system

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting a URL or file of a contract clause by a user; means for acquiring a clause text from the URL or file; means for summarizing the acquired clause text using a generation AI; means for comparing with a standard clause database; means for analyzing legal and economic risks based on the clause; means for evaluating validity of the contract based on prior information of the user; and means for presenting the evaluation results and individual problems to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Many consumer contracts are based on terms and conditions or agreements, but users often enter into these contracts without reading them at all. As a result, users are unable to grasp the important points and risks of the contract, and may end up agreeing to unfavorable terms. Furthermore, even if companies fulfill their obligation to explain the terms and conditions, contracts often proceed without the content being understood. This can lead to problems between companies and users and damage trust. There is a need to resolve these issues and make it easier for users to understand the content of contracts. [Means for solving the problem]

[0005] To solve the above-mentioned problems, we provide a system that allows users to input the URL or file of contract terms and conditions and retrieve the text of the terms and conditions from that URL or file. The system uses generative AI to summarize the retrieved text and compare it with a standard database of terms and conditions to highlight differences and characteristics. It also analyzes legal and economic risks and evaluates the validity of the contract based on the user's prior information. The evaluation results and individual issues are presented to the user, allowing them to easily understand the content and risks of the contract. This system improves users' understanding of the contract and enables fairer and more transparent contracts.

[0006] "User" means an individual or entity that uses the System to enter contract terms and conditions and receives the analysis results.

[0007] A "URL" is a uniform resource locator used to identify resources (e.g., web pages) on the Internet.

[0008] A "file" is a unit of digital data for storing and managing information on a computer.

[0009] "Terms and conditions text" is a text document that describes the detailed conditions and clauses of a contract.

[0010] "Generative AI" refers to artificial intelligence that uses natural language processing and machine learning techniques to analyze and generate text.

[0011] The "standard clauses database" is a database that collects samples and standards of commonly used clauses.

[0012] "Legal risk" refers to the possibility that clauses in a contract may conflict with laws or regulations and the resulting legal issues.

[0013] "Financial risk" refers to the possibility of financial burden or loss under a contract.

[0014] "Prior information" is personal and situational data provided by the user.

[0015] "Validity" refers to the legal and actual effect of a contract.

[0016] "Individual issues" refer to terms and conditions contained in a specific contract that are unfavorable to users or matters that should be taken into consideration. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] This invention builds a system that uses generative AI to automatically analyze contract terms and conditions and provide users with important information. This system allows users to efficiently understand online contract terms and conditions and assess risks. Specific embodiments are described below.

[0039] User Input

[0040] The user can input the URL or file of the contract terms using the device, for example, by entering the URL of the mobile carrier's contract terms through a web browser or a dedicated application, or by uploading a previously saved PDF file.

[0041] Obtaining and analyzing terms and conditions

[0042] The server retrieves the text of the terms and conditions from the URL entered by the user. To do this, it issues an HTTP request to retrieve the HTML document from the specified web page and extracts the text from specific tags. Alternatively, if a file is uploaded, it extracts the text using an appropriate library. For example, Apache Tika can be used to extract text from a PDF.

[0043] Terms and conditions summary function

[0044] The server then uses a generative AI to summarize the extracted clause text. This summarization is done using a natural language processing model (e.g., GPT-4) to extract key points from the clause based on important keywords and phrases, allowing users to understand lengthy clauses concisely.

[0045] Comparison function with standard clauses

[0046] The server compares the retrieved clause text with a database of standard clauses, using a comparison algorithm to identify differences and similarities and highlight any unusual clauses or different terms. For example, if the clauses regarding penalty fees or cancellation procedures differ from the standard clauses, this will be highlighted.

[0047] Legal and economic risk analysis

[0048] The server analyzes the legal and economic risks based on the contract text. It uses a risk assessment algorithm to assess clauses that may conflict with laws and regulations, as well as financial risks under the contract. For example, if there are unreasonable penalties or unfair clauses, it notifies the user.

[0049] Contract validity based on applicant's prior information

[0050] Users enter their personal information (e.g., age, occupation, and place of residence). The server evaluates the validity of the contract based on this information. For example, it evaluates and warns if the contract contains clauses that are inappropriate for minors or if certain conditions are not met.

[0051] Presentation of individual problems

[0052] Based on the analysis and comparison results, the server will present specific issues and items that the user should pay attention to, including a detailed explanation of the contract terms and the steps the user should take, such as providing details about automatic renewal terms and additional charges.

[0053] Displaying the results

[0054] Finally, the server displays the generated report on the user's device. This report includes a summary, risk analysis results, comparison results with standard terms and conditions, and points to note. The user can use this information to understand the contract contents and decide whether to proceed with the contract. For example, the user can click on links in the report to view more detailed information.

[0055] In this way, users can quickly understand the contents of complex contract terms and conditions, and proceed with the contract after understanding the risks and points to be aware of. The system reduces the burden on users and plays a role in making contracts fairer and more transparent.

[0056] The processing flow will be explained below.

[0057] Step 1:

[0058] The user inputs the URL or file of the contract terms and conditions using the terminal. The user inputs the URL into the input field of a web browser or dedicated application, or selects the file using the upload button.

[0059] Step 2:

[0060] The device sends the entered URL or uploaded file to the server, issuing an HTTP request containing the necessary request parameters to the server.

[0061] Step 3:

[0062] The server retrieves the clause text from the URL by issuing an HTTP request to retrieve the HTML document from the specified web page, extracting the text using an HTML parsing library, and, if a file was uploaded, extracting the text from the file using an appropriate library (e.g., Apache Tika).

[0063] Step 4:

[0064] The server uses a generative AI to summarize the terms and conditions text it has acquired. A natural language processing model (e.g., GPT-4) is used to generate a summary based on important keywords and phrases in the terms and conditions.

[0065] Step 5:

[0066] The server compares the summarized clause text with a database of standard clauses. Comparison algorithms are used to identify differences and similarities. By comparing with the standard clauses, unusual clauses and different terms are highlighted.

[0067] Step 6:

[0068] The server analyzes the legal and economic risks based on the contract text, using a risk assessment algorithm to assess clauses that may violate laws and regulations, as well as economic risks (e.g., high penalties, unfair terms).

[0069] Step 7:

[0070] The user enters their personal information (e.g., age, occupation, place of residence), and the device sends this information to the server.

[0071] Step 8:

[0072] The server evaluates the validity of the contract based on the prior information provided by the user, and verifies whether the contract is valid according to legal restrictions and applicable conditions.

[0073] Step 9:

[0074] The server presents individual issues based on the analysis and comparison results, lists unfavorable conditions and points to be aware of for users contained in specific contracts, and generates detailed explanations and recommendations.

[0075] Step 10:

[0076] The terminal displays the report received from the server to the user, which includes a summary, risk analysis results, comparison results with standard clauses, and points to note, allowing the user to easily check important information.

[0077] Example 1

[0078] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0079] Contract terms and conditions are typically difficult for users to understand, requiring a great deal of time and effort. Furthermore, users face the risk of overlooking legal and economic risks or unfair clauses, making it difficult for them to accurately grasp the contents of the contract. Furthermore, it is not easy to recognize clauses that differ from standard terms and conditions, or to determine the validity of a contract based on personal information. There is a need for a system that can solve these issues and enable users to quickly and accurately understand contract terms and conditions and assess risks.

[0080] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0081] In this invention, the server includes: means for a user to input a URL or file of the contract terms and conditions; means for acquiring the text of the terms and conditions from the URL or file; means for extracting the acquired text of the terms and conditions using data analysis means; means for summarizing the extracted text of the terms and conditions using a generative AI model; means for comparing the text with a standard database of terms and conditions; means for evaluating the legal and economic risks based on the terms and conditions; means for evaluating the validity of the contract based on the user's personal information; means for presenting the evaluation results and individual issues to the user; and means for displaying the evaluation results on the user's terminal using a display device. This allows the user to quickly understand the terms and conditions, grasp the legal and economic risks and points to note, and make an appropriate decision about the contract.

[0082] "User" means the entity that inputs the URL or file of the terms and conditions and receives information based thereon.

[0083] A "URL" is a Uniform Resource Locator that points to resources on the Internet and indicates the address of a web page.

[0084] A "file" is a unit for storing data, and in the present invention, it mainly refers to contract terms and conditions in PDF format.

[0085] "Terms and conditions text" refers to the text portion of a document that describes the terms and conditions of a contract.

[0086] "Data analysis means" refers to means for extracting useful information from input data.

[0087] A "generative AI model" is an artificial intelligence model that learns large amounts of data to generate language, such as GPT-4.

[0088] The "standard clause database" is a database that stores commonly used standard contract clauses.

[0089] "Legal and economic risks" refers to the legal and economic risks based on the terms and content of the contract.

[0090] "Personal information" refers to information that identifies an individual, such as a user's age, occupation, or place of residence.

[0091] "Evaluation results" refer to conclusions or judgments drawn based on analysis or comparison.

[0092] "Individual issues" refer to points of caution and risk factors in specific contract terms and conditions.

[0093] A "display device" is a device used to display information to users, and primarily refers to the screen of a computer or smartphone.

[0094] This invention builds a system that uses generative AI models to automatically analyze contract terms and conditions and provide users with important information. This system allows users to efficiently understand online contract terms and conditions and assess risks. The system's programming primarily relies on data analysis, natural language processing, and comparison algorithms.

[0095] First, the user uses the device to input the URL or file of the contract terms. This can be done through a web browser input form or a dedicated application. For example, the user can input the URL of the mobile carrier's contract terms or upload a saved PDF file.

[0096] The server issues an HTTP request to the URL entered by the user to retrieve the HTML document from the specified web page, and if a file was uploaded, extracts the text from the PDF using an appropriate library (e.g., Apache Tika). This text extraction is performed using an HTML parser.

[0097] Next, the server summarizes the extracted clause text using a generative AI model (e.g., GPT-4). The server inputs a prompt such as "Please summarize this text in 100 characters or less" to the generative AI model and receives the generated summary data. This allows the user to understand the lengthy clause text concisely.

[0098] The server then compares the retrieved clause text with a database of standard clauses, using a comparison algorithm to identify differences and similarities and highlight any unusual clauses or different terms. For example, if the clauses regarding penalty fees or cancellation procedures differ from the standard clauses, the differences will be highlighted.

[0099] The server then assesses the legal and financial risks of the contract text. Using a risk assessment algorithm, it analyzes clauses that may violate laws and regulations, as well as the financial risks associated with the contract. For example, it warns users of any unreasonable penalty charges or unfair clauses.

[0100] Users enter their personal information (e.g., age, occupation, and place of residence), and the server evaluates the validity of the contract based on this information. For example, it evaluates and warns if the contract contains clauses that are inappropriate for minors or if certain conditions are not met.

[0101] Based on the analysis and comparison results, the server will present specific issues that the user should pay attention to, including a detailed explanation of the contract terms and the steps the user should take, such as providing details about automatic renewal terms and additional charges.

[0102] Finally, the server displays the generated report on the user's device. This report includes a summary, risk analysis results, comparison results with standard terms and conditions, and points to note. The user can use this information to understand the contract contents and decide whether to proceed with the contract. For example, they can click on links in the report to view more detailed information.

[0103] Prompt Sentence Examples

[0104] Terms and conditions URL: https: / / example.com / contract-terms

[0105] or

[0106] Upload the PDF file of the terms and conditions: [Select PDF file]

[0107] User information: Age=25, Occupation=Engineer, Residence=Tokyo

[0108] Using this system, users can quickly and accurately understand the contents of contract terms and conditions and appropriately assess risks.

[0109] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0110] Step 1:

[0111] User Input

[0112] The user uses a device to enter the URL or file of the contract terms. For example, they can enter the URL of the contract terms (https: / / example.com / contract-terms) in the input field of a web browser, or they can launch a dedicated application, click the "Select File" button, and select a saved PDF file. The URL or file entered by the user becomes the input data. The output is the entered URL or file.

[0113] Step 2:

[0114] Obtaining the terms and conditions

[0115] The server issues an HTTP request to the URL entered by the user to retrieve the HTML document from the specified web page. If a file is uploaded, it also receives the file contents. Specifically, the server uses an HTTP GET request to download the HTML document. If a PDF file is uploaded, it receives the file. The input is the URL or file obtained from the user, and the output is the retrieved HTML document or PDF file.

[0116] Step 3:

[0117] Text Extraction

[0118] The server extracts text from an HTML document or PDF file. In the case of HTML, it parses specific tags to obtain the text, and in the case of PDF, it uses the Apache Tika library to extract the text. The server uses an HTML parser to extract the clause text from specific tags in the HTML document, and in the case of PDF files, it calls Apache Tika to extract the text. The input is an HTML document or a PDF file, and the output is the extracted clause text.

[0119] Step 4:

[0120] Generate summary of terms and conditions

[0121] The server inputs the extracted clause text into a generative AI model (e.g., GPT-4) to generate a summary. The server inputs a prompt ("Please summarize this text in 100 characters or less") to the generative AI model and receives the summarized text. Specifically, the server generates a prompt for GPT-4 and obtains the summary data through an API. The input is the extracted clause text, and the output is the summarized text.

[0122] Step 5:

[0123] Comparison with standard terms and conditions

[0124] The server compares the retrieved clause text with a standard clause database. It uses a comparison algorithm to identify differences and similarities and highlight unusual clauses or different terms. The server queries the standard clause database and compares it sentence by sentence with the retrieved clause text. The input is the clause text and the standard clause database, and the output is the comparison result data.

[0125] Step 6:

[0126] Legal and economic risk analysis

[0127] The server uses a risk assessment algorithm to analyze the clauses in the contract and identify legal and economic risks. If unfair clauses or unfair penalties exist, it generates data to warn the user. The input is the contract text, and the output is the risk assessment results.

[0128] Step 7:

[0129] Contract validity assessment based on personal information

[0130] The user enters their personal information (e.g., age, occupation, place of residence), and the server evaluates the validity of the contract based on this information. The server checks whether the contract terms are in compliance with the user's personal information and issues a warning. The input is the user's personal information and the contract text, and the output is the result of the contract validity evaluation.

[0131] Step 8:

[0132] Presentation of individual problems

[0133] Based on the analysis and comparison results, the server presents specific issues and items that the user should pay attention to. It provides detailed explanations and measures that the user should take. For example, it provides notes on the automatic renewal conditions and details of additional fees. The input is the comparison results and risk assessment results, and the output is data on issues and measures.

[0134] Step 9:

[0135] Displaying the results

[0136] The server displays the generated report on the user's device. This report includes a summary, risk analysis results, comparison results with standard clauses, and points to note. The user can use this information to understand the contract contents and decide whether to proceed with the contract. For example, they can click on a link in the report to view more detailed information. The input is various data in the report, and the output is the report displayed on the user's device.

[0137] (Application example 1)

[0138] 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."

[0139] Users of electronic payment services have difficulty quickly understanding the complex content of contract terms and conditions and assessing legal and economic risks. They also lack the means to identify unusual clauses compared to standard contract terms and obtain information to avoid risks. This increases the risk of entering into unfavorable contracts.

[0140] 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.

[0141] In this invention, the server includes means for a user to input a link or file of the contract terms and conditions, means for retrieving the text of the terms and conditions from the link or file, means for summarizing the retrieved text of the terms and conditions using a generation AI, means for comparing it with a standard database of terms and conditions, means for analyzing legal and economic risks based on the terms and conditions, means for evaluating the validity of the contract based on the user's prior information, means for presenting the evaluation results and individual issues to the user, and means for displaying the analysis results of the contract terms and conditions on the user's terminal. This allows the user to quickly and efficiently understand the contents of the contract terms and conditions, evaluate the risks, and make a comprehensive judgment to proceed with the appropriate contract.

[0142] "User" means a consumer who uses electronic payment services.

[0143] "Terms and conditions" are documents in which an electronic payment service provider lists the terms and conditions of use.

[0144] A "link" is a URL that accesses a specific web page.

[0145] "File" refers to document data stored in electronic format.

[0146] "Terms and conditions text" refers to the content of the contract terms and conditions expressed in text form.

[0147] "Generative AI" is an artificial intelligence technology that uses natural language processing to generate and analyze text.

[0148] A "summary" is a short summary of the most important parts of the original text.

[0149] A "standard clause database" is a collection of commonly used contract clauses managed as a database.

[0150] A "comparison algorithm" is a computational method that compares different texts to identify differences and similarities.

[0151] "Legal and Economic Risks" means legal issues and economic burdens that the User may incur under the Agreement.

[0152] "Prior information" refers to personal information or circumstances provided by the user.

[0153] "Validity" refers to whether a contract is legally established and effective.

[0154] "Evaluation results" refers to information provided by the system as a result of analysis.

[0155] "Individual issues" refer to specific points of caution or risk factors in the contract terms and conditions.

[0156] "Terminal" means a device (e.g., smartphone, tablet) used by a User to enter and display information.

[0157] "Displaying" refers to the act of visually providing analysis results and information on the user's device.

[0158] To realize this invention, the interaction between the user, the server, and the terminal used by the user is important.

[0159] First, the user inputs a link or an existing file to access the contract terms of the electronic payment service into the terminal. For example, the user can input the link to the contract terms using a web browser or a dedicated application, or upload a saved PDF file.

[0160] The server then issues an HTTP request from the provided link to retrieve the HTML document from the specified web page, or, if a file was uploaded, extracts the text using a text extraction library such as Apache Tika.

[0161] The retrieved contract text is summarized on the server using a generative AI model (e.g., GPT-4). This summarization process uses natural language processing techniques to extract key points from the contract based on important keywords and phrases, allowing users to easily understand lengthy contracts.

[0162] The server then compares the extracted clause text with a database of standard clauses using a comparison algorithm such as a Python-based Diff library, which identifies any unusual clauses or conditions that differ from the standard clauses and highlights them for the user.

[0163] In addition, the server applies a risk assessment algorithm to analyze legal and financial risks, which assesses the legal and financial consequences that users may incur. For example, any unreasonable penalties or unfair terms will be clearly indicated to the user.

[0164] Finally, the server generates a detailed report containing the analysis and comparison results, which is displayed on the user's device. This report includes a summary, risk analysis, comparison results with standard terms and conditions, and points to note. Based on this, the user can understand the contract contents and make a comprehensive decision on whether to proceed with the contract.

[0165] As a concrete example, consider a case where a user tries to analyze the terms and conditions at the URL "https: / / example.com / terms-and-conditions.pdf." When the user enters the URL into the app, the server downloads the PDF file and extracts the text. It then uses a generative AI model to create a summary and compare it with standard terms and conditions to identify any discrepancies. It also performs a risk analysis and warns the user if any unfair clauses are present. Finally, all analysis results are notified to the user, allowing them to quickly understand the contents of the contract terms and take appropriate action.

[0166] An example of a prompt is shown below.

[0167] Analyze the contract terms and conditions found at the URL "https: / / example.com / terms-and-conditions.pdf" and create a summary based on key keywords and phrases. Also compare it with standard terms and conditions, highlight any differences, and analyze the legal and financial risks.

[0168] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0169] Step 1:

[0170] The user inputs the link or file of the contract terms into the device. Specifically, the user opens a web browser or a dedicated application and inputs the URL to the contract terms or uploads an existing PDF file. The input for this step is the link or file, and the output is the information entered by the user.

[0171] Step 2:

[0172] The server retrieves the terms and conditions text based on the link or file received from the user. In the case of a link, the server issues an HTTP request to retrieve the HTML document from the specified web page. In the case of a file, the server uses a text extraction library such as Apache Tika to extract the text. The input for this step is the link or file provided by the user, and the output is the retrieved terms and conditions text.

[0173] Step 3:

[0174] The server summarizes the retrieved clause text using a generative AI model. The generative AI model (e.g., GPT-4) uses natural language processing techniques to extract key points from the clause based on important keywords and phrases. The input for this step is the retrieved clause text, and the output is a summarized clause.

[0175] Step 4:

[0176] The server compares the summarized clause text with a database of standard clauses. A comparison algorithm (e.g., a Python-based Diff library) is used to compare the extracted text with the contents of the standard clause database to identify differences and similarities. The input to this step is the summarized clause text, and the output is the identification of differences and similarities.

[0177] Step 5:

[0178] The server applies a risk assessment algorithm to analyze the legal and economic risks based on the retrieved contract text. Any unreasonable penalties or unfair clauses are identified and notified to the user. The input of this step is the retrieved contract text, and the output is the result of the risk analysis.

[0179] Step 6:

[0180] The server evaluates the validity of the contract based on the user's personal information. The user inputs personal information from the terminal (e.g., age, occupation), and the server evaluates whether the contract terms are legally appropriate based on this information. The input of this step is the user's prior information, and the output is the evaluation result of the validity of the contract.

[0181] Step 7:

[0182] The server presents the analysis results, comparison results, risk analysis, and individual issues to the user. A detailed report containing this information is generated and displayed on the user's terminal. The input to this step is each result of the analysis, and the output is a detailed report presented to the user.

[0183] Step 8:

[0184] The user checks the report on the terminal and understands the contract contents. Based on the report generated by the server, the user makes an overall decision on whether to proceed with the contract. The input of this step is the presented report, and the output is the user's decision and action.

[0185] 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.

[0186] This invention combines an emotion engine with a system that uses generative AI to automatically analyze contract terms and conditions and provide important information to users, recognizing the user's emotional state in real time and dynamically providing information. Specific embodiments are described below.

[0187] User Input

[0188] The user inputs the URL or file of the contract terms and conditions using a terminal. The user can either enter the URL into the input field of a web browser or dedicated application, or upload a saved PDF file. This provides the system with the contract terms and conditions that the user wants to analyze.

[0189] Obtaining and analyzing terms and conditions

[0190] The server issues an HTTP request to retrieve the clause text from the URL entered by the user, retrieves the HTML document from the specified web page, extracts the text using an HTML parsing library, and, if a file was uploaded, extracts the text from the file using an appropriate library (e.g., Apache Tika).

[0191] Terms and conditions summary function

[0192] The server then uses a generative AI to summarize the extracted clause text. This summary is done using a natural language processing model (e.g., GPT-4) to extract key points from the clause based on important keywords and phrases, allowing users to understand lengthy clauses concisely.

[0193] Comparison function with standard clauses

[0194] The server compares the retrieved clause text with a database of standard clauses, using a comparison algorithm to identify differences and similarities and highlight any unusual clauses or different terms. For example, if the clauses regarding penalty fees or cancellation procedures differ from the standard clauses, this will be highlighted.

[0195] Legal and economic risk analysis

[0196] The server analyzes the legal and economic risks based on the contract text. It uses a risk assessment algorithm to evaluate clauses that may conflict with laws and regulations, as well as financial risks under the contract (e.g., high penalty fees, unfair terms). This allows users to understand the potential risks contained in the contract.

[0197] Contract validity based on applicant's prior information

[0198] The user enters their personal information (e.g., age, occupation, place of residence). The server uses this information to assess the validity of the contract. By verifying whether the contract is valid according to legal restrictions and applicable conditions, the server can, for example, warn if the contract contains terms that are inappropriate for minors.

[0199] Presentation of individual problems

[0200] Based on the analysis and comparison results, the server presents specific issues and items that users should pay attention to. This includes listing unfavorable terms and conditions contained in specific contracts and generating detailed explanations and recommendations. For example, it provides notes on automatic renewal terms and details of additional fees.

[0201] Emotion Recognition and Dynamic Information Provision

[0202] The server is equipped with an emotion engine that analyzes the user's facial expressions and voice while they are typing and displaying reports, recognizing their emotions. For example, if the user looks anxious, the server will provide information that corresponds to that emotion. This makes it possible to dynamically adjust information while taking into account the user's emotional state.

[0203] Displaying the results

[0204] Finally, the server displays the generated report on the user's device. The report includes a summary, risk analysis results, comparison results with standard policy terms, points to note, and advice based on the user's emotional state. For example, users can click on links within the report to view more detailed information, which reflects feedback from the emotion engine.

[0205] In this way, users can quickly understand the contents of complex terms and conditions, and proceed with the contract after understanding the risks and points to note. The combination of the emotion engine makes it possible to provide appropriate information according to the user's emotional state, greatly improving the user experience.

[0206] The processing flow will be explained below.

[0207] Step 1:

[0208] The user inputs the URL or file of the contract terms and conditions using the terminal. The user either inputs the URL into the input field of a web browser or dedicated application, or selects the appropriate file using the upload button.

[0209] Step 2:

[0210] The terminal sends the URL entered by the user or the uploaded file to the server. The information sent to the server as an HTTP request includes the user's input data.

[0211] Step 3:

[0212] The server issues an HTTP request to retrieve the clause text from the URL, retrieves the HTML document for the specified web page, extracts the text from the HTML document using an HTML parsing library, or, if a file is uploaded, extracts the text using an appropriate library such as Apache Tika.

[0213] Step 4:

[0214] The server uses generative AI to summarize the terms and conditions text it has acquired. It uses a natural language processing model (e.g., GPT-4) to summarize the text based on important keywords and phrases, allowing the main points to be displayed concisely.

[0215] Step 5:

[0216] The server compares the summarized clause text with a database of standard clauses. Comparison algorithms are used to identify differences and similarities when compared to standard clauses. Different clauses and distinctive terms are highlighted.

[0217] Step 6:

[0218] The server analyzes the legal and economic risks of the terms and conditions, using a risk assessment algorithm to assess clauses that may violate laws and regulations, as well as economic risks (e.g., high penalties, unfair terms).

[0219] Step 7:

[0220] The user enters their personal information (e.g. age, occupation, place of residence, etc.) This information is used to evaluate the validity of legal and contractual terms.

[0221] Step 8:

[0222] The device sends the user's personal information to the server, including the personal information entered by the user as an HTTP request.

[0223] Step 9:

[0224] The server evaluates the validity of the contract based on the personal information provided by the user, and verifies whether the contract is valid based on legal and applicable conditions, for example by issuing a warning if the contract contains terms that are inappropriate for minors.

[0225] Step 10:

[0226] The server presents the results of the analysis, risk analysis, and individual issues to the user. This information includes the main points of the contract, risk assessment, comparison results with standard clauses, and points to note.

[0227] Step 11:

[0228] The emotion engine analyzes the user's facial expressions and voice while they are typing and viewing reports, and recognizes their emotions. This analysis is performed using a camera and microphone, and emotion recognition algorithms are applied.

[0229] Step 12:

[0230] The server dynamically adjusts the information and advice it displays based on the user's emotions as recognized by the emotion engine. For example, if the user feels anxious, it provides additional explanations or support information.

[0231] Step 13:

[0232] The device sends the emotion recognition results to the server, and the analyzed emotion data is used to personalize the user's experience.

[0233] Step 14:

[0234] The server incorporates the feedback from the emotion engine and displays a final report to the user, which includes a summary, risk assessment, comparison results, cautions, and advice based on the user's emotional state.

[0235] Step 15:

[0236] The user reviews the final report on their device, optionally clicking links for more information, and makes a decision on whether to proceed with the contract based on this feedback.

[0237] Example 2

[0238] 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."

[0239] Conventional contract clause analysis systems can summarize the contents of contract clauses and analyze risks, but they cannot provide information that takes into account the user's emotional state, making it difficult to provide information in a format that is easy for users to understand.In addition, there was a need for a system that could not only obtain the text of contract clauses from URLs or files entered by users, but also compare them with standard clauses and evaluate legal and economic risks in an integrated manner.

[0240] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for a user to input a URL or file of the terms and conditions, a means for acquiring the terms and conditions text from the URL or file, a means for summarizing the acquired terms and conditions text using a generation AI, a means for comparing it with a standard terms and conditions database, a means for analyzing legal and economic risks based on the terms and conditions, a means for evaluating the validity of the contract based on the user's prior information, a means for presenting the evaluation results and individual issues to the user, and a means for sensing the user's emotional state and dynamically providing information according to that state. This not only allows the user to quickly and accurately grasp the content of the contract terms and conditions and easily understand risks and points of caution, but also allows the user to receive information according to their emotional state.

[0241] "User" refers to a user who wishes to analyze the contract terms and conditions.

[0242] "URL" refers to the Uniform Resource Locator for specifying resources on the Internet.

[0243] A "file" refers to a collection of digital information stored in a particular format.

[0244] "Terms and Conditions Text" refers to the entire text of the contract terms and conditions.

[0245] "Generative AI" refers to artificial intelligence models that automatically generate natural language text.

[0246] "Summarizing" refers to shortening the original text and extracting only the important points.

[0247] "Standard clause database" refers to a database that contains commonly used contract clauses.

[0248] "Comparing" means placing two or more objects side by side to examine their differences and similarities.

[0249] "Legal and economic risk" refers to the possibility of disadvantage or loss from a legal or economic perspective.

[0250] "User's prior information" refers to personal information of the User that may affect the Agreement.

[0251] "Validity of a contract" refers to whether a contract is legally valid.

[0252] "Evaluate" means to judge the value or validity against specific criteria or conditions.

[0253] "Individual issues" refer to shortcomings or points requiring attention that exist in specific contract terms and conditions.

[0254] "Emotional state" refers to the emotional or psychological state a user has at a particular moment.

[0255] "Dynamic provision" refers to providing information in real time in response to changes in the situation or conditions.

[0256] This invention combines a system that uses generative AI to automatically analyze contract terms and conditions and provide important information to users with a function that recognizes the user's emotional state in real time and dynamically provides information. Specific embodiments are described below.

[0257] User Input

[0258] The user inputs the URL or file of the contract terms and conditions using a terminal. The user can either enter the URL into the input field of a web browser or dedicated application, or upload a saved PDF file. This provides the system with the contract terms and conditions that the user wants to analyze.

[0259] Obtaining and analyzing terms and conditions

[0260] The server issues an HTTP request to retrieve the terms and conditions text from the URL entered by the user, and retrieves the HTML document from the specified web page. The server extracts the text from the web page using an HTML parsing library (e.g., Beautiful Soup, lxml). If a file is uploaded, the server also extracts the text using a file parsing library such as Apache Tika.

[0261] Terms and conditions summary function

[0262] The server then uses a generative AI (e.g., GPT-4) to summarize the extracted text of the terms and conditions. This summary is generated using a natural language processing model to extract key points from the terms and conditions based on important keywords and phrases. For example, it generates a summary such as, "This contract is for a five-year contract, and the penalty is 10,000 yen."

[0263] Comparison function with standard clauses

[0264] The server compares the retrieved clause text with a database of standard clauses. It uses a comparison algorithm to identify differences and similarities and highlights unusual clauses or different terms. For example, if a clause stating "30 days' notice required for cancellation procedures" differs from the standard clause, the server identifies and highlights the difference.

[0265] Legal and economic risk analysis

[0266] The server analyzes legal and economic risks based on the contract text. It uses a risk assessment algorithm to evaluate financial risks based on clauses and contracts that may conflict with laws and regulations. For example, it identifies risks such as "high penalty fees and unfavorable terms for users" and reports them.

[0267] Contract validity based on applicant's prior information

[0268] Users enter their personal information (e.g., age, occupation, and place of residence), and the server uses that information to evaluate the validity of the contract and verify legal restrictions and applicable conditions. For example, it may issue a warning if the contract contains terms that are inappropriate for minors.

[0269] Presentation of individual problems

[0270] Based on the analysis results, the server presents specific issues and items that users should pay attention to. This includes listing unfavorable terms and points to be aware of, and generating detailed explanations and recommendations. For example, it lists issues such as "penalty clauses that are stricter than standard terms" and "automatic renewal terms that are difficult to understand."

[0271] Emotion Recognition and Dynamic Information Provision

[0272] The server is equipped with an emotion engine that analyzes the user's facial expressions and voice while they are entering data and displaying reports, recognizing their emotions. For example, if the emotion recognition result indicates that the user looks anxious, the server can provide additional information such as, "If the contract details are unclear, we recommend that you consult an expert."

[0273] Displaying the results

[0274] Finally, the server displays the generated report on the user's device. The report includes a summary, risk analysis results, comparison results with standard policy terms, points to note, and advice based on the user's emotional state. The user can click on links in the report to view more detailed information.

[0275] Examples of prompt statements

[0276] Below are some specific examples of prompt sentences to input to the generative AI model.

[0277] "The URL for the terms and conditions is below. Please summarize the key points of these terms. URL: [insert URL here]"

[0278] "Please analyze the contract terms and conditions contained in this PDF file and assess the risks. Please upload the PDF file."

[0279] "Please evaluate the validity of the contract based on the following personal information: Age: 25, Occupation: Company employee, Residence: Tokyo"

[0280] "Analyze the contract terms to see if they contain any unfavorable terms. Pay particular attention to any penalty fees or cancellation procedures."

[0281] By following these steps, the system helps users quickly and accurately understand the contents of complex contract terms, enabling them to proceed with the contract after understanding the risks and points to be aware of. In addition, by utilizing an emotion engine, information is provided according to the user's emotional state, greatly improving the user experience.

[0282] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0283] Step 1: User Input

[0284] The user uses the device to input the URL or file of the contract terms and conditions. Specifically, the user enters the URL into the input field of a web browser or dedicated application, or selects a saved PDF file in the device's file browser and clicks the upload button. This input provides the system with the contract terms and conditions data that the user wants to analyze. If there is a URL entered, that becomes the user's input, and the uploaded PDF file becomes the user's input.

[0285] Step 2: Obtain the terms and conditions

[0286] The server retrieves the clause text from the URL or file entered by the user. Specifically, if a URL is entered, the server issues an HTTP request to retrieve the HTML document from the specified web page. It then uses an HTML parsing library (e.g., Beautiful Soup, lxml) to extract the text from the retrieved HTML document. If a PDF file is uploaded, it uses a file parsing library such as Apache Tika to extract the text from the file. This retrieved text is the server's output.

[0287] Step 3: Text Summarization

[0288] The server summarizes the acquired text of the terms and conditions using a generation AI (e.g., GPT-4). Specifically, the acquired text is input into the generation AI along with the prompt, "Please summarize the main points of these terms and conditions." The generation AI generates a summary based on important keywords and phrases in the text. For example, it generates a summary such as, "This contract is for a five-year contract, and the penalty is 10,000 yen." This summary is provided to the user as the server's output.

[0289] Step 4: Compare with standard clauses

[0290] The server compares the retrieved clause text with a database of standard clauses. Specifically, it retrieves the standard clauses from the database and uses a comparison algorithm to identify differences and similarities between the retrieved clause text and the standard clauses. For example, if a clause such as "30 days' notice required for cancellation procedures" differs from the standard clauses, the difference is highlighted. The comparison results are provided to the user as server output.

[0291] Step 5: Legal and economic risk analysis

[0292] The server analyzes legal and economic risks based on the contract text. Specifically, it uses a risk assessment algorithm to evaluate clauses that may conflict with laws or regulations, as well as financial risks based on the contract (e.g., high penalty fees, unfair terms). For example, it identifies the risk that "penalties are high and terms are unfavorable to the user." The results of this risk assessment are provided to the user as the server's output.

[0293] Step 6: Assess contract validity

[0294] The user enters their personal information (e.g., age, occupation, and place of residence) into the terminal. The server evaluates the validity of the contract based on the input information. Specifically, it verifies whether the contract is valid according to legal restrictions and applicable conditions. For example, if the contract contains clauses that are inappropriate for minors, a warning about this is displayed. The evaluation result is provided to the user as the server's output.

[0295] Step 7: State the specific problem

[0296] Based on the analysis and comparison results, the server presents specific problems and items that users should pay attention to. Specifically, it lists unfavorable conditions and points to be aware of, and generates detailed explanations and recommendations. For example, it presents problems such as "the penalty clause is stricter than the standard terms and conditions" and "the automatic renewal conditions are difficult to understand." This list and recommendations are provided to the user as the server's output.

[0297] Step 8: Emotion recognition and dynamic information provision

[0298] The server is equipped with an emotion engine that analyzes the user's facial expressions and voice in real time while the user is entering data and while reports are being displayed. Specifically, it uses a webcam and microphone to sense the user's emotional state. For example, based on the emotion recognition result that "the user looks anxious," the server dynamically provides corresponding information. For example, it provides information such as "If the contract details are unclear, we recommend that you consult an expert." This information is dynamically provided as output from the server.

[0299] Step 9: View the results

[0300] Finally, the server displays the generated report on the user's device. Specifically, the report includes a summary of the policy, risk analysis results, comparison results with standard policy, points to note, and advice based on the user's emotional state. The user can check the report on their device and click links to view more detailed information. This report is provided to the user as the server's final output.

[0301] (Application example 2)

[0302] 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."

[0303] In today's world, when users sign contracts at brick-and-mortar stores, it is extremely difficult to quickly and accurately understand lengthy and complex contract terms and conditions and grasp the legal and economic risks involved. It is also difficult to determine whether the contract terms are appropriate for the user's individual circumstances. Furthermore, there is a lack of support that takes into account the user's emotional state during the contract process, which often results in users feeling anxious and confused. Technology that solves these issues is needed.

[0304] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: a means for a user to input a URL or file of the contract terms and conditions; a means for retrieving the text of the terms and conditions from the URL or file; a means for summarizing the retrieved text of the terms and conditions using a generation AI; a means for comparing the text with a standard terms and conditions database; a means for analyzing legal and economic risks based on the terms and conditions; a means for evaluating the validity of the contract based on the user's prior information; a means for presenting the evaluation results and individual issues to the user; a means for recognizing the user's emotional state; and a means for dynamically adjusting information provision based on the recognized emotional state. This allows users to quickly and accurately understand the contents of the contract terms and conditions, grasp legal and economic risks, and obtain information appropriate to their individual circumstances. Furthermore, the user experience is improved by providing support tailored to the user's emotional state.

[0305] "User" means any person or entity that uses the System to analyze contract terms and conditions.

[0306] "Contract terms and conditions" are documents that describe the contents of a contract and indicate the conditions and rules at the time of contract conclusion.

[0307] "URL" is an abbreviation for Uniform Resource Locator, and is an address that indicates the location of a resource such as a web page.

[0308] A "file" is a unit for storing digital data, and often refers to a digital document of contract terms and conditions.

[0309] "Generative AI" refers to an artificial intelligence model that automatically generates and analyzes text, and is used for natural language processing, etc.

[0310] "Summarizing" means extracting the important parts from a long piece of text and reconstructing them in a concise form.

[0311] The "standard clause database" is a database that stores commonly used standard contract clauses.

[0312] To compare means to put two or more elements side by side to reveal their similarities and differences.

[0313] "Legal and economic risk" refers to the possibility of violating laws and regulations or incurring financial loss.

[0314] "Prior information" refers to personal information and background information provided by the user in advance.

[0315] "Validity of a contract" is the standard for determining whether a contract is legally and practically valid.

[0316] "Evaluation results" are the results generated by the system after analysis and comparison.

[0317] "Specific issues" are issues or considerations that are unique to a particular contract or situation.

[0318] "Emotional state" refers to the user's psychological state or feeling, including anxiety, joy, interest, etc.

[0319] "Recognizing" means that the system obtains information from the user's facial expressions, voice, etc. and understands it.

[0320] "Dynamic adjustment" means changing the information provided in real time according to the situation and conditions.

[0321] This invention is a system that enables users to quickly and accurately understand contract terms and conditions, grasp legal and economic risks, and provide information appropriate to individual circumstances when signing a contract at a physical store. Specific embodiments for carrying out the invention are described below.

[0322] 1. System Overview

[0323] The system analyzes the URL or file of the contract terms entered by the user, summarizes it using generation AI, and compares it with a database of standard contract terms. It also has the function of evaluating the validity of the contract based on the user's personal information and presenting the evaluation results and individual problems. It also recognizes the user's emotional state and dynamically adjusts the information provided based on that state.

[0324] 2. Acquisition and analysis of contract terms

[0325] The server issues an HTTP request to the URL of the contract terms entered by the user and retrieves the HTML document from the specified web page. To parse the HTML document, it uses an HTML parsing library such as BeautifulSoup. If the user has uploaded a file, it extracts the text from the file using the Apache Tika library.

[0326] 3. Summary of Terms and Conditions

[0327] The retrieved contract text is summarized using a generative AI model (e.g., GPT-4), using the following prompt:

[0328] "Please summarize the following contract, including important clauses and risk points to be aware of: {Full contract}"

[0329] 4. Comparison with standard terms and conditions

[0330] The server compares the retrieved policy text with a standard policy database and uses a comparison algorithm (e.g., a text similarity algorithm) to identify differences and similarities.

[0331] 5. Risk Analysis and Effectiveness Assessment

[0332] The server uses risk assessment algorithms to assess legal and financial risks, and evaluates the validity of the contract based on the user's previously entered personal information (e.g., age, occupation, place of residence), using criteria based on laws and regulations.

[0333] 6. Emotion Recognition and Dynamic Information Provision

[0334] When a user is using smart glasses or a head-mounted display, these devices capture the user's facial expressions and voice and use an emotion engine (e.g., the EmotionDetector library) to recognize the user's emotional state in real time. The server dynamically adjusts the information provided according to the recognized emotional state, for example, providing more detailed explanations or additional information if the user looks anxious.

[0335] 7. Displaying the results

[0336] Finally, the server displays the generated report on the user's device. The report includes a summary, risk analysis, comparison with standard terms and conditions, individual issues, and advice based on the user's emotional state. The user can check detailed information on their device, and information reflecting feedback from the emotion engine is provided.

[0337] This system allows users to complete the contract process in a physical store smoothly and safely, and also improves the user experience by providing information tailored to the user's emotional state.

[0338] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0339] Step 1:

[0340] The user inputs the URL or file of the contract terms into the terminal. The user can either enter the URL into the input field of a web browser or dedicated application, or upload a saved PDF file. This provides the contract terms to the system for analysis.

[0341] Input: URL or PDF file

[0342] Output: Agreement data to be analyzed

[0343] Step 2:

[0344] The server issues an HTTP request to retrieve the contract terms text from the URL entered by the user, retrieves the HTML document from the specified web page, and extracts the text using an HTML parsing library (e.g., BeautifulSoup).

[0345] Input: Entered URL

[0346] Output: Contract terms text extracted from HTML document

[0347] Step 3:

[0348] For user uploaded files, the server uses the Apache Tika library to extract the text from the file.

[0349] Input: Uploaded PDF file

[0350] Output: Contract terms text extracted from PDF file

[0351] Step 4:

[0352] The server summarizes the contract terms and conditions using a generative AI model (e.g., GPT-4). The generative AI model uses the following prompt: "Please summarize the following contract. Please include important clauses and risk points to be aware of: {Full contract}"

[0353] Input: Contract terms text

[0354] Output: Abridged contract terms text

[0355] Step 5:

[0356] The server compares the retrieved policy text with a standard policy database, using a comparison algorithm to identify differences and similarities.

[0357] Input: Abridged contract terms text

[0358] Output: Comparison results with standard terms and conditions

[0359] Step 6:

[0360] The server uses a risk assessment algorithm to assess the legal and financial risks involved in the contract.

[0361] Input: Abridged contract terms text

[0362] Output: Risk assessment results

[0363] Step 7:

[0364] The server evaluates the validity of the contract based on the user's prior information (e.g., age, occupation, place of residence), and determines whether it is valid using evaluation criteria based on laws and regulations.

[0365] Input: User's prior information

[0366] Output: Contract validity evaluation result

[0367] Step 8:

[0368] The server presents the evaluation results and specific issues to the user, including any adverse conditions or caveats associated with the particular contract.

[0369] Input: Risk assessment results, contract validity assessment results

[0370] Output: Evaluation results and individual problems presented to the user

[0371] Step 9:

[0372] When a user is wearing smart glasses or a head-mounted display, the device captures the user's facial expressions and voice, and the server uses an emotion engine to recognize the user's emotional state in real time.

[0373] Input: User's facial expressions and voice data

[0374] Output: Perceived emotional state of the user

[0375] Step 10:

[0376] The server dynamically adjusts the information provided depending on the user's perceived emotional state, for example by providing more detailed explanations or additional information if the user appears anxious.

[0377] Input: Perceived emotional state of the user

[0378] Output: Dynamically adjusted informational

[0379] Step 11:

[0380] Finally, the server displays the generated report on the user's terminal, which includes a summary result, risk analysis result, comparison result with standard policy terms, individual problems, and advice according to the user's emotional state.

[0381] Input: Summary results, Risk analysis results, Comparison results, User's emotional state

[0382] Output: The generated report displayed on the user's terminal

[0383] 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.

[0384] 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.

[0385] 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.

[0386] [Second embodiment]

[0387] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0388] 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.

[0389] 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).

[0390] 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.

[0391] 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.

[0392] 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).

[0393] 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.

[0394] 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.

[0395] 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.

[0396] 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.

[0397] 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.

[0398] 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."

[0399] This invention builds a system that uses generative AI to automatically analyze contract terms and conditions and provide users with important information. This system allows users to efficiently understand online contract terms and conditions and assess risks. Specific embodiments are described below.

[0400] User Input

[0401] The user can input the URL or file of the contract terms using the device, for example, by entering the URL of the mobile carrier's contract terms through a web browser or a dedicated application, or by uploading a previously saved PDF file.

[0402] Obtaining and analyzing terms and conditions

[0403] The server retrieves the text of the terms and conditions from the URL entered by the user. To do this, it issues an HTTP request to retrieve the HTML document from the specified web page and extracts the text from specific tags. Alternatively, if a file is uploaded, it extracts the text using an appropriate library. For example, Apache Tika can be used to extract text from a PDF.

[0404] Terms and conditions summary function

[0405] The server then uses a generative AI to summarize the extracted clause text. This summarization is done using a natural language processing model (e.g., GPT-4) to extract key points from the clause based on important keywords and phrases, allowing users to understand lengthy clauses concisely.

[0406] Comparison function with standard clauses

[0407] The server compares the retrieved clause text with a database of standard clauses, using a comparison algorithm to identify differences and similarities and highlight any unusual clauses or different terms. For example, if the clauses regarding penalty fees or cancellation procedures differ from the standard clauses, this will be highlighted.

[0408] Legal and economic risk analysis

[0409] The server analyzes the legal and economic risks based on the contract text. It uses a risk assessment algorithm to assess clauses that may conflict with laws and regulations, as well as financial risks under the contract. For example, if there are unreasonable penalties or unfair clauses, it notifies the user.

[0410] Contract validity based on applicant's prior information

[0411] Users enter their personal information (e.g., age, occupation, and place of residence). The server evaluates the validity of the contract based on this information. For example, it evaluates and warns if the contract contains clauses that are inappropriate for minors or if certain conditions are not met.

[0412] Presentation of individual problems

[0413] Based on the analysis and comparison results, the server will present specific issues and items that the user should pay attention to, including a detailed explanation of the contract terms and the steps the user should take, such as providing details about automatic renewal terms and additional charges.

[0414] Displaying the results

[0415] Finally, the server displays the generated report on the user's device. This report includes a summary, risk analysis results, comparison results with standard terms and conditions, and points to note. The user can use this information to understand the contract contents and decide whether to proceed with the contract. For example, the user can click on links in the report to view more detailed information.

[0416] In this way, users can quickly understand the contents of complex contract terms and conditions, and proceed with the contract after understanding the risks and points to be aware of. The system reduces the burden on users and plays a role in making contracts fairer and more transparent.

[0417] The processing flow will be explained below.

[0418] Step 1:

[0419] The user inputs the URL or file of the contract terms and conditions using the terminal. The user inputs the URL into the input field of a web browser or dedicated application, or selects the file using the upload button.

[0420] Step 2:

[0421] The device sends the entered URL or uploaded file to the server, issuing an HTTP request containing the necessary request parameters to the server.

[0422] Step 3:

[0423] The server retrieves the clause text from the URL by issuing an HTTP request to retrieve the HTML document from the specified web page, extracting the text using an HTML parsing library, and, if a file was uploaded, extracting the text from the file using an appropriate library (e.g., Apache Tika).

[0424] Step 4:

[0425] The server uses a generative AI to summarize the terms and conditions text it has acquired. A natural language processing model (e.g., GPT-4) is used to generate a summary based on important keywords and phrases in the terms and conditions.

[0426] Step 5:

[0427] The server compares the summarized clause text with a database of standard clauses. Comparison algorithms are used to identify differences and similarities. By comparing with the standard clauses, unusual clauses and different terms are highlighted.

[0428] Step 6:

[0429] The server analyzes the legal and economic risks based on the contract text, using a risk assessment algorithm to assess clauses that may violate laws and regulations, as well as economic risks (e.g., high penalties, unfair terms).

[0430] Step 7:

[0431] The user enters their personal information (e.g., age, occupation, place of residence), and the device sends this information to the server.

[0432] Step 8:

[0433] The server evaluates the validity of the contract based on the prior information provided by the user, and verifies whether the contract is valid according to legal restrictions and applicable conditions.

[0434] Step 9:

[0435] The server presents individual issues based on the analysis and comparison results, lists unfavorable conditions and points to be aware of for users contained in specific contracts, and generates detailed explanations and recommendations.

[0436] Step 10:

[0437] The terminal displays the report received from the server to the user, which includes a summary, risk analysis results, comparison results with standard clauses, and points to note, allowing the user to easily check important information.

[0438] Example 1

[0439] 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."

[0440] Contract terms and conditions are typically difficult for users to understand, requiring a great deal of time and effort. Furthermore, users face the risk of overlooking legal and economic risks or unfair clauses, making it difficult for them to accurately grasp the contents of the contract. Furthermore, it is not easy to recognize clauses that differ from standard terms and conditions, or to determine the validity of a contract based on personal information. There is a need for a system that can solve these issues and enable users to quickly and accurately understand contract terms and conditions and assess risks.

[0441] 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.

[0442] In this invention, the server includes: means for a user to input a URL or file of the contract terms and conditions; means for acquiring the text of the terms and conditions from the URL or file; means for extracting the acquired text of the terms and conditions using data analysis means; means for summarizing the extracted text of the terms and conditions using a generative AI model; means for comparing the text with a standard database of terms and conditions; means for evaluating the legal and economic risks based on the terms and conditions; means for evaluating the validity of the contract based on the user's personal information; means for presenting the evaluation results and individual issues to the user; and means for displaying the evaluation results on the user's terminal using a display device. This allows the user to quickly understand the terms and conditions, grasp the legal and economic risks and points to note, and make an appropriate decision about the contract.

[0443] "User" means the entity that inputs the URL or file of the terms and conditions and receives information based thereon.

[0444] A "URL" is a Uniform Resource Locator that points to resources on the Internet and indicates the address of a web page.

[0445] A "file" is a unit for storing data, and in the present invention, it mainly refers to contract terms and conditions in PDF format.

[0446] "Terms and conditions text" refers to the text portion of a document that describes the terms and conditions of a contract.

[0447] "Data analysis means" refers to means for extracting useful information from input data.

[0448] A "generative AI model" is an artificial intelligence model that learns large amounts of data to generate language, such as GPT-4.

[0449] The "standard clause database" is a database that stores commonly used standard contract clauses.

[0450] "Legal and economic risks" refers to the legal and economic risks based on the terms and content of the contract.

[0451] "Personal information" refers to information that identifies an individual, such as a user's age, occupation, or place of residence.

[0452] "Evaluation results" refer to conclusions or judgments drawn based on analysis or comparison.

[0453] "Individual issues" refer to points of caution and risk factors in specific contract terms and conditions.

[0454] A "display device" is a device used to display information to users, and primarily refers to the screen of a computer or smartphone.

[0455] This invention builds a system that uses generative AI models to automatically analyze contract terms and conditions and provide users with important information. This system allows users to efficiently understand online contract terms and conditions and assess risks. The system's programming primarily relies on data analysis, natural language processing, and comparison algorithms.

[0456] First, the user uses the device to input the URL or file of the contract terms. This can be done through a web browser input form or a dedicated application. For example, the user can input the URL of the mobile carrier's contract terms or upload a saved PDF file.

[0457] The server issues an HTTP request to the URL entered by the user to retrieve the HTML document from the specified web page, and if a file was uploaded, extracts the text from the PDF using an appropriate library (e.g., Apache Tika). This text extraction is performed using an HTML parser.

[0458] Next, the server summarizes the extracted clause text using a generative AI model (e.g., GPT-4). The server inputs a prompt such as "Please summarize this text in 100 characters or less" to the generative AI model and receives the generated summary data. This allows the user to understand the lengthy clause text concisely.

[0459] The server then compares the retrieved clause text with a database of standard clauses, using a comparison algorithm to identify differences and similarities and highlight any unusual clauses or different terms. For example, if the clauses regarding penalty fees or cancellation procedures differ from the standard clauses, the differences will be highlighted.

[0460] The server then assesses the legal and financial risks of the contract text. Using a risk assessment algorithm, it analyzes clauses that may violate laws and regulations, as well as the financial risks associated with the contract. For example, it warns users of any unreasonable penalty charges or unfair clauses.

[0461] Users enter their personal information (e.g., age, occupation, and place of residence), and the server evaluates the validity of the contract based on this information. For example, it evaluates and warns if the contract contains clauses that are inappropriate for minors or if certain conditions are not met.

[0462] Based on the analysis and comparison results, the server will present specific issues that the user should pay attention to, including a detailed explanation of the contract terms and the steps the user should take, such as providing details about automatic renewal terms and additional charges.

[0463] Finally, the server displays the generated report on the user's device. This report includes a summary, risk analysis results, comparison results with standard terms and conditions, and points to note. The user can use this information to understand the contract contents and decide whether to proceed with the contract. For example, they can click on links in the report to view more detailed information.

[0464] Prompt Sentence Examples

[0465] Terms and conditions URL: https: / / example.com / contract-terms

[0466] or

[0467] Upload the PDF file of the terms and conditions: [Select PDF file]

[0468] User information: Age=25, Occupation=Engineer, Residence=Tokyo

[0469] Using this system, users can quickly and accurately understand the contents of contract terms and conditions and appropriately assess risks.

[0470] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0471] Step 1:

[0472] User Input

[0473] The user uses a device to enter the URL or file of the contract terms. For example, they can enter the URL of the contract terms (https: / / example.com / contract-terms) in the input field of a web browser, or they can launch a dedicated application, click the "Select File" button, and select a saved PDF file. The URL or file entered by the user becomes the input data. The output is the entered URL or file.

[0474] Step 2:

[0475] Obtaining the terms and conditions

[0476] The server issues an HTTP request to the URL entered by the user to retrieve the HTML document from the specified web page. If a file is uploaded, it also receives the file contents. Specifically, the server uses an HTTP GET request to download the HTML document. If a PDF file is uploaded, it receives the file. The input is the URL or file obtained from the user, and the output is the retrieved HTML document or PDF file.

[0477] Step 3:

[0478] Text Extraction

[0479] The server extracts text from an HTML document or PDF file. In the case of HTML, it parses specific tags to obtain the text, and in the case of PDF, it uses the Apache Tika library to extract the text. The server uses an HTML parser to extract the clause text from specific tags in the HTML document, and in the case of PDF files, it calls Apache Tika to extract the text. The input is an HTML document or a PDF file, and the output is the extracted clause text.

[0480] Step 4:

[0481] Generate summary of terms and conditions

[0482] The server inputs the extracted clause text into a generative AI model (e.g., GPT-4) to generate a summary. The server inputs a prompt ("Please summarize this text in 100 characters or less") to the generative AI model and receives the summarized text. Specifically, the server generates a prompt for GPT-4 and obtains the summary data through an API. The input is the extracted clause text, and the output is the summarized text.

[0483] Step 5:

[0484] Comparison with standard terms and conditions

[0485] The server compares the retrieved clause text with a standard clause database. It uses a comparison algorithm to identify differences and similarities and highlight unusual clauses or different terms. The server queries the standard clause database and compares it sentence by sentence with the retrieved clause text. The input is the clause text and the standard clause database, and the output is the comparison result data.

[0486] Step 6:

[0487] Legal and economic risk analysis

[0488] The server uses a risk assessment algorithm to analyze the clauses in the contract and identify legal and economic risks. If unfair clauses or unfair penalties exist, it generates data to warn the user. The input is the contract text, and the output is the risk assessment results.

[0489] Step 7:

[0490] Contract validity assessment based on personal information

[0491] The user enters their personal information (e.g., age, occupation, place of residence), and the server evaluates the validity of the contract based on this information. The server checks whether the contract terms are in compliance with the user's personal information and issues a warning. The input is the user's personal information and the contract text, and the output is the result of the contract validity evaluation.

[0492] Step 8:

[0493] Presentation of individual problems

[0494] Based on the analysis and comparison results, the server presents specific issues and items that the user should pay attention to. It provides detailed explanations and measures that the user should take. For example, it provides notes on the automatic renewal conditions and details of additional fees. The input is the comparison results and risk assessment results, and the output is data on issues and measures.

[0495] Step 9:

[0496] Displaying the results

[0497] The server displays the generated report on the user's device. This report includes a summary, risk analysis results, comparison results with standard clauses, and points to note. The user can use this information to understand the contract contents and decide whether to proceed with the contract. For example, they can click on a link in the report to view more detailed information. The input is various data in the report, and the output is the report displayed on the user's device.

[0498] (Application example 1)

[0499] 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."

[0500] Users of electronic payment services have difficulty quickly understanding the complex content of contract terms and conditions and assessing legal and economic risks. They also lack the means to identify unusual clauses compared to standard contract terms and obtain information to avoid risks. This increases the risk of entering into unfavorable contracts.

[0501] 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.

[0502] In this invention, the server includes means for a user to input a link or file of the contract terms and conditions, means for retrieving the text of the terms and conditions from the link or file, means for summarizing the retrieved text of the terms and conditions using a generation AI, means for comparing it with a standard database of terms and conditions, means for analyzing legal and economic risks based on the terms and conditions, means for evaluating the validity of the contract based on the user's prior information, means for presenting the evaluation results and individual issues to the user, and means for displaying the analysis results of the contract terms and conditions on the user's terminal. This allows the user to quickly and efficiently understand the contents of the contract terms and conditions, evaluate the risks, and make a comprehensive judgment to proceed with the appropriate contract.

[0503] "User" means a consumer who uses electronic payment services.

[0504] "Terms and conditions" are documents in which an electronic payment service provider lists the terms and conditions of use.

[0505] A "link" is a URL that accesses a specific web page.

[0506] "File" refers to document data stored in electronic format.

[0507] "Terms and conditions text" refers to the content of the contract terms and conditions expressed in text form.

[0508] "Generative AI" is an artificial intelligence technology that uses natural language processing to generate and analyze text.

[0509] A "summary" is a short summary of the most important parts of the original text.

[0510] A "standard clause database" is a collection of commonly used contract clauses managed as a database.

[0511] A "comparison algorithm" is a computational method that compares different texts to identify differences and similarities.

[0512] "Legal and Economic Risks" means legal issues and economic burdens that the User may incur under the Agreement.

[0513] "Prior information" refers to personal information or circumstances provided by the user.

[0514] "Validity" refers to whether a contract is legally established and effective.

[0515] "Evaluation results" refers to information provided by the system as a result of analysis.

[0516] "Individual issues" refer to specific points of caution or risk factors in the contract terms and conditions.

[0517] "Terminal" means a device (e.g., smartphone, tablet) used by a User to enter and display information.

[0518] "Displaying" refers to the act of visually providing analysis results and information on the user's device.

[0519] To realize this invention, the interaction between the user, the server, and the terminal used by the user is important.

[0520] First, the user inputs a link or an existing file to access the contract terms of the electronic payment service into the terminal. For example, the user can input the link to the contract terms using a web browser or a dedicated application, or upload a saved PDF file.

[0521] The server then issues an HTTP request from the provided link to retrieve the HTML document from the specified web page, or, if a file was uploaded, extracts the text using a text extraction library such as Apache Tika.

[0522] The retrieved contract text is summarized on the server using a generative AI model (e.g., GPT-4). This summarization process uses natural language processing techniques to extract key points from the contract based on important keywords and phrases, allowing users to easily understand lengthy contracts.

[0523] The server then compares the extracted clause text with a database of standard clauses using a comparison algorithm such as a Python-based Diff library, which identifies any unusual clauses or conditions that differ from the standard clauses and highlights them for the user.

[0524] In addition, the server applies a risk assessment algorithm to analyze legal and financial risks, which assesses the legal and financial consequences that users may incur. For example, any unreasonable penalties or unfair terms will be clearly indicated to the user.

[0525] Finally, the server generates a detailed report containing the analysis and comparison results, which is displayed on the user's device. This report includes a summary, risk analysis, comparison results with standard terms and conditions, and points to note. Based on this, the user can understand the contract contents and make a comprehensive decision on whether to proceed with the contract.

[0526] As a concrete example, consider a case where a user tries to analyze the terms and conditions at the URL "https: / / example.com / terms-and-conditions.pdf." When the user enters the URL into the app, the server downloads the PDF file and extracts the text. It then uses a generative AI model to create a summary and compare it with standard terms and conditions to identify any discrepancies. It also performs a risk analysis and warns the user if any unfair clauses are present. Finally, all analysis results are notified to the user, allowing them to quickly understand the contents of the contract terms and take appropriate action.

[0527] An example of a prompt is shown below.

[0528] Analyze the contract terms and conditions found at the URL "https: / / example.com / terms-and-conditions.pdf" and create a summary based on key keywords and phrases. Also compare it with standard terms and conditions, highlight any differences, and analyze the legal and financial risks.

[0529] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0530] Step 1:

[0531] The user inputs the link or file of the contract terms into the device. Specifically, the user opens a web browser or a dedicated application and inputs the URL to the contract terms or uploads an existing PDF file. The input for this step is the link or file, and the output is the information entered by the user.

[0532] Step 2:

[0533] The server retrieves the terms and conditions text based on the link or file received from the user. In the case of a link, the server issues an HTTP request to retrieve the HTML document from the specified web page. In the case of a file, the server uses a text extraction library such as Apache Tika to extract the text. The input for this step is the link or file provided by the user, and the output is the retrieved terms and conditions text.

[0534] Step 3:

[0535] The server summarizes the retrieved clause text using a generative AI model. The generative AI model (e.g., GPT-4) uses natural language processing techniques to extract key points from the clause based on important keywords and phrases. The input for this step is the retrieved clause text, and the output is a summarized clause.

[0536] Step 4:

[0537] The server compares the summarized clause text with a database of standard clauses. A comparison algorithm (e.g., a Python-based Diff library) is used to compare the extracted text with the contents of the standard clause database to identify differences and similarities. The input to this step is the summarized clause text, and the output is the identification of differences and similarities.

[0538] Step 5:

[0539] The server applies a risk assessment algorithm to analyze the legal and economic risks based on the retrieved contract text. Any unreasonable penalties or unfair clauses are identified and notified to the user. The input of this step is the retrieved contract text, and the output is the result of the risk analysis.

[0540] Step 6:

[0541] The server evaluates the validity of the contract based on the user's personal information. The user inputs personal information from the terminal (e.g., age, occupation), and the server evaluates whether the contract terms are legally appropriate based on this information. The input of this step is the user's prior information, and the output is the evaluation result of the validity of the contract.

[0542] Step 7:

[0543] The server presents the analysis results, comparison results, risk analysis, and individual issues to the user. A detailed report containing this information is generated and displayed on the user's terminal. The input to this step is each result of the analysis, and the output is a detailed report presented to the user.

[0544] Step 8:

[0545] The user checks the report on the terminal and understands the contract contents. Based on the report generated by the server, the user makes an overall decision on whether to proceed with the contract. The input of this step is the presented report, and the output is the user's decision and action.

[0546] 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.

[0547] This invention combines an emotion engine with a system that uses generative AI to automatically analyze contract terms and conditions and provide important information to users, recognizing the user's emotional state in real time and dynamically providing information. Specific embodiments are described below.

[0548] User Input

[0549] The user inputs the URL or file of the contract terms and conditions using a terminal. The user can either enter the URL into the input field of a web browser or dedicated application, or upload a saved PDF file. This provides the system with the contract terms and conditions that the user wants to analyze.

[0550] Obtaining and analyzing terms and conditions

[0551] The server issues an HTTP request to retrieve the clause text from the URL entered by the user, retrieves the HTML document from the specified web page, extracts the text using an HTML parsing library, and, if a file was uploaded, extracts the text from the file using an appropriate library (e.g., Apache Tika).

[0552] Terms and conditions summary function

[0553] The server then uses a generative AI to summarize the extracted clause text. This summary is done using a natural language processing model (e.g., GPT-4) to extract key points from the clause based on important keywords and phrases, allowing users to understand lengthy clauses concisely.

[0554] Comparison function with standard clauses

[0555] The server compares the retrieved clause text with a database of standard clauses, using a comparison algorithm to identify differences and similarities and highlight any unusual clauses or different terms. For example, if the clauses regarding penalty fees or cancellation procedures differ from the standard clauses, this will be highlighted.

[0556] Legal and economic risk analysis

[0557] The server analyzes the legal and economic risks based on the contract text. It uses a risk assessment algorithm to evaluate clauses that may conflict with laws and regulations, as well as financial risks under the contract (e.g., high penalty fees, unfair terms). This allows users to understand the potential risks contained in the contract.

[0558] Contract validity based on applicant's prior information

[0559] The user enters their personal information (e.g., age, occupation, place of residence). The server uses this information to assess the validity of the contract. By verifying whether the contract is valid according to legal restrictions and applicable conditions, the server can, for example, warn if the contract contains terms that are inappropriate for minors.

[0560] Presentation of individual problems

[0561] Based on the analysis and comparison results, the server presents specific issues and items that users should pay attention to. This includes listing unfavorable terms and conditions contained in specific contracts and generating detailed explanations and recommendations. For example, it provides notes on automatic renewal terms and details of additional fees.

[0562] Emotion Recognition and Dynamic Information Provision

[0563] The server is equipped with an emotion engine that analyzes the user's facial expressions and voice while they are typing and displaying reports, recognizing their emotions. For example, if the user looks anxious, the server will provide information that corresponds to that emotion. This makes it possible to dynamically adjust information while taking into account the user's emotional state.

[0564] Displaying the results

[0565] Finally, the server displays the generated report on the user's device. The report includes a summary, risk analysis results, comparison results with standard policy terms, points to note, and advice based on the user's emotional state. For example, users can click on links within the report to view more detailed information, which reflects feedback from the emotion engine.

[0566] In this way, users can quickly understand the contents of complex terms and conditions, and proceed with the contract after understanding the risks and points to note. The combination of the emotion engine makes it possible to provide appropriate information according to the user's emotional state, greatly improving the user experience.

[0567] The processing flow will be explained below.

[0568] Step 1:

[0569] The user inputs the URL or file of the contract terms and conditions using the terminal. The user either inputs the URL into the input field of a web browser or dedicated application, or selects the appropriate file using the upload button.

[0570] Step 2:

[0571] The terminal sends the URL entered by the user or the uploaded file to the server. The information sent to the server as an HTTP request includes the user's input data.

[0572] Step 3:

[0573] The server issues an HTTP request to retrieve the clause text from the URL, retrieves the HTML document for the specified web page, extracts the text from the HTML document using an HTML parsing library, or, if a file is uploaded, extracts the text using an appropriate library such as Apache Tika.

[0574] Step 4:

[0575] The server uses generative AI to summarize the terms and conditions text it has acquired. It uses a natural language processing model (e.g., GPT-4) to summarize the text based on important keywords and phrases, allowing the main points to be displayed concisely.

[0576] Step 5:

[0577] The server compares the summarized clause text with a database of standard clauses. Comparison algorithms are used to identify differences and similarities when compared to standard clauses. Different clauses and distinctive terms are highlighted.

[0578] Step 6:

[0579] The server analyzes the legal and economic risks of the terms and conditions, using a risk assessment algorithm to assess clauses that may violate laws and regulations, as well as economic risks (e.g., high penalties, unfair terms).

[0580] Step 7:

[0581] The user enters their personal information (e.g. age, occupation, place of residence, etc.) This information is used to evaluate the validity of legal and contractual terms.

[0582] Step 8:

[0583] The device sends the user's personal information to the server, including the personal information entered by the user as an HTTP request.

[0584] Step 9:

[0585] The server evaluates the validity of the contract based on the personal information provided by the user, and verifies whether the contract is valid based on legal and applicable conditions, for example by issuing a warning if the contract contains terms that are inappropriate for minors.

[0586] Step 10:

[0587] The server presents the results of the analysis, risk analysis, and individual issues to the user. This information includes the main points of the contract, risk assessment, comparison results with standard clauses, and points to note.

[0588] Step 11:

[0589] The emotion engine analyzes the user's facial expressions and voice while they are typing and viewing reports, and recognizes their emotions. This analysis is performed using a camera and microphone, and emotion recognition algorithms are applied.

[0590] Step 12:

[0591] The server dynamically adjusts the information and advice it displays based on the user's emotions as recognized by the emotion engine. For example, if the user feels anxious, it provides additional explanations or support information.

[0592] Step 13:

[0593] The device sends the emotion recognition results to the server, and the analyzed emotion data is used to personalize the user's experience.

[0594] Step 14:

[0595] The server incorporates the feedback from the emotion engine and displays a final report to the user, which includes a summary, risk assessment, comparison results, cautions, and advice based on the user's emotional state.

[0596] Step 15:

[0597] The user reviews the final report on their device, optionally clicking links for more information, and makes a decision on whether to proceed with the contract based on this feedback.

[0598] Example 2

[0599] 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."

[0600] Conventional contract clause analysis systems can summarize the contents of contract clauses and analyze risks, but they cannot provide information that takes into account the user's emotional state, making it difficult to provide information in a format that is easy for users to understand.In addition, there was a need for a system that could not only obtain the text of contract clauses from URLs or files entered by users, but also compare them with standard clauses and evaluate legal and economic risks in an integrated manner.

[0601] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for a user to input a URL or file of the terms and conditions, a means for acquiring the terms and conditions text from the URL or file, a means for summarizing the acquired terms and conditions text using a generation AI, a means for comparing it with a standard terms and conditions database, a means for analyzing legal and economic risks based on the terms and conditions, a means for evaluating the validity of the contract based on the user's prior information, a means for presenting the evaluation results and individual issues to the user, and a means for sensing the user's emotional state and dynamically providing information according to that state. This not only allows the user to quickly and accurately grasp the content of the contract terms and conditions and easily understand risks and points of caution, but also allows the user to receive information according to their emotional state.

[0602] "User" refers to a user who wishes to analyze the contract terms and conditions.

[0603] "URL" refers to the Uniform Resource Locator for specifying resources on the Internet.

[0604] A "file" refers to a collection of digital information stored in a particular format.

[0605] "Terms and Conditions Text" refers to the entire text of the contract terms and conditions.

[0606] "Generative AI" refers to artificial intelligence models that automatically generate natural language text.

[0607] "Summarizing" refers to shortening the original text and extracting only the important points.

[0608] "Standard clause database" refers to a database that contains commonly used contract clauses.

[0609] "Comparing" means placing two or more objects side by side to examine their differences and similarities.

[0610] "Legal and economic risk" refers to the possibility of disadvantage or loss from a legal or economic perspective.

[0611] "User's prior information" refers to personal information of the User that may affect the Agreement.

[0612] "Validity of a contract" refers to whether a contract is legally valid.

[0613] "Evaluate" means to judge the value or validity against specific criteria or conditions.

[0614] "Individual issues" refer to shortcomings or points requiring attention that exist in specific contract terms and conditions.

[0615] "Emotional state" refers to the emotional or psychological state a user has at a particular moment.

[0616] "Dynamic provision" refers to providing information in real time in response to changes in the situation or conditions.

[0617] This invention combines a system that uses generative AI to automatically analyze contract terms and conditions and provide important information to users with a function that recognizes the user's emotional state in real time and dynamically provides information. Specific embodiments are described below.

[0618] User Input

[0619] The user inputs the URL or file of the contract terms and conditions using a terminal. The user can either enter the URL into the input field of a web browser or dedicated application, or upload a saved PDF file. This provides the system with the contract terms and conditions that the user wants to analyze.

[0620] Obtaining and analyzing terms and conditions

[0621] The server issues an HTTP request to retrieve the terms and conditions text from the URL entered by the user, and retrieves the HTML document from the specified web page. The server extracts the text from the web page using an HTML parsing library (e.g., Beautiful Soup, lxml). If a file is uploaded, the server also extracts the text using a file parsing library such as Apache Tika.

[0622] Terms and conditions summary function

[0623] The server then uses a generative AI (e.g., GPT-4) to summarize the extracted text of the terms and conditions. This summary is generated using a natural language processing model to extract key points from the terms and conditions based on important keywords and phrases. For example, it generates a summary such as, "This contract is for a five-year contract, and the penalty is 10,000 yen."

[0624] Comparison function with standard clauses

[0625] The server compares the retrieved clause text with a database of standard clauses. It uses a comparison algorithm to identify differences and similarities and highlights unusual clauses or different terms. For example, if a clause stating "30 days' notice required for cancellation procedures" differs from the standard clause, the server identifies and highlights the difference.

[0626] Legal and economic risk analysis

[0627] The server analyzes legal and economic risks based on the contract text. It uses a risk assessment algorithm to evaluate financial risks based on clauses and contracts that may conflict with laws and regulations. For example, it identifies risks such as "high penalty fees and unfavorable terms for users" and reports them.

[0628] Contract validity based on applicant's prior information

[0629] Users enter their personal information (e.g., age, occupation, and place of residence), and the server uses that information to evaluate the validity of the contract and verify legal restrictions and applicable conditions. For example, it may issue a warning if the contract contains terms that are inappropriate for minors.

[0630] Presentation of individual problems

[0631] Based on the analysis results, the server presents specific issues and items that users should pay attention to. This includes listing unfavorable terms and points to be aware of, and generating detailed explanations and recommendations. For example, it lists issues such as "penalty clauses that are stricter than standard terms" and "automatic renewal terms that are difficult to understand."

[0632] Emotion Recognition and Dynamic Information Provision

[0633] The server is equipped with an emotion engine that analyzes the user's facial expressions and voice while they are entering data and displaying reports, recognizing their emotions. For example, if the emotion recognition result indicates that the user looks anxious, the server can provide additional information such as, "If the contract details are unclear, we recommend that you consult an expert."

[0634] Displaying the results

[0635] Finally, the server displays the generated report on the user's device. The report includes a summary, risk analysis results, comparison results with standard policy terms, points to note, and advice based on the user's emotional state. The user can click on links in the report to view more detailed information.

[0636] Examples of prompt statements

[0637] Below are some specific examples of prompt sentences to input to the generative AI model.

[0638] "The URL for the terms and conditions is below. Please summarize the key points of these terms. URL: [insert URL here]"

[0639] "Please analyze the contract terms and conditions contained in this PDF file and assess the risks. Please upload the PDF file."

[0640] "Please evaluate the validity of the contract based on the following personal information: Age: 25, Occupation: Company employee, Residence: Tokyo"

[0641] "Analyze the contract terms to see if they contain any unfavorable terms. Pay particular attention to any penalty fees or cancellation procedures."

[0642] By following these steps, the system helps users quickly and accurately understand the contents of complex contract terms, enabling them to proceed with the contract after understanding the risks and points to be aware of. In addition, by utilizing an emotion engine, information is provided according to the user's emotional state, greatly improving the user experience.

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

[0644] Step 1: User Input

[0645] The user uses the device to input the URL or file of the contract terms and conditions. Specifically, the user enters the URL into the input field of a web browser or dedicated application, or selects a saved PDF file in the device's file browser and clicks the upload button. This input provides the system with the contract terms and conditions data that the user wants to analyze. If there is a URL entered, that becomes the user's input, and the uploaded PDF file becomes the user's input.

[0646] Step 2: Obtain the terms and conditions

[0647] The server retrieves the clause text from the URL or file entered by the user. Specifically, if a URL is entered, the server issues an HTTP request to retrieve the HTML document from the specified web page. It then uses an HTML parsing library (e.g., Beautiful Soup, lxml) to extract the text from the retrieved HTML document. If a PDF file is uploaded, it uses a file parsing library such as Apache Tika to extract the text from the file. This retrieved text is the server's output.

[0648] Step 3: Text Summarization

[0649] The server summarizes the acquired text of the terms and conditions using a generation AI (e.g., GPT-4). Specifically, the acquired text is input into the generation AI along with the prompt, "Please summarize the main points of these terms and conditions." The generation AI generates a summary based on important keywords and phrases in the text. For example, it generates a summary such as, "This contract is for a five-year contract, and the penalty is 10,000 yen." This summary is provided to the user as the server's output.

[0650] Step 4: Compare with standard clauses

[0651] The server compares the retrieved clause text with a database of standard clauses. Specifically, it retrieves the standard clauses from the database and uses a comparison algorithm to identify differences and similarities between the retrieved clause text and the standard clauses. For example, if a clause such as "30 days' notice required for cancellation procedures" differs from the standard clauses, the difference is highlighted. The comparison results are provided to the user as server output.

[0652] Step 5: Legal and economic risk analysis

[0653] The server analyzes legal and economic risks based on the contract text. Specifically, it uses a risk assessment algorithm to evaluate clauses that may conflict with laws or regulations, as well as financial risks based on the contract (e.g., high penalty fees, unfair terms). For example, it identifies the risk that "penalties are high and terms are unfavorable to the user." The results of this risk assessment are provided to the user as the server's output.

[0654] Step 6: Assess contract validity

[0655] The user enters their personal information (e.g., age, occupation, and place of residence) into the terminal. The server evaluates the validity of the contract based on the input information. Specifically, it verifies whether the contract is valid according to legal restrictions and applicable conditions. For example, if the contract contains clauses that are inappropriate for minors, a warning about this is displayed. The evaluation result is provided to the user as the server's output.

[0656] Step 7: State the specific problem

[0657] Based on the analysis and comparison results, the server presents specific problems and items that users should pay attention to. Specifically, it lists unfavorable conditions and points to be aware of, and generates detailed explanations and recommendations. For example, it presents problems such as "the penalty clause is stricter than the standard terms and conditions" and "the automatic renewal conditions are difficult to understand." This list and recommendations are provided to the user as the server's output.

[0658] Step 8: Emotion recognition and dynamic information provision

[0659] The server is equipped with an emotion engine that analyzes the user's facial expressions and voice in real time while the user is entering data and while reports are being displayed. Specifically, it uses a webcam and microphone to sense the user's emotional state. For example, based on the emotion recognition result that "the user looks anxious," the server dynamically provides corresponding information. For example, it provides information such as "If the contract details are unclear, we recommend that you consult an expert." This information is dynamically provided as output from the server.

[0660] Step 9: View the results

[0661] Finally, the server displays the generated report on the user's device. Specifically, the report includes a summary of the policy, risk analysis results, comparison results with standard policy, points to note, and advice based on the user's emotional state. The user can check the report on their device and click links to view more detailed information. This report is provided to the user as the server's final output.

[0662] (Application example 2)

[0663] 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."

[0664] In today's world, when users sign contracts at brick-and-mortar stores, it is extremely difficult to quickly and accurately understand lengthy and complex contract terms and conditions and grasp the legal and economic risks involved. It is also difficult to determine whether the contract terms are appropriate for the user's individual circumstances. Furthermore, there is a lack of support that takes into account the user's emotional state during the contract process, which often results in users feeling anxious and confused. Technology that solves these issues is needed.

[0665] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: a means for a user to input a URL or file of the contract terms and conditions; a means for retrieving the text of the terms and conditions from the URL or file; a means for summarizing the retrieved text of the terms and conditions using a generation AI; a means for comparing the text with a standard terms and conditions database; a means for analyzing legal and economic risks based on the terms and conditions; a means for evaluating the validity of the contract based on the user's prior information; a means for presenting the evaluation results and individual issues to the user; a means for recognizing the user's emotional state; and a means for dynamically adjusting information provision based on the recognized emotional state. This allows users to quickly and accurately understand the contents of the contract terms and conditions, grasp legal and economic risks, and obtain information appropriate to their individual circumstances. Furthermore, the user experience is improved by providing support tailored to the user's emotional state.

[0666] "User" means any person or entity that uses the System to analyze contract terms and conditions.

[0667] "Contract terms and conditions" are documents that describe the contents of a contract and indicate the conditions and rules at the time of contract conclusion.

[0668] "URL" is an abbreviation for Uniform Resource Locator, and is an address that indicates the location of a resource such as a web page.

[0669] A "file" is a unit for storing digital data, and often refers to a digital document of contract terms and conditions.

[0670] "Generative AI" refers to an artificial intelligence model that automatically generates and analyzes text, and is used for natural language processing, etc.

[0671] "Summarizing" means extracting the important parts from a long piece of text and reconstructing them in a concise form.

[0672] The "standard clause database" is a database that stores commonly used standard contract clauses.

[0673] To compare means to put two or more elements side by side to reveal their similarities and differences.

[0674] "Legal and economic risk" refers to the possibility of violating laws and regulations or incurring financial loss.

[0675] "Prior information" refers to personal information and background information provided by the user in advance.

[0676] "Validity of a contract" is the standard for determining whether a contract is legally and practically valid.

[0677] "Evaluation results" are the results generated by the system after analysis and comparison.

[0678] "Specific issues" are issues or considerations that are unique to a particular contract or situation.

[0679] "Emotional state" refers to the user's psychological state or feeling, including anxiety, joy, interest, etc.

[0680] "Recognizing" means that the system obtains information from the user's facial expressions, voice, etc. and understands it.

[0681] "Dynamic adjustment" means changing the information provided in real time according to the situation and conditions.

[0682] This invention is a system that enables users to quickly and accurately understand contract terms and conditions, grasp legal and economic risks, and provide information appropriate to individual circumstances when signing a contract at a physical store. Specific embodiments for carrying out the invention are described below.

[0683] 1. System Overview

[0684] The system analyzes the URL or file of the contract terms entered by the user, summarizes it using generation AI, and compares it with a database of standard contract terms. It also has the function of evaluating the validity of the contract based on the user's personal information and presenting the evaluation results and individual problems. It also recognizes the user's emotional state and dynamically adjusts the information provided based on that state.

[0685] 2. Acquisition and analysis of contract terms

[0686] The server issues an HTTP request to the URL of the contract terms entered by the user and retrieves the HTML document from the specified web page. To parse the HTML document, it uses an HTML parsing library such as BeautifulSoup. If the user has uploaded a file, it extracts the text from the file using the Apache Tika library.

[0687] 3. Summary of Terms and Conditions

[0688] The retrieved contract text is summarized using a generative AI model (e.g., GPT-4), using the following prompt:

[0689] "Please summarize the following contract, including important clauses and risk points to be aware of: {Full contract}"

[0690] 4. Comparison with standard terms and conditions

[0691] The server compares the retrieved policy text with a standard policy database and uses a comparison algorithm (e.g., a text similarity algorithm) to identify differences and similarities.

[0692] 5. Risk Analysis and Effectiveness Assessment

[0693] The server uses risk assessment algorithms to assess legal and financial risks, and evaluates the validity of the contract based on the user's previously entered personal information (e.g., age, occupation, place of residence), using criteria based on laws and regulations.

[0694] 6. Emotion Recognition and Dynamic Information Provision

[0695] When a user is using smart glasses or a head-mounted display, these devices capture the user's facial expressions and voice and use an emotion engine (e.g., the EmotionDetector library) to recognize the user's emotional state in real time. The server dynamically adjusts the information provided according to the recognized emotional state, for example, providing more detailed explanations or additional information if the user looks anxious.

[0696] 7. Displaying the results

[0697] Finally, the server displays the generated report on the user's device. The report includes a summary, risk analysis, comparison with standard terms and conditions, individual issues, and advice based on the user's emotional state. The user can check detailed information on their device, and information reflecting feedback from the emotion engine is provided.

[0698] This system allows users to complete the contract process in a physical store smoothly and safely, and also improves the user experience by providing information tailored to the user's emotional state.

[0699] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0700] Step 1:

[0701] The user inputs the URL or file of the contract terms into the terminal. The user can either enter the URL into the input field of a web browser or dedicated application, or upload a saved PDF file. This provides the contract terms to the system for analysis.

[0702] Input: URL or PDF file

[0703] Output: Agreement data to be analyzed

[0704] Step 2:

[0705] The server issues an HTTP request to retrieve the contract terms text from the URL entered by the user, retrieves the HTML document from the specified web page, and extracts the text using an HTML parsing library (e.g., BeautifulSoup).

[0706] Input: Entered URL

[0707] Output: Contract terms text extracted from HTML document

[0708] Step 3:

[0709] For user uploaded files, the server uses the Apache Tika library to extract the text from the file.

[0710] Input: Uploaded PDF file

[0711] Output: Contract terms text extracted from PDF file

[0712] Step 4:

[0713] The server summarizes the contract terms and conditions using a generative AI model (e.g., GPT-4). The generative AI model uses the following prompt: "Please summarize the following contract. Please include important clauses and risk points to be aware of: {Full contract}"

[0714] Input: Contract terms text

[0715] Output: Abridged contract terms text

[0716] Step 5:

[0717] The server compares the retrieved policy text with a standard policy database, using a comparison algorithm to identify differences and similarities.

[0718] Input: Abridged contract terms text

[0719] Output: Comparison results with standard terms and conditions

[0720] Step 6:

[0721] The server uses a risk assessment algorithm to assess the legal and financial risks involved in the contract.

[0722] Input: Abridged contract terms text

[0723] Output: Risk assessment results

[0724] Step 7:

[0725] The server evaluates the validity of the contract based on the user's prior information (e.g., age, occupation, place of residence), and determines whether it is valid using evaluation criteria based on laws and regulations.

[0726] Input: User's prior information

[0727] Output: Contract validity evaluation result

[0728] Step 8:

[0729] The server presents the evaluation results and specific issues to the user, including any adverse conditions or caveats associated with the particular contract.

[0730] Input: Risk assessment results, contract validity assessment results

[0731] Output: Evaluation results and individual problems presented to the user

[0732] Step 9:

[0733] When a user is wearing smart glasses or a head-mounted display, the device captures the user's facial expressions and voice, and the server uses an emotion engine to recognize the user's emotional state in real time.

[0734] Input: User's facial expressions and voice data

[0735] Output: Perceived emotional state of the user

[0736] Step 10:

[0737] The server dynamically adjusts the information provided depending on the user's perceived emotional state, for example by providing more detailed explanations or additional information if the user appears anxious.

[0738] Input: Perceived emotional state of the user

[0739] Output: Dynamically adjusted informational

[0740] Step 11:

[0741] Finally, the server displays the generated report on the user's terminal, which includes a summary result, risk analysis result, comparison result with standard policy terms, individual problems, and advice according to the user's emotional state.

[0742] Input: Summary results, Risk analysis results, Comparison results, User's emotional state

[0743] Output: The generated report displayed on the user's terminal

[0744] 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.

[0745] 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.

[0746] 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.

[0747] [Third embodiment]

[0748] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0749] 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.

[0750] 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).

[0751] 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.

[0752] 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.

[0753] 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).

[0754] 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.

[0755] 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.

[0756] 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.

[0757] 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.

[0758] 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.

[0759] 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."

[0760] This invention builds a system that uses generative AI to automatically analyze contract terms and conditions and provide users with important information. This system allows users to efficiently understand online contract terms and conditions and assess risks. Specific embodiments are described below.

[0761] User Input

[0762] The user can input the URL or file of the contract terms using the device, for example, by entering the URL of the mobile carrier's contract terms through a web browser or a dedicated application, or by uploading a previously saved PDF file.

[0763] Obtaining and analyzing terms and conditions

[0764] The server retrieves the text of the terms and conditions from the URL entered by the user. To do this, it issues an HTTP request to retrieve the HTML document from the specified web page and extracts the text from specific tags. Alternatively, if a file is uploaded, it extracts the text using an appropriate library. For example, Apache Tika can be used to extract text from a PDF.

[0765] Terms and conditions summary function

[0766] The server then uses a generative AI to summarize the extracted clause text. This summarization is done using a natural language processing model (e.g., GPT-4) to extract key points from the clause based on important keywords and phrases, allowing users to understand lengthy clauses concisely.

[0767] Comparison function with standard clauses

[0768] The server compares the retrieved clause text with a database of standard clauses, using a comparison algorithm to identify differences and similarities and highlight any unusual clauses or different terms. For example, if the clauses regarding penalty fees or cancellation procedures differ from the standard clauses, this will be highlighted.

[0769] Legal and economic risk analysis

[0770] The server analyzes the legal and economic risks based on the contract text. It uses a risk assessment algorithm to assess clauses that may conflict with laws and regulations, as well as financial risks under the contract. For example, if there are unreasonable penalties or unfair clauses, it notifies the user.

[0771] Contract validity based on applicant's prior information

[0772] Users enter their personal information (e.g., age, occupation, and place of residence). The server evaluates the validity of the contract based on this information. For example, it evaluates and warns if the contract contains clauses that are inappropriate for minors or if certain conditions are not met.

[0773] Presentation of individual problems

[0774] Based on the analysis and comparison results, the server will present specific issues and items that the user should pay attention to, including a detailed explanation of the contract terms and the steps the user should take, such as providing details about automatic renewal terms and additional charges.

[0775] Displaying the results

[0776] Finally, the server displays the generated report on the user's device. This report includes a summary, risk analysis results, comparison results with standard terms and conditions, and points to note. The user can use this information to understand the contract contents and decide whether to proceed with the contract. For example, the user can click on links in the report to view more detailed information.

[0777] In this way, users can quickly understand the contents of complex contract terms and conditions, and proceed with the contract after understanding the risks and points to be aware of. The system reduces the burden on users and plays a role in making contracts fairer and more transparent.

[0778] The processing flow will be explained below.

[0779] Step 1:

[0780] The user inputs the URL or file of the contract terms and conditions using the terminal. The user inputs the URL into the input field of a web browser or dedicated application, or selects the file using the upload button.

[0781] Step 2:

[0782] The device sends the entered URL or uploaded file to the server, issuing an HTTP request containing the necessary request parameters to the server.

[0783] Step 3:

[0784] The server retrieves the clause text from the URL by issuing an HTTP request to retrieve the HTML document from the specified web page, extracting the text using an HTML parsing library, and, if a file was uploaded, extracting the text from the file using an appropriate library (e.g., Apache Tika).

[0785] Step 4:

[0786] The server uses a generative AI to summarize the terms and conditions text it has acquired. A natural language processing model (e.g., GPT-4) is used to generate a summary based on important keywords and phrases in the terms and conditions.

[0787] Step 5:

[0788] The server compares the summarized clause text with a database of standard clauses. Comparison algorithms are used to identify differences and similarities. By comparing with the standard clauses, unusual clauses and different terms are highlighted.

[0789] Step 6:

[0790] The server analyzes the legal and economic risks based on the contract text, using a risk assessment algorithm to assess clauses that may violate laws and regulations, as well as economic risks (e.g., high penalties, unfair terms).

[0791] Step 7:

[0792] The user enters their personal information (e.g., age, occupation, place of residence), and the device sends this information to the server.

[0793] Step 8:

[0794] The server evaluates the validity of the contract based on the prior information provided by the user, and verifies whether the contract is valid according to legal restrictions and applicable conditions.

[0795] Step 9:

[0796] The server presents individual issues based on the analysis and comparison results, lists unfavorable conditions and points to be aware of for users contained in specific contracts, and generates detailed explanations and recommendations.

[0797] Step 10:

[0798] The terminal displays the report received from the server to the user, which includes a summary, risk analysis results, comparison results with standard clauses, and points to note, allowing the user to easily check important information.

[0799] Example 1

[0800] 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."

[0801] Contract terms and conditions are typically difficult for users to understand, requiring a great deal of time and effort. Furthermore, users face the risk of overlooking legal and economic risks or unfair clauses, making it difficult for them to accurately grasp the contents of the contract. Furthermore, it is not easy to recognize clauses that differ from standard terms and conditions, or to determine the validity of a contract based on personal information. There is a need for a system that can solve these issues and enable users to quickly and accurately understand contract terms and conditions and assess risks.

[0802] 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.

[0803] In this invention, the server includes: means for a user to input a URL or file of the contract terms and conditions; means for acquiring the text of the terms and conditions from the URL or file; means for extracting the acquired text of the terms and conditions using data analysis means; means for summarizing the extracted text of the terms and conditions using a generative AI model; means for comparing the text with a standard database of terms and conditions; means for evaluating the legal and economic risks based on the terms and conditions; means for evaluating the validity of the contract based on the user's personal information; means for presenting the evaluation results and individual issues to the user; and means for displaying the evaluation results on the user's terminal using a display device. This allows the user to quickly understand the terms and conditions, grasp the legal and economic risks and points to note, and make an appropriate decision about the contract.

[0804] "User" means the entity that inputs the URL or file of the terms and conditions and receives information based thereon.

[0805] A "URL" is a Uniform Resource Locator that points to resources on the Internet and indicates the address of a web page.

[0806] A "file" is a unit for storing data, and in the present invention, it mainly refers to contract terms and conditions in PDF format.

[0807] "Terms and conditions text" refers to the text portion of a document that describes the terms and conditions of a contract.

[0808] "Data analysis means" refers to means for extracting useful information from input data.

[0809] A "generative AI model" is an artificial intelligence model that learns large amounts of data to generate language, such as GPT-4.

[0810] The "standard clause database" is a database that stores commonly used standard contract clauses.

[0811] "Legal and economic risks" refers to the legal and economic risks based on the terms and content of the contract.

[0812] "Personal information" refers to information that identifies an individual, such as a user's age, occupation, or place of residence.

[0813] "Evaluation results" refer to conclusions or judgments drawn based on analysis or comparison.

[0814] "Individual issues" refer to points of caution and risk factors in specific contract terms and conditions.

[0815] A "display device" is a device used to display information to users, and primarily refers to the screen of a computer or smartphone.

[0816] This invention builds a system that uses generative AI models to automatically analyze contract terms and conditions and provide users with important information. This system allows users to efficiently understand online contract terms and conditions and assess risks. The system's programming primarily relies on data analysis, natural language processing, and comparison algorithms.

[0817] First, the user uses the device to input the URL or file of the contract terms. This can be done through a web browser input form or a dedicated application. For example, the user can input the URL of the mobile carrier's contract terms or upload a saved PDF file.

[0818] The server issues an HTTP request to the URL entered by the user to retrieve the HTML document from the specified web page, and if a file was uploaded, extracts the text from the PDF using an appropriate library (e.g., Apache Tika). This text extraction is performed using an HTML parser.

[0819] Next, the server summarizes the extracted clause text using a generative AI model (e.g., GPT-4). The server inputs a prompt such as "Please summarize this text in 100 characters or less" to the generative AI model and receives the generated summary data. This allows the user to understand the lengthy clause text concisely.

[0820] The server then compares the retrieved clause text with a database of standard clauses, using a comparison algorithm to identify differences and similarities and highlight any unusual clauses or different terms. For example, if the clauses regarding penalty fees or cancellation procedures differ from the standard clauses, the differences will be highlighted.

[0821] The server then assesses the legal and financial risks of the contract text. Using a risk assessment algorithm, it analyzes clauses that may violate laws and regulations, as well as the financial risks associated with the contract. For example, it warns users of any unreasonable penalty charges or unfair clauses.

[0822] Users enter their personal information (e.g., age, occupation, and place of residence), and the server evaluates the validity of the contract based on this information. For example, it evaluates and warns if the contract contains clauses that are inappropriate for minors or if certain conditions are not met.

[0823] Based on the analysis and comparison results, the server will present specific issues that the user should pay attention to, including a detailed explanation of the contract terms and the steps the user should take, such as providing details about automatic renewal terms and additional charges.

[0824] Finally, the server displays the generated report on the user's device. This report includes a summary, risk analysis results, comparison results with standard terms and conditions, and points to note. The user can use this information to understand the contract contents and decide whether to proceed with the contract. For example, they can click on links in the report to view more detailed information.

[0825] Prompt Sentence Examples

[0826] Terms and conditions URL: https: / / example.com / contract-terms

[0827] or

[0828] Upload the PDF file of the terms and conditions: [Select PDF file]

[0829] User information: Age=25, Occupation=Engineer, Residence=Tokyo

[0830] Using this system, users can quickly and accurately understand the contents of contract terms and conditions and appropriately assess risks.

[0831] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0832] Step 1:

[0833] User Input

[0834] The user uses a device to enter the URL or file of the contract terms. For example, they can enter the URL of the contract terms (https: / / example.com / contract-terms) in the input field of a web browser, or they can launch a dedicated application, click the "Select File" button, and select a saved PDF file. The URL or file entered by the user becomes the input data. The output is the entered URL or file.

[0835] Step 2:

[0836] Obtaining the terms and conditions

[0837] The server issues an HTTP request to the URL entered by the user to retrieve the HTML document from the specified web page. If a file is uploaded, it also receives the file contents. Specifically, the server uses an HTTP GET request to download the HTML document. If a PDF file is uploaded, it receives the file. The input is the URL or file obtained from the user, and the output is the retrieved HTML document or PDF file.

[0838] Step 3:

[0839] Text Extraction

[0840] The server extracts text from an HTML document or PDF file. In the case of HTML, it parses specific tags to obtain the text, and in the case of PDF, it uses the Apache Tika library to extract the text. The server uses an HTML parser to extract the clause text from specific tags in the HTML document, and in the case of PDF files, it calls Apache Tika to extract the text. The input is an HTML document or a PDF file, and the output is the extracted clause text.

[0841] Step 4:

[0842] Generate summary of terms and conditions

[0843] The server inputs the extracted clause text into a generative AI model (e.g., GPT-4) to generate a summary. The server inputs a prompt ("Please summarize this text in 100 characters or less") to the generative AI model and receives the summarized text. Specifically, the server generates a prompt for GPT-4 and obtains the summary data through an API. The input is the extracted clause text, and the output is the summarized text.

[0844] Step 5:

[0845] Comparison with standard terms and conditions

[0846] The server compares the retrieved clause text with a standard clause database. It uses a comparison algorithm to identify differences and similarities and highlight unusual clauses or different terms. The server queries the standard clause database and compares it sentence by sentence with the retrieved clause text. The input is the clause text and the standard clause database, and the output is the comparison result data.

[0847] Step 6:

[0848] Legal and economic risk analysis

[0849] The server uses a risk assessment algorithm to analyze the clauses in the contract and identify legal and economic risks. If unfair clauses or unfair penalties exist, it generates data to warn the user. The input is the contract text, and the output is the risk assessment results.

[0850] Step 7:

[0851] Contract validity assessment based on personal information

[0852] The user enters their personal information (e.g., age, occupation, place of residence), and the server evaluates the validity of the contract based on this information. The server checks whether the contract terms are in compliance with the user's personal information and issues a warning. The input is the user's personal information and the contract text, and the output is the result of the contract validity evaluation.

[0853] Step 8:

[0854] Presentation of individual problems

[0855] Based on the analysis and comparison results, the server presents specific issues and items that the user should pay attention to. It provides detailed explanations and measures that the user should take. For example, it provides notes on the automatic renewal conditions and details of additional fees. The input is the comparison results and risk assessment results, and the output is data on issues and measures.

[0856] Step 9:

[0857] Displaying the results

[0858] The server displays the generated report on the user's device. This report includes a summary, risk analysis results, comparison results with standard clauses, and points to note. The user can use this information to understand the contract contents and decide whether to proceed with the contract. For example, they can click on a link in the report to view more detailed information. The input is various data in the report, and the output is the report displayed on the user's device.

[0859] (Application example 1)

[0860] 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."

[0861] Users of electronic payment services have difficulty quickly understanding the complex content of contract terms and conditions and assessing legal and economic risks. They also lack the means to identify unusual clauses compared to standard contract terms and obtain information to avoid risks. This increases the risk of entering into unfavorable contracts.

[0862] 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.

[0863] In this invention, the server includes means for a user to input a link or file of the contract terms and conditions, means for retrieving the text of the terms and conditions from the link or file, means for summarizing the retrieved text of the terms and conditions using a generation AI, means for comparing it with a standard database of terms and conditions, means for analyzing legal and economic risks based on the terms and conditions, means for evaluating the validity of the contract based on the user's prior information, means for presenting the evaluation results and individual issues to the user, and means for displaying the analysis results of the contract terms and conditions on the user's terminal. This allows the user to quickly and efficiently understand the contents of the contract terms and conditions, evaluate the risks, and make a comprehensive judgment to proceed with the appropriate contract.

[0864] "User" means a consumer who uses electronic payment services.

[0865] "Terms and conditions" are documents in which an electronic payment service provider lists the terms and conditions of use.

[0866] A "link" is a URL that accesses a specific web page.

[0867] "File" refers to document data stored in electronic format.

[0868] "Terms and conditions text" refers to the content of the contract terms and conditions expressed in text form.

[0869] "Generative AI" is an artificial intelligence technology that uses natural language processing to generate and analyze text.

[0870] A "summary" is a short summary of the most important parts of the original text.

[0871] A "standard clause database" is a collection of commonly used contract clauses managed as a database.

[0872] A "comparison algorithm" is a computational method that compares different texts to identify differences and similarities.

[0873] "Legal and Economic Risks" means legal issues and economic burdens that the User may incur under the Agreement.

[0874] "Prior information" refers to personal information or circumstances provided by the user.

[0875] "Validity" refers to whether a contract is legally established and effective.

[0876] "Evaluation results" refers to information provided by the system as a result of analysis.

[0877] "Individual issues" refer to specific points of caution or risk factors in the contract terms and conditions.

[0878] "Terminal" means a device (e.g., smartphone, tablet) used by a User to enter and display information.

[0879] "Displaying" refers to the act of visually providing analysis results and information on the user's device.

[0880] To realize this invention, the interaction between the user, the server, and the terminal used by the user is important.

[0881] First, the user inputs a link or an existing file to access the contract terms of the electronic payment service into the terminal. For example, the user can input the link to the contract terms using a web browser or a dedicated application, or upload a saved PDF file.

[0882] The server then issues an HTTP request from the provided link to retrieve the HTML document from the specified web page, or, if a file was uploaded, extracts the text using a text extraction library such as Apache Tika.

[0883] The retrieved contract text is summarized on the server using a generative AI model (e.g., GPT-4). This summarization process uses natural language processing techniques to extract key points from the contract based on important keywords and phrases, allowing users to easily understand lengthy contracts.

[0884] The server then compares the extracted clause text with a database of standard clauses using a comparison algorithm such as a Python-based Diff library, which identifies any unusual clauses or conditions that differ from the standard clauses and highlights them for the user.

[0885] In addition, the server applies a risk assessment algorithm to analyze legal and financial risks, which assesses the legal and financial consequences that users may incur. For example, any unreasonable penalties or unfair terms will be clearly indicated to the user.

[0886] Finally, the server generates a detailed report containing the analysis and comparison results, which is displayed on the user's device. This report includes a summary, risk analysis, comparison results with standard terms and conditions, and points to note. Based on this, the user can understand the contract contents and make a comprehensive decision on whether to proceed with the contract.

[0887] As a concrete example, consider a case where a user tries to analyze the terms and conditions at the URL "https: / / example.com / terms-and-conditions.pdf." When the user enters the URL into the app, the server downloads the PDF file and extracts the text. It then uses a generative AI model to create a summary and compare it with standard terms and conditions to identify any discrepancies. It also performs a risk analysis and warns the user if any unfair clauses are present. Finally, all analysis results are notified to the user, allowing them to quickly understand the contents of the contract terms and take appropriate action.

[0888] An example of a prompt is shown below.

[0889] Analyze the contract terms and conditions found at the URL "https: / / example.com / terms-and-conditions.pdf" and create a summary based on key keywords and phrases. Also compare it with standard terms and conditions, highlight any differences, and analyze the legal and financial risks.

[0890] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0891] Step 1:

[0892] The user inputs the link or file of the contract terms into the device. Specifically, the user opens a web browser or a dedicated application and inputs the URL to the contract terms or uploads an existing PDF file. The input for this step is the link or file, and the output is the information entered by the user.

[0893] Step 2:

[0894] The server retrieves the terms and conditions text based on the link or file received from the user. In the case of a link, the server issues an HTTP request to retrieve the HTML document from the specified web page. In the case of a file, the server uses a text extraction library such as Apache Tika to extract the text. The input for this step is the link or file provided by the user, and the output is the retrieved terms and conditions text.

[0895] Step 3:

[0896] The server summarizes the retrieved clause text using a generative AI model. The generative AI model (e.g., GPT-4) uses natural language processing techniques to extract key points from the clause based on important keywords and phrases. The input for this step is the retrieved clause text, and the output is a summarized clause.

[0897] Step 4:

[0898] The server compares the summarized clause text with a database of standard clauses. A comparison algorithm (e.g., a Python-based Diff library) is used to compare the extracted text with the contents of the standard clause database to identify differences and similarities. The input to this step is the summarized clause text, and the output is the identification of differences and similarities.

[0899] Step 5:

[0900] The server applies a risk assessment algorithm to analyze the legal and economic risks based on the retrieved contract text. Any unreasonable penalties or unfair clauses are identified and notified to the user. The input of this step is the retrieved contract text, and the output is the result of the risk analysis.

[0901] Step 6:

[0902] The server evaluates the validity of the contract based on the user's personal information. The user inputs personal information from the terminal (e.g., age, occupation), and the server evaluates whether the contract terms are legally appropriate based on this information. The input of this step is the user's prior information, and the output is the evaluation result of the validity of the contract.

[0903] Step 7:

[0904] The server presents the analysis results, comparison results, risk analysis, and individual issues to the user. A detailed report containing this information is generated and displayed on the user's terminal. The input to this step is each result of the analysis, and the output is a detailed report presented to the user.

[0905] Step 8:

[0906] The user checks the report on the terminal and understands the contract contents. Based on the report generated by the server, the user makes an overall decision on whether to proceed with the contract. The input of this step is the presented report, and the output is the user's decision and action.

[0907] 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.

[0908] This invention combines an emotion engine with a system that uses generative AI to automatically analyze contract terms and conditions and provide important information to users, recognizing the user's emotional state in real time and dynamically providing information. Specific embodiments are described below.

[0909] User Input

[0910] The user inputs the URL or file of the contract terms and conditions using a terminal. The user can either enter the URL into the input field of a web browser or dedicated application, or upload a saved PDF file. This provides the system with the contract terms and conditions that the user wants to analyze.

[0911] Obtaining and analyzing terms and conditions

[0912] The server issues an HTTP request to retrieve the clause text from the URL entered by the user, retrieves the HTML document from the specified web page, extracts the text using an HTML parsing library, and, if a file was uploaded, extracts the text from the file using an appropriate library (e.g., Apache Tika).

[0913] Terms and conditions summary function

[0914] The server then uses a generative AI to summarize the extracted clause text. This summary is done using a natural language processing model (e.g., GPT-4) to extract key points from the clause based on important keywords and phrases, allowing users to understand lengthy clauses concisely.

[0915] Comparison function with standard clauses

[0916] The server compares the retrieved clause text with a database of standard clauses, using a comparison algorithm to identify differences and similarities and highlight any unusual clauses or different terms. For example, if the clauses regarding penalty fees or cancellation procedures differ from the standard clauses, this will be highlighted.

[0917] Legal and economic risk analysis

[0918] The server analyzes the legal and economic risks based on the contract text. It uses a risk assessment algorithm to evaluate clauses that may conflict with laws and regulations, as well as financial risks under the contract (e.g., high penalty fees, unfair terms). This allows users to understand the potential risks contained in the contract.

[0919] Contract validity based on applicant's prior information

[0920] The user enters their personal information (e.g., age, occupation, place of residence). The server uses this information to assess the validity of the contract. By verifying whether the contract is valid according to legal restrictions and applicable conditions, the server can, for example, warn if the contract contains terms that are inappropriate for minors.

[0921] Presentation of individual problems

[0922] Based on the analysis and comparison results, the server presents specific issues and items that users should pay attention to. This includes listing unfavorable terms and conditions contained in specific contracts and generating detailed explanations and recommendations. For example, it provides notes on automatic renewal terms and details of additional fees.

[0923] Emotion Recognition and Dynamic Information Provision

[0924] The server is equipped with an emotion engine that analyzes the user's facial expressions and voice while they are typing and displaying reports, recognizing their emotions. For example, if the user looks anxious, the server will provide information that corresponds to that emotion. This makes it possible to dynamically adjust information while taking into account the user's emotional state.

[0925] Displaying the results

[0926] Finally, the server displays the generated report on the user's device. The report includes a summary, risk analysis results, comparison results with standard policy terms, points to note, and advice based on the user's emotional state. For example, users can click on links within the report to view more detailed information, which reflects feedback from the emotion engine.

[0927] In this way, users can quickly understand the contents of complex terms and conditions, and proceed with the contract after understanding the risks and points to note. The combination of the emotion engine makes it possible to provide appropriate information according to the user's emotional state, greatly improving the user experience.

[0928] The processing flow will be explained below.

[0929] Step 1:

[0930] The user inputs the URL or file of the contract terms and conditions using the terminal. The user either inputs the URL into the input field of a web browser or dedicated application, or selects the appropriate file using the upload button.

[0931] Step 2:

[0932] The terminal sends the URL entered by the user or the uploaded file to the server. The information sent to the server as an HTTP request includes the user's input data.

[0933] Step 3:

[0934] The server issues an HTTP request to retrieve the clause text from the URL, retrieves the HTML document for the specified web page, extracts the text from the HTML document using an HTML parsing library, or, if a file is uploaded, extracts the text using an appropriate library such as Apache Tika.

[0935] Step 4:

[0936] The server uses generative AI to summarize the terms and conditions text it has acquired. It uses a natural language processing model (e.g., GPT-4) to summarize the text based on important keywords and phrases, allowing the main points to be displayed concisely.

[0937] Step 5:

[0938] The server compares the summarized clause text with a database of standard clauses. Comparison algorithms are used to identify differences and similarities when compared to standard clauses. Different clauses and distinctive terms are highlighted.

[0939] Step 6:

[0940] The server analyzes the legal and economic risks of the terms and conditions, using a risk assessment algorithm to assess clauses that may violate laws and regulations, as well as economic risks (e.g., high penalties, unfair terms).

[0941] Step 7:

[0942] The user enters their personal information (e.g. age, occupation, place of residence, etc.) This information is used to evaluate the validity of legal and contractual terms.

[0943] Step 8:

[0944] The device sends the user's personal information to the server, including the personal information entered by the user as an HTTP request.

[0945] Step 9:

[0946] The server evaluates the validity of the contract based on the personal information provided by the user, and verifies whether the contract is valid based on legal and applicable conditions, for example by issuing a warning if the contract contains terms that are inappropriate for minors.

[0947] Step 10:

[0948] The server presents the results of the analysis, risk analysis, and individual issues to the user. This information includes the main points of the contract, risk assessment, comparison results with standard clauses, and points to note.

[0949] Step 11:

[0950] The emotion engine analyzes the user's facial expressions and voice while they are typing and viewing reports, and recognizes their emotions. This analysis is performed using a camera and microphone, and emotion recognition algorithms are applied.

[0951] Step 12:

[0952] The server dynamically adjusts the information and advice it displays based on the user's emotions as recognized by the emotion engine. For example, if the user feels anxious, it provides additional explanations or support information.

[0953] Step 13:

[0954] The device sends the emotion recognition results to the server, and the analyzed emotion data is used to personalize the user's experience.

[0955] Step 14:

[0956] The server incorporates the feedback from the emotion engine and displays a final report to the user, which includes a summary, risk assessment, comparison results, cautions, and advice based on the user's emotional state.

[0957] Step 15:

[0958] The user reviews the final report on their device, optionally clicking links for more information, and makes a decision on whether to proceed with the contract based on this feedback.

[0959] Example 2

[0960] 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."

[0961] Conventional contract clause analysis systems can summarize the contents of contract clauses and analyze risks, but they cannot provide information that takes into account the user's emotional state, making it difficult to provide information in a format that is easy for users to understand.In addition, there was a need for a system that could not only obtain the text of contract clauses from URLs or files entered by users, but also compare them with standard clauses and evaluate legal and economic risks in an integrated manner.

[0962] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for a user to input a URL or file of the terms and conditions, a means for acquiring the terms and conditions text from the URL or file, a means for summarizing the acquired terms and conditions text using a generation AI, a means for comparing it with a standard terms and conditions database, a means for analyzing legal and economic risks based on the terms and conditions, a means for evaluating the validity of the contract based on the user's prior information, a means for presenting the evaluation results and individual issues to the user, and a means for sensing the user's emotional state and dynamically providing information according to that state. This not only allows the user to quickly and accurately grasp the content of the contract terms and conditions and easily understand risks and points of caution, but also allows the user to receive information according to their emotional state.

[0963] "User" refers to a user who wishes to analyze the contract terms and conditions.

[0964] "URL" refers to the Uniform Resource Locator for specifying resources on the Internet.

[0965] A "file" refers to a collection of digital information stored in a particular format.

[0966] "Terms and Conditions Text" refers to the entire text of the contract terms and conditions.

[0967] "Generative AI" refers to artificial intelligence models that automatically generate natural language text.

[0968] "Summarizing" refers to shortening the original text and extracting only the important points.

[0969] "Standard clause database" refers to a database that contains commonly used contract clauses.

[0970] "Comparing" means placing two or more objects side by side to examine their differences and similarities.

[0971] "Legal and economic risk" refers to the possibility of disadvantage or loss from a legal or economic perspective.

[0972] "User's prior information" refers to personal information of the User that may affect the Agreement.

[0973] "Validity of a contract" refers to whether a contract is legally valid.

[0974] "Evaluate" means to judge the value or validity against specific criteria or conditions.

[0975] "Individual issues" refer to shortcomings or points requiring attention that exist in specific contract terms and conditions.

[0976] "Emotional state" refers to the emotional or psychological state a user has at a particular moment.

[0977] "Dynamic provision" refers to providing information in real time in response to changes in the situation or conditions.

[0978] This invention combines a system that uses generative AI to automatically analyze contract terms and conditions and provide important information to users with a function that recognizes the user's emotional state in real time and dynamically provides information. Specific embodiments are described below.

[0979] User Input

[0980] The user inputs the URL or file of the contract terms and conditions using a terminal. The user can either enter the URL into the input field of a web browser or dedicated application, or upload a saved PDF file. This provides the system with the contract terms and conditions that the user wants to analyze.

[0981] Obtaining and analyzing terms and conditions

[0982] The server issues an HTTP request to retrieve the terms and conditions text from the URL entered by the user, and retrieves the HTML document from the specified web page. The server extracts the text from the web page using an HTML parsing library (e.g., Beautiful Soup, lxml). If a file is uploaded, the server also extracts the text using a file parsing library such as Apache Tika.

[0983] Terms and conditions summary function

[0984] The server then uses a generative AI (e.g., GPT-4) to summarize the extracted text of the terms and conditions. This summary is generated using a natural language processing model to extract key points from the terms and conditions based on important keywords and phrases. For example, it generates a summary such as, "This contract is for a five-year contract, and the penalty is 10,000 yen."

[0985] Comparison function with standard clauses

[0986] The server compares the retrieved clause text with a database of standard clauses. It uses a comparison algorithm to identify differences and similarities and highlights unusual clauses or different terms. For example, if a clause stating "30 days' notice required for cancellation procedures" differs from the standard clause, the server identifies and highlights the difference.

[0987] Legal and economic risk analysis

[0988] The server analyzes legal and economic risks based on the contract text. It uses a risk assessment algorithm to evaluate financial risks based on clauses and contracts that may conflict with laws and regulations. For example, it identifies risks such as "high penalty fees and unfavorable terms for users" and reports them.

[0989] Contract validity based on applicant's prior information

[0990] Users enter their personal information (e.g., age, occupation, and place of residence), and the server uses that information to evaluate the validity of the contract and verify legal restrictions and applicable conditions. For example, it may issue a warning if the contract contains terms that are inappropriate for minors.

[0991] Presentation of individual problems

[0992] Based on the analysis results, the server presents specific issues and items that users should pay attention to. This includes listing unfavorable terms and points to be aware of, and generating detailed explanations and recommendations. For example, it lists issues such as "penalty clauses that are stricter than standard terms" and "automatic renewal terms that are difficult to understand."

[0993] Emotion Recognition and Dynamic Information Provision

[0994] The server is equipped with an emotion engine that analyzes the user's facial expressions and voice while they are entering data and displaying reports, recognizing their emotions. For example, if the emotion recognition result indicates that the user looks anxious, the server can provide additional information such as, "If the contract details are unclear, we recommend that you consult an expert."

[0995] Displaying the results

[0996] Finally, the server displays the generated report on the user's device. The report includes a summary, risk analysis results, comparison results with standard policy terms, points to note, and advice based on the user's emotional state. The user can click on links in the report to view more detailed information.

[0997] Examples of prompt statements

[0998] Below are some specific examples of prompt sentences to input to the generative AI model.

[0999] "The URL for the terms and conditions is below. Please summarize the key points of these terms. URL: [insert URL here]"

[1000] "Please analyze the contract terms and conditions contained in this PDF file and assess the risks. Please upload the PDF file."

[1001] "Please evaluate the validity of the contract based on the following personal information: Age: 25, Occupation: Company employee, Residence: Tokyo"

[1002] "Analyze the contract terms to see if they contain any unfavorable terms. Pay particular attention to any penalty fees or cancellation procedures."

[1003] By following these steps, the system helps users quickly and accurately understand the contents of complex contract terms, enabling them to proceed with the contract after understanding the risks and points to be aware of. In addition, by utilizing an emotion engine, information is provided according to the user's emotional state, greatly improving the user experience.

[1004] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1005] Step 1: User Input

[1006] The user uses the device to input the URL or file of the contract terms and conditions. Specifically, the user enters the URL into the input field of a web browser or dedicated application, or selects a saved PDF file in the device's file browser and clicks the upload button. This input provides the system with the contract terms and conditions data that the user wants to analyze. If there is a URL entered, that becomes the user's input, and the uploaded PDF file becomes the user's input.

[1007] Step 2: Obtain the terms and conditions

[1008] The server retrieves the clause text from the URL or file entered by the user. Specifically, if a URL is entered, the server issues an HTTP request to retrieve the HTML document from the specified web page. It then uses an HTML parsing library (e.g., Beautiful Soup, lxml) to extract the text from the retrieved HTML document. If a PDF file is uploaded, it uses a file parsing library such as Apache Tika to extract the text from the file. This retrieved text is the server's output.

[1009] Step 3: Text Summarization

[1010] The server summarizes the acquired text of the terms and conditions using a generation AI (e.g., GPT-4). Specifically, the acquired text is input into the generation AI along with the prompt, "Please summarize the main points of these terms and conditions." The generation AI generates a summary based on important keywords and phrases in the text. For example, it generates a summary such as, "This contract is for a five-year contract, and the penalty is 10,000 yen." This summary is provided to the user as the server's output.

[1011] Step 4: Compare with standard clauses

[1012] The server compares the retrieved clause text with a database of standard clauses. Specifically, it retrieves the standard clauses from the database and uses a comparison algorithm to identify differences and similarities between the retrieved clause text and the standard clauses. For example, if a clause such as "30 days' notice required for cancellation procedures" differs from the standard clauses, the difference is highlighted. The comparison results are provided to the user as server output.

[1013] Step 5: Legal and economic risk analysis

[1014] The server analyzes legal and economic risks based on the contract text. Specifically, it uses a risk assessment algorithm to evaluate clauses that may conflict with laws or regulations, as well as financial risks based on the contract (e.g., high penalty fees, unfair terms). For example, it identifies the risk that "penalties are high and terms are unfavorable to the user." The results of this risk assessment are provided to the user as the server's output.

[1015] Step 6: Assess contract validity

[1016] The user enters their personal information (e.g., age, occupation, and place of residence) into the terminal. The server evaluates the validity of the contract based on the input information. Specifically, it verifies whether the contract is valid according to legal restrictions and applicable conditions. For example, if the contract contains clauses that are inappropriate for minors, a warning about this is displayed. The evaluation result is provided to the user as the server's output.

[1017] Step 7: State the specific problem

[1018] Based on the analysis and comparison results, the server presents specific problems and items that users should pay attention to. Specifically, it lists unfavorable conditions and points to be aware of, and generates detailed explanations and recommendations. For example, it presents problems such as "the penalty clause is stricter than the standard terms and conditions" and "the automatic renewal conditions are difficult to understand." This list and recommendations are provided to the user as the server's output.

[1019] Step 8: Emotion recognition and dynamic information provision

[1020] The server is equipped with an emotion engine that analyzes the user's facial expressions and voice in real time while the user is entering data and while reports are being displayed. Specifically, it uses a webcam and microphone to sense the user's emotional state. For example, based on the emotion recognition result that "the user looks anxious," the server dynamically provides corresponding information. For example, it provides information such as "If the contract details are unclear, we recommend that you consult an expert." This information is dynamically provided as output from the server.

[1021] Step 9: View the results

[1022] Finally, the server displays the generated report on the user's device. Specifically, the report includes a summary of the policy, risk analysis results, comparison results with standard policy, points to note, and advice based on the user's emotional state. The user can check the report on their device and click links to view more detailed information. This report is provided to the user as the server's final output.

[1023] (Application example 2)

[1024] 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."

[1025] In today's world, when users sign contracts at brick-and-mortar stores, it is extremely difficult to quickly and accurately understand lengthy and complex contract terms and conditions and grasp the legal and economic risks involved. It is also difficult to determine whether the contract terms are appropriate for the user's individual circumstances. Furthermore, there is a lack of support that takes into account the user's emotional state during the contract process, which often results in users feeling anxious and confused. Technology that solves these issues is needed.

[1026] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: a means for a user to input a URL or file of the contract terms and conditions; a means for retrieving the text of the terms and conditions from the URL or file; a means for summarizing the retrieved text of the terms and conditions using a generation AI; a means for comparing the text with a standard terms and conditions database; a means for analyzing legal and economic risks based on the terms and conditions; a means for evaluating the validity of the contract based on the user's prior information; a means for presenting the evaluation results and individual issues to the user; a means for recognizing the user's emotional state; and a means for dynamically adjusting information provision based on the recognized emotional state. This allows users to quickly and accurately understand the contents of the contract terms and conditions, grasp legal and economic risks, and obtain information appropriate to their individual circumstances. Furthermore, the user experience is improved by providing support tailored to the user's emotional state.

[1027] "User" means any person or entity that uses the System to analyze contract terms and conditions.

[1028] "Contract terms and conditions" are documents that describe the contents of a contract and indicate the conditions and rules at the time of contract conclusion.

[1029] "URL" is an abbreviation for Uniform Resource Locator, and is an address that indicates the location of a resource such as a web page.

[1030] A "file" is a unit for storing digital data, and often refers to a digital document of contract terms and conditions.

[1031] "Generative AI" refers to an artificial intelligence model that automatically generates and analyzes text, and is used for natural language processing, etc.

[1032] "Summarizing" means extracting the important parts from a long piece of text and reconstructing them in a concise form.

[1033] The "standard clause database" is a database that stores commonly used standard contract clauses.

[1034] To compare means to put two or more elements side by side to reveal their similarities and differences.

[1035] "Legal and economic risk" refers to the possibility of violating laws and regulations or incurring financial loss.

[1036] "Prior information" refers to personal information and background information provided by the user in advance.

[1037] "Validity of a contract" is the standard for determining whether a contract is legally and practically valid.

[1038] "Evaluation results" are the results generated by the system after analysis and comparison.

[1039] "Specific issues" are issues or considerations that are unique to a particular contract or situation.

[1040] "Emotional state" refers to the user's psychological state or feeling, including anxiety, joy, interest, etc.

[1041] "Recognizing" means that the system obtains information from the user's facial expressions, voice, etc. and understands it.

[1042] "Dynamic adjustment" means changing the information provided in real time according to the situation and conditions.

[1043] This invention is a system that enables users to quickly and accurately understand contract terms and conditions, grasp legal and economic risks, and provide information appropriate to individual circumstances when signing a contract at a physical store. Specific embodiments for carrying out the invention are described below.

[1044] 1. System Overview

[1045] The system analyzes the URL or file of the contract terms entered by the user, summarizes it using generation AI, and compares it with a database of standard contract terms. It also has the function of evaluating the validity of the contract based on the user's personal information and presenting the evaluation results and individual problems. It also recognizes the user's emotional state and dynamically adjusts the information provided based on that state.

[1046] 2. Acquisition and analysis of contract terms

[1047] The server issues an HTTP request to the URL of the contract terms entered by the user and retrieves the HTML document from the specified web page. To parse the HTML document, it uses an HTML parsing library such as BeautifulSoup. If the user has uploaded a file, it extracts the text from the file using the Apache Tika library.

[1048] 3. Summary of Terms and Conditions

[1049] The retrieved contract text is summarized using a generative AI model (e.g., GPT-4), using the following prompt:

[1050] "Please summarize the following contract, including important clauses and risk points to be aware of: {Full contract}"

[1051] 4. Comparison with standard terms and conditions

[1052] The server compares the retrieved policy text with a standard policy database and uses a comparison algorithm (e.g., a text similarity algorithm) to identify differences and similarities.

[1053] 5. Risk Analysis and Effectiveness Assessment

[1054] The server uses risk assessment algorithms to assess legal and financial risks, and evaluates the validity of the contract based on the user's previously entered personal information (e.g., age, occupation, place of residence), using criteria based on laws and regulations.

[1055] 6. Emotion Recognition and Dynamic Information Provision

[1056] When a user is using smart glasses or a head-mounted display, these devices capture the user's facial expressions and voice and use an emotion engine (e.g., the EmotionDetector library) to recognize the user's emotional state in real time. The server dynamically adjusts the information provided according to the recognized emotional state, for example, providing more detailed explanations or additional information if the user looks anxious.

[1057] 7. Displaying the results

[1058] Finally, the server displays the generated report on the user's device. The report includes a summary, risk analysis, comparison with standard terms and conditions, individual issues, and advice based on the user's emotional state. The user can check detailed information on their device, and information reflecting feedback from the emotion engine is provided.

[1059] This system allows users to complete the contract process in a physical store smoothly and safely, and also improves the user experience by providing information tailored to the user's emotional state.

[1060] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1061] Step 1:

[1062] The user inputs the URL or file of the contract terms into the terminal. The user can either enter the URL into the input field of a web browser or dedicated application, or upload a saved PDF file. This provides the contract terms to the system for analysis.

[1063] Input: URL or PDF file

[1064] Output: Agreement data to be analyzed

[1065] Step 2:

[1066] The server issues an HTTP request to retrieve the contract terms text from the URL entered by the user, retrieves the HTML document from the specified web page, and extracts the text using an HTML parsing library (e.g., BeautifulSoup).

[1067] Input: Entered URL

[1068] Output: Contract terms text extracted from HTML document

[1069] Step 3:

[1070] For user uploaded files, the server uses the Apache Tika library to extract the text from the file.

[1071] Input: Uploaded PDF file

[1072] Output: Contract terms text extracted from PDF file

[1073] Step 4:

[1074] The server summarizes the contract terms and conditions using a generative AI model (e.g., GPT-4). The generative AI model uses the following prompt: "Please summarize the following contract. Please include important clauses and risk points to be aware of: {Full contract}"

[1075] Input: Contract terms text

[1076] Output: Abridged contract terms text

[1077] Step 5:

[1078] The server compares the retrieved policy text with a standard policy database, using a comparison algorithm to identify differences and similarities.

[1079] Input: Abridged contract terms text

[1080] Output: Comparison results with standard terms and conditions

[1081] Step 6:

[1082] The server uses a risk assessment algorithm to assess the legal and financial risks involved in the contract.

[1083] Input: Abridged contract terms text

[1084] Output: Risk assessment results

[1085] Step 7:

[1086] The server evaluates the validity of the contract based on the user's prior information (e.g., age, occupation, place of residence), and determines whether it is valid using evaluation criteria based on laws and regulations.

[1087] Input: User's prior information

[1088] Output: Contract validity evaluation result

[1089] Step 8:

[1090] The server presents the evaluation results and specific issues to the user, including any adverse conditions or caveats associated with the particular contract.

[1091] Input: Risk assessment results, contract validity assessment results

[1092] Output: Evaluation results and individual problems presented to the user

[1093] Step 9:

[1094] When a user is wearing smart glasses or a head-mounted display, the device captures the user's facial expressions and voice, and the server uses an emotion engine to recognize the user's emotional state in real time.

[1095] Input: User's facial expressions and voice data

[1096] Output: Perceived emotional state of the user

[1097] Step 10:

[1098] The server dynamically adjusts the information provided depending on the user's perceived emotional state, for example by providing more detailed explanations or additional information if the user appears anxious.

[1099] Input: Perceived emotional state of the user

[1100] Output: Dynamically adjusted informational

[1101] Step 11:

[1102] Finally, the server displays the generated report on the user's terminal, which includes a summary result, risk analysis result, comparison result with standard policy terms, individual problems, and advice according to the user's emotional state.

[1103] Input: Summary results, Risk analysis results, Comparison results, User's emotional state

[1104] Output: The generated report displayed on the user's terminal

[1105] 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.

[1106] 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.

[1107] 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.

[1108] [Fourth embodiment]

[1109] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1110] 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.

[1111] 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).

[1112] 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.

[1113] 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.

[1114] 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).

[1115] 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.

[1116] 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.

[1117] 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.

[1118] 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.

[1119] 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.

[1120] 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.

[1121] 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."

[1122] This invention builds a system that uses generative AI to automatically analyze contract terms and conditions and provide users with important information. This system allows users to efficiently understand online contract terms and conditions and assess risks. Specific embodiments are described below.

[1123] User Input

[1124] The user can input the URL or file of the contract terms using the device, for example, by entering the URL of the mobile carrier's contract terms through a web browser or a dedicated application, or by uploading a previously saved PDF file.

[1125] Obtaining and analyzing terms and conditions

[1126] The server retrieves the text of the terms and conditions from the URL entered by the user. To do this, it issues an HTTP request to retrieve the HTML document from the specified web page and extracts the text from specific tags. Alternatively, if a file is uploaded, it extracts the text using an appropriate library. For example, Apache Tika can be used to extract text from a PDF.

[1127] Terms and conditions summary function

[1128] The server then uses a generative AI to summarize the extracted clause text. This summarization is done using a natural language processing model (e.g., GPT-4) to extract key points from the clause based on important keywords and phrases, allowing users to understand lengthy clauses concisely.

[1129] Comparison function with standard clauses

[1130] The server compares the retrieved clause text with a database of standard clauses, using a comparison algorithm to identify differences and similarities and highlight any unusual clauses or different terms. For example, if the clauses regarding penalty fees or cancellation procedures differ from the standard clauses, this will be highlighted.

[1131] Legal and economic risk analysis

[1132] The server analyzes the legal and economic risks based on the contract text. It uses a risk assessment algorithm to assess clauses that may conflict with laws and regulations, as well as financial risks under the contract. For example, if there are unreasonable penalties or unfair clauses, it notifies the user.

[1133] Contract validity based on applicant's prior information

[1134] Users enter their personal information (e.g., age, occupation, and place of residence). The server evaluates the validity of the contract based on this information. For example, it evaluates and warns if the contract contains clauses that are inappropriate for minors or if certain conditions are not met.

[1135] Presentation of individual problems

[1136] Based on the analysis and comparison results, the server will present specific issues and items that the user should pay attention to, including a detailed explanation of the contract terms and the steps the user should take, such as providing details about automatic renewal terms and additional charges.

[1137] Displaying the results

[1138] Finally, the server displays the generated report on the user's device. This report includes a summary, risk analysis results, comparison results with standard terms and conditions, and points to note. The user can use this information to understand the contract contents and decide whether to proceed with the contract. For example, the user can click on links in the report to view more detailed information.

[1139] In this way, users can quickly understand the contents of complex contract terms and conditions, and proceed with the contract after understanding the risks and points to be aware of. The system reduces the burden on users and plays a role in making contracts fairer and more transparent.

[1140] The processing flow will be explained below.

[1141] Step 1:

[1142] The user inputs the URL or file of the contract terms and conditions using the terminal. The user inputs the URL into the input field of a web browser or dedicated application, or selects the file using the upload button.

[1143] Step 2:

[1144] The device sends the entered URL or uploaded file to the server, issuing an HTTP request containing the necessary request parameters to the server.

[1145] Step 3:

[1146] The server retrieves the clause text from the URL by issuing an HTTP request to retrieve the HTML document from the specified web page, extracting the text using an HTML parsing library, and, if a file was uploaded, extracting the text from the file using an appropriate library (e.g., Apache Tika).

[1147] Step 4:

[1148] The server uses a generative AI to summarize the terms and conditions text it has acquired. A natural language processing model (e.g., GPT-4) is used to generate a summary based on important keywords and phrases in the terms and conditions.

[1149] Step 5:

[1150] The server compares the summarized clause text with a database of standard clauses. Comparison algorithms are used to identify differences and similarities. By comparing with the standard clauses, unusual clauses and different terms are highlighted.

[1151] Step 6:

[1152] The server analyzes the legal and economic risks based on the contract text, using a risk assessment algorithm to assess clauses that may violate laws and regulations, as well as economic risks (e.g., high penalties, unfair terms).

[1153] Step 7:

[1154] The user enters their personal information (e.g., age, occupation, place of residence), and the device sends this information to the server.

[1155] Step 8:

[1156] The server evaluates the validity of the contract based on the prior information provided by the user, and verifies whether the contract is valid according to legal restrictions and applicable conditions.

[1157] Step 9:

[1158] The server presents individual issues based on the analysis and comparison results, lists unfavorable conditions and points to be aware of for users contained in specific contracts, and generates detailed explanations and recommendations.

[1159] Step 10:

[1160] The terminal displays the report received from the server to the user, which includes a summary, risk analysis results, comparison results with standard clauses, and points to note, allowing the user to easily check important information.

[1161] Example 1

[1162] 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."

[1163] Contract terms and conditions are typically difficult for users to understand, requiring a great deal of time and effort. Furthermore, users face the risk of overlooking legal and economic risks or unfair clauses, making it difficult for them to accurately grasp the contents of the contract. Furthermore, it is not easy to recognize clauses that differ from standard terms and conditions, or to determine the validity of a contract based on personal information. There is a need for a system that can solve these issues and enable users to quickly and accurately understand contract terms and conditions and assess risks.

[1164] 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.

[1165] In this invention, the server includes: means for a user to input a URL or file of the contract terms and conditions; means for acquiring the text of the terms and conditions from the URL or file; means for extracting the acquired text of the terms and conditions using data analysis means; means for summarizing the extracted text of the terms and conditions using a generative AI model; means for comparing the text with a standard database of terms and conditions; means for evaluating the legal and economic risks based on the terms and conditions; means for evaluating the validity of the contract based on the user's personal information; means for presenting the evaluation results and individual issues to the user; and means for displaying the evaluation results on the user's terminal using a display device. This allows the user to quickly understand the terms and conditions, grasp the legal and economic risks and points to note, and make an appropriate decision about the contract.

[1166] "User" means the entity that inputs the URL or file of the terms and conditions and receives information based thereon.

[1167] A "URL" is a Uniform Resource Locator that points to resources on the Internet and indicates the address of a web page.

[1168] A "file" is a unit for storing data, and in the present invention, it mainly refers to contract terms and conditions in PDF format.

[1169] "Terms and conditions text" refers to the text portion of a document that describes the terms and conditions of a contract.

[1170] "Data analysis means" refers to means for extracting useful information from input data.

[1171] A "generative AI model" is an artificial intelligence model that learns large amounts of data to generate language, such as GPT-4.

[1172] The "standard clause database" is a database that stores commonly used standard contract clauses.

[1173] "Legal and economic risks" refers to the legal and economic risks based on the terms and content of the contract.

[1174] "Personal information" refers to information that identifies an individual, such as a user's age, occupation, or place of residence.

[1175] "Evaluation results" refer to conclusions or judgments drawn based on analysis or comparison.

[1176] "Individual issues" refer to points of caution and risk factors in specific contract terms and conditions.

[1177] A "display device" is a device used to display information to users, and primarily refers to the screen of a computer or smartphone.

[1178] This invention builds a system that uses generative AI models to automatically analyze contract terms and conditions and provide users with important information. This system allows users to efficiently understand online contract terms and conditions and assess risks. The system's programming primarily relies on data analysis, natural language processing, and comparison algorithms.

[1179] First, the user uses the device to input the URL or file of the contract terms. This can be done through a web browser input form or a dedicated application. For example, the user can input the URL of the mobile carrier's contract terms or upload a saved PDF file.

[1180] The server issues an HTTP request to the URL entered by the user to retrieve the HTML document from the specified web page, and if a file was uploaded, extracts the text from the PDF using an appropriate library (e.g., Apache Tika). This text extraction is performed using an HTML parser.

[1181] Next, the server summarizes the extracted clause text using a generative AI model (e.g., GPT-4). The server inputs a prompt such as "Please summarize this text in 100 characters or less" to the generative AI model and receives the generated summary data. This allows the user to understand the lengthy clause text concisely.

[1182] The server then compares the retrieved clause text with a database of standard clauses, using a comparison algorithm to identify differences and similarities and highlight any unusual clauses or different terms. For example, if the clauses regarding penalty fees or cancellation procedures differ from the standard clauses, the differences will be highlighted.

[1183] The server then assesses the legal and financial risks of the contract text. Using a risk assessment algorithm, it analyzes clauses that may violate laws and regulations, as well as the financial risks associated with the contract. For example, it warns users of any unreasonable penalty charges or unfair clauses.

[1184] Users enter their personal information (e.g., age, occupation, and place of residence), and the server evaluates the validity of the contract based on this information. For example, it evaluates and warns if the contract contains clauses that are inappropriate for minors or if certain conditions are not met.

[1185] Based on the analysis and comparison results, the server will present specific issues that the user should pay attention to, including a detailed explanation of the contract terms and the steps the user should take, such as providing details about automatic renewal terms and additional charges.

[1186] Finally, the server displays the generated report on the user's device. This report includes a summary, risk analysis results, comparison results with standard terms and conditions, and points to note. The user can use this information to understand the contract contents and decide whether to proceed with the contract. For example, they can click on links in the report to view more detailed information.

[1187] Prompt Sentence Examples

[1188] Terms and conditions URL: https: / / example.com / contract-terms

[1189] or

[1190] Upload the PDF file of the terms and conditions: [Select PDF file]

[1191] User information: Age=25, Occupation=Engineer, Residence=Tokyo

[1192] Using this system, users can quickly and accurately understand the contents of contract terms and conditions and appropriately assess risks.

[1193] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1194] Step 1:

[1195] User Input

[1196] The user uses a device to enter the URL or file of the contract terms. For example, they can enter the URL of the contract terms (https: / / example.com / contract-terms) in the input field of a web browser, or they can launch a dedicated application, click the "Select File" button, and select a saved PDF file. The URL or file entered by the user becomes the input data. The output is the entered URL or file.

[1197] Step 2:

[1198] Obtaining the terms and conditions

[1199] The server issues an HTTP request to the URL entered by the user to retrieve the HTML document from the specified web page. If a file is uploaded, it also receives the file contents. Specifically, the server uses an HTTP GET request to download the HTML document. If a PDF file is uploaded, it receives the file. The input is the URL or file obtained from the user, and the output is the retrieved HTML document or PDF file.

[1200] Step 3:

[1201] Text Extraction

[1202] The server extracts text from an HTML document or PDF file. In the case of HTML, it parses specific tags to obtain the text, and in the case of PDF, it uses the Apache Tika library to extract the text. The server uses an HTML parser to extract the clause text from specific tags in the HTML document, and in the case of PDF files, it calls Apache Tika to extract the text. The input is an HTML document or a PDF file, and the output is the extracted clause text.

[1203] Step 4:

[1204] Generate summary of terms and conditions

[1205] The server inputs the extracted clause text into a generative AI model (e.g., GPT-4) to generate a summary. The server inputs a prompt ("Please summarize this text in 100 characters or less") to the generative AI model and receives the summarized text. Specifically, the server generates a prompt for GPT-4 and obtains the summary data through an API. The input is the extracted clause text, and the output is the summarized text.

[1206] Step 5:

[1207] Comparison with standard terms and conditions

[1208] The server compares the retrieved clause text with a standard clause database. It uses a comparison algorithm to identify differences and similarities and highlight unusual clauses or different terms. The server queries the standard clause database and compares it sentence by sentence with the retrieved clause text. The input is the clause text and the standard clause database, and the output is the comparison result data.

[1209] Step 6:

[1210] Legal and economic risk analysis

[1211] The server uses a risk assessment algorithm to analyze the clauses in the contract and identify legal and economic risks. If unfair clauses or unfair penalties exist, it generates data to warn the user. The input is the contract text, and the output is the risk assessment results.

[1212] Step 7:

[1213] Contract validity assessment based on personal information

[1214] The user enters their personal information (e.g., age, occupation, place of residence), and the server evaluates the validity of the contract based on this information. The server checks whether the contract terms are in compliance with the user's personal information and issues a warning. The input is the user's personal information and the contract text, and the output is the result of the contract validity evaluation.

[1215] Step 8:

[1216] Presentation of individual problems

[1217] Based on the analysis and comparison results, the server presents specific issues and items that the user should pay attention to. It provides detailed explanations and measures that the user should take. For example, it provides notes on the automatic renewal conditions and details of additional fees. The input is the comparison results and risk assessment results, and the output is data on issues and measures.

[1218] Step 9:

[1219] Displaying the results

[1220] The server displays the generated report on the user's device. This report includes a summary, risk analysis results, comparison results with standard clauses, and points to note. The user can use this information to understand the contract contents and decide whether to proceed with the contract. For example, they can click on a link in the report to view more detailed information. The input is various data in the report, and the output is the report displayed on the user's device.

[1221] (Application example 1)

[1222] 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."

[1223] Users of electronic payment services have difficulty quickly understanding the complex content of contract terms and conditions and assessing legal and economic risks. They also lack the means to identify unusual clauses compared to standard contract terms and obtain information to avoid risks. This increases the risk of entering into unfavorable contracts.

[1224] 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.

[1225] In this invention, the server includes means for a user to input a link or file of the contract terms and conditions, means for retrieving the text of the terms and conditions from the link or file, means for summarizing the retrieved text of the terms and conditions using a generation AI, means for comparing it with a standard database of terms and conditions, means for analyzing legal and economic risks based on the terms and conditions, means for evaluating the validity of the contract based on the user's prior information, means for presenting the evaluation results and individual issues to the user, and means for displaying the analysis results of the contract terms and conditions on the user's terminal. This allows the user to quickly and efficiently understand the contents of the contract terms and conditions, evaluate the risks, and make a comprehensive judgment to proceed with the appropriate contract.

[1226] "User" means a consumer who uses electronic payment services.

[1227] "Terms and conditions" are documents in which an electronic payment service provider lists the terms and conditions of use.

[1228] A "link" is a URL that accesses a specific web page.

[1229] "File" refers to document data stored in electronic format.

[1230] "Terms and conditions text" refers to the content of the contract terms and conditions expressed in text form.

[1231] "Generative AI" is an artificial intelligence technology that uses natural language processing to generate and analyze text.

[1232] A "summary" is a short summary of the most important parts of the original text.

[1233] A "standard clause database" is a collection of commonly used contract clauses managed as a database.

[1234] A "comparison algorithm" is a computational method that compares different texts to identify differences and similarities.

[1235] "Legal and Economic Risks" means legal issues and economic burdens that the User may incur under the Agreement.

[1236] "Prior information" refers to personal information or circumstances provided by the user.

[1237] "Validity" refers to whether a contract is legally established and effective.

[1238] "Evaluation results" refers to information provided by the system as a result of analysis.

[1239] "Individual issues" refer to specific points of caution or risk factors in the contract terms and conditions.

[1240] "Terminal" means a device (e.g., smartphone, tablet) used by a User to enter and display information.

[1241] "Displaying" refers to the act of visually providing analysis results and information on the user's device.

[1242] To realize this invention, the interaction between the user, the server, and the terminal used by the user is important.

[1243] First, the user inputs a link or an existing file to access the contract terms of the electronic payment service into the terminal. For example, the user can input the link to the contract terms using a web browser or a dedicated application, or upload a saved PDF file.

[1244] The server then issues an HTTP request from the provided link to retrieve the HTML document from the specified web page, or, if a file was uploaded, extracts the text using a text extraction library such as Apache Tika.

[1245] The retrieved contract text is summarized on the server using a generative AI model (e.g., GPT-4). This summarization process uses natural language processing techniques to extract key points from the contract based on important keywords and phrases, allowing users to easily understand lengthy contracts.

[1246] The server then compares the extracted clause text with a database of standard clauses using a comparison algorithm such as a Python-based Diff library, which identifies any unusual clauses or conditions that differ from the standard clauses and highlights them for the user.

[1247] In addition, the server applies a risk assessment algorithm to analyze legal and financial risks, which assesses the legal and financial consequences that users may incur. For example, any unreasonable penalties or unfair terms will be clearly indicated to the user.

[1248] Finally, the server generates a detailed report containing the analysis and comparison results, which is displayed on the user's device. This report includes a summary, risk analysis, comparison results with standard terms and conditions, and points to note. Based on this, the user can understand the contract contents and make a comprehensive decision on whether to proceed with the contract.

[1249] As a concrete example, consider a case where a user tries to analyze the terms and conditions at the URL "https: / / example.com / terms-and-conditions.pdf." When the user enters the URL into the app, the server downloads the PDF file and extracts the text. It then uses a generative AI model to create a summary and compare it with standard terms and conditions to identify any discrepancies. It also performs a risk analysis and warns the user if any unfair clauses are present. Finally, all analysis results are notified to the user, allowing them to quickly understand the contents of the contract terms and take appropriate action.

[1250] An example of a prompt is shown below.

[1251] Analyze the contract terms and conditions found at the URL "https: / / example.com / terms-and-conditions.pdf" and create a summary based on key keywords and phrases. Also compare it with standard terms and conditions, highlight any differences, and analyze the legal and financial risks.

[1252] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1253] Step 1:

[1254] The user inputs the link or file of the contract terms into the device. Specifically, the user opens a web browser or a dedicated application and inputs the URL to the contract terms or uploads an existing PDF file. The input for this step is the link or file, and the output is the information entered by the user.

[1255] Step 2:

[1256] The server retrieves the terms and conditions text based on the link or file received from the user. In the case of a link, the server issues an HTTP request to retrieve the HTML document from the specified web page. In the case of a file, the server uses a text extraction library such as Apache Tika to extract the text. The input for this step is the link or file provided by the user, and the output is the retrieved terms and conditions text.

[1257] Step 3:

[1258] The server summarizes the retrieved clause text using a generative AI model. The generative AI model (e.g., GPT-4) uses natural language processing techniques to extract key points from the clause based on important keywords and phrases. The input for this step is the retrieved clause text, and the output is a summarized clause.

[1259] Step 4:

[1260] The server compares the summarized clause text with a database of standard clauses. A comparison algorithm (e.g., a Python-based Diff library) is used to compare the extracted text with the contents of the standard clause database to identify differences and similarities. The input to this step is the summarized clause text, and the output is the identification of differences and similarities.

[1261] Step 5:

[1262] The server applies a risk assessment algorithm to analyze the legal and economic risks based on the retrieved contract text. Any unreasonable penalties or unfair clauses are identified and notified to the user. The input of this step is the retrieved contract text, and the output is the result of the risk analysis.

[1263] Step 6:

[1264] The server evaluates the validity of the contract based on the user's personal information. The user inputs personal information from the terminal (e.g., age, occupation), and the server evaluates whether the contract terms are legally appropriate based on this information. The input of this step is the user's prior information, and the output is the evaluation result of the validity of the contract.

[1265] Step 7:

[1266] The server presents the analysis results, comparison results, risk analysis, and individual issues to the user. A detailed report containing this information is generated and displayed on the user's terminal. The input to this step is each result of the analysis, and the output is a detailed report presented to the user.

[1267] Step 8:

[1268] The user checks the report on the terminal and understands the contract contents. Based on the report generated by the server, the user makes an overall decision on whether to proceed with the contract. The input of this step is the presented report, and the output is the user's decision and action.

[1269] 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.

[1270] This invention combines an emotion engine with a system that uses generative AI to automatically analyze contract terms and conditions and provide important information to users, recognizing the user's emotional state in real time and dynamically providing information. Specific embodiments are described below.

[1271] User Input

[1272] The user inputs the URL or file of the contract terms and conditions using a terminal. The user can either enter the URL into the input field of a web browser or dedicated application, or upload a saved PDF file. This provides the system with the contract terms and conditions that the user wants to analyze.

[1273] Obtaining and analyzing terms and conditions

[1274] The server issues an HTTP request to retrieve the clause text from the URL entered by the user, retrieves the HTML document from the specified web page, extracts the text using an HTML parsing library, and, if a file was uploaded, extracts the text from the file using an appropriate library (e.g., Apache Tika).

[1275] Terms and conditions summary function

[1276] The server then uses a generative AI to summarize the extracted clause text. This summary is done using a natural language processing model (e.g., GPT-4) to extract key points from the clause based on important keywords and phrases, allowing users to understand lengthy clauses concisely.

[1277] Comparison function with standard clauses

[1278] The server compares the retrieved clause text with a database of standard clauses, using a comparison algorithm to identify differences and similarities and highlight any unusual clauses or different terms. For example, if the clauses regarding penalty fees or cancellation procedures differ from the standard clauses, this will be highlighted.

[1279] Legal and economic risk analysis

[1280] The server analyzes the legal and economic risks based on the contract text. It uses a risk assessment algorithm to evaluate clauses that may conflict with laws and regulations, as well as financial risks under the contract (e.g., high penalty fees, unfair terms). This allows users to understand the potential risks contained in the contract.

[1281] Contract validity based on applicant's prior information

[1282] The user enters their personal information (e.g., age, occupation, place of residence). The server uses this information to assess the validity of the contract. By verifying whether the contract is valid according to legal restrictions and applicable conditions, the server can, for example, warn if the contract contains terms that are inappropriate for minors.

[1283] Presentation of individual problems

[1284] Based on the analysis and comparison results, the server presents specific issues and items that users should pay attention to. This includes listing unfavorable terms and conditions contained in specific contracts and generating detailed explanations and recommendations. For example, it provides notes on automatic renewal terms and details of additional fees.

[1285] Emotion Recognition and Dynamic Information Provision

[1286] The server is equipped with an emotion engine that analyzes the user's facial expressions and voice while they are typing and displaying reports, recognizing their emotions. For example, if the user looks anxious, the server will provide information that corresponds to that emotion. This makes it possible to dynamically adjust information while taking into account the user's emotional state.

[1287] Displaying the results

[1288] Finally, the server displays the generated report on the user's device. The report includes a summary, risk analysis results, comparison results with standard policy terms, points to note, and advice based on the user's emotional state. For example, users can click on links within the report to view more detailed information, which reflects feedback from the emotion engine.

[1289] In this way, users can quickly understand the contents of complex terms and conditions, and proceed with the contract after understanding the risks and points to note. The combination of the emotion engine makes it possible to provide appropriate information according to the user's emotional state, greatly improving the user experience.

[1290] The processing flow will be explained below.

[1291] Step 1:

[1292] The user inputs the URL or file of the contract terms and conditions using the terminal. The user either inputs the URL into the input field of a web browser or dedicated application, or selects the appropriate file using the upload button.

[1293] Step 2:

[1294] The terminal sends the URL entered by the user or the uploaded file to the server. The information sent to the server as an HTTP request includes the user's input data.

[1295] Step 3:

[1296] The server issues an HTTP request to retrieve the clause text from the URL, retrieves the HTML document for the specified web page, extracts the text from the HTML document using an HTML parsing library, or, if a file is uploaded, extracts the text using an appropriate library such as Apache Tika.

[1297] Step 4:

[1298] The server uses generative AI to summarize the terms and conditions text it has acquired. It uses a natural language processing model (e.g., GPT-4) to summarize the text based on important keywords and phrases, allowing the main points to be displayed concisely.

[1299] Step 5:

[1300] The server compares the summarized clause text with a database of standard clauses. Comparison algorithms are used to identify differences and similarities when compared to standard clauses. Different clauses and distinctive terms are highlighted.

[1301] Step 6:

[1302] The server analyzes the legal and economic risks of the terms and conditions, using a risk assessment algorithm to assess clauses that may violate laws and regulations, as well as economic risks (e.g., high penalties, unfair terms).

[1303] Step 7:

[1304] The user enters their personal information (e.g. age, occupation, place of residence, etc.) This information is used to evaluate the validity of legal and contractual terms.

[1305] Step 8:

[1306] The device sends the user's personal information to the server, including the personal information entered by the user as an HTTP request.

[1307] Step 9:

[1308] The server evaluates the validity of the contract based on the personal information provided by the user, and verifies whether the contract is valid based on legal and applicable conditions, for example by issuing a warning if the contract contains terms that are inappropriate for minors.

[1309] Step 10:

[1310] The server presents the results of the analysis, risk analysis, and individual issues to the user. This information includes the main points of the contract, risk assessment, comparison results with standard clauses, and points to note.

[1311] Step 11:

[1312] The emotion engine analyzes the user's facial expressions and voice while they are typing and viewing reports, and recognizes their emotions. This analysis is performed using a camera and microphone, and emotion recognition algorithms are applied.

[1313] Step 12:

[1314] The server dynamically adjusts the information and advice it displays based on the user's emotions as recognized by the emotion engine. For example, if the user feels anxious, it provides additional explanations or support information.

[1315] Step 13:

[1316] The device sends the emotion recognition results to the server, and the analyzed emotion data is used to personalize the user's experience.

[1317] Step 14:

[1318] The server incorporates the feedback from the emotion engine and displays a final report to the user, which includes a summary, risk assessment, comparison results, cautions, and advice based on the user's emotional state.

[1319] Step 15:

[1320] The user reviews the final report on their device, optionally clicking links for more information, and makes a decision on whether to proceed with the contract based on this feedback.

[1321] Example 2

[1322] 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."

[1323] Conventional contract clause analysis systems can summarize the contents of contract clauses and analyze risks, but they cannot provide information that takes into account the user's emotional state, making it difficult to provide information in a format that is easy for users to understand.In addition, there was a need for a system that could not only obtain the text of contract clauses from URLs or files entered by users, but also compare them with standard clauses and evaluate legal and economic risks in an integrated manner.

[1324] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for a user to input a URL or file of the terms and conditions, a means for acquiring the terms and conditions text from the URL or file, a means for summarizing the acquired terms and conditions text using a generation AI, a means for comparing it with a standard terms and conditions database, a means for analyzing legal and economic risks based on the terms and conditions, a means for evaluating the validity of the contract based on the user's prior information, a means for presenting the evaluation results and individual issues to the user, and a means for sensing the user's emotional state and dynamically providing information according to that state. This not only allows the user to quickly and accurately grasp the content of the contract terms and conditions and easily understand risks and points of caution, but also allows the user to receive information according to their emotional state.

[1325] "User" refers to a user who wishes to analyze the contract terms and conditions.

[1326] "URL" refers to the Uniform Resource Locator for specifying resources on the Internet.

[1327] A "file" refers to a collection of digital information stored in a particular format.

[1328] "Terms and Conditions Text" refers to the entire text of the contract terms and conditions.

[1329] "Generative AI" refers to artificial intelligence models that automatically generate natural language text.

[1330] "Summarizing" refers to shortening the original text and extracting only the important points.

[1331] "Standard clause database" refers to a database that contains commonly used contract clauses.

[1332] "Comparing" means placing two or more objects side by side to examine their differences and similarities.

[1333] "Legal and economic risk" refers to the possibility of disadvantage or loss from a legal or economic perspective.

[1334] "User's prior information" refers to personal information of the User that may affect the Agreement.

[1335] "Validity of a contract" refers to whether a contract is legally valid.

[1336] "Evaluate" means to judge the value or validity against specific criteria or conditions.

[1337] "Individual issues" refer to shortcomings or points requiring attention that exist in specific contract terms and conditions.

[1338] "Emotional state" refers to the emotional or psychological state a user has at a particular moment.

[1339] "Dynamic provision" refers to providing information in real time in response to changes in the situation or conditions.

[1340] This invention combines a system that uses generative AI to automatically analyze contract terms and conditions and provide important information to users with a function that recognizes the user's emotional state in real time and dynamically provides information. Specific embodiments are described below.

[1341] User Input

[1342] The user inputs the URL or file of the contract terms and conditions using a terminal. The user can either enter the URL into the input field of a web browser or dedicated application, or upload a saved PDF file. This provides the system with the contract terms and conditions that the user wants to analyze.

[1343] Obtaining and analyzing terms and conditions

[1344] The server issues an HTTP request to retrieve the terms and conditions text from the URL entered by the user, and retrieves the HTML document from the specified web page. The server extracts the text from the web page using an HTML parsing library (e.g., Beautiful Soup, lxml). If a file is uploaded, the server also extracts the text using a file parsing library such as Apache Tika.

[1345] Terms and conditions summary function

[1346] The server then uses a generative AI (e.g., GPT-4) to summarize the extracted text of the terms and conditions. This summary is generated using a natural language processing model to extract key points from the terms and conditions based on important keywords and phrases. For example, it generates a summary such as, "This contract is for a five-year contract, and the penalty is 10,000 yen."

[1347] Comparison function with standard clauses

[1348] The server compares the retrieved clause text with a database of standard clauses. It uses a comparison algorithm to identify differences and similarities and highlights unusual clauses or different terms. For example, if a clause stating "30 days' notice required for cancellation procedures" differs from the standard clause, the server identifies and highlights the difference.

[1349] Legal and economic risk analysis

[1350] The server analyzes legal and economic risks based on the contract text. It uses a risk assessment algorithm to evaluate financial risks based on clauses and contracts that may conflict with laws and regulations. For example, it identifies risks such as "high penalty fees and unfavorable terms for users" and reports them.

[1351] Contract validity based on applicant's prior information

[1352] Users enter their personal information (e.g., age, occupation, and place of residence), and the server uses that information to evaluate the validity of the contract and verify legal restrictions and applicable conditions. For example, it may issue a warning if the contract contains terms that are inappropriate for minors.

[1353] Presentation of individual problems

[1354] Based on the analysis results, the server presents specific issues and items that users should pay attention to. This includes listing unfavorable terms and points to be aware of, and generating detailed explanations and recommendations. For example, it lists issues such as "penalty clauses that are stricter than standard terms" and "automatic renewal terms that are difficult to understand."

[1355] Emotion Recognition and Dynamic Information Provision

[1356] The server is equipped with an emotion engine that analyzes the user's facial expressions and voice while they are entering data and displaying reports, recognizing their emotions. For example, if the emotion recognition result indicates that the user looks anxious, the server can provide additional information such as, "If the contract details are unclear, we recommend that you consult an expert."

[1357] Displaying the results

[1358] Finally, the server displays the generated report on the user's device. The report includes a summary, risk analysis results, comparison results with standard policy terms, points to note, and advice based on the user's emotional state. The user can click on links in the report to view more detailed information.

[1359] Examples of prompt statements

[1360] Below are some specific examples of prompt sentences to input to the generative AI model.

[1361] "The URL for the terms and conditions is below. Please summarize the key points of these terms. URL: [insert URL here]"

[1362] "Please analyze the contract terms and conditions contained in this PDF file and assess the risks. Please upload the PDF file."

[1363] "Please evaluate the validity of the contract based on the following personal information: Age: 25, Occupation: Company employee, Residence: Tokyo"

[1364] "Analyze the contract terms to see if they contain any unfavorable terms. Pay particular attention to any penalty fees or cancellation procedures."

[1365] By following these steps, the system helps users quickly and accurately understand the contents of complex contract terms, enabling them to proceed with the contract after understanding the risks and points to be aware of. In addition, by utilizing an emotion engine, information is provided according to the user's emotional state, greatly improving the user experience.

[1366] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1367] Step 1: User Input

[1368] The user uses the device to input the URL or file of the contract terms and conditions. Specifically, the user enters the URL into the input field of a web browser or dedicated application, or selects a saved PDF file in the device's file browser and clicks the upload button. This input provides the system with the contract terms and conditions data that the user wants to analyze. If there is a URL entered, that becomes the user's input, and the uploaded PDF file becomes the user's input.

[1369] Step 2: Obtain the terms and conditions

[1370] The server retrieves the clause text from the URL or file entered by the user. Specifically, if a URL is entered, the server issues an HTTP request to retrieve the HTML document from the specified web page. It then uses an HTML parsing library (e.g., Beautiful Soup, lxml) to extract the text from the retrieved HTML document. If a PDF file is uploaded, it uses a file parsing library such as Apache Tika to extract the text from the file. This retrieved text is the server's output.

[1371] Step 3: Text Summarization

[1372] The server summarizes the acquired text of the terms and conditions using a generation AI (e.g., GPT-4). Specifically, the acquired text is input into the generation AI along with the prompt, "Please summarize the main points of these terms and conditions." The generation AI generates a summary based on important keywords and phrases in the text. For example, it generates a summary such as, "This contract is for a five-year contract, and the penalty is 10,000 yen." This summary is provided to the user as the server's output.

[1373] Step 4: Compare with standard clauses

[1374] The server compares the retrieved clause text with a database of standard clauses. Specifically, it retrieves the standard clauses from the database and uses a comparison algorithm to identify differences and similarities between the retrieved clause text and the standard clauses. For example, if a clause such as "30 days' notice required for cancellation procedures" differs from the standard clauses, the difference is highlighted. The comparison results are provided to the user as server output.

[1375] Step 5: Legal and economic risk analysis

[1376] The server analyzes legal and economic risks based on the contract text. Specifically, it uses a risk assessment algorithm to evaluate clauses that may conflict with laws or regulations, as well as financial risks based on the contract (e.g., high penalty fees, unfair terms). For example, it identifies the risk that "penalties are high and terms are unfavorable to the user." The results of this risk assessment are provided to the user as the server's output.

[1377] Step 6: Assess contract validity

[1378] The user enters their personal information (e.g., age, occupation, and place of residence) into the terminal. The server evaluates the validity of the contract based on the input information. Specifically, it verifies whether the contract is valid according to legal restrictions and applicable conditions. For example, if the contract contains clauses that are inappropriate for minors, a warning about this is displayed. The evaluation result is provided to the user as the server's output.

[1379] Step 7: State the specific problem

[1380] Based on the analysis and comparison results, the server presents specific problems and items that users should pay attention to. Specifically, it lists unfavorable conditions and points to be aware of, and generates detailed explanations and recommendations. For example, it presents problems such as "the penalty clause is stricter than the standard terms and conditions" and "the automatic renewal conditions are difficult to understand." This list and recommendations are provided to the user as the server's output.

[1381] Step 8: Emotion recognition and dynamic information provision

[1382] The server is equipped with an emotion engine that analyzes the user's facial expressions and voice in real time while the user is entering data and while reports are being displayed. Specifically, it uses a webcam and microphone to sense the user's emotional state. For example, based on the emotion recognition result that "the user looks anxious," the server dynamically provides corresponding information. For example, it provides information such as "If the contract details are unclear, we recommend that you consult an expert." This information is dynamically provided as output from the server.

[1383] Step 9: View the results

[1384] Finally, the server displays the generated report on the user's device. Specifically, the report includes a summary of the policy, risk analysis results, comparison results with standard policy, points to note, and advice based on the user's emotional state. The user can check the report on their device and click links to view more detailed information. This report is provided to the user as the server's final output.

[1385] (Application example 2)

[1386] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1387] In today's world, when users sign contracts at brick-and-mortar stores, it is extremely difficult to quickly and accurately understand lengthy and complex contract terms and conditions and grasp the legal and economic risks involved. It is also difficult to determine whether the contract terms are appropriate for the user's individual circumstances. Furthermore, there is a lack of support that takes into account the user's emotional state during the contract process, which often results in users feeling anxious and confused. Technology that solves these issues is needed.

[1388] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: a means for a user to input a URL or file of the contract terms and conditions; a means for retrieving the text of the terms and conditions from the URL or file; a means for summarizing the retrieved text of the terms and conditions using a generation AI; a means for comparing the text with a standard terms and conditions database; a means for analyzing legal and economic risks based on the terms and conditions; a means for evaluating the validity of the contract based on the user's prior information; a means for presenting the evaluation results and individual issues to the user; a means for recognizing the user's emotional state; and a means for dynamically adjusting information provision based on the recognized emotional state. This allows users to quickly and accurately understand the contents of the contract terms and conditions, grasp legal and economic risks, and obtain information appropriate to their individual circumstances. Furthermore, the user experience is improved by providing support tailored to the user's emotional state.

[1389] "User" means any person or entity that uses the System to analyze contract terms and conditions.

[1390] "Contract terms and conditions" are documents that describe the contents of a contract and indicate the conditions and rules at the time of contract conclusion.

[1391] "URL" is an abbreviation for Uniform Resource Locator, and is an address that indicates the location of a resource such as a web page.

[1392] A "file" is a unit for storing digital data, and often refers to a digital document of contract terms and conditions.

[1393] "Generative AI" refers to an artificial intelligence model that automatically generates and analyzes text, and is used for natural language processing, etc.

[1394] "Summarizing" means extracting the important parts from a long piece of text and reconstructing them in a concise form.

[1395] The "standard clause database" is a database that stores commonly used standard contract clauses.

[1396] To compare means to put two or more elements side by side to reveal their similarities and differences.

[1397] "Legal and economic risk" refers to the possibility of violating laws and regulations or incurring financial loss.

[1398] "Prior information" refers to personal information and background information provided by the user in advance.

[1399] "Validity of a contract" is the standard for determining whether a contract is legally and practically valid.

[1400] "Evaluation results" are the results generated by the system after analysis and comparison.

[1401] "Specific issues" are issues or considerations that are unique to a particular contract or situation.

[1402] "Emotional state" refers to the user's psychological state or feeling, including anxiety, joy, interest, etc.

[1403] "Recognizing" means that the system obtains information from the user's facial expressions, voice, etc. and understands it.

[1404] "Dynamic adjustment" means changing the information provided in real time according to the situation and conditions.

[1405] This invention is a system that enables users to quickly and accurately understand contract terms and conditions, grasp legal and economic risks, and provide information appropriate to individual circumstances when signing a contract at a physical store. Specific embodiments for carrying out the invention are described below.

[1406] 1. System Overview

[1407] The system analyzes the URL or file of the contract terms entered by the user, summarizes it using generation AI, and compares it with a database of standard contract terms. It also has the function of evaluating the validity of the contract based on the user's personal information and presenting the evaluation results and individual problems. It also recognizes the user's emotional state and dynamically adjusts the information provided based on that state.

[1408] 2. Acquisition and analysis of contract terms

[1409] The server issues an HTTP request to the URL of the contract terms entered by the user and retrieves the HTML document from the specified web page. To parse the HTML document, it uses an HTML parsing library such as BeautifulSoup. If the user has uploaded a file, it extracts the text from the file using the Apache Tika library.

[1410] 3. Summary of Terms and Conditions

[1411] The retrieved contract text is summarized using a generative AI model (e.g., GPT-4), using the following prompt:

[1412] "Please summarize the following contract, including important clauses and risk points to be aware of: {Full contract}"

[1413] 4. Comparison with standard terms and conditions

[1414] The server compares the retrieved policy text with a standard policy database and uses a comparison algorithm (e.g., a text similarity algorithm) to identify differences and similarities.

[1415] 5. Risk Analysis and Effectiveness Assessment

[1416] The server uses risk assessment algorithms to assess legal and financial risks, and evaluates the validity of the contract based on the user's previously entered personal information (e.g., age, occupation, place of residence), using criteria based on laws and regulations.

[1417] 6. Emotion Recognition and Dynamic Information Provision

[1418] When a user is using smart glasses or a head-mounted display, these devices capture the user's facial expressions and voice and use an emotion engine (e.g., the EmotionDetector library) to recognize the user's emotional state in real time. The server dynamically adjusts the information provided according to the recognized emotional state, for example, providing more detailed explanations or additional information if the user looks anxious.

[1419] 7. Displaying the results

[1420] Finally, the server displays the generated report on the user's device. The report includes a summary, risk analysis, comparison with standard terms and conditions, individual issues, and advice based on the user's emotional state. The user can check detailed information on their device, and information reflecting feedback from the emotion engine is provided.

[1421] This system allows users to complete the contract process in a physical store smoothly and safely, and also improves the user experience by providing information tailored to the user's emotional state.

[1422] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1423] Step 1:

[1424] The user inputs the URL or file of the contract terms into the terminal. The user can either enter the URL into the input field of a web browser or dedicated application, or upload a saved PDF file. This provides the contract terms to the system for analysis.

[1425] Input: URL or PDF file

[1426] Output: Agreement data to be analyzed

[1427] Step 2:

[1428] The server issues an HTTP request to retrieve the contract terms text from the URL entered by the user, retrieves the HTML document from the specified web page, and extracts the text using an HTML parsing library (e.g., BeautifulSoup).

[1429] Input: Entered URL

[1430] Output: Contract terms text extracted from HTML document

[1431] Step 3:

[1432] For user uploaded files, the server uses the Apache Tika library to extract the text from the file.

[1433] Input: Uploaded PDF file

[1434] Output: Contract terms text extracted from PDF file

[1435] Step 4:

[1436] The server summarizes the contract terms and conditions using a generative AI model (e.g., GPT-4). The generative AI model uses the following prompt: "Please summarize the following contract. Please include important clauses and risk points to be aware of: {Full contract}"

[1437] Input: Contract terms text

[1438] Output: Abridged contract terms text

[1439] Step 5:

[1440] The server compares the retrieved policy text with a standard policy database, using a comparison algorithm to identify differences and similarities.

[1441] Input: Abridged contract terms text

[1442] Output: Comparison results with standard terms and conditions

[1443] Step 6:

[1444] The server uses a risk assessment algorithm to assess the legal and financial risks involved in the contract.

[1445] Input: Abridged contract terms text

[1446] Output: Risk assessment results

[1447] Step 7:

[1448] The server evaluates the validity of the contract based on the user's prior information (e.g., age, occupation, place of residence), and determines whether it is valid using evaluation criteria based on laws and regulations.

[1449] Input: User's prior information

[1450] Output: Contract validity evaluation result

[1451] Step 8:

[1452] The server presents the evaluation results and specific issues to the user, including any adverse conditions or caveats associated with the particular contract.

[1453] Input: Risk assessment results, contract validity assessment results

[1454] Output: Evaluation results and individual problems presented to the user

[1455] Step 9:

[1456] When a user is wearing smart glasses or a head-mounted display, the device captures the user's facial expressions and voice, and the server uses an emotion engine to recognize the user's emotional state in real time.

[1457] Input: User's facial expressions and voice data

[1458] Output: Perceived emotional state of the user

[1459] Step 10:

[1460] The server dynamically adjusts the information provided depending on the user's perceived emotional state, for example by providing more detailed explanations or additional information if the user appears anxious.

[1461] Input: Perceived emotional state of the user

[1462] Output: Dynamically adjusted informational

[1463] Step 11:

[1464] Finally, the server displays the generated report on the user's terminal, which includes a summary result, risk analysis result, comparison result with standard policy terms, individual problems, and advice according to the user's emotional state.

[1465] Input: Summary results, Risk analysis results, Comparison results, User's emotional state

[1466] Output: The generated report displayed on the user's terminal

[1467] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1468] 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.

[1469] 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 robot 414.

[1470] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1471] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1472] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1473] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1474] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1475] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1476] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1477] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1478] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1479] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1480] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1481] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1482] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1483] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1484] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1485] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1486] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1487] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1488] The following is further disclosed regarding the above embodiment.

[1489] (Claim 1)

[1490] A means for the user to input the URL or file of the terms and conditions;

[1491] means for retrieving the clause text from the URL or file;

[1492] A means for summarizing the acquired clause text using a generation AI;

[1493] a means of comparison with a standard clause database;

[1494] A means of analyzing legal and economic risks under the terms and conditions;

[1495] a means for assessing the validity of the contract based on the user's prior information;

[1496] A means for presenting the evaluation results and individual problems to the user;

[1497] A system including:

[1498] (Claim 2)

[1499] The system according to claim 1, wherein the results of summarizing the acquired clause text are based on specific keywords or phrases.

[1500] (Claim 3)

[1501] 10. The system of claim 1, wherein a comparison algorithm is used to identify differences and similarities when comparing with a standard policy database.

[1502] (Claim 4)

[1503] 10. The system of claim 1, wherein a risk assessment algorithm is used to analyze legal and financial risks.

[1504] (Claim 5)

[1505] 10. The system of claim 1, further comprising verifying the validity of the contract based on prior information provided by the user and in accordance with legal constraints and applicable conditions.

[1506] "Example 1"

[1507] (Claim 1)

[1508] A means for the user to input the URL or file of the terms and conditions;

[1509] means for retrieving the clause text from the URL or file;

[1510] A means for extracting the acquired clause text using a data analysis means;

[1511] A means for summarizing the extracted clause text using a generative AI model; and

[1512] a means of comparison with a standard clause database;

[1513] A means of assessing legal and economic risks under the terms and conditions;

[1514] means for assessing the validity of the contract based on the user's personal data;

[1515] A means for presenting the evaluation results and individual problems to the user;

[1516] means for displaying the evaluation results on a user's terminal by a display device;

[1517] A system including:

[1518] (Claim 2)

[1519] The system according to claim 1, wherein the results of summarizing the acquired clause text are based on specific keywords or phrases.

[1520] (Claim 3)

[1521] 10. The system of claim 1, wherein a comparison algorithm is used to identify differences and similarities when comparing with a standard policy database.

[1522] "Application Example 1"

[1523] (Claim 1)

[1524] A means for the user to input a link or file of the terms and conditions;

[1525] means for retrieving the terms and conditions text from said link or file;

[1526] A means for summarizing the acquired clause text using a generation AI;

[1527] a means of comparison with a standard clause database;

[1528] A means of analyzing legal and economic risks under the terms and conditions;

[1529] a means for assessing the validity of the contract based on the user's prior information;

[1530] A means for presenting the evaluation results and individual problems to the user;

[1531] A means for displaying the analysis results of the contract terms and conditions on the user's device;

[1532] A system including:

[1533] (Claim 2)

[1534] The system according to claim 1, wherein the results of summarizing the acquired clause text are based on specific keywords or phrases.

[1535] (Claim 3)

[1536] 10. The system of claim 1, wherein a comparison algorithm is used to identify differences and similarities when comparing with a standard policy database.

[1537] "Example 2: Combining Emotion Engines"

[1538] (Claim 1)

[1539] A means for the user to input the URL or file of the terms and conditions;

[1540] means for retrieving the clause text from the URL or file;

[1541] A means for summarizing the acquired clause text using a generation AI;

[1542] a means of comparison with a standard clause database;

[1543] A means of analyzing legal and economic risks under the terms and conditions;

[1544] a means for assessing the validity of the contract based on the user's prior information;

[1545] A means for presenting the evaluation results and individual problems to the user;

[1546] means for sensing a user's emotional state and dynamically providing information according to that state;

[1547] A system including:

[1548] (Claim 2)

[1549] The system according to claim 1, wherein the results of summarizing the acquired clause text are based on specific keywords or phrases.

[1550] (Claim 3)

[1551] 10. The system of claim 1, wherein an algorithm is used to identify differences and similarities when comparing with a standard policy database.

[1552] "Application example 2 when combining emotion engines"

[1553] (Claim 1)

[1554] A means for the user to input the URL or file of the terms and conditions;

[1555] means for retrieving the clause text from the URL or file;

[1556] A means for summarizing the acquired clause text using a generation AI;

[1557] a means of comparison with a standard clause database;

[1558] A means of analyzing legal and economic risks under the terms and conditions;

[1559] a means for assessing the validity of the contract based on the user's prior information;

[1560] A means for presenting the evaluation results and individual problems to the user;

[1561] a means for recognizing the emotional state of a user;

[1562] a means for dynamically adjusting information provision in response to the perceived emotional state;

[1563] A system including:

[1564] (Claim 2)

[1565] The system according to claim 1, wherein the results of summarizing the acquired clause text are based on specific keywords or phrases.

[1566] (Claim 3)

[1567] 10. The system of claim 1, wherein a comparison algorithm is used to identify differences and similarities when comparing with a standard policy database. [Explanation of symbols]

[1568] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for the user to input the URL or file of the terms and conditions; means for retrieving the clause text from the URL or file; A means for summarizing the acquired clause text using a generation AI; a means of comparison with a standard clause database; A means of analyzing legal and economic risks under the terms and conditions; a means for assessing the validity of the contract based on the user's prior information; A means for presenting the evaluation results and individual problems to the user; A system including:

2. 2. The system according to claim 1, wherein the results of summarizing the acquired clause text are based on specific keywords or phrases.

3. 10. The system of claim 1, wherein a comparison algorithm is used to identify differences and similarities when comparing with a standard policy database.

4. 10. The system of claim 1, wherein a risk assessment algorithm is used to analyze legal and financial risks.

5. 10. The system of claim 1, further comprising: verifying the validity of the contract based on prior information provided by the user and in accordance with legal restrictions and applicable conditions.

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