output information to the terminal for the user to review. The input is the generated reviews and advice, and the output is the transfer of that data to the terminal. 【0124】 Step 7: 【0125】 The user refers to the provided reviews and advice and modifies the contract as needed. At this stage, the user takes action based on the information presented on the device. The input is the advice provided on the device, and the output is the possible contract modifications the user may make. 【0126】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0127】 This invention combines an emotion engine with a system for processing document information such as contracts provided by users and providing legal advice. To implement this system, the user uploads input information such as contracts using a terminal. The terminal receives the input information from the user and transmits it to the server. 【0128】 The server uses natural language processing technology to analyze the received information. First, it divides the information into contract clauses through text analysis and extracts legal risks. Furthermore, an emotion engine analyzes the user's emotional state. This analysis utilizes behavioral data from when the user interacts with the input information, as well as optional opinions and feedback. 【0129】 The server uses an AI model to generate contract reviews and advice, taking into account the user's emotional state. This allows for the provision of optimized advice tailored to the user's emotional condition. For example, if the server detects that the user is stressed, it can replace specialized terminology in the advice with simpler terms to aid user understanding. 【0130】 The generated review results and legal advice are sent from the server to the terminal. The terminal receives these results and presents them to the user in a visualized format. This may include specific correction suggestions and supplementary explanations to aid understanding based on the user's current emotional state. 【0131】 For example, if a user has doubts about a clause in a contract and feels burdened by that clause, the server uses an emotion engine to identify this emotion. This emotion data is then used to provide information about the risks and areas for improvement of the clause in a way that is more user-friendly. 【0132】 This system allows users to deepen their understanding and accuracy of contract reviews, and improve efficiency. Furthermore, by utilizing sentiment information, it enhances the user experience and supports better legal decision-making. 【0133】 The following describes the processing flow. 【0134】 Step 1: 【0135】 The user uploads the contract file to the system using a terminal. The terminal verifies the information entered by the user and sends this information to the server. 【0136】 Step 2: 【0137】 The server receives the uploaded file. The server identifies the file format (text, PDF, image, etc.) and prepares to process the format as needed. 【0138】 Step 3: 【0139】 The server begins analyzing the input information. First, it uses OCR technology to extract text from the image data. Next, it uses natural language processing technology to divide the contract clauses into sections and analyze their content. 【0140】 Step 4: 【0141】 The server uses the analysis results to set up the initial stage of contract review. At this stage, an initial legal risk analysis and identification of important legal terms are performed. 【0142】 Step 5: 【0143】 The server uses an emotion engine to analyze the user's emotions. It profiles the emotional state based on the user's input methods, work pace, and past feedback data. 【0144】 Step 6: 【0145】 The server uses an AI model that takes the user's emotional state into account to generate a detailed review of the contract and legal advice. This allows for advice and suggestions that are tailored to the user's emotions. 【0146】 Step 7: 【0147】 The server compiles the reviews and advice it generates and creates a report for the user in an appropriate format. The report includes explanations in simple language as needed to aid user understanding. 【0148】 Step 8: 【0149】 The terminal receives the report sent from the server and displays it to the user. The user can then refer to this report and make revisions to the contract. 【0150】 Step 9: 【0151】 The user uploads the revised contract to the system again. The server receives the revised data and performs re-analysis and re-review. This allows for continuous improvement to meet user needs. 【0152】 (Example 2) 【0153】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0154】 In today's world, contract information is provided in diverse formats, and there is a need to accurately analyze its contents and provide legal advice. However, conventional systems lack the accuracy of document analysis and the ability to optimize advice while considering user emotions, resulting in insufficient means to deepen user understanding. Furthermore, the influence of user emotional states on how contract contents are perceived is often underestimated, limiting the effectiveness of advice. Therefore, there is an urgent need to develop a system that can provide accurate and optimal contract information review and legal advice while considering user emotions. 【0155】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0156】 In this invention, the server includes means for analyzing the user's emotional state based on behavioral data and opinion data, means for generating a review of contract information and legal advice based on the analysis results, and means for optimizing the generated review and advice according to the user's emotional state. As a result, the user can receive analysis results of contract information and legal advice that are tailored to their emotional state, deepening their understanding and enabling them to make accurate legal decisions. 【0157】 A "user" refers to an entity that provides contract information to the system and receives analysis results and legal advice. 【0158】 "Input information" refers to document data in various formats, including contracts, that is provided to the system by users and is subject to analysis. 【0159】 "Natural language processing technology" is a technology that allows computers to analyze and understand human language. This technology is used to analyze contract information, divide clauses, and extract risk factors. 【0160】 "Emotional state" refers to the user's emotions and psychological state, and is analyzed based on user behavioral data and opinion data during device operation. 【0161】 "Behavioral data" refers to data about the specific actions users take when manipulating contract information, including mouse movements, click speed, and time spent on a page. 【0162】 "Opinion data" refers to subjective opinions and feedback that users provide to the system, and is used for sentiment analysis by the emotion engine. 【0163】 "Legal advice" refers to expert advice generated based on the analysis of contract information, and includes assessments of legal risks and suggestions for clause revisions. 【0164】 "Optimization" refers to adjusting information according to the user's emotional state and level of understanding, making it easier for the user to understand and more effective. 【0165】 "Review" is the process of analyzing the entire contract information to clarify important items and risk factors. 【0166】 This invention is a system that efficiently processes document information such as contracts provided by users and optimizes legal advice. Users first upload contract information to the system using a terminal. The terminal transmits input information in various formats to the server. To ensure the security of the information, it is recommended that this communication use an encrypted protocol. 【0167】 The server uses software that implements natural language processing technology to analyze the received document information. Specifically, it automatically divides the content of the contract into clauses and examines each clause to clarify the legal risks. Furthermore, it has a built-in emotion engine that analyzes the user's emotional state in real time. User behavior data and opinion data are used in this analysis. 【0168】 Based on the analyzed information, the server utilizes a generative AI model to generate a review of the contract information and legal advice. This generation process allows for adjustments to word choice and advice content based on the user's emotional state. Optimized advice enables users to gain a deeper understanding of the contract. 【0169】 Finally, the reviews and advice generated by the server are sent to the terminal. The terminal provides a mechanism to display this information in an easy-to-understand manner for the user. By including specific revision suggestions and supplementary explanations tailored to the user's sentiments, it supports legal decision-making. 【0170】 For example, when a user expresses concern about a particular contract clause, the server uses an emotion engine to identify that concern and provides advice that clearly indicates risk information and areas for improvement in the clause. In this way, incorporating feedback based on the user's emotional information can enhance the overall usefulness of the system. 【0171】 A concrete example of a prompt message would be something like, "Analyze the risks in this contract and determine if the user is feeling uneasy." 【0172】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0173】 Step 1: 【0174】 The user uploads contract information using their device. 【0175】 The user selects the contract file through the GUI and presses the upload button. 【0176】 Input: Contract files in PDF or Word format. 【0177】 Output: The terminal becomes ready to send contract information to the server. 【0178】 Step 2: 【0179】 The device sends contract information to the server. 【0180】 The device encrypts the contract information uploaded by the user and sends it to the server using a secure protocol (e.g., HTTPS). 【0181】 Input: A contract file uploaded by the user. 【0182】 Output: Encrypted contract information transferred to the server. 【0183】 Step 3: 【0184】 The server receives the contract information and begins analysis. 【0185】 The server uses natural language processing technology to analyze the contract information and divides the contract into clauses. 【0186】 Input: Encrypted contract information. 【0187】 Output: The clauses of the divided contract and the associated initial analysis data. 【0188】 Step 4: 【0189】 The server analyzes the user's emotional state. 【0190】 The server uses an emotion engine to analyze user behavior data (e.g., mouse movements, click speed) and opinion data to determine the user's emotional state. 【0191】 Input: User behavior data and opinion data. 【0192】 Output: Information about the user's emotional state. 【0193】 Step 5: 【0194】 The server generates legal advice. 【0195】 The server uses a generative AI model to review contract information and generate legal advice based on the user's emotional state. 【0196】 Input: Divided contract terms, initial analysis data, user sentiment information. 【0197】 Output: Optimized legal advice and review of contract information. 【0198】 Step 6: 【0199】 The server sends the generated results to the terminal. 【0200】 The server encrypts the generated legal advice and review and sends it to the terminal. 【0201】 Input: Optimized legal advice and review of contract information. 【0202】 Output: Encrypted review and advice data transferred to the terminal. 【0203】 Step 7: 【0204】 The device displays the results to the user. 【0205】 The terminal decrypts the data received from the server and displays it in an easy-to-understand format for the user. This includes suggested corrections and supplementary explanations. 【0206】 Input: Review and advice data sent from the server. 【0207】 Output: Analysis results and optimized legal advice displayed to the user. 【0208】 (Application Example 2) 【0209】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal". 【0210】 Current legal document review systems often present users with highly specialized and complex information, leading to misunderstandings and anxieties. Furthermore, the inability to respond flexibly to users' emotional states can make the system inconvenient to use. Additionally, in situations such as electronic payments, where terms of service and contractual documents are complex, there is a need for improved user understanding and enhanced decision-making processes. 【0211】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0212】 In this invention, the server includes means for receiving diverse forms of input information provided by the user, means for analyzing the input information using natural language processing technology, and means for measuring the user's emotional state using sentiment analysis technology. This makes it possible to generate reviews and legal advice based on the analysis results of contract documents, and further optimize the advice according to the user's emotional state. 【0213】 "Input information in various formats" refers to document data from users that have different formats and content, such as contract documents and terms of service. 【0214】 "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate language that humans use on a daily basis. 【0215】 "Legal advice" refers to information that provides users with legal opinions or recommendations regarding contract documents, etc. 【0216】 "Emotion analysis technology" is a technology that analyzes and evaluates a user's emotional state based on their input and actions. 【0217】 An "AI model" is a software model that uses artificial intelligence to analyze data and learn and apply patterns and trends. 【0218】 A "review" is a report that summarizes the results of a detailed examination and analysis of contract documents or terms of service. 【0219】 "Optimization" is the process of making adjustments and improvements to obtain the most effective and efficient results under specific conditions. 【0220】 This invention is a system designed to make documents related to the use of electronic payment services easier for users to understand, and it provides legal advice using natural language processing and sentiment analysis technologies. The server and terminal work in conjunction with each other. 【0221】 First, users upload various types of input information, such as contract documents and terms of service, using their devices. This data is sent to the server. The server uses natural language processing engines such as "SpaCy" and "BERT" to analyze the documents in detail and extract clauses and risk factors. For sentiment analysis, it uses an "NLP Sentiment Analysis API" to evaluate the emotional state from the user's operation data. 【0222】 The server further utilizes AI generation models such as "GPT" to generate advice tailored to the user's emotional state. This simplifies technical terms and complex expressions, aiding understanding. This optimized advice is then sent back to the terminal and presented to the user in a visualized form. 【0223】 For example, if a user feels uneasy about the "cancellation policy" within the terms of service of an electronic payment service, sentiment analysis technology can identify that uneasy point, and the server will provide a clear explanation based on that. This allows the user to understand the terms more clearly. 【0224】 An example of a prompt to be input into the generation AI model is: "For specific clauses in the document uploaded by the user, generate optimization advice based on sentiment data, along with risk analysis results, and present it in an easy-to-understand format." This allows users to gain the knowledge necessary to use electronic payment services with confidence. 【0225】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0226】 Step 1: 【0227】 The user uploads the contract document for the electronic payment service using a terminal. The terminal prepares to send the document data to the server. In this step, the user's contract document data is the input, and it is ready to be sent to the server as output. 【0228】 Step 2: 【0229】 The server analyzes document data received from the terminal using a natural language processing engine. Using technologies such as "SpaCy" and "BERT," the input data is divided into clauses, and important risk factors are extracted. As output, analysis data for each clause is generated and used for the next processing step. 【0230】 Step 3: 【0231】 The server applies emotion analysis technology to evaluate the user's emotional state. Using tools such as the "NLP Emotion Analysis API," it analyzes emotions input from the user's operation data and outputs specific states (e.g., anxiety, tension). This information is used in the optimization process. 【0232】 Step 4: 【0233】 The server uses a generative AI model to generate legal advice based on the terms of service. The server takes sentiment analysis results into consideration and receives a prompt message in the form of "Generate optimized advice based on sentiment data, along with risk analysis results, for specific clauses in the document uploaded by the user, and present it in an easy-to-understand manner," to output the optimized advice. 【0234】 Step 5: 【0235】 Optimized advice and analysis results are sent from the server to the terminal. The terminal presents this information to the user in a visually and easily understandable format. The user reviews this information and uses it to make their own decisions. As output, the final advice data is provided in a format that is easy for the user to understand. 【0236】 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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. 【0237】 Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0238】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14. 【0239】 [Second Embodiment] 【0240】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0241】 As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server. 【0242】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0243】 The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52. 【0244】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0245】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0246】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0247】 Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0248】 The specific processing program 56 is an example of a "program" relating to the technology of this 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. 【0249】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0250】 In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0251】 Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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". 【0252】 This system utilizes AI technology to streamline legal operations. When users require contract review or legal advice, they can access this system and provide input information in various formats (e.g., text files, images, etc.). The terminal sends the user's input information to the server, which receives and begins processing it. 【0253】 The server analyzes the received information using natural language processing technology. Specifically, it identifies key clauses within the contract and extracts legal risks and issues. This process is based on advanced text analysis by an AI model. Furthermore, the AI ​​model generates contract reviews and legal advice based on the analysis results. This advice may include suggestions for revising contract clauses and warnings about ambiguous terminology. 【0254】 The generated advice and review results are sent from the server to the terminal and provided to the user. The user can refer to this and revise the contract as needed. By uploading the revised contract back to the system, it can undergo a more detailed review. 【0255】 As a concrete example, consider a case where a user uploads a contract in image format. In this case, the server uses OCR technology to extract text data from the image and performs analysis. As a result, warnings about ambiguous clauses and undefined legal terms are generated and provided to the user. If the user makes corrections based on these warnings, further review is possible, leading to continuous improvement. 【0256】 This system improves the accuracy and efficiency of contract reviews and facilitates responses to international legal issues. Through this process, it becomes possible to standardize legal work and reduce the burden on individual employees. 【0257】 The following describes the processing flow. 【0258】 Step 1: 【0259】 The user uploads the contract file to the system using a terminal. The terminal verifies the user's input information and sends this information to the server. 【0260】 Step 2: 【0261】 The server receives the uploaded file. It identifies the file format (text, PDF, image, etc.) and prepares it for analysis. 【0262】 Step 3: 【0263】 The server performs preprocessing based on the format of the received file. In the case of image files, text data is extracted using OCR technology and then standardized. 【0264】 Step 4: 【0265】 The server uses natural language processing (NLP) technology to analyze text data. It identifies clauses within the contract and extracts important legal terms and risk factors. 【0266】 Step 5: 【0267】 The server runs an AI model based on the analysis results, generating a contract review and legal advice. The AI ​​model consults legal databases to prepare relevant reference information and proposed revisions. 【0268】 Step 6: 【0269】 The server compiles the generated review results and advice into a report for the user. The report includes points of concern, recommended corrections, and reference materials. 【0270】 Step 7: 【0271】 The terminal receives reports from the server and displays them to the user in a visualized format. The user then reviews the reports and makes revisions to the contract. 【0272】 Step 8: 【0273】 The user uploads the revised contract to the system again. The server receives the revised information and performs re-analysis and re-review. 【0274】 Step 9: 【0275】 By repeating steps 3 through 8 as needed, the quality of the final contract will be improved. 【0276】 (Example 1) 【0277】 Next, we will describe Example 1. 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." 【0278】 To efficiently review contracts and provide legal advice, it is necessary to process diverse contractual documents quickly and accurately, and to identify key clauses and risk factors. However, traditional methods become cumbersome and prone to inaccuracies when dealing with different document formats. Furthermore, expert reviews are time-consuming and costly. There is a need to improve this situation. 【0279】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0280】 In this invention, the server includes means for receiving input information in various formats provided by the user, means for extracting text data using optical character recognition technology, and means for analyzing the extracted text data using natural language processing technology. This makes it possible to automatically and accurately analyze contracts regardless of their format and to quickly identify important clauses and risk factors. 【0281】 "Input information" refers to various forms of data, such as contracts, provided by users. 【0282】 "Optical character recognition technology" is a technology for electronically reading text data from images, printed materials, and other sources. 【0283】 "Text data" refers to a collection of character information converted into a format that can be processed by a computer. 【0284】 "Natural language processing technology" refers to the technology for a computer to understand and analyze human language. 【0285】 "Analysis" refers to the process of processing data and extracting necessary information. 【0286】 "Contract" refers to a document that documents a legal contract, usually a document with terms described. 【0287】 "Clause" refers to the part that represents the conditions and regulations defined in a document. 【0288】 "Legal risk" refers to the legal uncertainties and potential problems that may occur in contracts and transactions. 【0289】 "Advice" refers to the advice and recommendations given to achieve a specific purpose. 【0290】 "System" refers to a set of components that are mutually related to realize a specific function. 【0291】 This invention provides a system for efficiently providing legal document review and legal advice. Users access this system using a terminal during legal work. Users upload legal documents such as contracts in text file or image format. 【0292】 The terminal sends the input information obtained from the user to the server. This server is composed of a computer device and receives and processes the input information. The server uses optical character recognition technology to extract text data from the input information in image format. The extracted text data is analyzed using natural language processing technology. A generative AI model that executes an advanced text analysis algorithm is used for this processing. 【0293】 Based on the analysis results, the server identifies key clauses within the contract and extracts legal risks and potential issues. This generates a contract review and legal advice. 【0294】 The generated reviews and advice are sent from the server to the terminal and provided to the user. The user can use this information to make necessary revisions to the contract, and then re-upload the results to the system for further analysis and review. This ensures that the contract is more accurate and less risky. 【0295】 As a concrete example, consider a scenario where a user uploads a contract in image format to the system. The server uses OCR technology to extract text information, and an AI model identifies ambiguous clauses and undefined legal terms. It then generates warnings and suggested revisions related to these issues and provides them to the user. 【0296】 An example of a prompt is the sentence, "Analyze the image of the contract to identify important clauses and legal risks." Based on this prompt, the AI ​​model performs the analysis and provides the necessary information to the user. 【0297】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0298】 Step 1: 【0299】 Users access the system via a terminal to receive contract review and legal advice. Users upload contract documents as text files or image files as input information. The terminal sends this input information to the server. Here, the input is the contract file uploaded by the user, and the output is the completion of the transmission to the server. 【0300】 Step 2: 【0301】 The server receives the contract data sent from the terminal and stores it in the storage. Then, if the data includes image-formatted data, the server uses optical character recognition (OCR) technology to convert it into text data. The input of this process is the contract data in image format, and the output is the extracted text data. As a specific operation, the server recognizes characters from the image and stores them in the database as text. 【0302】 Step 3: 【0303】 The server provides the text data to the generative AI model and analyzes the data using natural language processing technology. In this analysis, the terms in the contract are extracted to identify risk factors and issues. The input is the text data extracted by OCR, and the output is the information generated based on the analysis, namely the important terms and warning items. The server also executes a text analysis algorithm to extract hidden risks. 【0304】 Step 4: 【0305】 The server uses the generative AI model to generate legal advice and contract review results based on the analysis results. The input for this process is the information obtained from the analysis, and the output is the review results and advice provided to the user. The AI model is responsible for generating actions such as proposed amendments to specific terms and warnings. 【0306】 Step 5: 【0307】 The server sends the generated review and advice to the terminal that the user accesses. The terminal displays the provided information to the user and makes it viewable. The input is the data provided by the server, and the output is the review and advice that the user can view on the screen. The terminal explicitly notifies the user of the discovered risks and prompts the next action. 【0308】 Step 6: 【0309】 Users can revise the contract based on the advice provided through the terminal. By uploading the revised contract back to the system, they can request re-analysis and re-review. In this step, the input is the user-updated contract, and the output is the new evaluation and improvement suggestions. Users then take specific actions to scrutinize the contract clauses and decide on revisions. 【0310】 (Application Example 1) 【0311】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0312】 Traditionally, reviewing contracts in legal practice has required significant time and expertise, and has been plagued by a heavy reliance on individual expertise, particularly in risk assessment and the identification of critical clauses. Furthermore, there is a growing need for efficient and timely legal advice utilizing smart devices to improve user convenience. 【0313】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0314】 In this invention, the server includes means for receiving input information in various forms provided by the user, means for analyzing the input information using natural language processing technology, means for generating contract reviews and legal advice based on the analysis results, means for providing the generated reviews and advice to the user, means for acquiring input data through photography of contract documents, means for using character recognition technology to extract character data from the captured images, and means for presenting immediate feedback and legal evaluations to the user. This enables increased efficiency in legal work and immediate improvements through rapid feedback on contract reviews. 【0315】 "Input information" refers to various forms of data provided by the user, including text files and image files. 【0316】 "Natural language processing technology" refers to the technology used to analyze, understand, and generate human language using computers. 【0317】 "Review" refers to the act of evaluating the content of contracts and legal documents and pointing out problems and areas for improvement. 【0318】 "Advice" refers to suggestions that guide users on what actions they should take and what precautions they should take from a legal perspective. 【0319】 "Feedback" refers to the act of providing users with information that encourages improvement and correction by returning analysis results and evaluations. 【0320】 "Character recognition technology" is a technology that converts characters contained in an image into digital text data. 【0321】 "Photography" refers to the act of acquiring an image of a physical document using the camera of a smart device. 【0322】 A "risk factor" refers to a point in a contract where there are potential problems or uncertainties that could later lead to trouble. 【0323】 The system implementing this invention begins with the user using a smart device to input a contract as a photograph. The user takes a picture of the contract with the device and sends the image to the system. This device utilizes an internet connection. 【0324】 When the server receives an image of a contract, it first uses optical character recognition (OCR) technology to extract text data from the image. The OCR technology used includes Tesseract OCR. 【0325】 Next, the server analyzes the extracted text data using natural language processing techniques. This analysis utilizes natural language processing libraries such as spaCy and NLTK, as well as generative AI models such as BERT and GPT-3. This process identifies important clauses and risk factors within the contract. 【0326】 Based on the analysis results, the server generates a contract review and legal advice. This advice includes suggested revisions to contract clauses and warnings about ambiguous terminology. The generated information is immediately sent to the terminal and presented to the user. 【0327】 For example, when a user uploads a home purchase agreement, the server identifies unclear penalty clauses as risk factors and provides a more detailed legal assessment. This allows the user to quickly take appropriate action regarding the contract. 【0328】 A specific example of a prompt might be, "I have uploaded my home purchase agreement. Please assess the legal risks regarding the penalty clause." Through this prompt, the user can obtain the desired legal advice from the system. 【0329】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0330】 Step 1: 【0331】 The user takes a picture of the contract using a smart device. At this stage, the camera attached to the smart device acquires a physical image of the contract. The input is the actual image of the contract, and the output is the acquired image data. 【0332】 Step 2: 【0333】 The terminal sends the captured image of the contract to the server. Here, the terminal uploads the image data to the server via the internet connection. The input is the image data obtained in the previous step, and the output is the transfer of the image data to the server. 【0334】 Step 3: 【0335】 The server converts the received image data into text data using optical character recognition (OCR) technology. Here, Tesseract OCR is used to analyze the characters in the image and generate digital text data. The input is the received image data, and the output is the extracted text data. 【0336】 Step 4: 【0337】 The server analyzes the extracted text data using natural language processing techniques. Specifically, it uses spaCy and NLTK to perform grammatical analysis and identify important clauses and legal risks. The input is text data extracted by OCR, and the output is important clauses and risk information as a result of the analysis. 【0338】 Step 5: 【0339】 Based on the analysis results, the server uses a generative AI model (e.g., BERT or GPT-3) to generate a review of the contract and legal advice. At this stage, the AI ​​model uses the analysis results as prompts to generate specific revision suggestions and warnings. The input is the analysis results from step 4, and the output is the review and advice provided to the user. 【0340】 Step 6: 【0341】 The server sends the generated reviews and advice back to the terminal. Here, the server sends the output information to the terminal for the user to review. The input is the generated reviews and advice, and the output is the transfer of that data to the terminal. 【0342】 Step 7: 【0343】 The user refers to the provided reviews and advice and modifies the contract as needed. At this stage, the user takes action based on the information presented on the device. The input is the advice provided on the device, and the output is the possible contract modifications the user may make. 【0344】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0345】 This invention combines an emotion engine with a system for processing document information such as contracts provided by users and providing legal advice. To implement this system, the user uploads input information such as contracts using a terminal. The terminal receives the input information from the user and transmits it to the server. 【0346】 The server uses natural language processing technology to analyze the received information. First, it divides the information into contract clauses through text analysis and extracts legal risks. Furthermore, an emotion engine analyzes the user's emotional state. This analysis utilizes behavioral data from when the user interacts with the input information, as well as optional opinions and feedback. 【0347】 The server uses an AI model to generate contract reviews and advice, taking into account the user's emotional state. This allows for the provision of optimized advice tailored to the user's emotional condition. For example, if the server detects that the user is stressed, it can replace specialized terminology in the advice with simpler terms to aid user understanding. 【0348】 The generated review results and legal advice are sent from the server to the terminal. The terminal receives these results and presents them to the user in a visualized format. This may include specific correction suggestions and supplementary explanations to aid understanding based on the user's current emotional state. 【0349】 For example, if a user has doubts about a clause in a contract and feels burdened by that clause, the server uses an emotion engine to identify this emotion. This emotion data is then used to provide information about the risks and areas for improvement of the clause in a way that is more user-friendly. 【0350】 This system allows users to deepen their understanding and accuracy of contract reviews, and improve efficiency. Furthermore, by utilizing sentiment information, it enhances the user experience and supports better legal decision-making. 【0351】 The following describes the processing flow. 【0352】 Step 1: 【0353】 The user uploads the contract file to the system using a terminal. The terminal verifies the information entered by the user and sends this information to the server. 【0354】 Step 2: 【0355】 The server receives the uploaded file. The server identifies the file format (text, PDF, image, etc.) and prepares to process the format as needed. 【0356】 Step 3: 【0357】 The server begins analyzing the input information. First, it uses OCR technology to extract text from the image data. Next, it uses natural language processing technology to divide the contract clauses into sections and analyze their content. 【0358】 Step 4: 【0359】 The server uses the analysis results to set up the initial stage of contract review. At this stage, an initial legal risk analysis and identification of important legal terms are performed. 【0360】 Step 5: 【0361】 The server uses an emotion engine to analyze the user's emotions. It profiles the emotional state based on the user's input methods, work pace, and past feedback data. 【0362】 Step 6: 【0363】 The server uses an AI model that takes the user's emotional state into account to generate a detailed review of the contract and legal advice. This allows for advice and suggestions that are tailored to the user's emotions. 【0364】 Step 7: 【0365】 The server compiles the reviews and advice it generates and creates a report for the user in an appropriate format. The report includes explanations in simple language as needed to aid user understanding. 【0366】 Step 8: 【0367】 The terminal receives the report sent from the server and displays it to the user. The user can then refer to this report and make revisions to the contract. 【0368】 Step 9: 【0369】 The user uploads the revised contract to the system again. The server receives the revised data and performs re-analysis and re-review. This allows for continuous improvement to meet user needs. 【0370】 (Example 2) 【0371】 Next, we will describe Example 2. 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". 【0372】 In today's world, contract information is provided in diverse formats, and there is a need to accurately analyze its contents and provide legal advice. However, conventional systems lack the accuracy of document analysis and the ability to optimize advice while considering user emotions, resulting in insufficient means to deepen user understanding. Furthermore, the influence of user emotional states on how contract contents are perceived is often underestimated, limiting the effectiveness of advice. Therefore, there is an urgent need to develop a system that can provide accurate and optimal contract information review and legal advice while considering user emotions. 【0373】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0374】 In this invention, the server includes means for analyzing the user's emotional state based on behavioral data and opinion data, means for generating a review of contract information and legal advice based on the analysis results, and means for optimizing the generated review and advice according to the user's emotional state. As a result, the user can receive analysis results of contract information and legal advice that are tailored to their emotional state, deepening their understanding and enabling them to make accurate legal decisions. 【0375】 A "user" refers to an entity that provides contract information to the system and receives analysis results and legal advice. 【0376】 "Input information" refers to document data in various formats, including contracts, that is provided to the system by users and is subject to analysis. 【0377】 "Natural language processing technology" is a technology that allows computers to analyze and understand human language. This technology is used to analyze contract information, divide clauses, and extract risk factors. 【0378】 "Emotional state" refers to the user's emotions and psychological state, and is analyzed based on user behavioral data and opinion data during device operation. 【0379】 "Behavioral data" refers to data about the specific actions users take when manipulating contract information, including mouse movements, click speed, and time spent on a page. 【0380】 "Opinion data" refers to subjective opinions and feedback that users provide to the system, and is used for sentiment analysis by the emotion engine. 【0381】 "Legal advice" refers to expert advice generated based on the analysis of contract information, and includes assessments of legal risks and suggestions for clause revisions. 【0382】 "Optimization" refers to adjusting information according to the user's emotional state and level of understanding, making it easier for the user to understand and more effective. 【0383】 "Review" is the process of analyzing the entire contract information to clarify important items and risk factors. 【0384】 This invention is a system that efficiently processes document information such as contracts provided by users and optimizes legal advice. Users first upload contract information to the system using a terminal. The terminal transmits input information in various formats to the server. To ensure the security of the information, it is recommended that this communication use an encrypted protocol. 【0385】 The server uses software that implements natural language processing technology to analyze the received document information. Specifically, it automatically divides the content of the contract into clauses and examines each clause to clarify the legal risks. Furthermore, it has a built-in emotion engine that analyzes the user's emotional state in real time. User behavior data and opinion data are used in this analysis. 【0386】 Based on the analyzed information, the server utilizes a generative AI model to generate a review of the contract information and legal advice. This generation process allows for adjustments to word choice and advice content based on the user's emotional state. Optimized advice enables users to gain a deeper understanding of the contract. 【0387】 Finally, the reviews and advice generated by the server are sent to the terminal. The terminal provides a mechanism to display this information in an easy-to-understand manner for the user. By including specific revision suggestions and supplementary explanations tailored to the user's sentiments, it supports legal decision-making. 【0388】 For example, when a user expresses concern about a particular contract clause, the server uses an emotion engine to identify that concern and provides advice that clearly indicates risk information and areas for improvement in the clause. In this way, incorporating feedback based on the user's emotional information can enhance the overall usefulness of the system. 【0389】 A concrete example of a prompt message would be something like, "Analyze the risks in this contract and determine if the user is feeling uneasy." 【0390】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0391】 Step 1: 【0392】 The user uploads contract information using their device. 【0393】 The user selects the contract file through the GUI and presses the upload button. 【0394】 Input: Contract files in PDF or Word format. 【0395】 Output: The terminal becomes ready to send contract information to the server. 【0396】 Step 2: 【0397】 The device sends contract information to the server. 【0398】 The device encrypts the contract information uploaded by the user and sends it to the server using a secure protocol (e.g., HTTPS). 【0399】 Input: A contract file uploaded by the user. 【0400】 Output: Encrypted contract information transferred to the server. 【0401】 Step 3: 【0402】 The server receives the contract information and begins analysis. 【0403】 The server uses natural language processing technology to analyze the contract information and divides the contract into clauses. 【0404】 Input: Encrypted contract information. 【0405】 Output: The clauses of the divided contract and the associated initial analysis data. 【0406】 Step 4: 【0407】 The server analyzes the user's emotional state. 【0408】 The server uses an emotion engine to analyze user behavior data (e.g., mouse movements, click speed) and opinion data to determine the user's emotional state. 【0409】 Input: User behavior data and opinion data. 【0410】 Output: Information about the user's emotional state. 【0411】 Step 5: 【0412】 The server generates legal advice. 【0413】 The server uses a generative AI model to review contract information and generate legal advice based on the user's emotional state. 【0414】 Input: Divided contract terms, initial analysis data, user sentiment information. 【0415】 Output: Optimized legal advice and review of contract information. 【0416】 Step 6: 【0417】 The server sends the generated results to the terminal. 【0418】 The server encrypts the generated legal advice and review and sends it to the terminal. 【0419】 Input: Optimized legal advice and review of contract information. 【0420】 Output: Encrypted review and advice data transferred to the terminal. 【0421】 Step 7: 【0422】 The device displays the results to the user. 【0423】 The terminal decrypts the data received from the server and displays it in an easy-to-understand format for the user. This includes suggested corrections and supplementary explanations. 【0424】 Input: Review and advice data sent from the server. 【0425】 Output: Analysis results and optimized legal advice displayed to the user. 【0426】 (Application Example 2) 【0427】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0428】 Current legal document review systems often present users with highly specialized and complex information, leading to misunderstandings and anxieties. Furthermore, the inability to respond flexibly to users' emotional states can make the system inconvenient to use. Additionally, in situations such as electronic payments, where terms of service and contractual documents are complex, there is a need for improved user understanding and enhanced decision-making processes. 【0429】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0430】 In this invention, the server includes means for receiving diverse forms of input information provided by the user, means for analyzing the input information using natural language processing technology, and means for measuring the user's emotional state using sentiment analysis technology. This makes it possible to generate reviews and legal advice based on the analysis results of contract documents, and further optimize the advice according to the user's emotional state. 【0431】 "Input information in various formats" refers to document data from users that have different formats and content, such as contract documents and terms of service. 【0432】 "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate language that humans use on a daily basis. 【0433】 "Legal advice" refers to information that provides users with legal opinions or recommendations regarding contract documents, etc. 【0434】 "Emotion analysis technology" is a technology that analyzes and evaluates a user's emotional state based on their input and actions. 【0435】 An "AI model" is a software model that uses artificial intelligence to analyze data and learn and apply patterns and trends. 【0436】 A "review" is a report that summarizes the results of a detailed examination and analysis of contract documents or terms of service. 【0437】 "Optimization" is the process of making adjustments and improvements to obtain the most effective and efficient results under specific conditions. 【0438】 This invention is a system designed to make documents related to the use of electronic payment services easier for users to understand, and it provides legal advice using natural language processing and sentiment analysis technologies. The server and terminal work in conjunction with each other. 【0439】 First, users upload various types of input information, such as contract documents and terms of service, using their devices. This data is sent to the server. The server uses natural language processing engines such as "SpaCy" and "BERT" to analyze the documents in detail and extract clauses and risk factors. For sentiment analysis, it uses an "NLP Sentiment Analysis API" to evaluate the emotional state from the user's operation data. 【0440】 The server further utilizes AI generation models such as "GPT" to generate advice tailored to the user's emotional state. This simplifies technical terms and complex expressions, aiding understanding. This optimized advice is then sent back to the terminal and presented to the user in a visualized form. 【0441】 For example, if a user feels uneasy about the "cancellation policy" within the terms of service of an electronic payment service, sentiment analysis technology can identify that uneasy point, and the server will provide a clear explanation based on that. This allows the user to understand the terms more clearly. 【0442】 An example of a prompt to be input into the generation AI model is: "For specific clauses in the document uploaded by the user, generate optimization advice based on sentiment data, along with risk analysis results, and present it in an easy-to-understand format." This allows users to gain the knowledge necessary to use electronic payment services with confidence. 【0443】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0444】 Step 1: 【0445】 The user uploads the contract document for the electronic payment service using a terminal. The terminal prepares to send the document data to the server. In this step, the user's contract document data is the input, and it is ready to be sent to the server as output. 【0446】 Step 2: 【0447】 The server analyzes document data received from the terminal using a natural language processing engine. Using technologies such as "SpaCy" and "BERT," the input data is divided into clauses, and important risk factors are extracted. As output, analysis data for each clause is generated and used for the next processing step. 【0448】 Step 3: 【0449】 The server applies emotion analysis technology to evaluate the user's emotional state. Using tools such as the "NLP Emotion Analysis API," it analyzes emotions input from the user's operation data and outputs specific states (e.g., anxiety, tension). This information is used in the optimization process. 【0450】 Step 4: 【0451】 The server uses a generative AI model to generate legal advice based on the terms of service. The server takes sentiment analysis results into consideration and receives a prompt message in the form of "Generate optimized advice based on sentiment data, along with risk analysis results, for specific clauses in the document uploaded by the user, and present it in an easy-to-understand manner," to output the optimized advice. 【0452】 Step 5: 【0453】 Optimized advice and analysis results are sent from the server to the terminal. The terminal presents this information to the user in a visually and easily understandable format. The user reviews this information and uses it to make their own decisions. As output, the final advice data is provided in a format that is easy for the user to understand. 【0454】 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0455】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0456】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214. 【0457】 [Third Embodiment] 【0458】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0459】 As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server. 【0460】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0461】 The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52. 【0462】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0463】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0464】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0465】 Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0466】 The specific processing program 56 is an example of a "program" relating to the technology of this 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. 【0467】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0468】 In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0469】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal". 【0470】 This system utilizes AI technology to streamline legal operations. When users require contract review or legal advice, they can access this system and provide input information in various formats (e.g., text files, images, etc.). The terminal sends the user's input information to the server, which receives and begins processing it. 【0471】 The server analyzes the received information using natural language processing technology. Specifically, it identifies key clauses within the contract and extracts legal risks and issues. This process is based on advanced text analysis by an AI model. Furthermore, the AI ​​model generates contract reviews and legal advice based on the analysis results. This advice may include suggestions for revising contract clauses and warnings about ambiguous terminology. 【0472】 The generated advice and review results are sent from the server to the terminal and provided to the user. The user can refer to this and revise the contract as needed. By uploading the revised contract back to the system, it can undergo a more detailed review. 【0473】 As a concrete example, consider a case where a user uploads a contract in image format. In this case, the server uses OCR technology to extract text data from the image and performs analysis. As a result, warnings about ambiguous clauses and undefined legal terms are generated and provided to the user. If the user makes corrections based on these warnings, further review is possible, leading to continuous improvement. 【0474】 This system improves the accuracy and efficiency of contract reviews and facilitates responses to international legal issues. Through this process, it becomes possible to standardize legal work and reduce the burden on individual employees. 【0475】 The following describes the processing flow. 【0476】 Step 1: 【0477】 The user uploads the contract file to the system using a terminal. The terminal verifies the user's input information and sends this information to the server. 【0478】 Step 2: 【0479】 The server receives the uploaded file. It identifies the file format (text, PDF, image, etc.) and prepares it for analysis. 【0480】 Step 3: 【0481】 The server performs preprocessing based on the format of the received file. In the case of image files, text data is extracted using OCR technology and then standardized. 【0482】 Step 4: 【0483】 The server uses natural language processing (NLP) technology to analyze text data. It identifies clauses within the contract and extracts important legal terms and risk factors. 【0484】 Step 5: 【0485】 The server runs an AI model based on the analysis results, generating a contract review and legal advice. The AI ​​model consults legal databases to prepare relevant reference information and proposed revisions. 【0486】 Step 6: 【0487】 The server compiles the generated review results and advice into a report for the user. The report includes points of concern, recommended corrections, and reference materials. 【0488】 Step 7: 【0489】 The terminal receives reports from the server and displays them to the user in a visualized format. The user then reviews the reports and makes revisions to the contract. 【0490】 Step 8: 【0491】 The user uploads the revised contract to the system again. The server receives the revised information and performs re-analysis and re-review. 【0492】 Step 9: 【0493】 By repeating steps 3 through 8 as needed, the quality of the final contract will be improved. 【0494】 (Example 1) 【0495】 Next, we will describe Example 1. 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." 【0496】 To efficiently review contracts and provide legal advice, it is necessary to process diverse contractual documents quickly and accurately, and to identify key clauses and risk factors. However, traditional methods become cumbersome and prone to inaccuracies when dealing with different document formats. Furthermore, expert reviews are time-consuming and costly. There is a need to improve this situation. 【0497】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0498】 In this invention, the server includes means for receiving input information in various formats provided by the user, means for extracting text data using optical character recognition technology, and means for analyzing the extracted text data using natural language processing technology. This makes it possible to automatically and accurately analyze contracts regardless of their format and to quickly identify important clauses and risk factors. 【0499】 "Input information" refers to various forms of data, such as contracts, provided by users. 【0500】 "Optical character recognition technology" is a technology for electronically reading text data from images, printed materials, and other sources. 【0501】 "Text data" refers to a collection of character information converted into a format that can be processed by a computer. 【0502】 "Natural language processing technology" is a technology that enables computers to understand and analyze human language. 【0503】 "Analysis" refers to the process of processing data and extracting necessary information. 【0504】 A "contract" refers to a document that formalizes a legal agreement, and is typically a document that contains clauses and terms. 【0505】 A "clause" is a section of a document that represents the conditions or provisions set forth within it. 【0506】 "Legal risk" refers to the legal uncertainties and potential problems that may arise in contracts and transactions. 【0507】 "Advice" refers to suggestions or recommendations given to achieve a specific objective. 【0508】 A "system" is a collection of interconnected components that work together to perform a specific function. 【0509】 This invention provides a system that efficiently offers legal document review and legal advice, and users access this system using a terminal during legal work. Users upload legal documents such as contracts as text files or image files. 【0510】 The terminal sends input information obtained from the user to the server. This server is a computer system that receives and processes the input information. The server uses optical character recognition technology to extract text data from the image-formatted input information. The extracted text data is analyzed using natural language processing technology. This process uses a generative AI model that executes advanced text analysis algorithms. 【0511】 Based on the analysis results, the server identifies key clauses within the contract and extracts legal risks and potential issues. This generates a contract review and legal advice. 【0512】 The generated reviews and advice are sent from the server to the terminal and provided to the user. The user can use this information to make necessary revisions to the contract, and then re-upload the results to the system for further analysis and review. This ensures that the contract is more accurate and less risky. 【0513】 As a concrete example, consider a scenario where a user uploads a contract in image format to the system. The server uses OCR technology to extract text information, and an AI model identifies ambiguous clauses and undefined legal terms. It then generates warnings and suggested revisions related to these issues and provides them to the user. 【0514】 An example of a prompt is the sentence, "Analyze the image of the contract to identify important clauses and legal risks." Based on this prompt, the AI ​​model performs the analysis and provides the necessary information to the user. 【0515】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0516】 Step 1: 【0517】 Users access the system via a terminal to receive contract review and legal advice. Users upload contract documents as text files or image files as input information. The terminal sends this input information to the server. Here, the input is the contract file uploaded by the user, and the output is the completion of the transmission to the server. 【0518】 Step 2: 【0519】 The server receives contract data sent from the terminal and stores it in storage. If the data includes image format, the server then uses optical character recognition (OCR) technology to convert it into text data. The input to this process is the image-format contract data, and the output is the extracted text data. Specifically, the server recognizes characters from the image and stores them as text in a database. 【0520】 Step 3: 【0521】 The server provides text data to a generating AI model, which analyzes the data using natural language processing techniques. This analysis extracts clauses from the contract and identifies risk factors and problems. The input is text data extracted by OCR, and the output is information generated based on the analysis, namely important clauses and warning items. The server also runs a text analysis algorithm to extract hidden risks. 【0522】 Step 4: 【0523】 The server uses a generative AI model to generate legal advice and contract review results based on the analysis. The input to this process is the information obtained through analysis, and the output is the review results and advice provided to the user. The AI ​​model is responsible for generating suggestions and warnings for specific clauses. 【0524】 Step 5: 【0525】 The server sends the generated reviews and advice to the user's device. The device displays and makes the provided information available to the user for review. The input is data provided by the server, and the output is reviews and advice that the user can view on the screen. The device notifies the user of any identified risks and prompts them to take further action. 【0526】 Step 6: 【0527】 Users can revise the contract based on the advice provided through the terminal. By uploading the revised contract back to the system, they can request re-analysis and re-review. In this step, the input is the user-updated contract, and the output is the new evaluation and improvement suggestions. Users then take specific actions to scrutinize the contract clauses and decide on revisions. 【0528】 (Application Example 1) 【0529】 Next, we will explain Application Example 1. In the following explanation, 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." 【0530】 Traditionally, reviewing contracts in legal practice has required significant time and expertise, and has been plagued by a heavy reliance on individual expertise, particularly in risk assessment and the identification of critical clauses. Furthermore, there is a growing need for efficient and timely legal advice utilizing smart devices to improve user convenience. 【0531】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0532】 In this invention, the server includes means for receiving input information in various forms provided by the user, means for analyzing the input information using natural language processing technology, means for generating contract reviews and legal advice based on the analysis results, means for providing the generated reviews and advice to the user, means for acquiring input data through photography of contract documents, means for using character recognition technology to extract character data from the captured images, and means for presenting immediate feedback and legal evaluations to the user. This enables increased efficiency in legal work and immediate improvements through rapid feedback on contract reviews. 【0533】 "Input information" refers to various types of data provided by the user, including text files and image files. 【0534】 "Natural language processing technology" refers to the technology used to analyze, understand, and generate human language using computers. 【0535】 "Review" refers to the act of evaluating the content of contracts and legal documents and pointing out problems and areas for improvement. 【0536】 "Advice" refers to suggestions that guide users on what actions they should take and what precautions they should take from a legal perspective. 【0537】 "Feedback" refers to the act of providing users with information that encourages improvement and correction by returning analysis results and evaluations. 【0538】 "Character recognition technology" is a technology that converts characters contained in an image into digital text data. 【0539】 "Photography" refers to the act of acquiring an image of a physical document using the camera of a smart device. 【0540】 A "risk factor" refers to a point in a contract where there are potential problems or uncertainties that could later lead to trouble. 【0541】 The system implementing this invention begins with the user using a smart device to input a contract as a photograph. The user takes a picture of the contract with the device and sends the image to the system. This device utilizes an internet connection. 【0542】 When the server receives an image of a contract, it first uses optical character recognition (OCR) technology to extract text data from the image. The OCR technology used includes Tesseract OCR. 【0543】 Next, the server analyzes the extracted text data using natural language processing techniques. This analysis utilizes natural language processing libraries such as spaCy and NLTK, as well as generative AI models such as BERT and GPT-3. This process identifies important clauses and risk factors within the contract. 【0544】 Based on the analysis results, the server generates a contract review and legal advice. This advice includes suggested revisions to contract clauses and warnings about ambiguous terminology. The generated information is immediately sent to the terminal and presented to the user. 【0545】 For example, when a user uploads a home purchase agreement, the server identifies unclear penalty clauses as risk factors and provides a more detailed legal assessment. This allows the user to quickly take appropriate action regarding the contract. 【0546】 A specific example of a prompt might be, "I have uploaded my home purchase agreement. Please assess the legal risks regarding the penalty clause." Through this prompt, the user can obtain the desired legal advice from the system. 【0547】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0548】 Step 1: 【0549】 The user takes a picture of the contract using a smart device. At this stage, the camera attached to the smart device acquires a physical image of the contract. The input is the actual image of the contract, and the output is the acquired image data. 【0550】 Step 2: 【0551】 The terminal sends the captured image of the contract to the server. Here, the terminal uploads the image data to the server via the internet connection. The input is the image data obtained in the previous step, and the output is the transfer of the image data to the server. 【0552】 Step 3: 【0553】 The server converts the received image data into text data using optical character recognition (OCR) technology. Here, Tesseract OCR is used to analyze the characters in the image and generate digital text data. The input is the received image data, and the output is the extracted text data. 【0554】 Step 4: 【0555】 The server analyzes the extracted text data using natural language processing techniques. Specifically, it uses spaCy and NLTK to perform grammatical analysis and identify important clauses and legal risks. The input is text data extracted by OCR, and the output is important clauses and risk information as a result of the analysis. 【0556】 Step 5: 【0557】 Based on the analysis results, the server uses a generative AI model (e.g., BERT or GPT-3) to generate a review of the contract and legal advice. At this stage, the AI ​​model uses the analysis results as prompts to generate specific revision suggestions and warnings. The input is the analysis results from step 4, and the output is the review and advice provided to the user. 【0558】 Step 6: 【0559】 The server sends the generated reviews and advice back to the terminal. Here, the server sends the output information to the terminal for the user to review. The input is the generated reviews and advice, and the output is the transfer of that data to the terminal. 【0560】 Step 7: 【0561】 The user refers to the provided reviews and advice and modifies the contract as needed. At this stage, the user takes action based on the information presented on the device. The input is the advice provided on the device, and the output is the possible contract modifications the user may make. 【0562】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0563】 This invention combines an emotion engine with a system for processing document information such as contracts provided by users and providing legal advice. To implement this system, the user uploads input information such as contracts using a terminal. The terminal receives the input information from the user and transmits it to the server. 【0564】 The server uses natural language processing technology to analyze the received information. First, it divides the information into contract clauses through text analysis and extracts legal risks. Furthermore, an emotion engine analyzes the user's emotional state. This analysis utilizes behavioral data from when the user interacts with the input information, as well as optional opinions and feedback. 【0565】 The server uses an AI model to generate contract reviews and advice, taking into account the user's emotional state. This allows for the provision of optimized advice tailored to the user's emotional condition. For example, if the server detects that the user is stressed, it can replace specialized terminology in the advice with simpler terms to aid user understanding. 【0566】 The generated review results and legal advice are sent from the server to the terminal. The terminal receives these results and presents them to the user in a visualized format. This may include specific correction suggestions and supplementary explanations to aid understanding based on the user's current emotional state. 【0567】 For example, if a user has doubts about a clause in a contract and feels burdened by that clause, the server uses an emotion engine to identify this emotion. This emotion data is then used to provide information about the risks and areas for improvement of the clause in a way that is more user-friendly. 【0568】 This system allows users to deepen their understanding and accuracy of contract reviews, and improve efficiency. Furthermore, by utilizing sentiment information, it enhances the user experience and supports better legal decision-making. 【0569】 The following describes the processing flow. 【0570】 Step 1: 【0571】 The user uploads the contract file to the system using a terminal. The terminal verifies the information entered by the user and sends this information to the server. 【0572】 Step 2: 【0573】 The server receives the uploaded file. The server identifies the file format (text, PDF, image, etc.) and prepares to process the format as needed. 【0574】 Step 3: 【0575】 The server begins analyzing the input information. First, it uses OCR technology to extract text from the image data. Next, it uses natural language processing technology to divide the contract clauses into sections and analyze their content. 【0576】 Step 4: 【0577】 The server uses the analysis results to set up the initial stage of contract review. At this stage, an initial legal risk analysis and identification of important legal terms are performed. 【0578】 Step 5: 【0579】 The server uses an emotion engine to analyze the user's emotions. It profiles the emotional state based on the user's input methods, work pace, and past feedback data. 【0580】 Step 6: 【0581】 The server uses an AI model that takes the user's emotional state into account to generate a detailed review of the contract and legal advice. This allows for advice and suggestions that are tailored to the user's emotions. 【0582】 Step 7: 【0583】 The server compiles the reviews and advice it generates and creates a report for the user in an appropriate format. The report includes explanations in simple language as needed to aid user understanding. 【0584】 Step 8: 【0585】 The terminal receives the report sent from the server and displays it to the user. The user can then refer to this report and make revisions to the contract. 【0586】 Step 9: 【0587】 The user uploads the revised contract to the system again. The server receives the revised data and performs re-analysis and re-review. This allows for continuous improvement to meet user needs. 【0588】 (Example 2) 【0589】 Next, we will describe Example 2. 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." 【0590】 In today's world, contract information is provided in diverse formats, and there is a need to accurately analyze its contents and provide legal advice. However, conventional systems lack the accuracy of document analysis and the ability to optimize advice while considering user emotions, resulting in insufficient means to deepen user understanding. Furthermore, the influence of user emotional states on how contract contents are perceived is often underestimated, limiting the effectiveness of advice. Therefore, there is an urgent need to develop a system that can provide accurate and optimal contract information review and legal advice while considering user emotions. 【0591】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0592】 In this invention, the server includes means for analyzing the user's emotional state based on behavioral data and opinion data, means for generating a review of contract information and legal advice based on the analysis results, and means for optimizing the generated review and advice according to the user's emotional state. As a result, the user can receive analysis results of contract information and legal advice that are tailored to their emotional state, deepening their understanding and enabling them to make accurate legal decisions. 【0593】 A "user" refers to an entity that provides contract information to the system and receives analysis results and legal advice. 【0594】 "Input information" refers to document data in various formats, including contracts, that is provided to the system by users and is subject to analysis. 【0595】 "Natural language processing technology" is a technology that allows computers to analyze and understand human language. This technology is used to analyze contract information, divide clauses, and extract risk factors. 【0596】 "Emotional state" refers to the user's emotions and psychological state, and is analyzed based on user behavioral data and opinion data during device operation. 【0597】 "Behavioral data" refers to data about the specific actions users take when manipulating contract information, including mouse movements, click speed, and time spent on a page. 【0598】 "Opinion data" refers to subjective opinions and feedback that users provide to the system, and is used for sentiment analysis by the emotion engine. 【0599】 "Legal advice" refers to expert advice generated based on the analysis of contract information, and includes assessments of legal risks and suggestions for clause revisions. 【0600】 "Optimization" refers to adjusting information according to the user's emotional state and level of understanding, making it easier for the user to understand and more effective. 【0601】 "Review" is the process of analyzing the entire contract information to clarify important items and risk factors. 【0602】 This invention is a system that efficiently processes document information such as contracts provided by users and optimizes legal advice. Users first upload contract information to the system using a terminal. The terminal transmits input information in various formats to the server. To ensure the security of the information, it is recommended that this communication use an encrypted protocol. 【0603】 The server uses software that implements natural language processing technology to analyze the received document information. Specifically, it automatically divides the content of the contract into clauses and examines each clause to clarify the legal risks. Furthermore, it has a built-in emotion engine that analyzes the user's emotional state in real time. User behavior data and opinion data are used in this analysis. 【0604】 Based on the analyzed information, the server utilizes a generative AI model to generate a review of the contract information and legal advice. This generation process allows for adjustments to word choice and advice content based on the user's emotional state. Optimized advice enables users to gain a deeper understanding of the contract. 【0605】 Finally, the reviews and advice generated by the server are sent to the terminal. The terminal provides a mechanism to display this information in an easy-to-understand manner for the user. By including specific revision suggestions and supplementary explanations tailored to the user's sentiments, it supports legal decision-making. 【0606】 For example, when a user expresses concern about a particular contract clause, the server uses an emotion engine to identify that concern and provides advice that clearly indicates risk information and areas for improvement in the clause. In this way, incorporating feedback based on the user's emotional information can enhance the overall usefulness of the system. 【0607】 A concrete example of a prompt message would be something like, "Analyze the risks in this contract and determine if the user is feeling uneasy." 【0608】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0609】 Step 1: 【0610】 The user uploads contract information using their device. 【0611】 The user selects the contract file through the GUI and presses the upload button. 【0612】 Input: Contract files in PDF or Word format. 【0613】 Output: The terminal becomes ready to send contract information to the server. 【0614】 Step 2: 【0615】 The device sends contract information to the server. 【0616】 The device encrypts the contract information uploaded by the user and sends it to the server using a secure protocol (e.g., HTTPS). 【0617】 Input: A contract file uploaded by the user. 【0618】 Output: Encrypted contract information transferred to the server. 【0619】 Step 3: 【0620】 The server receives the contract information and begins analysis. 【0621】 The server uses natural language processing technology to analyze the contract information and divides the contract into clauses. 【0622】 Input: Encrypted contract information. 【0623】 Output: The clauses of the divided contract and the associated initial analysis data. 【0624】 Step 4: 【0625】 The server analyzes the user's emotional state. 【0626】 The server uses an emotion engine to analyze user behavior data (e.g., mouse movements, click speed) and opinion data to determine the user's emotional state. 【0627】 Input: User behavior data and opinion data. 【0628】 Output: Information about the user's emotional state. 【0629】 Step 5: 【0630】 The server generates legal advice. 【0631】 The server uses a generative AI model to review contract information and generate legal advice based on the user's emotional state. 【0632】 Input: Divided contract terms, initial analysis data, user sentiment information. 【0633】 Output: Optimized legal advice and review of contract information. 【0634】 Step 6: 【0635】 The server sends the generated results to the terminal. 【0636】 The server encrypts the generated legal advice and review and sends it to the terminal. 【0637】 Input: Optimized legal advice and review of contract information. 【0638】 Output: Encrypted review and advice data transferred to the terminal. 【0639】 Step 7: 【0640】 The device displays the results to the user. 【0641】 The terminal decrypts the data received from the server and displays it in an easy-to-understand format for the user. This includes suggested corrections and supplementary explanations. 【0642】 Input: Review and advice data sent from the server. 【0643】 Output: Analysis results and optimized legal advice displayed to the user. 【0644】 (Application Example 2) 【0645】 Next, we will explain application example 2. In the following explanation, 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." 【0646】 Current legal document review systems often present users with highly specialized and complex information, leading to misunderstandings and anxieties. Furthermore, the inability to respond flexibly to users' emotional states can make the system inconvenient to use. Additionally, in situations such as electronic payments, where terms of service and contractual documents are complex, there is a need for improved user understanding and enhanced decision-making processes. 【0647】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0648】 In this invention, the server includes means for receiving diverse forms of input information provided by the user, means for analyzing the input information using natural language processing technology, and means for measuring the user's emotional state using sentiment analysis technology. This makes it possible to generate reviews and legal advice based on the analysis results of contract documents, and further optimize the advice according to the user's emotional state. 【0649】 "Input information in various formats" refers to document data from users that have different formats and content, such as contract documents and terms of service. 【0650】 "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate language that humans use on a daily basis. 【0651】 "Legal advice" refers to information that provides users with legal opinions or recommendations regarding contract documents, etc. 【0652】 "Emotion analysis technology" is a technology that analyzes and evaluates a user's emotional state based on their input and actions. 【0653】 An "AI model" is a software model that uses artificial intelligence to analyze data and learn and apply patterns and trends. 【0654】 A "review" is a report that summarizes the results of a detailed examination and analysis of contract documents or terms of service. 【0655】 "Optimization" is the process of making adjustments and improvements to obtain the most effective and efficient results under specific conditions. 【0656】 This invention is a system designed to make documents related to the use of electronic payment services easier for users to understand, and it provides legal advice using natural language processing and sentiment analysis technologies. The server and terminal work in conjunction with each other. 【0657】 First, users upload various types of input information, such as contract documents and terms of service, using their devices. This data is sent to the server. The server uses natural language processing engines such as "SpaCy" and "BERT" to analyze the documents in detail and extract clauses and risk factors. For sentiment analysis, it uses an "NLP Sentiment Analysis API" to evaluate the emotional state from the user's operation data. 【0658】 The server further utilizes AI generation models such as "GPT" to generate advice tailored to the user's emotional state. This simplifies technical terms and complex expressions, aiding understanding. This optimized advice is then sent back to the terminal and presented to the user in a visualized form. 【0659】 For example, if a user feels uneasy about the "cancellation policy" within the terms of service of an electronic payment service, sentiment analysis technology can identify that uneasy point, and the server will provide a clear explanation based on that. This allows the user to understand the terms more clearly. 【0660】 An example of a prompt to be input into the generation AI model is: "For specific clauses in the document uploaded by the user, generate optimization advice based on sentiment data, along with risk analysis results, and present it in an easy-to-understand format." This allows users to gain the knowledge necessary to use electronic payment services with confidence. 【0661】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0662】 Step 1: 【0663】 The user uploads the contract document for the electronic payment service using a terminal. The terminal prepares to send the document data to the server. In this step, the user's contract document data is the input, and it is ready to be sent to the server as output. 【0664】 Step 2: 【0665】 The server analyzes document data received from the terminal using a natural language processing engine. Using technologies such as "SpaCy" and "BERT," the input data is divided into clauses, and important risk factors are extracted. As output, analysis data for each clause is generated and used for the next processing step. 【0666】 Step 3: 【0667】 The server applies emotion analysis technology to evaluate the user's emotional state. Using tools such as the "NLP Emotion Analysis API," it analyzes emotions input from the user's operation data and outputs specific states (e.g., anxiety, tension). This information is used in the optimization process. 【0668】 Step 4: 【0669】 The server uses a generative AI model to generate legal advice based on the terms of service. The server takes sentiment analysis results into consideration and receives a prompt message in the form of "Generate optimized advice based on sentiment data, along with risk analysis results, for specific clauses in the document uploaded by the user, and present it in an easy-to-understand manner," to output the optimized advice. 【0670】 Step 5: 【0671】 Optimized advice and analysis results are sent from the server to the terminal. The terminal presents this information to the user in a visually and easily understandable format. The user reviews this information and uses it to make their own decisions. As output, the final advice data is provided in a format that is easy for the user to understand. 【0672】 The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0673】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0674】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314. 【0675】 [Fourth Embodiment] 【0676】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0677】 As shown in Figure 7, the 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. 【0678】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0679】 The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52. 【0680】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the 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 image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0682】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0683】 The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes. 【0684】 Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0685】 The specific processing program 56 is an example of a "program" relating to the technology of this 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. 【0686】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0687】 In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0688】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0689】 This system utilizes AI technology to streamline legal operations. When users require contract review or legal advice, they can access this system and provide input information in various formats (e.g., text files, images, etc.). The terminal sends the user's input information to the server, which receives and begins processing it. 【0690】 The server analyzes the received information using natural language processing technology. Specifically, it identifies key clauses within the contract and extracts legal risks and issues. This process is based on advanced text analysis by an AI model. Furthermore, the AI ​​model generates contract reviews and legal advice based on the analysis results. This advice may include suggestions for revising contract clauses and warnings about ambiguous terminology. 【0691】 The generated advice and review results are sent from the server to the terminal and provided to the user. The user can refer to this and revise the contract as needed. By uploading the revised contract back to the system, it can undergo a more detailed review. 【0692】 As a concrete example, consider a case where a user uploads a contract in image format. In this case, the server uses OCR technology to extract text data from the image and performs analysis. As a result, warnings about ambiguous clauses and undefined legal terms are generated and provided to the user. If the user makes corrections based on these warnings, further review is possible, leading to continuous improvement. 【0693】 This system improves the accuracy and efficiency of contract reviews and facilitates responses to international legal issues. Through this process, it becomes possible to standardize legal work and reduce the burden on individual employees. 【0694】 The following describes the processing flow. 【0695】 Step 1: 【0696】 The user uploads the contract file to the system using a terminal. The terminal verifies the user's input information and sends this information to the server. 【0697】 Step 2: 【0698】 The server receives the uploaded file. It identifies the file format (text, PDF, image, etc.) and prepares it for analysis. 【0699】 Step 3: 【0700】 The server performs preprocessing based on the format of the received file. In the case of image files, text data is extracted using OCR technology and then standardized. 【0701】 Step 4: 【0702】 The server uses natural language processing (NLP) technology to analyze text data. It identifies clauses within the contract and extracts important legal terms and risk factors. 【0703】 Step 5: 【0704】 The server runs an AI model based on the analysis results, generating a contract review and legal advice. The AI ​​model consults legal databases to prepare relevant reference information and proposed revisions. 【0705】 Step 6: 【0706】 The server compiles the generated review results and advice into a report for the user. The report includes points of concern, recommended corrections, and reference materials. 【0707】 Step 7: 【0708】 The terminal receives reports from the server and displays them to the user in a visualized format. The user then reviews the reports and makes revisions to the contract. 【0709】 Step 8: 【0710】 The user uploads the revised contract to the system again. The server receives the revised information and performs re-analysis and re-review. 【0711】 Step 9: 【0712】 By repeating steps 3 through 8 as needed, the quality of the final contract will be improved. 【0713】 (Example 1) 【0714】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0715】 To efficiently review contracts and provide legal advice, it is necessary to process diverse contractual documents quickly and accurately, and to identify key clauses and risk factors. However, traditional methods become cumbersome and prone to inaccuracies when dealing with different document formats. Furthermore, expert reviews are time-consuming and costly. There is a need to improve this situation. 【0716】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0717】 In this invention, the server includes means for receiving input information in various formats provided by the user, means for extracting text data using optical character recognition technology, and means for analyzing the extracted text data using natural language processing technology. This makes it possible to automatically and accurately analyze contracts regardless of their format and to quickly identify important clauses and risk factors. 【0718】 "Input information" refers to various forms of data, such as contracts, provided by users. 【0719】 "Optical character recognition technology" is a technology for electronically reading text data from images, printed materials, and other sources. 【0720】 "Text data" refers to a collection of character information converted into a format that can be processed by a computer. 【0721】 "Natural language processing technology" is a technology that enables computers to understand and analyze human language. 【0722】 "Analysis" refers to the process of processing data and extracting necessary information. 【0723】 A "contract" refers to a document that formalizes a legal agreement, and is typically a document that contains clauses and terms. 【0724】 A "clause" is a section of a document that represents the conditions or provisions set forth within it. 【0725】 "Legal risk" refers to the legal uncertainties and potential problems that may arise in contracts and transactions. 【0726】 "Advice" refers to suggestions or recommendations given to achieve a specific objective. 【0727】 A "system" is a collection of interconnected components that work together to perform a specific function. 【0728】 This invention provides a system that efficiently offers legal document review and legal advice, and users access this system using a terminal during legal work. Users upload legal documents such as contracts as text files or image files. 【0729】 The terminal sends input information obtained from the user to the server. This server is a computer system that receives and processes the input information. The server uses optical character recognition technology to extract text data from the image-formatted input information. The extracted text data is analyzed using natural language processing technology. This process uses a generative AI model that executes advanced text analysis algorithms. 【0730】 Based on the analysis results, the server identifies key clauses within the contract and extracts legal risks and potential issues. This generates a contract review and legal advice. 【0731】 The generated reviews and advice are sent from the server to the terminal and provided to the user. The user can use this information to make necessary revisions to the contract, and then re-upload the results to the system for further analysis and review. This ensures that the contract is more accurate and less risky. 【0732】 As a concrete example, consider a scenario where a user uploads a contract in image format to the system. The server uses OCR technology to extract text information, and an AI model identifies ambiguous clauses and undefined legal terms. It then generates warnings and suggested revisions related to these issues and provides them to the user. 【0733】 An example of a prompt is the sentence, "Analyze the image of the contract to identify important clauses and legal risks." Based on this prompt, the AI ​​model performs the analysis and provides the necessary information to the user. 【0734】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0735】 Step 1: 【0736】 Users access the system via a terminal to receive contract review and legal advice. Users upload contract documents as text files or image files as input information. The terminal sends this input information to the server. Here, the input is the contract file uploaded by the user, and the output is the completion of the transmission to the server. 【0737】 Step 2: 【0738】 The server receives contract data sent from the terminal and stores it in storage. If the data includes image format, the server then uses optical character recognition (OCR) technology to convert it into text data. The input to this process is the image-format contract data, and the output is the extracted text data. Specifically, the server recognizes characters from the image and stores them as text in a database. 【0739】 Step 3: 【0740】 The server provides text data to a generating AI model, which analyzes the data using natural language processing techniques. This analysis extracts clauses from the contract and identifies risk factors and problems. The input is text data extracted by OCR, and the output is information generated based on the analysis, namely important clauses and warning items. The server also runs a text analysis algorithm to extract hidden risks. 【0741】 Step 4: 【0742】 The server uses a generative AI model to generate legal advice and contract review results based on the analysis. The input to this process is the information obtained through analysis, and the output is the review results and advice provided to the user. The AI ​​model is responsible for generating suggestions and warnings for specific clauses. 【0743】 Step 5: 【0744】 The server sends the generated reviews and advice to the user's device. The device displays and makes the provided information available to the user for review. The input is data provided by the server, and the output is reviews and advice that the user can view on the screen. The device notifies the user of any identified risks and prompts them to take further action. 【0745】 Step 6: 【0746】 Users can revise the contract based on the advice provided through the terminal. By uploading the revised contract back to the system, they can request re-analysis and re-review. In this step, the input is the user-updated contract, and the output is the new evaluation and improvement suggestions. Users then take specific actions to scrutinize the contract clauses and decide on revisions. 【0747】 (Application Example 1) 【0748】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0749】 Traditionally, reviewing contracts in legal practice has required significant time and expertise, and has been plagued by a heavy reliance on individual expertise, particularly in risk assessment and the identification of critical clauses. Furthermore, there is a growing need for efficient and timely legal advice utilizing smart devices to improve user convenience. 【0750】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0751】 In this invention, the server includes means for receiving input information in various forms provided by the user, means for analyzing the input information using natural language processing technology, means for generating contract reviews and legal advice based on the analysis results, means for providing the generated reviews and advice to the user, means for acquiring input data through photography of contract documents, means for using character recognition technology to extract character data from the captured images, and means for presenting immediate feedback and legal evaluations to the user. This enables increased efficiency in legal work and immediate improvements through rapid feedback on contract reviews. 【0752】 "Input information" refers to various types of data provided by the user, including text files and image files. 【0753】 "Natural language processing technology" refers to the technology used to analyze, understand, and generate human language using computers. 【0754】 "Review" refers to the act of evaluating the content of contracts and legal documents and pointing out problems and areas for improvement. 【0755】 "Advice" refers to suggestions that guide users on what actions they should take and what precautions they should take from a legal perspective. 【0756】 "Feedback" refers to the act of providing users with information that encourages improvement and correction by returning analysis results and evaluations. 【0757】 "Character recognition technology" is a technology that converts characters contained in an image into digital text data. 【0758】 "Photography" refers to the act of acquiring an image of a physical document using the camera of a smart device. 【0759】 A "risk factor" refers to a point in a contract where there are potential problems or uncertainties that could later lead to trouble. 【0760】 The system implementing this invention begins with the user using a smart device to input a contract as a photograph. The user takes a picture of the contract with the device and sends the image to the system. This device utilizes an internet connection. 【0761】 When the server receives an image of a contract, it first uses optical character recognition (OCR) technology to extract text data from the image. The OCR technology used includes Tesseract OCR. 【0762】 Next, the server analyzes the extracted text data using natural language processing techniques. This analysis utilizes natural language processing libraries such as spaCy and NLTK, as well as generative AI models such as BERT and GPT-3. This process identifies important clauses and risk factors within the contract. 【0763】 Based on the analysis results, the server generates a contract review and legal advice. This advice includes suggested revisions to contract clauses and warnings about ambiguous terminology. The generated information is immediately sent to the terminal and presented to the user. 【0764】 For example, when a user uploads a home purchase agreement, the server identifies unclear penalty clauses as risk factors and provides a more detailed legal assessment. This allows the user to quickly take appropriate action regarding the contract. 【0765】 A specific example of a prompt might be, "I have uploaded my home purchase agreement. Please assess the legal risks regarding the penalty clause." Through this prompt, the user can obtain the desired legal advice from the system. 【0766】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0767】 Step 1: 【0768】 The user takes a picture of the contract using a smart device. At this stage, the camera attached to the smart device acquires a physical image of the contract. The input is the actual image of the contract, and the output is the acquired image data. 【0769】 Step 2: 【0770】 The terminal sends the captured image of the contract to the server. Here, the terminal uploads the image data to the server via the internet connection. The input is the image data obtained in the previous step, and the output is the transfer of the image data to the server. 【0771】 Step 3: 【0772】 The server converts the received image data into text data using optical character recognition (OCR) technology. Here, Tesseract OCR is used to analyze the characters in the image and generate digital text data. The input is the received image data, and the output is the extracted text data. 【0773】 Step 4: 【0774】 The server analyzes the extracted text data using natural language processing techniques. Specifically, it uses spaCy and NLTK to perform grammatical analysis and identify important clauses and legal risks. The input is text data extracted by OCR, and the output is important clauses and risk information as a result of the analysis. 【0775】 Step 5: 【0776】 Based on the analysis results, the server uses a generative AI model (e.g., BERT or GPT-3) to generate a review of the contract and legal advice. At this stage, the AI ​​model uses the analysis results as prompts to generate specific revision suggestions and warnings. The input is the analysis results from step 4, and the output is the review and advice provided to the user. 【0777】 Step 6: 【0778】 The server sends the generated reviews and advice back to the terminal. Here, the server sends the output information to the terminal for the user to review. The input is the generated reviews and advice, and the output is the transfer of that data to the terminal. 【0779】 Step 7: 【0780】 The user refers to the provided reviews and advice and modifies the contract as needed. At this stage, the user takes action based on the information presented on the device. The input is the advice provided on the device, and the output is the possible contract modifications the user may make. 【0781】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0782】 This invention combines an emotion engine with a system for processing document information such as contracts provided by users and providing legal advice. To implement this system, the user uploads input information such as contracts using a terminal. The terminal receives the input information from the user and transmits it to the server. 【0783】 The server uses natural language processing technology to analyze the received information. First, it divides the information into contract clauses through text analysis and extracts legal risks. Furthermore, an emotion engine analyzes the user's emotional state. This analysis utilizes behavioral data from when the user interacts with the input information, as well as optional opinions and feedback. 【0784】 The server uses an AI model to generate contract reviews and advice, taking into account the user's emotional state. This allows for the provision of optimized advice tailored to the user's emotional condition. For example, if the server detects that the user is stressed, it can replace specialized terminology in the advice with simpler terms to aid user understanding. 【0785】 The generated review results and legal advice are sent from the server to the terminal. The terminal receives these results and presents them to the user in a visualized format. This may include specific correction suggestions and supplementary explanations to aid understanding based on the user's current emotional state. 【0786】 For example, if a user has doubts about a clause in a contract and feels burdened by that clause, the server uses an emotion engine to identify this emotion. This emotion data is then used to provide information about the risks and areas for improvement of the clause in a way that is more user-friendly. 【0787】 This system allows users to deepen their understanding and accuracy of contract reviews, and improve efficiency. Furthermore, by utilizing sentiment information, it enhances the user experience and supports better legal decision-making. 【0788】 The following describes the processing flow. 【0789】 Step 1: 【0790】 The user uploads the contract file to the system using a terminal. The terminal verifies the information entered by the user and sends this information to the server. 【0791】 Step 2: 【0792】 The server receives the uploaded file. The server identifies the file format (text, PDF, image, etc.) and prepares to process the format as needed. 【0793】 Step 3: 【0794】 The server begins analyzing the input information. First, it uses OCR technology to extract text from the image data. Next, it uses natural language processing technology to divide the contract clauses into sections and analyze their content. 【0795】 Step 4: 【0796】 The server uses the analysis results to set up the initial stage of contract review. At this stage, an initial legal risk analysis and identification of important legal terms are performed. 【0797】 Step 5: 【0798】 The server uses an emotion engine to analyze the user's emotions. It profiles the emotional state based on the user's input methods, work pace, and past feedback data. 【0799】 Step 6: 【0800】 The server uses an AI model that takes the user's emotional state into account to generate a detailed review of the contract and legal advice. This allows for advice and suggestions that are tailored to the user's emotions. 【0801】 Step 7: 【0802】 The server compiles the reviews and advice it generates and creates a report for the user in an appropriate format. The report includes explanations in simple language as needed to aid user understanding. 【0803】 Step 8: 【0804】 The terminal receives the report sent from the server and displays it to the user. The user can then refer to this report and make revisions to the contract. 【0805】 Step 9: 【0806】 The user uploads the revised contract to the system again. The server receives the revised data and performs re-analysis and re-review. This allows for continuous improvement to meet user needs. 【0807】 (Example 2) 【0808】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0809】 In today's world, contract information is provided in diverse formats, and there is a need to accurately analyze its contents and provide legal advice. However, conventional systems lack the accuracy of document analysis and the ability to optimize advice while considering user emotions, resulting in insufficient means to deepen user understanding. Furthermore, the influence of user emotional states on how contract contents are perceived is often underestimated, limiting the effectiveness of advice. Therefore, there is an urgent need to develop a system that can provide accurate and optimal contract information review and legal advice while considering user emotions. 【0810】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0811】 In this invention, the server includes means for analyzing the user's emotional state based on behavioral data and opinion data, means for generating a review of contract information and legal advice based on the analysis results, and means for optimizing the generated review and advice according to the user's emotional state. As a result, the user can receive analysis results of contract information and legal advice that are tailored to their emotional state, deepening their understanding and enabling them to make accurate legal decisions. 【0812】 A "user" refers to an entity that provides contract information to the system and receives analysis results and legal advice. 【0813】 "Input information" refers to document data in various formats, including contracts, that is provided to the system by users and is subject to analysis. 【0814】 "Natural language processing technology" is a technology that allows computers to analyze and understand human language. This technology is used to analyze contract information, divide clauses, and extract risk factors. 【0815】 "Emotional state" refers to the user's emotions and psychological state, and is analyzed based on user behavioral data and opinion data during device operation. 【0816】 "Behavioral data" refers to data about the specific actions users take when manipulating contract information, including mouse movements, click speed, and time spent on a page. 【0817】 "Opinion data" refers to subjective opinions and feedback that users provide to the system, and is used for sentiment analysis by the emotion engine. 【0818】 "Legal advice" refers to expert advice generated based on the analysis of contract information, and includes assessments of legal risks and suggestions for clause revisions. 【0819】 "Optimization" refers to adjusting information according to the user's emotional state and level of understanding, making it easier for the user to understand and more effective. 【0820】 "Review" is the process of analyzing the entire contract information to clarify important items and risk factors. 【0821】 This invention is a system that efficiently processes document information such as contracts provided by users and optimizes legal advice. Users first upload contract information to the system using a terminal. The terminal transmits input information in various formats to the server. To ensure the security of the information, it is recommended that this communication use an encrypted protocol. 【0822】 The server uses software that implements natural language processing technology to analyze the received document information. Specifically, it automatically divides the content of the contract into clauses and examines each clause to clarify the legal risks. Furthermore, it has a built-in emotion engine that analyzes the user's emotional state in real time. User behavior data and opinion data are used in this analysis. 【0823】 Based on the analyzed information, the server utilizes a generative AI model to generate a review of the contract information and legal advice. This generation process allows for adjustments to word choice and advice content based on the user's emotional state. Optimized advice enables users to gain a deeper understanding of the contract. 【0824】 Finally, the reviews and advice generated by the server are sent to the terminal. The terminal provides a mechanism to display this information in an easy-to-understand manner for the user. By including specific revision suggestions and supplementary explanations tailored to the user's sentiments, it supports legal decision-making. 【0825】 For example, when a user expresses concern about a particular contract clause, the server uses an emotion engine to identify that concern and provides advice that clearly indicates risk information and areas for improvement in the clause. In this way, incorporating feedback based on the user's emotional information can enhance the overall usefulness of the system. 【0826】 A concrete example of a prompt message would be something like, "Analyze the risks in this contract and determine if the user is feeling uneasy." 【0827】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0828】 Step 1: 【0829】 The user uploads contract information using their device. 【0830】 The user selects the contract file through the GUI and presses the upload button. 【0831】 Input: Contract files in PDF or Word format. 【0832】 Output: The terminal becomes ready to send contract information to the server. 【0833】 Step 2: 【0834】 The device sends contract information to the server. 【0835】 The device encrypts the contract information uploaded by the user and sends it to the server using a secure protocol (e.g., HTTPS). 【0836】 Input: A contract file uploaded by the user. 【0837】 Output: Encrypted contract information transferred to the server. 【0838】 Step 3: 【0839】 The server receives the contract information and begins analysis. 【0840】 The server uses natural language processing technology to analyze the contract information and divides the contract into clauses. 【0841】 Input: Encrypted contract information. 【0842】 Output: The clauses of the divided contract and the associated initial analysis data. 【0843】 Step 4: 【0844】 The server analyzes the user's emotional state. 【0845】 The server uses an emotion engine to analyze user behavior data (e.g., mouse movements, click speed) and opinion data to determine the user's emotional state. 【0846】 Input: User behavior data and opinion data. 【0847】 Output: Information about the user's emotional state. 【0848】 Step 5: 【0849】 The server generates legal advice. 【0850】 The server uses a generative AI model to review contract information and generate legal advice based on the user's emotional state. 【0851】 Input: Divided contract terms, initial analysis data, user sentiment information. 【0852】 Output: Optimized legal advice and review of contract information. 【0853】 Step 6: 【0854】 The server sends the generated results to the terminal. 【0855】 The server encrypts the generated legal advice and review and sends it to the terminal. 【0856】 Input: Optimized legal advice and review of contract information. 【0857】 Output: Encrypted review and advice data transferred to the terminal. 【0858】 Step 7: 【0859】 The device displays the results to the user. 【0860】 The terminal decrypts the data received from the server and displays it in an easy-to-understand format for the user. This includes suggested corrections and supplementary explanations. 【0861】 Input: Review and advice data sent from the server. 【0862】 Output: Analysis results and optimized legal advice displayed to the user. 【0863】 (Application Example 2) 【0864】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0865】 Current legal document review systems often present users with highly specialized and complex information, leading to misunderstandings and anxieties. Furthermore, the inability to respond flexibly to users' emotional states can make the system inconvenient to use. Additionally, in situations such as electronic payments, where terms of service and contractual documents are complex, there is a need for improved user understanding and enhanced decision-making processes. 【0866】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0867】 In this invention, the server includes means for receiving diverse forms of input information provided by the user, means for analyzing the input information using natural language processing technology, and means for measuring the user's emotional state using sentiment analysis technology. This makes it possible to generate reviews and legal advice based on the analysis results of contract documents, and further optimize the advice according to the user's emotional state. 【0868】 "Input information in various formats" refers to document data from users that have different formats and content, such as contract documents and terms of service. 【0869】 "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate language that humans use on a daily basis. 【0870】 "Legal advice" refers to information that provides users with legal opinions or recommendations regarding contract documents, etc. 【0871】 "Emotion analysis technology" is a technology that analyzes and evaluates a user's emotional state based on their input and actions. 【0872】 An "AI model" is a software model that uses artificial intelligence to analyze data and learn and apply patterns and trends. 【0873】 A "review" is a report that summarizes the results of a detailed examination and analysis of contract documents or terms of service. 【0874】 "Optimization" is the process of making adjustments and improvements to obtain the most effective and efficient results under specific conditions. 【0875】 This invention is a system designed to make documents related to the use of electronic payment services easier for users to understand, and it provides legal advice using natural language processing and sentiment analysis technologies. The server and terminal work in conjunction with each other. 【0876】 First, users upload various types of input information, such as contract documents and terms of service, using their devices. This data is sent to the server. The server uses natural language processing engines such as "SpaCy" and "BERT" to analyze the documents in detail and extract clauses and risk factors. For sentiment analysis, it uses an "NLP Sentiment Analysis API" to evaluate the emotional state from the user's operation data. 【0877】 The server further utilizes AI generation models such as "GPT" to generate advice tailored to the user's emotional state. This simplifies technical terms and complex expressions, aiding understanding. This optimized advice is then sent back to the terminal and presented to the user in a visualized form. 【0878】 For example, if a user feels uneasy about the "cancellation policy" within the terms of service of an electronic payment service, sentiment analysis technology can identify that uneasy point, and the server will provide a clear explanation based on that. This allows the user to understand the terms more clearly. 【0879】 An example of a prompt to be input into the generation AI model is: "For specific clauses in the document uploaded by the user, generate optimization advice based on sentiment data, along with risk analysis results, and present it in an easy-to-understand format." This allows users to gain the knowledge necessary to use electronic payment services with confidence. 【0880】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0881】 Step 1: 【0882】 The user uploads the contract document for the electronic payment service using a terminal. The terminal prepares to send the document data to the server. In this step, the user's contract document data is the input, and it is ready to be sent to the server as output. 【0883】 Step 2: 【0884】 The server analyzes document data received from the terminal using a natural language processing engine. Using technologies such as "SpaCy" and "BERT," the input data is divided into clauses, and important risk factors are extracted. As output, analysis data for each clause is generated and used for the next processing step. 【0885】 Step 3: 【0886】 The server applies emotion analysis technology to evaluate the user's emotional state. Using tools such as the "NLP Emotion Analysis API," it analyzes emotions input from the user's operation data and outputs specific states (e.g., anxiety, tension). This information is used in the optimization process. 【0887】 Step 4: 【0888】 The server uses a generative AI model to generate legal advice based on the terms of service. The server takes sentiment analysis results into consideration and receives a prompt message in the form of "Generate optimized advice based on sentiment data, along with risk analysis results, for specific clauses in the document uploaded by the user, and present it in an easy-to-understand manner," to output the optimized advice. 【0889】 Step 5: 【0890】 Optimized advice and analysis results are sent from the server to the terminal. The terminal presents this information to the user in a visually and easily understandable format. The user reviews this information and uses it to make their own decisions. As output, the final advice data is provided in a format that is easy for the user to understand. 【0891】 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0892】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0893】 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414. 【0894】 Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion. 【0895】 Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together. 【0896】 These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression. 【0897】 The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become. 【0898】 Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant. 【0899】 The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more." 【0900】 The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values. 【0901】 The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format. 【0902】 In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data. 【0903】 In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56. 【0904】 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. 【0905】 Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56. 【0906】 The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory. 【0907】 The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor. 【0908】 Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources. 【0909】 Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose. 【0910】 The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above. 【0911】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference. 【0912】 The following is further disclosed regarding the embodiments described above. 【0913】 (Claim 1) 【0914】 A means for receiving input information in various formats provided by the user, 【0915】 The means for analyzing the aforementioned input information using natural language processing technology, 【0916】 A means of generating contract reviews and legal advice based on analysis results, 【0917】 A means of providing the generated reviews and advice to the user, 【0918】 A system that includes this. 【0919】 (Claim 2) 【0920】 The system according to claim 1, comprising means for extracting important clauses and risk factors based on the results of contract analysis. 【0921】 (Claim 3) 【0922】 The system according to claim 1, comprising means for receiving a revised contract from a user and performing re-analysis and re-review. 【0923】 "Example 1" 【0924】 (Claim 1) 【0925】 A means for receiving input information in various formats provided by the user, 【0926】 The means for extracting text data from the aforementioned input information using optical character recognition technology, 【0927】 A means of analyzing extracted text data using natural language processing techniques, 【0928】 A means to identify key clauses of a contract based on the analysis results, extract legal risks and issues, and generate legal advice. 【0929】 A means of providing the generated reviews and advice to the user, 【0930】 A means of receiving, re-analyzing, and re-reviewing user-modified contract documents, 【0931】 A system that includes this. 【0932】 (Claim 2) 【0933】 The system according to claim 1, comprising the extraction of text data using optical character recognition technology. 【0934】 (Claim 3) 【0935】 The system according to claim 1 for identifying important clauses and risk factors of a contract. 【0936】 "Application Example 1" 【0937】 (Claim 1) 【0938】 A means for receiving input information in various formats provided by the user, 【0939】 The means for analyzing the aforementioned input information using natural language processing technology, 【0940】 A means of generating contract reviews and legal advice based on analysis results, 【0941】 A means of providing the generated reviews and advice to the user, 【0942】 A means of obtaining input data through photographing contract documents, 【0943】 A method using character recognition technology to extract character data from captured images, 【0944】 A means of providing users with immediate feedback and legal evaluations, 【0945】 A system that includes this. 【0946】 (Claim 2) 【0947】 The system according to claim 1, comprising means for extracting important clauses and risk factors based on the results of contract analysis. 【0948】 (Claim 3) 【0949】 The system according to claim 1, comprising means for receiving a revised contract from a user and performing re-analysis and re-review. 【0950】 "Example 2 of combining an emotion engine" 【0951】 (Claim 1) 【0952】 A means for receiving input information in various formats provided by the user, 【0953】 The means for analyzing the aforementioned input information using natural language processing technology, 【0954】 A means for analyzing a user's emotional state based on behavioral data and opinion data, 【0955】 A means for generating a review of contract information and legal advice based on the analysis results, 【0956】 A means for optimizing the generated reviews and advice according to the user's emotional state, 【0957】 Means for providing the generated reviews and advice to the user, 【0958】 A system that includes this. 【0959】 (Claim 2) 【0960】 The system according to claim 1, comprising means for extracting important items and risk factors based on the results of analyzing contract information. 【0961】 (Claim 3) 【0962】 The system according to claim 1, comprising means for receiving modified contract information from a user and performing re-analysis and re-review. 【0963】 "Application example 2 when combining with an emotional engine" 【0964】 (Claim 1) 【0965】 A means for receiving input information in various formats provided by the user, 【0966】 The means for analyzing the aforementioned input information using natural language processing technology, 【0967】 A means of generating contract document reviews and legal advice based on analysis results, 【0968】 A means of measuring a user's emotional state using emotion analysis technology, 【0969】 A means of using AI models to optimize advice according to the user's emotional state, 【0970】 A means of providing the generated reviews and advice to the user, 【0971】 A system that includes this. 【0972】 (Claim 2) 【0973】 The system according to claim 1, comprising means for extracting important elements and risk factors based on the results of analyzing a contract document and for interpreting them while taking into account the user's emotional state. 【0974】 (Claim 3) 【0975】 The system according to claim 1, comprising means for receiving a revised contract document from a user, re-analyzing and re-evaluating it, and again providing advice that takes the user's emotional state into consideration. [Explanation of symbols] 【0976】 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

[Claim 1] A means for receiving input information in various formats provided by the user, The means for analyzing the aforementioned input information using natural language processing technology, A means of generating contract reviews and legal advice based on analysis results, A means of providing the generated reviews and advice to the user, A system that includes this. [Claim 2] The system according to claim 1, comprising means for extracting important clauses and risk factors based on the results of contract analysis. [Claim 3] The system according to claim 1, comprising means for receiving a revised contract from a user and performing re-analysis and re-review.

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