System

Abstract

A system is provided.SOLUTION: This system includes a means for acquiring clause information, a means for analyzing the acquired clause information and automatically detecting a change point, a means for summarizing the detected change point and displaying it to a user, and a means for accepting clause evaluation by the user and disclosing an evaluation result.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In modern society, many individuals use smartphones and the internet on a daily basis to access a variety of online services. However, using these services requires agreeing to contracts and terms and conditions, which are often very complex and lengthy, making them difficult to fully understand. As a result, users often agree without fully understanding the terms, potentially exposing themselves to risks such as personal information leaks and inappropriate data use. Furthermore, there are few ways for users to evaluate and share their opinions on contracts, making it difficult for other users to use them as reference. Furthermore, companies may be unable to fully utilize user feedback, hindering service quality improvements. To address these issues, a system is needed to easily understand changes to terms and conditions and clarify risks, as well as to create an environment that makes it easy for users to share their opinions. [Means for solving the problem]

[0005] The present invention provides a system that automatically detects changes in terms of use and displays a summary that is easy for users to understand. The system also provides a means for users to evaluate terms of use and publish the results, creating an environment for sharing information that can be used as reference by other users.

[0006] The above problem is solved by including a means for acquiring clause information, a means for analyzing the acquired clause information and automatically detecting changes, a means for summarizing the detected changes and displaying them to the user, a means for accepting clause evaluations by users and publishing the evaluation results, a means for selecting highly reliable services and applications based on the evaluation results and displaying them in a dedicated store, and a means for analyzing the evaluations and reviews collected from users and generating an improvement proposal report for companies based on the analysis results. This allows users to easily grasp risks and use services with peace of mind, while also allowing service providers to receive accurate feedback and improve service quality.

[0007] "Terms and conditions information" refers to documents that describe the terms of use, privacy policy, and other contractual conditions that a service provider presents to users.

[0008] "Means of acquisition" refers to the technology or method by which a server collects information from designated web pages or databases via the Internet.

[0009] "Means of analysis" refers to algorithms or programs used to analyze acquired information and understand its content and structure.

[0010] "Means for detecting changes" refers to techniques or methods for comparing previously collected information with newly acquired information and recognizing differences.

[0011] The "means for summarizing and displaying" refers to a display method or interface for concisely summarizing the changes and presenting them in a format that can be intuitively understood by the user.

[0012] The "means for accepting user ratings" refers to a form or interface that allows users to input and collect ratings and opinions about the service and its terms and conditions.

[0013] "Means for publishing evaluation results" refers to a system or method for saving and displaying user evaluations in a form that can be viewed by other users.

[0014] "Means for selecting reliable services and applications" refers to technologies and methods for identifying safe and high-quality services and applications based on published evaluation results and other criteria.

[0015] "Means for displaying in a dedicated store" means a system or method for listing selected services or applications so that they can be used on a dedicated online platform and providing them to users.

[0016] "Means for analyzing ratings and reviews" refers to algorithms and programs that statistically and content-wise analyze ratings and impressions collected from users and extract useful information.

[0017] The "means for generating improvement proposal reports for businesses" refers to techniques and methods for creating reports that summarize specific improvement proposals for service providers based on the analysis results. [Brief explanation of the drawings]

[0018] [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

[0019] 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.

[0020] First, the terms used in the following description will be explained.

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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."

[0039] This invention is a system that automatically acquires and analyzes terms of use (terms and conditions) presented by online service providers, and displays a summary in an easy-to-understand format for users. It also has the functionality to receive user ratings, evaluate reliability based on those ratings, and provide improvement suggestions to companies. Below, we will explain how to specifically implement this system.

[0040] Overall system overview

[0041] The system has the following main functions:

[0042] 1. A function that automatically acquires and analyzes clause information to detect changes.

[0043] 2. Ability to summarize detected changes and notify the user.

[0044] 3. Ability to collect and publish user ratings.

[0045] 4. The ability to select reliable services and applications and display them in a dedicated store.

[0046] 5. A function that makes improvement suggestions to companies based on user ratings and reviews.

[0047] Automatic acquisition and analysis of clause information

[0048] The server periodically accesses a pre-registered web page (terms of service page) to retrieve the text data of the terms of service. The retrieved data is then sent to an analysis engine, which compares it with existing data to detect changes. For example, if a music streaming service revises part of its terms of service, the engine compares the old and new terms and automatically identifies changes to the data usage policy.

[0049] Risk Summary and Notification

[0050] The detected changes are summarized by the generative AI and the associated risks are explained in an easy-to-understand manner. The server stores the summarized information in a database, allowing users to review the information based on their own profile. Users can view the risk summary through their devices and intuitively understand it.

[0051] Collecting and publishing user ratings

[0052] Using a device, users access the service's terms of service page and use the interface to submit a rating. The rating includes a star rating and comments, which are then sent to the server. The server then stores the rating data in a database, making public ratings available to other users.

[0053] Selection and display of reliable services and applications

[0054] The server selects reliable services and applications based on the collected evaluation data, and displays these reliable services and applications in a dedicated online store, allowing users to download and install them with confidence.

[0055] Improvement proposals for companies

[0056] The server analyzes user ratings and reviews to identify common problems and areas for improvement. Based on this, an improvement proposal report is generated and provided to the service provider. For example, if multiple users have the same complaints about a particular feature, the server analyzes their feedback and makes appropriate improvement proposals.

[0057] Specific examples

[0058] For example, when a user signs up for a new video streaming service, the server automatically retrieves and analyzes the service's terms of service. The generative AI summarizes any important changes to the terms (e.g., updates to the privacy policy). This information is then notified to the user via their device. The user then reviews the summary and rates the terms. This rating is then sent to the server and made public for other users to refer to.

[0059] This system allows users to easily understand the terms of use and risks involved, creating an environment where they can use services with peace of mind. It also enables service providers to continuously improve the quality of their services based on user feedback.

[0060] The processing flow will be explained below.

[0061] Step 1:

[0062] The server executes a program that periodically accesses the terms of use page of a pre-registered Web service.

[0063] Step 2:

[0064] The server acquires the latest terms of use text data from the terms of use page and stores it in a database.

[0065] Step 3:

[0066] The server sends the latest obtained terms of use text data to the analysis engine.

[0067] Step 4:

[0068] The analysis engine compares the newly acquired terms of use text data with existing data and automatically detects changes.

[0069] Step 5:

[0070] The analysis engine sends the detected changes to the generation AI.

[0071] Step 6:

[0072] The generative AI evaluates the importance of the changes and generates a summary text.

[0073] Step 7:

[0074] The server stores the generated summary text in a risk assessment database.

[0075] Step 8:

[0076] The server notifies a particular user of a risk summary based on the user's profile information.

[0077] Step 9:

[0078] The user uses the terminal to check the risk summary notice.

[0079] Step 10:

[0080] The user accesses an interface to review the risk summary and evaluate the terms.

[0081] Step 11:

[0082] The terminal displays an input form for rating the regulations, allowing the user to input ratings and comments.

[0083] Step 12:

[0084] The user inputs a rating and a comment and submits it.

[0085] Step 13:

[0086] The server receives the evaluation data sent by the user and stores it in an evaluation database.

[0087] Step 14:

[0088] The server posts the evaluation in a public evaluation database so that other users can refer to the evaluation results.

[0089] Step 15:

[0090] The server selects highly reliable services and applications based on published evaluation data.

[0091] Step 16:

[0092] The server displays the selected services and applications in a dedicated store and makes them available to users.

[0093] Step 17:

[0094] Users using the device can access a dedicated store to view and download selected services and applications.

[0095] Step 18:

[0096] The server continuously analyzes user reviews and ratings to identify common problems and areas for improvement.

[0097] Step 19:

[0098] The analysis engine generates a report of specific improvement proposals based on the extracted problems and areas for improvement.

[0099] Step 20:

[0100] The server sends the generated improvement suggestion report to the company and provides feedback for service improvement.

[0101] Example 1

[0102] 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."

[0103] In modern Internet services, changes to terms of use are frequent, making it difficult for users to understand and evaluate the changes. Furthermore, there is a lack of objective criteria for selecting reliable services, and no mechanism exists for service providers to effectively incorporate user feedback into improvement proposals. This often leaves users feeling uneasy about using services, and service providers find it difficult to make appropriate improvements.

[0104] 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.

[0105] In this invention, the server includes means for acquiring terms and conditions information, means for analyzing the acquired terms and conditions information and automatically detecting changes, means for summarizing the detected changes using a generative AI model and displaying them to the user, and means for accepting user evaluations of the terms and conditions and publishing the evaluation results. This enables users to easily understand and evaluate changes to the terms and conditions, enabling them to select highly reliable services and propose appropriate improvements to service providers.

[0106] "Terms and conditions information" is a document containing the terms and conditions that a service provider presents to users.

[0107] "Means" refers to a method or apparatus for achieving a specific function or operation.

[0108] A "server" is a computer system that manages, processes, and distributes data over a network.

[0109] "User" refers to any individual or entity using the Service.

[0110] "Acquisition" is the act of collecting or obtaining necessary data or information.

[0111] "Analysis" is the process of examining data or information in detail to understand its meaning and structure.

[0112] "Changes" refers to the differences or modifications between the two documents or data being compared, old and new.

[0113] A "generative AI model" is a model that uses artificial intelligence technology to automatically generate text.

[0114] "Summarizing" refers to the process of summarizing detailed information concisely to extract only the main points.

[0115] "Evaluation" is the act of judging performance or value based on specific criteria and giving a score or comment.

[0116] "Publication" refers to making certain information publicly accessible.

[0117] "Reliability" refers to the ability and characteristics of a service or system to operate stably and as expected.

[0118] "Service" means an application or online platform that offers specific functionality or benefits.

[0119] "Selection" is the act of choosing the best one based on specific criteria.

[0120] "Exclusive Store" refers to an online platform that offers only selected specific applications and services.

[0121] A "review" is an act in which a user writes their opinion or impression about a service or product.

[0122] "Improvement proposals" are specific proposals for solving existing problems and improving performance and user experience.

[0123] A "report" is a document that systematically compiles specific information.

[0124] This invention relates to a system that automatically detects changes in terms of use for Internet services, summarizes them, and presents them to users, and selects and provides more reliable services. The invention is realized through processing steps mainly involving a server, a terminal, and a user.

[0125] Overall structure

[0126] The system includes the following main features:

[0127] 1. Automatic Acquisition of Terms of Use

[0128] 2. Analysis of changes to the Terms of Use

[0129] 3. Generate a summary of changes

[0130] 4. Summary storage and notification

[0131] 5. Collection and publication of user ratings

[0132] 6. Select a reliable service

[0133] 7. Generating improvement proposals for companies

[0134] Hardware and Software

[0135] The server works in conjunction with a database and natural language processing engine to automatically retrieve terms of use, analyze them, detect changes, generate summaries using a generative AI model, provide notifications, collect and publish ratings, select reliable services, and generate improvement proposal reports for companies.

[0136] As a specific example, the analysis engine can use a natural language processing toolkit such as NLTK or spaCy. For the generative AI, OpenAI (registered trademark) GPT is used as the generative AI model. For the database, an SQL database or a NoSQL database can be used.

[0137] The terminal provides an interface for users to view summary information and evaluation results and input their own evaluations. Terminals include various devices such as smartphones, tablets, and PCs.

[0138] Users can check the summary of terms of service, rate and review the terms of service, and use a dedicated store to select reliable services.

[0139] Specific examples of processing

[0140] For example, when a user signs up for a new video streaming service, the server processes the following:

[0141] 1. The server accesses the terms of use page for that service and retrieves the HTML content.

[0142] 2. The retrieved content is analyzed using a natural language processing toolkit to detect changes.

[0143] 3. The changes are fed into a generative AI model to generate a summary.

[0144] 4. The server stores the generated summary in a database and notifies the user based on their profile.

[0145] 5. The user receives the notification through their device, checks the summary, and gives a rating, which is sent to the server and stored in the database.

[0146] Prompt Sentence Examples

[0147] "I've signed up for a new video streaming service. If the terms of service for this service change, I'd like to be notified with a summary of the changes. I'd also like to see other users' reviews."

[0148] This allows users to easily understand the terms of service and their changes, and to make appropriate evaluations. It also allows service providers to improve their services based on user feedback. This system increases user convenience and improves reliability.

[0149] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0150] Step 1:

[0151] The server periodically accesses a pre-registered web page (terms of use page) and retrieves HTML content. This operation is performed by sending an HTTP request and receiving HTML data as a response. The input is a list of URLs, and the output is the retrieved HTML content.

[0152] Step 2:

[0153] The server parses the retrieved HTML content and extracts the terms of use text data. It uses a parsing library (e.g. BeautifulSoup) to extract text from HTML. The input is the HTML content, and the output is the terms of use text data.

[0154] Step 3:

[0155] The server sends the retrieved terms of use text to an analysis engine (for example, natural language processing toolkits such as NLTK or spaCy), which compares the old and new data to detect changes. The input is the old and new terms of use text data, and the output is a list of changes.

[0156] Step 4:

[0157] The server inputs the list of changes into a generative AI model and generates a text summary of them. The summary is created using a generative AI model (e.g., OpenAI GPT). The input is the list of changes, and the output is a summarized risk description text.

[0158] Step 5:

[0159] The server saves the generated summary text to a database. This operation is performed by inserting the summary data into a specific table using a database connection library. The input is the summary text and the user's profile information, and the output is a flag indicating whether the save operation to the database was successful.

[0160] Step 6:

[0161] The server notifies the user to view information based on their profile. Notifications can be sent via email, push notification, or in-app notification. The input is the user's profile information and summary text, and the output is the notification sending status.

[0162] Step 7:

[0163] The user receives the notification through the terminal and views the summary information. The summary text is displayed on the terminal interface. The input is the notification message, and the output is the user's browsing history.

[0164] Step 8:

[0165] Users rate the terms of use and input their rating results. Star ratings and comments are recorded through the rating interface. The input is rating data (star ratings and comments), and the output is a rating record.

[0166] Step 9:

[0167] The server saves the evaluation results sent by users in a database and makes them publicly accessible to other users. This is also an operation that inserts and publishes evaluation data using the database connection library. The input is the evaluation data, and the output is a public evaluation dataset.

[0168] Step 10:

[0169] The server selects reliable services and applications based on the collected reputation data. This is the process of analyzing the reputation data and identifying services with high reputations. The input is a reputation dataset, and the output is a list of reliable services.

[0170] Step 11:

[0171] The server displays the selected reliable services in a dedicated store by inserting them into a display table in the database. The input is a list of reliable services, and the output is a display item in the dedicated store.

[0172] Step 12:

[0173] The server analyzes the ratings and reviews collected from users and extracts common problems and areas for improvement. This analysis is performed using a natural language processing toolkit. The input is the text data of the ratings and reviews, and the output is a list of the extracted problems and areas for improvement.

[0174] Step 13:

[0175] The server uses a generative AI model to generate an improvement proposal report for the company based on the extracted problems and improvement points. The input is a list of problems and improvement points, and the output is an improvement proposal report.

[0176] (Application example 1)

[0177] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0178] The frequent changes in terms of service for online services such as content distribution services make it difficult for users to understand the content. Users also have difficulty grasping the risks posed by changes in terms of service, leading to concerns about the reliability of the service. Furthermore, there is a lack of means to accurately reflect user feedback and improve the service.

[0179] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0180] In this invention, the server includes a means for acquiring terms and conditions information, a means for analyzing the acquired terms and conditions information and automatically detecting changes, a means for summarizing the detected changes using a generative AI model and displaying them to the user, a means for accepting user evaluations of the terms and conditions and publishing the evaluation results, and a means for recommending reliable content distribution services. This allows users to intuitively understand changes to the terms and conditions and the risks involved, and select reliable services. The server also includes a means for analyzing the evaluations and reviews collected from users using a generative AI model and generating improvement proposal reports for companies, enabling service providers to continuously improve their services based on user feedback.

[0181] A "server" is a computer system that receives requests over a network and provides data or services.

[0182] The "means for acquiring terms and conditions information" is a function that automatically collects text data of terms of use from the web page of the content distribution service.

[0183] "Means for automatically detecting changes by analyzing terms and conditions information" is a function that compares the old and new terms of use and identifies changes within the terms and conditions.

[0184] "Means for summarizing and displaying to the user using a generative AI model" is a function that uses AI technology to summarize detected changes and displays the summary in an easy-to-read format for the user.

[0185] The "means for accepting user evaluations of terms and conditions and publishing the evaluation results" is a function that allows users to submit evaluations and comments on the terms and conditions and publish the evaluations in a form that can be viewed by other users.

[0186] The "means for recommending highly reliable content distribution services" is a function that selects safe and highly reliable content distribution services based on collected user evaluation data and recommends them to users.

[0187] The "analysis means" is a function that analyzes collected user ratings and reviews and identifies areas for improvement in the service based on the results.

[0188] The "means for generating improvement proposal reports for companies" is a function that automatically creates reports that make specific improvement proposals to service providers based on user feedback.

[0189] This invention is a system that provides an environment in which users can use content distribution services with peace of mind by automatically acquiring, analyzing, summarizing, and evaluating terms of use. The following describes how to specifically implement this system.

[0190] Overall flow

[0191] First, the server periodically retrieves the text data of the terms of use from the web page of the content distribution service via the network. This is done using the Python libraries "requests" and "BeautifulSoup." The retrieved text data is then compared with old data, and changes are automatically detected using the "difflib" library.

[0192] The detected changes are then summarized using a generative AI model, using AI techniques such as GPT-4®, and the summary is sent to the user's device, allowing them to intuitively understand the changes.

[0193] Users can use their devices to rate the terms of use and submit their evaluation comments. This evaluation data is stored on the server and can be accessed by other users.

[0194] Furthermore, the server analyzes the evaluation data and selects and recommends reliable content delivery services. To do this, it uses "SQLAlchemy" to manage the database and analyze the evaluation data.

[0195] Finally, the collected user ratings and reviews are analyzed using the generative AI model again to create a report with specific improvement proposals for the company. This report is provided to the service provider to support continuous service improvement.

[0196] Hardware and software used

[0197] Server: The central computer system that retrieves and processes data from the web pages of a content delivery service.

[0198] Device: The device used by the user, such as a smartphone, computer, or tablet.

[0199] software:

[0200] Python: Overall program control.

[0201] BeautifulSoup, requests: Get text data from web pages.

[0202] difflib: Detect changes in text data.

[0203] GPT-4 (OpenAI API): Generates summaries using a generative AI model.

[0204] Firebase Cloud Messaging (FCM): Sends notifications to users.

[0205] Flask, SQLAlchemy: Server-side data management and API construction.

[0206] Specific examples

[0207] 1. The server accesses the web page of a specific content distribution service and obtains the terms of use in text format.

[0208] 2. Analyze the old and new terms of use data and detect changes.

[0209] 3. Use a generative AI model (e.g., GPT-4) to summarize the changes and create a summary.

[0210] 4. The summary is sent to the user's device using FCM.

[0211] 5. Users will receive a notification and review and evaluate the changes to the Terms of Use.

[0212] 6. The server collects evaluation data from users and selects and recommends reliable services.

[0213] 7. Furthermore, the system reanalyzes user ratings and reviews to generate a report with specific improvement suggestions for the service provider.

[0214] Prompt Sentence Examples

[0215] "Please summarize the following changes to the terms and conditions and explain their risks.

[0216] New Terms: [New Terms Text]

[0217] Old Terms: [old terms text]"

[0218] This system allows users to easily understand the terms of use and risks involved, enabling them to use content distribution services with peace of mind. It also enables service providers to continuously improve their services based on user feedback.

[0219] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0220] Step 1:

[0221] The server accesses the web page of a specific content distribution service and retrieves the text data of the terms of use. Specifically, it uses the Python "requests" and "BeautifulSoup" libraries to scrape the terms of use text from this web page. The input of this step is the URL of the web page, and the output is the retrieved text data of the terms of use.

[0222] Step 2:

[0223] The server compares the retrieved text data of the terms of use with the existing data to detect changes. The "difflib" library is used to detect changes. The input is the old and new terms of use text, and the output is differential information indicating the changes. In this data processing process, the old and new texts are compared line by line, and the different parts are extracted.

[0224] Step 3:

[0225] The server summarizes the detected changes using a generative AI model. AI technologies such as GPT-4 are used for generation. Specifically, the changes are sent as input data to the OpenAI API, and the summarized text is received as output. The input is difference information, and the output is the summarized changes.

[0226] Step 4:

[0227] The server notifies the user's device of the summarized changes. This notification uses Firebase Cloud Messaging (FCM). The input is the text of the summarized changes, and the output is a notification that is displayed on the user's device. The server obtains the user's device ID and sends the notification message via FCM.

[0228] Step 5:

[0229] The user uses the terminal to check the changes to the terms of use and rate the terms. The rating can include star ratings and comments. The input is a summary of the changes and the user's rating information, and the output is the rating data. The terminal receives the input from the user through a rating interface.

[0230] Step 6:

[0231] The server stores the evaluation data collected from users in a database and selects reliable content delivery services. "SQLAlchemy" is used for database management. The input is user evaluation data, and the output is a list of reliable services. The server scores the evaluation data and lists the services with the highest scores.

[0232] Step 7:

[0233] The server uses a generative AI model to analyze the ratings and reviews collected from users and generate a report of specific improvement proposals for the company. GPT-4 is again used for the analysis. The input is the user's rating data and reviews, and the output is a report of improvement proposals. The server sends the ratings and reviews to the AI ​​model and compiles the generated improvement proposals for the company.

[0234] Through each step of this process, the system enables users to intuitively understand the content and risks of the terms of use, helps them select reliable services, and allows service providers to continuously improve their services based on user feedback.

[0235] 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.

[0236] This invention is a system that combines an emotion engine that recognizes user emotions, and has the function of automatically acquiring and analyzing terms of use (terms and conditions) presented by online service providers, and displaying a summary of any changes. It also has the function of providing user ratings, reliability assessments based on those ratings, and suggesting improvements to companies. Below, we will explain how to specifically implement this system.

[0237] Overall system overview

[0238] The system has the following main functions:

[0239] 1. A function that automatically acquires and analyzes clause information to detect changes.

[0240] 2. Ability to summarize detected changes and notify the user.

[0241] 3. The ability to recognize user sentiment and customize risk summaries based on that data.

[0242] 4. A function to collect user ratings and publish the results.

[0243] 5. Ability to select reliable services and applications and display them in a dedicated store.

[0244] 6. Ability to use user sentiment data to improve the reliability of ratings.

[0245] 7. A function that makes improvement suggestions to companies based on user ratings and reviews.

[0246] Automatic acquisition and analysis of clause information

[0247] The server periodically accesses a pre-registered web page (terms of use page) and retrieves the text data of the terms of use. The retrieved data is sent to an analysis engine, which compares it with existing data to detect changes. For example, if a social networking service revise its terms of use, the old and new terms are compared and changes regarding the handling of user data are automatically identified.

[0248] Risk summary and emotion-aware notification

[0249] The server uses generative AI to summarize the detected changes and clearly explain the risks. The emotion engine also works to retrieve past emotional data from the user's profile and customize the risk summary notification accordingly. For example, a user who has previously expressed strong concerns about data leaks will receive notifications that specifically highlight changes related to data security.

[0250] Collecting and publishing user ratings

[0251] Using a device, users access the service's terms of use page and use the interface to rate the service. The rating includes a star rating and comments, and is sent to the server. The server stores the rating data in a database so that other users can refer to public ratings.

[0252] Selection and display of reliable services and applications

[0253] The server comprehensively evaluates the collected evaluation data and emotion data to select highly reliable services and applications. These highly reliable services and applications are displayed in a dedicated online store, allowing users to use them with peace of mind.

[0254] Improving the reliability of ratings using user emotions

[0255] The emotion engine collects emotional data from users at the time of rating and uses that data to verify the reliability of the ratings. For example, if a particular rating is extremely high, it may determine that the user is overly excited and may discount that rating.

[0256] Improvement proposals for companies

[0257] The server analyzes user ratings, reviews, and sentiment data to identify common issues and areas for improvement. Specific improvement proposal reports are then provided to the service provider. For example, if multiple users express concerns about a new pricing plan, the server can suggest reconsidering the plan based on that feedback.

[0258] Specific examples

[0259] For example, when a user signs up for a new cloud storage service, the server automatically retrieves and analyzes the service's terms of use to detect any changes. The generative AI summarizes important changes to the terms (e.g., changes to data retention periods), and this information is passed through an emotion engine to notify the user in a format appropriate for them. The user then checks the notification and rates the service. This rating is made public for other users to view, and the service is displayed in a dedicated store as a reliable service. Companies can use the provided improvement proposal report to improve their services.

[0260] This system allows users to easily understand the terms of use, understand the risks, and use the service with peace of mind. It also enables service providers to continuously improve the quality of their services based on user feedback and sentiment data.

[0261] The processing flow will be explained below.

[0262] Step 1:

[0263] The server executes a program that periodically accesses the terms of use page of a pre-registered Web service.

[0264] Step 2:

[0265] The server acquires the latest terms of use text data from the terms of use page and stores it in a database.

[0266] Step 3:

[0267] The server sends the latest obtained terms of use text data to the analysis engine.

[0268] Step 4:

[0269] The analysis engine compares the newly acquired terms of use text data with existing data and automatically detects changes.

[0270] Step 5:

[0271] The analysis engine sends the detected changes to the generation AI.

[0272] Step 6:

[0273] The generative AI evaluates the importance of the changes and generates a summary text.

[0274] Step 7:

[0275] The generation AI compares past user emotional data and reflects it in the risk summary text.

[0276] Step 8:

[0277] The server stores the generated summary text in a risk assessment database.

[0278] Step 9:

[0279] The server notifies a particular user of a risk summary based on the user's profile information.

[0280] Step 10:

[0281] The user checks the risk summary notice using the terminal.

[0282] Step 11:

[0283] The user has access to an interface to review the risk summary and evaluate the terms and conditions.

[0284] Step 12:

[0285] The terminal displays an input form for evaluation, allowing the user to input an evaluation and comments.

[0286] Step 13:

[0287] The user inputs a rating and a comment and submits it.

[0288] Step 14:

[0289] The emotion engine collects real-time emotion data from users who are rating.

[0290] Step 15:

[0291] The server receives the ratings and emotion data sent by the users and stores them in a rating database.

[0292] Step 16:

[0293] The server posts the evaluation in a public evaluation database so that other users can refer to the evaluation results.

[0294] Step 17:

[0295] The server selects reliable services and applications based on the published evaluation data and emotion data.

[0296] Step 18:

[0297] The server displays the selected services and applications in a dedicated store and makes them available to users.

[0298] Step 19:

[0299] Users using the device can access a dedicated store to view and download selected services and applications.

[0300] Step 20:

[0301] The server continuously analyzes user reviews and ratings to identify common problems and areas for improvement.

[0302] Step 21:

[0303] The analysis engine generates a report of specific improvement proposals based on the extracted problems and areas for improvement.

[0304] Step 22:

[0305] The server sends the generated improvement suggestion report to the company and provides feedback for service improvement.

[0306] Example 2

[0307] 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."

[0308] In modern information technology services, terms of use are frequently updated, and their complicated content makes it difficult for users to understand the changes. Furthermore, there is a lack of information provided that reflects users' feelings and individual risk perceptions, making it difficult for users to appropriately manage risks. Furthermore, user evaluations are not widely shared as reliable, and the quality of feedback provided to service providers is low. As a result, there are problems with delays in improving service reliability and implementing improvement suggestions.

[0309] 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 means for acquiring terms of use information, means for automatically detecting changes by analyzing the acquired terms of use information, means for using a generative AI model to summarize the detected changes, means for customizing a risk summary based on user emotion data, means for notifying the user of the customized summary, and means for accepting user terms of use evaluations and publishing the evaluation results. This makes it possible to quickly and accurately notify users of changes to the terms of use and provide information tailored to individual risk perceptions. Furthermore, the collected user evaluations can be used to improve the reliability of services and make specific improvement proposals to service providers.

[0310] "Terms of Use Information" refers to documents that include the terms of use and privacy policy of the services that information technology services provide to users.

[0311] "Means of acquisition" refers to the function by which the server accesses a web page via the Internet and automatically acquires terms of use information.

[0312] "Means of analysis" refers to the function of sending the terms of use information acquired by the server to an internal analysis engine and converting the text into structured data using natural language processing technology.

[0313] "Means for automatically detecting changes" refers to a function in which the server uses an algorithm to compare the old and new terms of use information and identify the differences.

[0314] "Means for using a generative AI model" refers to the function by which the server sends a prompt sentence to the generative AI model and automatically generates a summary.

[0315] "User emotion data" refers to a log of a user's past reactions and emotions, data that is used to create a customized summary.

[0316] "Means for customizing risk summaries based on emotional data" refers to a function that adjusts the summary content according to the user's emotions based on the user's emotional data collected by the server.

[0317] "Means for notifying the user of the customized summary" refers to the function by which the server sends the customized summary to the user's device via email or in-app push notification.

[0318] The "means for accepting a regulation evaluation" refers to a function that provides an interface for users to input evaluations and that the server accepts them.

[0319] "Means for publishing evaluation results" refers to a function that stores the evaluation data collected by the server in a database and makes it publicly available for other users to refer to.

[0320] "Highly reliable information technology services" refer to services that are judged to have high overall reliability based on user ratings and sentiment data.

[0321] "Means for displaying in a dedicated store" refers to a function for displaying highly reliable services selected by the server to users in an online store.

[0322] "Sales Improvement Proposal Report" refers to a report containing specific improvements that is provided to service providers after analyzing ratings, reviews, and sentiment data collected from users.

[0323] This invention builds a system that combines an emotion engine that recognizes user emotions. The system periodically accesses the terms of use page, analyzes the acquired data to detect changes, generates summaries using a generative AI model, and customizes information based on the user's emotion data. Furthermore, it collects user ratings, selects and displays reliable services based on them, and makes improvement suggestions to companies.

[0324] Hardware and software used

[0325] The server contains the following main components:

[0326] Web crawler: Periodically accesses terms of use pages on the Internet and acquires text data. Specific software used is Apache (registered trademark) Nutch or Scrapy.

[0327] Analysis engine: Analyzes the acquired text and stores it as structured data. It utilizes natural language processing (NLP) technology using Python or Java (registered trademark). NLTK or spaCy are often used.

[0328] Difference detection algorithm: Compares the old and new data and detects changes. Diff-Match-Patch or a similar library is used for difference detection.

[0329] Generative AI model: To summarize the changes, we use a generative AI model such as OpenAI GPT. We create an input prompt and generate a summary.

[0330] Sentiment engine: Analyzes user sentiment data and customizes summary content. Sentiment analysis uses Google® Cloud Natural Language API and Microsoft® Azure® Text Analytics.

[0331] Notification system: Notifies users with a customized summary. Possible notification methods include email and push notifications. Firebase Cloud Messaging (FCM) and AWS (registered trademark) SNS (Simple Notification Service) are used.

[0332] The terminal is used as an interface for users to input their evaluations. Specifically, this applies to smartphones, PCs, and tablets.

[0333] Users receive notifications and provide ratings, and the rating data is used to improve reliability and propose improvements to the company.

[0334] Specific examples

[0335] For example, when a user signs up for a new cloud storage service, the following happens:

[0336] 1. The server accesses the terms of use page of the cloud storage service to obtain text data. Using a web crawler, the server periodically accesses this page to obtain the latest terms.

[0337] 2. The server sends the acquired text data to an analysis engine, which uses natural language processing technology to extract paragraphs and sections and store them in a database.

[0338] 3. The server compares the old and new data and identifies changes using a difference detection algorithm. For example, it detects that the "personal information storage period" has been changed from "6 months" to "1 year."

[0339] 4. The server generates a summary by sending the following prompt to the generative AI model: "Please summarize the changes in the new terms of use, such as changes to data retention periods and new policies regarding information leaks. Please make sure the risks are clearly explained."

[0340] 5. The server uses an emotion engine to customize this summary based on the user's emotion data. For example, if a user has previously expressed strong concerns about data leaks, the server generates a summary that specifically highlights changes related to data security.

[0341] 6. The server sends a customized summary to the user's device. Notification methods include email and push notification. "The terms of use for the new cloud storage service have been revised. The data retention period has been changed from six months to one year. Please click here for details."

[0342] 7. Upon receiving the notification, the user enters their rating using their device, leaving a comment or star rating, and the rating data is sent to the server.

[0343] 8. The server stores the collected evaluation data in a database and makes it publicly available for other users to refer to, allowing other users to determine the reliability of information technology services.

[0344] 9. The server selects reliable IT services based on the collected evaluation data and displays them in a dedicated store, allowing users to select services with confidence.

[0345] 10. The server analyzes the ratings and reviews collected from users and generates a report of improvement proposals for sales based on the results. It provides the service provider with a specific report such as, "70% of users are unsure about the new pricing plan, so we recommend that you reconsider the plan."

[0346] As a result, users will be able to quickly understand changes to the terms of use and receive information tailored to their individual risk perceptions, and appropriate feedback will be provided to service providers, which is expected to lead to improved service quality.

[0347] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0348] Step 1: Automatically retrieve terms of use

[0349] The server periodically accesses a pre-registered web page (terms of use page) and obtains text data. A web crawler (for example, Apache Nutch or Scrapy) is used to access the URL and download the terms of use in HTML format. The input data is the URL, and the output data is the obtained text data. This text data is saved in a data store within the server.

[0350] Step 2: Parsing the Terms of Use

[0351] The server sends the acquired text data to an analysis engine. The analysis engine (e.g., NLTK or spaCy) uses natural language processing techniques to divide the text into paragraphs and sections and convert it into structured data. The input data is the terms of use text in HTML format, and the output data is structured paragraph data. The analysis results are stored in a database.

[0352] Step 3: Detecting changes

[0353] The server compares the newly acquired terms of use data with the existing terms of use data. It uses a difference detection algorithm (e.g., Diff-Match-Patch) to detect changes between the two. The input data is the old and new terms of use data, and the output data is a list of changes. This list of changes is also saved in the database.

[0354] Step 4: Generative AI model generates a summary

[0355] The server sends the list of detected changes to a generative AI model, which generates a summary. The input prompt is, "Please summarize the changes in the new terms of use. For example, changes to data retention periods or new policies regarding information leaks. Please make sure that the risks are clearly explained." The generative AI model (e.g., OpenAI GPT) generates a summary based on this prompt and the list of changes. The input data are the prompt and the list of changes, and the output data is a summary of the changes. This summary is also stored in the database.

[0356] Step 5: Customize the risk summary

[0357] The server uses the user's emotional data to customize the generated summary. The emotion engine (e.g., Google Cloud Natural Language API) analyzes the user's past emotional data and customizes the importance and risk of changes. The input data is the user's emotional data and the summary, and the output data is the customized summary. This customized summary is associated with the user profile and saved.

[0358] Step 6: Notify users

[0359] The server sends a customized summary to the user's device. A notification system (for example, Firebase Cloud Messaging or AWS SNS) is used to send the notification to the user's email address or app. The input data is the customized summary and the user's contact information, and the output data is the sending result (success or failure). The notification content often includes a message such as, "The terms of use for the new cloud storage service have been revised. The data retention period has been changed from 6 months to 1 year. Please click here for details."

[0360] Step 7: Collect user ratings

[0361] The user checks the notification using a terminal and rates it through the rating interface. The user accesses the rating interface and inputs a star rating and comments. The input data is the user's rating information, and the output data is data stored in the rating database. The rating content includes comments such as "I feel reassured by the new policy."

[0362] Step 8: Publish evaluation data

[0363] The server stores the collected evaluation data in a database and makes it publicly available for other users to refer to. Highly reliable service information is provided through a public interface. The input data is the data in the evaluation database, and the output data is evaluation information that can be viewed by other users. This allows newly registered users to refer to the evaluations of other users.

[0364] Step 9: Choose a reliable service

[0365] The server comprehensively evaluates the collected evaluation data and sentiment data to select highly reliable services. It uses an algorithm to calculate a reliability score and selects services with a certain score or higher. The input data are the evaluation data and sentiment data, and the output data is a list of selected highly reliable services. This list is displayed in a dedicated store.

[0366] Step 10: Generate improvement proposals for the company

[0367] The server analyzes the ratings and reviews collected from users and generates an improvement proposal report based on the results. An analysis engine is used to extract common problems and areas for improvement, and specific proposals are generated. The input data are rating data and reviews, and the output data is an improvement proposal report. This report is provided to the service provider and used to improve the service. For example, a report may be generated stating, "70% of users are unsure about the new pricing plan, so we recommend that you reconsider the plan."

[0368] (Application example 2)

[0369] 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."

[0370] Modern internet services frequently change their terms of use, making it difficult for users to keep track of all of these changes. Furthermore, because users' feelings and perceptions of risk vary, typical notification methods fail to provide appropriate information to each user. This raises the risk that users may miss important changes to the terms of use and end up suffering disadvantages. Furthermore, there is currently a lack of appropriate collection and analysis of user feedback, and the resulting evaluation of reliability and measures to improve services.

[0371] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring terms and conditions information, means for automatically detecting changes by analyzing the acquired terms and conditions information, means for summarizing the detected changes and displaying them to the user, means for analyzing the user's emotional data and customizing and notifying a risk summary, and means for accepting user evaluations of the terms and conditions and publishing the evaluation results. This allows users to easily understand important changes to the terms and conditions and receive information based on their own emotions and risk perceptions. In addition, collecting and publishing user feedback allows other users to select reliable services, and companies can improve their services based on user evaluations and reviews.

[0372] The "means for obtaining terms and conditions information" is a function that automatically collects terms and conditions data that are periodically posted by service providers on the Internet.

[0373] "Means for automatically detecting changes by analyzing acquired terms and conditions information" is a function that analyzes collected terms and conditions data and identifies changes by comparing it with the previous version.

[0374] "Means for summarizing detected changes and displaying them to the user" is a function that uses a generative AI model to summarize detected changes and display them in an easy-to-understand manner for the user.

[0375] The "means for analyzing user emotional data and customizing and notifying a risk summary" is a function that analyzes a user's past emotional data and generates and notifies an optimal risk summary for each individual user.

[0376] The "means for accepting user evaluations of terms and conditions and publishing the evaluation results" is a function that collects evaluations and feedback on the terms and conditions provided by users and publishes the results so that other users can view them.

[0377] "Means of selecting reliable services and applications based on evaluation results and displaying them in a dedicated store" refers to a function that selects highly rated services and applications based on collected evaluation data and displays them on a dedicated store page.

[0378] "A means for analyzing ratings and reviews collected from users and generating improvement proposal reports for companies based on the analysis results" refers to a function that performs data analysis of ratings and reviews provided by users and generates a report that makes improvement proposals to companies based on the results.

[0379] A "generative AI model" is a form of artificial intelligence that learns from massive amounts of text data and performs text generation, automatic summarization, and question answering for specific tasks.

[0380] A "prompt sentence" is an input sentence that instructs a generative AI model on the task to be performed or the content to be generated.

[0381] This invention is a system for enabling users to properly understand the importance of changes to terms of use, and provides a customized risk summary based on the user's emotional data. This system is mainly composed of a server, a user terminal, and a communication network.

[0382] Overall system description

[0383] The server has the following main functions:

[0384] How to obtain policy information

[0385] A method for automatically detecting changes by analyzing acquired clause information

[0386] A means to summarize the detected changes and display them to the user

[0387] A method to analyze user sentiment data and provide customized risk summaries

[0388] A means of accepting user evaluations of terms and conditions and publishing the evaluation results

[0389] Hardware and software used

[0390] The system uses the following hardware and software:

[0391] Hardware: Servers, smartphones

[0392] Software: Python, BeautifulSoup (HTML parsing), requests (HTTP requests), SentimentEngine (sentiment analysis module), SummaryEngine (summary generation module)

[0393] Data processing and calculation

[0394] The server periodically accesses pre-registered web pages (terms of use pages for various services) and retrieves the text data of the terms of use using the HTML analysis library BeautifulSoup and the HTTP request library requests. The retrieved data is compared with past terms of use data to detect changes. As part of this analysis, a generative AI model is used to generate a summary of the changes.

[0395] The smartphone, which acts as a user terminal, receives and displays the summary notification sent from the server. In addition, the user's emotional data is analyzed using SentimentEngine, and a risk summary is customized based on the user's past emotional data.

[0396] Specific examples

[0397] For example, when a user registers for a new web storage service, the server automatically retrieves and analyzes the service's terms of use to detect any changes. The generative AI summarizes important changes to the terms (e.g., changes to data retention periods), and this information is passed through an emotion engine to notify the user in a format appropriate for them. The user then checks the notification and rates the service. This rating is made public for other users to view, and the service is displayed in a dedicated store as a reliable service. Companies can use the provided improvement proposal report to improve their services.

[0398] Prompt Sentence Examples

[0399] "Analyze the changes in the new Terms of Service, highlight the changes in the Privacy Policy, and generate a summary that is relevant to the user, who has expressed strong concerns about data security in the past."

[0400] By using this specific method, users can easily understand the terms of use and use the service with peace of mind. In addition, service providers can continuously improve the quality of their services based on user feedback and sentiment data.

[0401] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0402] Step 1:

[0403] The server periodically accesses a pre-registered web page (terms of use page) and retrieves the text data of the terms of use using the HTML parsing library BeautifulSoup and the HTTP request library requests. The input is the URL of the terms of use page, and the output is the retrieved text data. Specifically, the requests library sends an HTTP request and receives an HTML response. BeautifulSoup is then used to parse the HTML data and extract the text portion.

[0404] Step 2:

[0405] The server saves the acquired text data and compares it with past data to detect changes. The input is the text data of the old and new terms of use, and the output is a list of changes. Here, a text comparison algorithm is used to identify the changes. Specifically, the strings on each line are compared with past data, and the changed parts are listed.

[0406] Step 3:

[0407] The server inputs the detected changes into a generative AI model to generate a summary. The input is a list of changes and a prompt, and the output is the summarized changes. Specifically, the server inputs a list of changes to the generative AI model using a prompt (e.g., "Please analyze the changes in the new terms of use and generate a summary") to obtain a summary.

[0408] Step 4:

[0409] The server inputs the user's emotional data into the Sentiment Engine for analysis, and then generates a risk summary. The input is the user's emotional data and summarized changes, and the output is a customized risk summary. Specifically, the server uses the Sentiment Engine to analyze the user's past emotional data, and based on the results, inputs prompts that highlight and notify the risks of the summarized changes into the generative AI model, and obtains the results.

[0410] Step 5:

[0411] The terminal receives the customized risk summary sent from the server and notifies the user. The input is the risk summary sent from the server, and the output is the notification displayed to the user. Specifically, the mobile terminal application receives the push notification and displays it on the user screen.

[0412] Step 6:

[0413] The user checks the notified risk summary and enters their evaluation of the terms of use through the application. The input is the user's evaluation data (star ratings and comments), and the output is the evaluation results being sent to the server. Specifically, the user enters the evaluation using the user interface and sends the data to the server.

[0414] Step 7:

[0415] The server stores the evaluation data collected from users in a database and makes it publicly available for other users to view. The input is the user's evaluation data, and the output is the published evaluation results. Specifically, the evaluation data is stored in a database management system and made public through a web interface.

[0416] Step 8:

[0417] The server selects reliable services and applications based on the collected evaluation data and displays them on a dedicated store. The input is a compilation of evaluation data, and the output is a list of reliable services. Specifically, services with high evaluation scores are selected using statistical analysis and displayed on a dedicated store page.

[0418] Step 9:

[0419] The server analyzes the ratings and reviews collected from users and generates an improvement proposal report for the company. The input is the rating and review data, and the output is an improvement proposal report. Specifically, it performs text mining to extract common problems and areas for improvement, and creates improvement proposals based on that.

[0420] 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.

[0421] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0422] 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.

[0423] [Second embodiment]

[0424] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0425] 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.

[0426] 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).

[0427] 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.

[0428] 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.

[0429] 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).

[0430] 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.

[0431] 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.

[0432] 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.

[0433] 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.

[0434] In the smart glasses 214, 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.

[0435] 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."

[0436] This invention is a system that automatically acquires and analyzes terms of use (terms and conditions) presented by online service providers, and displays a summary in an easy-to-understand format for users. It also has the functionality to receive user ratings, evaluate reliability based on those ratings, and provide improvement suggestions to companies. Below, we will explain how to specifically implement this system.

[0437] Overall system overview

[0438] The system has the following main functions:

[0439] 1. A function that automatically acquires and analyzes clause information to detect changes.

[0440] 2. Ability to summarize detected changes and notify the user.

[0441] 3. Ability to collect and publish user ratings.

[0442] 4. The ability to select reliable services and applications and display them in a dedicated store.

[0443] 5. A function that makes improvement suggestions to companies based on user ratings and reviews.

[0444] Automatic acquisition and analysis of clause information

[0445] The server periodically accesses a pre-registered web page (terms of service page) to retrieve the text data of the terms of service. The retrieved data is then sent to an analysis engine, which compares it with existing data to detect changes. For example, if a music streaming service revises part of its terms of service, the engine compares the old and new terms and automatically identifies changes to the data usage policy.

[0446] Risk Summary and Notification

[0447] The detected changes are summarized by the generative AI and the associated risks are explained in an easy-to-understand manner. The server stores the summarized information in a database, allowing users to review the information based on their own profile. Users can view the risk summary through their devices and intuitively understand it.

[0448] Collecting and publishing user ratings

[0449] Using a device, users access the service's terms of service page and use the interface to submit a rating. The rating includes a star rating and comments, which are then sent to the server. The server then stores the rating data in a database, making public ratings available to other users.

[0450] Selection and display of reliable services and applications

[0451] The server selects reliable services and applications based on the collected evaluation data, and displays these reliable services and applications in a dedicated online store, allowing users to download and install them with confidence.

[0452] Improvement proposals for companies

[0453] The server analyzes user ratings and reviews to identify common problems and areas for improvement. Based on this, an improvement proposal report is generated and provided to the service provider. For example, if multiple users have the same complaints about a particular feature, the server analyzes their feedback and makes appropriate improvement proposals.

[0454] Specific examples

[0455] For example, when a user signs up for a new video streaming service, the server automatically retrieves and analyzes the service's terms of service. The generative AI summarizes any important changes to the terms (e.g., updates to the privacy policy). This information is then notified to the user via their device. The user then reviews the summary and rates the terms. This rating is then sent to the server and made public for other users to refer to.

[0456] This system allows users to easily understand the terms of use and risks involved, creating an environment where they can use services with peace of mind. It also enables service providers to continuously improve the quality of their services based on user feedback.

[0457] The processing flow will be explained below.

[0458] Step 1:

[0459] The server executes a program that periodically accesses the terms of use page of a pre-registered Web service.

[0460] Step 2:

[0461] The server acquires the latest terms of use text data from the terms of use page and stores it in a database.

[0462] Step 3:

[0463] The server sends the latest obtained terms of use text data to the analysis engine.

[0464] Step 4:

[0465] The analysis engine compares the newly acquired terms of use text data with existing data and automatically detects changes.

[0466] Step 5:

[0467] The analysis engine sends the detected changes to the generation AI.

[0468] Step 6:

[0469] The generative AI evaluates the importance of the changes and generates a summary text.

[0470] Step 7:

[0471] The server stores the generated summary text in a risk assessment database.

[0472] Step 8:

[0473] The server notifies a particular user of a risk summary based on the user's profile information.

[0474] Step 9:

[0475] The user uses the terminal to check the risk summary notice.

[0476] Step 10:

[0477] The user accesses an interface to review the risk summary and evaluate the terms.

[0478] Step 11:

[0479] The terminal displays an input form for rating the regulations, allowing the user to input ratings and comments.

[0480] Step 12:

[0481] The user inputs a rating and a comment and submits it.

[0482] Step 13:

[0483] The server receives the evaluation data sent by the user and stores it in an evaluation database.

[0484] Step 14:

[0485] The server posts the evaluation in a public evaluation database so that other users can refer to the evaluation results.

[0486] Step 15:

[0487] The server selects highly reliable services and applications based on published evaluation data.

[0488] Step 16:

[0489] The server displays the selected services and applications in a dedicated store and makes them available to users.

[0490] Step 17:

[0491] Users using the device can access a dedicated store to view and download selected services and applications.

[0492] Step 18:

[0493] The server continuously analyzes user reviews and ratings to identify common problems and areas for improvement.

[0494] Step 19:

[0495] The analysis engine generates a report of specific improvement proposals based on the extracted problems and areas for improvement.

[0496] Step 20:

[0497] The server sends the generated improvement suggestion report to the company and provides feedback for service improvement.

[0498] Example 1

[0499] 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."

[0500] In modern Internet services, changes to terms of use are frequent, making it difficult for users to understand and evaluate the changes. Furthermore, there is a lack of objective criteria for selecting reliable services, and no mechanism exists for service providers to effectively incorporate user feedback into improvement proposals. This often leaves users feeling uneasy about using services, and service providers find it difficult to make appropriate improvements.

[0501] 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.

[0502] In this invention, the server includes means for acquiring terms and conditions information, means for analyzing the acquired terms and conditions information and automatically detecting changes, means for summarizing the detected changes using a generative AI model and displaying them to the user, and means for accepting user evaluations of the terms and conditions and publishing the evaluation results. This enables users to easily understand and evaluate changes to the terms and conditions, enabling them to select highly reliable services and propose appropriate improvements to service providers.

[0503] "Terms and conditions information" is a document containing the terms and conditions that a service provider presents to users.

[0504] "Means" refers to a method or apparatus for achieving a specific function or operation.

[0505] A "server" is a computer system that manages, processes, and distributes data over a network.

[0506] "User" refers to any individual or entity using the Service.

[0507] "Acquisition" is the act of collecting or obtaining necessary data or information.

[0508] "Analysis" is the process of examining data or information in detail to understand its meaning and structure.

[0509] "Changes" refers to the differences or modifications between the two documents or data being compared, old and new.

[0510] A "generative AI model" is a model that uses artificial intelligence technology to automatically generate text.

[0511] "Summarizing" refers to the process of summarizing detailed information concisely to extract only the main points.

[0512] "Evaluation" is the act of judging performance or value based on specific criteria and giving a score or comment.

[0513] "Publication" refers to making certain information publicly accessible.

[0514] "Reliability" refers to the ability and characteristics of a service or system to operate stably and as expected.

[0515] "Service" means an application or online platform that offers specific functionality or benefits.

[0516] "Selection" is the act of choosing the best one based on specific criteria.

[0517] "Exclusive Store" refers to an online platform that offers only selected specific applications and services.

[0518] A "review" is an act in which a user writes their opinion or impression about a service or product.

[0519] "Improvement proposals" are specific proposals for solving existing problems and improving performance and user experience.

[0520] A "report" is a document that systematically compiles specific information.

[0521] This invention relates to a system that automatically detects changes in terms of use for Internet services, summarizes them, and presents them to users, and selects and provides more reliable services. The invention is realized through processing steps mainly involving a server, a terminal, and a user.

[0522] Overall structure

[0523] The system includes the following main features:

[0524] 1. Automatic Acquisition of Terms of Use

[0525] 2. Analysis of changes to the Terms of Use

[0526] 3. Generate a summary of changes

[0527] 4. Summary storage and notification

[0528] 5. Collection and publication of user ratings

[0529] 6. Select a reliable service

[0530] 7. Generating improvement proposals for companies

[0531] Hardware and Software

[0532] The server works in conjunction with a database and natural language processing engine to automatically retrieve terms of use, analyze them, detect changes, generate summaries using a generative AI model, provide notifications, collect and publish ratings, select reliable services, and generate improvement proposal reports for companies.

[0533] For example, the analysis engine can use natural language processing toolkits such as NLTK and spaCy. For generative AI, OpenAI GPT is used as the generative AI model. The database can be an SQL database or a NoSQL database.

[0534] The terminal provides an interface for users to view summary information and evaluation results and input their own evaluations. Terminals include various devices such as smartphones, tablets, and PCs.

[0535] Users can check the summary of terms of service, rate and review the terms of service, and use a dedicated store to select reliable services.

[0536] Specific examples of processing

[0537] For example, when a user signs up for a new video streaming service, the server processes the following:

[0538] 1. The server accesses the terms of use page for that service and retrieves the HTML content.

[0539] 2. The retrieved content is analyzed using a natural language processing toolkit to detect changes.

[0540] 3. The changes are fed into a generative AI model to generate a summary.

[0541] 4. The server stores the generated summary in a database and notifies the user based on their profile.

[0542] 5. The user receives the notification through their device, checks the summary, and gives a rating, which is sent to the server and stored in the database.

[0543] Prompt Sentence Examples

[0544] "I've signed up for a new video streaming service. If the terms of service for this service change, I'd like to be notified with a summary of the changes. I'd also like to see other users' reviews."

[0545] This allows users to easily understand the terms of service and their changes, and to make appropriate evaluations. It also allows service providers to improve their services based on user feedback. This system increases user convenience and improves reliability.

[0546] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0547] Step 1:

[0548] The server periodically accesses a pre-registered web page (terms of use page) and retrieves HTML content. This operation is performed by sending an HTTP request and receiving HTML data as a response. The input is a list of URLs, and the output is the retrieved HTML content.

[0549] Step 2:

[0550] The server parses the retrieved HTML content and extracts the terms of use text data. It uses a parsing library (e.g. BeautifulSoup) to extract text from HTML. The input is the HTML content, and the output is the terms of use text data.

[0551] Step 3:

[0552] The server sends the retrieved terms of use text to an analysis engine (for example, natural language processing toolkits such as NLTK or spaCy), which compares the old and new data to detect changes. The input is the old and new terms of use text data, and the output is a list of changes.

[0553] Step 4:

[0554] The server inputs the list of changes into a generative AI model and generates a text summary of them. The summary is created using a generative AI model (e.g., OpenAI GPT). The input is the list of changes, and the output is a summarized risk description text.

[0555] Step 5:

[0556] The server saves the generated summary text to a database. This operation is performed by inserting the summary data into a specific table using a database connection library. The input is the summary text and the user's profile information, and the output is a flag indicating whether the save operation to the database was successful.

[0557] Step 6:

[0558] The server notifies the user to view information based on their profile. Notifications can be sent via email, push notification, or in-app notification. The input is the user's profile information and summary text, and the output is the notification sending status.

[0559] Step 7:

[0560] The user receives the notification through the terminal and views the summary information. The summary text is displayed on the terminal interface. The input is the notification message, and the output is the user's browsing history.

[0561] Step 8:

[0562] Users rate the terms of use and input their rating results. Star ratings and comments are recorded through the rating interface. The input is rating data (star ratings and comments), and the output is a rating record.

[0563] Step 9:

[0564] The server saves the evaluation results sent by users in a database and makes them publicly accessible to other users. This is also an operation that inserts and publishes evaluation data using the database connection library. The input is the evaluation data, and the output is a public evaluation dataset.

[0565] Step 10:

[0566] The server selects reliable services and applications based on the collected reputation data. This is the process of analyzing the reputation data and identifying services with high reputations. The input is a reputation dataset, and the output is a list of reliable services.

[0567] Step 11:

[0568] The server displays the selected reliable services in a dedicated store by inserting them into a display table in the database. The input is a list of reliable services, and the output is a display item in the dedicated store.

[0569] Step 12:

[0570] The server analyzes the ratings and reviews collected from users and extracts common problems and areas for improvement. This analysis is performed using a natural language processing toolkit. The input is the text data of the ratings and reviews, and the output is a list of the extracted problems and areas for improvement.

[0571] Step 13:

[0572] The server uses a generative AI model to generate an improvement proposal report for the company based on the extracted problems and improvement points. The input is a list of problems and improvement points, and the output is an improvement proposal report.

[0573] (Application example 1)

[0574] 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."

[0575] The frequent changes in terms of service for online services such as content distribution services make it difficult for users to understand the content. Users also have difficulty grasping the risks posed by changes in terms of service, leading to concerns about the reliability of the service. Furthermore, there is a lack of means to accurately reflect user feedback and improve the service.

[0576] 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.

[0577] In this invention, the server includes a means for acquiring terms and conditions information, a means for analyzing the acquired terms and conditions information and automatically detecting changes, a means for summarizing the detected changes using a generative AI model and displaying them to the user, a means for accepting user evaluations of the terms and conditions and publishing the evaluation results, and a means for recommending reliable content distribution services. This allows users to intuitively understand changes to the terms and conditions and the risks involved, and select reliable services. The server also includes a means for analyzing the evaluations and reviews collected from users using a generative AI model and generating improvement proposal reports for companies, enabling service providers to continuously improve their services based on user feedback.

[0578] A "server" is a computer system that receives requests over a network and provides data or services.

[0579] The "means for acquiring terms and conditions information" is a function that automatically collects text data of terms of use from the web page of the content distribution service.

[0580] "Means for automatically detecting changes by analyzing terms and conditions information" is a function that compares the old and new terms of use and identifies changes within the terms and conditions.

[0581] "Means for summarizing and displaying to the user using a generative AI model" is a function that uses AI technology to summarize detected changes and displays the summary in an easy-to-read format for the user.

[0582] The "means for accepting user evaluations of terms and conditions and publishing the evaluation results" is a function that allows users to submit evaluations and comments on the terms and conditions and publish the evaluations in a form that can be viewed by other users.

[0583] The "means for recommending highly reliable content distribution services" is a function that selects safe and highly reliable content distribution services based on collected user evaluation data and recommends them to users.

[0584] The "analysis means" is a function that analyzes collected user ratings and reviews and identifies areas for improvement in the service based on the results.

[0585] The "means for generating improvement proposal reports for companies" is a function that automatically creates reports that make specific improvement proposals to service providers based on user feedback.

[0586] This invention is a system that provides an environment in which users can use content distribution services with peace of mind by automatically acquiring, analyzing, summarizing, and evaluating terms of use. The following describes how to specifically implement this system.

[0587] Overall flow

[0588] First, the server periodically retrieves the text data of the terms of use from the web page of the content distribution service via the network. This is done using the Python libraries "requests" and "BeautifulSoup." The retrieved text data is then compared with old data, and changes are automatically detected using the "difflib" library.

[0589] The detected changes are then summarized using a generative AI model, using AI techniques such as GPT-4, and the summary is sent to the user's device, allowing them to intuitively understand the changes.

[0590] Users can use their devices to rate the terms of use and submit their evaluation comments. This evaluation data is stored on the server and can be accessed by other users.

[0591] Furthermore, the server analyzes the evaluation data and selects and recommends reliable content delivery services. To do this, it uses "SQLAlchemy" to manage the database and analyze the evaluation data.

[0592] Finally, the collected user ratings and reviews are analyzed using the generative AI model again to create a report with specific improvement proposals for the company. This report is provided to the service provider to support continuous service improvement.

[0593] Hardware and software used

[0594] Server: The central computer system that retrieves and processes data from the web pages of a content delivery service.

[0595] Device: The device used by the user, such as a smartphone, computer, or tablet.

[0596] software:

[0597] Python: Overall program control.

[0598] BeautifulSoup, requests: Get text data from web pages.

[0599] difflib: Detect changes in text data.

[0600] GPT-4 (OpenAI API): Generates summaries using a generative AI model.

[0601] Firebase Cloud Messaging (FCM): Sends notifications to users.

[0602] Flask, SQLAlchemy: Server-side data management and API construction.

[0603] Specific examples

[0604] 1. The server accesses the web page of a specific content distribution service and obtains the terms of use in text format.

[0605] 2. Analyze the old and new terms of use data and detect changes.

[0606] 3. Use a generative AI model (e.g., GPT-4) to summarize the changes and create a summary.

[0607] 4. The summary is sent to the user's device using FCM.

[0608] 5. Users will receive a notification and review and evaluate the changes to the Terms of Use.

[0609] 6. The server collects evaluation data from users and selects and recommends reliable services.

[0610] 7. Furthermore, the system reanalyzes user ratings and reviews to generate a report with specific improvement suggestions for the service provider.

[0611] Prompt Sentence Examples

[0612] "Please summarize the following changes to the terms and conditions and explain their risks.

[0613] New Terms: [New Terms Text]

[0614] Old Terms: [old terms text]"

[0615] This system allows users to easily understand the terms of use and risks involved, enabling them to use content distribution services with peace of mind. It also enables service providers to continuously improve their services based on user feedback.

[0616] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0617] Step 1:

[0618] The server accesses the web page of a specific content distribution service and retrieves the text data of the terms of use. Specifically, it uses the Python "requests" and "BeautifulSoup" libraries to scrape the terms of use text from this web page. The input of this step is the URL of the web page, and the output is the retrieved text data of the terms of use.

[0619] Step 2:

[0620] The server compares the retrieved text data of the terms of use with the existing data to detect changes. The "difflib" library is used to detect changes. The input is the old and new terms of use text, and the output is differential information indicating the changes. In this data processing process, the old and new texts are compared line by line, and the different parts are extracted.

[0621] Step 3:

[0622] The server summarizes the detected changes using a generative AI model. AI technologies such as GPT-4 are used for generation. Specifically, the changes are sent as input data to the OpenAI API, and the summarized text is received as output. The input is difference information, and the output is the summarized changes.

[0623] Step 4:

[0624] The server notifies the user's device of the summarized changes. This notification uses Firebase Cloud Messaging (FCM). The input is the text of the summarized changes, and the output is a notification that is displayed on the user's device. The server obtains the user's device ID and sends the notification message via FCM.

[0625] Step 5:

[0626] The user uses the terminal to check the changes to the terms of use and rate the terms. The rating can include star ratings and comments. The input is a summary of the changes and the user's rating information, and the output is the rating data. The terminal receives the input from the user through a rating interface.

[0627] Step 6:

[0628] The server stores the evaluation data collected from users in a database and selects reliable content delivery services. "SQLAlchemy" is used for database management. The input is user evaluation data, and the output is a list of reliable services. The server scores the evaluation data and lists the services with the highest scores.

[0629] Step 7:

[0630] The server uses a generative AI model to analyze the ratings and reviews collected from users and generate a report of specific improvement proposals for the company. GPT-4 is again used for the analysis. The input is the user's rating data and reviews, and the output is a report of improvement proposals. The server sends the ratings and reviews to the AI ​​model and compiles the generated improvement proposals for the company.

[0631] Through each step of this process, the system enables users to intuitively understand the content and risks of the terms of use, helps them select reliable services, and allows service providers to continuously improve their services based on user feedback.

[0632] 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.

[0633] This invention is a system that combines an emotion engine that recognizes user emotions, and has the function of automatically acquiring and analyzing terms of use (terms and conditions) presented by online service providers, and displaying a summary of any changes. It also has the function of providing user ratings, reliability assessments based on those ratings, and suggesting improvements to companies. Below, we will explain how to specifically implement this system.

[0634] Overall system overview

[0635] The system has the following main functions:

[0636] 1. A function that automatically acquires and analyzes clause information to detect changes.

[0637] 2. Ability to summarize detected changes and notify the user.

[0638] 3. The ability to recognize user sentiment and customize risk summaries based on that data.

[0639] 4. A function to collect user ratings and publish the results.

[0640] 5. Ability to select reliable services and applications and display them in a dedicated store.

[0641] 6. Ability to use user sentiment data to improve the reliability of ratings.

[0642] 7. A function that makes improvement suggestions to companies based on user ratings and reviews.

[0643] Automatic acquisition and analysis of clause information

[0644] The server periodically accesses a pre-registered web page (terms of use page) and retrieves the text data of the terms of use. The retrieved data is sent to an analysis engine, which compares it with existing data to detect changes. For example, if a social networking service revise its terms of use, the old and new terms are compared and changes regarding the handling of user data are automatically identified.

[0645] Risk summary and emotion-aware notification

[0646] The server uses generative AI to summarize the detected changes and clearly explain the risks. The emotion engine also works to retrieve past emotional data from the user's profile and customize the risk summary notification accordingly. For example, a user who has previously expressed strong concerns about data leaks will receive notifications that specifically highlight changes related to data security.

[0647] Collecting and publishing user ratings

[0648] Using a device, users access the service's terms of use page and use the interface to rate the service. The rating includes a star rating and comments, and is sent to the server. The server stores the rating data in a database so that other users can refer to public ratings.

[0649] Selection and display of reliable services and applications

[0650] The server comprehensively evaluates the collected evaluation data and emotion data to select highly reliable services and applications. These highly reliable services and applications are displayed in a dedicated online store, allowing users to use them with peace of mind.

[0651] Improving the reliability of ratings using user emotions

[0652] The emotion engine collects emotional data from users at the time of rating and uses that data to verify the reliability of the ratings. For example, if a particular rating is extremely high, it may determine that the user is overly excited and may discount that rating.

[0653] Improvement proposals for companies

[0654] The server analyzes user ratings, reviews, and sentiment data to identify common issues and areas for improvement. Specific improvement proposal reports are then provided to the service provider. For example, if multiple users express concerns about a new pricing plan, the server can suggest reconsidering the plan based on that feedback.

[0655] Specific examples

[0656] For example, when a user signs up for a new cloud storage service, the server automatically retrieves and analyzes the service's terms of use to detect any changes. The generative AI summarizes important changes to the terms (e.g., changes to data retention periods), and this information is passed through an emotion engine to notify the user in a format appropriate for them. The user then checks the notification and rates the service. This rating is made public for other users to view, and the service is displayed in a dedicated store as a reliable service. Companies can use the provided improvement proposal report to improve their services.

[0657] This system allows users to easily understand the terms of use, understand the risks, and use the service with peace of mind. It also enables service providers to continuously improve the quality of their services based on user feedback and sentiment data.

[0658] The processing flow will be explained below.

[0659] Step 1:

[0660] The server executes a program that periodically accesses the terms of use page of a pre-registered Web service.

[0661] Step 2:

[0662] The server acquires the latest terms of use text data from the terms of use page and stores it in a database.

[0663] Step 3:

[0664] The server sends the latest obtained terms of use text data to the analysis engine.

[0665] Step 4:

[0666] The analysis engine compares the newly acquired terms of use text data with existing data and automatically detects changes.

[0667] Step 5:

[0668] The analysis engine sends the detected changes to the generation AI.

[0669] Step 6:

[0670] The generative AI evaluates the importance of the changes and generates a summary text.

[0671] Step 7:

[0672] The generation AI compares past user emotional data and reflects it in the risk summary text.

[0673] Step 8:

[0674] The server stores the generated summary text in a risk assessment database.

[0675] Step 9:

[0676] The server notifies a particular user of a risk summary based on the user's profile information.

[0677] Step 10:

[0678] The user checks the risk summary notice using the terminal.

[0679] Step 11:

[0680] The user has access to an interface to review the risk summary and evaluate the terms and conditions.

[0681] Step 12:

[0682] The terminal displays an input form for evaluation, allowing the user to input an evaluation and comments.

[0683] Step 13:

[0684] The user inputs a rating and a comment and submits it.

[0685] Step 14:

[0686] The emotion engine collects real-time emotion data from users who are rating.

[0687] Step 15:

[0688] The server receives the ratings and emotion data sent by the users and stores them in a rating database.

[0689] Step 16:

[0690] The server posts the evaluation in a public evaluation database so that other users can refer to the evaluation results.

[0691] Step 17:

[0692] The server selects reliable services and applications based on the published evaluation data and emotion data.

[0693] Step 18:

[0694] The server displays the selected services and applications in a dedicated store and makes them available to users.

[0695] Step 19:

[0696] Users using the device can access a dedicated store to view and download selected services and applications.

[0697] Step 20:

[0698] The server continuously analyzes user reviews and ratings to identify common problems and areas for improvement.

[0699] Step 21:

[0700] The analysis engine generates a report of specific improvement proposals based on the extracted problems and areas for improvement.

[0701] Step 22:

[0702] The server sends the generated improvement suggestion report to the company and provides feedback for service improvement.

[0703] Example 2

[0704] 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."

[0705] In modern information technology services, terms of use are frequently updated, and their complicated content makes it difficult for users to understand the changes. Furthermore, there is a lack of information provided that reflects users' feelings and individual risk perceptions, making it difficult for users to appropriately manage risks. Furthermore, user evaluations are not widely shared as reliable, and the quality of feedback provided to service providers is low. As a result, there are problems with delays in improving service reliability and implementing improvement suggestions.

[0706] 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 means for acquiring terms of use information, means for automatically detecting changes by analyzing the acquired terms of use information, means for using a generative AI model to summarize the detected changes, means for customizing a risk summary based on user emotion data, means for notifying the user of the customized summary, and means for accepting user terms of use evaluations and publishing the evaluation results. This makes it possible to quickly and accurately notify users of changes to the terms of use and provide information tailored to individual risk perceptions. Furthermore, the collected user evaluations can be used to improve the reliability of services and make specific improvement proposals to service providers.

[0707] "Terms of Use Information" refers to documents that include the terms of use and privacy policy of the services that information technology services provide to users.

[0708] "Means of acquisition" refers to the function by which the server accesses a web page via the Internet and automatically acquires terms of use information.

[0709] "Means of analysis" refers to the function of sending the terms of use information acquired by the server to an internal analysis engine and converting the text into structured data using natural language processing technology.

[0710] "Means for automatically detecting changes" refers to a function in which the server uses an algorithm to compare the old and new terms of use information and identify the differences.

[0711] "Means for using a generative AI model" refers to the function by which the server sends a prompt sentence to the generative AI model and automatically generates a summary.

[0712] "User emotion data" refers to a log of a user's past reactions and emotions, data that is used to create a customized summary.

[0713] "Means for customizing risk summaries based on emotional data" refers to a function that adjusts the summary content according to the user's emotions based on the user's emotional data collected by the server.

[0714] "Means for notifying the user of the customized summary" refers to the function by which the server sends the customized summary to the user's device via email or in-app push notification.

[0715] The "means for accepting a regulation evaluation" refers to a function that provides an interface for users to input evaluations and that the server accepts them.

[0716] "Means for publishing evaluation results" refers to a function that stores the evaluation data collected by the server in a database and makes it publicly available for other users to refer to.

[0717] "Highly reliable information technology services" refer to services that are judged to have high overall reliability based on user ratings and sentiment data.

[0718] "Means for displaying in a dedicated store" refers to a function for displaying highly reliable services selected by the server to users in an online store.

[0719] "Sales Improvement Proposal Report" refers to a report containing specific improvements that is provided to service providers after analyzing ratings, reviews, and sentiment data collected from users.

[0720] This invention builds a system that combines an emotion engine that recognizes user emotions. The system periodically accesses the terms of use page, analyzes the acquired data to detect changes, generates summaries using a generative AI model, and customizes information based on the user's emotion data. Furthermore, it collects user ratings, selects and displays reliable services based on them, and makes improvement suggestions to companies.

[0721] Hardware and software used

[0722] The server contains the following main components:

[0723] Web crawler: Periodically accesses terms of use pages on the Internet and obtains text data. Specific software used is Apache Nutch and Scrapy.

[0724] Analysis engine: Analyzes the acquired text and stores it as structured data. Utilizes natural language processing (NLP) technology using Python or Java. NLTK or spaCy are often used.

[0725] Difference detection algorithm: Compares the old and new data and detects changes. Diff-Match-Patch or a similar library is used for difference detection.

[0726] Generative AI model: To summarize the changes, we use a generative AI model such as OpenAI GPT. We create an input prompt and generate a summary.

[0727] Sentiment engine: Analyzes user sentiment data and customizes summary content. Sentiment analysis uses Google Cloud Natural Language API and Microsoft Azure Text Analytics.

[0728] Notification system: Notify users with a customized summary. Possible notification methods include email and push notifications. Firebase Cloud Messaging (FCM) and AWS SNS (Simple Notification Service) are used.

[0729] The terminal is used as an interface for users to input their evaluations. Specifically, this applies to smartphones, PCs, and tablets.

[0730] Users receive notifications and provide ratings, and the rating data is used to improve reliability and propose improvements to the company.

[0731] Specific examples

[0732] For example, when a user signs up for a new cloud storage service, the following happens:

[0733] 1. The server accesses the terms of use page of the cloud storage service to obtain text data. Using a web crawler, the server periodically accesses this page to obtain the latest terms.

[0734] 2. The server sends the acquired text data to an analysis engine, which uses natural language processing technology to extract paragraphs and sections and store them in a database.

[0735] 3. The server compares the old and new data and identifies changes using a difference detection algorithm. For example, it detects that the "personal information storage period" has been changed from "6 months" to "1 year."

[0736] 4. The server generates a summary by sending the following prompt to the generative AI model: "Please summarize the changes in the new terms of use, such as changes to data retention periods and new policies regarding information leaks. Please make sure the risks are clearly explained."

[0737] 5. The server uses an emotion engine to customize this summary based on the user's emotion data. For example, if a user has previously expressed strong concerns about data leaks, the server generates a summary that specifically highlights changes related to data security.

[0738] 6. The server sends a customized summary to the user's device. Notification methods include email and push notification. "The terms of use for the new cloud storage service have been revised. The data retention period has been changed from six months to one year. Please click here for details."

[0739] 7. Upon receiving the notification, the user enters their rating using their device, leaving a comment or star rating, and the rating data is sent to the server.

[0740] 8. The server stores the collected evaluation data in a database and makes it publicly available for other users to refer to, allowing other users to determine the reliability of information technology services.

[0741] 9. The server selects reliable IT services based on the collected evaluation data and displays them in a dedicated store, allowing users to select services with confidence.

[0742] 10. The server analyzes the ratings and reviews collected from users and generates a report of improvement proposals for sales based on the results. It provides the service provider with a specific report such as, "70% of users are unsure about the new pricing plan, so we recommend that you reconsider the plan."

[0743] As a result, users will be able to quickly understand changes to the terms of use and receive information tailored to their individual risk perceptions, and appropriate feedback will be provided to service providers, which is expected to lead to improved service quality.

[0744] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0745] Step 1: Automatically retrieve terms of use

[0746] The server periodically accesses a pre-registered web page (terms of use page) and obtains text data. A web crawler (for example, Apache Nutch or Scrapy) is used to access the URL and download the terms of use in HTML format. The input data is the URL, and the output data is the obtained text data. This text data is saved in a data store within the server.

[0747] Step 2: Parsing the Terms of Use

[0748] The server sends the acquired text data to an analysis engine. The analysis engine (e.g., NLTK or spaCy) uses natural language processing techniques to divide the text into paragraphs and sections and convert it into structured data. The input data is the terms of use text in HTML format, and the output data is structured paragraph data. The analysis results are stored in a database.

[0749] Step 3: Detecting changes

[0750] The server compares the newly acquired terms of use data with the existing terms of use data. It uses a difference detection algorithm (e.g., Diff-Match-Patch) to detect changes between the two. The input data is the old and new terms of use data, and the output data is a list of changes. This list of changes is also saved in the database.

[0751] Step 4: Generative AI model generates a summary

[0752] The server sends the list of detected changes to a generative AI model, which generates a summary. The input prompt is, "Please summarize the changes in the new terms of use. For example, changes to data retention periods or new policies regarding information leaks. Please make sure that the risks are clearly explained." The generative AI model (e.g., OpenAI GPT) generates a summary based on this prompt and the list of changes. The input data are the prompt and the list of changes, and the output data is a summary of the changes. This summary is also stored in the database.

[0753] Step 5: Customize the risk summary

[0754] The server uses the user's emotional data to customize the generated summary. The emotion engine (e.g., Google Cloud Natural Language API) analyzes the user's past emotional data and customizes the importance and risk of changes. The input data is the user's emotional data and the summary, and the output data is the customized summary. This customized summary is associated with the user profile and saved.

[0755] Step 6: Notify users

[0756] The server sends a customized summary to the user's device. A notification system (for example, Firebase Cloud Messaging or AWS SNS) is used to send the notification to the user's email address or app. The input data is the customized summary and the user's contact information, and the output data is the sending result (success or failure). The notification content often includes a message such as, "The terms of use for the new cloud storage service have been revised. The data retention period has been changed from 6 months to 1 year. Please click here for details."

[0757] Step 7: Collect user ratings

[0758] The user checks the notification using a terminal and rates it through the rating interface. The user accesses the rating interface and inputs a star rating and comments. The input data is the user's rating information, and the output data is data stored in the rating database. The rating content includes comments such as "I feel reassured by the new policy."

[0759] Step 8: Publish evaluation data

[0760] The server stores the collected evaluation data in a database and makes it publicly available for other users to refer to. Highly reliable service information is provided through a public interface. The input data is the data in the evaluation database, and the output data is evaluation information that can be viewed by other users. This allows newly registered users to refer to the evaluations of other users.

[0761] Step 9: Choose a reliable service

[0762] The server comprehensively evaluates the collected evaluation data and sentiment data to select highly reliable services. It uses an algorithm to calculate a reliability score and selects services with a certain score or higher. The input data are the evaluation data and sentiment data, and the output data is a list of selected highly reliable services. This list is displayed in a dedicated store.

[0763] Step 10: Generate improvement proposals for the company

[0764] The server analyzes the ratings and reviews collected from users and generates an improvement proposal report based on the results. An analysis engine is used to extract common problems and areas for improvement, and specific proposals are generated. The input data are rating data and reviews, and the output data is an improvement proposal report. This report is provided to the service provider and used to improve the service. For example, a report may be generated stating, "70% of users are unsure about the new pricing plan, so we recommend that you reconsider the plan."

[0765] (Application example 2)

[0766] 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."

[0767] Modern internet services frequently change their terms of use, making it difficult for users to keep track of all of these changes. Furthermore, because users' feelings and perceptions of risk vary, typical notification methods fail to provide appropriate information to each user. This raises the risk that users may miss important changes to the terms of use and end up suffering disadvantages. Furthermore, there is currently a lack of appropriate collection and analysis of user feedback, and the resulting evaluation of reliability and measures to improve services.

[0768] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring terms and conditions information, means for automatically detecting changes by analyzing the acquired terms and conditions information, means for summarizing the detected changes and displaying them to the user, means for analyzing the user's emotional data and customizing and notifying a risk summary, and means for accepting user evaluations of the terms and conditions and publishing the evaluation results. This allows users to easily understand important changes to the terms and conditions and receive information based on their own emotions and risk perceptions. In addition, collecting and publishing user feedback allows other users to select reliable services, and companies can improve their services based on user evaluations and reviews.

[0769] The "means for obtaining terms and conditions information" is a function that automatically collects terms and conditions data that are periodically posted by service providers on the Internet.

[0770] "Means for automatically detecting changes by analyzing acquired terms and conditions information" is a function that analyzes collected terms and conditions data and identifies changes by comparing it with the previous version.

[0771] "Means for summarizing detected changes and displaying them to the user" is a function that uses a generative AI model to summarize detected changes and display them in an easy-to-understand manner for the user.

[0772] The "means for analyzing user emotional data and customizing and notifying a risk summary" is a function that analyzes a user's past emotional data and generates and notifies an optimal risk summary for each individual user.

[0773] The "means for accepting user evaluations of terms and conditions and publishing the evaluation results" is a function that collects evaluations and feedback on the terms and conditions provided by users and publishes the results so that other users can view them.

[0774] "Means of selecting reliable services and applications based on evaluation results and displaying them in a dedicated store" refers to a function that selects highly rated services and applications based on collected evaluation data and displays them on a dedicated store page.

[0775] "A means for analyzing ratings and reviews collected from users and generating improvement proposal reports for companies based on the analysis results" refers to a function that performs data analysis of ratings and reviews provided by users and generates a report that makes improvement proposals to companies based on the results.

[0776] A "generative AI model" is a form of artificial intelligence that learns from massive amounts of text data and performs text generation, automatic summarization, and question answering for specific tasks.

[0777] A "prompt sentence" is an input sentence that instructs a generative AI model on the task to be performed or the content to be generated.

[0778] This invention is a system for enabling users to properly understand the importance of changes to terms of use, and provides a customized risk summary based on the user's emotional data. This system is mainly composed of a server, a user terminal, and a communication network.

[0779] Overall system description

[0780] The server has the following main functions:

[0781] How to obtain policy information

[0782] A method for automatically detecting changes by analyzing acquired clause information

[0783] A means to summarize the detected changes and display them to the user

[0784] A method to analyze user sentiment data and provide customized risk summaries

[0785] A means of accepting user evaluations of terms and conditions and publishing the evaluation results

[0786] Hardware and software used

[0787] The system uses the following hardware and software:

[0788] Hardware: Servers, smartphones

[0789] Software: Python, BeautifulSoup (HTML parsing), requests (HTTP requests), SentimentEngine (sentiment analysis module), SummaryEngine (summary generation module)

[0790] Data processing and calculation

[0791] The server periodically accesses pre-registered web pages (terms of use pages for various services) and retrieves the text data of the terms of use using the HTML analysis library BeautifulSoup and the HTTP request library requests. The retrieved data is compared with past terms of use data to detect changes. As part of this analysis, a generative AI model is used to generate a summary of the changes.

[0792] The smartphone, which acts as a user terminal, receives and displays the summary notification sent from the server. In addition, the user's emotional data is analyzed using SentimentEngine, and a risk summary is customized based on the user's past emotional data.

[0793] Specific examples

[0794] For example, when a user registers for a new web storage service, the server automatically retrieves and analyzes the service's terms of use to detect any changes. The generative AI summarizes important changes to the terms (e.g., changes to data retention periods), and this information is passed through an emotion engine to notify the user in a format appropriate for them. The user then checks the notification and rates the service. This rating is made public for other users to view, and the service is displayed in a dedicated store as a reliable service. Companies can use the provided improvement proposal report to improve their services.

[0795] Prompt Sentence Examples

[0796] "Analyze the changes in the new Terms of Service, highlight the changes in the Privacy Policy, and generate a summary that is relevant to the user, who has expressed strong concerns about data security in the past."

[0797] By using this specific method, users can easily understand the terms of use and use the service with peace of mind. In addition, service providers can continuously improve the quality of their services based on user feedback and sentiment data.

[0798] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0799] Step 1:

[0800] The server periodically accesses a pre-registered web page (terms of use page) and retrieves the text data of the terms of use using the HTML parsing library BeautifulSoup and the HTTP request library requests. The input is the URL of the terms of use page, and the output is the retrieved text data. Specifically, the requests library sends an HTTP request and receives an HTML response. BeautifulSoup is then used to parse the HTML data and extract the text portion.

[0801] Step 2:

[0802] The server saves the acquired text data and compares it with past data to detect changes. The input is the text data of the old and new terms of use, and the output is a list of changes. Here, a text comparison algorithm is used to identify the changes. Specifically, the strings on each line are compared with past data, and the changed parts are listed.

[0803] Step 3:

[0804] The server inputs the detected changes into a generative AI model to generate a summary. The input is a list of changes and a prompt, and the output is the summarized changes. Specifically, the server inputs a list of changes to the generative AI model using a prompt (e.g., "Please analyze the changes in the new terms of use and generate a summary") to obtain a summary.

[0805] Step 4:

[0806] The server inputs the user's emotional data into the Sentiment Engine for analysis, and then generates a risk summary. The input is the user's emotional data and summarized changes, and the output is a customized risk summary. Specifically, the server uses the Sentiment Engine to analyze the user's past emotional data, and based on the results, inputs prompts that highlight and notify the risks of the summarized changes into the generative AI model, and obtains the results.

[0807] Step 5:

[0808] The terminal receives the customized risk summary sent from the server and notifies the user. The input is the risk summary sent from the server, and the output is the notification displayed to the user. Specifically, the mobile terminal application receives the push notification and displays it on the user screen.

[0809] Step 6:

[0810] The user checks the notified risk summary and enters their evaluation of the terms of use through the application. The input is the user's evaluation data (star ratings and comments), and the output is the evaluation results being sent to the server. Specifically, the user enters the evaluation using the user interface and sends the data to the server.

[0811] Step 7:

[0812] The server stores the evaluation data collected from users in a database and makes it publicly available for other users to view. The input is the user's evaluation data, and the output is the published evaluation results. Specifically, the evaluation data is stored in a database management system and made public through a web interface.

[0813] Step 8:

[0814] The server selects reliable services and applications based on the collected evaluation data and displays them on a dedicated store. The input is a compilation of evaluation data, and the output is a list of reliable services. Specifically, services with high evaluation scores are selected using statistical analysis and displayed on a dedicated store page.

[0815] Step 9:

[0816] The server analyzes the ratings and reviews collected from users and generates an improvement proposal report for the company. The input is the rating and review data, and the output is an improvement proposal report. Specifically, it performs text mining to extract common problems and areas for improvement, and creates improvement proposals based on that.

[0817] 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.

[0818] 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.

[0819] 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.

[0820] [Third embodiment]

[0821] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0822] 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.

[0823] 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).

[0824] 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.

[0825] 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.

[0826] 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).

[0827] 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.

[0828] 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.

[0829] 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.

[0830] 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.

[0831] 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.

[0832] 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."

[0833] This invention is a system that automatically acquires and analyzes terms of use (terms and conditions) presented by online service providers, and displays a summary in an easy-to-understand format for users. It also has the functionality to receive user ratings, evaluate reliability based on those ratings, and provide improvement suggestions to companies. Below, we will explain how to specifically implement this system.

[0834] Overall system overview

[0835] The system has the following main functions:

[0836] 1. A function that automatically acquires and analyzes clause information to detect changes.

[0837] 2. Ability to summarize detected changes and notify the user.

[0838] 3. Ability to collect and publish user ratings.

[0839] 4. The ability to select reliable services and applications and display them in a dedicated store.

[0840] 5. A function that makes improvement suggestions to companies based on user ratings and reviews.

[0841] Automatic acquisition and analysis of clause information

[0842] The server periodically accesses a pre-registered web page (terms of service page) to retrieve the text data of the terms of service. The retrieved data is then sent to an analysis engine, which compares it with existing data to detect changes. For example, if a music streaming service revises part of its terms of service, the engine compares the old and new terms and automatically identifies changes to the data usage policy.

[0843] Risk Summary and Notification

[0844] The detected changes are summarized by the generative AI and the associated risks are explained in an easy-to-understand manner. The server stores the summarized information in a database, allowing users to review the information based on their own profile. Users can view the risk summary through their devices and intuitively understand it.

[0845] Collecting and publishing user ratings

[0846] Using a device, users access the service's terms of service page and use the interface to submit a rating. The rating includes a star rating and comments, which are then sent to the server. The server then stores the rating data in a database, making public ratings available to other users.

[0847] Selection and display of reliable services and applications

[0848] The server selects reliable services and applications based on the collected evaluation data, and displays these reliable services and applications in a dedicated online store, allowing users to download and install them with confidence.

[0849] Improvement proposals for companies

[0850] The server analyzes user ratings and reviews to identify common problems and areas for improvement. Based on this, an improvement proposal report is generated and provided to the service provider. For example, if multiple users have the same complaints about a particular feature, the server analyzes their feedback and makes appropriate improvement proposals.

[0851] Specific examples

[0852] For example, when a user signs up for a new video streaming service, the server automatically retrieves and analyzes the service's terms of service. The generative AI summarizes any important changes to the terms (e.g., updates to the privacy policy). This information is then notified to the user via their device. The user then reviews the summary and rates the terms. This rating is then sent to the server and made public for other users to refer to.

[0853] This system allows users to easily understand the terms of use and risks involved, creating an environment where they can use services with peace of mind. It also enables service providers to continuously improve the quality of their services based on user feedback.

[0854] The processing flow will be explained below.

[0855] Step 1:

[0856] The server executes a program that periodically accesses the terms of use page of a pre-registered Web service.

[0857] Step 2:

[0858] The server acquires the latest terms of use text data from the terms of use page and stores it in a database.

[0859] Step 3:

[0860] The server sends the latest obtained terms of use text data to the analysis engine.

[0861] Step 4:

[0862] The analysis engine compares the newly acquired terms of use text data with existing data and automatically detects changes.

[0863] Step 5:

[0864] The analysis engine sends the detected changes to the generation AI.

[0865] Step 6:

[0866] The generative AI evaluates the importance of the changes and generates a summary text.

[0867] Step 7:

[0868] The server stores the generated summary text in a risk assessment database.

[0869] Step 8:

[0870] The server notifies a particular user of a risk summary based on the user's profile information.

[0871] Step 9:

[0872] The user uses the terminal to check the risk summary notice.

[0873] Step 10:

[0874] The user accesses an interface to review the risk summary and evaluate the terms.

[0875] Step 11:

[0876] The terminal displays an input form for rating the regulations, allowing the user to input ratings and comments.

[0877] Step 12:

[0878] The user inputs a rating and a comment and submits it.

[0879] Step 13:

[0880] The server receives the evaluation data sent by the user and stores it in an evaluation database.

[0881] Step 14:

[0882] The server posts the evaluation in a public evaluation database so that other users can refer to the evaluation results.

[0883] Step 15:

[0884] The server selects highly reliable services and applications based on published evaluation data.

[0885] Step 16:

[0886] The server displays the selected services and applications in a dedicated store and makes them available to users.

[0887] Step 17:

[0888] Users using the device can access a dedicated store to view and download selected services and applications.

[0889] Step 18:

[0890] The server continuously analyzes user reviews and ratings to identify common problems and areas for improvement.

[0891] Step 19:

[0892] The analysis engine generates a report of specific improvement proposals based on the extracted problems and areas for improvement.

[0893] Step 20:

[0894] The server sends the generated improvement suggestion report to the company and provides feedback for service improvement.

[0895] Example 1

[0896] 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."

[0897] In modern Internet services, changes to terms of use are frequent, making it difficult for users to understand and evaluate the changes. Furthermore, there is a lack of objective criteria for selecting reliable services, and no mechanism exists for service providers to effectively incorporate user feedback into improvement proposals. This often leaves users feeling uneasy about using services, and service providers find it difficult to make appropriate improvements.

[0898] 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.

[0899] In this invention, the server includes means for acquiring terms and conditions information, means for analyzing the acquired terms and conditions information and automatically detecting changes, means for summarizing the detected changes using a generative AI model and displaying them to the user, and means for accepting user evaluations of the terms and conditions and publishing the evaluation results. This enables users to easily understand and evaluate changes to the terms and conditions, enabling them to select highly reliable services and propose appropriate improvements to service providers.

[0900] "Terms and conditions information" is a document containing the terms and conditions that a service provider presents to users.

[0901] "Means" refers to a method or apparatus for achieving a specific function or operation.

[0902] A "server" is a computer system that manages, processes, and distributes data over a network.

[0903] "User" refers to any individual or entity using the Service.

[0904] "Acquisition" is the act of collecting or obtaining necessary data or information.

[0905] "Analysis" is the process of examining data or information in detail to understand its meaning and structure.

[0906] "Changes" refers to the differences or modifications between the two documents or data being compared, old and new.

[0907] A "generative AI model" is a model that uses artificial intelligence technology to automatically generate text.

[0908] "Summarizing" refers to the process of summarizing detailed information concisely to extract only the main points.

[0909] "Evaluation" is the act of judging performance or value based on specific criteria and giving a score or comment.

[0910] "Publication" refers to making certain information publicly accessible.

[0911] "Reliability" refers to the ability and characteristics of a service or system to operate stably and as expected.

[0912] "Service" means an application or online platform that offers specific functionality or benefits.

[0913] "Selection" is the act of choosing the best one based on specific criteria.

[0914] "Exclusive Store" refers to an online platform that offers only selected specific applications and services.

[0915] A "review" is an act in which a user writes their opinion or impression about a service or product.

[0916] "Improvement proposals" are specific proposals for solving existing problems and improving performance and user experience.

[0917] A "report" is a document that systematically compiles specific information.

[0918] This invention relates to a system that automatically detects changes in terms of use for Internet services, summarizes them, and presents them to users, and selects and provides more reliable services. The invention is realized through processing steps mainly involving a server, a terminal, and a user.

[0919] Overall structure

[0920] The system includes the following main features:

[0921] 1. Automatic Acquisition of Terms of Use

[0922] 2. Analysis of changes to the Terms of Use

[0923] 3. Generate a summary of changes

[0924] 4. Summary storage and notification

[0925] 5. Collection and publication of user ratings

[0926] 6. Select a reliable service

[0927] 7. Generating improvement proposals for companies

[0928] Hardware and Software

[0929] The server works in conjunction with a database and natural language processing engine to automatically retrieve terms of use, analyze them, detect changes, generate summaries using a generative AI model, provide notifications, collect and publish ratings, select reliable services, and generate improvement proposal reports for companies.

[0930] For example, the analysis engine can use natural language processing toolkits such as NLTK and spaCy. For generative AI, OpenAI GPT is used as the generative AI model. The database can be an SQL database or a NoSQL database.

[0931] The terminal provides an interface for users to view summary information and evaluation results and input their own evaluations. Terminals include various devices such as smartphones, tablets, and PCs.

[0932] Users can check the summary of terms of service, rate and review the terms of service, and use a dedicated store to select reliable services.

[0933] Specific examples of processing

[0934] For example, when a user signs up for a new video streaming service, the server processes the following:

[0935] 1. The server accesses the terms of use page for that service and retrieves the HTML content.

[0936] 2. The retrieved content is analyzed using a natural language processing toolkit to detect changes.

[0937] 3. The changes are fed into a generative AI model to generate a summary.

[0938] 4. The server stores the generated summary in a database and notifies the user based on their profile.

[0939] 5. The user receives the notification through their device, checks the summary, and gives a rating, which is sent to the server and stored in the database.

[0940] Prompt Sentence Examples

[0941] "I've signed up for a new video streaming service. If the terms of service for this service change, I'd like to be notified with a summary of the changes. I'd also like to see other users' reviews."

[0942] This allows users to easily understand the terms of service and their changes, and to make appropriate evaluations. It also allows service providers to improve their services based on user feedback. This system increases user convenience and improves reliability.

[0943] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0944] Step 1:

[0945] The server periodically accesses a pre-registered web page (terms of use page) and retrieves HTML content. This operation is performed by sending an HTTP request and receiving HTML data as a response. The input is a list of URLs, and the output is the retrieved HTML content.

[0946] Step 2:

[0947] The server parses the retrieved HTML content and extracts the terms of use text data. It uses a parsing library (e.g. BeautifulSoup) to extract text from HTML. The input is the HTML content, and the output is the terms of use text data.

[0948] Step 3:

[0949] The server sends the retrieved terms of use text to an analysis engine (for example, natural language processing toolkits such as NLTK or spaCy), which compares the old and new data to detect changes. The input is the old and new terms of use text data, and the output is a list of changes.

[0950] Step 4:

[0951] The server inputs the list of changes into a generative AI model and generates a text summary of them. The summary is created using a generative AI model (e.g., OpenAI GPT). The input is the list of changes, and the output is a summarized risk description text.

[0952] Step 5:

[0953] The server saves the generated summary text to a database. This operation is performed by inserting the summary data into a specific table using a database connection library. The input is the summary text and the user's profile information, and the output is a flag indicating whether the save operation to the database was successful.

[0954] Step 6:

[0955] The server notifies the user to view information based on their profile. Notifications can be sent via email, push notification, or in-app notification. The input is the user's profile information and summary text, and the output is the notification sending status.

[0956] Step 7:

[0957] The user receives the notification through the terminal and views the summary information. The summary text is displayed on the terminal interface. The input is the notification message, and the output is the user's browsing history.

[0958] Step 8:

[0959] Users rate the terms of use and input their rating results. Star ratings and comments are recorded through the rating interface. The input is rating data (star ratings and comments), and the output is a rating record.

[0960] Step 9:

[0961] The server saves the evaluation results sent by users in a database and makes them publicly accessible to other users. This is also an operation that inserts and publishes evaluation data using the database connection library. The input is the evaluation data, and the output is a public evaluation dataset.

[0962] Step 10:

[0963] The server selects reliable services and applications based on the collected reputation data. This is the process of analyzing the reputation data and identifying services with high reputations. The input is a reputation dataset, and the output is a list of reliable services.

[0964] Step 11:

[0965] The server displays the selected reliable services in a dedicated store by inserting them into a display table in the database. The input is a list of reliable services, and the output is a display item in the dedicated store.

[0966] Step 12:

[0967] The server analyzes the ratings and reviews collected from users and extracts common problems and areas for improvement. This analysis is performed using a natural language processing toolkit. The input is the text data of the ratings and reviews, and the output is a list of the extracted problems and areas for improvement.

[0968] Step 13:

[0969] The server uses a generative AI model to generate an improvement proposal report for the company based on the extracted problems and improvement points. The input is a list of problems and improvement points, and the output is an improvement proposal report.

[0970] (Application example 1)

[0971] 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."

[0972] The frequent changes in terms of service for online services such as content distribution services make it difficult for users to understand the content. Users also have difficulty grasping the risks posed by changes in terms of service, leading to concerns about the reliability of the service. Furthermore, there is a lack of means to accurately reflect user feedback and improve the service.

[0973] 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.

[0974] In this invention, the server includes a means for acquiring terms and conditions information, a means for analyzing the acquired terms and conditions information and automatically detecting changes, a means for summarizing the detected changes using a generative AI model and displaying them to the user, a means for accepting user evaluations of the terms and conditions and publishing the evaluation results, and a means for recommending reliable content distribution services. This allows users to intuitively understand changes to the terms and conditions and the risks involved, and select reliable services. The server also includes a means for analyzing the evaluations and reviews collected from users using a generative AI model and generating improvement proposal reports for companies, enabling service providers to continuously improve their services based on user feedback.

[0975] A "server" is a computer system that receives requests over a network and provides data or services.

[0976] The "means for acquiring terms and conditions information" is a function that automatically collects text data of terms of use from the web page of the content distribution service.

[0977] "Means for automatically detecting changes by analyzing terms and conditions information" is a function that compares the old and new terms of use and identifies changes within the terms and conditions.

[0978] "Means for summarizing and displaying to the user using a generative AI model" is a function that uses AI technology to summarize detected changes and displays the summary in an easy-to-read format for the user.

[0979] The "means for accepting user evaluations of terms and conditions and publishing the evaluation results" is a function that allows users to submit evaluations and comments on the terms and conditions and publish the evaluations in a form that can be viewed by other users.

[0980] The "means for recommending highly reliable content distribution services" is a function that selects safe and highly reliable content distribution services based on collected user evaluation data and recommends them to users.

[0981] The "analysis means" is a function that analyzes collected user ratings and reviews and identifies areas for improvement in the service based on the results.

[0982] The "means for generating improvement proposal reports for companies" is a function that automatically creates reports that make specific improvement proposals to service providers based on user feedback.

[0983] This invention is a system that provides an environment in which users can use content distribution services with peace of mind by automatically acquiring, analyzing, summarizing, and evaluating terms of use. The following describes how to specifically implement this system.

[0984] Overall flow

[0985] First, the server periodically retrieves the text data of the terms of use from the web page of the content distribution service via the network. This is done using the Python libraries "requests" and "BeautifulSoup." The retrieved text data is then compared with old data, and changes are automatically detected using the "difflib" library.

[0986] The detected changes are then summarized using a generative AI model, using AI techniques such as GPT-4, and the summary is sent to the user's device, allowing them to intuitively understand the changes.

[0987] Users can use their devices to rate the terms of use and submit their evaluation comments. This evaluation data is stored on the server and can be accessed by other users.

[0988] Furthermore, the server analyzes the evaluation data and selects and recommends reliable content delivery services. To do this, it uses "SQLAlchemy" to manage the database and analyze the evaluation data.

[0989] Finally, the collected user ratings and reviews are analyzed using the generative AI model again to create a report with specific improvement proposals for the company. This report is provided to the service provider to support continuous service improvement.

[0990] Hardware and software used

[0991] Server: The central computer system that retrieves and processes data from the web pages of a content delivery service.

[0992] Device: The device used by the user, such as a smartphone, computer, or tablet.

[0993] software:

[0994] Python: Overall program control.

[0995] BeautifulSoup, requests: Get text data from web pages.

[0996] difflib: Detect changes in text data.

[0997] GPT-4 (OpenAI API): Generates summaries using a generative AI model.

[0998] Firebase Cloud Messaging (FCM): Sends notifications to users.

[0999] Flask, SQLAlchemy: Server-side data management and API construction.

[1000] Specific examples

[1001] 1. The server accesses the web page of a specific content distribution service and obtains the terms of use in text format.

[1002] 2. Analyze the old and new terms of use data and detect changes.

[1003] 3. Use a generative AI model (e.g., GPT-4) to summarize the changes and create a summary.

[1004] 4. The summary is sent to the user's device using FCM.

[1005] 5. Users will receive a notification and review and evaluate the changes to the Terms of Use.

[1006] 6. The server collects evaluation data from users and selects and recommends reliable services.

[1007] 7. Furthermore, the system reanalyzes user ratings and reviews to generate a report with specific improvement suggestions for the service provider.

[1008] Prompt Sentence Examples

[1009] "Please summarize the following changes to the terms and conditions and explain their risks.

[1010] New Terms: [New Terms Text]

[1011] Old Terms: [old terms text]"

[1012] This system allows users to easily understand the terms of use and risks involved, enabling them to use content distribution services with peace of mind. It also enables service providers to continuously improve their services based on user feedback.

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

[1014] Step 1:

[1015] The server accesses the web page of a specific content distribution service and retrieves the text data of the terms of use. Specifically, it uses the Python "requests" and "BeautifulSoup" libraries to scrape the terms of use text from this web page. The input of this step is the URL of the web page, and the output is the retrieved text data of the terms of use.

[1016] Step 2:

[1017] The server compares the retrieved text data of the terms of use with the existing data to detect changes. The "difflib" library is used to detect changes. The input is the old and new terms of use text, and the output is differential information indicating the changes. In this data processing process, the old and new texts are compared line by line, and the different parts are extracted.

[1018] Step 3:

[1019] The server summarizes the detected changes using a generative AI model. AI technologies such as GPT-4 are used for generation. Specifically, the changes are sent as input data to the OpenAI API, and the summarized text is received as output. The input is difference information, and the output is the summarized changes.

[1020] Step 4:

[1021] The server notifies the user's device of the summarized changes. This notification uses Firebase Cloud Messaging (FCM). The input is the text of the summarized changes, and the output is a notification that is displayed on the user's device. The server obtains the user's device ID and sends the notification message via FCM.

[1022] Step 5:

[1023] The user uses the terminal to check the changes to the terms of use and rate the terms. The rating can include star ratings and comments. The input is a summary of the changes and the user's rating information, and the output is the rating data. The terminal receives the input from the user through a rating interface.

[1024] Step 6:

[1025] The server stores the evaluation data collected from users in a database and selects reliable content delivery services. "SQLAlchemy" is used for database management. The input is user evaluation data, and the output is a list of reliable services. The server scores the evaluation data and lists the services with the highest scores.

[1026] Step 7:

[1027] The server uses a generative AI model to analyze the ratings and reviews collected from users and generate a report of specific improvement proposals for the company. GPT-4 is again used for the analysis. The input is the user's rating data and reviews, and the output is a report of improvement proposals. The server sends the ratings and reviews to the AI ​​model and compiles the generated improvement proposals for the company.

[1028] Through each step of this process, the system enables users to intuitively understand the content and risks of the terms of use, helps them select reliable services, and allows service providers to continuously improve their services based on user feedback.

[1029] 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.

[1030] This invention is a system that combines an emotion engine that recognizes user emotions, and has the function of automatically acquiring and analyzing terms of use (terms and conditions) presented by online service providers, and displaying a summary of any changes. It also has the function of providing user ratings, reliability assessments based on those ratings, and suggesting improvements to companies. Below, we will explain how to specifically implement this system.

[1031] Overall system overview

[1032] The system has the following main functions:

[1033] 1. A function that automatically acquires and analyzes clause information to detect changes.

[1034] 2. Ability to summarize detected changes and notify the user.

[1035] 3. The ability to recognize user sentiment and customize risk summaries based on that data.

[1036] 4. A function to collect user ratings and publish the results.

[1037] 5. Ability to select reliable services and applications and display them in a dedicated store.

[1038] 6. Ability to use user sentiment data to improve the reliability of ratings.

[1039] 7. A function that makes improvement suggestions to companies based on user ratings and reviews.

[1040] Automatic acquisition and analysis of clause information

[1041] The server periodically accesses a pre-registered web page (terms of use page) and retrieves the text data of the terms of use. The retrieved data is sent to an analysis engine, which compares it with existing data to detect changes. For example, if a social networking service revise its terms of use, the old and new terms are compared and changes regarding the handling of user data are automatically identified.

[1042] Risk summary and emotion-aware notification

[1043] The server uses generative AI to summarize the detected changes and clearly explain the risks. The emotion engine also works to retrieve past emotional data from the user's profile and customize the risk summary notification accordingly. For example, a user who has previously expressed strong concerns about data leaks will receive notifications that specifically highlight changes related to data security.

[1044] Collecting and publishing user ratings

[1045] Using a device, users access the service's terms of use page and use the interface to rate the service. The rating includes a star rating and comments, and is sent to the server. The server stores the rating data in a database so that other users can refer to public ratings.

[1046] Selection and display of reliable services and applications

[1047] The server comprehensively evaluates the collected evaluation data and emotion data to select highly reliable services and applications. These highly reliable services and applications are displayed in a dedicated online store, allowing users to use them with peace of mind.

[1048] Improving the reliability of ratings using user emotions

[1049] The emotion engine collects emotional data from users at the time of rating and uses that data to verify the reliability of the ratings. For example, if a particular rating is extremely high, it may determine that the user is overly excited and may discount that rating.

[1050] Improvement proposals for companies

[1051] The server analyzes user ratings, reviews, and sentiment data to identify common issues and areas for improvement. Specific improvement proposal reports are then provided to the service provider. For example, if multiple users express concerns about a new pricing plan, the server can suggest reconsidering the plan based on that feedback.

[1052] Specific examples

[1053] For example, when a user signs up for a new cloud storage service, the server automatically retrieves and analyzes the service's terms of use to detect any changes. The generative AI summarizes important changes to the terms (e.g., changes to data retention periods), and this information is passed through an emotion engine to notify the user in a format appropriate for them. The user then checks the notification and rates the service. This rating is made public for other users to view, and the service is displayed in a dedicated store as a reliable service. Companies can use the provided improvement proposal report to improve their services.

[1054] This system allows users to easily understand the terms of use, understand the risks, and use the service with peace of mind. It also enables service providers to continuously improve the quality of their services based on user feedback and sentiment data.

[1055] The processing flow will be explained below.

[1056] Step 1:

[1057] The server executes a program that periodically accesses the terms of use page of a pre-registered Web service.

[1058] Step 2:

[1059] The server acquires the latest terms of use text data from the terms of use page and stores it in a database.

[1060] Step 3:

[1061] The server sends the latest obtained terms of use text data to the analysis engine.

[1062] Step 4:

[1063] The analysis engine compares the newly acquired terms of use text data with existing data and automatically detects changes.

[1064] Step 5:

[1065] The analysis engine sends the detected changes to the generation AI.

[1066] Step 6:

[1067] The generative AI evaluates the importance of the changes and generates a summary text.

[1068] Step 7:

[1069] The generation AI compares past user emotional data and reflects it in the risk summary text.

[1070] Step 8:

[1071] The server stores the generated summary text in a risk assessment database.

[1072] Step 9:

[1073] The server notifies a particular user of a risk summary based on the user's profile information.

[1074] Step 10:

[1075] The user checks the risk summary notice using the terminal.

[1076] Step 11:

[1077] The user has access to an interface to review the risk summary and evaluate the terms and conditions.

[1078] Step 12:

[1079] The terminal displays an input form for evaluation, allowing the user to input an evaluation and comments.

[1080] Step 13:

[1081] The user inputs a rating and a comment and submits it.

[1082] Step 14:

[1083] The emotion engine collects real-time emotion data from users who are rating.

[1084] Step 15:

[1085] The server receives the ratings and emotion data sent by the users and stores them in a rating database.

[1086] Step 16:

[1087] The server posts the evaluation in a public evaluation database so that other users can refer to the evaluation results.

[1088] Step 17:

[1089] The server selects reliable services and applications based on the published evaluation data and emotion data.

[1090] Step 18:

[1091] The server displays the selected services and applications in a dedicated store and makes them available to users.

[1092] Step 19:

[1093] Users using the device can access a dedicated store to view and download selected services and applications.

[1094] Step 20:

[1095] The server continuously analyzes user reviews and ratings to identify common problems and areas for improvement.

[1096] Step 21:

[1097] The analysis engine generates a report of specific improvement proposals based on the extracted problems and areas for improvement.

[1098] Step 22:

[1099] The server sends the generated improvement suggestion report to the company and provides feedback for service improvement.

[1100] Example 2

[1101] 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."

[1102] In modern information technology services, terms of use are frequently updated, and their complicated content makes it difficult for users to understand the changes. Furthermore, there is a lack of information provided that reflects users' feelings and individual risk perceptions, making it difficult for users to appropriately manage risks. Furthermore, user evaluations are not widely shared as reliable, and the quality of feedback provided to service providers is low. As a result, there are problems with delays in improving service reliability and implementing improvement suggestions.

[1103] 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 means for acquiring terms of use information, means for automatically detecting changes by analyzing the acquired terms of use information, means for using a generative AI model to summarize the detected changes, means for customizing a risk summary based on user emotion data, means for notifying the user of the customized summary, and means for accepting user terms of use evaluations and publishing the evaluation results. This makes it possible to quickly and accurately notify users of changes to the terms of use and provide information tailored to individual risk perceptions. Furthermore, the collected user evaluations can be used to improve the reliability of services and make specific improvement proposals to service providers.

[1104] "Terms of Use Information" refers to documents that include the terms of use and privacy policy of the services that information technology services provide to users.

[1105] "Means of acquisition" refers to the function by which the server accesses a web page via the Internet and automatically acquires terms of use information.

[1106] "Means of analysis" refers to the function of sending the terms of use information acquired by the server to an internal analysis engine and converting the text into structured data using natural language processing technology.

[1107] "Means for automatically detecting changes" refers to a function in which the server uses an algorithm to compare the old and new terms of use information and identify the differences.

[1108] "Means for using a generative AI model" refers to the function by which the server sends a prompt sentence to the generative AI model and automatically generates a summary.

[1109] "User emotion data" refers to a log of a user's past reactions and emotions, data that is used to create a customized summary.

[1110] "Means for customizing risk summaries based on emotional data" refers to a function that adjusts the summary content according to the user's emotions based on the user's emotional data collected by the server.

[1111] "Means for notifying the user of the customized summary" refers to the function by which the server sends the customized summary to the user's device via email or in-app push notification.

[1112] The "means for accepting a regulation evaluation" refers to a function that provides an interface for users to input evaluations and that the server accepts them.

[1113] "Means for publishing evaluation results" refers to a function that stores the evaluation data collected by the server in a database and makes it publicly available for other users to refer to.

[1114] "Highly reliable information technology services" refer to services that are judged to have high overall reliability based on user ratings and sentiment data.

[1115] "Means for displaying in a dedicated store" refers to a function for displaying highly reliable services selected by the server to users in an online store.

[1116] "Sales Improvement Proposal Report" refers to a report containing specific improvements that is provided to service providers after analyzing ratings, reviews, and sentiment data collected from users.

[1117] This invention builds a system that combines an emotion engine that recognizes user emotions. The system periodically accesses the terms of use page, analyzes the acquired data to detect changes, generates summaries using a generative AI model, and customizes information based on the user's emotion data. Furthermore, it collects user ratings, selects and displays reliable services based on them, and makes improvement suggestions to companies.

[1118] Hardware and software used

[1119] The server contains the following main components:

[1120] Web crawler: Periodically accesses terms of use pages on the Internet and obtains text data. Specific software used is Apache Nutch and Scrapy.

[1121] Analysis engine: Analyzes the acquired text and stores it as structured data. Utilizes natural language processing (NLP) technology using Python or Java. NLTK or spaCy are often used.

[1122] Difference detection algorithm: Compares the old and new data and detects changes. Diff-Match-Patch or a similar library is used for difference detection.

[1123] Generative AI model: To summarize the changes, we use a generative AI model such as OpenAI GPT. We create an input prompt and generate a summary.

[1124] Sentiment engine: Analyzes user sentiment data and customizes summary content. Sentiment analysis uses Google Cloud Natural Language API and Microsoft Azure Text Analytics.

[1125] Notification system: Notify users with a customized summary. Possible notification methods include email and push notifications. Firebase Cloud Messaging (FCM) and AWS SNS (Simple Notification Service) are used.

[1126] The terminal is used as an interface for users to input their evaluations. Specifically, this applies to smartphones, PCs, and tablets.

[1127] Users receive notifications and provide ratings, and the rating data is used to improve reliability and propose improvements to the company.

[1128] Specific examples

[1129] For example, when a user signs up for a new cloud storage service, the following happens:

[1130] 1. The server accesses the terms of use page of the cloud storage service to obtain text data. Using a web crawler, the server periodically accesses this page to obtain the latest terms.

[1131] 2. The server sends the acquired text data to an analysis engine, which uses natural language processing technology to extract paragraphs and sections and store them in a database.

[1132] 3. The server compares the old and new data and identifies changes using a difference detection algorithm. For example, it detects that the "personal information storage period" has been changed from "6 months" to "1 year."

[1133] 4. The server generates a summary by sending the following prompt to the generative AI model: "Please summarize the changes in the new terms of use, such as changes to data retention periods and new policies regarding information leaks. Please make sure the risks are clearly explained."

[1134] 5. The server uses an emotion engine to customize this summary based on the user's emotion data. For example, if a user has previously expressed strong concerns about data leaks, the server generates a summary that specifically highlights changes related to data security.

[1135] 6. The server sends a customized summary to the user's device. Notification methods include email and push notification. "The terms of use for the new cloud storage service have been revised. The data retention period has been changed from six months to one year. Please click here for details."

[1136] 7. Upon receiving the notification, the user enters their rating using their device, leaving a comment or star rating, and the rating data is sent to the server.

[1137] 8. The server stores the collected evaluation data in a database and makes it publicly available for other users to refer to, allowing other users to determine the reliability of information technology services.

[1138] 9. The server selects reliable IT services based on the collected evaluation data and displays them in a dedicated store, allowing users to select services with confidence.

[1139] 10. The server analyzes the ratings and reviews collected from users and generates a report of improvement proposals for sales based on the results. It provides the service provider with a specific report such as, "70% of users are unsure about the new pricing plan, so we recommend that you reconsider the plan."

[1140] As a result, users will be able to quickly understand changes to the terms of use and receive information tailored to their individual risk perceptions, and appropriate feedback will be provided to service providers, which is expected to lead to improved service quality.

[1141] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1142] Step 1: Automatically retrieve terms of use

[1143] The server periodically accesses a pre-registered web page (terms of use page) and obtains text data. A web crawler (for example, Apache Nutch or Scrapy) is used to access the URL and download the terms of use in HTML format. The input data is the URL, and the output data is the obtained text data. This text data is saved in a data store within the server.

[1144] Step 2: Parsing the Terms of Use

[1145] The server sends the acquired text data to an analysis engine. The analysis engine (e.g., NLTK or spaCy) uses natural language processing techniques to divide the text into paragraphs and sections and convert it into structured data. The input data is the terms of use text in HTML format, and the output data is structured paragraph data. The analysis results are stored in a database.

[1146] Step 3: Detecting changes

[1147] The server compares the newly acquired terms of use data with the existing terms of use data. It uses a difference detection algorithm (e.g., Diff-Match-Patch) to detect changes between the two. The input data is the old and new terms of use data, and the output data is a list of changes. This list of changes is also saved in the database.

[1148] Step 4: Generative AI model generates a summary

[1149] The server sends the list of detected changes to a generative AI model, which generates a summary. The input prompt is, "Please summarize the changes in the new terms of use. For example, changes to data retention periods or new policies regarding information leaks. Please make sure that the risks are clearly explained." The generative AI model (e.g., OpenAI GPT) generates a summary based on this prompt and the list of changes. The input data are the prompt and the list of changes, and the output data is a summary of the changes. This summary is also stored in the database.

[1150] Step 5: Customize the risk summary

[1151] The server uses the user's emotional data to customize the generated summary. The emotion engine (e.g., Google Cloud Natural Language API) analyzes the user's past emotional data and customizes the importance and risk of changes. The input data is the user's emotional data and the summary, and the output data is the customized summary. This customized summary is associated with the user profile and saved.

[1152] Step 6: Notify users

[1153] The server sends a customized summary to the user's device. A notification system (for example, Firebase Cloud Messaging or AWS SNS) is used to send the notification to the user's email address or app. The input data is the customized summary and the user's contact information, and the output data is the sending result (success or failure). The notification content often includes a message such as, "The terms of use for the new cloud storage service have been revised. The data retention period has been changed from 6 months to 1 year. Please click here for details."

[1154] Step 7: Collect user ratings

[1155] The user checks the notification using a terminal and rates it through the rating interface. The user accesses the rating interface and inputs a star rating and comments. The input data is the user's rating information, and the output data is data stored in the rating database. The rating content includes comments such as "I feel reassured by the new policy."

[1156] Step 8: Publish evaluation data

[1157] The server stores the collected evaluation data in a database and makes it publicly available for other users to refer to. Highly reliable service information is provided through a public interface. The input data is the data in the evaluation database, and the output data is evaluation information that can be viewed by other users. This allows newly registered users to refer to the evaluations of other users.

[1158] Step 9: Choose a reliable service

[1159] The server comprehensively evaluates the collected evaluation data and sentiment data to select highly reliable services. It uses an algorithm to calculate a reliability score and selects services with a certain score or higher. The input data are the evaluation data and sentiment data, and the output data is a list of selected highly reliable services. This list is displayed in a dedicated store.

[1160] Step 10: Generate improvement proposals for the company

[1161] The server analyzes the ratings and reviews collected from users and generates an improvement proposal report based on the results. An analysis engine is used to extract common problems and areas for improvement, and specific proposals are generated. The input data are rating data and reviews, and the output data is an improvement proposal report. This report is provided to the service provider and used to improve the service. For example, a report may be generated stating, "70% of users are unsure about the new pricing plan, so we recommend that you reconsider the plan."

[1162] (Application example 2)

[1163] 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."

[1164] Modern internet services frequently change their terms of use, making it difficult for users to keep track of all of these changes. Furthermore, because users' feelings and perceptions of risk vary, typical notification methods fail to provide appropriate information to each user. This raises the risk that users may miss important changes to the terms of use and end up suffering disadvantages. Furthermore, there is currently a lack of appropriate collection and analysis of user feedback, and the resulting evaluation of reliability and measures to improve services.

[1165] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring terms and conditions information, means for automatically detecting changes by analyzing the acquired terms and conditions information, means for summarizing the detected changes and displaying them to the user, means for analyzing the user's emotional data and customizing and notifying a risk summary, and means for accepting user evaluations of the terms and conditions and publishing the evaluation results. This allows users to easily understand important changes to the terms and conditions and receive information based on their own emotions and risk perceptions. In addition, collecting and publishing user feedback allows other users to select reliable services, and companies can improve their services based on user evaluations and reviews.

[1166] The "means for obtaining terms and conditions information" is a function that automatically collects terms and conditions data that are periodically posted by service providers on the Internet.

[1167] "Means for automatically detecting changes by analyzing acquired terms and conditions information" is a function that analyzes collected terms and conditions data and identifies changes by comparing it with the previous version.

[1168] "Means for summarizing detected changes and displaying them to the user" is a function that uses a generative AI model to summarize detected changes and display them in an easy-to-understand manner for the user.

[1169] The "means for analyzing user emotional data and customizing and notifying a risk summary" is a function that analyzes a user's past emotional data and generates and notifies an optimal risk summary for each individual user.

[1170] The "means for accepting user evaluations of terms and conditions and publishing the evaluation results" is a function that collects evaluations and feedback on the terms and conditions provided by users and publishes the results so that other users can view them.

[1171] "Means of selecting reliable services and applications based on evaluation results and displaying them in a dedicated store" refers to a function that selects highly rated services and applications based on collected evaluation data and displays them on a dedicated store page.

[1172] "A means for analyzing ratings and reviews collected from users and generating improvement proposal reports for companies based on the analysis results" refers to a function that performs data analysis of ratings and reviews provided by users and generates a report that makes improvement proposals to companies based on the results.

[1173] A "generative AI model" is a form of artificial intelligence that learns from massive amounts of text data and performs text generation, automatic summarization, and question answering for specific tasks.

[1174] A "prompt sentence" is an input sentence that instructs a generative AI model on the task to be performed or the content to be generated.

[1175] This invention is a system for enabling users to properly understand the importance of changes to terms of use, and provides a customized risk summary based on the user's emotional data. This system is mainly composed of a server, a user terminal, and a communication network.

[1176] Overall system description

[1177] The server has the following main functions:

[1178] How to obtain policy information

[1179] A method for automatically detecting changes by analyzing acquired clause information

[1180] A means to summarize the detected changes and display them to the user

[1181] A method to analyze user sentiment data and provide customized risk summaries

[1182] A means of accepting user evaluations of terms and conditions and publishing the evaluation results

[1183] Hardware and software used

[1184] The system uses the following hardware and software:

[1185] Hardware: Servers, smartphones

[1186] Software: Python, BeautifulSoup (HTML parsing), requests (HTTP requests), SentimentEngine (sentiment analysis module), SummaryEngine (summary generation module)

[1187] Data processing and calculation

[1188] The server periodically accesses pre-registered web pages (terms of use pages for various services) and retrieves the text data of the terms of use using the HTML analysis library BeautifulSoup and the HTTP request library requests. The retrieved data is compared with past terms of use data to detect changes. As part of this analysis, a generative AI model is used to generate a summary of the changes.

[1189] The smartphone, which acts as a user terminal, receives and displays the summary notification sent from the server. In addition, the user's emotional data is analyzed using SentimentEngine, and a risk summary is customized based on the user's past emotional data.

[1190] Specific examples

[1191] For example, when a user registers for a new web storage service, the server automatically retrieves and analyzes the service's terms of use to detect any changes. The generative AI summarizes important changes to the terms (e.g., changes to data retention periods), and this information is passed through an emotion engine to notify the user in a format appropriate for them. The user then checks the notification and rates the service. This rating is made public for other users to view, and the service is displayed in a dedicated store as a reliable service. Companies can use the provided improvement proposal report to improve their services.

[1192] Prompt Sentence Examples

[1193] "Analyze the changes in the new Terms of Service, highlight the changes in the Privacy Policy, and generate a summary that is relevant to the user, who has expressed strong concerns about data security in the past."

[1194] By using this specific method, users can easily understand the terms of use and use the service with peace of mind. In addition, service providers can continuously improve the quality of their services based on user feedback and sentiment data.

[1195] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1196] Step 1:

[1197] The server periodically accesses a pre-registered web page (terms of use page) and retrieves the text data of the terms of use using the HTML parsing library BeautifulSoup and the HTTP request library requests. The input is the URL of the terms of use page, and the output is the retrieved text data. Specifically, the requests library sends an HTTP request and receives an HTML response. BeautifulSoup is then used to parse the HTML data and extract the text portion.

[1198] Step 2:

[1199] The server saves the acquired text data and compares it with past data to detect changes. The input is the text data of the old and new terms of use, and the output is a list of changes. Here, a text comparison algorithm is used to identify the changes. Specifically, the strings on each line are compared with past data, and the changed parts are listed.

[1200] Step 3:

[1201] The server inputs the detected changes into a generative AI model to generate a summary. The input is a list of changes and a prompt, and the output is the summarized changes. Specifically, the server inputs a list of changes to the generative AI model using a prompt (e.g., "Please analyze the changes in the new terms of use and generate a summary") to obtain a summary.

[1202] Step 4:

[1203] The server inputs the user's emotional data into the Sentiment Engine for analysis, and then generates a risk summary. The input is the user's emotional data and summarized changes, and the output is a customized risk summary. Specifically, the server uses the Sentiment Engine to analyze the user's past emotional data, and based on the results, inputs prompts that highlight and notify the risks of the summarized changes into the generative AI model, and obtains the results.

[1204] Step 5:

[1205] The terminal receives the customized risk summary sent from the server and notifies the user. The input is the risk summary sent from the server, and the output is the notification displayed to the user. Specifically, the mobile terminal application receives the push notification and displays it on the user screen.

[1206] Step 6:

[1207] The user checks the notified risk summary and enters their evaluation of the terms of use through the application. The input is the user's evaluation data (star ratings and comments), and the output is the evaluation results being sent to the server. Specifically, the user enters the evaluation using the user interface and sends the data to the server.

[1208] Step 7:

[1209] The server stores the evaluation data collected from users in a database and makes it publicly available for other users to view. The input is the user's evaluation data, and the output is the published evaluation results. Specifically, the evaluation data is stored in a database management system and made public through a web interface.

[1210] Step 8:

[1211] The server selects reliable services and applications based on the collected evaluation data and displays them on a dedicated store. The input is a compilation of evaluation data, and the output is a list of reliable services. Specifically, services with high evaluation scores are selected using statistical analysis and displayed on a dedicated store page.

[1212] Step 9:

[1213] The server analyzes the ratings and reviews collected from users and generates an improvement proposal report for the company. The input is the rating and review data, and the output is an improvement proposal report. Specifically, it performs text mining to extract common problems and areas for improvement, and creates improvement proposals based on that.

[1214] 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.

[1215] 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.

[1216] 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.

[1217] [Fourth embodiment]

[1218] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1219] 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.

[1220] 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).

[1221] 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.

[1222] 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.

[1223] 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).

[1224] 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.

[1225] 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.

[1226] 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.

[1227] 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.

[1228] 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.

[1229] 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.

[1230] 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."

[1231] This invention is a system that automatically acquires and analyzes terms of use (terms and conditions) presented by online service providers, and displays a summary in an easy-to-understand format for users. It also has the functionality to receive user ratings, evaluate reliability based on those ratings, and provide improvement suggestions to companies. Below, we will explain how to specifically implement this system.

[1232] Overall system overview

[1233] The system has the following main functions:

[1234] 1. A function that automatically acquires and analyzes clause information to detect changes.

[1235] 2. Ability to summarize detected changes and notify the user.

[1236] 3. Ability to collect and publish user ratings.

[1237] 4. The ability to select reliable services and applications and display them in a dedicated store.

[1238] 5. A function that makes improvement suggestions to companies based on user ratings and reviews.

[1239] Automatic acquisition and analysis of clause information

[1240] The server periodically accesses a pre-registered web page (terms of service page) to retrieve the text data of the terms of service. The retrieved data is then sent to an analysis engine, which compares it with existing data to detect changes. For example, if a music streaming service revises part of its terms of service, the engine compares the old and new terms and automatically identifies changes to the data usage policy.

[1241] Risk Summary and Notification

[1242] The detected changes are summarized by the generative AI and the associated risks are explained in an easy-to-understand manner. The server stores the summarized information in a database, allowing users to review the information based on their own profile. Users can view the risk summary through their devices and intuitively understand it.

[1243] Collecting and publishing user ratings

[1244] Using a device, users access the service's terms of service page and use the interface to submit a rating. The rating includes a star rating and comments, which are then sent to the server. The server then stores the rating data in a database, making public ratings available to other users.

[1245] Selection and display of reliable services and applications

[1246] The server selects reliable services and applications based on the collected evaluation data, and displays these reliable services and applications in a dedicated online store, allowing users to download and install them with confidence.

[1247] Improvement proposals for companies

[1248] The server analyzes user ratings and reviews to identify common problems and areas for improvement. Based on this, an improvement proposal report is generated and provided to the service provider. For example, if multiple users have the same complaints about a particular feature, the server analyzes their feedback and makes appropriate improvement proposals.

[1249] Specific examples

[1250] For example, when a user signs up for a new video streaming service, the server automatically retrieves and analyzes the service's terms of service. The generative AI summarizes any important changes to the terms (e.g., updates to the privacy policy). This information is then notified to the user via their device. The user then reviews the summary and rates the terms. This rating is then sent to the server and made public for other users to refer to.

[1251] This system allows users to easily understand the terms of use and risks involved, creating an environment where they can use services with peace of mind. It also enables service providers to continuously improve the quality of their services based on user feedback.

[1252] The processing flow will be explained below.

[1253] Step 1:

[1254] The server executes a program that periodically accesses the terms of use page of a pre-registered Web service.

[1255] Step 2:

[1256] The server acquires the latest terms of use text data from the terms of use page and stores it in a database.

[1257] Step 3:

[1258] The server sends the latest obtained terms of use text data to the analysis engine.

[1259] Step 4:

[1260] The analysis engine compares the newly acquired terms of use text data with existing data and automatically detects changes.

[1261] Step 5:

[1262] The analysis engine sends the detected changes to the generation AI.

[1263] Step 6:

[1264] The generative AI evaluates the importance of the changes and generates a summary text.

[1265] Step 7:

[1266] The server stores the generated summary text in a risk assessment database.

[1267] Step 8:

[1268] The server notifies a particular user of a risk summary based on the user's profile information.

[1269] Step 9:

[1270] The user uses the terminal to check the risk summary notice.

[1271] Step 10:

[1272] The user accesses an interface to review the risk summary and evaluate the terms.

[1273] Step 11:

[1274] The terminal displays an input form for rating the regulations, allowing the user to input ratings and comments.

[1275] Step 12:

[1276] The user inputs a rating and a comment and submits it.

[1277] Step 13:

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

[1279] Step 14:

[1280] The server posts the evaluation in a public evaluation database so that other users can refer to the evaluation results.

[1281] Step 15:

[1282] The server selects highly reliable services and applications based on published evaluation data.

[1283] Step 16:

[1284] The server displays the selected services and applications in a dedicated store and makes them available to users.

[1285] Step 17:

[1286] Users using the device can access a dedicated store to view and download selected services and applications.

[1287] Step 18:

[1288] The server continuously analyzes user reviews and ratings to identify common problems and areas for improvement.

[1289] Step 19:

[1290] The analysis engine generates a report of specific improvement proposals based on the extracted problems and areas for improvement.

[1291] Step 20:

[1292] The server sends the generated improvement suggestion report to the company and provides feedback for service improvement.

[1293] Example 1

[1294] 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."

[1295] In modern Internet services, changes to terms of use are frequent, making it difficult for users to understand and evaluate the changes. Furthermore, there is a lack of objective criteria for selecting reliable services, and no mechanism exists for service providers to effectively incorporate user feedback into improvement proposals. This often leaves users feeling uneasy about using services, and service providers find it difficult to make appropriate improvements.

[1296] 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.

[1297] In this invention, the server includes means for acquiring terms and conditions information, means for analyzing the acquired terms and conditions information and automatically detecting changes, means for summarizing the detected changes using a generative AI model and displaying them to the user, and means for accepting user evaluations of the terms and conditions and publishing the evaluation results. This enables users to easily understand and evaluate changes to the terms and conditions, enabling them to select highly reliable services and propose appropriate improvements to service providers.

[1298] "Terms and conditions information" is a document containing the terms and conditions that a service provider presents to users.

[1299] "Means" refers to a method or apparatus for achieving a specific function or operation.

[1300] A "server" is a computer system that manages, processes, and distributes data over a network.

[1301] "User" refers to any individual or entity using the Service.

[1302] "Acquisition" is the act of collecting or obtaining necessary data or information.

[1303] "Analysis" is the process of examining data or information in detail to understand its meaning and structure.

[1304] "Changes" refers to the differences or modifications between the two documents or data being compared, old and new.

[1305] A "generative AI model" is a model that uses artificial intelligence technology to automatically generate text.

[1306] "Summarizing" refers to the process of summarizing detailed information concisely to extract only the main points.

[1307] "Evaluation" is the act of judging performance or value based on specific criteria and giving a score or comment.

[1308] "Publication" refers to making certain information publicly accessible.

[1309] "Reliability" refers to the ability and characteristics of a service or system to operate stably and as expected.

[1310] "Service" means an application or online platform that offers specific functionality or benefits.

[1311] "Selection" is the act of choosing the best one based on specific criteria.

[1312] "Exclusive Store" refers to an online platform that offers only selected specific applications and services.

[1313] A "review" is an act in which a user writes their opinion or impression about a service or product.

[1314] "Improvement proposals" are specific proposals for solving existing problems and improving performance and user experience.

[1315] A "report" is a document that systematically compiles specific information.

[1316] This invention relates to a system that automatically detects changes in terms of use for Internet services, summarizes them, and presents them to users, and selects and provides more reliable services. The invention is realized through processing steps mainly involving a server, a terminal, and a user.

[1317] Overall structure

[1318] The system includes the following main features:

[1319] 1. Automatic Acquisition of Terms of Use

[1320] 2. Analysis of changes to the Terms of Use

[1321] 3. Generate a summary of changes

[1322] 4. Summary storage and notification

[1323] 5. Collection and publication of user ratings

[1324] 6. Select a reliable service

[1325] 7. Generating improvement proposals for companies

[1326] Hardware and Software

[1327] The server works in conjunction with a database and natural language processing engine to automatically retrieve terms of use, analyze them, detect changes, generate summaries using a generative AI model, provide notifications, collect and publish ratings, select reliable services, and generate improvement proposal reports for companies.

[1328] For example, the analysis engine can use natural language processing toolkits such as NLTK and spaCy. For generative AI, OpenAI GPT is used as the generative AI model. The database can be an SQL database or a NoSQL database.

[1329] The terminal provides an interface for users to view summary information and evaluation results and input their own evaluations. Terminals include various devices such as smartphones, tablets, and PCs.

[1330] Users can check the summary of terms of service, rate and review the terms of service, and use a dedicated store to select reliable services.

[1331] Specific examples of processing

[1332] For example, when a user signs up for a new video streaming service, the server processes the following:

[1333] 1. The server accesses the terms of use page for that service and retrieves the HTML content.

[1334] 2. The retrieved content is analyzed using a natural language processing toolkit to detect changes.

[1335] 3. The changes are fed into a generative AI model to generate a summary.

[1336] 4. The server stores the generated summary in a database and notifies the user based on their profile.

[1337] 5. The user receives the notification through their device, checks the summary, and gives a rating, which is sent to the server and stored in the database.

[1338] Prompt Sentence Examples

[1339] "I've signed up for a new video streaming service. If the terms of service for this service change, I'd like to be notified with a summary of the changes. I'd also like to see other users' reviews."

[1340] This allows users to easily understand the terms of service and their changes, and to make appropriate evaluations. It also allows service providers to improve their services based on user feedback. This system increases user convenience and improves reliability.

[1341] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1342] Step 1:

[1343] The server periodically accesses a pre-registered web page (terms of use page) and retrieves HTML content. This operation is performed by sending an HTTP request and receiving HTML data as a response. The input is a list of URLs, and the output is the retrieved HTML content.

[1344] Step 2:

[1345] The server parses the retrieved HTML content and extracts the terms of use text data. It uses a parsing library (e.g. BeautifulSoup) to extract text from HTML. The input is the HTML content, and the output is the terms of use text data.

[1346] Step 3:

[1347] The server sends the retrieved terms of use text to an analysis engine (for example, natural language processing toolkits such as NLTK or spaCy), which compares the old and new data to detect changes. The input is the old and new terms of use text data, and the output is a list of changes.

[1348] Step 4:

[1349] The server inputs the list of changes into a generative AI model and generates a text summary of them. The summary is created using a generative AI model (e.g., OpenAI GPT). The input is the list of changes, and the output is a summarized risk description text.

[1350] Step 5:

[1351] The server saves the generated summary text to a database. This operation is performed by inserting the summary data into a specific table using a database connection library. The input is the summary text and the user's profile information, and the output is a flag indicating whether the save operation to the database was successful.

[1352] Step 6:

[1353] The server notifies the user to view information based on their profile. Notifications can be sent via email, push notification, or in-app notification. The input is the user's profile information and summary text, and the output is the notification sending status.

[1354] Step 7:

[1355] The user receives the notification through the terminal and views the summary information. The summary text is displayed on the terminal interface. The input is the notification message, and the output is the user's browsing history.

[1356] Step 8:

[1357] Users rate the terms of use and input their rating results. Star ratings and comments are recorded through the rating interface. The input is rating data (star ratings and comments), and the output is a rating record.

[1358] Step 9:

[1359] The server saves the evaluation results sent by users in a database and makes them publicly accessible to other users. This is also an operation that inserts and publishes evaluation data using the database connection library. The input is the evaluation data, and the output is a public evaluation dataset.

[1360] Step 10:

[1361] The server selects reliable services and applications based on the collected reputation data. This is the process of analyzing the reputation data and identifying services with high reputations. The input is a reputation dataset, and the output is a list of reliable services.

[1362] Step 11:

[1363] The server displays the selected reliable services in a dedicated store by inserting them into a display table in the database. The input is a list of reliable services, and the output is a display item in the dedicated store.

[1364] Step 12:

[1365] The server analyzes the ratings and reviews collected from users and extracts common problems and areas for improvement. This analysis is performed using a natural language processing toolkit. The input is the text data of the ratings and reviews, and the output is a list of the extracted problems and areas for improvement.

[1366] Step 13:

[1367] The server uses a generative AI model to generate an improvement proposal report for the company based on the extracted problems and improvement points. The input is a list of problems and improvement points, and the output is an improvement proposal report.

[1368] (Application example 1)

[1369] 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."

[1370] The frequent changes in terms of service for online services such as content distribution services make it difficult for users to understand the content. Users also have difficulty grasping the risks posed by changes in terms of service, leading to concerns about the reliability of the service. Furthermore, there is a lack of means to accurately reflect user feedback and improve the service.

[1371] 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.

[1372] In this invention, the server includes a means for acquiring terms and conditions information, a means for analyzing the acquired terms and conditions information and automatically detecting changes, a means for summarizing the detected changes using a generative AI model and displaying them to the user, a means for accepting user evaluations of the terms and conditions and publishing the evaluation results, and a means for recommending reliable content distribution services. This allows users to intuitively understand changes to the terms and conditions and the risks involved, and select reliable services. The server also includes a means for analyzing the evaluations and reviews collected from users using a generative AI model and generating improvement proposal reports for companies, enabling service providers to continuously improve their services based on user feedback.

[1373] A "server" is a computer system that receives requests over a network and provides data or services.

[1374] The "means for acquiring terms and conditions information" is a function that automatically collects text data of terms of use from the web page of the content distribution service.

[1375] "Means for automatically detecting changes by analyzing terms and conditions information" is a function that compares the old and new terms of use and identifies changes within the terms and conditions.

[1376] "Means for summarizing and displaying to the user using a generative AI model" is a function that uses AI technology to summarize detected changes and displays the summary in an easy-to-read format for the user.

[1377] The "means for accepting user evaluations of terms and conditions and publishing the evaluation results" is a function that allows users to submit evaluations and comments on the terms and conditions and publish the evaluations in a form that can be viewed by other users.

[1378] The "means for recommending highly reliable content distribution services" is a function that selects safe and highly reliable content distribution services based on collected user evaluation data and recommends them to users.

[1379] The "analysis means" is a function that analyzes collected user ratings and reviews and identifies areas for improvement in the service based on the results.

[1380] The "means for generating improvement proposal reports for companies" is a function that automatically creates reports that make specific improvement proposals to service providers based on user feedback.

[1381] This invention is a system that provides an environment in which users can use content distribution services with peace of mind by automatically acquiring, analyzing, summarizing, and evaluating terms of use. The following describes how to specifically implement this system.

[1382] Overall flow

[1383] First, the server periodically retrieves the text data of the terms of use from the web page of the content distribution service via the network. This is done using the Python libraries "requests" and "BeautifulSoup." The retrieved text data is then compared with old data, and changes are automatically detected using the "difflib" library.

[1384] The detected changes are then summarized using a generative AI model, using AI techniques such as GPT-4, and the summary is sent to the user's device, allowing them to intuitively understand the changes.

[1385] Users can use their devices to rate the terms of use and submit their evaluation comments. This evaluation data is stored on the server and can be accessed by other users.

[1386] Furthermore, the server analyzes the evaluation data and selects and recommends reliable content delivery services. To do this, it uses "SQLAlchemy" to manage the database and analyze the evaluation data.

[1387] Finally, the collected user ratings and reviews are analyzed using the generative AI model again to create a report with specific improvement proposals for the company. This report is provided to the service provider to support continuous service improvement.

[1388] Hardware and software used

[1389] Server: The central computer system that retrieves and processes data from the web pages of a content delivery service.

[1390] Device: The device used by the user, such as a smartphone, computer, or tablet.

[1391] software:

[1392] Python: Overall program control.

[1393] BeautifulSoup, requests: Get text data from web pages.

[1394] difflib: Detect changes in text data.

[1395] GPT-4 (OpenAI API): Generates summaries using a generative AI model.

[1396] Firebase Cloud Messaging (FCM): Sends notifications to users.

[1397] Flask, SQLAlchemy: Server-side data management and API construction.

[1398] Specific examples

[1399] 1. The server accesses the web page of a specific content distribution service and obtains the terms of use in text format.

[1400] 2. Analyze the old and new terms of use data and detect changes.

[1401] 3. Use a generative AI model (e.g., GPT-4) to summarize the changes and create a summary.

[1402] 4. The summary is sent to the user's device using FCM.

[1403] 5. Users will receive a notification and review and evaluate the changes to the Terms of Use.

[1404] 6. The server collects evaluation data from users and selects and recommends reliable services.

[1405] 7. Furthermore, the system reanalyzes user ratings and reviews to generate a report with specific improvement suggestions for the service provider.

[1406] Prompt Sentence Examples

[1407] "Please summarize the following changes to the terms and conditions and explain their risks.

[1408] New Terms: [New Terms Text]

[1409] Old Terms: [old terms text]"

[1410] This system allows users to easily understand the terms of use and risks involved, enabling them to use content distribution services with peace of mind. It also enables service providers to continuously improve their services based on user feedback.

[1411] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1412] Step 1:

[1413] The server accesses the web page of a specific content distribution service and retrieves the text data of the terms of use. Specifically, it uses the Python "requests" and "BeautifulSoup" libraries to scrape the terms of use text from this web page. The input of this step is the URL of the web page, and the output is the retrieved text data of the terms of use.

[1414] Step 2:

[1415] The server compares the retrieved text data of the terms of use with the existing data to detect changes. The "difflib" library is used to detect changes. The input is the old and new terms of use text, and the output is differential information indicating the changes. In this data processing process, the old and new texts are compared line by line, and the different parts are extracted.

[1416] Step 3:

[1417] The server summarizes the detected changes using a generative AI model. AI technologies such as GPT-4 are used for generation. Specifically, the changes are sent as input data to the OpenAI API, and the summarized text is received as output. The input is difference information, and the output is the summarized changes.

[1418] Step 4:

[1419] The server notifies the user's device of the summarized changes. This notification uses Firebase Cloud Messaging (FCM). The input is the text of the summarized changes, and the output is a notification that is displayed on the user's device. The server obtains the user's device ID and sends the notification message via FCM.

[1420] Step 5:

[1421] The user uses the terminal to check the changes to the terms of use and rate the terms. The rating can include star ratings and comments. The input is a summary of the changes and the user's rating information, and the output is the rating data. The terminal receives the input from the user through a rating interface.

[1422] Step 6:

[1423] The server stores the evaluation data collected from users in a database and selects reliable content delivery services. "SQLAlchemy" is used for database management. The input is user evaluation data, and the output is a list of reliable services. The server scores the evaluation data and lists the services with the highest scores.

[1424] Step 7:

[1425] The server uses a generative AI model to analyze the ratings and reviews collected from users and generate a report of specific improvement proposals for the company. GPT-4 is again used for the analysis. The input is the user's rating data and reviews, and the output is a report of improvement proposals. The server sends the ratings and reviews to the AI ​​model and compiles the generated improvement proposals for the company.

[1426] Through each step of this process, the system enables users to intuitively understand the content and risks of the terms of use, helps them select reliable services, and allows service providers to continuously improve their services based on user feedback.

[1427] 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.

[1428] This invention is a system that combines an emotion engine that recognizes user emotions, and has the function of automatically acquiring and analyzing terms of use (terms and conditions) presented by online service providers, and displaying a summary of any changes. It also has the function of providing user ratings, reliability assessments based on those ratings, and suggesting improvements to companies. Below, we will explain how to specifically implement this system.

[1429] Overall system overview

[1430] The system has the following main functions:

[1431] 1. A function that automatically acquires and analyzes clause information to detect changes.

[1432] 2. Ability to summarize detected changes and notify the user.

[1433] 3. The ability to recognize user sentiment and customize risk summaries based on that data.

[1434] 4. A function to collect user ratings and publish the results.

[1435] 5. Ability to select reliable services and applications and display them in a dedicated store.

[1436] 6. Ability to use user sentiment data to improve the reliability of ratings.

[1437] 7. A function that makes improvement suggestions to companies based on user ratings and reviews.

[1438] Automatic acquisition and analysis of clause information

[1439] The server periodically accesses a pre-registered web page (terms of use page) and retrieves the text data of the terms of use. The retrieved data is sent to an analysis engine, which compares it with existing data to detect changes. For example, if a social networking service revise its terms of use, the old and new terms are compared and changes regarding the handling of user data are automatically identified.

[1440] Risk summary and emotion-aware notification

[1441] The server uses generative AI to summarize the detected changes and clearly explain the risks. The emotion engine also works to retrieve past emotional data from the user's profile and customize the risk summary notification accordingly. For example, a user who has previously expressed strong concerns about data leaks will receive notifications that specifically highlight changes related to data security.

[1442] Collecting and publishing user ratings

[1443] Using a device, users access the service's terms of use page and use the interface to rate the service. The rating includes a star rating and comments, and is sent to the server. The server stores the rating data in a database so that other users can refer to public ratings.

[1444] Selection and display of reliable services and applications

[1445] The server comprehensively evaluates the collected evaluation data and emotion data to select highly reliable services and applications. These highly reliable services and applications are displayed in a dedicated online store, allowing users to use them with peace of mind.

[1446] Improving the reliability of ratings using user emotions

[1447] The emotion engine collects emotional data from users at the time of rating and uses that data to verify the reliability of the ratings. For example, if a particular rating is extremely high, it may determine that the user is overly excited and may discount that rating.

[1448] Improvement proposals for companies

[1449] The server analyzes user ratings, reviews, and sentiment data to identify common issues and areas for improvement. Specific improvement proposal reports are then provided to the service provider. For example, if multiple users express concerns about a new pricing plan, the server can suggest reconsidering the plan based on that feedback.

[1450] Specific examples

[1451] For example, when a user signs up for a new cloud storage service, the server automatically retrieves and analyzes the service's terms of use to detect any changes. The generative AI summarizes important changes to the terms (e.g., changes to data retention periods), and this information is passed through an emotion engine to notify the user in a format appropriate for them. The user then checks the notification and rates the service. This rating is made public for other users to view, and the service is displayed in a dedicated store as a reliable service. Companies can use the provided improvement proposal report to improve their services.

[1452] This system allows users to easily understand the terms of use, understand the risks, and use the service with peace of mind. It also enables service providers to continuously improve the quality of their services based on user feedback and sentiment data.

[1453] The processing flow will be explained below.

[1454] Step 1:

[1455] The server executes a program that periodically accesses the terms of use page of a pre-registered Web service.

[1456] Step 2:

[1457] The server acquires the latest terms of use text data from the terms of use page and stores it in a database.

[1458] Step 3:

[1459] The server sends the latest obtained terms of use text data to the analysis engine.

[1460] Step 4:

[1461] The analysis engine compares the newly acquired terms of use text data with existing data and automatically detects changes.

[1462] Step 5:

[1463] The analysis engine sends the detected changes to the generation AI.

[1464] Step 6:

[1465] The generative AI evaluates the importance of the changes and generates a summary text.

[1466] Step 7:

[1467] The generation AI compares past user emotional data and reflects it in the risk summary text.

[1468] Step 8:

[1469] The server stores the generated summary text in a risk assessment database.

[1470] Step 9:

[1471] The server notifies a particular user of a risk summary based on the user's profile information.

[1472] Step 10:

[1473] The user checks the risk summary notice using the terminal.

[1474] Step 11:

[1475] The user has access to an interface to review the risk summary and evaluate the terms and conditions.

[1476] Step 12:

[1477] The terminal displays an input form for evaluation, allowing the user to input an evaluation and comments.

[1478] Step 13:

[1479] The user inputs a rating and a comment and submits it.

[1480] Step 14:

[1481] The emotion engine collects real-time emotion data from users who are rating.

[1482] Step 15:

[1483] The server receives the ratings and emotion data sent by the users and stores them in a rating database.

[1484] Step 16:

[1485] The server posts the evaluation in a public evaluation database so that other users can refer to the evaluation results.

[1486] Step 17:

[1487] The server selects reliable services and applications based on the published evaluation data and emotion data.

[1488] Step 18:

[1489] The server displays the selected services and applications in a dedicated store and makes them available to users.

[1490] Step 19:

[1491] Users using the device can access a dedicated store to view and download selected services and applications.

[1492] Step 20:

[1493] The server continuously analyzes user reviews and ratings to identify common problems and areas for improvement.

[1494] Step 21:

[1495] The analysis engine generates a report of specific improvement proposals based on the extracted problems and areas for improvement.

[1496] Step 22:

[1497] The server sends the generated improvement suggestion report to the company and provides feedback for service improvement.

[1498] Example 2

[1499] 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."

[1500] In modern information technology services, terms of use are frequently updated, and their complicated content makes it difficult for users to understand the changes. Furthermore, there is a lack of information provided that reflects users' feelings and individual risk perceptions, making it difficult for users to appropriately manage risks. Furthermore, user evaluations are not widely shared as reliable, and the quality of feedback provided to service providers is low. As a result, there are problems with delays in improving service reliability and implementing improvement suggestions.

[1501] 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 means for acquiring terms of use information, means for automatically detecting changes by analyzing the acquired terms of use information, means for using a generative AI model to summarize the detected changes, means for customizing a risk summary based on user emotion data, means for notifying the user of the customized summary, and means for accepting user terms of use evaluations and publishing the evaluation results. This makes it possible to quickly and accurately notify users of changes to the terms of use and provide information tailored to individual risk perceptions. Furthermore, the collected user evaluations can be used to improve the reliability of services and make specific improvement proposals to service providers.

[1502] "Terms of Use Information" refers to documents that include the terms of use and privacy policy of the services that information technology services provide to users.

[1503] "Means of acquisition" refers to the function by which the server accesses a web page via the Internet and automatically acquires terms of use information.

[1504] "Means of analysis" refers to the function of sending the terms of use information acquired by the server to an internal analysis engine and converting the text into structured data using natural language processing technology.

[1505] "Means for automatically detecting changes" refers to a function in which the server uses an algorithm to compare the old and new terms of use information and identify the differences.

[1506] "Means for using a generative AI model" refers to the function by which the server sends a prompt sentence to the generative AI model and automatically generates a summary.

[1507] "User emotion data" refers to a log of a user's past reactions and emotions, data that is used to create a customized summary.

[1508] "Means for customizing risk summaries based on emotional data" refers to a function that adjusts the summary content according to the user's emotions based on the user's emotional data collected by the server.

[1509] "Means for notifying the user of the customized summary" refers to the function by which the server sends the customized summary to the user's device via email or in-app push notification.

[1510] The "means for accepting a regulation evaluation" refers to a function that provides an interface for users to input evaluations and that the server accepts them.

[1511] "Means for publishing evaluation results" refers to a function that stores the evaluation data collected by the server in a database and makes it publicly available for other users to refer to.

[1512] "Highly reliable information technology services" refer to services that are judged to have high overall reliability based on user ratings and sentiment data.

[1513] "Means for displaying in a dedicated store" refers to a function for displaying highly reliable services selected by the server to users in an online store.

[1514] "Sales Improvement Proposal Report" refers to a report containing specific improvements that is provided to service providers after analyzing ratings, reviews, and sentiment data collected from users.

[1515] This invention builds a system that combines an emotion engine that recognizes user emotions. The system periodically accesses the terms of use page, analyzes the acquired data to detect changes, generates summaries using a generative AI model, and customizes information based on the user's emotion data. Furthermore, it collects user ratings, selects and displays reliable services based on them, and makes improvement suggestions to companies.

[1516] Hardware and software used

[1517] The server contains the following main components:

[1518] Web crawler: Periodically accesses terms of use pages on the Internet and obtains text data. Specific software used is Apache Nutch and Scrapy.

[1519] Analysis engine: Analyzes the acquired text and stores it as structured data. Utilizes natural language processing (NLP) technology using Python or Java. NLTK or spaCy are often used.

[1520] Difference detection algorithm: Compares the old and new data and detects changes. Diff-Match-Patch or a similar library is used for difference detection.

[1521] Generative AI model: To summarize the changes, we use a generative AI model such as OpenAI GPT. We create an input prompt and generate a summary.

[1522] Sentiment engine: Analyzes user sentiment data and customizes summary content. Sentiment analysis uses Google Cloud Natural Language API and Microsoft Azure Text Analytics.

[1523] Notification system: Notify users with a customized summary. Possible notification methods include email and push notifications. Firebase Cloud Messaging (FCM) and AWS SNS (Simple Notification Service) are used.

[1524] The terminal is used as an interface for users to input their evaluations. Specifically, this applies to smartphones, PCs, and tablets.

[1525] Users receive notifications and provide ratings, and the rating data is used to improve reliability and propose improvements to the company.

[1526] Specific examples

[1527] For example, when a user signs up for a new cloud storage service, the following happens:

[1528] 1. The server accesses the terms of use page of the cloud storage service to obtain text data. Using a web crawler, the server periodically accesses this page to obtain the latest terms.

[1529] 2. The server sends the acquired text data to an analysis engine, which uses natural language processing technology to extract paragraphs and sections and store them in a database.

[1530] 3. The server compares the old and new data and identifies changes using a difference detection algorithm. For example, it detects that the "personal information storage period" has been changed from "6 months" to "1 year."

[1531] 4. The server generates a summary by sending the following prompt to the generative AI model: "Please summarize the changes in the new terms of use, such as changes to data retention periods and new policies regarding information leaks. Please make sure the risks are clearly explained."

[1532] 5. The server uses an emotion engine to customize this summary based on the user's emotion data. For example, if a user has previously expressed strong concerns about data leaks, the server generates a summary that specifically highlights changes related to data security.

[1533] 6. The server sends a customized summary to the user's device. Notification methods include email and push notification. "The terms of use for the new cloud storage service have been revised. The data retention period has been changed from six months to one year. Please click here for details."

[1534] 7. Upon receiving the notification, the user enters their rating using their device, leaving a comment or star rating, and the rating data is sent to the server.

[1535] 8. The server stores the collected evaluation data in a database and makes it publicly available for other users to refer to, allowing other users to determine the reliability of information technology services.

[1536] 9. The server selects reliable IT services based on the collected evaluation data and displays them in a dedicated store, allowing users to select services with confidence.

[1537] 10. The server analyzes the ratings and reviews collected from users and generates a report of improvement proposals for sales based on the results. It provides the service provider with a specific report such as, "70% of users are unsure about the new pricing plan, so we recommend that you reconsider the plan."

[1538] As a result, users will be able to quickly understand changes to the terms of use and receive information tailored to their individual risk perceptions, and appropriate feedback will be provided to service providers, which is expected to lead to improved service quality.

[1539] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1540] Step 1: Automatically retrieve terms of use

[1541] The server periodically accesses a pre-registered web page (terms of use page) and obtains text data. A web crawler (for example, Apache Nutch or Scrapy) is used to access the URL and download the terms of use in HTML format. The input data is the URL, and the output data is the obtained text data. This text data is saved in a data store within the server.

[1542] Step 2: Parsing the Terms of Use

[1543] The server sends the acquired text data to an analysis engine. The analysis engine (e.g., NLTK or spaCy) uses natural language processing techniques to divide the text into paragraphs and sections and convert it into structured data. The input data is the terms of use text in HTML format, and the output data is structured paragraph data. The analysis results are stored in a database.

[1544] Step 3: Detecting changes

[1545] The server compares the newly acquired terms of use data with the existing terms of use data. It uses a difference detection algorithm (e.g., Diff-Match-Patch) to detect changes between the two. The input data is the old and new terms of use data, and the output data is a list of changes. This list of changes is also saved in the database.

[1546] Step 4: Generative AI model generates a summary

[1547] The server sends the list of detected changes to a generative AI model, which generates a summary. The input prompt is, "Please summarize the changes in the new terms of use. For example, changes to data retention periods or new policies regarding information leaks. Please make sure that the risks are clearly explained." The generative AI model (e.g., OpenAI GPT) generates a summary based on this prompt and the list of changes. The input data are the prompt and the list of changes, and the output data is a summary of the changes. This summary is also stored in the database.

[1548] Step 5: Customize the risk summary

[1549] The server uses the user's emotional data to customize the generated summary. The emotion engine (e.g., Google Cloud Natural Language API) analyzes the user's past emotional data and customizes the importance and risk of changes. The input data is the user's emotional data and the summary, and the output data is the customized summary. This customized summary is associated with the user profile and saved.

[1550] Step 6: Notify users

[1551] The server sends a customized summary to the user's device. A notification system (for example, Firebase Cloud Messaging or AWS SNS) is used to send the notification to the user's email address or app. The input data is the customized summary and the user's contact information, and the output data is the sending result (success or failure). The notification content often includes a message such as, "The terms of use for the new cloud storage service have been revised. The data retention period has been changed from 6 months to 1 year. Please click here for details."

[1552] Step 7: Collect user ratings

[1553] The user checks the notification using a terminal and rates it through the rating interface. The user accesses the rating interface and inputs a star rating and comments. The input data is the user's rating information, and the output data is data stored in the rating database. The rating content includes comments such as "I feel reassured by the new policy."

[1554] Step 8: Publish evaluation data

[1555] The server stores the collected evaluation data in a database and makes it publicly available for other users to refer to. Highly reliable service information is provided through a public interface. The input data is the data in the evaluation database, and the output data is evaluation information that can be viewed by other users. This allows newly registered users to refer to the evaluations of other users.

[1556] Step 9: Choose a reliable service

[1557] The server comprehensively evaluates the collected evaluation data and sentiment data to select highly reliable services. It uses an algorithm to calculate a reliability score and selects services with a certain score or higher. The input data are the evaluation data and sentiment data, and the output data is a list of selected highly reliable services. This list is displayed in a dedicated store.

[1558] Step 10: Generate improvement proposals for the company

[1559] The server analyzes the ratings and reviews collected from users and generates an improvement proposal report based on the results. An analysis engine is used to extract common problems and areas for improvement, and specific proposals are generated. The input data are rating data and reviews, and the output data is an improvement proposal report. This report is provided to the service provider and used to improve the service. For example, a report may be generated stating, "70% of users are unsure about the new pricing plan, so we recommend that you reconsider the plan."

[1560] (Application example 2)

[1561] 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."

[1562] Modern internet services frequently change their terms of use, making it difficult for users to keep track of all of these changes. Furthermore, because users' feelings and perceptions of risk vary, typical notification methods fail to provide appropriate information to each user. This raises the risk that users may miss important changes to the terms of use and end up suffering disadvantages. Furthermore, there is currently a lack of appropriate collection and analysis of user feedback, and the resulting evaluation of reliability and measures to improve services.

[1563] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring terms and conditions information, means for automatically detecting changes by analyzing the acquired terms and conditions information, means for summarizing the detected changes and displaying them to the user, means for analyzing the user's emotional data and customizing and notifying a risk summary, and means for accepting user evaluations of the terms and conditions and publishing the evaluation results. This allows users to easily understand important changes to the terms and conditions and receive information based on their own emotions and risk perceptions. In addition, collecting and publishing user feedback allows other users to select reliable services, and companies can improve their services based on user evaluations and reviews.

[1564] The "means for obtaining terms and conditions information" is a function that automatically collects terms and conditions data that are periodically posted by service providers on the Internet.

[1565] "Means for automatically detecting changes by analyzing acquired terms and conditions information" is a function that analyzes collected terms and conditions data and identifies changes by comparing it with the previous version.

[1566] "Means for summarizing detected changes and displaying them to the user" is a function that uses a generative AI model to summarize detected changes and display them in an easy-to-understand manner for the user.

[1567] The "means for analyzing user emotional data and customizing and notifying a risk summary" is a function that analyzes a user's past emotional data and generates and notifies an optimal risk summary for each individual user.

[1568] The "means for accepting user evaluations of terms and conditions and publishing the evaluation results" is a function that collects evaluations and feedback on the terms and conditions provided by users and publishes the results so that other users can view them.

[1569] "Means of selecting reliable services and applications based on evaluation results and displaying them in a dedicated store" refers to a function that selects highly rated services and applications based on collected evaluation data and displays them on a dedicated store page.

[1570] "A means for analyzing ratings and reviews collected from users and generating improvement proposal reports for companies based on the analysis results" refers to a function that performs data analysis of ratings and reviews provided by users and generates a report that makes improvement proposals to companies based on the results.

[1571] A "generative AI model" is a form of artificial intelligence that learns from massive amounts of text data and performs text generation, automatic summarization, and question answering for specific tasks.

[1572] A "prompt sentence" is an input sentence that instructs a generative AI model on the task to be performed or the content to be generated.

[1573] This invention is a system for enabling users to properly understand the importance of changes to terms of use, and provides a customized risk summary based on the user's emotional data. This system is mainly composed of a server, a user terminal, and a communication network.

[1574] Overall system description

[1575] The server has the following main functions:

[1576] How to obtain policy information

[1577] A method for automatically detecting changes by analyzing acquired clause information

[1578] A means to summarize the detected changes and display them to the user

[1579] A method to analyze user sentiment data and provide customized risk summaries

[1580] A means of accepting user evaluations of terms and conditions and publishing the evaluation results

[1581] Hardware and software used

[1582] The system uses the following hardware and software:

[1583] Hardware: Servers, smartphones

[1584] Software: Python, BeautifulSoup (HTML parsing), requests (HTTP requests), SentimentEngine (sentiment analysis module), SummaryEngine (summary generation module)

[1585] Data processing and calculation

[1586] The server periodically accesses pre-registered web pages (terms of use pages for various services) and retrieves the text data of the terms of use using the HTML analysis library BeautifulSoup and the HTTP request library requests. The retrieved data is compared with past terms of use data to detect changes. As part of this analysis, a generative AI model is used to generate a summary of the changes.

[1587] The smartphone, which acts as a user terminal, receives and displays the summary notification sent from the server. In addition, the user's emotional data is analyzed using SentimentEngine, and a risk summary is customized based on the user's past emotional data.

[1588] Specific examples

[1589] For example, when a user registers for a new web storage service, the server automatically retrieves and analyzes the service's terms of use to detect any changes. The generative AI summarizes important changes to the terms (e.g., changes to data retention periods), and this information is passed through an emotion engine to notify the user in a format appropriate for them. The user then checks the notification and rates the service. This rating is made public for other users to view, and the service is displayed in a dedicated store as a reliable service. Companies can use the provided improvement proposal report to improve their services.

[1590] Prompt Sentence Examples

[1591] "Analyze the changes in the new Terms of Service, highlight the changes in the Privacy Policy, and generate a summary that is relevant to the user, who has expressed strong concerns about data security in the past."

[1592] By using this specific method, users can easily understand the terms of use and use the service with peace of mind. In addition, service providers can continuously improve the quality of their services based on user feedback and sentiment data.

[1593] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1594] Step 1:

[1595] The server periodically accesses a pre-registered web page (terms of use page) and retrieves the text data of the terms of use using the HTML parsing library BeautifulSoup and the HTTP request library requests. The input is the URL of the terms of use page, and the output is the retrieved text data. Specifically, the requests library sends an HTTP request and receives an HTML response. BeautifulSoup is then used to parse the HTML data and extract the text portion.

[1596] Step 2:

[1597] The server saves the acquired text data and compares it with past data to detect changes. The input is the text data of the old and new terms of use, and the output is a list of changes. Here, a text comparison algorithm is used to identify the changes. Specifically, the strings on each line are compared with past data, and the changed parts are listed.

[1598] Step 3:

[1599] The server inputs the detected changes into a generative AI model to generate a summary. The input is a list of changes and a prompt, and the output is the summarized changes. Specifically, the server inputs a list of changes to the generative AI model using a prompt (e.g., "Please analyze the changes in the new terms of use and generate a summary") to obtain a summary.

[1600] Step 4:

[1601] The server inputs the user's emotional data into the Sentiment Engine for analysis, and then generates a risk summary. The input is the user's emotional data and summarized changes, and the output is a customized risk summary. Specifically, the server uses the Sentiment Engine to analyze the user's past emotional data, and based on the results, inputs prompts that highlight and notify the risks of the summarized changes into the generative AI model, and obtains the results.

[1602] Step 5:

[1603] The terminal receives the customized risk summary sent from the server and notifies the user. The input is the risk summary sent from the server, and the output is the notification displayed to the user. Specifically, the mobile terminal application receives the push notification and displays it on the user screen.

[1604] Step 6:

[1605] The user checks the notified risk summary and enters their evaluation of the terms of use through the application. The input is the user's evaluation data (star ratings and comments), and the output is the evaluation results being sent to the server. Specifically, the user enters the evaluation using the user interface and sends the data to the server.

[1606] Step 7:

[1607] The server stores the evaluation data collected from users in a database and makes it publicly available for other users to view. The input is the user's evaluation data, and the output is the published evaluation results. Specifically, the evaluation data is stored in a database management system and made public through a web interface.

[1608] Step 8:

[1609] The server selects reliable services and applications based on the collected evaluation data and displays them on a dedicated store. The input is a compilation of evaluation data, and the output is a list of reliable services. Specifically, services with high evaluation scores are selected using statistical analysis and displayed on a dedicated store page.

[1610] Step 9:

[1611] The server analyzes the ratings and reviews collected from users and generates an improvement proposal report for the company. The input is the rating and review data, and the output is an improvement proposal report. Specifically, it performs text mining to extract common problems and areas for improvement, and creates improvement proposals based on that.

[1612] 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.

[1613] 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.

[1614] 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.

[1615] 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.

[1616] 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.

[1617] 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.

[1618] 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).

[1619] 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.

[1620] 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."

[1621] 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.

[1622] 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).

[1623] 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.

[1624] 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.

[1625] 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.

[1626] 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.

[1627] 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.

[1628] 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.

[1629] 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.

[1630] 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.

[1631] 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.

[1632] 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.

[1633] The following is further disclosed regarding the above embodiment.

[1634] (Claim 1)

[1635] A means for obtaining clause information;

[1636] A means for automatically detecting changes by analyzing the acquired clause information;

[1637] a means for summarizing the detected changes and displaying them to the user;

[1638] a means for accepting evaluations of the terms and conditions by users and publishing the evaluation results;

[1639] A system including:

[1640] (Claim 2)

[1641] The system according to claim 1, further comprising means for selecting highly reliable services and applications based on the evaluation results and displaying them in the dedicated store.

[1642] (Claim 3)

[1643] 10. The system of claim 1, further comprising means for analyzing the ratings and reviews collected from users and generating an improvement proposal report for the company based on the analysis results.

[1644] "Example 1"

[1645] (Claim 1)

[1646] A means for obtaining clause information;

[1647] A means for automatically detecting changes by analyzing the acquired clause information;

[1648] A means for summarizing the detected changes using a generative AI model and displaying them to a user;

[1649] a means for accepting evaluations of the terms and conditions by users and publishing the evaluation results;

[1650] A system including:

[1651] (Claim 2)

[1652] The system according to claim 1, further comprising means for selecting highly reliable services and applications based on the evaluation results and displaying them in the dedicated store.

[1653] (Claim 3)

[1654] The system of claim 1, further comprising means for analyzing ratings and reviews collected from users and generating an improvement proposal report for the company based on the analysis results using a generative AI model.

[1655] "Application Example 1"

[1656] (Claim 1)

[1657] A means for obtaining clause information;

[1658] A means for automatically detecting changes by analyzing the acquired clause information;

[1659] A means for summarizing the detected changes using a generative AI model and displaying them to the user;

[1660] a means for accepting evaluations of the terms and conditions by users and publishing the evaluation results;

[1661] A means of recommending reliable content distribution services;

[1662] A system including:

[1663] (Claim 2)

[1664] The system according to claim 1, further comprising means for selecting highly reliable services and applications based on the evaluation results and displaying them in the dedicated store.

[1665] (Claim 3)

[1666] 2. The system of claim 1, further comprising means for analyzing the ratings and reviews collected from users using a generative AI model and generating an improvement proposal report for the company based on the analysis results.

[1667] "Example 2: Combining Emotion Engines"

[1668] (Claim 1)

[1669] A means for obtaining terms of use information;

[1670] A means for automatically detecting changes by analyzing the acquired terms of use information;

[1671] a means for using a generative AI model to summarize the detected changes; and

[1672] means for customizing a risk summary based on the user's sentiment data;

[1673] means for communicating the customized summary to the user;

[1674] a means for accepting evaluations of the terms and conditions by users and publishing the evaluation results;

[1675] A system including:

[1676] (Claim 2)

[1677] 2. The system according to claim 1, further comprising means for selecting reliable information technology services based on the evaluation results and displaying them in the dedicated store.

[1678] (Claim 3)

[1679] 2. The system according to claim 1, further comprising means for analyzing the ratings and reviews collected from users and generating an improvement proposal report for sales based on the analysis results.

[1680] "Application example 2 when combining emotion engines"

[1681] (Claim 1)

[1682] A means for obtaining clause information;

[1683] A means for automatically detecting changes by analyzing the acquired clause information;

[1684] a means for summarizing the detected changes and displaying them to the user;

[1685] a means for accepting evaluations of the terms and conditions by users and publishing the evaluation results;

[1686] A means for analyzing user sentiment data and providing a customized risk summary;

[1687] A system including:

[1688] (Claim 2)

[1689] The system according to claim 1, further comprising means for selecting highly reliable services and applications based on the evaluation results and displaying them in the dedicated store.

[1690] (Claim 3)

[1691] 10. The system of claim 1, further comprising means for analyzing the ratings and reviews collected from users and generating an improvement proposal report for the company based on the analysis results. [Explanation of symbols]

[1692] 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 obtaining clause information; A means for automatically detecting changes by analyzing the acquired clause information; a means for summarizing the detected changes and displaying them to the user; a means for accepting evaluations of the terms and conditions by users and publishing the evaluation results; A system including:

2. The system according to claim 1 , further comprising means for selecting highly reliable services and applications based on the evaluation results and displaying them in the dedicated store.

3. The system according to claim 1 , further comprising means for analyzing the ratings and reviews collected from users and generating an improvement proposal report for the company based on the analysis results.

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