System

Abstract

A system is provided.SOLUTION: A system comprising: means for periodically obtaining a latest version of a contract or agreement; means for comparing the obtained contract or agreement with a previous version to identify differences; means for analyzing the identified differences to classify and assess risk; and means for visually presenting the classified and assessed risk to a user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Currently, many users find it difficult to understand the details of contracts and terms and conditions. In particular, terms and conditions for services provided online are frequently updated, and changes and risks are often overlooked. Even when entering into individual contracts, users often enter into them without fully understanding the risks, which can lead to high levels of disadvantage. Furthermore, if users wish to change the content of a contract, the process is complicated and time-consuming. There is a need for a system that can solve these problems and enable users to enter into contracts in a safer and more transparent manner. [Means for solving the problem]

[0005] The present invention provides a system for automating the acquisition, comparison, analysis, and risk assessment of contracts and clauses, and visually presenting them to a user. Specifically, the system includes the following means:

[0006] 1. A system that includes a means for periodically obtaining the latest version of a contract or clause, a means for comparing the obtained contract or clause with past versions to identify differences, a means for analyzing the identified differences and classifying and assessing risks, and a means for visually presenting the classified and assessed risks to the user.

[0007] 2. It includes a means for users to input ratings for the contract contents, a means for saving the input rating data and performing statistical processing in real time, and a means for disclosing the aggregated rating data to other users.

[0008] 3. Includes a means for scanning or uploading the contents of individual contracts, a means for extracting the text of the uploaded contracts, a means for analyzing the extracted text data and assessing the risks, and a means for providing the assessed risk information to the user.

[0009] 4. Includes a means for the user to input changes to the contract content if the user wishes to do so, a means for automatically generating a new draft contract based on the entered changes, and a means for providing the generated draft contract to the user and making it available for download.

[0010] This allows users to easily understand the contract details and associated risks, enabling them to make appropriate decisions. Furthermore, changes to contract details can be made efficiently, reducing the burden on users.

[0011] A "contract" is a written document concluded under specific conditions and rules that clarifies the rights and obligations of the parties.

[0012] "Terms and Conditions" means a document that contains the standard conditions and regulations for services or transactions and forms part of a contract.

[0013] "Risk" refers to uncertain factors or events that may potentially occur in a contract or transaction and that have the potential to cause disadvantage or damage.

[0014] "Comparison" is an operation that juxtaposes two or more documents or data to clarify their differences and similarities.

[0015] A "difference" is a difference found when comparing two documents or data, specifically any changes or additions.

[0016] "Risk assessment" is the process of analyzing how significant a particular risk is and assessing its classification and impact.

[0017] "User" means an individual or organization that uses the system and understands, evaluates, and proposes changes to the contract and terms.

[0018] "Input" refers to the operation by which a user provides data or information to a system, and is performed using input devices such as a keyboard or mouse.

[0019] "Storage" is the act of recording data or information in a memory or device in a form that can be accessed later.

[0020] "Real-time" means that data is collected, processed, and displayed immediately, without delay.

[0021] "Scanning" is the act of converting a physical document or image into electronic data, usually using a scanner.

[0022] "Text extraction" is the process of extracting character information from non-text data such as images or PDFs and extracting it as text data.

[0023] "Automatic generation" is the process by which a system generates documents or data independently without user intervention.

[0024] "Downloading" is the act of transferring and storing data or files from a remote server to a local device. [Brief explanation of the drawings]

[0025] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0026] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0027] First, the terms used in the following description will be explained.

[0028] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0029] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0030] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0031] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0032] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0033] [First embodiment]

[0034] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0035] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0036] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0037] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0038] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0039] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0040] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0041] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0042] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0043] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0044] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0045] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0046] The present invention is a system designed to enable users to easily understand the contents of contracts and terms and conditions, and is realized using the following means.

[0047] Overall system configuration

[0048] This system consists of three main components: a server, a terminal, and a user. The server manages and analyzes data on contracts and clauses, while the terminal provides the user interface. Users use the terminal to evaluate, upload, and input proposed changes to contracts and clauses.

[0049] Understanding changes to contracts and terms and conditions and clarifying risks

[0050] The server periodically retrieves the latest versions of contracts and terms and conditions published on specific websites from the Internet. The server stores this data in storage and compares it with previous versions. Changes are identified as differences as a result of the comparison, and are classified and analyzed using a risk assessment algorithm. The analyzed risk information is visually presented to the user. For example, if a provision regarding data sharing is added to the new terms of use of a social media platform, that information is highlighted.

[0051] Evaluation and disclosure of contract details

[0052] Users use their devices to input their evaluations of contract details. For example, they can input an evaluation score indicating whether they were satisfied or dissatisfied with a contract with a certain internet service provider. The device sends this evaluation to a server, which stores the evaluation data in a database. The server statistically processes the evaluations of all users, generates information such as average scores and frequently occurring comments, and makes this information public to other users. Other users can use this public information as a reference when considering the contract details.

[0053] Individual contract risk assessment

[0054] Users use their devices to scan or upload individual contracts, such as land sales or building construction contracts, as electronic files. The devices then send the uploaded contracts to a server. The server then uses OCR technology to extract text data from the contracts, analyzes the text data, and performs a risk assessment. The assessment results identify specific risks in the contract (such as construction delays or additional costs) and provide them to the user.

[0055] Drafting and providing contract amendment proposals

[0056] If a user wishes to change the contract details, they use their device to input the specific details. For example, if they wish to shorten the contract period for building construction work, they can input this information. The device then sends this information to the server, which then automatically generates a new contract based on the proposed changes. The generated contract draft is then provided to the user for final confirmation and download.

[0057] Specific examples

[0058] For example, if a user is considering new terms of use for an online storage service, the server retrieves the latest terms of use, compares them with previous terms, and identifies any changes. If the changes relate to the handling of personal information, the server analyzes the risks in detail and notifies the user. The user can then use this information to consider using the service.

[0059] In addition, if a user uploads a contract for the construction of a new building, the server analyzes the contract and notifies the user of specific risks (e.g., construction delays, additional costs), allowing the user to review the contract and, if necessary, input proposed changes and generate a new contract.

[0060] In this way, the present invention makes it easier for users to understand the contents of contracts and terms and conditions, helps them understand potential risks, and provides a method for efficiently making changes to the contract contents.

[0061] The processing flow will be explained below.

[0062] Understanding changes to contracts and terms and conditions and clarifying risks

[0063] Step 1:

[0064] The server crawls the specified website URL list to retrieve the latest version of the contract or terms and conditions, and stores the retrieved data in storage.

[0065] Step 2:

[0066] The server uses a difference detection library (e.g., diff-match-patch) to compare the latest version of the contract or clause with the previous version and identify the changes.

[0067] Step 3:

[0068] The server analyzes the identified changes and classifies and assesses the risk using a risk assessment algorithm. For example, if a change related to the handling of personal information is detected, the server classifies the risk as high.

[0069] Step 4:

[0070] The server stores the analysis results in a database and prepares a visual display of the risks when accessed by the user.

[0071] Step 5:

[0072] When a user accesses the risk information page, the device visually displays the changes and the risks involved using color coding, etc.

[0073] Evaluation and disclosure of contract details

[0074] Step 1:

[0075] The user uses an input form on the terminal to input an evaluation score and comments on the contract contents.

[0076] Step 2:

[0077] The terminal transmits the evaluation score and comments entered by the user to the server.

[0078] Step 3:

[0079] The server stores the received evaluation data in a database and performs real-time statistical processing, such as calculating the average evaluation score and frequently occurring comments.

[0080] Step 4:

[0081] The server visualizes the results and updates the evaluation page so that other users can see them.

[0082] Step 5:

[0083] When other users access the rating page, the terminal displays the aggregated rating scores and comments.

[0084] Individual contract risk assessment

[0085] Step 1:

[0086] The user uses the upload function on the device to scan the contract or upload it in PDF format.

[0087] Step 2:

[0088] The terminal transmits the uploaded contract to the server.

[0089] Step 3:

[0090] The server uses OCR (Optical Character Recognition) software to extract text data from the contract.

[0091] Step 4:

[0092] The server analyzes the extracted text data and identifies risks using a risk assessment algorithm.

[0093] Step 5:

[0094] The server organizes the risk information and stores it in a database in order to provide the evaluation results to the user.

[0095] Step 6:

[0096] The terminal visually presents the risk assessment results to the user, for example by highlighting specific risk areas.

[0097] Drafting and providing contract amendment proposals

[0098] Step 1:

[0099] The user uses the input form on the terminal to input the changes he or she wishes to make to the contract contents.

[0100] Step 2:

[0101] The terminal transmits the input desired changes to the server.

[0102] Step 3:

[0103] The server uses an automated contract generation library to generate a new draft contract based on the user's input.

[0104] Step 4:

[0105] The server checks the generated draft contract using an internal review system and makes corrections as necessary.

[0106] Step 5:

[0107] The server stores the revised draft contract in a database in order to provide it to the user.

[0108] Step 6:

[0109] The terminal will visually display the new draft contract to the user and make it available for download if desired.

[0110] In this way, by explaining each processing step separately, it becomes easier to understand the specific operation of the system.

[0111] Example 1

[0112] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0113] The contents of contracts and terms and conditions are complex and contain many technical terms, making them difficult for general users to understand. Furthermore, tracking changes to contracts and terms and assessing risks is time-consuming and requires specialized knowledge. In addition, there are limited ways for users to share their assessments of contract contents with other users. This makes it difficult for users to understand contract contents, grasp risks, and make decisions based on the assessments of other users.

[0114] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0115] In this invention, the server includes means for periodically obtaining the latest version of the contract or terms and conditions, means for comparing the obtained contract or terms and conditions with past versions to identify differences, means for analyzing the identified differences and classifying and assessing risks, means for visually presenting the classified and assessed risks to the user, means for extracting text data from the contract using machine reading comprehension technology, means for the user to input changes to the contract, and means for automatically generating a new draft contract based on the input changes. This allows the user to easily understand changes and risks in the contract or terms and conditions, efficiently create a contract that reflects their own opinions, and also enables them to refer to evaluation information from other users.

[0116] A "contract" is a document that sets out the rights and obligations between the parties under a particular contract.

[0117] "Terms and conditions" are documents that set out the standard terms and conditions offered by a company or organization.

[0118] "Latest version" means the most recent version of the agreement or terms and conditions.

[0119] "Means of collection" refers to methods and technologies for automatically collecting data.

[0120] "Means for comparing and identifying differences" refers to methods and techniques for comparing different versions of contracts or terms and conditions and identifying changes.

[0121] "Means for classifying and assessing risks" refers to methods and techniques for analyzing changes to contracts and clauses to identify, classify, and assess potential risks.

[0122] "Visual presentation means" refers to methods and technologies that visually display analysis results to users in an easy-to-understand manner.

[0123] "Machine reading comprehension technology" refers to technology for automatically reading and understanding text data.

[0124] "Means for extracting text data" refers to methods or techniques for extracting text information from scanned images or uploaded files.

[0125] "Means for users to input changes to the contract" refers to the methods and technologies that allow users to input their desired changes to the contract into the system.

[0126] "Means for automatically generating a new draft contract" refers to methods or technologies that automatically create a new contract based on changes entered by the user.

[0127] The present invention is a system designed to enable users to easily understand the contents of contracts and terms and conditions, and is composed of three main elements: a server, a terminal, and a user.

[0128] Server Roles

[0129] The server manages and analyzes data on contracts and clauses. Specifically, the server periodically retrieves the latest versions of contracts and clauses published on specific websites from the Internet and stores the retrieved data in storage. Contract data is stored in an AWS (registered trademark) S3 bucket, and the program performs web scraping using Python and the Beautiful Soup library. The server also compares the old and new contracts to identify differences and calculates text differences using the diff-match-patch library. It then uses the NLTK library to classify and assess the risk of changes using a risk assessment algorithm. The assessed risk information is visually presented to the user. The front end uses React to highlight the results.

[0130] Device Role

[0131] The terminal provides a user interface, allowing users to evaluate, upload, and input proposed changes to the contract contents. For example, when a user scans or uploads an individual contract as an electronic file, the terminal sends this data to the server. The server uses OCR technology (Tesseract OCR) to extract text data from the contract and analyzes the text data to evaluate risk. If the user wishes to make changes to the contract contents, they can use the terminal to enter the specific details, which are then sent to the server. The server then automatically generates a new contract based on the proposed changes. The document is generated using a specific template, and can be downloaded after final confirmation.

[0132] User Roles

[0133] Users operate the system to evaluate their own contracts and input proposals for changes to the contract and terms. For example, they can use an evaluation form to input their level of satisfaction with a contract with an internet service provider. The evaluation results are sent to a server, where they are statistically processed in real time and made available to other users.

[0134] Specific examples

[0135] For example, if a user is considering new terms of use for an online storage service, the server retrieves the latest terms of use, compares them with previous terms, and identifies any changes. If the changes relate to the handling of personal information, the server analyzes the risks in detail and notifies the user. The user can then use this information to consider using the service.

[0136] In addition, when a user uploads a contract for constructing a new building, the server analyzes the contract, identifies risks (e.g., construction delays, additional costs) and notifies the user, who can then review the contract and, if necessary, input proposed changes to generate a new contract.

[0137] Prompt Sentence Examples

[0138] An example of a prompt to be input to a generative AI model is, "I would like to develop a system that analyzes contract contents, identifies risks, and presents them visually. This system retrieves the latest versions of contracts and terms and conditions from the Internet and compares them with previous versions. It uses a risk assessment algorithm to classify and analyze risks by category and notify the user of the results."

[0139] In this way, the present invention makes it easier for users to understand the contents of contracts and terms and conditions, helps them understand potential risks, and provides a method for efficiently making changes to the contract contents.

[0140] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0141] Step 1:

[0142] The server periodically retrieves the latest version of the contract or terms and conditions from a specific website on the Internet. Specifically, it uses Python's Beautiful Soup library to retrieve HTML content from a specified URL and extracts links to the new contract or terms and conditions. The retrieved data is saved in text format.

[0143] Enter: Website URL

[0144] Output: Text data of the latest contracts and terms and conditions

[0145] Step 2:

[0146] The server stores the acquired contract and clause data in cloud storage such as an AWS S3 bucket, which is used for later comparison and analysis.

[0147] Input: Text data of the latest contracts and terms and conditions

[0148] Output: File saved in cloud storage

[0149] Step 3:

[0150] The server compares the old and new contracts and clauses and identifies the changes as differences. This is achieved by calculating the text differences using the diff-match-patch library. This difference data becomes the basis for change analysis.

[0151] Input: Text data of past and latest contracts and terms and conditions

[0152] Output: Diff data of changes

[0153] Step 4:

[0154] The server analyzes the delta data and uses a risk assessment algorithm to classify and assess the risk. It uses the NLTK library to perform text analysis to identify the risks of the changes. This risk information is then categorized.

[0155] Input: Difference data of changes

[0156] Output: Assessed risk information

[0157] Step 5:

[0158] The server visually presents the assessed risk information to the user, and a front-end is built using React to highlight changes and risks.

[0159] Input: Assessed risk information

[0160] Output: Visual risk information displayed in the user interface

[0161] Step 6:

[0162] The user uses a terminal to input their evaluation of the contract contents, and enters the evaluation score and comments using an HTML form, and the data is sent to the server.

[0163] Input: User rating score and comments

[0164] Output: Rating data sent to the server

[0165] Step 7:

[0166] The server statistically processes all users' rating data and compiles average scores and frequently occurring comments in real time. It uses the Pandas library to aggregate the rating data and generate statistical information.

[0167] Input: Multiple user rating data

[0168] Output: Aggregated average scores and frequently occurring comments

[0169] Step 8:

[0170] The server then publishes the aggregated evaluation data to other users, who can use the published information as a reference when considering contract details.

[0171] Input: Aggregated average rating score and frequently occurring comments

[0172] Output: Aggregate information displayed in the user interface

[0173] Step 9:

[0174] The user uses the terminal to scan or upload the individual contract in electronic file format, and the terminal sends the uploaded data to the server.

[0175] Input: Scanned or uploaded agreement

[0176] Output: Agreement data sent to the server

[0177] Step 10:

[0178] The server extracts text data from the uploaded contract using OCR technology. It uses the Tesseract OCR library to extract text from images.

[0179] Input: Image data of the uploaded contract

[0180] Output: Extracted text data

[0181] Step 11:

[0182] The server analyzes the extracted text data and performs risk assessment. It uses a risk assessment algorithm to identify specific risks (e.g., construction delays, additional costs).

[0183] Input: Extracted text data

[0184] Output: Assessed risk information

[0185] Step 12:

[0186] The server provides the assessed risk information to the user, who is then notified and displayed in a visual interface.

[0187] Input: Assessed risk information

[0188] Output: Risk information provided to the user

[0189] Step 13:

[0190] If a user wishes to change the contents of their contract, they use their device to input the specific changes, and the input data is sent to the server.

[0191] Input: User requests to change contract details

[0192] Output: Changes sent to the server

[0193] Step 14:

[0194] The server automatically generates a new contract based on input from the user, creates a new contract using a specific template, and provides it to the user.

[0195] Input: Proposed changes to the contract contents desired by the user

[0196] Output: The new contract that is generated.

[0197] In this way, the present invention provides a system that makes it easier for users to understand the contents of contracts and terms and conditions, and assists in understanding and evaluating potential risks.

[0198] (Application example 1)

[0199] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0200] There is a need for a system that can quickly identify changes and risks in contracts and clauses, allowing users to easily understand them. However, existing systems require users to manually compare and analyze contracts and clauses, which is extremely labor-intensive. Furthermore, risk assessment of contract content and feedback information from other users are not centrally provided. This can lead to delays and inaccuracies in understanding contract content and appropriate risk assessment. This invention aims to solve these issues by extracting text from contracts and clauses, analyzing risks, visually presenting them through a user interface, and performing detailed analysis using a generative AI model.

[0201] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0202] In this invention, the server includes: means for periodically obtaining the latest version of the contract or terms and conditions; means for comparing the obtained contract or terms and conditions with previous versions to identify differences; means for analyzing the identified differences and classifying and assessing risks; means for visually presenting the classified and assessed risks to the user; means for the user to photograph or upload the contract or terms and conditions; means for using optical character recognition technology to extract text data; means for analyzing the extracted text data and assessing risks; and means for providing a user interface for visually displaying the assessed risk information to the user. This allows the user to quickly understand changes and risks in the contract or terms and conditions and perform appropriate risk assessments. Furthermore, a generative AI model is used to perform detailed analysis of the contract content, which is expected to promote user understanding and improve assessment accuracy.

[0203] "Means for periodically obtaining the latest version of contracts or terms and conditions" refers to technology that automatically collects the latest information on contracts and terms and conditions that are published on the Internet.

[0204] "Means for identifying differences by comparing acquired contracts or terms and conditions with past versions" refers to a technology that compares the latest collected contracts and terms and conditions with past versions to clarify changes.

[0205] "Means for analyzing identified differences and classifying and assessing risks" refers to algorithms or programs for analyzing changes and identifying, classifying, and assessing the risks.

[0206] "Means for visually presenting classified and assessed risks to the user" refers to a technology that displays analyzed risk information in an easy-to-understand manner through a user interface.

[0207] "Means for users to photograph or upload contracts or terms and conditions" refers to technology that allows users to send images or files of contracts or terms and conditions to the system using a smartphone or computer.

[0208] "Means using optical character recognition technology to extract text data" refers to OCR (optical character recognition) technology to extract text information from uploaded images.

[0209] The "means for analyzing extracted text data and assessing risk" refers to a program or algorithm for analyzing the contract content based on the extracted text information and assessing the risk.

[0210] "Means for providing a user interface for visually displaying assessed risk information to a user" refers to an interface technology for displaying assessment results in a form that is visually easy for a user to understand.

[0211] The "means for users to input evaluations of the contract contents" refers to an interface that allows users to input their satisfaction and opinions regarding the contract contents into the system.

[0212] "Means for saving input evaluation data and performing statistical processing in real time" refers to technology that saves evaluation data from users and analyzes and processes it in real time.

[0213] "Means for disclosing aggregated evaluation data to other users" refers to technology that allows analyzed and processed evaluation data to be disclosed and shared with other users.

[0214] "Means of inputting the contents of a contract or terms and conditions as prompt sentences using a generative AI model" refers to a technology that uses natural language processing technology to formalize the contents of a contract or terms and conditions as prompt sentences.

[0215] "Means for performing detailed analysis of contract content using a generative AI model" refers to technology that uses a generative AI model to perform detailed analysis of contract content and provide the results.

[0216] This invention is a system designed to help users easily understand the contents of contracts and terms and conditions. It consists of three main elements: a server, a terminal, and a user. The system's purpose is to quickly identify changes and risks in contracts and terms and conditions and visually present them to users. It can also analyze contract contents using a generative AI model and provide detailed information.

[0217] Server Roles

[0218] The server periodically retrieves the latest version of the contract or terms and conditions from the Internet and stores it in a specific storage device. At this time, the server compares the previous version with the new version and identifies the changes as differences. The identified differences are analyzed using a risk assessment algorithm, and the risks are classified and assessed. This risk information is presented visually to the user.

[0219] The server also uses optical character recognition (OCR) technology to extract text data from contracts and clauses uploaded by users from their devices. The extracted text data is then analyzed in detail using a generative AI model. The analyzed risk information is then sent to the device.

[0220] Device Role

[0221] Users use their smartphone or computer to take a photo of the contract or terms and conditions or upload them as a file. The device then sends this data to the server, which acts as a trigger for OCR processing. The risk information and analysis results received from the server are displayed visually through the device's user interface. Users can easily understand the contract contents based on the visually presented risk information.

[0222] Users can also enter ratings for the contract details, and the rating data is sent to the server in real time. The server stores the rating data and performs statistical processing. This generates and publishes rating information that can be used as reference by other users.

[0223] User operations

[0224] When loading a contract or clause, the user can take a photo using the device's camera or upload an existing file. The device then sends this to the server, which receives risk assessment and analysis results and displays them in an easy-to-read format. The user can also enter their satisfaction with the contract content as an evaluation, and this feedback information is also saved on the server.

[0225] Hardware and software used

[0226] Hardware: smartphones, tablets, computers

[0227] software:

[0228] GOOGLE FI (registered trademark) rebase (backend service)

[0229] OCR library (e.g. Tesseract OCR)

[0230] TENSORFLOW(R) Lite (Natural Language Processing using Generative AI Models)

[0231] React Native (Mobile Frontend)

[0232] Examples of concrete examples and prompts

[0233] For example, if a user is considering new terms of use for an online storage service, they can take a photo of the new terms of use with their smartphone and upload it. The server will then compare the latest terms with the previous terms to identify any changes. If the changes relate to the handling of personal information, the server will perform a detailed analysis of the risks involved and notify the user. The user can then use this information to consider using the service.

[0234] Example prompt sentence:

[0235] "The changes in the terms and conditions of the new online storage service relate to the handling of personal information, so please assess the risks involved."

[0236] This allows users to quickly understand changes and risks in contracts and terms and conditions, and to conduct appropriate risk assessments. A generative AI model is also used to perform detailed analysis of contract content, which is expected to promote user understanding and improve assessment accuracy.

[0237] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0238] Flow of the system program that realizes the application example

[0239] Step 1:

[0240] Users can photograph or upload contracts and terms and conditions

[0241] Users use their smartphones or computers to take a photo of the contract or terms and conditions or upload an existing file. This input data is in the form of an image or electronic file and is sent from the device to the server.

[0242] Step 2:

[0243] The server extracts the text data

[0244] The server receives uploaded images and files and extracts text data using OCR (Optical Character Recognition) technology. At this stage, the input is image or file format data, and the output is text data.

[0245] Step 3:

[0246] The server compares with the previous version

[0247] The server compares the extracted text data with past versions and performs a difference calculation to identify changes. The input is the current text data and the past text data, and the output is a list of changes.

[0248] Step 4:

[0249] Server analyzes identified differences

[0250] The server runs a risk assessment algorithm based on the identified differences, including a generative AI model. The input is a list of changes, and the output is a risk assessment result.

[0251] Step 5:

[0252] The server sends the risk assessment information to the user

[0253] The server sends the analyzed risk assessment information to the terminal. The input is the risk assessment result, and the output is data that can be displayed visually.

[0254] Step 6:

[0255] The device visually displays risk information

[0256] The terminal visually presents the risk assessment information received from the server to the user. In this step, the user interface displays the risk information in an easy-to-understand format. The input is the visualization data sent from the server, and the output is the display on the screen.

[0257] Step 7:

[0258] The user enters their evaluation of the contract contents

[0259] Users input their evaluation of the contract details through their device. The evaluation data is entered in the form of comments and scores and is sent from the device to the server.

[0260] Step 8:

[0261] The server stores and processes the evaluation data

[0262] The server stores the evaluation data received from users and performs statistical processing in real time. The input is the user evaluation data, and the output is the statistical processing result.

[0263] Step 9:

[0264] The server exposes the rating data to other users

[0265] The server displays the statistically processed evaluation data in a specific interface to make it public to other users. The input is the statistically processed evaluation data, and the output is public information.

[0266] Specific examples of actions and prompt format

[0267] For example, when a user reviews new terms of service for an online storage service, they might use the following prompt:

[0268] "The changes in the terms and conditions of the new online storage service relate to the handling of personal information, so please assess the risks involved."

[0269] By inputting this prompt into the generative AI model, users can quickly receive a specific risk assessment, significantly reducing the burden on users and making it easier for them to evaluate and understand the contract contents.

[0270] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0271] The present invention is a system that presents changes to contracts and terms and conditions to users, evaluates and notifies them of the risks involved, and dynamically adjusts the interface based on user emotions. Specifically, the system is implemented as follows:

[0272] Overall system configuration

[0273] This system consists of a server, a terminal, a user, and an emotion engine. The server is responsible for data management and analysis of contracts and terms and conditions, and emotional data processing, while the terminal provides the user interface. The emotion engine recognizes user emotions in real time and optimizes system operation based on them.

[0274] Understanding changes to contracts and terms and conditions and clarifying risks

[0275] The server periodically retrieves the latest version of the contract or clause from the website. The retrieved data is compared with previous versions to identify any changes. The server analyzes these changes and uses a risk assessment algorithm to classify and assess the risks. The classified and assessed risk information is stored in a database for visual presentation to the user.

[0276] When a user accesses a risk information page, the device displays the changes and their associated risks in a visually easy-to-understand format, including color coding. If the user expresses an emotional reaction to a particular section, the device's emotion engine analyzes the data and dynamically adjusts the display. For example, if the user is extremely anxious, the device will provide more detailed information and advice on that section.

[0277] Evaluation and disclosure of contract details

[0278] Users input their ratings of the contract details through their terminals. The entered rating data is sent to the server and stored in a database. The server then statistically processes the rating data in real time and makes the results available to other users.

[0279] The emotion engine recognizes the emotion a user is feeling when entering a rating and incorporates that emotion data into the rating process. For example, if a user has very positive emotions, their rating may be weighted higher.

[0280] Individual contract risk assessment

[0281] Users scan or upload individual contracts as electronic files. The device receives the documents and sends them to the server. The server uses OCR technology to extract text from the contract and analyzes it with a risk assessment algorithm. The results are then reported to the user, and the necessary risk information is displayed on the device.

[0282] The emotion engine recognizes the emotions users express while viewing risk information and adjusts how the risk is presented based on that emotion. For example, if a user expresses surprise or disappointment, additional explanations or solutions will be provided for that risk.

[0283] Drafting and providing contract amendment proposals

[0284] If the user wishes to change the contract terms, they enter the changes. The device sends the changes to the server, which then uses an automated contract generation library to generate a new contract draft. The draft is then reviewed and provided to the user.

[0285] The emotion engine also takes into account the user's emotions when drafting contract changes, helping to reduce stress. For example, if the user is feeling impatient, it will provide operational guidance and real-time support.

[0286] Specific examples

[0287] For example, if a user is considering new terms of use for an online storage service, the server retrieves the latest terms and compares them with previous terms to identify any changes. If the changes relate to the handling of personal information, the server performs a detailed analysis of the risks and notifies the user. If the information makes the user feel uneasy, the emotion engine recognizes this emotion and provides more detailed information or additional advice.

[0288] For example, if a user uploads a contract for constructing a new building, the server analyzes the contract and notifies the user about specific risks (e.g., construction delays, additional costs). If the user expresses surprise or concern, the emotion engine will detect this and provide more detailed countermeasures for the risk.

[0289] As described above, the present invention makes it easier to understand the contents of contracts and terms and conditions while taking into account the user's emotions, helps to identify potential risks, and provides a method for efficiently changing the contents of contracts.

[0290] The processing flow will be explained below.

[0291] Understanding changes to contracts and terms and conditions and clarifying risks

[0292] Step 1:

[0293] The server periodically crawls the specified list of websites to retrieve the latest version of the contract or terms and conditions, and stores the retrieved data in storage.

[0294] Step 2:

[0295] The server uses a difference detection library (e.g., diff-match-patch) to compare the latest version of the contract or clause with the previous version and identify the changes.

[0296] Step 3:

[0297] The server then analyzes the identified changes with a risk assessment algorithm to classify and assess the risk. For example, if there is a change related to the handling of personal information, it will classify it as a high risk.

[0298] Step 4:

[0299] The server stores the analysis results in a database and prepares it so that risk information can be visually presented when accessed by a user.

[0300] Step 5:

[0301] When a user accesses the risk information page, the device displays the changes and risks in a visually easy-to-understand format, such as color-coding.

[0302] Evaluation and disclosure of contract details

[0303] Step 1:

[0304] The user uses an input form on the terminal to input an evaluation score and comments on the contract contents.

[0305] Step 2:

[0306] The terminal transmits the evaluation score and comments entered by the user to the server.

[0307] Step 3:

[0308] The server stores the received evaluation data in a database and performs real-time statistical processing, such as calculating the average evaluation score and frequently occurring comments.

[0309] Step 4:

[0310] The server visualizes the results and updates the evaluation page so that other users can see them.

[0311] Step 5:

[0312] When other users access the rating page, the terminal displays the aggregated rating scores and comments.

[0313] Individual contract risk assessment

[0314] Step 1:

[0315] The user uses the upload function on the device to upload the contract in scanned or PDF format.

[0316] Step 2:

[0317] The terminal transmits the uploaded contract to the server.

[0318] Step 3:

[0319] The server uses OCR (Optical Character Recognition) software to extract text data from the contract.

[0320] Step 4:

[0321] The server then analyzes the extracted text data using a risk assessment algorithm to identify risks, such as risks related to payment terms or construction extensions.

[0322] Step 5:

[0323] The server stores the evaluation results in a database and makes them available for user review.

[0324] Step 6:

[0325] The device provides the user with the risk assessment results in an easily identifiable manner, highlighting areas of concern or specific risk areas.

[0326] Drafting and providing contract amendment proposals

[0327] Step 1:

[0328] The user uses an input form on the terminal to input requests for changes to the contract contents, such as shortening the contract period or changing the payment terms.

[0329] Step 2:

[0330] The terminal transmits the input desired changes to the server.

[0331] Step 3:

[0332] The server uses an automated contract generation library to generate a new draft contract based on the inputs.

[0333] Step 4:

[0334] The server checks the generated draft contract using an internal review system and makes corrections as necessary.

[0335] Step 5:

[0336] The server stores the revised draft contract in a database so that it can be provided to the user.

[0337] Step 6:

[0338] The terminal displays the new draft contract to the user and makes it available for download if desired.

[0339] Operation using emotion engine (processing based on additional claims)

[0340] Step 1:

[0341] The emotion engine analyzes facial expressions and voice data in real time while the user is viewing a contract or terms and conditions.

[0342] Step 2:

[0343] The server receives the emotion data sent from the emotion engine and identifies the user's emotional state based on the analysis results. For example, if the user shows surprise or anxiety, the emotion data is reflected in the risk assessment.

[0344] Step 3:

[0345] The device dynamically changes how it presents risk information depending on the user's emotional state: if the user feels anxious, it displays additional details or advice.

[0346] Step 4:

[0347] The server stores the emotion data in a database and uses it as reference information for future interactions.

[0348] Step 5:

[0349] The emotion engine weights contract and risk assessment results based on the user's emotional data, providing more personalized results.

[0350] Step 6:

[0351] The user can use the terminal to make decisions or make changes to the contract contents based on feedback and advice from the emotion engine.

[0352] In this way, by explaining each processing step in detail, the specific operation of the system and its linkage with the emotion engine become clear.

[0353] Example 2

[0354] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0355] The contents of contracts and terms and conditions change frequently, making it difficult to quickly and accurately grasp these changes. Furthermore, risk assessment and information presentation that takes user emotions into consideration are not adequately implemented, making it difficult for users to accurately understand risks and respond appropriately. Conventional systems do not dynamically adjust the display method based on the user's emotional state, which can result in a poor user experience. Furthermore, when users input their evaluation of specific contract content, there is also the issue of the evaluation not being properly fed back based on their emotions.

[0356] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for periodically acquiring the latest version of the contract or terms and conditions, a means for comparing the acquired contract or terms and conditions with previous versions to identify differences, a means for analyzing the identified differences and classifying and assessing risks, a means for visually presenting the classified and assessed risks to the user, and a means for recognizing the user's emotions in real time and dynamically adjusting the display method based on the recognition results. This allows the user to quickly and accurately grasp changes to the contract or terms and understand the risks. Furthermore, the dynamic presentation of information according to the user's emotions improves the user experience. Furthermore, more appropriate feedback can be provided by incorporating the user's emotional evaluation into statistical processing.

[0357] "Means for periodically obtaining the latest version of the contract or terms and conditions" refers to a system that automatically obtains the latest version of the contract or terms and conditions from a website or database at regular intervals.

[0358] "Means for comparing the acquired contract or terms and conditions with previous versions to identify differences" refers to algorithms or processes for comparing the content of the latest contract or terms and conditions with previous versions and identifying any changes.

[0359] The "means of analyzing identified differences and classifying and assessing risks" is a mechanism for analyzing the changed parts in detail, extracting each risk element, and classifying and assessing them.

[0360] "Means for visually presenting classified and assessed risks to users" refers to an interface that displays assessment results in a format that is easy for users to understand, and a mechanism that provides visual feedback.

[0361] "Means for recognizing a user's emotions in real time and dynamically adjusting the display method based on the recognition results" refers to a technology that monitors a user's emotional state in real time through sensor devices such as cameras and microphones, and automatically changes the content and method of display according to the obtained emotional data.

[0362] The "means for users to input evaluations of the contract contents" is an interface that allows users to input evaluations and comments on the contract and terms and conditions.

[0363] The "means for saving the input evaluation data and performing statistical processing in real time" refers to a system for saving user evaluations in a database and instantly analyzing and statistically processing the data.

[0364] The "means for disclosing aggregated evaluation data to other users" is an interface that provides the analyzed and statistically processed evaluation results in a form that can be accessed by other users.

[0365] "Means for incorporating user emotional evaluations into statistical processing" refers to a process for analyzing user emotional data together with evaluation data to provide statistical feedback and improvements.

[0366] "Means for scanning or uploading individual contract contents" means a method by which a user can convert a physical contract into digital form or submit an existing electronic file to the system.

[0367] "Means for extracting the text of an uploaded contract" refers to technology for extracting text information from the digital data of a scanned or uploaded contract, including OCR (optical character recognition) technology.

[0368] The "means for analyzing extracted text data and assessing risks" refers to a process of analyzing the contract contents in detail based on the extracted text information, and identifying and assessing potential risks.

[0369] "Means for providing assessed risk information to a user" means an interface for providing analyzed and assessed risk information to a user in a visual or notification format.

[0370] "Means for recognizing the user's emotions and adjusting the way risk information is presented based on the results of that recognition" refers to a mechanism that analyzes the user's emotional data in real time and changes the way risk information is presented based on the results.

[0371] This invention is a system that presents changes to contracts and terms and conditions to users, evaluates and notifies them of the risks involved, and dynamically adjusts the interface based on user emotions. The detailed configuration of the system and specific implementation methods are described below.

[0372] System configuration

[0373] This system consists of a server, a terminal, a user, and an emotion engine. The server is responsible for data management and analysis of contracts and terms and conditions, and emotional data processing, while the terminal provides the user interface. The emotion engine recognizes user emotions in real time and optimizes system operation based on them.

[0374] Hardware and software used

[0375] Server: Performs data analysis and management. Software used includes TensorFlow and PyTorch, the Tesseract OCR engine as OCR technology, and MySQL (registered trademark) and PostgreSQL for database management.

[0376] Terminal: Provides a user interface. Dynamically generates pages using a web browser with HTML / CSS and JavaScript (registered trademark).

[0377] Emotion Engine: Recognizes user emotions using Microsoft® Azure® Cognitive Services and OpenCV.

[0378] System Operation

[0379] Understanding changes to contracts and terms and conditions and clarifying risks

[0380] The server periodically scrapes the website to retrieve the latest version of the contract and terms and conditions, using Python's BeautifulSoup and Scrapy.

[0381] The server compares the retrieved data with previous versions and uses a Diff check algorithm to identify changes.

[0382] The server analyzes the changes and classifies and assesses the risks using a risk assessment algorithm (using TensorFlow and PyTorch).

[0383] The server stores the classified and evaluated risk information in a database (MySQL or PostgreSQL) and provides it to the terminal.

[0384] User Interface

[0385] When a user accesses a risk information page, the device visually displays the changes and the associated risks, using color coding and icons for visual feedback.

[0386] The emotion engine captures user emotional data via the camera and microphone, analyzes it using Microsoft Azure Cognitive Services and OpenCV, and if the user feels anxious or surprised, it will change the way it is displayed and provide additional information or advice.

[0387] Evaluation and disclosure of contract details

[0388] The user inputs their evaluation of the contract contents through the terminal and sends it to the server.

[0389] The server processes the evaluation data in real time and publishes the results to other users using NumPy and Pandas.

[0390] The emotion engine recognizes how users feel when they are entering their ratings and incorporates that emotional data into the rating process.

[0391] Individual contract risk assessment

[0392] Users upload individual contracts as scanned or electronic files.

[0393] The device receives this and sends it to a server, which uses OCR technology (such as Tesseract OCR) to extract the text and analyzes it with a risk assessment algorithm.

[0394] The server notifies the terminal of the evaluation results and displays the necessary risk information.

[0395] The emotion engine recognizes the emotions users feel when reviewing risk information and adjusts how risks are presented based on that information.

[0396] Drafting and providing contract amendment proposals

[0397] If the user wishes to change the contract, they enter the changes into their device and send them to the server, which then uses an automated contract generation library (such as the Docxtpl library) to generate a new contract draft and provides it to the user after review.

[0398] The emotion engine takes user emotions into consideration when creating contract change proposals, supporting stress-free operation.

[0399] Examples and prompts

[0400] Example 1: Changes to the terms of use of an online storage service

[0401] The server retrieves the latest terms of use and compares them with the previous terms.

[0402] If there are any changes regarding the handling of personal information, the risks will be analyzed in detail and notified to the device.

[0403] The emotion engine recognizes the user's concerns and provides detailed explanations and additional advice.

[0404] Prompt Sentence Examples

[0405] I am reviewing the new terms of service for an online storage service. Please obtain the latest version and identify the differences from the previous version. Please analyze in detail the changes, especially those related to personal information, and assess the risks involved. Please explain how the sentiment engine works and provides additional advice if the user feels uneasy.

[0406] Example 2: Contract for the construction of a new building

[0407] Users upload construction contracts.

[0408] The server extracts the text using OCR and performs a risk assessment.

[0409] The terminal will notify you of risks such as construction delays and additional costs.

[0410] The emotion engine detects users' surprise or concern and provides detailed solutions.

[0411] Prompt Sentence Examples

[0412] I uploaded a contract for constructing a new building. I want you to use OCR technology to extract the text from the contract and perform a risk assessment. I want you to notify the user of risks such as delays and additional costs, and explain how the emotion engine will react if the user is surprised or worried.

[0413] The above is a specific embodiment of the present invention.

[0414] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0415] Step 1:

[0416] The server periodically retrieves the latest version of the contract or terms and conditions from the website. Python's BeautifulSoup and Scrapy are used to scrape the webpage and extract the contract or terms and conditions links from the HTML tags. This allows the server to retrieve the latest version of the contract or terms and conditions data. The input is the URL of a specific website, and the output is the latest contract or terms and conditions data.

[0417] Step 2:

[0418] The server compares the retrieved contract or clause data with past versions to identify changes. Specifically, it uses a Diff check algorithm to compare the lines of each text data. When changes are identified, that information is output as a difference list. The input is the latest version of the text and the past version of the text, and the output is a list of changes.

[0419] Step 3:

[0420] The server analyzes the identified changes and classifies and evaluates the risk using a risk assessment algorithm. It uses machine learning frameworks such as TensorFlow and PyTorch to score the risk of each change. The input is a list of changes, and the output is classified and evaluated risk information.

[0421] Step 4:

[0422] The server stores the classified and evaluated risk information in a database. The database used is MySQL, PostgreSQL, etc., and writes the risk information to the database in an appropriate format. The input is the classified and evaluated risk information, and the output is the risk information stored in the database.

[0423] Step 5:

[0424] When a user accesses a risk information page, the terminal visually displays the changes and risks. Using HTML / CSS and JavaScript, the changed parts are displayed with color coding and icons, allowing the user to understand the risks at a glance. The input is risk information retrieved from the database, and the output is the visually displayed risk information.

[0425] Step 6:

[0426] The emotion engine uses the user's camera and microphone to capture emotional data in real time and analyzes it using Microsoft Azure Cognitive Services and OpenCV. It dynamically adjusts how risk information is displayed based on the user's emotional state. For example, if the user feels anxious, it will pop up additional details and advice. The input is the user's video and audio, and the output is the dynamically adjusted display method.

[0427] Step 7:

[0428] Users input their evaluation of the contract contents through their terminals and send the data to the server. Evaluation data is collected by filling out the evaluation form and clicking the submit button. The input is the user's evaluation data, and the output is the evaluation data sent to the server.

[0429] Step 8:

[0430] The server stores the evaluation data sent by users in a database and performs statistical processing in real time using NumPy and Pandas. The aggregated results are reflected on a web page and made publicly accessible to other users. The input is the user's evaluation data, and the output is the aggregated evaluation data.

[0431] Step 9:

[0432] The user scans or uploads individual contracts in electronic file format and sends them to the server via the terminal. The terminal provides an upload button and sends the selected file to the server. The input is the contract in electronic file format, and the output is the contract data sent to the server.

[0433] Step 10:

[0434] The server uses the Tesseract OCR engine to extract the text of the uploaded contract and parses it with a risk assessment algorithm. The input is the image data of the contract, and the output is the extracted text data and assessed risk information.

[0435] Step 11:

[0436] The server notifies the terminal of the evaluation results and provides risk information to the user. The necessary risk information is visually displayed on the terminal. The input is the evaluated risk information, and the output is the visually displayed risk information.

[0437] Step 12:

[0438] The emotion engine recognizes the user's emotions when reviewing risk information and adjusts the presentation of risk information based on that information. If the user expresses surprise or disappointment, it displays additional explanations and suggested solutions. The input is the user's emotional data, and the output is the adjusted presentation of risk information.

[0439] Step 13:

[0440] If a user wishes to change the contents of the contract, they enter the changes via their terminal and send them to the server. They enter the changes in the input form and click the send button. The input is the changes the user wishes to make, and the output is the changes sent to the server.

[0441] Step 14:

[0442] The server generates a new draft contract using an automated contract generation library (such as the Docxtpl library). The input is the user's desired changes, and the output is the generated draft contract.

[0443] Step 15:

[0444] The server provides the generated contract draft to the user after review, and the emotion engine takes the user's emotions into consideration to support stress-free operation. The input is the generated contract draft and the user's emotion data, and the output is the provided contract draft and adjusted operation method.

[0445] (Application example 2)

[0446] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0447] It is important to visually present changes to contracts and terms and conditions to users and effectively evaluate and classify the risks, making it easier for users to understand the content of the contract. However, presenting risks without taking into account the anxiety and confusion that accompanies users' emotions can lead to different perceptions of information and delays in appropriate responses. Furthermore, when users evaluate contract content or upload individual contracts to check risks, a poor user experience can result if the interface is not dynamically adjusted based on the user's emotions.

[0448] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for periodically acquiring the latest version of the contract or terms of use, means for comparing the acquired contract or terms of use with previous versions to identify differences, means for analyzing the identified differences and classifying and assessing risks, means for visually presenting the classified and assessed risks to the user, means for recognizing the user's emotions in real time, and means for dynamically adjusting the interface based on the recognized emotions. This not only makes it easier for the user to understand risks when reviewing the contract or its contents, but also makes it possible to provide optimal information according to the user's emotions.

[0449] "Means for periodically obtaining the latest version of the agreement or terms of use" refers to a function that automatically obtains the latest version of the agreement or terms of use online or from a database on a regular basis.

[0450] "Means for comparing the acquired contract or terms of use with a previous version to identify differences" refers to an analysis function for comparing the latest acquired contract or terms of use with a previous version and identifying differences in changes or additions.

[0451] "Means for analyzing identified differences and classifying and assessing risks" refers to a function for identifying and classifying risks and assessing their importance and impact by analyzing identified differences.

[0452] "Means for visually presenting classified and assessed risks to users" refers to a function that graphically displays assessed risk information to users and provides information in a visually easy-to-understand format.

[0453] "Means of recognizing the user's emotions in real time" refers to an analytical function that analyzes the user's voice, facial expressions, behavior, etc., and recognizes the emotions the user is feeling in real time.

[0454] "Means for dynamically adjusting the interface based on recognized emotions" refers to a function that dynamically changes and optimizes the content and manner of display of the user interface in response to the recognized emotions of the user.

[0455] "Means for users to input evaluations of the contract contents" refers to an interface that allows users to input their own evaluations and opinions of the contract contents they are using.

[0456] "Means for adjusting the evaluation process based on emotion recognition data" refers to a function that adjusts the evaluation process and the way evaluation results are displayed by referring to the user's emotion data.

[0457] "Means for scanning or uploading the contents of individual contracts" refers to the function of scanning individual contracts from paper and converting them into digital data, or uploading them directly in electronic file format.

[0458] "Means for extracting text from uploaded contracts" refers to a function that extracts text data from uploaded contracts and converts it into an analyzable format.

[0459] "Means for recognizing emotions when checking risk information and adjusting the way in which risk is presented" refers to a function that recognizes the emotions of users when checking risk information and adjusts the way in which risk information is presented and its content based on those emotions.

[0460] This system presents changes to contracts and terms and conditions to users, evaluates and notifies them of the risks involved, and dynamically adjusts the interface by recognizing the user's emotions. This system consists of a server, terminals, users, and an emotion engine.

[0461] Overall system configuration

[0462] The server is responsible for data management, analysis, and emotional data processing of contracts and terms and conditions. The server periodically retrieves the latest version of the contract or terms and conditions from the website and compares it with previous versions to identify any discrepancies. The retrieved data is analyzed using a risk assessment algorithm to classify and assess risks. This assessment information is stored in a database.

[0463] The device provides a user interface using a smartphone. When a user accesses a risk information page, the device displays the changes and their associated risks in a visually easy-to-understand format. It also includes an emotion engine that analyzes the user's voice, facial expressions, and behavior to recognize emotions in real time, dynamically adjusting the interface based on the emotional data. For example, if the user is feeling anxious, the device will provide more detailed information and advice on that point.

[0464] Understanding changes to contracts and terms and conditions and clarifying risks

[0465] The server compares the latest version of the contract or clause with the previous version to identify any changes. The identified differences are analyzed by a risk assessment algorithm to classify and evaluate the risks. The classified and evaluated risk information is stored in a database for visual presentation.

[0466] User emotion recognition and interface adjustment

[0467] The device is equipped with an emotion engine that recognizes the user's emotions as they review risk information. The emotion engine analyzes the user's voice, facial expressions, and behavior to recognize emotions in real time. Based on the emotion data, the user interface is dynamically adjusted according to the recognized emotion. For example, if the user feels anxious, additional details and advice are added. This allows the user to understand the contract details and make a decision with confidence.

[0468] User ratings and sentiment data

[0469] The terminal provides an interface for users to input their ratings of the contract contents. The user's rating input is sent to the server in real time and stored in a database. The server performs statistical processing of the rating data in real time and makes the results available to other users. An emotion engine also recognizes the user's emotions, and the emotion data is reflected in the rating process. For example, the ratings of users who show very positive emotions may be weighted.

[0470] Individual contract risk assessment

[0471] Users scan or upload individual contracts as electronic files. The device receives the documents and sends them to the server. The server uses OCR technology to extract text from the contract and analyzes it with a risk assessment algorithm. The results are then reported to the user, and the necessary risk information is displayed on the device.

[0472] Specific examples

[0473] For example, if a user is considering new terms of use for an online storage service, the server retrieves the latest terms and compares them with previous terms to identify any changes. If the changes relate to the handling of personal information, the server performs a detailed analysis of the risks and notifies the user. If the information makes the user feel uneasy, the emotion engine recognizes this emotion and provides more detailed information and additional advice. Similarly, if a user uploads a contract for the construction of a new building, the server analyzes the contract and notifies the user of specific risks (e.g., construction delays, additional costs). If the user is surprised or worried, the emotion engine detects this and provides more detailed countermeasures for the risk.

[0474] Example prompts for generative AI models

[0475] "How can we assess the risk regarding the latest security terms of service changes, recognize user sentiment and provide more information?"

[0476] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0477] Step 1:

[0478] The server periodically retrieves the latest version of the contract or terms of use from an online or database. Specifically, it retrieves data via a specific URL or API and stores it in a local database. The input is the URL or API information to be retrieved, and the output is the retrieved latest version of the contract or terms of use data.

[0479] Step 2:

[0480] The server compares the latest version of the contract or terms of use with previous versions to identify differences. This process uses a difference analysis library such as difflib to detect differences in text. The input is the latest and previous versions of the contract data, and the output is the identified differences.

[0481] Step 3:

[0482] The server analyzes the identified differences and classifies and assesses the risk using a risk assessment algorithm. In this process, risks are classified as high, medium, low, etc. based on specific keywords or phrases. The inputs are the difference information and the risk assessment algorithm, and the output is the classified and assessed risk data.

[0483] Step 4:

[0484] When a user accesses the risk information page, the terminal visually displays the risk data obtained from the server. Specifically, the degree of risk is clearly expressed using color coding and icons. The input is risk data, and the output is risk information displayed on the user interface.

[0485] Step 5:

[0486] The device runs an emotion engine that analyzes the user's voice, facial expressions, and behavior to recognize emotions in real time. The emotion engine analyzes the collected data and determines the user's emotional state (e.g., anxiety, relief, surprise). The input is the user's voice, facial expressions, and behavior data, and the output is the recognized emotion data.

[0487] Step 6:

[0488] The device dynamically adjusts the user interface based on the recognized emotion, for example, displaying a more information box or additional advice if the user is feeling anxious. The input is emotion data and user interface data, and the output is an adjusted user interface.

[0489] Step 7:

[0490] When a user inputs an evaluation of the contract contents, the terminal sends the evaluation data to the server. In addition, emotional data recognized by the emotion engine is also sent. The input is the user's evaluation and emotional data, and the output is the evaluation data sent to the server.

[0491] Step 8:

[0492] The server processes the submitted evaluation data in real time and publishes the results to other users. In this process, the evaluation data is aggregated and statistical information about specific items is generated. The input is the evaluation data, and the output is the statistically processed evaluation results.

[0493] Step 9:

[0494] When a user scans or uploads an individual contract, the device sends the contract to the server, which uses OCR technology to extract text from the contract and analyzes it with a risk assessment algorithm. The input is the uploaded contract data, and the output is the analyzed risk information.

[0495] Step 10:

[0496] When providing risk information to the user, the device monitors the user's emotions in real time and adjusts the risk presentation method. Based on the recognized emotion data, it provides additional explanations and countermeasures. The input is the user's emotion data and risk information, and the output is the adjusted risk presentation method.

[0497] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0498] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0499] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0500] [Second embodiment]

[0501] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0502] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0503] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0504] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0505] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0506] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0507] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0508] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0509] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0510] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0511] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0512] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0513] The present invention is a system designed to enable users to easily understand the contents of contracts and terms and conditions, and is realized using the following means.

[0514] Overall system configuration

[0515] This system consists of three main components: a server, a terminal, and a user. The server manages and analyzes data on contracts and clauses, while the terminal provides the user interface. Users use the terminal to evaluate, upload, and input proposed changes to contracts and clauses.

[0516] Understanding changes to contracts and terms and conditions and clarifying risks

[0517] The server periodically retrieves the latest versions of contracts and terms and conditions published on specific websites from the Internet. The server stores this data in storage and compares it with previous versions. Changes are identified as differences as a result of the comparison, and are classified and analyzed using a risk assessment algorithm. The analyzed risk information is visually presented to the user. For example, if a provision regarding data sharing is added to the new terms of use of a social media platform, that information is highlighted.

[0518] Evaluation and disclosure of contract details

[0519] Users use their devices to input their evaluations of contract details. For example, they can input an evaluation score indicating whether they were satisfied or dissatisfied with a contract with a certain internet service provider. The device sends this evaluation to a server, which stores the evaluation data in a database. The server statistically processes the evaluations of all users, generates information such as average scores and frequently occurring comments, and makes this information public to other users. Other users can use this public information as a reference when considering the contract details.

[0520] Individual contract risk assessment

[0521] Users use their devices to scan or upload individual contracts, such as land sales or building construction contracts, as electronic files. The devices then send the uploaded contracts to a server. The server then uses OCR technology to extract text data from the contracts, analyzes the text data, and performs a risk assessment. The assessment results identify specific risks in the contract (such as construction delays or additional costs) and provide them to the user.

[0522] Drafting and providing contract amendment proposals

[0523] If a user wishes to change the contract details, they use their device to input the specific details. For example, if they wish to shorten the contract period for building construction work, they can input this information. The device then sends this information to the server, which then automatically generates a new contract based on the proposed changes. The generated contract draft is then provided to the user for final confirmation and download.

[0524] Specific examples

[0525] For example, if a user is considering new terms of use for an online storage service, the server retrieves the latest terms of use, compares them with previous terms, and identifies any changes. If the changes relate to the handling of personal information, the server analyzes the risks in detail and notifies the user. The user can then use this information to consider using the service.

[0526] In addition, if a user uploads a contract for the construction of a new building, the server analyzes the contract and notifies the user of specific risks (e.g., construction delays, additional costs), allowing the user to review the contract and, if necessary, input proposed changes and generate a new contract.

[0527] In this way, the present invention makes it easier for users to understand the contents of contracts and terms and conditions, helps them understand potential risks, and provides a method for efficiently making changes to the contract contents.

[0528] The processing flow will be explained below.

[0529] Understanding changes to contracts and terms and conditions and clarifying risks

[0530] Step 1:

[0531] The server crawls the specified website URL list to retrieve the latest version of the contract or terms and conditions, and stores the retrieved data in storage.

[0532] Step 2:

[0533] The server uses a difference detection library (e.g., diff-match-patch) to compare the latest version of the contract or clause with the previous version and identify the changes.

[0534] Step 3:

[0535] The server analyzes the identified changes and classifies and assesses the risk using a risk assessment algorithm. For example, if a change related to the handling of personal information is detected, the server classifies the risk as high.

[0536] Step 4:

[0537] The server stores the analysis results in a database and prepares a visual display of the risks when accessed by the user.

[0538] Step 5:

[0539] When a user accesses the risk information page, the device visually displays the changes and the risks involved using color coding, etc.

[0540] Evaluation and disclosure of contract details

[0541] Step 1:

[0542] The user uses an input form on the terminal to input an evaluation score and comments on the contract contents.

[0543] Step 2:

[0544] The terminal transmits the evaluation score and comments entered by the user to the server.

[0545] Step 3:

[0546] The server stores the received evaluation data in a database and performs real-time statistical processing, such as calculating the average evaluation score and frequently occurring comments.

[0547] Step 4:

[0548] The server visualizes the results and updates the evaluation page so that other users can see them.

[0549] Step 5:

[0550] When other users access the rating page, the terminal displays the aggregated rating scores and comments.

[0551] Individual contract risk assessment

[0552] Step 1:

[0553] The user uses the upload function on the device to scan the contract or upload it in PDF format.

[0554] Step 2:

[0555] The terminal transmits the uploaded contract to the server.

[0556] Step 3:

[0557] The server uses OCR (Optical Character Recognition) software to extract text data from the contract.

[0558] Step 4:

[0559] The server analyzes the extracted text data and identifies risks using a risk assessment algorithm.

[0560] Step 5:

[0561] The server organizes the risk information and stores it in a database in order to provide the evaluation results to the user.

[0562] Step 6:

[0563] The terminal visually presents the risk assessment results to the user, for example by highlighting specific risk areas.

[0564] Drafting and providing contract amendment proposals

[0565] Step 1:

[0566] The user uses the input form on the terminal to input the changes he or she wishes to make to the contract contents.

[0567] Step 2:

[0568] The terminal transmits the input desired changes to the server.

[0569] Step 3:

[0570] The server uses an automated contract generation library to generate a new draft contract based on the user's input.

[0571] Step 4:

[0572] The server checks the generated draft contract using an internal review system and makes corrections as necessary.

[0573] Step 5:

[0574] The server stores the revised draft contract in a database in order to provide it to the user.

[0575] Step 6:

[0576] The terminal will visually display the new draft contract to the user and make it available for download if desired.

[0577] In this way, by explaining each processing step separately, it becomes easier to understand the specific operation of the system.

[0578] Example 1

[0579] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0580] The contents of contracts and terms and conditions are complex and contain many technical terms, making them difficult for general users to understand. Furthermore, tracking changes to contracts and terms and assessing risks is time-consuming and requires specialized knowledge. In addition, there are limited ways for users to share their assessments of contract contents with other users. This makes it difficult for users to understand contract contents, grasp risks, and make decisions based on the assessments of other users.

[0581] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0582] In this invention, the server includes means for periodically obtaining the latest version of the contract or terms and conditions, means for comparing the obtained contract or terms and conditions with past versions to identify differences, means for analyzing the identified differences and classifying and assessing risks, means for visually presenting the classified and assessed risks to the user, means for extracting text data from the contract using machine reading comprehension technology, means for the user to input changes to the contract, and means for automatically generating a new draft contract based on the input changes. This allows the user to easily understand changes and risks in the contract or terms and conditions, efficiently create a contract that reflects their own opinions, and also enables them to refer to evaluation information from other users.

[0583] A "contract" is a document that sets out the rights and obligations between the parties under a particular contract.

[0584] "Terms and conditions" are documents that set out the standard terms and conditions offered by a company or organization.

[0585] "Latest version" means the most recent version of the agreement or terms and conditions.

[0586] "Means of collection" refers to methods and technologies for automatically collecting data.

[0587] "Means for comparing and identifying differences" refers to methods and techniques for comparing different versions of contracts or terms and conditions and identifying changes.

[0588] "Means for classifying and assessing risks" refers to methods and techniques for analyzing changes to contracts and clauses to identify, classify, and assess potential risks.

[0589] "Visual presentation means" refers to methods and technologies that visually display analysis results to users in an easy-to-understand manner.

[0590] "Machine reading comprehension technology" refers to technology for automatically reading and understanding text data.

[0591] "Means for extracting text data" refers to methods or techniques for extracting text information from scanned images or uploaded files.

[0592] "Means for users to input changes to the contract" refers to the methods and technologies that allow users to input their desired changes to the contract into the system.

[0593] "Means for automatically generating a new draft contract" refers to methods or technologies that automatically create a new contract based on changes entered by the user.

[0594] The present invention is a system designed to enable users to easily understand the contents of contracts and terms and conditions, and is composed of three main elements: a server, a terminal, and a user.

[0595] Server Roles

[0596] The server manages and analyzes data on contracts and clauses. Specifically, the server periodically retrieves the latest versions of contracts and clauses published on specific websites from the Internet and stores the retrieved data in storage. An AWS S3 bucket is used to store the contract data, and the program performs web scraping using Python and the Beautiful Soup library. The server also compares the old and new contracts to identify differences and calculates text differences using the diff-match-patch library. The NLTK library is then used to classify and evaluate the risk of the changes using a risk assessment algorithm. The evaluated risk information is visually presented to the user. The front end uses React to highlight the results.

[0597] Device Role

[0598] The terminal provides a user interface, allowing users to evaluate, upload, and input proposed changes to the contract contents. For example, when a user scans or uploads an individual contract as an electronic file, the terminal sends this data to the server. The server uses OCR technology (Tesseract OCR) to extract text data from the contract and analyzes the text data to evaluate risk. If the user wishes to make changes to the contract contents, they can use the terminal to enter the specific details, which are then sent to the server. The server then automatically generates a new contract based on the proposed changes. The document is generated using a specific template, and can be downloaded after final confirmation.

[0599] User Roles

[0600] Users operate the system to evaluate their own contracts and input proposals for changes to the contract and terms. For example, they can use an evaluation form to input their level of satisfaction with a contract with an internet service provider. The evaluation results are sent to a server, where they are statistically processed in real time and made available to other users.

[0601] Specific examples

[0602] For example, if a user is considering new terms of use for an online storage service, the server retrieves the latest terms of use, compares them with previous terms, and identifies any changes. If the changes relate to the handling of personal information, the server analyzes the risks in detail and notifies the user. The user can then use this information to consider using the service.

[0603] In addition, when a user uploads a contract for constructing a new building, the server analyzes the contract, identifies risks (e.g., construction delays, additional costs) and notifies the user, who can then review the contract and, if necessary, input proposed changes to generate a new contract.

[0604] Prompt Sentence Examples

[0605] An example of a prompt to be input to a generative AI model is, "I would like to develop a system that analyzes contract contents, identifies risks, and presents them visually. This system retrieves the latest versions of contracts and terms and conditions from the Internet and compares them with previous versions. It uses a risk assessment algorithm to classify and analyze risks by category and notify the user of the results."

[0606] In this way, the present invention makes it easier for users to understand the contents of contracts and terms and conditions, helps them understand potential risks, and provides a method for efficiently making changes to the contract contents.

[0607] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0608] Step 1:

[0609] The server periodically retrieves the latest version of the contract or terms and conditions from a specific website on the Internet. Specifically, it uses Python's Beautiful Soup library to retrieve HTML content from a specified URL and extracts links to the new contract or terms and conditions. The retrieved data is saved in text format.

[0610] Enter: Website URL

[0611] Output: Text data of the latest contracts and terms and conditions

[0612] Step 2:

[0613] The server stores the acquired contract and clause data in cloud storage such as an AWS S3 bucket, which is used for later comparison and analysis.

[0614] Input: Text data of the latest contracts and terms and conditions

[0615] Output: File saved in cloud storage

[0616] Step 3:

[0617] The server compares the old and new contracts and clauses and identifies the changes as differences. This is achieved by calculating the text differences using the diff-match-patch library. This difference data becomes the basis for change analysis.

[0618] Input: Text data of past and latest contracts and terms and conditions

[0619] Output: Diff data of changes

[0620] Step 4:

[0621] The server analyzes the delta data and uses a risk assessment algorithm to classify and assess the risk. It uses the NLTK library to perform text analysis to identify the risks of the changes. This risk information is then categorized.

[0622] Input: Difference data of changes

[0623] Output: Assessed risk information

[0624] Step 5:

[0625] The server visually presents the assessed risk information to the user, and a front-end is built using React to highlight changes and risks.

[0626] Input: Assessed risk information

[0627] Output: Visual risk information displayed in the user interface

[0628] Step 6:

[0629] The user uses a terminal to input their evaluation of the contract contents, and enters the evaluation score and comments using an HTML form, and the data is sent to the server.

[0630] Input: User rating score and comments

[0631] Output: Rating data sent to the server

[0632] Step 7:

[0633] The server statistically processes all users' rating data and compiles average scores and frequently occurring comments in real time. It uses the Pandas library to aggregate the rating data and generate statistical information.

[0634] Input: Multiple user rating data

[0635] Output: Aggregated average scores and frequently occurring comments

[0636] Step 8:

[0637] The server then publishes the aggregated evaluation data to other users, who can use the published information as a reference when considering contract details.

[0638] Input: Aggregated average rating score and frequently occurring comments

[0639] Output: Aggregate information displayed in the user interface

[0640] Step 9:

[0641] The user uses the terminal to scan or upload the individual contract in electronic file format, and the terminal sends the uploaded data to the server.

[0642] Input: Scanned or uploaded agreement

[0643] Output: Agreement data sent to the server

[0644] Step 10:

[0645] The server extracts text data from the uploaded contract using OCR technology. It uses the Tesseract OCR library to extract text from images.

[0646] Input: Image data of the uploaded contract

[0647] Output: Extracted text data

[0648] Step 11:

[0649] The server analyzes the extracted text data and performs risk assessment. It uses a risk assessment algorithm to identify specific risks (e.g., construction delays, additional costs).

[0650] Input: Extracted text data

[0651] Output: Assessed risk information

[0652] Step 12:

[0653] The server provides the assessed risk information to the user, who is then notified and displayed in a visual interface.

[0654] Input: Assessed risk information

[0655] Output: Risk information provided to the user

[0656] Step 13:

[0657] If a user wishes to change the contents of their contract, they use their device to input the specific changes, and the input data is sent to the server.

[0658] Input: User requests to change contract details

[0659] Output: Changes sent to the server

[0660] Step 14:

[0661] The server automatically generates a new contract based on input from the user, creates a new contract using a specific template, and provides it to the user.

[0662] Input: Proposed changes to the contract contents desired by the user

[0663] Output: The new contract that is generated.

[0664] In this way, the present invention provides a system that makes it easier for users to understand the contents of contracts and terms and conditions, and assists in understanding and evaluating potential risks.

[0665] (Application example 1)

[0666] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0667] There is a need for a system that can quickly identify changes and risks in contracts and clauses, allowing users to easily understand them. However, existing systems require users to manually compare and analyze contracts and clauses, which is extremely labor-intensive. Furthermore, risk assessment of contract content and feedback information from other users are not centrally provided. This can lead to delays and inaccuracies in understanding contract content and appropriate risk assessment. This invention aims to solve these issues by extracting text from contracts and clauses, analyzing risks, visually presenting them through a user interface, and performing detailed analysis using a generative AI model.

[0668] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0669] In this invention, the server includes: means for periodically obtaining the latest version of the contract or terms and conditions; means for comparing the obtained contract or terms and conditions with previous versions to identify differences; means for analyzing the identified differences and classifying and assessing risks; means for visually presenting the classified and assessed risks to the user; means for the user to photograph or upload the contract or terms and conditions; means for using optical character recognition technology to extract text data; means for analyzing the extracted text data and assessing risks; and means for providing a user interface for visually displaying the assessed risk information to the user. This allows the user to quickly understand changes and risks in the contract or terms and conditions and perform appropriate risk assessments. Furthermore, a generative AI model is used to perform detailed analysis of the contract content, which is expected to promote user understanding and improve assessment accuracy.

[0670] "Means for periodically obtaining the latest version of contracts or terms and conditions" refers to technology that automatically collects the latest information on contracts and terms and conditions that are published on the Internet.

[0671] "Means for identifying differences by comparing acquired contracts or terms and conditions with past versions" refers to a technology that compares the latest collected contracts and terms and conditions with past versions to clarify changes.

[0672] "Means for analyzing identified differences and classifying and assessing risks" refers to algorithms or programs for analyzing changes and identifying, classifying, and assessing the risks.

[0673] "Means for visually presenting classified and assessed risks to the user" refers to a technology that displays analyzed risk information in an easy-to-understand manner through a user interface.

[0674] "Means for users to photograph or upload contracts or terms and conditions" refers to technology that allows users to send images or files of contracts or terms and conditions to the system using a smartphone or computer.

[0675] "Means using optical character recognition technology to extract text data" refers to OCR (optical character recognition) technology to extract text information from uploaded images.

[0676] The "means for analyzing extracted text data and assessing risk" refers to a program or algorithm for analyzing the contract content based on the extracted text information and assessing the risk.

[0677] "Means for providing a user interface for visually displaying assessed risk information to a user" refers to an interface technology for displaying assessment results in a form that is visually easy for a user to understand.

[0678] The "means for users to input evaluations of the contract contents" refers to an interface that allows users to input their satisfaction and opinions regarding the contract contents into the system.

[0679] "Means for saving input evaluation data and performing statistical processing in real time" refers to technology that saves evaluation data from users and analyzes and processes it in real time.

[0680] "Means for disclosing aggregated evaluation data to other users" refers to technology that allows analyzed and processed evaluation data to be disclosed and shared with other users.

[0681] "Means of inputting the contents of a contract or terms and conditions as prompt sentences using a generative AI model" refers to a technology that uses natural language processing technology to formalize the contents of a contract or terms and conditions as prompt sentences.

[0682] "Means for performing detailed analysis of contract content using a generative AI model" refers to technology that uses a generative AI model to perform detailed analysis of contract content and provide the results.

[0683] This invention is a system designed to help users easily understand the contents of contracts and terms and conditions. It consists of three main elements: a server, a terminal, and a user. The system's purpose is to quickly identify changes and risks in contracts and terms and conditions and visually present them to users. It can also analyze contract contents using a generative AI model and provide detailed information.

[0684] Server Roles

[0685] The server periodically retrieves the latest version of the contract or terms and conditions from the Internet and stores it in a specific storage device. At this time, the server compares the previous version with the new version and identifies the changes as differences. The identified differences are analyzed using a risk assessment algorithm, and the risks are classified and assessed. This risk information is presented visually to the user.

[0686] The server also uses optical character recognition (OCR) technology to extract text data from contracts and clauses uploaded by users from their devices. The extracted text data is then analyzed in detail using a generative AI model. The analyzed risk information is then sent to the device.

[0687] Device Role

[0688] Users use their smartphone or computer to take a photo of the contract or terms and conditions or upload them as a file. The device then sends this data to the server, which acts as a trigger for OCR processing. The risk information and analysis results received from the server are displayed visually through the device's user interface. Users can easily understand the contract contents based on the visually presented risk information.

[0689] Users can also enter ratings for the contract details, and the rating data is sent to the server in real time. The server stores the rating data and performs statistical processing. This generates and publishes rating information that can be used as reference by other users.

[0690] User operations

[0691] When loading a contract or clause, the user can take a photo using the device's camera or upload an existing file. The device then sends this to the server, which receives risk assessment and analysis results and displays them in an easy-to-read format. The user can also enter their satisfaction with the contract content as an evaluation, and this feedback information is also saved on the server.

[0692] Hardware and software used

[0693] Hardware: smartphones, tablets, computers

[0694] software:

[0695] Google(R) Firebase (backend service)

[0696] OCR library (e.g. Tesseract OCR)

[0697] TensorFlow Lite (Natural Language Processing using Generative AI Models)

[0698] React Native (Mobile Frontend)

[0699] Examples of concrete examples and prompts

[0700] For example, if a user is considering new terms of use for an online storage service, they can take a photo of the new terms of use with their smartphone and upload it. The server will then compare the latest terms with the previous terms to identify any changes. If the changes relate to the handling of personal information, the server will perform a detailed analysis of the risks involved and notify the user. The user can then use this information to consider using the service.

[0701] Example prompt sentence:

[0702] "The changes in the terms and conditions of the new online storage service relate to the handling of personal information, so please assess the risks involved."

[0703] This allows users to quickly understand changes and risks in contracts and terms and conditions, and to conduct appropriate risk assessments. A generative AI model is also used to perform detailed analysis of contract content, which is expected to promote user understanding and improve assessment accuracy.

[0704] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0705] Flow of the system program that realizes the application example

[0706] Step 1:

[0707] Users can photograph or upload contracts and terms and conditions

[0708] Users use their smartphones or computers to take a photo of the contract or terms and conditions or upload an existing file. This input data is in the form of an image or electronic file and is sent from the device to the server.

[0709] Step 2:

[0710] The server extracts the text data

[0711] The server receives uploaded images and files and extracts text data using OCR (Optical Character Recognition) technology. At this stage, the input is image or file format data, and the output is text data.

[0712] Step 3:

[0713] The server compares with the previous version

[0714] The server compares the extracted text data with past versions and performs a difference calculation to identify changes. The input is the current text data and the past text data, and the output is a list of changes.

[0715] Step 4:

[0716] Server analyzes identified differences

[0717] The server runs a risk assessment algorithm based on the identified differences, including a generative AI model. The input is a list of changes, and the output is a risk assessment result.

[0718] Step 5:

[0719] The server sends the risk assessment information to the user

[0720] The server sends the analyzed risk assessment information to the terminal. The input is the risk assessment result, and the output is data that can be displayed visually.

[0721] Step 6:

[0722] The device visually displays risk information

[0723] The terminal visually presents the risk assessment information received from the server to the user. In this step, the user interface displays the risk information in an easy-to-understand format. The input is the visualization data sent from the server, and the output is the display on the screen.

[0724] Step 7:

[0725] The user enters their evaluation of the contract contents

[0726] Users input their evaluation of the contract details through their device. The evaluation data is entered in the form of comments and scores and is sent from the device to the server.

[0727] Step 8:

[0728] The server stores and processes the evaluation data

[0729] The server stores the evaluation data received from users and performs statistical processing in real time. The input is the user evaluation data, and the output is the statistical processing result.

[0730] Step 9:

[0731] The server exposes the rating data to other users

[0732] The server displays the statistically processed evaluation data in a specific interface to make it public to other users. The input is the statistically processed evaluation data, and the output is public information.

[0733] Specific examples of actions and prompt format

[0734] For example, when a user reviews new terms of service for an online storage service, they might use the following prompt:

[0735] "The changes in the terms and conditions of the new online storage service relate to the handling of personal information, so please assess the risks involved."

[0736] By inputting this prompt into the generative AI model, users can quickly receive a specific risk assessment, significantly reducing the burden on users and making it easier for them to evaluate and understand the contract contents.

[0737] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0738] The present invention is a system that presents changes to contracts and terms and conditions to users, evaluates and notifies them of the risks involved, and dynamically adjusts the interface based on user emotions. Specifically, the system is implemented as follows:

[0739] Overall system configuration

[0740] This system consists of a server, a terminal, a user, and an emotion engine. The server is responsible for data management and analysis of contracts and terms and conditions, and emotional data processing, while the terminal provides the user interface. The emotion engine recognizes user emotions in real time and optimizes system operation based on them.

[0741] Understanding changes to contracts and terms and conditions and clarifying risks

[0742] The server periodically retrieves the latest version of the contract or clause from the website. The retrieved data is compared with previous versions to identify any changes. The server analyzes these changes and uses a risk assessment algorithm to classify and assess the risks. The classified and assessed risk information is stored in a database for visual presentation to the user.

[0743] When a user accesses a risk information page, the device displays the changes and their associated risks in a visually easy-to-understand format, including color coding. If the user expresses an emotional reaction to a particular section, the device's emotion engine analyzes the data and dynamically adjusts the display. For example, if the user is extremely anxious, the device will provide more detailed information and advice on that section.

[0744] Evaluation and disclosure of contract details

[0745] Users input their ratings of the contract details through their terminals. The entered rating data is sent to the server and stored in a database. The server then statistically processes the rating data in real time and makes the results available to other users.

[0746] The emotion engine recognizes the emotion a user is feeling when entering a rating and incorporates that emotion data into the rating process. For example, if a user has very positive emotions, their rating may be weighted higher.

[0747] Individual contract risk assessment

[0748] Users scan or upload individual contracts as electronic files. The device receives the documents and sends them to the server. The server uses OCR technology to extract text from the contract and analyzes it with a risk assessment algorithm. The results are then reported to the user, and the necessary risk information is displayed on the device.

[0749] The emotion engine recognizes the emotions users express while viewing risk information and adjusts how the risk is presented based on that emotion. For example, if a user expresses surprise or disappointment, additional explanations or solutions will be provided for that risk.

[0750] Drafting and providing contract amendment proposals

[0751] If the user wishes to change the contract terms, they enter the changes. The device sends the changes to the server, which then uses an automated contract generation library to generate a new contract draft. The draft is then reviewed and provided to the user.

[0752] The emotion engine also takes into account the user's emotions when drafting contract changes, helping to reduce stress. For example, if the user is feeling impatient, it will provide operational guidance and real-time support.

[0753] Specific examples

[0754] For example, if a user is considering new terms of use for an online storage service, the server retrieves the latest terms and compares them with previous terms to identify any changes. If the changes relate to the handling of personal information, the server performs a detailed analysis of the risks and notifies the user. If the information makes the user feel uneasy, the emotion engine recognizes this emotion and provides more detailed information or additional advice.

[0755] For example, if a user uploads a contract for constructing a new building, the server analyzes the contract and notifies the user about specific risks (e.g., construction delays, additional costs). If the user expresses surprise or concern, the emotion engine will detect this and provide more detailed countermeasures for the risk.

[0756] As described above, the present invention makes it easier to understand the contents of contracts and terms and conditions while taking into account the user's emotions, helps to identify potential risks, and provides a method for efficiently changing the contents of contracts.

[0757] The processing flow will be explained below.

[0758] Understanding changes to contracts and terms and conditions and clarifying risks

[0759] Step 1:

[0760] The server periodically crawls the specified list of websites to retrieve the latest version of the contract or terms and conditions, and stores the retrieved data in storage.

[0761] Step 2:

[0762] The server uses a difference detection library (e.g., diff-match-patch) to compare the latest version of the contract or clause with the previous version and identify the changes.

[0763] Step 3:

[0764] The server then analyzes the identified changes with a risk assessment algorithm to classify and assess the risk. For example, if there is a change related to the handling of personal information, it will classify it as a high risk.

[0765] Step 4:

[0766] The server stores the analysis results in a database and prepares it so that risk information can be visually presented when accessed by a user.

[0767] Step 5:

[0768] When a user accesses the risk information page, the device displays the changes and risks in a visually easy-to-understand format, such as color-coding.

[0769] Evaluation and disclosure of contract details

[0770] Step 1:

[0771] The user uses an input form on the terminal to input an evaluation score and comments on the contract contents.

[0772] Step 2:

[0773] The terminal transmits the evaluation score and comments entered by the user to the server.

[0774] Step 3:

[0775] The server stores the received evaluation data in a database and performs real-time statistical processing, such as calculating the average evaluation score and frequently occurring comments.

[0776] Step 4:

[0777] The server visualizes the results and updates the evaluation page so that other users can see them.

[0778] Step 5:

[0779] When other users access the rating page, the terminal displays the aggregated rating scores and comments.

[0780] Individual contract risk assessment

[0781] Step 1:

[0782] The user uses the upload function on the device to upload the contract in scanned or PDF format.

[0783] Step 2:

[0784] The terminal transmits the uploaded contract to the server.

[0785] Step 3:

[0786] The server uses OCR (Optical Character Recognition) software to extract text data from the contract.

[0787] Step 4:

[0788] The server then analyzes the extracted text data using a risk assessment algorithm to identify risks, such as risks related to payment terms or construction extensions.

[0789] Step 5:

[0790] The server stores the evaluation results in a database and makes them available for user review.

[0791] Step 6:

[0792] The device provides the user with the risk assessment results in an easily identifiable manner, highlighting areas of concern or specific risk areas.

[0793] Drafting and providing contract amendment proposals

[0794] Step 1:

[0795] The user uses an input form on the terminal to input requests for changes to the contract contents, such as shortening the contract period or changing the payment terms.

[0796] Step 2:

[0797] The terminal transmits the input desired changes to the server.

[0798] Step 3:

[0799] The server uses an automated contract generation library to generate a new draft contract based on the inputs.

[0800] Step 4:

[0801] The server checks the generated draft contract using an internal review system and makes corrections as necessary.

[0802] Step 5:

[0803] The server stores the revised draft contract in a database so that it can be provided to the user.

[0804] Step 6:

[0805] The terminal displays the new draft contract to the user and makes it available for download if desired.

[0806] Operation using emotion engine (processing based on additional claims)

[0807] Step 1:

[0808] The emotion engine analyzes facial expressions and voice data in real time while the user is viewing a contract or terms and conditions.

[0809] Step 2:

[0810] The server receives the emotion data sent from the emotion engine and identifies the user's emotional state based on the analysis results. For example, if the user shows surprise or anxiety, the emotion data is reflected in the risk assessment.

[0811] Step 3:

[0812] The device dynamically changes how it presents risk information depending on the user's emotional state: if the user feels anxious, it displays additional details or advice.

[0813] Step 4:

[0814] The server stores the emotion data in a database and uses it as reference information for future interactions.

[0815] Step 5:

[0816] The emotion engine weights contract and risk assessment results based on the user's emotional data, providing more personalized results.

[0817] Step 6:

[0818] The user can use the terminal to make decisions or make changes to the contract contents based on feedback and advice from the emotion engine.

[0819] In this way, by explaining each processing step in detail, the specific operation of the system and its linkage with the emotion engine become clear.

[0820] Example 2

[0821] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0822] The contents of contracts and terms and conditions change frequently, making it difficult to quickly and accurately grasp these changes. Furthermore, risk assessment and information presentation that takes user emotions into consideration are not adequately implemented, making it difficult for users to accurately understand risks and respond appropriately. Conventional systems do not dynamically adjust the display method based on the user's emotional state, which can result in a poor user experience. Furthermore, when users input their evaluation of specific contract content, there is also the issue of the evaluation not being properly fed back based on their emotions.

[0823] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for periodically acquiring the latest version of the contract or terms and conditions, a means for comparing the acquired contract or terms and conditions with previous versions to identify differences, a means for analyzing the identified differences and classifying and assessing risks, a means for visually presenting the classified and assessed risks to the user, and a means for recognizing the user's emotions in real time and dynamically adjusting the display method based on the recognition results. This allows the user to quickly and accurately grasp changes to the contract or terms and understand the risks. Furthermore, the dynamic presentation of information according to the user's emotions improves the user experience. Furthermore, more appropriate feedback can be provided by incorporating the user's emotional evaluation into statistical processing.

[0824] "Means for periodically obtaining the latest version of the contract or terms and conditions" refers to a system that automatically obtains the latest version of the contract or terms and conditions from a website or database at regular intervals.

[0825] "Means for comparing the acquired contract or terms and conditions with previous versions to identify differences" refers to algorithms or processes for comparing the content of the latest contract or terms and conditions with previous versions and identifying any changes.

[0826] The "means of analyzing identified differences and classifying and assessing risks" is a mechanism for analyzing the changed parts in detail, extracting each risk element, and classifying and assessing them.

[0827] "Means for visually presenting classified and assessed risks to users" refers to an interface that displays assessment results in a format that is easy for users to understand, and a mechanism that provides visual feedback.

[0828] "Means for recognizing a user's emotions in real time and dynamically adjusting the display method based on the recognition results" refers to a technology that monitors a user's emotional state in real time through sensor devices such as cameras and microphones, and automatically changes the content and method of display according to the obtained emotional data.

[0829] The "means for users to input evaluations of the contract contents" is an interface that allows users to input evaluations and comments on the contract and terms and conditions.

[0830] The "means for saving the input evaluation data and performing statistical processing in real time" refers to a system for saving user evaluations in a database and instantly analyzing and statistically processing the data.

[0831] The "means for disclosing aggregated evaluation data to other users" is an interface that provides the analyzed and statistically processed evaluation results in a form that can be accessed by other users.

[0832] "Means for incorporating user emotional evaluations into statistical processing" refers to a process for analyzing user emotional data together with evaluation data to provide statistical feedback and improvements.

[0833] "Means for scanning or uploading individual contract contents" means a method by which a user can convert a physical contract into digital form or submit an existing electronic file to the system.

[0834] "Means for extracting the text of an uploaded contract" refers to technology for extracting text information from the digital data of a scanned or uploaded contract, including OCR (optical character recognition) technology.

[0835] The "means for analyzing extracted text data and assessing risks" refers to a process of analyzing the contract contents in detail based on the extracted text information, and identifying and assessing potential risks.

[0836] "Means for providing assessed risk information to a user" means an interface for providing analyzed and assessed risk information to a user in a visual or notification format.

[0837] "Means for recognizing the user's emotions and adjusting the way risk information is presented based on the results of that recognition" refers to a mechanism that analyzes the user's emotional data in real time and changes the way risk information is presented based on the results.

[0838] This invention is a system that presents changes to contracts and terms and conditions to users, evaluates and notifies them of the risks involved, and dynamically adjusts the interface based on user emotions. The detailed configuration of the system and specific implementation methods are described below.

[0839] System configuration

[0840] This system consists of a server, a terminal, a user, and an emotion engine. The server is responsible for data management and analysis of contracts and terms and conditions, and emotional data processing, while the terminal provides the user interface. The emotion engine recognizes user emotions in real time and optimizes system operation based on them.

[0841] Hardware and software used

[0842] Server: Performs data analysis and management. Software used includes TensorFlow and PyTorch, the Tesseract OCR engine as OCR technology, and MySQL and PostgreSQL for database management.

[0843] Terminal: Provides the user interface. Dynamically generates pages using HTML / CSS and JavaScript using a web browser.

[0844] Emotion Engine: Recognizes user emotions using Microsoft Azure Cognitive Services and OpenCV.

[0845] System Operation

[0846] Understanding changes to contracts and terms and conditions and clarifying risks

[0847] The server periodically scrapes the website to retrieve the latest version of the contract and terms and conditions, using Python's BeautifulSoup and Scrapy.

[0848] The server compares the retrieved data with previous versions and uses a Diff check algorithm to identify changes.

[0849] The server analyzes the changes and classifies and assesses the risks using a risk assessment algorithm (using TensorFlow and PyTorch).

[0850] The server stores the classified and evaluated risk information in a database (MySQL or PostgreSQL) and provides it to the terminal.

[0851] User Interface

[0852] When a user accesses a risk information page, the device visually displays the changes and the associated risks, using color coding and icons for visual feedback.

[0853] The emotion engine captures user emotional data via the camera and microphone, analyzes it using Microsoft Azure Cognitive Services and OpenCV, and if the user feels anxious or surprised, it will change the way it is displayed and provide additional information or advice.

[0854] Evaluation and disclosure of contract details

[0855] The user inputs their evaluation of the contract contents through the terminal and sends it to the server.

[0856] The server processes the evaluation data in real time and publishes the results to other users using NumPy and Pandas.

[0857] The emotion engine recognizes how users feel when they are entering their ratings and incorporates that emotional data into the rating process.

[0858] Individual contract risk assessment

[0859] Users upload individual contracts as scanned or electronic files.

[0860] The device receives this and sends it to a server, which uses OCR technology (such as Tesseract OCR) to extract the text and analyzes it with a risk assessment algorithm.

[0861] The server notifies the terminal of the evaluation results and displays the necessary risk information.

[0862] The emotion engine recognizes the emotions users feel when reviewing risk information and adjusts how risks are presented based on that information.

[0863] Drafting and providing contract amendment proposals

[0864] If the user wishes to change the contract, they enter the changes into their device and send them to the server, which then uses an automated contract generation library (such as the Docxtpl library) to generate a new contract draft and provides it to the user after review.

[0865] The emotion engine takes user emotions into consideration when creating contract change proposals, supporting stress-free operation.

[0866] Examples and prompts

[0867] Example 1: Changes to the terms of use of an online storage service

[0868] The server retrieves the latest terms of use and compares them with the previous terms.

[0869] If there are any changes regarding the handling of personal information, the risks will be analyzed in detail and notified to the device.

[0870] The emotion engine recognizes the user's concerns and provides detailed explanations and additional advice.

[0871] Prompt Sentence Examples

[0872] I am reviewing the new terms of service for an online storage service. Please obtain the latest version and identify the differences from the previous version. Please analyze in detail the changes, especially those related to personal information, and assess the risks involved. Please explain how the sentiment engine works and provides additional advice if the user feels uneasy.

[0873] Example 2: Contract for the construction of a new building

[0874] Users upload construction contracts.

[0875] The server extracts the text using OCR and performs a risk assessment.

[0876] The terminal will notify you of risks such as construction delays and additional costs.

[0877] The emotion engine detects users' surprise or concern and provides detailed solutions.

[0878] Prompt Sentence Examples

[0879] I uploaded a contract for constructing a new building. I want you to use OCR technology to extract the text from the contract and perform a risk assessment. I want you to notify the user of risks such as delays and additional costs, and explain how the emotion engine will react if the user is surprised or worried.

[0880] The above is a specific embodiment of the present invention.

[0881] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0882] Step 1:

[0883] The server periodically retrieves the latest version of the contract or terms and conditions from the website. Python's BeautifulSoup and Scrapy are used to scrape the webpage and extract the contract or terms and conditions links from the HTML tags. This allows the server to retrieve the latest version of the contract or terms and conditions data. The input is the URL of a specific website, and the output is the latest contract or terms and conditions data.

[0884] Step 2:

[0885] The server compares the retrieved contract or clause data with past versions to identify changes. Specifically, it uses a Diff check algorithm to compare the lines of each text data. When changes are identified, that information is output as a difference list. The input is the latest version of the text and the past version of the text, and the output is a list of changes.

[0886] Step 3:

[0887] The server analyzes the identified changes and classifies and evaluates the risk using a risk assessment algorithm. It uses machine learning frameworks such as TensorFlow and PyTorch to score the risk of each change. The input is a list of changes, and the output is classified and evaluated risk information.

[0888] Step 4:

[0889] The server stores the classified and evaluated risk information in a database. The database used is MySQL, PostgreSQL, etc., and writes the risk information to the database in an appropriate format. The input is the classified and evaluated risk information, and the output is the risk information stored in the database.

[0890] Step 5:

[0891] When a user accesses a risk information page, the terminal visually displays the changes and risks. Using HTML / CSS and JavaScript, the changed parts are displayed with color coding and icons, allowing the user to understand the risks at a glance. The input is risk information retrieved from the database, and the output is the visually displayed risk information.

[0892] Step 6:

[0893] The emotion engine uses the user's camera and microphone to capture emotional data in real time and analyzes it using Microsoft Azure Cognitive Services and OpenCV. It dynamically adjusts how risk information is displayed based on the user's emotional state. For example, if the user feels anxious, it will pop up additional details and advice. The input is the user's video and audio, and the output is the dynamically adjusted display method.

[0894] Step 7:

[0895] Users input their evaluation of the contract contents through their terminals and send the data to the server. Evaluation data is collected by filling out the evaluation form and clicking the submit button. The input is the user's evaluation data, and the output is the evaluation data sent to the server.

[0896] Step 8:

[0897] The server stores the evaluation data sent by users in a database and performs statistical processing in real time using NumPy and Pandas. The aggregated results are reflected on a web page and made publicly accessible to other users. The input is the user's evaluation data, and the output is the aggregated evaluation data.

[0898] Step 9:

[0899] The user scans or uploads individual contracts in electronic file format and sends them to the server via the terminal. The terminal provides an upload button and sends the selected file to the server. The input is the contract in electronic file format, and the output is the contract data sent to the server.

[0900] Step 10:

[0901] The server uses the Tesseract OCR engine to extract the text of the uploaded contract and parses it with a risk assessment algorithm. The input is the image data of the contract, and the output is the extracted text data and assessed risk information.

[0902] Step 11:

[0903] The server notifies the terminal of the evaluation results and provides risk information to the user. The necessary risk information is visually displayed on the terminal. The input is the evaluated risk information, and the output is the visually displayed risk information.

[0904] Step 12:

[0905] The emotion engine recognizes the user's emotions when reviewing risk information and adjusts the presentation of risk information based on that information. If the user expresses surprise or disappointment, it displays additional explanations and suggested solutions. The input is the user's emotional data, and the output is the adjusted presentation of risk information.

[0906] Step 13:

[0907] If a user wishes to change the contents of the contract, they enter the changes via their terminal and send them to the server. They enter the changes in the input form and click the send button. The input is the changes the user wishes to make, and the output is the changes sent to the server.

[0908] Step 14:

[0909] The server generates a new draft contract using an automated contract generation library (such as the Docxtpl library). The input is the user's desired changes, and the output is the generated draft contract.

[0910] Step 15:

[0911] The server provides the generated contract draft to the user after review, and the emotion engine takes the user's emotions into consideration to support stress-free operation. The input is the generated contract draft and the user's emotion data, and the output is the provided contract draft and adjusted operation method.

[0912] (Application example 2)

[0913] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0914] It is important to visually present changes to contracts and terms and conditions to users and effectively evaluate and classify the risks, making it easier for users to understand the content of the contract. However, presenting risks without taking into account the anxiety and confusion that accompanies users' emotions can lead to different perceptions of information and delays in appropriate responses. Furthermore, when users evaluate contract content or upload individual contracts to check risks, a poor user experience can result if the interface is not dynamically adjusted based on the user's emotions.

[0915] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for periodically acquiring the latest version of the contract or terms of use, means for comparing the acquired contract or terms of use with previous versions to identify differences, means for analyzing the identified differences and classifying and assessing risks, means for visually presenting the classified and assessed risks to the user, means for recognizing the user's emotions in real time, and means for dynamically adjusting the interface based on the recognized emotions. This not only makes it easier for the user to understand risks when reviewing the contract or its contents, but also makes it possible to provide optimal information according to the user's emotions.

[0916] "Means for periodically obtaining the latest version of the agreement or terms of use" refers to a function that automatically obtains the latest version of the agreement or terms of use online or from a database on a regular basis.

[0917] "Means for comparing the acquired contract or terms of use with a previous version to identify differences" refers to an analysis function for comparing the latest acquired contract or terms of use with a previous version and identifying differences in changes or additions.

[0918] "Means for analyzing identified differences and classifying and assessing risks" refers to a function for identifying and classifying risks and assessing their importance and impact by analyzing identified differences.

[0919] "Means for visually presenting classified and assessed risks to users" refers to a function that graphically displays assessed risk information to users and provides information in a visually easy-to-understand format.

[0920] "Means of recognizing the user's emotions in real time" refers to an analytical function that analyzes the user's voice, facial expressions, behavior, etc., and recognizes the emotions the user is feeling in real time.

[0921] "Means for dynamically adjusting the interface based on recognized emotions" refers to a function that dynamically changes and optimizes the content and manner of display of the user interface in response to the recognized emotions of the user.

[0922] "Means for users to input evaluations of the contract contents" refers to an interface that allows users to input their own evaluations and opinions of the contract contents they are using.

[0923] "Means for adjusting the evaluation process based on emotion recognition data" refers to a function that adjusts the evaluation process and the way evaluation results are displayed by referring to the user's emotion data.

[0924] "Means for scanning or uploading the contents of individual contracts" refers to the function of scanning individual contracts from paper and converting them into digital data, or uploading them directly in electronic file format.

[0925] "Means for extracting text from uploaded contracts" refers to a function that extracts text data from uploaded contracts and converts it into an analyzable format.

[0926] "Means for recognizing emotions when checking risk information and adjusting the way in which risk is presented" refers to a function that recognizes the emotions of users when checking risk information and adjusts the way in which risk information is presented and its content based on those emotions.

[0927] This system presents changes to contracts and terms and conditions to users, evaluates and notifies them of the risks involved, and dynamically adjusts the interface by recognizing the user's emotions. This system consists of a server, terminals, users, and an emotion engine.

[0928] Overall system configuration

[0929] The server is responsible for data management, analysis, and emotional data processing of contracts and terms and conditions. The server periodically retrieves the latest version of the contract or terms and conditions from the website and compares it with previous versions to identify any discrepancies. The retrieved data is analyzed using a risk assessment algorithm to classify and assess risks. This assessment information is stored in a database.

[0930] The device provides a user interface using a smartphone. When a user accesses a risk information page, the device displays the changes and their associated risks in a visually easy-to-understand format. It also includes an emotion engine that analyzes the user's voice, facial expressions, and behavior to recognize emotions in real time, dynamically adjusting the interface based on the emotional data. For example, if the user is feeling anxious, the device will provide more detailed information and advice on that point.

[0931] Understanding changes to contracts and terms and conditions and clarifying risks

[0932] The server compares the latest version of the contract or clause with the previous version to identify any changes. The identified differences are analyzed by a risk assessment algorithm to classify and evaluate the risks. The classified and evaluated risk information is stored in a database for visual presentation.

[0933] User emotion recognition and interface adjustment

[0934] The device is equipped with an emotion engine that recognizes the user's emotions as they review risk information. The emotion engine analyzes the user's voice, facial expressions, and behavior to recognize emotions in real time. Based on the emotion data, the user interface is dynamically adjusted according to the recognized emotion. For example, if the user feels anxious, additional details and advice are added. This allows the user to understand the contract details and make a decision with confidence.

[0935] User ratings and sentiment data

[0936] The terminal provides an interface for users to input their ratings of the contract contents. The user's rating input is sent to the server in real time and stored in a database. The server performs statistical processing of the rating data in real time and makes the results available to other users. An emotion engine also recognizes the user's emotions, and the emotion data is reflected in the rating process. For example, the ratings of users who show very positive emotions may be weighted.

[0937] Individual contract risk assessment

[0938] Users scan or upload individual contracts as electronic files. The device receives the documents and sends them to the server. The server uses OCR technology to extract text from the contract and analyzes it with a risk assessment algorithm. The results are then reported to the user, and the necessary risk information is displayed on the device.

[0939] Specific examples

[0940] For example, if a user is considering new terms of use for an online storage service, the server retrieves the latest terms and compares them with previous terms to identify any changes. If the changes relate to the handling of personal information, the server performs a detailed analysis of the risks and notifies the user. If the information makes the user feel uneasy, the emotion engine recognizes this emotion and provides more detailed information and additional advice. Similarly, if a user uploads a contract for the construction of a new building, the server analyzes the contract and notifies the user of specific risks (e.g., construction delays, additional costs). If the user is surprised or worried, the emotion engine detects this and provides more detailed countermeasures for the risk.

[0941] Example prompts for generative AI models

[0942] "How can we assess the risk regarding the latest security terms of service changes, recognize user sentiment and provide more information?"

[0943] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0944] Step 1:

[0945] The server periodically retrieves the latest version of the contract or terms of use from an online or database. Specifically, it retrieves data via a specific URL or API and stores it in a local database. The input is the URL or API information to be retrieved, and the output is the retrieved latest version of the contract or terms of use data.

[0946] Step 2:

[0947] The server compares the latest version of the contract or terms of use with previous versions to identify differences. This process uses a difference analysis library such as difflib to detect differences in text. The input is the latest and previous versions of the contract data, and the output is the identified differences.

[0948] Step 3:

[0949] The server analyzes the identified differences and classifies and assesses the risk using a risk assessment algorithm. In this process, risks are classified as high, medium, low, etc. based on specific keywords or phrases. The inputs are the difference information and the risk assessment algorithm, and the output is the classified and assessed risk data.

[0950] Step 4:

[0951] When a user accesses the risk information page, the terminal visually displays the risk data obtained from the server. Specifically, the degree of risk is clearly expressed using color coding and icons. The input is risk data, and the output is risk information displayed on the user interface.

[0952] Step 5:

[0953] The device runs an emotion engine that analyzes the user's voice, facial expressions, and behavior to recognize emotions in real time. The emotion engine analyzes the collected data and determines the user's emotional state (e.g., anxiety, relief, surprise). The input is the user's voice, facial expressions, and behavior data, and the output is the recognized emotion data.

[0954] Step 6:

[0955] The device dynamically adjusts the user interface based on the recognized emotion, for example, displaying a more information box or additional advice if the user is feeling anxious. The input is emotion data and user interface data, and the output is an adjusted user interface.

[0956] Step 7:

[0957] When a user inputs an evaluation of the contract contents, the terminal sends the evaluation data to the server. In addition, emotional data recognized by the emotion engine is also sent. The input is the user's evaluation and emotional data, and the output is the evaluation data sent to the server.

[0958] Step 8:

[0959] The server processes the submitted evaluation data in real time and publishes the results to other users. In this process, the evaluation data is aggregated and statistical information about specific items is generated. The input is the evaluation data, and the output is the statistically processed evaluation results.

[0960] Step 9:

[0961] When a user scans or uploads an individual contract, the device sends the contract to the server, which uses OCR technology to extract text from the contract and analyzes it with a risk assessment algorithm. The input is the uploaded contract data, and the output is the analyzed risk information.

[0962] Step 10:

[0963] When providing risk information to the user, the device monitors the user's emotions in real time and adjusts the risk presentation method. Based on the recognized emotion data, it provides additional explanations and countermeasures. The input is the user's emotion data and risk information, and the output is the adjusted risk presentation method.

[0964] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0965] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0966] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0967] [Third embodiment]

[0968] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0969] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0970] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0971] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0972] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0973] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0974] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0975] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0976] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0977] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0978] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0979] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0980] The present invention is a system designed to enable users to easily understand the contents of contracts and terms and conditions, and is realized using the following means.

[0981] Overall system configuration

[0982] This system consists of three main components: a server, a terminal, and a user. The server manages and analyzes data on contracts and clauses, while the terminal provides the user interface. Users use the terminal to evaluate, upload, and input proposed changes to contracts and clauses.

[0983] Understanding changes to contracts and terms and conditions and clarifying risks

[0984] The server periodically retrieves the latest versions of contracts and terms and conditions published on specific websites from the Internet. The server stores this data in storage and compares it with previous versions. Changes are identified as differences as a result of the comparison, and are classified and analyzed using a risk assessment algorithm. The analyzed risk information is visually presented to the user. For example, if a provision regarding data sharing is added to the new terms of use of a social media platform, that information is highlighted.

[0985] Evaluation and disclosure of contract details

[0986] Users use their devices to input their evaluations of contract details. For example, they can input an evaluation score indicating whether they were satisfied or dissatisfied with a contract with a certain internet service provider. The device sends this evaluation to a server, which stores the evaluation data in a database. The server statistically processes the evaluations of all users, generates information such as average scores and frequently occurring comments, and makes this information public to other users. Other users can use this public information as a reference when considering the contract details.

[0987] Individual contract risk assessment

[0988] Users use their devices to scan or upload individual contracts, such as land sales or building construction contracts, as electronic files. The devices then send the uploaded contracts to a server. The server then uses OCR technology to extract text data from the contracts, analyzes the text data, and performs a risk assessment. The assessment results identify specific risks in the contract (such as construction delays or additional costs) and provide them to the user.

[0989] Drafting and providing contract amendment proposals

[0990] If a user wishes to change the contract details, they use their device to input the specific details. For example, if they wish to shorten the contract period for building construction work, they can input this information. The device then sends this information to the server, which then automatically generates a new contract based on the proposed changes. The generated contract draft is then provided to the user for final confirmation and download.

[0991] Specific examples

[0992] For example, if a user is considering new terms of use for an online storage service, the server retrieves the latest terms of use, compares them with previous terms, and identifies any changes. If the changes relate to the handling of personal information, the server analyzes the risks in detail and notifies the user. The user can then use this information to consider using the service.

[0993] In addition, if a user uploads a contract for the construction of a new building, the server analyzes the contract and notifies the user of specific risks (e.g., construction delays, additional costs), allowing the user to review the contract and, if necessary, input proposed changes and generate a new contract.

[0994] In this way, the present invention makes it easier for users to understand the contents of contracts and terms and conditions, helps them understand potential risks, and provides a method for efficiently making changes to the contract contents.

[0995] The processing flow will be explained below.

[0996] Understanding changes to contracts and terms and conditions and clarifying risks

[0997] Step 1:

[0998] The server crawls the specified website URL list to retrieve the latest version of the contract or terms and conditions, and stores the retrieved data in storage.

[0999] Step 2:

[1000] The server uses a difference detection library (e.g., diff-match-patch) to compare the latest version of the contract or clause with the previous version and identify the changes.

[1001] Step 3:

[1002] The server analyzes the identified changes and classifies and assesses the risk using a risk assessment algorithm. For example, if a change related to the handling of personal information is detected, the server classifies the risk as high.

[1003] Step 4:

[1004] The server stores the analysis results in a database and prepares a visual display of the risks when accessed by the user.

[1005] Step 5:

[1006] When a user accesses the risk information page, the device visually displays the changes and the risks involved using color coding, etc.

[1007] Evaluation and disclosure of contract details

[1008] Step 1:

[1009] The user uses an input form on the terminal to input an evaluation score and comments on the contract contents.

[1010] Step 2:

[1011] The terminal transmits the evaluation score and comments entered by the user to the server.

[1012] Step 3:

[1013] The server stores the received evaluation data in a database and performs real-time statistical processing, such as calculating the average evaluation score and frequently occurring comments.

[1014] Step 4:

[1015] The server visualizes the results and updates the evaluation page so that other users can see them.

[1016] Step 5:

[1017] When other users access the rating page, the terminal displays the aggregated rating scores and comments.

[1018] Individual contract risk assessment

[1019] Step 1:

[1020] The user uses the upload function on the device to scan the contract or upload it in PDF format.

[1021] Step 2:

[1022] The terminal transmits the uploaded contract to the server.

[1023] Step 3:

[1024] The server uses OCR (Optical Character Recognition) software to extract text data from the contract.

[1025] Step 4:

[1026] The server analyzes the extracted text data and identifies risks using a risk assessment algorithm.

[1027] Step 5:

[1028] The server organizes the risk information and stores it in a database in order to provide the evaluation results to the user.

[1029] Step 6:

[1030] The terminal visually presents the risk assessment results to the user, for example by highlighting specific risk areas.

[1031] Drafting and providing contract amendment proposals

[1032] Step 1:

[1033] The user uses the input form on the terminal to input the changes he or she wishes to make to the contract contents.

[1034] Step 2:

[1035] The terminal transmits the input desired changes to the server.

[1036] Step 3:

[1037] The server uses an automated contract generation library to generate a new draft contract based on the user's input.

[1038] Step 4:

[1039] The server checks the generated draft contract using an internal review system and makes corrections as necessary.

[1040] Step 5:

[1041] The server stores the revised draft contract in a database in order to provide it to the user.

[1042] Step 6:

[1043] The terminal will visually display the new draft contract to the user and make it available for download if desired.

[1044] In this way, by explaining each processing step separately, it becomes easier to understand the specific operation of the system.

[1045] Example 1

[1046] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1047] The contents of contracts and terms and conditions are complex and contain many technical terms, making them difficult for general users to understand. Furthermore, tracking changes to contracts and terms and assessing risks is time-consuming and requires specialized knowledge. In addition, there are limited ways for users to share their assessments of contract contents with other users. This makes it difficult for users to understand contract contents, grasp risks, and make decisions based on the assessments of other users.

[1048] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1049] In this invention, the server includes means for periodically obtaining the latest version of the contract or terms and conditions, means for comparing the obtained contract or terms and conditions with past versions to identify differences, means for analyzing the identified differences and classifying and assessing risks, means for visually presenting the classified and assessed risks to the user, means for extracting text data from the contract using machine reading comprehension technology, means for the user to input changes to the contract, and means for automatically generating a new draft contract based on the input changes. This allows the user to easily understand changes and risks in the contract or terms and conditions, efficiently create a contract that reflects their own opinions, and also enables them to refer to evaluation information from other users.

[1050] A "contract" is a document that sets out the rights and obligations between the parties under a particular contract.

[1051] "Terms and conditions" are documents that set out the standard terms and conditions offered by a company or organization.

[1052] "Latest version" means the most recent version of the agreement or terms and conditions.

[1053] "Means of collection" refers to methods and technologies for automatically collecting data.

[1054] "Means for comparing and identifying differences" refers to methods and techniques for comparing different versions of contracts or terms and conditions and identifying changes.

[1055] "Means for classifying and assessing risks" refers to methods and techniques for analyzing changes to contracts and clauses to identify, classify, and assess potential risks.

[1056] "Visual presentation means" refers to methods and technologies that visually display analysis results to users in an easy-to-understand manner.

[1057] "Machine reading comprehension technology" refers to technology for automatically reading and understanding text data.

[1058] "Means for extracting text data" refers to methods or techniques for extracting text information from scanned images or uploaded files.

[1059] "Means for users to input changes to the contract" refers to the methods and technologies that allow users to input their desired changes to the contract into the system.

[1060] "Means for automatically generating a new draft contract" refers to methods or technologies that automatically create a new contract based on changes entered by the user.

[1061] The present invention is a system designed to enable users to easily understand the contents of contracts and terms and conditions, and is composed of three main elements: a server, a terminal, and a user.

[1062] Server Roles

[1063] The server manages and analyzes data on contracts and clauses. Specifically, the server periodically retrieves the latest versions of contracts and clauses published on specific websites from the Internet and stores the retrieved data in storage. An AWS S3 bucket is used to store the contract data, and the program performs web scraping using Python and the Beautiful Soup library. The server also compares the old and new contracts to identify differences and calculates text differences using the diff-match-patch library. The NLTK library is then used to classify and evaluate the risk of the changes using a risk assessment algorithm. The evaluated risk information is visually presented to the user. The front end uses React to highlight the results.

[1064] Device Role

[1065] The terminal provides a user interface, allowing users to evaluate, upload, and input proposed changes to the contract contents. For example, when a user scans or uploads an individual contract as an electronic file, the terminal sends this data to the server. The server uses OCR technology (Tesseract OCR) to extract text data from the contract and analyzes the text data to evaluate risk. If the user wishes to make changes to the contract contents, they can use the terminal to enter the specific details, which are then sent to the server. The server then automatically generates a new contract based on the proposed changes. The document is generated using a specific template, and can be downloaded after final confirmation.

[1066] User Roles

[1067] Users operate the system to evaluate their own contracts and input proposals for changes to the contract and terms. For example, they can use an evaluation form to input their level of satisfaction with a contract with an internet service provider. The evaluation results are sent to a server, where they are statistically processed in real time and made available to other users.

[1068] Specific examples

[1069] For example, if a user is considering new terms of use for an online storage service, the server retrieves the latest terms of use, compares them with previous terms, and identifies any changes. If the changes relate to the handling of personal information, the server analyzes the risks in detail and notifies the user. The user can then use this information to consider using the service.

[1070] In addition, when a user uploads a contract for constructing a new building, the server analyzes the contract, identifies risks (e.g., construction delays, additional costs) and notifies the user, who can then review the contract and, if necessary, input proposed changes to generate a new contract.

[1071] Prompt Sentence Examples

[1072] An example of a prompt to be input to a generative AI model is, "I would like to develop a system that analyzes contract contents, identifies risks, and presents them visually. This system retrieves the latest versions of contracts and terms and conditions from the Internet and compares them with previous versions. It uses a risk assessment algorithm to classify and analyze risks by category and notify the user of the results."

[1073] In this way, the present invention makes it easier for users to understand the contents of contracts and terms and conditions, helps them understand potential risks, and provides a method for efficiently making changes to the contract contents.

[1074] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1075] Step 1:

[1076] The server periodically retrieves the latest version of the contract or terms and conditions from a specific website on the Internet. Specifically, it uses Python's Beautiful Soup library to retrieve HTML content from a specified URL and extracts links to the new contract or terms and conditions. The retrieved data is saved in text format.

[1077] Enter: Website URL

[1078] Output: Text data of the latest contracts and terms and conditions

[1079] Step 2:

[1080] The server stores the acquired contract and clause data in cloud storage such as an AWS S3 bucket, which is used for later comparison and analysis.

[1081] Input: Text data of the latest contracts and terms and conditions

[1082] Output: File saved in cloud storage

[1083] Step 3:

[1084] The server compares the old and new contracts and clauses and identifies the changes as differences. This is achieved by calculating the text differences using the diff-match-patch library. This difference data becomes the basis for change analysis.

[1085] Input: Text data of past and latest contracts and terms and conditions

[1086] Output: Diff data of changes

[1087] Step 4:

[1088] The server analyzes the delta data and uses a risk assessment algorithm to classify and assess the risk. It uses the NLTK library to perform text analysis to identify the risks of the changes. This risk information is then categorized.

[1089] Input: Difference data of changes

[1090] Output: Assessed risk information

[1091] Step 5:

[1092] The server visually presents the assessed risk information to the user, and a front-end is built using React to highlight changes and risks.

[1093] Input: Assessed risk information

[1094] Output: Visual risk information displayed in the user interface

[1095] Step 6:

[1096] The user uses a terminal to input their evaluation of the contract contents, and enters the evaluation score and comments using an HTML form, and the data is sent to the server.

[1097] Input: User rating score and comments

[1098] Output: Rating data sent to the server

[1099] Step 7:

[1100] The server statistically processes all users' rating data and compiles average scores and frequently occurring comments in real time. It uses the Pandas library to aggregate the rating data and generate statistical information.

[1101] Input: Multiple user rating data

[1102] Output: Aggregated average scores and frequently occurring comments

[1103] Step 8:

[1104] The server then publishes the aggregated evaluation data to other users, who can use the published information as a reference when considering contract details.

[1105] Input: Aggregated average rating score and frequently occurring comments

[1106] Output: Aggregate information displayed in the user interface

[1107] Step 9:

[1108] The user uses the terminal to scan or upload the individual contract in electronic file format, and the terminal sends the uploaded data to the server.

[1109] Input: Scanned or uploaded agreement

[1110] Output: Agreement data sent to the server

[1111] Step 10:

[1112] The server extracts text data from the uploaded contract using OCR technology. It uses the Tesseract OCR library to extract text from images.

[1113] Input: Image data of the uploaded contract

[1114] Output: Extracted text data

[1115] Step 11:

[1116] The server analyzes the extracted text data and performs risk assessment. It uses a risk assessment algorithm to identify specific risks (e.g., construction delays, additional costs).

[1117] Input: Extracted text data

[1118] Output: Assessed risk information

[1119] Step 12:

[1120] The server provides the assessed risk information to the user, who is then notified and displayed in a visual interface.

[1121] Input: Assessed risk information

[1122] Output: Risk information provided to the user

[1123] Step 13:

[1124] If a user wishes to change the contents of their contract, they use their device to input the specific changes, and the input data is sent to the server.

[1125] Input: User requests to change contract details

[1126] Output: Changes sent to the server

[1127] Step 14:

[1128] The server automatically generates a new contract based on input from the user, creates a new contract using a specific template, and provides it to the user.

[1129] Input: Proposed changes to the contract contents desired by the user

[1130] Output: The new contract that is generated.

[1131] In this way, the present invention provides a system that makes it easier for users to understand the contents of contracts and terms and conditions, and assists in understanding and evaluating potential risks.

[1132] (Application example 1)

[1133] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1134] There is a need for a system that can quickly identify changes and risks in contracts and clauses, allowing users to easily understand them. However, existing systems require users to manually compare and analyze contracts and clauses, which is extremely labor-intensive. Furthermore, risk assessment of contract content and feedback information from other users are not centrally provided. This can lead to delays and inaccuracies in understanding contract content and appropriate risk assessment. This invention aims to solve these issues by extracting text from contracts and clauses, analyzing risks, visually presenting them through a user interface, and performing detailed analysis using a generative AI model.

[1135] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1136] In this invention, the server includes: means for periodically obtaining the latest version of the contract or terms and conditions; means for comparing the obtained contract or terms and conditions with previous versions to identify differences; means for analyzing the identified differences and classifying and assessing risks; means for visually presenting the classified and assessed risks to the user; means for the user to photograph or upload the contract or terms and conditions; means for using optical character recognition technology to extract text data; means for analyzing the extracted text data and assessing risks; and means for providing a user interface for visually displaying the assessed risk information to the user. This allows the user to quickly understand changes and risks in the contract or terms and conditions and perform appropriate risk assessments. Furthermore, a generative AI model is used to perform detailed analysis of the contract content, which is expected to promote user understanding and improve assessment accuracy.

[1137] "Means for periodically obtaining the latest version of contracts or terms and conditions" refers to technology that automatically collects the latest information on contracts and terms and conditions that are published on the Internet.

[1138] "Means for identifying differences by comparing acquired contracts or terms and conditions with past versions" refers to a technology that compares the latest collected contracts and terms and conditions with past versions to clarify changes.

[1139] "Means for analyzing identified differences and classifying and assessing risks" refers to algorithms or programs for analyzing changes and identifying, classifying, and assessing the risks.

[1140] "Means for visually presenting classified and assessed risks to the user" refers to a technology that displays analyzed risk information in an easy-to-understand manner through a user interface.

[1141] "Means for users to photograph or upload contracts or terms and conditions" refers to technology that allows users to send images or files of contracts or terms and conditions to the system using a smartphone or computer.

[1142] "Means using optical character recognition technology to extract text data" refers to OCR (optical character recognition) technology to extract text information from uploaded images.

[1143] The "means for analyzing extracted text data and assessing risk" refers to a program or algorithm for analyzing the contract content based on the extracted text information and assessing the risk.

[1144] "Means for providing a user interface for visually displaying assessed risk information to a user" refers to an interface technology for displaying assessment results in a form that is visually easy for a user to understand.

[1145] The "means for users to input evaluations of the contract contents" refers to an interface that allows users to input their satisfaction and opinions regarding the contract contents into the system.

[1146] "Means for saving input evaluation data and performing statistical processing in real time" refers to technology that saves evaluation data from users and analyzes and processes it in real time.

[1147] "Means for disclosing aggregated evaluation data to other users" refers to technology that allows analyzed and processed evaluation data to be disclosed and shared with other users.

[1148] "Means of inputting the contents of a contract or terms and conditions as prompt sentences using a generative AI model" refers to a technology that uses natural language processing technology to formalize the contents of a contract or terms and conditions as prompt sentences.

[1149] "Means for performing detailed analysis of contract content using a generative AI model" refers to technology that uses a generative AI model to perform detailed analysis of contract content and provide the results.

[1150] This invention is a system designed to help users easily understand the contents of contracts and terms and conditions. It consists of three main elements: a server, a terminal, and a user. The system's purpose is to quickly identify changes and risks in contracts and terms and conditions and visually present them to users. It can also analyze contract contents using a generative AI model and provide detailed information.

[1151] Server Roles

[1152] The server periodically retrieves the latest version of the contract or terms and conditions from the Internet and stores it in a specific storage device. At this time, the server compares the previous version with the new version and identifies the changes as differences. The identified differences are analyzed using a risk assessment algorithm, and the risks are classified and assessed. This risk information is presented visually to the user.

[1153] The server also uses optical character recognition (OCR) technology to extract text data from contracts and clauses uploaded by users from their devices. The extracted text data is then analyzed in detail using a generative AI model. The analyzed risk information is then sent to the device.

[1154] Device Role

[1155] Users use their smartphone or computer to take a photo of the contract or terms and conditions or upload them as a file. The device then sends this data to the server, which acts as a trigger for OCR processing. The risk information and analysis results received from the server are displayed visually through the device's user interface. Users can easily understand the contract contents based on the visually presented risk information.

[1156] Users can also enter ratings for the contract details, and the rating data is sent to the server in real time. The server stores the rating data and performs statistical processing. This generates and publishes rating information that can be used as reference by other users.

[1157] User operations

[1158] When loading a contract or clause, the user can take a photo using the device's camera or upload an existing file. The device then sends this to the server, which receives risk assessment and analysis results and displays them in an easy-to-read format. The user can also enter their satisfaction with the contract content as an evaluation, and this feedback information is also saved on the server.

[1159] Hardware and software used

[1160] Hardware: smartphones, tablets, computers

[1161] software:

[1162] Google Firebase (backend service)

[1163] OCR library (e.g. Tesseract OCR)

[1164] TensorFlow Lite (Natural Language Processing using Generative AI Models)

[1165] React Native (Mobile Frontend)

[1166] Examples of concrete examples and prompts

[1167] For example, if a user is considering new terms of use for an online storage service, they can take a photo of the new terms of use with their smartphone and upload it. The server will then compare the latest terms with the previous terms to identify any changes. If the changes relate to the handling of personal information, the server will perform a detailed analysis of the risks involved and notify the user. The user can then use this information to consider using the service.

[1168] Example prompt sentence:

[1169] "The changes in the terms and conditions of the new online storage service relate to the handling of personal information, so please assess the risks involved."

[1170] This allows users to quickly understand changes and risks in contracts and terms and conditions, and to conduct appropriate risk assessments. A generative AI model is also used to perform detailed analysis of contract content, which is expected to promote user understanding and improve assessment accuracy.

[1171] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1172] Flow of the system program that realizes the application example

[1173] Step 1:

[1174] Users can photograph or upload contracts and terms and conditions

[1175] Users use their smartphones or computers to take a photo of the contract or terms and conditions or upload an existing file. This input data is in the form of an image or electronic file and is sent from the device to the server.

[1176] Step 2:

[1177] The server extracts the text data

[1178] The server receives uploaded images and files and extracts text data using OCR (Optical Character Recognition) technology. At this stage, the input is image or file format data, and the output is text data.

[1179] Step 3:

[1180] The server compares with the previous version

[1181] The server compares the extracted text data with past versions and performs a difference calculation to identify changes. The input is the current text data and the past text data, and the output is a list of changes.

[1182] Step 4:

[1183] Server analyzes identified differences

[1184] The server runs a risk assessment algorithm based on the identified differences, including a generative AI model. The input is a list of changes, and the output is a risk assessment result.

[1185] Step 5:

[1186] The server sends the risk assessment information to the user

[1187] The server sends the analyzed risk assessment information to the terminal. The input is the risk assessment result, and the output is data that can be displayed visually.

[1188] Step 6:

[1189] The device visually displays risk information

[1190] The terminal visually presents the risk assessment information received from the server to the user. In this step, the user interface displays the risk information in an easy-to-understand format. The input is the visualization data sent from the server, and the output is the display on the screen.

[1191] Step 7:

[1192] The user enters their evaluation of the contract contents

[1193] Users input their evaluation of the contract details through their device. The evaluation data is entered in the form of comments and scores and is sent from the device to the server.

[1194] Step 8:

[1195] The server stores and processes the evaluation data

[1196] The server stores the evaluation data received from users and performs statistical processing in real time. The input is the user evaluation data, and the output is the statistical processing result.

[1197] Step 9:

[1198] The server exposes the rating data to other users

[1199] The server displays the statistically processed evaluation data in a specific interface to make it public to other users. The input is the statistically processed evaluation data, and the output is public information.

[1200] Specific examples of actions and prompt format

[1201] For example, when a user reviews new terms of service for an online storage service, they might use the following prompt:

[1202] "The changes in the terms and conditions of the new online storage service relate to the handling of personal information, so please assess the risks involved."

[1203] By inputting this prompt into the generative AI model, users can quickly receive a specific risk assessment, significantly reducing the burden on users and making it easier for them to evaluate and understand the contract contents.

[1204] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1205] The present invention is a system that presents changes to contracts and terms and conditions to users, evaluates and notifies them of the risks involved, and dynamically adjusts the interface based on user emotions. Specifically, the system is implemented as follows:

[1206] Overall system configuration

[1207] This system consists of a server, a terminal, a user, and an emotion engine. The server is responsible for data management and analysis of contracts and terms and conditions, and emotional data processing, while the terminal provides the user interface. The emotion engine recognizes user emotions in real time and optimizes system operation based on them.

[1208] Understanding changes to contracts and terms and conditions and clarifying risks

[1209] The server periodically retrieves the latest version of the contract or clause from the website. The retrieved data is compared with previous versions to identify any changes. The server analyzes these changes and uses a risk assessment algorithm to classify and assess the risks. The classified and assessed risk information is stored in a database for visual presentation to the user.

[1210] When a user accesses a risk information page, the device displays the changes and their associated risks in a visually easy-to-understand format, including color coding. If the user expresses an emotional reaction to a particular section, the device's emotion engine analyzes the data and dynamically adjusts the display. For example, if the user is extremely anxious, the device will provide more detailed information and advice on that section.

[1211] Evaluation and disclosure of contract details

[1212] Users input their ratings of the contract details through their terminals. The entered rating data is sent to the server and stored in a database. The server then statistically processes the rating data in real time and makes the results available to other users.

[1213] The emotion engine recognizes the emotion a user is feeling when entering a rating and incorporates that emotion data into the rating process. For example, if a user has very positive emotions, their rating may be weighted higher.

[1214] Individual contract risk assessment

[1215] Users scan or upload individual contracts as electronic files. The device receives the documents and sends them to the server. The server uses OCR technology to extract text from the contract and analyzes it with a risk assessment algorithm. The results are then reported to the user, and the necessary risk information is displayed on the device.

[1216] The emotion engine recognizes the emotions users express while viewing risk information and adjusts how the risk is presented based on that emotion. For example, if a user expresses surprise or disappointment, additional explanations or solutions will be provided for that risk.

[1217] Drafting and providing contract amendment proposals

[1218] If the user wishes to change the contract terms, they enter the changes. The device sends the changes to the server, which then uses an automated contract generation library to generate a new contract draft. The draft is then reviewed and provided to the user.

[1219] The emotion engine also takes into account the user's emotions when drafting contract changes, helping to reduce stress. For example, if the user is feeling impatient, it will provide operational guidance and real-time support.

[1220] Specific examples

[1221] For example, if a user is considering new terms of use for an online storage service, the server retrieves the latest terms and compares them with previous terms to identify any changes. If the changes relate to the handling of personal information, the server performs a detailed analysis of the risks and notifies the user. If the information makes the user feel uneasy, the emotion engine recognizes this emotion and provides more detailed information or additional advice.

[1222] For example, if a user uploads a contract for constructing a new building, the server analyzes the contract and notifies the user about specific risks (e.g., construction delays, additional costs). If the user expresses surprise or concern, the emotion engine will detect this and provide more detailed countermeasures for the risk.

[1223] As described above, the present invention makes it easier to understand the contents of contracts and terms and conditions while taking into account the user's emotions, helps to identify potential risks, and provides a method for efficiently changing the contents of contracts.

[1224] The processing flow will be explained below.

[1225] Understanding changes to contracts and terms and conditions and clarifying risks

[1226] Step 1:

[1227] The server periodically crawls the specified list of websites to retrieve the latest version of the contract or terms and conditions, and stores the retrieved data in storage.

[1228] Step 2:

[1229] The server uses a difference detection library (e.g., diff-match-patch) to compare the latest version of the contract or clause with the previous version and identify the changes.

[1230] Step 3:

[1231] The server then analyzes the identified changes with a risk assessment algorithm to classify and assess the risk. For example, if there is a change related to the handling of personal information, it will classify it as a high risk.

[1232] Step 4:

[1233] The server stores the analysis results in a database and prepares it so that risk information can be visually presented when accessed by a user.

[1234] Step 5:

[1235] When a user accesses the risk information page, the device displays the changes and risks in a visually easy-to-understand format, such as color-coding.

[1236] Evaluation and disclosure of contract details

[1237] Step 1:

[1238] The user uses an input form on the terminal to input an evaluation score and comments on the contract contents.

[1239] Step 2:

[1240] The terminal transmits the evaluation score and comments entered by the user to the server.

[1241] Step 3:

[1242] The server stores the received evaluation data in a database and performs real-time statistical processing, such as calculating the average evaluation score and frequently occurring comments.

[1243] Step 4:

[1244] The server visualizes the results and updates the evaluation page so that other users can see them.

[1245] Step 5:

[1246] When other users access the rating page, the terminal displays the aggregated rating scores and comments.

[1247] Individual contract risk assessment

[1248] Step 1:

[1249] The user uses the upload function on the device to upload the contract in scanned or PDF format.

[1250] Step 2:

[1251] The terminal transmits the uploaded contract to the server.

[1252] Step 3:

[1253] The server uses OCR (Optical Character Recognition) software to extract text data from the contract.

[1254] Step 4:

[1255] The server then analyzes the extracted text data using a risk assessment algorithm to identify risks, such as risks related to payment terms or construction extensions.

[1256] Step 5:

[1257] The server stores the evaluation results in a database and makes them available for user review.

[1258] Step 6:

[1259] The device provides the user with the risk assessment results in an easily identifiable manner, highlighting areas of concern or specific risk areas.

[1260] Drafting and providing contract amendment proposals

[1261] Step 1:

[1262] The user uses an input form on the terminal to input requests for changes to the contract contents, such as shortening the contract period or changing the payment terms.

[1263] Step 2:

[1264] The terminal transmits the input desired changes to the server.

[1265] Step 3:

[1266] The server uses an automated contract generation library to generate a new draft contract based on the inputs.

[1267] Step 4:

[1268] The server checks the generated draft contract using an internal review system and makes corrections as necessary.

[1269] Step 5:

[1270] The server stores the revised draft contract in a database so that it can be provided to the user.

[1271] Step 6:

[1272] The terminal displays the new draft contract to the user and makes it available for download if desired.

[1273] Operation using emotion engine (processing based on additional claims)

[1274] Step 1:

[1275] The emotion engine analyzes facial expressions and voice data in real time while the user is viewing a contract or terms and conditions.

[1276] Step 2:

[1277] The server receives the emotion data sent from the emotion engine and identifies the user's emotional state based on the analysis results. For example, if the user shows surprise or anxiety, the emotion data is reflected in the risk assessment.

[1278] Step 3:

[1279] The device dynamically changes how it presents risk information depending on the user's emotional state: if the user feels anxious, it displays additional details or advice.

[1280] Step 4:

[1281] The server stores the emotion data in a database and uses it as reference information for future interactions.

[1282] Step 5:

[1283] The emotion engine weights contract and risk assessment results based on the user's emotional data, providing more personalized results.

[1284] Step 6:

[1285] The user can use the terminal to make decisions or make changes to the contract contents based on feedback and advice from the emotion engine.

[1286] In this way, by explaining each processing step in detail, the specific operation of the system and its linkage with the emotion engine become clear.

[1287] Example 2

[1288] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1289] The contents of contracts and terms and conditions change frequently, making it difficult to quickly and accurately grasp these changes. Furthermore, risk assessment and information presentation that takes user emotions into consideration are not adequately implemented, making it difficult for users to accurately understand risks and respond appropriately. Conventional systems do not dynamically adjust the display method based on the user's emotional state, which can result in a poor user experience. Furthermore, when users input their evaluation of specific contract content, there is also the issue of the evaluation not being properly fed back based on their emotions.

[1290] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for periodically acquiring the latest version of the contract or terms and conditions, a means for comparing the acquired contract or terms and conditions with previous versions to identify differences, a means for analyzing the identified differences and classifying and assessing risks, a means for visually presenting the classified and assessed risks to the user, and a means for recognizing the user's emotions in real time and dynamically adjusting the display method based on the recognition results. This allows the user to quickly and accurately grasp changes to the contract or terms and understand the risks. Furthermore, the dynamic presentation of information according to the user's emotions improves the user experience. Furthermore, more appropriate feedback can be provided by incorporating the user's emotional evaluation into statistical processing.

[1291] "Means for periodically obtaining the latest version of the contract or terms and conditions" refers to a system that automatically obtains the latest version of the contract or terms and conditions from a website or database at regular intervals.

[1292] "Means for comparing the acquired contract or terms and conditions with previous versions to identify differences" refers to algorithms or processes for comparing the content of the latest contract or terms and conditions with previous versions and identifying any changes.

[1293] The "means of analyzing identified differences and classifying and assessing risks" is a mechanism for analyzing the changed parts in detail, extracting each risk element, and classifying and assessing them.

[1294] "Means for visually presenting classified and assessed risks to users" refers to an interface that displays assessment results in a format that is easy for users to understand, and a mechanism that provides visual feedback.

[1295] "Means for recognizing a user's emotions in real time and dynamically adjusting the display method based on the recognition results" refers to a technology that monitors a user's emotional state in real time through sensor devices such as cameras and microphones, and automatically changes the content and method of display according to the obtained emotional data.

[1296] The "means for users to input evaluations of the contract contents" is an interface that allows users to input evaluations and comments on the contract and terms and conditions.

[1297] The "means for saving the input evaluation data and performing statistical processing in real time" refers to a system for saving user evaluations in a database and instantly analyzing and statistically processing the data.

[1298] The "means for disclosing aggregated evaluation data to other users" is an interface that provides the analyzed and statistically processed evaluation results in a form that can be accessed by other users.

[1299] "Means for incorporating user emotional evaluations into statistical processing" refers to a process for analyzing user emotional data together with evaluation data to provide statistical feedback and improvements.

[1300] "Means for scanning or uploading individual contract contents" means a method by which a user can convert a physical contract into digital form or submit an existing electronic file to the system.

[1301] "Means for extracting the text of an uploaded contract" refers to technology for extracting text information from the digital data of a scanned or uploaded contract, including OCR (optical character recognition) technology.

[1302] The "means for analyzing extracted text data and assessing risks" refers to a process of analyzing the contract contents in detail based on the extracted text information, and identifying and assessing potential risks.

[1303] "Means for providing assessed risk information to a user" means an interface for providing analyzed and assessed risk information to a user in a visual or notification format.

[1304] "Means for recognizing the user's emotions and adjusting the way risk information is presented based on the results of that recognition" refers to a mechanism that analyzes the user's emotional data in real time and changes the way risk information is presented based on the results.

[1305] This invention is a system that presents changes to contracts and terms and conditions to users, evaluates and notifies them of the risks involved, and dynamically adjusts the interface based on user emotions. The detailed configuration of the system and specific implementation methods are described below.

[1306] System configuration

[1307] This system consists of a server, a terminal, a user, and an emotion engine. The server is responsible for data management and analysis of contracts and terms and conditions, and emotional data processing, while the terminal provides the user interface. The emotion engine recognizes user emotions in real time and optimizes system operation based on them.

[1308] Hardware and software used

[1309] Server: Performs data analysis and management. Software used includes TensorFlow and PyTorch, the Tesseract OCR engine as OCR technology, and MySQL and PostgreSQL for database management.

[1310] Terminal: Provides the user interface. Dynamically generates pages using HTML / CSS and JavaScript using a web browser.

[1311] Emotion Engine: Recognizes user emotions using Microsoft Azure Cognitive Services and OpenCV.

[1312] System Operation

[1313] Understanding changes to contracts and terms and conditions and clarifying risks

[1314] The server periodically scrapes the website to retrieve the latest version of the contract and terms and conditions, using Python's BeautifulSoup and Scrapy.

[1315] The server compares the retrieved data with previous versions and uses a Diff check algorithm to identify changes.

[1316] The server analyzes the changes and classifies and assesses the risks using a risk assessment algorithm (using TensorFlow and PyTorch).

[1317] The server stores the classified and evaluated risk information in a database (MySQL or PostgreSQL) and provides it to the terminal.

[1318] User Interface

[1319] When a user accesses a risk information page, the device visually displays the changes and the associated risks, using color coding and icons for visual feedback.

[1320] The emotion engine captures user emotional data via the camera and microphone, analyzes it using Microsoft Azure Cognitive Services and OpenCV, and if the user feels anxious or surprised, it will change the way it is displayed and provide additional information or advice.

[1321] Evaluation and disclosure of contract details

[1322] The user inputs their evaluation of the contract contents through the terminal and sends it to the server.

[1323] The server processes the evaluation data in real time and publishes the results to other users using NumPy and Pandas.

[1324] The emotion engine recognizes how users feel when they are entering their ratings and incorporates that emotional data into the rating process.

[1325] Individual contract risk assessment

[1326] Users upload individual contracts as scanned or electronic files.

[1327] The device receives this and sends it to a server, which uses OCR technology (such as Tesseract OCR) to extract the text and analyzes it with a risk assessment algorithm.

[1328] The server notifies the terminal of the evaluation results and displays the necessary risk information.

[1329] The emotion engine recognizes the emotions users feel when reviewing risk information and adjusts how risks are presented based on that information.

[1330] Drafting and providing contract amendment proposals

[1331] If the user wishes to change the contract, they enter the changes into their device and send them to the server, which then uses an automated contract generation library (such as the Docxtpl library) to generate a new contract draft and provides it to the user after review.

[1332] The emotion engine takes user emotions into consideration when creating contract change proposals, supporting stress-free operation.

[1333] Examples and prompts

[1334] Example 1: Changes to the terms of use of an online storage service

[1335] The server retrieves the latest terms of use and compares them with the previous terms.

[1336] If there are any changes regarding the handling of personal information, the risks will be analyzed in detail and notified to the device.

[1337] The emotion engine recognizes the user's concerns and provides detailed explanations and additional advice.

[1338] Prompt Sentence Examples

[1339] I am reviewing the new terms of service for an online storage service. Please obtain the latest version and identify the differences from the previous version. Please analyze in detail the changes, especially those related to personal information, and assess the risks involved. Please explain how the sentiment engine works and provides additional advice if the user feels uneasy.

[1340] Example 2: Contract for the construction of a new building

[1341] Users upload construction contracts.

[1342] The server extracts the text using OCR and performs a risk assessment.

[1343] The terminal will notify you of risks such as construction delays and additional costs.

[1344] The emotion engine detects users' surprise or concern and provides detailed solutions.

[1345] Prompt Sentence Examples

[1346] I uploaded a contract for constructing a new building. I want you to use OCR technology to extract the text from the contract and perform a risk assessment. I want you to notify the user of risks such as delays and additional costs, and explain how the emotion engine will react if the user is surprised or worried.

[1347] The above is a specific embodiment of the present invention.

[1348] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1349] Step 1:

[1350] The server periodically retrieves the latest version of the contract or terms and conditions from the website. Python's BeautifulSoup and Scrapy are used to scrape the webpage and extract the contract or terms and conditions links from the HTML tags. This allows the server to retrieve the latest version of the contract or terms and conditions data. The input is the URL of a specific website, and the output is the latest contract or terms and conditions data.

[1351] Step 2:

[1352] The server compares the retrieved contract or clause data with past versions to identify changes. Specifically, it uses a Diff check algorithm to compare the lines of each text data. When changes are identified, that information is output as a difference list. The input is the latest version of the text and the past version of the text, and the output is a list of changes.

[1353] Step 3:

[1354] The server analyzes the identified changes and classifies and evaluates the risk using a risk assessment algorithm. It uses machine learning frameworks such as TensorFlow and PyTorch to score the risk of each change. The input is a list of changes, and the output is classified and evaluated risk information.

[1355] Step 4:

[1356] The server stores the classified and evaluated risk information in a database. The database used is MySQL, PostgreSQL, etc., and writes the risk information to the database in an appropriate format. The input is the classified and evaluated risk information, and the output is the risk information stored in the database.

[1357] Step 5:

[1358] When a user accesses a risk information page, the terminal visually displays the changes and risks. Using HTML / CSS and JavaScript, the changed parts are displayed with color coding and icons, allowing the user to understand the risks at a glance. The input is risk information retrieved from the database, and the output is the visually displayed risk information.

[1359] Step 6:

[1360] The emotion engine uses the user's camera and microphone to capture emotional data in real time and analyzes it using Microsoft Azure Cognitive Services and OpenCV. It dynamically adjusts how risk information is displayed based on the user's emotional state. For example, if the user feels anxious, it will pop up additional details and advice. The input is the user's video and audio, and the output is the dynamically adjusted display method.

[1361] Step 7:

[1362] Users input their evaluation of the contract contents through their terminals and send the data to the server. Evaluation data is collected by filling out the evaluation form and clicking the submit button. The input is the user's evaluation data, and the output is the evaluation data sent to the server.

[1363] Step 8:

[1364] The server stores the evaluation data sent by users in a database and performs statistical processing in real time using NumPy and Pandas. The aggregated results are reflected on a web page and made publicly accessible to other users. The input is the user's evaluation data, and the output is the aggregated evaluation data.

[1365] Step 9:

[1366] The user scans or uploads individual contracts in electronic file format and sends them to the server via the terminal. The terminal provides an upload button and sends the selected file to the server. The input is the contract in electronic file format, and the output is the contract data sent to the server.

[1367] Step 10:

[1368] The server uses the Tesseract OCR engine to extract the text of the uploaded contract and parses it with a risk assessment algorithm. The input is the image data of the contract, and the output is the extracted text data and assessed risk information.

[1369] Step 11:

[1370] The server notifies the terminal of the evaluation results and provides risk information to the user. The necessary risk information is visually displayed on the terminal. The input is the evaluated risk information, and the output is the visually displayed risk information.

[1371] Step 12:

[1372] The emotion engine recognizes the user's emotions when reviewing risk information and adjusts the presentation of risk information based on that information. If the user expresses surprise or disappointment, it displays additional explanations and suggested solutions. The input is the user's emotional data, and the output is the adjusted presentation of risk information.

[1373] Step 13:

[1374] If a user wishes to change the contents of the contract, they enter the changes via their terminal and send them to the server. They enter the changes in the input form and click the send button. The input is the changes the user wishes to make, and the output is the changes sent to the server.

[1375] Step 14:

[1376] The server generates a new draft contract using an automated contract generation library (such as the Docxtpl library). The input is the user's desired changes, and the output is the generated draft contract.

[1377] Step 15:

[1378] The server provides the generated contract draft to the user after review, and the emotion engine takes the user's emotions into consideration to support stress-free operation. The input is the generated contract draft and the user's emotion data, and the output is the provided contract draft and adjusted operation method.

[1379] (Application example 2)

[1380] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1381] It is important to visually present changes to contracts and terms and conditions to users and effectively evaluate and classify the risks, making it easier for users to understand the content of the contract. However, presenting risks without taking into account the anxiety and confusion that accompanies users' emotions can lead to different perceptions of information and delays in appropriate responses. Furthermore, when users evaluate contract content or upload individual contracts to check risks, a poor user experience can result if the interface is not dynamically adjusted based on the user's emotions.

[1382] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for periodically acquiring the latest version of the contract or terms of use, means for comparing the acquired contract or terms of use with previous versions to identify differences, means for analyzing the identified differences and classifying and assessing risks, means for visually presenting the classified and assessed risks to the user, means for recognizing the user's emotions in real time, and means for dynamically adjusting the interface based on the recognized emotions. This not only makes it easier for the user to understand risks when reviewing the contract or its contents, but also makes it possible to provide optimal information according to the user's emotions.

[1383] "Means for periodically obtaining the latest version of the agreement or terms of use" refers to a function that automatically obtains the latest version of the agreement or terms of use online or from a database on a regular basis.

[1384] "Means for comparing the acquired contract or terms of use with a previous version to identify differences" refers to an analysis function for comparing the latest acquired contract or terms of use with a previous version and identifying differences in changes or additions.

[1385] "Means for analyzing identified differences and classifying and assessing risks" refers to a function for identifying and classifying risks and assessing their importance and impact by analyzing identified differences.

[1386] "Means for visually presenting classified and assessed risks to users" refers to a function that graphically displays assessed risk information to users and provides information in a visually easy-to-understand format.

[1387] "Means of recognizing the user's emotions in real time" refers to an analytical function that analyzes the user's voice, facial expressions, behavior, etc., and recognizes the emotions the user is feeling in real time.

[1388] "Means for dynamically adjusting the interface based on recognized emotions" refers to a function that dynamically changes and optimizes the content and manner of display of the user interface in response to the recognized emotions of the user.

[1389] "Means for users to input evaluations of the contract contents" refers to an interface that allows users to input their own evaluations and opinions of the contract contents they are using.

[1390] "Means for adjusting the evaluation process based on emotion recognition data" refers to a function that adjusts the evaluation process and the way evaluation results are displayed by referring to the user's emotion data.

[1391] "Means for scanning or uploading the contents of individual contracts" refers to the function of scanning individual contracts from paper and converting them into digital data, or uploading them directly in electronic file format.

[1392] "Means for extracting text from uploaded contracts" refers to a function that extracts text data from uploaded contracts and converts it into an analyzable format.

[1393] "Means for recognizing emotions when checking risk information and adjusting the way in which risk is presented" refers to a function that recognizes the emotions of users when checking risk information and adjusts the way in which risk information is presented and its content based on those emotions.

[1394] This system presents changes to contracts and terms and conditions to users, evaluates and notifies them of the risks involved, and dynamically adjusts the interface by recognizing the user's emotions. This system consists of a server, terminals, users, and an emotion engine.

[1395] Overall system configuration

[1396] The server is responsible for data management, analysis, and emotional data processing of contracts and terms and conditions. The server periodically retrieves the latest version of the contract or terms and conditions from the website and compares it with previous versions to identify any discrepancies. The retrieved data is analyzed using a risk assessment algorithm to classify and assess risks. This assessment information is stored in a database.

[1397] The device provides a user interface using a smartphone. When a user accesses a risk information page, the device displays the changes and their associated risks in a visually easy-to-understand format. It also includes an emotion engine that analyzes the user's voice, facial expressions, and behavior to recognize emotions in real time, dynamically adjusting the interface based on the emotional data. For example, if the user is feeling anxious, the device will provide more detailed information and advice on that point.

[1398] Understanding changes to contracts and terms and conditions and clarifying risks

[1399] The server compares the latest version of the contract or clause with the previous version to identify any changes. The identified differences are analyzed by a risk assessment algorithm to classify and evaluate the risks. The classified and evaluated risk information is stored in a database for visual presentation.

[1400] User emotion recognition and interface adjustment

[1401] The device is equipped with an emotion engine that recognizes the user's emotions as they review risk information. The emotion engine analyzes the user's voice, facial expressions, and behavior to recognize emotions in real time. Based on the emotion data, the user interface is dynamically adjusted according to the recognized emotion. For example, if the user feels anxious, additional details and advice are added. This allows the user to understand the contract details and make a decision with confidence.

[1402] User ratings and sentiment data

[1403] The terminal provides an interface for users to input their ratings of the contract contents. The user's rating input is sent to the server in real time and stored in a database. The server performs statistical processing of the rating data in real time and makes the results available to other users. An emotion engine also recognizes the user's emotions, and the emotion data is reflected in the rating process. For example, the ratings of users who show very positive emotions may be weighted.

[1404] Individual contract risk assessment

[1405] Users scan or upload individual contracts as electronic files. The device receives the documents and sends them to the server. The server uses OCR technology to extract text from the contract and analyzes it with a risk assessment algorithm. The results are then reported to the user, and the necessary risk information is displayed on the device.

[1406] Specific examples

[1407] For example, if a user is considering new terms of use for an online storage service, the server retrieves the latest terms and compares them with previous terms to identify any changes. If the changes relate to the handling of personal information, the server performs a detailed analysis of the risks and notifies the user. If the information makes the user feel uneasy, the emotion engine recognizes this emotion and provides more detailed information and additional advice. Similarly, if a user uploads a contract for the construction of a new building, the server analyzes the contract and notifies the user of specific risks (e.g., construction delays, additional costs). If the user is surprised or worried, the emotion engine detects this and provides more detailed countermeasures for the risk.

[1408] Example prompts for generative AI models

[1409] "How can we assess the risk regarding the latest security terms of service changes, recognize user sentiment and provide more information?"

[1410] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1411] Step 1:

[1412] The server periodically retrieves the latest version of the contract or terms of use from an online or database. Specifically, it retrieves data via a specific URL or API and stores it in a local database. The input is the URL or API information to be retrieved, and the output is the retrieved latest version of the contract or terms of use data.

[1413] Step 2:

[1414] The server compares the latest version of the contract or terms of use with previous versions to identify differences. This process uses a difference analysis library such as difflib to detect differences in text. The input is the latest and previous versions of the contract data, and the output is the identified differences.

[1415] Step 3:

[1416] The server analyzes the identified differences and classifies and assesses the risk using a risk assessment algorithm. In this process, risks are classified as high, medium, low, etc. based on specific keywords or phrases. The inputs are the difference information and the risk assessment algorithm, and the output is the classified and assessed risk data.

[1417] Step 4:

[1418] When a user accesses the risk information page, the terminal visually displays the risk data obtained from the server. Specifically, the degree of risk is clearly expressed using color coding and icons. The input is risk data, and the output is risk information displayed on the user interface.

[1419] Step 5:

[1420] The device runs an emotion engine that analyzes the user's voice, facial expressions, and behavior to recognize emotions in real time. The emotion engine analyzes the collected data and determines the user's emotional state (e.g., anxiety, relief, surprise). The input is the user's voice, facial expressions, and behavior data, and the output is the recognized emotion data.

[1421] Step 6:

[1422] The device dynamically adjusts the user interface based on the recognized emotion, for example, displaying a more information box or additional advice if the user is feeling anxious. The input is emotion data and user interface data, and the output is an adjusted user interface.

[1423] Step 7:

[1424] When a user inputs an evaluation of the contract contents, the terminal sends the evaluation data to the server. In addition, emotional data recognized by the emotion engine is also sent. The input is the user's evaluation and emotional data, and the output is the evaluation data sent to the server.

[1425] Step 8:

[1426] The server processes the submitted evaluation data in real time and publishes the results to other users. In this process, the evaluation data is aggregated and statistical information about specific items is generated. The input is the evaluation data, and the output is the statistically processed evaluation results.

[1427] Step 9:

[1428] When a user scans or uploads an individual contract, the device sends the contract to the server, which uses OCR technology to extract text from the contract and analyzes it with a risk assessment algorithm. The input is the uploaded contract data, and the output is the analyzed risk information.

[1429] Step 10:

[1430] When providing risk information to the user, the device monitors the user's emotions in real time and adjusts the risk presentation method. Based on the recognized emotion data, it provides additional explanations and countermeasures. The input is the user's emotion data and risk information, and the output is the adjusted risk presentation method.

[1431] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1432] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1433] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1434] [Fourth embodiment]

[1435] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1436] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1437] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1438] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1439] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1440] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1441] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1442] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1443] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1444] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1445] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1446] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1447] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1448] The present invention is a system designed to enable users to easily understand the contents of contracts and terms and conditions, and is realized using the following means.

[1449] Overall system configuration

[1450] This system consists of three main components: a server, a terminal, and a user. The server manages and analyzes data on contracts and clauses, while the terminal provides the user interface. Users use the terminal to evaluate, upload, and input proposed changes to contracts and clauses.

[1451] Understanding changes to contracts and terms and conditions and clarifying risks

[1452] The server periodically retrieves the latest versions of contracts and terms and conditions published on specific websites from the Internet. The server stores this data in storage and compares it with previous versions. Changes are identified as differences as a result of the comparison, and are classified and analyzed using a risk assessment algorithm. The analyzed risk information is visually presented to the user. For example, if a provision regarding data sharing is added to the new terms of use of a social media platform, that information is highlighted.

[1453] Evaluation and disclosure of contract details

[1454] Users use their devices to input their evaluations of contract details. For example, they can input an evaluation score indicating whether they were satisfied or dissatisfied with a contract with a certain internet service provider. The device sends this evaluation to a server, which stores the evaluation data in a database. The server statistically processes the evaluations of all users, generates information such as average scores and frequently occurring comments, and makes this information public to other users. Other users can use this public information as a reference when considering the contract details.

[1455] Individual contract risk assessment

[1456] Users use their devices to scan or upload individual contracts, such as land sales or building construction contracts, as electronic files. The devices then send the uploaded contracts to a server. The server then uses OCR technology to extract text data from the contracts, analyzes the text data, and performs a risk assessment. The assessment results identify specific risks in the contract (such as construction delays or additional costs) and provide them to the user.

[1457] Drafting and providing contract amendment proposals

[1458] If a user wishes to change the contract details, they use their device to input the specific details. For example, if they wish to shorten the contract period for building construction work, they can input this information. The device then sends this information to the server, which then automatically generates a new contract based on the proposed changes. The generated contract draft is then provided to the user for final confirmation and download.

[1459] Specific examples

[1460] For example, if a user is considering new terms of use for an online storage service, the server retrieves the latest terms of use, compares them with previous terms, and identifies any changes. If the changes relate to the handling of personal information, the server analyzes the risks in detail and notifies the user. The user can then use this information to consider using the service.

[1461] In addition, if a user uploads a contract for the construction of a new building, the server analyzes the contract and notifies the user of specific risks (e.g., construction delays, additional costs), allowing the user to review the contract and, if necessary, input proposed changes and generate a new contract.

[1462] In this way, the present invention makes it easier for users to understand the contents of contracts and terms and conditions, helps them understand potential risks, and provides a method for efficiently making changes to the contract contents.

[1463] The processing flow will be explained below.

[1464] Understanding changes to contracts and terms and conditions and clarifying risks

[1465] Step 1:

[1466] The server crawls the specified website URL list to retrieve the latest version of the contract or terms and conditions, and stores the retrieved data in storage.

[1467] Step 2:

[1468] The server uses a difference detection library (e.g., diff-match-patch) to compare the latest version of the contract or clause with the previous version and identify the changes.

[1469] Step 3:

[1470] The server analyzes the identified changes and classifies and assesses the risk using a risk assessment algorithm. For example, if a change related to the handling of personal information is detected, the server classifies the risk as high.

[1471] Step 4:

[1472] The server stores the analysis results in a database and prepares a visual display of the risks when accessed by the user.

[1473] Step 5:

[1474] When a user accesses the risk information page, the device visually displays the changes and the risks involved using color coding, etc.

[1475] Evaluation and disclosure of contract details

[1476] Step 1:

[1477] The user uses an input form on the terminal to input an evaluation score and comments on the contract contents.

[1478] Step 2:

[1479] The terminal transmits the evaluation score and comments entered by the user to the server.

[1480] Step 3:

[1481] The server stores the received evaluation data in a database and performs real-time statistical processing, such as calculating the average evaluation score and frequently occurring comments.

[1482] Step 4:

[1483] The server visualizes the results and updates the evaluation page so that other users can see them.

[1484] Step 5:

[1485] When other users access the rating page, the terminal displays the aggregated rating scores and comments.

[1486] Individual contract risk assessment

[1487] Step 1:

[1488] The user uses the upload function on the device to scan the contract or upload it in PDF format.

[1489] Step 2:

[1490] The terminal transmits the uploaded contract to the server.

[1491] Step 3:

[1492] The server uses OCR (Optical Character Recognition) software to extract text data from the contract.

[1493] Step 4:

[1494] The server analyzes the extracted text data and identifies risks using a risk assessment algorithm.

[1495] Step 5:

[1496] The server organizes the risk information and stores it in a database in order to provide the evaluation results to the user.

[1497] Step 6:

[1498] The terminal visually presents the risk assessment results to the user, for example by highlighting specific risk areas.

[1499] Drafting and providing contract amendment proposals

[1500] Step 1:

[1501] The user uses the input form on the terminal to input the changes he or she wishes to make to the contract contents.

[1502] Step 2:

[1503] The terminal transmits the input desired changes to the server.

[1504] Step 3:

[1505] The server uses an automated contract generation library to generate a new draft contract based on the user's input.

[1506] Step 4:

[1507] The server checks the generated draft contract using an internal review system and makes corrections as necessary.

[1508] Step 5:

[1509] The server stores the revised draft contract in a database in order to provide it to the user.

[1510] Step 6:

[1511] The terminal will visually display the new draft contract to the user and make it available for download if desired.

[1512] In this way, by explaining each processing step separately, it becomes easier to understand the specific operation of the system.

[1513] Example 1

[1514] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1515] The contents of contracts and terms and conditions are complex and contain many technical terms, making them difficult for general users to understand. Furthermore, tracking changes to contracts and terms and assessing risks is time-consuming and requires specialized knowledge. In addition, there are limited ways for users to share their assessments of contract contents with other users. This makes it difficult for users to understand contract contents, grasp risks, and make decisions based on the assessments of other users.

[1516] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1517] In this invention, the server includes means for periodically obtaining the latest version of the contract or terms and conditions, means for comparing the obtained contract or terms and conditions with past versions to identify differences, means for analyzing the identified differences and classifying and assessing risks, means for visually presenting the classified and assessed risks to the user, means for extracting text data from the contract using machine reading comprehension technology, means for the user to input changes to the contract, and means for automatically generating a new draft contract based on the input changes. This allows the user to easily understand changes and risks in the contract or terms and conditions, efficiently create a contract that reflects their own opinions, and also enables them to refer to evaluation information from other users.

[1518] A "contract" is a document that sets out the rights and obligations between the parties under a particular contract.

[1519] "Terms and conditions" are documents that set out the standard terms and conditions offered by a company or organization.

[1520] "Latest version" means the most recent version of the agreement or terms and conditions.

[1521] "Means of collection" refers to methods and technologies for automatically collecting data.

[1522] "Means for comparing and identifying differences" refers to methods and techniques for comparing different versions of contracts or terms and conditions and identifying changes.

[1523] "Means for classifying and assessing risks" refers to methods and techniques for analyzing changes to contracts and clauses to identify, classify, and assess potential risks.

[1524] "Visual presentation means" refers to methods and technologies that visually display analysis results to users in an easy-to-understand manner.

[1525] "Machine reading comprehension technology" refers to technology for automatically reading and understanding text data.

[1526] "Means for extracting text data" refers to methods or techniques for extracting text information from scanned images or uploaded files.

[1527] "Means for users to input changes to the contract" refers to the methods and technologies that allow users to input their desired changes to the contract into the system.

[1528] "Means for automatically generating a new draft contract" refers to methods or technologies that automatically create a new contract based on changes entered by the user.

[1529] The present invention is a system designed to enable users to easily understand the contents of contracts and terms and conditions, and is composed of three main elements: a server, a terminal, and a user.

[1530] Server Roles

[1531] The server manages and analyzes data on contracts and clauses. Specifically, the server periodically retrieves the latest versions of contracts and clauses published on specific websites from the Internet and stores the retrieved data in storage. An AWS S3 bucket is used to store the contract data, and the program performs web scraping using Python and the Beautiful Soup library. The server also compares the old and new contracts to identify differences and calculates text differences using the diff-match-patch library. The NLTK library is then used to classify and evaluate the risk of the changes using a risk assessment algorithm. The evaluated risk information is visually presented to the user. The front end uses React to highlight the results.

[1532] Device Role

[1533] The terminal provides a user interface, allowing users to evaluate, upload, and input proposed changes to the contract contents. For example, when a user scans or uploads an individual contract as an electronic file, the terminal sends this data to the server. The server uses OCR technology (Tesseract OCR) to extract text data from the contract and analyzes the text data to evaluate risk. If the user wishes to make changes to the contract contents, they can use the terminal to enter the specific details, which are then sent to the server. The server then automatically generates a new contract based on the proposed changes. The document is generated using a specific template, and can be downloaded after final confirmation.

[1534] User Roles

[1535] Users operate the system to evaluate their own contracts and input proposals for changes to the contract and terms. For example, they can use an evaluation form to input their level of satisfaction with a contract with an internet service provider. The evaluation results are sent to a server, where they are statistically processed in real time and made available to other users.

[1536] Specific examples

[1537] For example, if a user is considering new terms of use for an online storage service, the server retrieves the latest terms of use, compares them with previous terms, and identifies any changes. If the changes relate to the handling of personal information, the server analyzes the risks in detail and notifies the user. The user can then use this information to consider using the service.

[1538] In addition, when a user uploads a contract for constructing a new building, the server analyzes the contract, identifies risks (e.g., construction delays, additional costs) and notifies the user, who can then review the contract and, if necessary, input proposed changes to generate a new contract.

[1539] Prompt Sentence Examples

[1540] An example of a prompt to be input to a generative AI model is, "I would like to develop a system that analyzes contract contents, identifies risks, and presents them visually. This system retrieves the latest versions of contracts and terms and conditions from the Internet and compares them with previous versions. It uses a risk assessment algorithm to classify and analyze risks by category and notify the user of the results."

[1541] In this way, the present invention makes it easier for users to understand the contents of contracts and terms and conditions, helps them understand potential risks, and provides a method for efficiently making changes to the contract contents.

[1542] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1543] Step 1:

[1544] The server periodically retrieves the latest version of the contract or terms and conditions from a specific website on the Internet. Specifically, it uses Python's Beautiful Soup library to retrieve HTML content from a specified URL and extracts links to the new contract or terms and conditions. The retrieved data is saved in text format.

[1545] Enter: Website URL

[1546] Output: Text data of the latest contracts and terms and conditions

[1547] Step 2:

[1548] The server stores the acquired contract and clause data in cloud storage such as an AWS S3 bucket, which is used for later comparison and analysis.

[1549] Input: Text data of the latest contracts and terms and conditions

[1550] Output: File saved in cloud storage

[1551] Step 3:

[1552] The server compares the old and new contracts and clauses and identifies the changes as differences. This is achieved by calculating the text differences using the diff-match-patch library. This difference data becomes the basis for change analysis.

[1553] Input: Text data of past and latest contracts and terms and conditions

[1554] Output: Diff data of changes

[1555] Step 4:

[1556] The server analyzes the delta data and uses a risk assessment algorithm to classify and assess the risk. It uses the NLTK library to perform text analysis to identify the risks of the changes. This risk information is then categorized.

[1557] Input: Difference data of changes

[1558] Output: Assessed risk information

[1559] Step 5:

[1560] The server visually presents the assessed risk information to the user, and a front-end is built using React to highlight changes and risks.

[1561] Input: Assessed risk information

[1562] Output: Visual risk information displayed in the user interface

[1563] Step 6:

[1564] The user uses a terminal to input their evaluation of the contract contents, and enters the evaluation score and comments using an HTML form, and the data is sent to the server.

[1565] Input: User rating score and comments

[1566] Output: Rating data sent to the server

[1567] Step 7:

[1568] The server statistically processes all users' rating data and compiles average scores and frequently occurring comments in real time. It uses the Pandas library to aggregate the rating data and generate statistical information.

[1569] Input: Multiple user rating data

[1570] Output: Aggregated average scores and frequently occurring comments

[1571] Step 8:

[1572] The server then publishes the aggregated evaluation data to other users, who can use the published information as a reference when considering contract details.

[1573] Input: Aggregated average rating score and frequently occurring comments

[1574] Output: Aggregate information displayed in the user interface

[1575] Step 9:

[1576] The user uses the terminal to scan or upload the individual contract in electronic file format, and the terminal sends the uploaded data to the server.

[1577] Input: Scanned or uploaded agreement

[1578] Output: Agreement data sent to the server

[1579] Step 10:

[1580] The server extracts text data from the uploaded contract using OCR technology. It uses the Tesseract OCR library to extract text from images.

[1581] Input: Image data of the uploaded contract

[1582] Output: Extracted text data

[1583] Step 11:

[1584] The server analyzes the extracted text data and performs risk assessment. It uses a risk assessment algorithm to identify specific risks (e.g., construction delays, additional costs).

[1585] Input: Extracted text data

[1586] Output: Assessed risk information

[1587] Step 12:

[1588] The server provides the assessed risk information to the user, who is then notified and displayed in a visual interface.

[1589] Input: Assessed risk information

[1590] Output: Risk information provided to the user

[1591] Step 13:

[1592] If a user wishes to change the contents of their contract, they use their device to input the specific changes, and the input data is sent to the server.

[1593] Input: User requests to change contract details

[1594] Output: Changes sent to the server

[1595] Step 14:

[1596] The server automatically generates a new contract based on input from the user, creates a new contract using a specific template, and provides it to the user.

[1597] Input: Proposed changes to the contract contents desired by the user

[1598] Output: The new contract that is generated.

[1599] In this way, the present invention provides a system that makes it easier for users to understand the contents of contracts and terms and conditions, and assists in understanding and evaluating potential risks.

[1600] (Application example 1)

[1601] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1602] There is a need for a system that can quickly identify changes and risks in contracts and clauses, allowing users to easily understand them. However, existing systems require users to manually compare and analyze contracts and clauses, which is extremely labor-intensive. Furthermore, risk assessment of contract content and feedback information from other users are not centrally provided. This can lead to delays and inaccuracies in understanding contract content and appropriate risk assessment. This invention aims to solve these issues by extracting text from contracts and clauses, analyzing risks, visually presenting them through a user interface, and performing detailed analysis using a generative AI model.

[1603] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1604] In this invention, the server includes: means for periodically obtaining the latest version of the contract or terms and conditions; means for comparing the obtained contract or terms and conditions with previous versions to identify differences; means for analyzing the identified differences and classifying and assessing risks; means for visually presenting the classified and assessed risks to the user; means for the user to photograph or upload the contract or terms and conditions; means for using optical character recognition technology to extract text data; means for analyzing the extracted text data and assessing risks; and means for providing a user interface for visually displaying the assessed risk information to the user. This allows the user to quickly understand changes and risks in the contract or terms and conditions and perform appropriate risk assessments. Furthermore, a generative AI model is used to perform detailed analysis of the contract content, which is expected to promote user understanding and improve assessment accuracy.

[1605] "Means for periodically obtaining the latest version of contracts or terms and conditions" refers to technology that automatically collects the latest information on contracts and terms and conditions that are published on the Internet.

[1606] "Means for identifying differences by comparing acquired contracts or terms and conditions with past versions" refers to a technology that compares the latest collected contracts and terms and conditions with past versions to clarify changes.

[1607] "Means for analyzing identified differences and classifying and assessing risks" refers to algorithms or programs for analyzing changes and identifying, classifying, and assessing the risks.

[1608] "Means for visually presenting classified and assessed risks to the user" refers to a technology that displays analyzed risk information in an easy-to-understand manner through a user interface.

[1609] "Means for users to photograph or upload contracts or terms and conditions" refers to technology that allows users to send images or files of contracts or terms and conditions to the system using a smartphone or computer.

[1610] "Means using optical character recognition technology to extract text data" refers to OCR (optical character recognition) technology to extract text information from uploaded images.

[1611] The "means for analyzing extracted text data and assessing risk" refers to a program or algorithm for analyzing the contract content based on the extracted text information and assessing the risk.

[1612] "Means for providing a user interface for visually displaying assessed risk information to a user" refers to an interface technology for displaying assessment results in a form that is visually easy for a user to understand.

[1613] The "means for users to input evaluations of the contract contents" refers to an interface that allows users to input their satisfaction and opinions regarding the contract contents into the system.

[1614] "Means for saving input evaluation data and performing statistical processing in real time" refers to technology that saves evaluation data from users and analyzes and processes it in real time.

[1615] "Means for disclosing aggregated evaluation data to other users" refers to technology that allows analyzed and processed evaluation data to be disclosed and shared with other users.

[1616] "Means of inputting the contents of a contract or terms and conditions as prompt sentences using a generative AI model" refers to a technology that uses natural language processing technology to formalize the contents of a contract or terms and conditions as prompt sentences.

[1617] "Means for performing detailed analysis of contract content using a generative AI model" refers to technology that uses a generative AI model to perform detailed analysis of contract content and provide the results.

[1618] This invention is a system designed to help users easily understand the contents of contracts and terms and conditions. It consists of three main elements: a server, a terminal, and a user. The system's purpose is to quickly identify changes and risks in contracts and terms and conditions and visually present them to users. It can also analyze contract contents using a generative AI model and provide detailed information.

[1619] Server Roles

[1620] The server periodically retrieves the latest version of the contract or terms and conditions from the Internet and stores it in a specific storage device. At this time, the server compares the previous version with the new version and identifies the changes as differences. The identified differences are analyzed using a risk assessment algorithm, and the risks are classified and assessed. This risk information is presented visually to the user.

[1621] The server also uses optical character recognition (OCR) technology to extract text data from contracts and clauses uploaded by users from their devices. The extracted text data is then analyzed in detail using a generative AI model. The analyzed risk information is then sent to the device.

[1622] Device Role

[1623] Users use their smartphone or computer to take a photo of the contract or terms and conditions or upload them as a file. The device then sends this data to the server, which acts as a trigger for OCR processing. The risk information and analysis results received from the server are displayed visually through the device's user interface. Users can easily understand the contract contents based on the visually presented risk information.

[1624] Users can also enter ratings for the contract details, and the rating data is sent to the server in real time. The server stores the rating data and performs statistical processing. This generates and publishes rating information that can be used as reference by other users.

[1625] User operations

[1626] When loading a contract or clause, the user can take a photo using the device's camera or upload an existing file. The device then sends this to the server, which receives risk assessment and analysis results and displays them in an easy-to-read format. The user can also enter their satisfaction with the contract content as an evaluation, and this feedback information is also saved on the server.

[1627] Hardware and software used

[1628] Hardware: smartphones, tablets, computers

[1629] software:

[1630] Google Firebase (backend service)

[1631] OCR library (e.g. Tesseract OCR)

[1632] TensorFlow Lite (Natural Language Processing using Generative AI Models)

[1633] React Native (Mobile Frontend)

[1634] Examples of concrete examples and prompts

[1635] For example, if a user is considering new terms of use for an online storage service, they can take a photo of the new terms of use with their smartphone and upload it. The server will then compare the latest terms with the previous terms to identify any changes. If the changes relate to the handling of personal information, the server will perform a detailed analysis of the risks involved and notify the user. The user can then use this information to consider using the service.

[1636] Example prompt sentence:

[1637] "The changes in the terms and conditions of the new online storage service relate to the handling of personal information, so please assess the risks involved."

[1638] This allows users to quickly understand changes and risks in contracts and terms and conditions, and to conduct appropriate risk assessments. A generative AI model is also used to perform detailed analysis of contract content, which is expected to promote user understanding and improve assessment accuracy.

[1639] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1640] Flow of the system program that realizes the application example

[1641] Step 1:

[1642] Users can photograph or upload contracts and terms and conditions

[1643] Users use their smartphones or computers to take a photo of the contract or terms and conditions or upload an existing file. This input data is in the form of an image or electronic file and is sent from the device to the server.

[1644] Step 2:

[1645] The server extracts the text data

[1646] The server receives uploaded images and files and extracts text data using OCR (Optical Character Recognition) technology. At this stage, the input is image or file format data, and the output is text data.

[1647] Step 3:

[1648] The server compares with the previous version

[1649] The server compares the extracted text data with past versions and performs a difference calculation to identify changes. The input is the current text data and the past text data, and the output is a list of changes.

[1650] Step 4:

[1651] Server analyzes identified differences

[1652] The server runs a risk assessment algorithm based on the identified differences, including a generative AI model. The input is a list of changes, and the output is a risk assessment result.

[1653] Step 5:

[1654] The server sends the risk assessment information to the user

[1655] The server sends the analyzed risk assessment information to the terminal. The input is the risk assessment result, and the output is data that can be displayed visually.

[1656] Step 6:

[1657] The device visually displays risk information

[1658] The terminal visually presents the risk assessment information received from the server to the user. In this step, the user interface displays the risk information in an easy-to-understand format. The input is the visualization data sent from the server, and the output is the display on the screen.

[1659] Step 7:

[1660] The user enters their evaluation of the contract contents

[1661] Users input their evaluation of the contract details through their device. The evaluation data is entered in the form of comments and scores and is sent from the device to the server.

[1662] Step 8:

[1663] The server stores and processes the evaluation data

[1664] The server stores the evaluation data received from users and performs statistical processing in real time. The input is the user evaluation data, and the output is the statistical processing result.

[1665] Step 9:

[1666] The server exposes the rating data to other users

[1667] The server displays the statistically processed evaluation data in a specific interface to make it public to other users. The input is the statistically processed evaluation data, and the output is public information.

[1668] Specific examples of actions and prompt format

[1669] For example, when a user reviews new terms of service for an online storage service, they might use the following prompt:

[1670] "The changes in the terms and conditions of the new online storage service relate to the handling of personal information, so please assess the risks involved."

[1671] By inputting this prompt into the generative AI model, users can quickly receive a specific risk assessment, significantly reducing the burden on users and making it easier for them to evaluate and understand the contract contents.

[1672] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1673] The present invention is a system that presents changes to contracts and terms and conditions to users, evaluates and notifies them of the risks involved, and dynamically adjusts the interface based on user emotions. Specifically, the system is implemented as follows:

[1674] Overall system configuration

[1675] This system consists of a server, a terminal, a user, and an emotion engine. The server is responsible for data management and analysis of contracts and terms and conditions, and emotional data processing, while the terminal provides the user interface. The emotion engine recognizes user emotions in real time and optimizes system operation based on them.

[1676] Understanding changes to contracts and terms and conditions and clarifying risks

[1677] The server periodically retrieves the latest version of the contract or clause from the website. The retrieved data is compared with previous versions to identify any changes. The server analyzes these changes and uses a risk assessment algorithm to classify and assess the risks. The classified and assessed risk information is stored in a database for visual presentation to the user.

[1678] When a user accesses a risk information page, the device displays the changes and their associated risks in a visually easy-to-understand format, including color coding. If the user expresses an emotional reaction to a particular section, the device's emotion engine analyzes the data and dynamically adjusts the display. For example, if the user is extremely anxious, the device will provide more detailed information and advice on that section.

[1679] Evaluation and disclosure of contract details

[1680] Users input their ratings of the contract details through their terminals. The entered rating data is sent to the server and stored in a database. The server then statistically processes the rating data in real time and makes the results available to other users.

[1681] The emotion engine recognizes the emotion a user is feeling when entering a rating and incorporates that emotion data into the rating process. For example, if a user has very positive emotions, their rating may be weighted higher.

[1682] Individual contract risk assessment

[1683] Users scan or upload individual contracts as electronic files. The device receives the documents and sends them to the server. The server uses OCR technology to extract text from the contract and analyzes it with a risk assessment algorithm. The results are then reported to the user, and the necessary risk information is displayed on the device.

[1684] The emotion engine recognizes the emotions users express while viewing risk information and adjusts how the risk is presented based on that emotion. For example, if a user expresses surprise or disappointment, additional explanations or solutions will be provided for that risk.

[1685] Drafting and providing contract amendment proposals

[1686] If the user wishes to change the contract terms, they enter the changes. The device sends the changes to the server, which then uses an automated contract generation library to generate a new contract draft. The draft is then reviewed and provided to the user.

[1687] The emotion engine also takes into account the user's emotions when drafting contract changes, helping to reduce stress. For example, if the user is feeling impatient, it will provide operational guidance and real-time support.

[1688] Specific examples

[1689] For example, if a user is considering new terms of use for an online storage service, the server retrieves the latest terms and compares them with previous terms to identify any changes. If the changes relate to the handling of personal information, the server performs a detailed analysis of the risks and notifies the user. If the information makes the user feel uneasy, the emotion engine recognizes this emotion and provides more detailed information or additional advice.

[1690] For example, if a user uploads a contract for constructing a new building, the server analyzes the contract and notifies the user about specific risks (e.g., construction delays, additional costs). If the user expresses surprise or concern, the emotion engine will detect this and provide more detailed countermeasures for the risk.

[1691] As described above, the present invention makes it easier to understand the contents of contracts and terms and conditions while taking into account the user's emotions, helps to identify potential risks, and provides a method for efficiently changing the contents of contracts.

[1692] The processing flow will be explained below.

[1693] Understanding changes to contracts and terms and conditions and clarifying risks

[1694] Step 1:

[1695] The server periodically crawls the specified list of websites to retrieve the latest version of the contract or terms and conditions, and stores the retrieved data in storage.

[1696] Step 2:

[1697] The server uses a difference detection library (e.g., diff-match-patch) to compare the latest version of the contract or clause with the previous version and identify the changes.

[1698] Step 3:

[1699] The server then analyzes the identified changes with a risk assessment algorithm to classify and assess the risk. For example, if there is a change related to the handling of personal information, it will classify it as a high risk.

[1700] Step 4:

[1701] The server stores the analysis results in a database and prepares it so that risk information can be visually presented when accessed by a user.

[1702] Step 5:

[1703] When a user accesses the risk information page, the device displays the changes and risks in a visually easy-to-understand format, such as color-coding.

[1704] Evaluation and disclosure of contract details

[1705] Step 1:

[1706] The user uses an input form on the terminal to input an evaluation score and comments on the contract contents.

[1707] Step 2:

[1708] The terminal transmits the evaluation score and comments entered by the user to the server.

[1709] Step 3:

[1710] The server stores the received evaluation data in a database and performs real-time statistical processing, such as calculating the average evaluation score and frequently occurring comments.

[1711] Step 4:

[1712] The server visualizes the results and updates the evaluation page so that other users can see them.

[1713] Step 5:

[1714] When other users access the rating page, the terminal displays the aggregated rating scores and comments.

[1715] Individual contract risk assessment

[1716] Step 1:

[1717] The user uses the upload function on the device to upload the contract in scanned or PDF format.

[1718] Step 2:

[1719] The terminal transmits the uploaded contract to the server.

[1720] Step 3:

[1721] The server uses OCR (Optical Character Recognition) software to extract text data from the contract.

[1722] Step 4:

[1723] The server then analyzes the extracted text data using a risk assessment algorithm to identify risks, such as risks related to payment terms or construction extensions.

[1724] Step 5:

[1725] The server stores the evaluation results in a database and makes them available for user review.

[1726] Step 6:

[1727] The device provides the user with the risk assessment results in an easily identifiable manner, highlighting areas of concern or specific risk areas.

[1728] Drafting and providing contract amendment proposals

[1729] Step 1:

[1730] The user uses an input form on the terminal to input requests for changes to the contract contents, such as shortening the contract period or changing the payment terms.

[1731] Step 2:

[1732] The terminal transmits the input desired changes to the server.

[1733] Step 3:

[1734] The server uses an automated contract generation library to generate a new draft contract based on the inputs.

[1735] Step 4:

[1736] The server checks the generated draft contract using an internal review system and makes corrections as necessary.

[1737] Step 5:

[1738] The server stores the revised draft contract in a database so that it can be provided to the user.

[1739] Step 6:

[1740] The terminal displays the new draft contract to the user and makes it available for download if desired.

[1741] Operation using emotion engine (processing based on additional claims)

[1742] Step 1:

[1743] The emotion engine analyzes facial expressions and voice data in real time while the user is viewing a contract or terms and conditions.

[1744] Step 2:

[1745] The server receives the emotion data sent from the emotion engine and identifies the user's emotional state based on the analysis results. For example, if the user shows surprise or anxiety, the emotion data is reflected in the risk assessment.

[1746] Step 3:

[1747] The device dynamically changes how it presents risk information depending on the user's emotional state: if the user feels anxious, it displays additional details or advice.

[1748] Step 4:

[1749] The server stores the emotion data in a database and uses it as reference information for future interactions.

[1750] Step 5:

[1751] The emotion engine weights contract and risk assessment results based on the user's emotional data, providing more personalized results.

[1752] Step 6:

[1753] The user can use the terminal to make decisions or make changes to the contract contents based on feedback and advice from the emotion engine.

[1754] In this way, by explaining each processing step in detail, the specific operation of the system and its linkage with the emotion engine become clear.

[1755] Example 2

[1756] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1757] The contents of contracts and terms and conditions change frequently, making it difficult to quickly and accurately grasp these changes. Furthermore, risk assessment and information presentation that takes user emotions into consideration are not adequately implemented, making it difficult for users to accurately understand risks and respond appropriately. Conventional systems do not dynamically adjust the display method based on the user's emotional state, which can result in a poor user experience. Furthermore, when users input their evaluation of specific contract content, there is also the issue of the evaluation not being properly fed back based on their emotions.

[1758] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for periodically acquiring the latest version of the contract or terms and conditions, a means for comparing the acquired contract or terms and conditions with previous versions to identify differences, a means for analyzing the identified differences and classifying and assessing risks, a means for visually presenting the classified and assessed risks to the user, and a means for recognizing the user's emotions in real time and dynamically adjusting the display method based on the recognition results. This allows the user to quickly and accurately grasp changes to the contract or terms and understand the risks. Furthermore, the dynamic presentation of information according to the user's emotions improves the user experience. Furthermore, more appropriate feedback can be provided by incorporating the user's emotional evaluation into statistical processing.

[1759] "Means for periodically obtaining the latest version of the contract or terms and conditions" refers to a system that automatically obtains the latest version of the contract or terms and conditions from a website or database at regular intervals.

[1760] "Means for comparing the acquired contract or terms and conditions with previous versions to identify differences" refers to algorithms or processes for comparing the content of the latest contract or terms and conditions with previous versions and identifying any changes.

[1761] The "means of analyzing identified differences and classifying and assessing risks" is a mechanism for analyzing the changed parts in detail, extracting each risk element, and classifying and assessing them.

[1762] "Means for visually presenting classified and assessed risks to users" refers to an interface that displays assessment results in a format that is easy for users to understand, and a mechanism that provides visual feedback.

[1763] "Means for recognizing a user's emotions in real time and dynamically adjusting the display method based on the recognition results" refers to a technology that monitors a user's emotional state in real time through sensor devices such as cameras and microphones, and automatically changes the content and method of display according to the obtained emotional data.

[1764] The "means for users to input evaluations of the contract contents" is an interface that allows users to input evaluations and comments on the contract and terms and conditions.

[1765] The "means for saving the input evaluation data and performing statistical processing in real time" refers to a system for saving user evaluations in a database and instantly analyzing and statistically processing the data.

[1766] The "means for disclosing aggregated evaluation data to other users" is an interface that provides the analyzed and statistically processed evaluation results in a form that can be accessed by other users.

[1767] "Means for incorporating user emotional evaluations into statistical processing" refers to a process for analyzing user emotional data together with evaluation data to provide statistical feedback and improvements.

[1768] "Means for scanning or uploading individual contract contents" means a method by which a user can convert a physical contract into digital form or submit an existing electronic file to the system.

[1769] "Means for extracting the text of an uploaded contract" refers to technology for extracting text information from the digital data of a scanned or uploaded contract, including OCR (optical character recognition) technology.

[1770] The "means for analyzing extracted text data and assessing risks" refers to a process of analyzing the contract contents in detail based on the extracted text information, and identifying and assessing potential risks.

[1771] "Means for providing assessed risk information to a user" means an interface for providing analyzed and assessed risk information to a user in a visual or notification format.

[1772] "Means for recognizing the user's emotions and adjusting the way risk information is presented based on the results of that recognition" refers to a mechanism that analyzes the user's emotional data in real time and changes the way risk information is presented based on the r...

Claims

1. A means of periodically obtaining the most current version of the contract or terms and conditions; A means of comparing the retrieved contract or clause with a previous version to identify any differences; A means of analyzing the identified gaps and categorizing and assessing the risks; a means of visually presenting the classified and assessed risks to the user; A system including:

2. A means for users to input their evaluation of the contract contents; A means for storing the input evaluation data and performing real-time statistical processing; a means for publishing the aggregated evaluation data to other users; The system of claim 1 , comprising:

3. A means to scan or upload the contents of the individual contract; a means for extracting the text of the uploaded contract; a means for analyzing the extracted text data and assessing risk; a means for providing assessed risk information to users; The system of claim 1 , comprising:

4. A means for the user to input changes to the contract contents when the user wishes to change the contents; A means for automatically generating a new draft contract based on the entered changes; a means for providing the generated draft contract to the user and making it available for download; The system of claim 1 , comprising:

5. 2. The system according to claim 1, further comprising a means for displaying the types of changes in different colors as a risk notification means for the changed terms and conditions.

Images