System

Abstract

A system is provided.SOLUTION: A system comprising: means for periodically checking for updates to a reference source document; means for analyzing updates to the reference source document; means for generating proposed modifications to a user document based on the analysis; means for notifying a user of the generated proposed modifications; means for receiving an approval of the proposed modifications from the user; and means for automatically updating the user document based on the approval.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[0004] Due to the rapid change in information in today's world, documents managed by users can easily become outdated, potentially leading to incorrect information being used in business operations and decision-making. Furthermore, when source information is updated or deleted, a wide range of documents based on that information must also be revised, increasing the maintenance burden. This problem is particularly pronounced in organizations that handle large volumes of information, which require the ability to track information updates and revise documents accurately and quickly. Furthermore, there is a need for an efficient system that not only detects information updates but also generates specific revision proposals and notifies and prompts users for approval. [Means for solving the problem]

[0005] In order to solve the above problems, the present invention provides the following means. First, a means for periodically checking for updates to a referencing document is provided. This means immediately detects any updates to the referencing document. Next, a means for analyzing the updated content of the referencing document is provided. This means uses natural language processing technology to automatically analyze the differences in the updated content and evaluate their importance. Next, a means for generating a revision proposal for a user document based on the analysis results is provided. This means automatically generates a revision proposal including specific wording and revision steps. Further, a means for notifying a user of the generated revision proposal is provided. This allows the user to confirm the content of the revision proposal. In addition, a means for receiving approval of the revision proposal from the user is provided. This means allows the user to choose whether to approve the revision proposal. Finally, a means for automatically updating the user document based on the approval is provided. This makes it possible to update documents with the latest information while minimizing user effort. A system having such a series of means enables efficient and strategic document maintenance and management.

[0006] A "reference document" is an information source that is the basis for documents managed by a user, and is a document that provides information that exists on the Internet or in an in-house database and needs to be updated.

[0007] "Means for periodically checking for updates" refers to a technology or mechanism for accessing the source document at predetermined intervals and obtaining the latest information.

[0008] The "analysis means" refers to a technology or mechanism used to analyze the updated content of the acquired reference source document and identify the differences and changes.

[0009] The "means for generating revision suggestions" is a technology or mechanism that automatically generates specific revision suggestions for documents managed by a user based on the analyzed update content.

[0010] "Means for notification" refers to a technology or mechanism for notifying the user of the generated revision proposal, and includes email, pop-up notification, chat tools, etc.

[0011] The "means for receiving approval" is a technique or mechanism for receiving an action of approving or rejecting the proposed revision from the user.

[0012] The "automatic updating means" is a technology or mechanism that automatically updates the document managed by the user to reflect the new information after the user approves the proposed revision.

[0013] "Natural language processing technology" is a technology that allows computers to understand, analyze, and generate human language, and is used to analyze update content.

[0014] "User documents" are documents that are managed and used by users and are based on information in the referenced documents. [Brief explanation of the drawings]

[0015] [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 illustrating 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

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] The present invention relates to a system for automatically checking and analyzing updates to referenced documents and maintaining up-to-date information for user documents. The system operates in cooperation with a server, a terminal, and a user.

[0037] System Embodiments

[0038] The system of the present invention includes the following configuration.

[0039] 1. Server

[0040] The server periodically checks for updates to the referencing documents. Specifically, the server periodically retrieves the referencing documents from a pre-registered URL list and analyzes their contents. The analysis is performed using natural language processing (NLP) technology.

[0041] When a referenced document is updated, the server analyzes the update and generates specific suggested modifications to the user document, such as adding, modifying, or deleting text.

[0042] After generating the suggested revision, the server sends a notification to the user, which includes the suggested revision and its background.

[0043] 2. Terminal

[0044] Users receive notifications using a terminal, which may include an email client or an interface that displays pop-up notifications.

[0045] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. The approved proposed revision is transmitted to the server.

[0046] After the user approves, the terminal displays the updated document, allowing the user to confirm that the latest information is reflected.

[0047] 3. Users

[0048] The user receives a notification of the update of the referenced document and checks the contents of the proposed revision.

[0049] If the proposed revision is deemed appropriate, the user takes the action of approving it, which is done through the terminal interface.

[0050] After approval, the user can check the automatically updated document and apply it to their work.

[0051] Program processing explanation

[0052] Check and retrieve updates to referenced documents

[0053] The server periodically accesses the URL of the referenced document to retrieve the latest content, for example, from an internet news site or an internal document management system.

[0054] Update analysis

[0055] The server compares the old and new data and uses natural language processing technology to extract changes. The analysis results are a list of added, modified, and deleted information.

[0056] Generate correction suggestions

[0057] The server then generates suggested revisions based on the analysis results, including specific wording and changes, such as "add new statistical data to the third paragraph of the document."

[0058] Sending notifications

[0059] The server notifies the user of the proposed changes via email or a pop-up on the device, explaining the proposed changes and the reasons for them.

[0060] Approval of the amendment

[0061] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. If the proposed revision is approved, the information is sent to the server.

[0062] Automatic document updates

[0063] The server automatically updates the user document after receiving approval from the user. Updates include adding, modifying, or deleting specific text. Once the update is complete, the updated document is displayed on the terminal.

[0064] Specific examples

[0065] For example, consider the case where a new health guideline is added to a company's guideline document.

[0066] 1. The server detects updates to the guideline document.

[0067] Access the "referred URL" and obtain the new guideline document.

[0068] 2. The server compares the old and new guideline documents and identifies the changes.

[0069] Analyze the addition of new health guidelines and extract the differences.

[0070] 3. The server generates specific fix suggestions

[0071] "Added the following new health guideline to Chapter 2: 'Employees are encouraged to undergo regular health checks.'"

[0072] 4. Notify users

[0073] The user will be notified of the proposed fix via email and also via a pop-up.

[0074] 5. The user approves the proposed revision

[0075] The user checks the notification using the device and clicks the approval button.

[0076] 6. The server updates the document

[0077] The server that receives the approval automatically updates the guideline document and displays the latest document on the terminal.

[0078] This allows users to easily maintain up-to-date information and ensures efficient document maintenance. This system is an effective means of dealing with frequent changes in information and maintaining accurate information.

[0079] The processing flow will be explained below.

[0080] Step 1:

[0081] The server periodically retrieves a list of referencing document URLs, which determines which documents to check for updates.

[0082] Step 2:

[0083] The server accesses each URL in the obtained URL list. The server sends an HTTP request to obtain the latest document data. This may involve using an API or web scraping technology.

[0084] Step 3:

[0085] The server temporarily stores the latest document data, which is then used in subsequent processing.

[0086] Step 4:

[0087] The server compares the latest stored data with the previously acquired data, analyzes the differences, and identifies changes. Specifically, it extracts added, deleted, and modified text.

[0088] Step 5:

[0089] The server uses natural language processing (NLP) techniques to assess the importance of the changes, thereby determining how much impact they will have on the user's documents.

[0090] Step 6:

[0091] The server generates suggested modifications to the user's document based on the identified changes, for example, if new statistical data has been added, it generates instructions to insert that data into the document at the appropriate point.

[0092] Step 7:

[0093] The server notifies the user of the generated revision suggestions, either by sending them to the user's email address or by displaying them as a pop-up notification on the device.

[0094] Step 8:

[0095] The terminal receives the notification and displays it to the user, who then checks the content of the notification and views the details of the proposed revision via the terminal.

[0096] Step 9:

[0097] The user checks the proposed amendment and takes action to approve or reject it. If the user selects approval, he clicks the approve button.

[0098] Step 10:

[0099] The terminal sends the user's approval action to the server, and the server receives the approval.

[0100] Step 11:

[0101] After receiving approval from the user, the server automatically updates the user document with all the changes specified in the proposed amendment.

[0102] Step 12:

[0103] The terminal displays the updated user document, allowing the user to confirm the latest status.

[0104] Through these steps, the DocuGuardian system automatically checks for updates to the source documents and keeps user documents up-to-date, ensuring the reliability and accuracy of information and reducing the maintenance burden on users.

[0105] Example 1

[0106] 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."

[0107] Currently, manually updating user documents every time a referenced document is updated is a time-consuming and laborious task. Furthermore, when documents are updated frequently, it is difficult to keep the information up-to-date, and there is a risk that important information will not be updated. Furthermore, when managing a large number of documents, manual updating is practically impossible. To solve these problems, an efficient and effective system is needed to automatically detect changes in referenced documents and maintain up-to-date user documents.

[0108] 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.

[0109] In this invention, the server includes means for periodically checking for updates to a referencing document, means for acquiring the latest content of the referencing document, means for analyzing the acquired latest content to compare and extract update details, means for generating specific revision proposals for the user document based on the analysis results, means for notifying the user of the generated revision proposals, means for receiving approval of the revision proposals from the user, and means for automatically updating the user document based on the approval, thereby enabling the user document to always maintain the latest information.

[0110] "Source documents" refers to external documents or information sources that the system uses to monitor update status.

[0111] "Means for periodic checking" refers to a mechanism that provides the system with the ability to set a time interval and automatically check for updates to the referenced document.

[0112] "Means of obtaining the latest content" refers to a mechanism that accesses the referrer URL, automatically downloads the latest information, and obtains the data necessary for analysis.

[0113] "Means for analyzing, comparing, and extracting updated content" refers to a mechanism for comparing the old and new data in the source document and identifying changes using natural language processing technology.

[0114] The "means for generating a specific revision proposal" refers to a mechanism for creating specific change instructions to be reflected in the user document based on the updated content.

[0115] "Means for notifying the user" refers to a mechanism for notifying the user of the generated revision proposal by means of email, pop-up notification, or the like.

[0116] The "means for receiving approval from the user" refers to a mechanism for providing an interface that enables the user to check the proposed revision and convey to the system their intention to approve or reject it.

[0117] "Means for automatic updating" refers to a mechanism for automatically reflecting necessary changes to user documents upon receiving approval from the user.

[0118] A "generative AI model" refers to a model that uses artificial intelligence technology to generate and analyze text data.

[0119] A "prompt" is an instruction or question entered into a generative AI model to cause it to generate a specific output.

[0120] "User document" refers to a document that is managed by the system and to which updates are reflected.

[0121] "Natural language processing technology" refers to all technologies that enable computers to understand, analyze, and generate human language.

[0122] The system of the present invention provides a technique for automatically checking and analyzing updates to referenced documents and maintaining the latest information on user documents. The system operates in cooperation with three parties: a server, a terminal, and a user.

[0123] Server Features

[0124] The server has the ability to periodically check for updates to the referenced documents and retrieve the latest content. The referenced documents are stored in information sources on the Internet or in an internal document management system. The server accesses the URL using the "requests" library and retrieves the HTML content. The server then parses this retrieved content using the "BeautifulSoup" library to extract the necessary data.

[0125] The acquired new and old data is compared using the "difflib" library to extract changes. These changes are then analyzed using natural language processing (NLP) technology. Specific tools used include "spaCy" and "NLTK." Based on the analysis results, the server generates suggested modifications. These suggested modifications are generated by inputting prompt sentences into a generative AI model such as "OpenAI GPT-4."

[0126] After generating the proposed changes, the server will send a notification to the user using SendGrid or Amazon SES, including the specific changes and the reasons for them.

[0127] Device Features

[0128] The terminal is a device through which the user receives notifications from the server. The terminal includes an interface that displays a mail client and pop-up notifications. The user can check the notifications through the terminal and accept or reject the proposed amendments. The accepted amendments are sent to the server, which automatically updates the user document based on the information.

[0129] User Roles

[0130] The user receives a notification on their device, checks the proposed revisions, and takes action to approve them. Based on the approved revisions, the user checks the updated document and incorporates them into their work. This allows the user to always have the latest information.

[0131] Specific examples

[0132] Below are some examples of how new health guidelines may be added to a company's guidance document:

[0133] 1. The server detects an update to the guideline document:

[0134] The server accesses "https: / / example.com / guidelines.html" and retrieves the new guideline document.

[0135] Use "requests" and "BeautifulSoup" for this operation.

[0136] 2. The server compares the old and new guideline documents and identifies the changes:

[0137] The server uses "difflib" to identify where new health guidelines should be added.

[0138] Analyze the context using "spaCy".

[0139] 3. The server generates a concrete fix:

[0140] The prompt sentence for the proposed correction is input to the generative AI model, which generates a correction suggestion such as:

[0141] "Added the following new health guideline to Chapter 2: 'Employees are encouraged to undergo regular health checks.'"

[0142] 4. Notify users:

[0143] The server uses SendGrid to send an email to the user and display a pop-up notification on the device.

[0144] 5. User accepts proposed amendment:

[0145] The user checks the proposed revisions using the terminal and clicks the approve button.

[0146] 6. The server updates the document:

[0147] The server updates the guideline document using the Google Docs API or the Microsoft Office 365 API.

[0148] The updated document is displayed on the terminal, allowing the user to view the latest document.

[0149] This effectively keeps user documents up to date and simplifies document maintenance.

[0150] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0151] Step 1: Check for updates to the referenced document

[0152] The server periodically checks a list of pre-registered URLs. The input is a list of each URL, and the server accesses each URL based on that. Specifically, a system scheduler (e.g., a cron job) is used to check for URL updates every day at 3:00 AM. Based on this check, an output is obtained that determines whether or not there have been any updates.

[0153] Step 2: Get the latest content

[0154] The server accesses the referrer URLs to retrieve HTML content. The input is a list of referrer URLs. The server accesses the URLs using the "requests" library and parses the retrieved HTML data using "BeautifulSoup." The output as a result of this processing is the extraction of the latest updated content.

[0155] Step 3: Analyze the updates

[0156] The server saves the latest content it has retrieved and compares it with the previous content. The input is the latest content and the previous content. The server uses the "difflib" library to extract the differences and analyzes them with natural language processing technology (such as "spaCy" or "NLTK"). This gives the output that identifies which parts have been added, modified, or deleted.

[0157] Step 4: Generate correction suggestions

[0158] The server generates specific revision suggestions based on the changes. The input is the analysis result of the update content. The server inputs a prompt sentence into a generative AI model (e.g., "OpenAI GPT-4") and outputs the generated revision suggestions. Specifically, it generates the revision suggestion, "Please add new statistical data to the third paragraph of the document."

[0159] Step 5: Sending notifications

[0160] The server notifies the user of the proposed revisions. The input is the proposed revisions. The notification is sent via email using "SendGrid" or "Amazon SES," and is also displayed as a pop-up notification on the device. The result of this processing is an output that tells the user the specific proposed revisions and the reasons for them.

[0161] Step 6: Review and approve proposed amendments

[0162] The user receives a notification on their device and checks the proposed revision. The input is the notification and the proposed revision received from the server. The user accepts or rejects the proposed revision using the interface on their device. Specific actions include pressing buttons on an email client or browser. The output resulting from this process is that information about the approved proposed revision is sent to the server.

[0163] Step 7: Automatically update user documents

[0164] The server receives approval from the user and automatically updates the user document. The input is the approved revision proposal from the user. The update process is performed using the Google Docs API or Microsoft Office 365 API, and specific text is added, modified, or deleted. The result of this process is an updated user document that is displayed on the terminal.

[0165] (Application example 1)

[0166] 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."

[0167] Updating operation manuals and work procedures for industrial machinery requires manual work, which is inefficient and does not reflect the latest information in a timely manner. Rapid technological innovation and changes in security requirements mean that it is especially important to quickly reflect accurate and up-to-date information. While this improves worker safety and production efficiency, it has been difficult to achieve this effectively using conventional methods.

[0168] 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.

[0169] In this invention, the server includes means for periodically checking for updates to a reference source document, means for analyzing the update content of the reference source document, means for generating a revision proposal for a user document based on the analysis result, means for notifying the user of the generated revision proposal, means for receiving approval for the revision proposal from the user, means for automatically updating the user document based on the approval, means for operating manuals and work procedure manuals of industrial machinery, means for displaying the revision proposal through a user interface and requesting approval from the user, and means for adding new operating procedures and safety guidelines to the manuals if the revision proposal is approved. This automates the updating of operating manuals and work procedure manuals of industrial machinery, reflecting the latest information in a timely manner, thereby improving worker safety and production efficiency.

[0170] "Reference documents" are documents that are the source of updates for industrial machinery operation manuals and work procedures, and include information sources on the Internet and internal documents.

[0171] The "means for analyzing the updated content" refers to a device or software that allows the server to use natural language processing technology to extract the differences between the old and new documents and identify the changes.

[0172] The "means for generating suggested revisions" refers to a device or software that has the function of generating a proposal that specifically indicates the parts of the user document that need to be changed or added, based on the analysis results.

[0173] "Means for notifying the user" refers to a system by which the server sends suggested revisions to the user via email or pop-up notification.

[0174] The "means for receiving approval" is a device or software that allows the server to receive information that allows the user to review the proposed revision and take action to approve or reject it.

[0175] An "automatic updating means" is a device or software that allows the server to automatically modify, add, or delete user documents based on user approval.

[0176] An "industrial machinery operation manual" refers to a document that contains operating procedures and safety guidelines for robots and machinery used in factories.

[0177] A "work procedure manual" is a document that details the operation and maintenance procedures of industrial machinery, and serves as a supplement to the operation manual.

[0178] A "user interface" is a screen or application that allows a user to review and approve proposed revisions, and is an interface that is displayed on a smartphone or computer.

[0179] The present invention relates to an automatic update system for operating manuals and work procedures for industrial machines. This system operates in cooperation with three parties: a server, a terminal, and a user.

[0180] System configuration

[0181] The system of the present invention includes the following components:

[0182] 1. Server

[0183] The server periodically checks for updates to the referenced documents. Specifically, it periodically retrieves the referenced documents from URL lists of Internet information sources and internal documents, and analyzes their contents. The analysis is performed using natural language processing techniques (e.g., NLTK or spaCy).

[0184] When a referenced document is updated, the server analyzes the update and generates specific suggested modifications to the user document, such as adding, modifying, or deleting text.

[0185] After generating the suggested revision, the server sends a notification to the user, which includes the suggested revision and its background.

[0186] 2. Terminal

[0187] Users receive notifications using a terminal, which may include an email client or an interface that displays pop-up notifications.

[0188] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. The approved proposed revision is transmitted to the server.

[0189] After the user approves, the terminal displays the updated document, allowing the user to confirm that the latest information is reflected.

[0190] 3. Users

[0191] The user receives a notification of the update of the referenced document and checks the contents of the proposed revision.

[0192] If the proposed revision is deemed appropriate, the user takes the action of approving it, which is done through the terminal interface.

[0193] After approval, the user can check the automatically updated document and apply it to their work.

[0194] Program processing explanation

[0195] Check and retrieve updates to referenced documents

[0196] The server periodically accesses the URLs of the factory's operational guidelines and work procedures to retrieve the latest content. This process uses Python and the requests library. For example, the BeautifulSoup library is used to parse the HTML content retrieved from the URL and extract the required text.

[0197] Update analysis

[0198] The server compares the old and new data and uses natural language processing technology to extract changes. The analysis results are a list of added, modified, and deleted information. Python and the difflib library are used here. NLTK and spaCy are also used for natural language analysis.

[0199] Generate correction suggestions

[0200] The server generates proposed revisions based on the analysis results, specifically by automatically creating revisions that include specific wording and changes, such as "add a new sensor installation method to the third paragraph of the document." This process may involve the use of generative AI models.

[0201] Sending notifications

[0202] The server notifies the user of the proposed changes via email or a popup on the device, explaining the proposed changes and the reasons for them. This is done using the smtplib library.

[0203] Specific examples

[0204] For example, if a new sensor installation procedure is added, the flow is as follows:

[0205] 1. The server retrieves the new guideline document.

[0206] URL: https: / / example.com / robot_manual.html

[0207] 2. The server compares the old and new documents and identifies the new procedure.

[0208] Additional steps: "How to install a new sensor: Step 1: [Details] ..."

[0209] 3. The server generates a correction proposal

[0210] Proposed fix: "Add new sensor placement instructions to Chapter 3: [Details]"

[0211] 4. Notify the user

[0212] Email subject: "Operation manual update proposal"

[0213] Email body: "New sensor installation instructions have been added to Chapter 3. Please review the contents."

[0214] 5. User Approval

[0215] Check the notification on your smartphone app and tap the "Approve" button.

[0216] 6. The server automatically updates the document

[0217] The operation manual is automatically updated and the latest information is displayed on your smartphone.

[0218] Prompt Sentence Examples

[0219] The prompt to periodically check for updates is:

[0220] "Get the latest content from the source document URL and compare it with the previous version to analyze the changes."

[0221] "If new operating procedures or guidelines are added, generate specific revisions based on them."

[0222] By utilizing this system, robot operations within factories can be quickly updated based on the latest guidelines and procedures, improving efficiency and safety.

[0223] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0224] Step 1:

[0225] The server periodically checks for updates to the referenced document.

[0226] Input: A list of URLs pre-registered on the server

[0227] How it works: The server periodically accesses each URL using the requests library and retrieves the HTML content.

[0228] Output: Latest document content

[0229] Step 2:

[0230] The server compares the old and new data of the document it has acquired and analyzes the updated content.

[0231] Input: Old and new document contents

[0232] How it works: The server uses the difflib library to extract the differences between the old and new documents, and uses natural language processing techniques (NLTK and spaCy) to identify the changes.

[0233] Output: List of changes (additions, modifications, deletions)

[0234] Step 3:

[0235] The server generates suggested modifications based on the analysis results.

[0236] Input: List of changes

[0237] How it works: The server automatically generates specific revision suggestions based on the analysis results. For example, it generates revision suggestions such as "Add a new sensor installation method to this paragraph." Generative AI models may also be used.

[0238] Output: A list of suggested fixes

[0239] Step 4:

[0240] The server notifies the user of the proposed revisions.

[0241] Input: List of proposed amendments

[0242] How it works: The server uses the smtplib library or other notification system to send suggested fixes to the user via email or popup notification.

[0243] Output: A message to inform the user

[0244] Step 5:

[0245] The user receives the notification on their device and checks the proposed changes.

[0246] Input: Notification message sent by the server

[0247] How it works: A notification appears on the user's device, and the user can review the suggested fix.

[0248] Output: User action (approve or reject)

[0249] Step 6:

[0250] The user takes action to approve or reject the proposed amendment.

[0251] Input: Proposed amendment

[0252] How it works: The user uses the device interface to accept or reject the proposed amendment.

[0253] Output: User authorization information

[0254] Step 7:

[0255] The server receives the user's authorization information and automatically updates the user document.

[0256] Input: User authorization information

[0257] Action: The server automatically updates the user documentation with the approved modifications, specifically adding the new sensor placement instructions to the operations manual and updating any other modifications.

[0258] Output: Latest user documents

[0259] Step 8:

[0260] The terminal displays the updated document to the user.

[0261] Input: Latest user document

[0262] What it does: The updated document appears on the user's device, allowing them to see the latest information.

[0263] Output: User-readable, up-to-date operating manual or work instructions

[0264] 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.

[0265] This invention combines emotion recognition technology with a system for automatically checking and analyzing updates to source documents and maintaining up-to-date user documents. The system works in cooperation with four parties: a server, a terminal, a user, and an emotion engine.

[0266] System Embodiments

[0267] The system of the present invention includes the following configuration.

[0268] 1. Server

[0269] The server periodically checks for updates to the referencing documents. Specifically, the server periodically retrieves the referencing documents from a pre-registered URL list and analyzes their contents. The analysis is performed using natural language processing (NLP) technology.

[0270] When a referenced document is updated, the server analyzes the update and generates specific suggested modifications to the user document, such as adding, modifying, or deleting text.

[0271] After generating the suggested revision, the server sends a notification to the user, which includes the suggested revision and its background.

[0272] 2. Emotion Engine

[0273] The emotion engine recognizes the user's emotions in real time. It uses facial expression recognition and voice analysis technologies to identify multiple emotional states, such as joy, sadness, surprise, and anger.

[0274] Adapt the content and format of notifications based on the user's emotional state. For example, if the user is tired, shorten the notification and add an uplifting message.

[0275] 3. Terminal

[0276] Users receive notifications using a terminal, which may include an email client or an interface that displays pop-up notifications.

[0277] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. The approved proposed revision is transmitted to the server.

[0278] After the user approves, the terminal displays the updated document, allowing the user to confirm that the latest information is reflected.

[0279] 4. Users

[0280] The user receives a notification of the update of the referenced document and checks the contents of the proposed revision.

[0281] If the proposed revision is deemed appropriate, the user takes the action of approving it, which is done through the terminal interface.

[0282] After approval, the user can check the automatically updated document and apply it to their work.

[0283] Program processing explanation

[0284] Check and retrieve updates to referenced documents

[0285] The server periodically accesses the list of URLs of the referencing documents to retrieve the latest content, for example, from internet news sites or an internal document management system.

[0286] Update analysis

[0287] The server compares the old and new data and uses natural language processing technology to extract changes. The analysis results are a list of added, modified, and deleted information.

[0288] Generate correction suggestions

[0289] The server generates suggested revisions based on the analysis results, including specific wording and changes, such as "add new statistical data to the third paragraph of the document."

[0290] Sending notifications

[0291] The server notifies the user of the generated revision suggestions, either by sending them to the user's email address or by displaying them as a pop-up notification on the device.

[0292] Emotional engine regulation

[0293] The emotion engine recognizes the user's emotions when receiving a notification and fine-tunes the content of the notification accordingly: for example, if the user is feeling tired, the notification will be brief and an encouraging message will be added.

[0294] Approval of the amendment

[0295] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. If the proposed revision is approved, the information is sent to the server.

[0296] Automatic document updates

[0297] After receiving approval from the user, the server automatically updates the user document with all the changes specified in the proposed revision. Once the update is complete, the terminal displays the latest document.

[0298] Specific examples

[0299] For example, consider the case where a new health guideline is added to a company's guideline document.

[0300] 1. The server detects updates to the guideline document.

[0301] Access the "referred URL" and obtain the new guideline document.

[0302] 2. The server compares the old and new guideline documents and identifies the changes.

[0303] Analyze the addition of new health guidelines and extract the differences.

[0304] 3. The server generates specific fix suggestions

[0305] "Added the following new health guideline to Chapter 2: 'Employees are encouraged to undergo regular health checks.'"

[0306] 4. Emotion engine analyzes user emotions

[0307] Recognize that the user is in a fatigued state when receiving a suggested revision notification.

[0308] 5. Tailor notification content with an emotion engine

[0309] Adapt it to be concise and easy to understand, and add encouragement such as, "Thank you for your hard work. Please check back for new health guidelines."

[0310] 6. Notify users

[0311] The user will be notified of the proposed fix via email and also via a pop-up.

[0312] 7. The user approves the proposed revision

[0313] The user checks the notification using the device and clicks the approval button.

[0314] 8. The server updates the document

[0315] The server that receives the approval automatically updates the guideline document and displays the latest document on the terminal.

[0316] In this way, by combining emotion recognition technology, the DocuGuardian system can provide a more personalized experience for users and make information retention more efficient.

[0317] The processing flow will be explained below.

[0318] Step 1:

[0319] The server periodically retrieves a list of referencing document URLs, which determines which documents to check for updates.

[0320] Step 2:

[0321] The server accesses each URL in the obtained URL list. The server sends an HTTP request to obtain the latest document data. This may involve using an API or web scraping technology.

[0322] Step 3:

[0323] The server temporarily stores the latest document data, which is then used in subsequent processing.

[0324] Step 4:

[0325] The server compares the latest saved data with previously acquired data and analyzes the differences, specifically extracting added, deleted, and modified text.

[0326] Step 5:

[0327] The server uses natural language processing (NLP) techniques to rate the importance of the extracted changes, thereby determining how much impact they will have on the user's document.

[0328] Step 6:

[0329] The server generates suggested modifications to user documents based on the most significant changes, such as adding new statistical data and generating text to insert the data into the appropriate places in the document.

[0330] Step 7:

[0331] The server notifies the user of the generated revision suggestions, which may be sent to the user's email address or displayed as a pop-up notification on the device.

[0332] Step 8:

[0333] The terminal receives the notification and displays it to the user, who then checks the content of the notification and views the details of the proposed revision via the terminal.

[0334] Step 9:

[0335] The emotion engine analyzes the user's emotions in real time, for example, by analyzing the user's facial expressions and voice to identify their emotional state (e.g., joy, sadness, surprise, anger, etc.).

[0336] Step 10:

[0337] The emotion engine fine-tunes notification content based on the user's emotional state: for example, if the user is tired, it will shorten the notification text and add an uplifting message.

[0338] Step 11:

[0339] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. If the proposed revision is approved, the information is sent to the server.

[0340] Step 12:

[0341] After receiving approval from the user, the server automatically updates the user document with all the changes specified in the proposed amendment.

[0342] Step 13:

[0343] The terminal displays the updated user document, allowing the user to confirm the latest status.

[0344] In this way, the DocuGuardian system, combined with emotion recognition technology, can provide users with more personalized notifications and make information retention more efficient.

[0345] Example 2

[0346] 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."

[0347] In conventional document management systems, users had to manually check for updates to the source documents and manually update the user documents accordingly, which was time-consuming. Furthermore, the system did not respond to the user's feelings or situation when receiving the update notification, which placed a heavy burden on the user and made efficient information management difficult.

[0348] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for periodically checking for updates to the referencing document, means for analyzing the update content, means for generating a revision proposal based on the analysis result, means for notifying the user of the generated revision proposal, means for recognizing the user's emotional state in real time and adjusting the notification content, means for receiving approval of the revision proposal from the user, and means for automatically updating the user document based on the approval. This makes it possible to automatically check for and analyze updates to the referencing document, notify the user in an appropriate manner that takes into consideration the user's emotions, and efficiently keep the user document up to date.

[0349] A "reference document" is a document that the system periodically checks for updates and is an information source that users refer to.

[0350] "Updates" refers to information that has been newly added, modified, or deleted from the referenced document.

[0351] "Analysis Method" refers to the technology or algorithm used to identify updates to the source document and extract the differences.

[0352] "Proposed revisions" refers to specific proposed changes to a user document generated based on analytical measures.

[0353] "Notification means" refers to the methods or techniques used to notify the user of generated revision suggestions.

[0354] "Emotional state" refers to the psychological state or emotion that can be read from the user's facial expression, voice, etc.

[0355] "Real-time recognition" refers to technology that instantly analyzes user behavior and reactions and provides results.

[0356] "Approval means" refers to an interface or process that allows a user to take action to approve or reject a proposed amendment.

[0357] "Automatically updating" refers to the system bringing user documents up to date without manual intervention, subject to user approval.

[0358] This invention combines emotion recognition technology with a system for automatically checking and analyzing updates to source documents and maintaining up-to-date user documents. The system works in cooperation with four parties: a server, a terminal, a user, and an emotion engine.

[0359] System configuration

[0360] The system of the present invention includes the following configuration.

[0361] server

[0362] The server is responsible for periodically checking for updates to the referenced documents and analyzing their contents. Based on a pre-registered URL list, the server periodically retrieves documents from online news sites and the company's internal document management system. To do this, the server uses HTTP requests. Natural language processing (NLP) technology is used to analyze the documents, and the Python NLP libraries spaCy and NLTK are used as specific analysis tools.

[0363] Emotion Engine

[0364] The emotion engine uses technology to analyze the user's facial expressions and voice to recognize their emotions in real time. It uses a camera and microphone to capture the user's emotional state. Based on the results, it can adjust the content of notifications, such as sending a briefer notification if the user is fatigued.

[0365] Terminal

[0366] The user receives a notification via their device and checks the proposed revision. The device includes an interface that displays an email client or a pop-up notification, through which the user can accept or reject the proposed revision. The user's action is transmitted to the server via an API.

[0367] User

[0368] The user receives a notification that the referenced document has been updated and checks the proposed revisions. If the proposed revisions are deemed appropriate, the user approves them via their terminal. The automatically updated document can then be reviewed and reflected in the business.

[0369] Hardware and software used

[0370] The specific implementation of the system uses the following hardware and software:

[0371] Server: A physical or virtual server with a high-performance processor (e.g., AWS EC2, Google Cloud Compute Engine)

[0372] Natural language processing libraries: spaCy and NLTK implemented in Python

[0373] Facial expression and voice analysis: Camera module, microphone, image analysis library such as OpenCV, and voice analysis library

[0374] Notification systems: SMTP protocol, Firebase Cloud Messaging (FCM), WebSocket

[0375] Specific examples

[0376] For example, consider a case where a new health guideline is added to a company's guideline document.

[0377] 1. Obtaining the referenced document: The server periodically accesses the "referenced URL" and obtains new guideline documents.

[0378] 2. Analysis of update content: The server compares the old and new guideline documents to identify changes. It analyzes the addition of new health guidelines and extracts the differences.

[0379] 3. Generate amendments: The server generates amendments such as "Add the following new health guideline to Chapter 2: 'Employees are encouraged to undergo regular health checks.'"

[0380] 4. Using the emotion engine: When the user receives the proposed revision notification, the emotion engine recognizes that the user is in a fatigued state.

[0381] 5. Notification content adjustment: The emotion engine will shorten the notification content and add encouraging messages such as, "Good job, please check the new health guidelines."

[0382] 6. Notify the user: The server will send a notification of the proposed fix to the user's email and display a pop-up notification on the device.

[0383] 7. Approval of proposed amendment: The user checks the notification via their device and clicks the approval button.

[0384] 8. Automatic document update: After the server receives approval, it automatically updates the guideline document and displays the latest document on the terminal.

[0385] Prompt Sentence Examples

[0386] Using a concrete example of this system, please explain in detail the process by which users actually review and approve proposed revisions.

[0387] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0388] Step 1: Check for and obtain updates to the referenced documents

[0389] The server periodically retrieves the referenced documents based on a pre-registered URL list. The input is a list of URLs, and the output is the most recent retrieved document. Specifically, it sends an HTTP request to download data from news sites on the Internet or an internal document management system. This process is scheduled, for example, every day at 9:00 AM.

[0390] Step 2: Analyze the updates

[0391] The server analyzes the acquired new and old document data using natural language processing technology. The input is the new document and the old document, and the output is an analysis result that identifies the changes. Specifically, it uses a text comparison algorithm to list added, deleted, and modified information. It uses Python NLP libraries spaCy and NLTK.

[0392] Step 3: Generate correction suggestions

[0393] The server generates specific revision suggestions based on the analysis results. The input is the analyzed changes, and the output is the revision suggestions. Specific actions include creating a revision suggestion with detailed instructions, such as "add new statistics to the third paragraph of the document." The revision suggestions can be formatted in Markdown or HTML.

[0394] Step 4: Sending notifications

[0395] The server notifies the user of the generated proposed corrections. The input is the proposed corrections, and the output is the notification email or popup notification. Specifically, it sends a notification to the user's email address using the SMTP protocol, or displays a popup notification in real time using Firebase Cloud Messaging (FCM) or WebSocket.

[0396] Step 5: Emotional Engine Adjustment

[0397] The emotion engine recognizes the emotional state of the user who received the notification in real time and adjusts the notification content accordingly. The input is the user's facial expression data and voice data, and the output is the adjusted notification content. Specifically, it analyzes facial expression data captured by the camera and voice data acquired by the microphone, and if the user is tired, it simplifies the notification text and adds an encouraging message.

[0398] Step 6: Approval of amendments

[0399] The user uses the device to check the proposed revision and take action to approve or reject it. The input is the notified revision proposal, and the output is the user's action to approve or reject it. Specifically, the user views the revision proposal through the device interface (web browser or mobile app) and clicks the approve or reject button.

[0400] Step 7: Automatically update documents

[0401] The server automatically updates the user document after receiving approval from the user. The input is the user's approved revision proposal, and the output is the updated user document. Specifically, the original document is edited based on the approved revision proposal to reflect the updates. The updated document is committed to a version control system (e.g., Git). After the update is complete, the latest document is displayed on the terminal.

[0402] (Application example 2)

[0403] 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."

[0404] In modern factories, changes to production processes and operation manuals occur frequently, requiring rapid response. However, quickly updating the workplace with updated information is extremely cumbersome and labor-intensive. In particular, issuing notifications without considering employees' emotions and states can lead to reduced efficiency. To improve this situation, there is a need for a system that automatically checks and analyzes updates to referenced documents, maintains the latest information on user documents, and recognizes users' emotions to provide appropriate notifications.

[0405] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0406] In this invention, the server includes means for periodically checking for updates to the referenced document, means for analyzing the updates to the referenced document, means for generating proposed revisions to the user document based on the analysis results, means for notifying the user of the generated proposed revisions, means for receiving approval of the proposed revisions from the user, means for automatically updating the user document based on the approval, means for recognizing the user's emotions, and means for adjusting the notification content based on the emotions. This enables efficient updates of the latest information on production processes and manuals in the factory and personalized notifications according to the user's emotional state.

[0407] A "referenced document" is a document that the system periodically checks and analyzes for updates.

[0408] "Means for analyzing update content" refers to the processes and techniques for extracting changes in the source document and understanding their content.

[0409] A "user document" is a document that is modified based on the updated content of the referencing document.

[0410] A "proposed revision" is a specific change proposed to a user document to reflect an update to a referenced document.

[0411] "Means of notification" refers to the interface or technology used to notify the user of the proposed revisions.

[0412] "Means for receiving approval" refers to the interface or process by which a user reviews the proposed revision and communicates approval or rejection to the system.

[0413] "Automatic updating means" refers to the process or technology for automatically updating user documents with the latest information upon user approval.

[0414] "Means for recognizing emotions" refers to techniques and processes for identifying a user's emotional state and obtaining that information.

[0415] "Means for adjusting notification content" refers to techniques or processes for changing the content or format of notification text depending on the user's emotional state.

[0416] This invention is a system that automatically updates the latest information on production processes and operation manuals in factories, recognizes the user's emotions, and notifies them appropriately. This system works in cooperation with four parties: a server, a terminal, a user, and an emotion engine.

[0417] System configuration

[0418] The system of the present invention includes the following configuration.

[0419] 1. Server

[0420] The server periodically checks for updates to the referencing document. Specifically, the server periodically retrieves the referencing document from a pre-registered URL list and analyzes its contents. The analysis is performed using natural language processing (NLP) technology. When the referencing document is updated, the server analyzes the update content and generates specific suggested modifications to the user document. Suggested modifications include adding, correcting, or deleting text. After generating the suggested modifications, the server sends a notification to the user. This notification includes the content of the suggested modifications and their background. As a specific example, if a factory safety manual has been updated, the server will notify the user that "a new safety procedure has been added to Chapter 2."

[0421] 2. Emotion Engine

[0422] The emotion engine recognizes the user's emotions in real time. It uses facial expression recognition and voice analysis technology to identify multiple emotional states, such as joy, sadness, surprise, and anger. It adjusts the content and format of notifications based on the user's emotional state. For example, if the user is tired, it shortens the notification and adds an encouraging message. The specific software used is "EmotionRecognition."

[0423] 3. Terminal

[0424] A terminal is a device through which a user receives notifications. The terminal includes an interface that displays a mail client and pop-up notifications. The user uses the terminal to check the contents of the proposed amendment and take action to approve or reject it. The approved amendment is transmitted to the server. After the user approves it, the terminal displays the updated document, allowing the user to confirm that the latest information is reflected. For example, the terminal displays a pop-up notification saying, "Please review the new safety procedures."

[0425] 4. Users

[0426] The user receives a notification that the referenced document has been updated and checks the proposed revisions. If the proposed revisions are deemed appropriate, the user takes action to approve them. This is done through the terminal interface. After approval, the user checks the automatically updated document and incorporates it into their work.

[0427] Specific examples

[0428] For example, if a new health guideline is added to a factory safety manual, the server detects the change and generates a correction suggestion. If the emotion engine detects the user's fatigue, it shortens the notification to "Thank you for your hard work. Please check the new health guideline." An example of a prompt is as follows:

[0429] Example prompt sentence:

[0430] Input to the generative AI model:

[0431] "A new procedure has been added to the factory safety manual. Analyze the update and generate specific suggested fixes. Also, use emotion recognition to tailor notification messages. If the user is feeling fatigued, keep the message brief."

[0432] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0433] Step 1:

[0434] The server checks for updates to the referencing document.

[0435] Input: A list of pre-registered URLs.

[0436] The server periodically accesses the list of URLs to retrieve the latest document content, for example by downloading data from a news feed or an internal document management system.

[0437] Output: The latest retrieved document content.

[0438] Step 2:

[0439] The server parses the updates.

[0440] Input: The latest document content obtained in step 1.

[0441] The server uses natural language processing (NLP) technology to compare the old and new data and extract changes.

[0442] Specifically, it uses BeautifulSoup to parse the HTML, and spacy to tokenize the document and identify additions, modifications, and deletions of text.

[0443] Output: A list of changes.

[0444] Step 3:

[0445] The server generates a revision suggestion.

[0446] Input: The list of changes identified in step 2.

[0447] The server automatically generates specific suggested revisions to the user's document based on the changes.

[0448] For example, include specific revisions such as "Add a new procedure to the third paragraph."

[0449] Output: The generated correction suggestions.

[0450] Step 4:

[0451] The server will notify you of the proposed revision.

[0452] Input: The proposed fix generated in step 3.

[0453] The server will send suggested revisions to the user via email or pop-up notification.

[0454] Specifically, it sends emails using the SMTP protocol and provides real-time notifications using WebSocket.

[0455] Output: Notification sent to the user.

[0456] Step 5:

[0457] The emotion engine recognizes the user's emotions.

[0458] Input: Camera video and audio data when the user receives a notification.

[0459] The emotion engine uses facial expression recognition and voice analysis techniques to identify the user's emotional state.

[0460] Specifically, it uses EmotionRecognition software to analyze the user's emotions in real time.

[0461] Output: The perceived emotional state of the user.

[0462] Step 6:

[0463] The server adjusts the notification content based on the emotional state.

[0464] Input: The user's emotional state recognized in step 5, and the notification sent in step 4.

[0465] The server fine-tunes the content and format of the notification message depending on the user's emotions.

[0466] For example, if the user is tired, change the message to something more concise like "Great work, check out the new steps."

[0467] Output: The adjusted notification message.

[0468] Step 7:

[0469] The terminal receives the user's approval.

[0470] Input: The notification message adjusted in step 6.

[0471] The user can review the notification through the device interface and accept or reject the proposed changes.

[0472] Specifically, approval information is sent to the server by clicking a UI button on the terminal.

[0473] Output: User approval or denial information.

[0474] Step 8:

[0475] The server automatically updates the user document.

[0476] Input: User approval information received in step 7 and correction proposal generated in step 3.

[0477] The server automatically updates the user document based on the approved amendments.

[0478] For example, updating a MySQL database to reflect the latest information in a document management system.

[0479] Output: The latest updated user documentation.

[0480] 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.

[0481] 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.

[0482] 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.

[0483] [Second embodiment]

[0484] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0485] 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.

[0486] 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).

[0487] 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.

[0488] 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.

[0489] 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).

[0490] 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.

[0491] 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.

[0492] 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.

[0493] 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.

[0494] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0495] 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."

[0496] The present invention relates to a system for automatically checking and analyzing updates to referenced documents and maintaining up-to-date information for user documents. The system operates in cooperation with a server, a terminal, and a user.

[0497] System Embodiments

[0498] The system of the present invention includes the following configuration.

[0499] 1. Server

[0500] The server periodically checks for updates to the referencing documents. Specifically, the server periodically retrieves the referencing documents from a pre-registered URL list and analyzes their contents. The analysis is performed using natural language processing (NLP) technology.

[0501] When a referenced document is updated, the server analyzes the update and generates specific suggested modifications to the user document, such as adding, modifying, or deleting text.

[0502] After generating the suggested revision, the server sends a notification to the user, which includes the suggested revision and its background.

[0503] 2. Terminal

[0504] Users receive notifications using a terminal, which may include an email client or an interface that displays pop-up notifications.

[0505] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. The approved proposed revision is transmitted to the server.

[0506] After the user approves, the terminal displays the updated document, allowing the user to confirm that the latest information is reflected.

[0507] 3. Users

[0508] The user receives a notification of the update of the referenced document and checks the contents of the proposed revision.

[0509] If the proposed revision is deemed appropriate, the user takes the action of approving it, which is done through the terminal interface.

[0510] After approval, the user can check the automatically updated document and apply it to their work.

[0511] Program processing explanation

[0512] Check and retrieve updates to referenced documents

[0513] The server periodically accesses the URL of the referenced document to retrieve the latest content, for example, from an internet news site or an internal document management system.

[0514] Update analysis

[0515] The server compares the old and new data and uses natural language processing technology to extract changes. The analysis results are a list of added, modified, and deleted information.

[0516] Generate correction suggestions

[0517] The server then generates suggested revisions based on the analysis results, including specific wording and changes, such as "add new statistical data to the third paragraph of the document."

[0518] Sending notifications

[0519] The server notifies the user of the proposed changes via email or a pop-up on the device, explaining the proposed changes and the reasons for them.

[0520] Approval of the amendment

[0521] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. If the proposed revision is approved, the information is sent to the server.

[0522] Automatic document updates

[0523] The server automatically updates the user document after receiving approval from the user. Updates include adding, modifying, or deleting specific text. Once the update is complete, the updated document is displayed on the terminal.

[0524] Specific examples

[0525] For example, consider the case where a new health guideline is added to a company's guideline document.

[0526] 1. The server detects updates to the guideline document.

[0527] Access the "referred URL" and obtain the new guideline document.

[0528] 2. The server compares the old and new guideline documents and identifies the changes.

[0529] Analyze the addition of new health guidelines and extract the differences.

[0530] 3. The server generates specific fix suggestions

[0531] "Added the following new health guideline to Chapter 2: 'Employees are encouraged to undergo regular health checks.'"

[0532] 4. Notify users

[0533] The user will be notified of the proposed fix via email and also via a pop-up.

[0534] 5. The user approves the proposed revision

[0535] The user checks the notification using the device and clicks the approval button.

[0536] 6. The server updates the document

[0537] The server that receives the approval automatically updates the guideline document and displays the latest document on the terminal.

[0538] This allows users to easily maintain up-to-date information and ensures efficient document maintenance. This system is an effective means of dealing with frequent changes in information and maintaining accurate information.

[0539] The processing flow will be explained below.

[0540] Step 1:

[0541] The server periodically retrieves a list of referencing document URLs, which determines which documents to check for updates.

[0542] Step 2:

[0543] The server accesses each URL in the obtained URL list. The server sends an HTTP request to obtain the latest document data. This may involve using an API or web scraping technology.

[0544] Step 3:

[0545] The server temporarily stores the latest document data, which is then used in subsequent processing.

[0546] Step 4:

[0547] The server compares the latest stored data with the previously acquired data, analyzes the differences, and identifies changes. Specifically, it extracts added, deleted, and modified text.

[0548] Step 5:

[0549] The server uses natural language processing (NLP) techniques to assess the importance of the changes, thereby determining how much impact they will have on the user's documents.

[0550] Step 6:

[0551] The server generates suggested modifications to the user's document based on the identified changes, for example, if new statistical data has been added, it generates instructions to insert that data into the document at the appropriate point.

[0552] Step 7:

[0553] The server notifies the user of the generated revision suggestions, either by sending them to the user's email address or by displaying them as a pop-up notification on the device.

[0554] Step 8:

[0555] The terminal receives the notification and displays it to the user, who then checks the content of the notification and views the details of the proposed revision via the terminal.

[0556] Step 9:

[0557] The user checks the proposed amendment and takes action to approve or reject it. If the user selects approval, he clicks the approve button.

[0558] Step 10:

[0559] The terminal sends the user's approval action to the server, and the server receives the approval.

[0560] Step 11:

[0561] After receiving approval from the user, the server automatically updates the user document with all the changes specified in the proposed amendment.

[0562] Step 12:

[0563] The terminal displays the updated user document, allowing the user to confirm the latest status.

[0564] Through these steps, the DocuGuardian system automatically checks for updates to the source documents and keeps user documents up-to-date, ensuring the reliability and accuracy of information and reducing the maintenance burden on users.

[0565] Example 1

[0566] 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."

[0567] Currently, manually updating user documents every time a referenced document is updated is a time-consuming and laborious task. Furthermore, when documents are updated frequently, it is difficult to keep the information up-to-date, and there is a risk that important information will not be updated. Furthermore, when managing a large number of documents, manual updating is practically impossible. To solve these problems, an efficient and effective system is needed to automatically detect changes in referenced documents and maintain up-to-date user documents.

[0568] 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.

[0569] In this invention, the server includes means for periodically checking for updates to a referencing document, means for acquiring the latest content of the referencing document, means for analyzing the acquired latest content to compare and extract update details, means for generating specific revision proposals for the user document based on the analysis results, means for notifying the user of the generated revision proposals, means for receiving approval of the revision proposals from the user, and means for automatically updating the user document based on the approval, thereby enabling the user document to always maintain the latest information.

[0570] "Source documents" refers to external documents or information sources that the system uses to monitor update status.

[0571] "Means for periodic checking" refers to a mechanism that provides the system with the ability to set a time interval and automatically check for updates to the referenced document.

[0572] "Means of obtaining the latest content" refers to a mechanism that accesses the referrer URL, automatically downloads the latest information, and obtains the data necessary for analysis.

[0573] "Means for analyzing, comparing, and extracting updated content" refers to a mechanism for comparing the old and new data in the source document and identifying changes using natural language processing technology.

[0574] The "means for generating a specific revision proposal" refers to a mechanism for creating specific change instructions to be reflected in the user document based on the updated content.

[0575] "Means for notifying the user" refers to a mechanism for notifying the user of the generated revision proposal by means of email, pop-up notification, or the like.

[0576] The "means for receiving approval from the user" refers to a mechanism for providing an interface that enables the user to check the proposed revision and convey to the system their intention to approve or reject it.

[0577] "Means for automatic updating" refers to a mechanism for automatically reflecting necessary changes to user documents upon receiving approval from the user.

[0578] A "generative AI model" refers to a model that uses artificial intelligence technology to generate and analyze text data.

[0579] A "prompt" is an instruction or question entered into a generative AI model to cause it to generate a specific output.

[0580] "User document" refers to a document that is managed by the system and to which updates are reflected.

[0581] "Natural language processing technology" refers to all technologies that enable computers to understand, analyze, and generate human language.

[0582] The system of the present invention provides a technique for automatically checking and analyzing updates to referenced documents and maintaining the latest information on user documents. The system operates in cooperation with three parties: a server, a terminal, and a user.

[0583] Server Features

[0584] The server has the ability to periodically check for updates to the referenced documents and retrieve the latest content. The referenced documents are stored in information sources on the Internet or in an internal document management system. The server accesses the URL using the "requests" library and retrieves the HTML content. The server then parses this retrieved content using the "BeautifulSoup" library to extract the necessary data.

[0585] The acquired new and old data is compared using the "difflib" library to extract changes. These changes are then analyzed using natural language processing (NLP) technology. Specific tools used include "spaCy" and "NLTK." Based on the analysis results, the server generates suggested modifications. These suggested modifications are generated by inputting prompt sentences into a generative AI model such as "OpenAI GPT-4."

[0586] After generating the proposed changes, the server will send a notification to the user using SendGrid or Amazon SES, including the specific changes and the reasons for them.

[0587] Device Features

[0588] The terminal is a device through which the user receives notifications from the server. The terminal includes an interface that displays a mail client and pop-up notifications. The user can check the notifications through the terminal and accept or reject the proposed amendments. The accepted amendments are sent to the server, which automatically updates the user document based on the information.

[0589] User Roles

[0590] The user receives a notification on their device, checks the proposed revisions, and takes action to approve them. Based on the approved revisions, the user checks the updated document and incorporates them into their work. This allows the user to always have the latest information.

[0591] Specific examples

[0592] Below are some examples of how new health guidelines may be added to a company's guidance document:

[0593] 1. The server detects an update to the guideline document:

[0594] The server accesses "https: / / example.com / guidelines.html" and retrieves the new guideline document.

[0595] Use "requests" and "BeautifulSoup" for this operation.

[0596] 2. The server compares the old and new guideline documents and identifies the changes:

[0597] The server uses "difflib" to identify where new health guidelines should be added.

[0598] Analyze the context using "spaCy".

[0599] 3. The server generates a concrete fix:

[0600] The prompt sentence for the proposed correction is input to the generative AI model, which generates a correction suggestion such as:

[0601] "Added the following new health guideline to Chapter 2: 'Employees are encouraged to undergo regular health checks.'"

[0602] 4. Notify users:

[0603] The server uses SendGrid to send an email to the user and display a pop-up notification on the device.

[0604] 5. User accepts proposed amendment:

[0605] The user checks the proposed revisions using the terminal and clicks the approve button.

[0606] 6. The server updates the document:

[0607] The server updates the guideline document using the Google Docs API or the Microsoft Office 365 API.

[0608] The updated document is displayed on the terminal, allowing the user to view the latest document.

[0609] This effectively keeps user documents up to date and simplifies document maintenance.

[0610] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0611] Step 1: Check for updates to the referenced document

[0612] The server periodically checks a list of pre-registered URLs. The input is a list of each URL, and the server accesses each URL based on that. Specifically, a system scheduler (e.g., a cron job) is used to check for URL updates every day at 3:00 AM. Based on this check, an output is obtained that determines whether or not there have been any updates.

[0613] Step 2: Get the latest content

[0614] The server accesses the referrer URLs to retrieve HTML content. The input is a list of referrer URLs. The server accesses the URLs using the "requests" library and parses the retrieved HTML data using "BeautifulSoup." The output as a result of this processing is the extraction of the latest updated content.

[0615] Step 3: Analyze the updates

[0616] The server saves the latest content it has retrieved and compares it with the previous content. The input is the latest content and the previous content. The server uses the "difflib" library to extract the differences and analyzes them with natural language processing technology (such as "spaCy" or "NLTK"). This gives the output that identifies which parts have been added, modified, or deleted.

[0617] Step 4: Generate correction suggestions

[0618] The server generates specific revision suggestions based on the changes. The input is the analysis result of the update content. The server inputs a prompt sentence into a generative AI model (e.g., "OpenAI GPT-4") and outputs the generated revision suggestions. Specifically, it generates the revision suggestion, "Please add new statistical data to the third paragraph of the document."

[0619] Step 5: Sending notifications

[0620] The server notifies the user of the proposed revisions. The input is the proposed revisions. The notification is sent via email using "SendGrid" or "Amazon SES," and is also displayed as a pop-up notification on the device. The result of this processing is an output that tells the user the specific proposed revisions and the reasons for them.

[0621] Step 6: Review and approve proposed amendments

[0622] The user receives a notification on their device and checks the proposed revision. The input is the notification and the proposed revision received from the server. The user accepts or rejects the proposed revision using the interface on their device. Specific actions include pressing buttons on an email client or browser. The output resulting from this process is that information about the approved proposed revision is sent to the server.

[0623] Step 7: Automatically update user documents

[0624] The server receives approval from the user and automatically updates the user document. The input is the approved revision proposal from the user. The update process is performed using the Google Docs API or Microsoft Office 365 API, and specific text is added, modified, or deleted. The result of this process is an updated user document that is displayed on the terminal.

[0625] (Application example 1)

[0626] 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."

[0627] Updating operation manuals and work procedures for industrial machinery requires manual work, which is inefficient and does not reflect the latest information in a timely manner. Rapid technological innovation and changes in security requirements mean that it is especially important to quickly reflect accurate and up-to-date information. While this improves worker safety and production efficiency, it has been difficult to achieve this effectively using conventional methods.

[0628] 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.

[0629] In this invention, the server includes means for periodically checking for updates to a reference source document, means for analyzing the update content of the reference source document, means for generating a revision proposal for a user document based on the analysis result, means for notifying the user of the generated revision proposal, means for receiving approval for the revision proposal from the user, means for automatically updating the user document based on the approval, means for operating manuals and work procedure manuals of industrial machinery, means for displaying the revision proposal through a user interface and requesting approval from the user, and means for adding new operating procedures and safety guidelines to the manuals if the revision proposal is approved. This automates the updating of operating manuals and work procedure manuals of industrial machinery, reflecting the latest information in a timely manner, thereby improving worker safety and production efficiency.

[0630] "Reference documents" are documents that are the source of updates for industrial machinery operation manuals and work procedures, and include information sources on the Internet and internal documents.

[0631] The "means for analyzing the updated content" refers to a device or software that allows the server to use natural language processing technology to extract the differences between the old and new documents and identify the changes.

[0632] The "means for generating suggested revisions" refers to a device or software that has the function of generating a proposal that specifically indicates the parts of the user document that need to be changed or added, based on the analysis results.

[0633] "Means for notifying the user" refers to a system by which the server sends suggested revisions to the user via email or pop-up notification.

[0634] The "means for receiving approval" is a device or software that allows the server to receive information that allows the user to review the proposed revision and take action to approve or reject it.

[0635] An "automatic updating means" is a device or software that allows the server to automatically modify, add, or delete user documents based on user approval.

[0636] An "industrial machinery operation manual" refers to a document that contains operating procedures and safety guidelines for robots and machinery used in factories.

[0637] A "work procedure manual" is a document that details the operation and maintenance procedures of industrial machinery, and serves as a supplement to the operation manual.

[0638] A "user interface" is a screen or application that allows a user to review and approve proposed revisions, and is an interface that is displayed on a smartphone or computer.

[0639] The present invention relates to an automatic update system for operating manuals and work procedures for industrial machines. This system operates in cooperation with three parties: a server, a terminal, and a user.

[0640] System configuration

[0641] The system of the present invention includes the following components:

[0642] 1. Server

[0643] The server periodically checks for updates to the referenced documents. Specifically, it periodically retrieves the referenced documents from URL lists of Internet information sources and internal documents, and analyzes their contents. The analysis is performed using natural language processing techniques (e.g., NLTK or spaCy).

[0644] When a referenced document is updated, the server analyzes the update and generates specific suggested modifications to the user document, such as adding, modifying, or deleting text.

[0645] After generating the suggested revision, the server sends a notification to the user, which includes the suggested revision and its background.

[0646] 2. Terminal

[0647] Users receive notifications using a terminal, which may include an email client or an interface that displays pop-up notifications.

[0648] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. The approved proposed revision is transmitted to the server.

[0649] After the user approves, the terminal displays the updated document, allowing the user to confirm that the latest information is reflected.

[0650] 3. Users

[0651] The user receives a notification of the update of the referenced document and checks the contents of the proposed revision.

[0652] If the proposed revision is deemed appropriate, the user takes the action of approving it, which is done through the terminal interface.

[0653] After approval, the user can check the automatically updated document and apply it to their work.

[0654] Program processing explanation

[0655] Check and retrieve updates to referenced documents

[0656] The server periodically accesses the URLs of the factory's operational guidelines and work procedures to retrieve the latest content. This process uses Python and the requests library. For example, the BeautifulSoup library is used to parse the HTML content retrieved from the URL and extract the required text.

[0657] Update analysis

[0658] The server compares the old and new data and uses natural language processing technology to extract changes. The analysis results are a list of added, modified, and deleted information. Python and the difflib library are used here. NLTK and spaCy are also used for natural language analysis.

[0659] Generate correction suggestions

[0660] The server generates proposed revisions based on the analysis results, specifically by automatically creating revisions that include specific wording and changes, such as "add a new sensor installation method to the third paragraph of the document." This process may involve the use of generative AI models.

[0661] Sending notifications

[0662] The server notifies the user of the proposed changes via email or a popup on the device, explaining the proposed changes and the reasons for them. This is done using the smtplib library.

[0663] Specific examples

[0664] For example, if a new sensor installation procedure is added, the flow is as follows:

[0665] 1. The server retrieves the new guideline document.

[0666] URL: https: / / example.com / robot_manual.html

[0667] 2. The server compares the old and new documents and identifies the new procedure.

[0668] Additional steps: "How to install a new sensor: Step 1: [Details] ..."

[0669] 3. The server generates a correction proposal

[0670] Proposed fix: "Add new sensor placement instructions to Chapter 3: [Details]"

[0671] 4. Notify the user

[0672] Email subject: "Operation manual update proposal"

[0673] Email body: "New sensor installation instructions have been added to Chapter 3. Please review the contents."

[0674] 5. User Approval

[0675] Check the notification on your smartphone app and tap the "Approve" button.

[0676] 6. The server automatically updates the document

[0677] The operation manual is automatically updated and the latest information is displayed on your smartphone.

[0678] Prompt Sentence Examples

[0679] The prompt to periodically check for updates is:

[0680] "Get the latest content from the source document URL and compare it with the previous version to analyze the changes."

[0681] "If new operating procedures or guidelines are added, generate specific revisions based on them."

[0682] By utilizing this system, robot operations within factories can be quickly updated based on the latest guidelines and procedures, improving efficiency and safety.

[0683] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0684] Step 1:

[0685] The server periodically checks for updates to the referenced document.

[0686] Input: A list of URLs pre-registered on the server

[0687] How it works: The server periodically accesses each URL using the requests library and retrieves the HTML content.

[0688] Output: Latest document content

[0689] Step 2:

[0690] The server compares the old and new data of the document it has acquired and analyzes the updated content.

[0691] Input: Old and new document contents

[0692] How it works: The server uses the difflib library to extract the differences between the old and new documents, and uses natural language processing techniques (NLTK and spaCy) to identify the changes.

[0693] Output: List of changes (additions, modifications, deletions)

[0694] Step 3:

[0695] The server generates suggested modifications based on the analysis results.

[0696] Input: List of changes

[0697] How it works: The server automatically generates specific revision suggestions based on the analysis results. For example, it generates revision suggestions such as "Add a new sensor installation method to this paragraph." Generative AI models may also be used.

[0698] Output: A list of suggested fixes

[0699] Step 4:

[0700] The server notifies the user of the proposed revisions.

[0701] Input: List of proposed amendments

[0702] How it works: The server uses the smtplib library or other notification system to send suggested fixes to the user via email or popup notification.

[0703] Output: A message to inform the user

[0704] Step 5:

[0705] The user receives the notification on their device and checks the proposed changes.

[0706] Input: Notification message sent by the server

[0707] How it works: A notification appears on the user's device, and the user can review the suggested fix.

[0708] Output: User action (approve or reject)

[0709] Step 6:

[0710] The user takes action to approve or reject the proposed amendment.

[0711] Input: Proposed amendment

[0712] How it works: The user uses the device interface to accept or reject the proposed amendment.

[0713] Output: User authorization information

[0714] Step 7:

[0715] The server receives the user's authorization information and automatically updates the user document.

[0716] Input: User authorization information

[0717] Action: The server automatically updates the user documentation with the approved modifications, specifically adding the new sensor placement instructions to the operations manual and updating any other modifications.

[0718] Output: Latest user documents

[0719] Step 8:

[0720] The terminal displays the updated document to the user.

[0721] Input: Latest user document

[0722] What it does: The updated document appears on the user's device, allowing them to see the latest information.

[0723] Output: User-readable, up-to-date operating manual or work instructions

[0724] 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.

[0725] This invention combines emotion recognition technology with a system for automatically checking and analyzing updates to source documents and maintaining up-to-date user documents. The system works in cooperation with four parties: a server, a terminal, a user, and an emotion engine.

[0726] System Embodiments

[0727] The system of the present invention includes the following configuration.

[0728] 1. Server

[0729] The server periodically checks for updates to the referencing documents. Specifically, the server periodically retrieves the referencing documents from a pre-registered URL list and analyzes their contents. The analysis is performed using natural language processing (NLP) technology.

[0730] When a referenced document is updated, the server analyzes the update and generates specific suggested modifications to the user document, such as adding, modifying, or deleting text.

[0731] After generating the suggested revision, the server sends a notification to the user, which includes the suggested revision and its background.

[0732] 2. Emotion Engine

[0733] The emotion engine recognizes the user's emotions in real time. It uses facial expression recognition and voice analysis technologies to identify multiple emotional states, such as joy, sadness, surprise, and anger.

[0734] Adapt the content and format of notifications based on the user's emotional state. For example, if the user is tired, shorten the notification and add an uplifting message.

[0735] 3. Terminal

[0736] Users receive notifications using a terminal, which may include an email client or an interface that displays pop-up notifications.

[0737] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. The approved proposed revision is transmitted to the server.

[0738] After the user approves, the terminal displays the updated document, allowing the user to confirm that the latest information is reflected.

[0739] 4. Users

[0740] The user receives a notification of the update of the referenced document and checks the contents of the proposed revision.

[0741] If the proposed revision is deemed appropriate, the user takes the action of approving it, which is done through the terminal interface.

[0742] After approval, the user can check the automatically updated document and apply it to their work.

[0743] Program processing explanation

[0744] Check and retrieve updates to referenced documents

[0745] The server periodically accesses the list of URLs of the referencing documents to retrieve the latest content, for example, from internet news sites or an internal document management system.

[0746] Update analysis

[0747] The server compares the old and new data and uses natural language processing technology to extract changes. The analysis results are a list of added, modified, and deleted information.

[0748] Generate correction suggestions

[0749] The server generates suggested revisions based on the analysis results, including specific wording and changes, such as "add new statistical data to the third paragraph of the document."

[0750] Sending notifications

[0751] The server notifies the user of the generated revision suggestions, either by sending them to the user's email address or by displaying them as a pop-up notification on the device.

[0752] Emotional engine regulation

[0753] The emotion engine recognizes the user's emotions when receiving a notification and fine-tunes the content of the notification accordingly: for example, if the user is feeling tired, the notification will be brief and an encouraging message will be added.

[0754] Approval of the amendment

[0755] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. If the proposed revision is approved, the information is sent to the server.

[0756] Automatic document updates

[0757] After receiving approval from the user, the server automatically updates the user document with all the changes specified in the proposed revision. Once the update is complete, the terminal displays the latest document.

[0758] Specific examples

[0759] For example, consider the case where a new health guideline is added to a company's guideline document.

[0760] 1. The server detects updates to the guideline document.

[0761] Access the "referred URL" and obtain the new guideline document.

[0762] 2. The server compares the old and new guideline documents and identifies the changes.

[0763] Analyze the addition of new health guidelines and extract the differences.

[0764] 3. The server generates specific fix suggestions

[0765] "Added the following new health guideline to Chapter 2: 'Employees are encouraged to undergo regular health checks.'"

[0766] 4. Emotion engine analyzes user emotions

[0767] Recognize that the user is in a fatigued state when receiving a suggested revision notification.

[0768] 5. Tailor notification content with an emotion engine

[0769] Adapt it to be concise and easy to understand, and add encouragement such as, "Thank you for your hard work. Please check back for new health guidelines."

[0770] 6. Notify users

[0771] The user will be notified of the proposed fix via email and also via a pop-up.

[0772] 7. The user approves the proposed revision

[0773] The user checks the notification using the device and clicks the approval button.

[0774] 8. The server updates the document

[0775] The server that receives the approval automatically updates the guideline document and displays the latest document on the terminal.

[0776] In this way, by combining emotion recognition technology, the DocuGuardian system can provide a more personalized experience for users and make information retention more efficient.

[0777] The processing flow will be explained below.

[0778] Step 1:

[0779] The server periodically retrieves a list of referencing document URLs, which determines which documents to check for updates.

[0780] Step 2:

[0781] The server accesses each URL in the obtained URL list. The server sends an HTTP request to obtain the latest document data. This may involve using an API or web scraping technology.

[0782] Step 3:

[0783] The server temporarily stores the latest document data, which is then used in subsequent processing.

[0784] Step 4:

[0785] The server compares the latest saved data with previously acquired data and analyzes the differences, specifically extracting added, deleted, and modified text.

[0786] Step 5:

[0787] The server uses natural language processing (NLP) techniques to rate the importance of the extracted changes, thereby determining how much impact they will have on the user's document.

[0788] Step 6:

[0789] The server generates suggested modifications to user documents based on the most significant changes, such as adding new statistical data and generating text to insert the data into the appropriate places in the document.

[0790] Step 7:

[0791] The server notifies the user of the generated revision suggestions, which may be sent to the user's email address or displayed as a pop-up notification on the device.

[0792] Step 8:

[0793] The terminal receives the notification and displays it to the user, who then checks the content of the notification and views the details of the proposed revision via the terminal.

[0794] Step 9:

[0795] The emotion engine analyzes the user's emotions in real time, for example, by analyzing the user's facial expressions and voice to identify their emotional state (e.g., joy, sadness, surprise, anger, etc.).

[0796] Step 10:

[0797] The emotion engine fine-tunes notification content based on the user's emotional state: for example, if the user is tired, it will shorten the notification text and add an uplifting message.

[0798] Step 11:

[0799] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. If the proposed revision is approved, the information is sent to the server.

[0800] Step 12:

[0801] After receiving approval from the user, the server automatically updates the user document with all the changes specified in the proposed amendment.

[0802] Step 13:

[0803] The terminal displays the updated user document, allowing the user to confirm the latest status.

[0804] In this way, the DocuGuardian system, combined with emotion recognition technology, can provide users with more personalized notifications and make information retention more efficient.

[0805] Example 2

[0806] 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."

[0807] In conventional document management systems, users had to manually check for updates to the source documents and manually update the user documents accordingly, which was time-consuming. Furthermore, the system did not respond to the user's feelings or situation when receiving the update notification, which placed a heavy burden on the user and made efficient information management difficult.

[0808] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for periodically checking for updates to the referencing document, means for analyzing the update content, means for generating a revision proposal based on the analysis result, means for notifying the user of the generated revision proposal, means for recognizing the user's emotional state in real time and adjusting the notification content, means for receiving approval of the revision proposal from the user, and means for automatically updating the user document based on the approval. This makes it possible to automatically check for and analyze updates to the referencing document, notify the user in an appropriate manner that takes into consideration the user's emotions, and efficiently keep the user document up to date.

[0809] A "reference document" is a document that the system periodically checks for updates and is an information source that users refer to.

[0810] "Updates" refers to information that has been newly added, modified, or deleted from the referenced document.

[0811] "Analysis Method" refers to the technology or algorithm used to identify updates to the source document and extract the differences.

[0812] "Proposed revisions" refers to specific proposed changes to a user document generated based on analytical measures.

[0813] "Notification means" refers to the methods or techniques used to notify the user of generated revision suggestions.

[0814] "Emotional state" refers to the psychological state or emotion that can be read from the user's facial expression, voice, etc.

[0815] "Real-time recognition" refers to technology that instantly analyzes user behavior and reactions and provides results.

[0816] "Approval means" refers to an interface or process that allows a user to take action to approve or reject a proposed amendment.

[0817] "Automatically updating" refers to the system bringing user documents up to date without manual intervention, subject to user approval.

[0818] This invention combines emotion recognition technology with a system for automatically checking and analyzing updates to source documents and maintaining up-to-date user documents. The system works in cooperation with four parties: a server, a terminal, a user, and an emotion engine.

[0819] System configuration

[0820] The system of the present invention includes the following configuration.

[0821] server

[0822] The server is responsible for periodically checking for updates to the referenced documents and analyzing their contents. Based on a pre-registered URL list, the server periodically retrieves documents from online news sites and the company's internal document management system. To do this, the server uses HTTP requests. Natural language processing (NLP) technology is used to analyze the documents, and the Python NLP libraries spaCy and NLTK are used as specific analysis tools.

[0823] Emotion Engine

[0824] The emotion engine uses technology to analyze the user's facial expressions and voice to recognize their emotions in real time. It uses a camera and microphone to capture the user's emotional state. Based on the results, it can adjust the content of notifications, such as sending a briefer notification if the user is fatigued.

[0825] Terminal

[0826] The user receives a notification via their device and checks the proposed revision. The device includes an interface that displays an email client or a pop-up notification, through which the user can accept or reject the proposed revision. The user's action is transmitted to the server via an API.

[0827] User

[0828] The user receives a notification that the referenced document has been updated and checks the proposed revisions. If the proposed revisions are deemed appropriate, the user approves them via their terminal. The automatically updated document can then be reviewed and reflected in the business.

[0829] Hardware and software used

[0830] The specific implementation of the system uses the following hardware and software:

[0831] Server: A physical or virtual server with a high-performance processor (e.g., AWS EC2, Google Cloud Compute Engine)

[0832] Natural language processing libraries: spaCy and NLTK implemented in Python

[0833] Facial expression and voice analysis: Camera module, microphone, image analysis library such as OpenCV, and voice analysis library

[0834] Notification systems: SMTP protocol, Firebase Cloud Messaging (FCM), WebSocket

[0835] Specific examples

[0836] For example, consider a case where a new health guideline is added to a company's guideline document.

[0837] 1. Obtaining the referenced document: The server periodically accesses the "referenced URL" and obtains new guideline documents.

[0838] 2. Analysis of update content: The server compares the old and new guideline documents to identify changes. It analyzes the addition of new health guidelines and extracts the differences.

[0839] 3. Generate amendments: The server generates amendments such as "Add the following new health guideline to Chapter 2: 'Employees are encouraged to undergo regular health checks.'"

[0840] 4. Using the emotion engine: When the user receives the proposed revision notification, the emotion engine recognizes that the user is in a fatigued state.

[0841] 5. Notification content adjustment: The emotion engine will shorten the notification content and add encouraging messages such as, "Good job, please check the new health guidelines."

[0842] 6. Notify the user: The server will send a notification of the proposed fix to the user's email and display a pop-up notification on the device.

[0843] 7. Approval of proposed amendment: The user checks the notification via their device and clicks the approval button.

[0844] 8. Automatic document update: After the server receives approval, it automatically updates the guideline document and displays the latest document on the terminal.

[0845] Prompt Sentence Examples

[0846] Using a concrete example of this system, please explain in detail the process by which users actually review and approve proposed revisions.

[0847] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0848] Step 1: Check for and obtain updates to the referenced documents

[0849] The server periodically retrieves the referenced documents based on a pre-registered URL list. The input is a list of URLs, and the output is the most recent retrieved document. Specifically, it sends an HTTP request to download data from news sites on the Internet or an internal document management system. This process is scheduled, for example, every day at 9:00 AM.

[0850] Step 2: Analyze the updates

[0851] The server analyzes the acquired new and old document data using natural language processing technology. The input is the new document and the old document, and the output is an analysis result that identifies the changes. Specifically, it uses a text comparison algorithm to list added, deleted, and modified information. It uses Python NLP libraries spaCy and NLTK.

[0852] Step 3: Generate correction suggestions

[0853] The server generates specific revision suggestions based on the analysis results. The input is the analyzed changes, and the output is the revision suggestions. Specific actions include creating a revision suggestion with detailed instructions, such as "add new statistics to the third paragraph of the document." The revision suggestions can be formatted in Markdown or HTML.

[0854] Step 4: Sending notifications

[0855] The server notifies the user of the generated proposed corrections. The input is the proposed corrections, and the output is the notification email or popup notification. Specifically, it sends a notification to the user's email address using the SMTP protocol, or displays a popup notification in real time using Firebase Cloud Messaging (FCM) or WebSocket.

[0856] Step 5: Emotional Engine Adjustment

[0857] The emotion engine recognizes the emotional state of the user who received the notification in real time and adjusts the notification content accordingly. The input is the user's facial expression data and voice data, and the output is the adjusted notification content. Specifically, it analyzes facial expression data captured by the camera and voice data acquired by the microphone, and if the user is tired, it simplifies the notification text and adds an encouraging message.

[0858] Step 6: Approval of amendments

[0859] The user uses the device to check the proposed revision and take action to approve or reject it. The input is the notified revision proposal, and the output is the user's action to approve or reject it. Specifically, the user views the revision proposal through the device interface (web browser or mobile app) and clicks the approve or reject button.

[0860] Step 7: Automatically update documents

[0861] The server automatically updates the user document after receiving approval from the user. The input is the user's approved revision proposal, and the output is the updated user document. Specifically, the original document is edited based on the approved revision proposal to reflect the updates. The updated document is committed to a version control system (e.g., Git). After the update is complete, the latest document is displayed on the terminal.

[0862] (Application example 2)

[0863] 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."

[0864] In modern factories, changes to production processes and operation manuals occur frequently, requiring rapid response. However, quickly updating the workplace with updated information is extremely cumbersome and labor-intensive. In particular, issuing notifications without considering employees' emotions and states can lead to reduced efficiency. To improve this situation, there is a need for a system that automatically checks and analyzes updates to referenced documents, maintains the latest information on user documents, and recognizes users' emotions to provide appropriate notifications.

[0865] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0866] In this invention, the server includes means for periodically checking for updates to the referenced document, means for analyzing the updates to the referenced document, means for generating proposed revisions to the user document based on the analysis results, means for notifying the user of the generated proposed revisions, means for receiving approval of the proposed revisions from the user, means for automatically updating the user document based on the approval, means for recognizing the user's emotions, and means for adjusting the notification content based on the emotions. This enables efficient updates of the latest information on production processes and manuals in the factory and personalized notifications according to the user's emotional state.

[0867] A "referenced document" is a document that the system periodically checks and analyzes for updates.

[0868] "Means for analyzing update content" refers to the processes and techniques for extracting changes in the source document and understanding their content.

[0869] A "user document" is a document that is modified based on the updated content of the referencing document.

[0870] A "proposed revision" is a specific change proposed to a user document to reflect an update to a referenced document.

[0871] "Means of notification" refers to the interface or technology used to notify the user of the proposed revisions.

[0872] "Means for receiving approval" refers to the interface or process by which a user reviews the proposed revision and communicates approval or rejection to the system.

[0873] "Automatic updating means" refers to the process or technology for automatically updating user documents with the latest information upon user approval.

[0874] "Means for recognizing emotions" refers to techniques and processes for identifying a user's emotional state and obtaining that information.

[0875] "Means for adjusting notification content" refers to techniques or processes for changing the content or format of notification text depending on the user's emotional state.

[0876] This invention is a system that automatically updates the latest information on production processes and operation manuals in factories, recognizes the user's emotions, and notifies them appropriately. This system works in cooperation with four parties: a server, a terminal, a user, and an emotion engine.

[0877] System configuration

[0878] The system of the present invention includes the following configuration.

[0879] 1. Server

[0880] The server periodically checks for updates to the referencing document. Specifically, the server periodically retrieves the referencing document from a pre-registered URL list and analyzes its contents. The analysis is performed using natural language processing (NLP) technology. When the referencing document is updated, the server analyzes the update content and generates specific suggested modifications to the user document. Suggested modifications include adding, correcting, or deleting text. After generating the suggested modifications, the server sends a notification to the user. This notification includes the content of the suggested modifications and their background. As a specific example, if a factory safety manual has been updated, the server will notify the user that "a new safety procedure has been added to Chapter 2."

[0881] 2. Emotion Engine

[0882] The emotion engine recognizes the user's emotions in real time. It uses facial expression recognition and voice analysis technology to identify multiple emotional states, such as joy, sadness, surprise, and anger. It adjusts the content and format of notifications based on the user's emotional state. For example, if the user is tired, it shortens the notification and adds an encouraging message. The specific software used is "EmotionRecognition."

[0883] 3. Terminal

[0884] A terminal is a device through which a user receives notifications. The terminal includes an interface that displays a mail client and pop-up notifications. The user uses the terminal to check the contents of the proposed amendment and take action to approve or reject it. The approved amendment is transmitted to the server. After the user approves it, the terminal displays the updated document, allowing the user to confirm that the latest information is reflected. For example, the terminal displays a pop-up notification saying, "Please review the new safety procedures."

[0885] 4. Users

[0886] The user receives a notification that the referenced document has been updated and checks the proposed revisions. If the proposed revisions are deemed appropriate, the user takes action to approve them. This is done through the terminal interface. After approval, the user checks the automatically updated document and incorporates it into their work.

[0887] Specific examples

[0888] For example, if a new health guideline is added to a factory safety manual, the server detects the change and generates a correction suggestion. If the emotion engine detects the user's fatigue, it shortens the notification to "Thank you for your hard work. Please check the new health guideline." An example of a prompt is as follows:

[0889] Example prompt sentence:

[0890] Input to the generative AI model:

[0891] "A new procedure has been added to the factory safety manual. Analyze the update and generate specific suggested fixes. Also, use emotion recognition to tailor notification messages. If the user is feeling fatigued, keep the message brief."

[0892] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0893] Step 1:

[0894] The server checks for updates to the referencing document.

[0895] Input: A list of pre-registered URLs.

[0896] The server periodically accesses the list of URLs to retrieve the latest document content, for example by downloading data from a news feed or an internal document management system.

[0897] Output: The latest retrieved document content.

[0898] Step 2:

[0899] The server parses the updates.

[0900] Input: The latest document content obtained in step 1.

[0901] The server uses natural language processing (NLP) technology to compare the old and new data and extract changes.

[0902] Specifically, it uses BeautifulSoup to parse the HTML, and spacy to tokenize the document and identify additions, modifications, and deletions of text.

[0903] Output: A list of changes.

[0904] Step 3:

[0905] The server generates a revision suggestion.

[0906] Input: The list of changes identified in step 2.

[0907] The server automatically generates specific suggested revisions to the user's document based on the changes.

[0908] For example, include specific revisions such as "Add a new procedure to the third paragraph."

[0909] Output: The generated correction suggestions.

[0910] Step 4:

[0911] The server will notify you of the proposed revision.

[0912] Input: The proposed fix generated in step 3.

[0913] The server will send suggested revisions to the user via email or pop-up notification.

[0914] Specifically, it sends emails using the SMTP protocol and provides real-time notifications using WebSocket.

[0915] Output: Notification sent to the user.

[0916] Step 5:

[0917] The emotion engine recognizes the user's emotions.

[0918] Input: Camera video and audio data when the user receives a notification.

[0919] The emotion engine uses facial expression recognition and voice analysis techniques to identify the user's emotional state.

[0920] Specifically, it uses EmotionRecognition software to analyze the user's emotions in real time.

[0921] Output: The perceived emotional state of the user.

[0922] Step 6:

[0923] The server adjusts the notification content based on the emotional state.

[0924] Input: The user's emotional state recognized in step 5, and the notification sent in step 4.

[0925] The server fine-tunes the content and format of the notification message depending on the user's emotions.

[0926] For example, if the user is tired, change the message to something more concise like "Great work, check out the new steps."

[0927] Output: The adjusted notification message.

[0928] Step 7:

[0929] The terminal receives the user's approval.

[0930] Input: The notification message adjusted in step 6.

[0931] The user can review the notification through the device interface and accept or reject the proposed changes.

[0932] Specifically, approval information is sent to the server by clicking a UI button on the terminal.

[0933] Output: User approval or denial information.

[0934] Step 8:

[0935] The server automatically updates the user document.

[0936] Input: User approval information received in step 7 and correction proposal generated in step 3.

[0937] The server automatically updates the user document based on the approved amendments.

[0938] For example, updating a MySQL database to reflect the latest information in a document management system.

[0939] Output: The latest updated user documentation.

[0940] 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.

[0941] 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.

[0942] 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.

[0943] [Third embodiment]

[0944] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0945] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0946] 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).

[0947] 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.

[0948] 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.

[0949] 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).

[0950] 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.

[0951] 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.

[0952] 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.

[0953] 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.

[0954] 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.

[0955] 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."

[0956] The present invention relates to a system for automatically checking and analyzing updates to referenced documents and maintaining up-to-date information for user documents. The system operates in cooperation with a server, a terminal, and a user.

[0957] System Embodiments

[0958] The system of the present invention includes the following configuration.

[0959] 1. Server

[0960] The server periodically checks for updates to the referencing documents. Specifically, the server periodically retrieves the referencing documents from a pre-registered URL list and analyzes their contents. The analysis is performed using natural language processing (NLP) technology.

[0961] When a referenced document is updated, the server analyzes the update and generates specific suggested modifications to the user document, such as adding, modifying, or deleting text.

[0962] After generating the suggested revision, the server sends a notification to the user, which includes the suggested revision and its background.

[0963] 2. Terminal

[0964] Users receive notifications using a terminal, which may include an email client or an interface that displays pop-up notifications.

[0965] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. The approved proposed revision is transmitted to the server.

[0966] After the user approves, the terminal displays the updated document, allowing the user to confirm that the latest information is reflected.

[0967] 3. Users

[0968] The user receives a notification of the update of the referenced document and checks the contents of the proposed revision.

[0969] If the proposed revision is deemed appropriate, the user takes the action of approving it, which is done through the terminal interface.

[0970] After approval, the user can check the automatically updated document and apply it to their work.

[0971] Program processing explanation

[0972] Check and retrieve updates to referenced documents

[0973] The server periodically accesses the URL of the referenced document to retrieve the latest content, for example, from an internet news site or an internal document management system.

[0974] Update analysis

[0975] The server compares the old and new data and uses natural language processing technology to extract changes. The analysis results are a list of added, modified, and deleted information.

[0976] Generate correction suggestions

[0977] The server then generates suggested revisions based on the analysis results, including specific wording and changes, such as "add new statistical data to the third paragraph of the document."

[0978] Sending notifications

[0979] The server notifies the user of the proposed changes via email or a pop-up on the device, explaining the proposed changes and the reasons for them.

[0980] Approval of the amendment

[0981] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. If the proposed revision is approved, the information is sent to the server.

[0982] Automatic document updates

[0983] The server automatically updates the user document after receiving approval from the user. Updates include adding, modifying, or deleting specific text. Once the update is complete, the updated document is displayed on the terminal.

[0984] Specific examples

[0985] For example, consider the case where a new health guideline is added to a company's guideline document.

[0986] 1. The server detects updates to the guideline document.

[0987] Access the "referred URL" and obtain the new guideline document.

[0988] 2. The server compares the old and new guideline documents and identifies the changes.

[0989] Analyze the addition of new health guidelines and extract the differences.

[0990] 3. The server generates specific fix suggestions

[0991] "Added the following new health guideline to Chapter 2: 'Employees are encouraged to undergo regular health checks.'"

[0992] 4. Notify users

[0993] The user will be notified of the proposed fix via email and also via a pop-up.

[0994] 5. The user approves the proposed revision

[0995] The user checks the notification using the device and clicks the approval button.

[0996] 6. The server updates the document

[0997] The server that receives the approval automatically updates the guideline document and displays the latest document on the terminal.

[0998] This allows users to easily maintain up-to-date information and ensures efficient document maintenance. This system is an effective means of dealing with frequent changes in information and maintaining accurate information.

[0999] The processing flow will be explained below.

[1000] Step 1:

[1001] The server periodically retrieves a list of referencing document URLs, which determines which documents to check for updates.

[1002] Step 2:

[1003] The server accesses each URL in the obtained URL list. The server sends an HTTP request to obtain the latest document data. This may involve using an API or web scraping technology.

[1004] Step 3:

[1005] The server temporarily stores the latest document data, which is then used in subsequent processing.

[1006] Step 4:

[1007] The server compares the latest stored data with the previously acquired data, analyzes the differences, and identifies changes. Specifically, it extracts added, deleted, and modified text.

[1008] Step 5:

[1009] The server uses natural language processing (NLP) techniques to assess the importance of the changes, thereby determining how much impact they will have on the user's documents.

[1010] Step 6:

[1011] The server generates suggested modifications to the user's document based on the identified changes, for example, if new statistical data has been added, it generates instructions to insert that data into the document at the appropriate point.

[1012] Step 7:

[1013] The server notifies the user of the generated revision suggestions, either by sending them to the user's email address or by displaying them as a pop-up notification on the device.

[1014] Step 8:

[1015] The terminal receives the notification and displays it to the user, who then checks the content of the notification and views the details of the proposed revision via the terminal.

[1016] Step 9:

[1017] The user checks the proposed amendment and takes action to approve or reject it. If the user selects approval, he clicks the approve button.

[1018] Step 10:

[1019] The terminal sends the user's approval action to the server, and the server receives the approval.

[1020] Step 11:

[1021] After receiving approval from the user, the server automatically updates the user document with all the changes specified in the proposed amendment.

[1022] Step 12:

[1023] The terminal displays the updated user document, allowing the user to confirm the latest status.

[1024] Through these steps, the DocuGuardian system automatically checks for updates to the source documents and keeps user documents up-to-date, ensuring the reliability and accuracy of information and reducing the maintenance burden on users.

[1025] Example 1

[1026] 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."

[1027] Currently, manually updating user documents every time a referenced document is updated is a time-consuming and laborious task. Furthermore, when documents are updated frequently, it is difficult to keep the information up-to-date, and there is a risk that important information will not be updated. Furthermore, when managing a large number of documents, manual updating is practically impossible. To solve these problems, an efficient and effective system is needed to automatically detect changes in referenced documents and maintain up-to-date user documents.

[1028] 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.

[1029] In this invention, the server includes means for periodically checking for updates to a referencing document, means for acquiring the latest content of the referencing document, means for analyzing the acquired latest content to compare and extract update details, means for generating specific revision proposals for the user document based on the analysis results, means for notifying the user of the generated revision proposals, means for receiving approval of the revision proposals from the user, and means for automatically updating the user document based on the approval, thereby enabling the user document to always maintain the latest information.

[1030] "Source documents" refers to external documents or information sources that the system uses to monitor update status.

[1031] "Means for periodic checking" refers to a mechanism that provides the system with the ability to set a time interval and automatically check for updates to the referenced document.

[1032] "Means of obtaining the latest content" refers to a mechanism that accesses the referrer URL, automatically downloads the latest information, and obtains the data necessary for analysis.

[1033] "Means for analyzing, comparing, and extracting updated content" refers to a mechanism for comparing the old and new data in the source document and identifying changes using natural language processing technology.

[1034] The "means for generating a specific revision proposal" refers to a mechanism for creating specific change instructions to be reflected in the user document based on the updated content.

[1035] "Means for notifying the user" refers to a mechanism for notifying the user of the generated revision proposal by means of email, pop-up notification, or the like.

[1036] The "means for receiving approval from the user" refers to a mechanism for providing an interface that enables the user to check the proposed revision and convey to the system their intention to approve or reject it.

[1037] "Means for automatic updating" refers to a mechanism for automatically reflecting necessary changes to user documents upon receiving approval from the user.

[1038] A "generative AI model" refers to a model that uses artificial intelligence technology to generate and analyze text data.

[1039] A "prompt" is an instruction or question entered into a generative AI model to cause it to generate a specific output.

[1040] "User document" refers to a document that is managed by the system and to which updates are reflected.

[1041] "Natural language processing technology" refers to all technologies that enable computers to understand, analyze, and generate human language.

[1042] The system of the present invention provides a technique for automatically checking and analyzing updates to referenced documents and maintaining the latest information on user documents. The system operates in cooperation with three parties: a server, a terminal, and a user.

[1043] Server Features

[1044] The server has the ability to periodically check for updates to the referenced documents and retrieve the latest content. The referenced documents are stored in information sources on the Internet or in an internal document management system. The server accesses the URL using the "requests" library and retrieves the HTML content. The server then parses this retrieved content using the "BeautifulSoup" library to extract the necessary data.

[1045] The acquired new and old data is compared using the "difflib" library to extract changes. These changes are then analyzed using natural language processing (NLP) technology. Specific tools used include "spaCy" and "NLTK." Based on the analysis results, the server generates suggested modifications. These suggested modifications are generated by inputting prompt sentences into a generative AI model such as "OpenAI GPT-4."

[1046] After generating the proposed changes, the server will send a notification to the user using SendGrid or Amazon SES, including the specific changes and the reasons for them.

[1047] Device Features

[1048] The terminal is a device through which the user receives notifications from the server. The terminal includes an interface that displays a mail client and pop-up notifications. The user can check the notifications through the terminal and accept or reject the proposed amendments. The accepted amendments are sent to the server, which automatically updates the user document based on the information.

[1049] User Roles

[1050] The user receives a notification on their device, checks the proposed revisions, and takes action to approve them. Based on the approved revisions, the user checks the updated document and incorporates them into their work. This allows the user to always have the latest information.

[1051] Specific examples

[1052] Below are some examples of how new health guidelines may be added to a company's guidance document:

[1053] 1. The server detects an update to the guideline document:

[1054] The server accesses "https: / / example.com / guidelines.html" and retrieves the new guideline document.

[1055] Use "requests" and "BeautifulSoup" for this operation.

[1056] 2. The server compares the old and new guideline documents and identifies the changes:

[1057] The server uses "difflib" to identify where new health guidelines should be added.

[1058] Analyze the context using "spaCy".

[1059] 3. The server generates a concrete fix:

[1060] The prompt sentence for the proposed correction is input to the generative AI model, which generates a correction suggestion such as:

[1061] "Added the following new health guideline to Chapter 2: 'Employees are encouraged to undergo regular health checks.'"

[1062] 4. Notify users:

[1063] The server uses SendGrid to send an email to the user and display a pop-up notification on the device.

[1064] 5. User accepts proposed amendment:

[1065] The user checks the proposed revisions using the terminal and clicks the approve button.

[1066] 6. The server updates the document:

[1067] The server updates the guideline document using the Google Docs API or the Microsoft Office 365 API.

[1068] The updated document is displayed on the terminal, allowing the user to view the latest document.

[1069] This effectively keeps user documents up to date and simplifies document maintenance.

[1070] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1071] Step 1: Check for updates to the referenced document

[1072] The server periodically checks a list of pre-registered URLs. The input is a list of each URL, and the server accesses each URL based on that. Specifically, a system scheduler (e.g., a cron job) is used to check for URL updates every day at 3:00 AM. Based on this check, an output is obtained that determines whether or not there have been any updates.

[1073] Step 2: Get the latest content

[1074] The server accesses the referrer URLs to retrieve HTML content. The input is a list of referrer URLs. The server accesses the URLs using the "requests" library and parses the retrieved HTML data using "BeautifulSoup." The output as a result of this processing is the extraction of the latest updated content.

[1075] Step 3: Analyze the updates

[1076] The server saves the latest content it has retrieved and compares it with the previous content. The input is the latest content and the previous content. The server uses the "difflib" library to extract the differences and analyzes them with natural language processing technology (such as "spaCy" or "NLTK"). This gives the output that identifies which parts have been added, modified, or deleted.

[1077] Step 4: Generate correction suggestions

[1078] The server generates specific revision suggestions based on the changes. The input is the analysis result of the update content. The server inputs a prompt sentence into a generative AI model (e.g., "OpenAI GPT-4") and outputs the generated revision suggestions. Specifically, it generates the revision suggestion, "Please add new statistical data to the third paragraph of the document."

[1079] Step 5: Sending notifications

[1080] The server notifies the user of the proposed revisions. The input is the proposed revisions. The notification is sent via email using "SendGrid" or "Amazon SES," and is also displayed as a pop-up notification on the device. The result of this processing is an output that tells the user the specific proposed revisions and the reasons for them.

[1081] Step 6: Review and approve proposed amendments

[1082] The user receives a notification on their device and checks the proposed revision. The input is the notification and the proposed revision received from the server. The user accepts or rejects the proposed revision using the interface on their device. Specific actions include pressing buttons on an email client or browser. The output resulting from this process is that information about the approved proposed revision is sent to the server.

[1083] Step 7: Automatically update user documents

[1084] The server receives approval from the user and automatically updates the user document. The input is the approved revision proposal from the user. The update process is performed using the Google Docs API or Microsoft Office 365 API, and specific text is added, modified, or deleted. The result of this process is an updated user document that is displayed on the terminal.

[1085] (Application example 1)

[1086] 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."

[1087] Updating operation manuals and work procedures for industrial machinery requires manual work, which is inefficient and does not reflect the latest information in a timely manner. Rapid technological innovation and changes in security requirements mean that it is especially important to quickly reflect accurate and up-to-date information. While this improves worker safety and production efficiency, it has been difficult to achieve this effectively using conventional methods.

[1088] 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.

[1089] In this invention, the server includes means for periodically checking for updates to a reference source document, means for analyzing the update content of the reference source document, means for generating a revision proposal for a user document based on the analysis result, means for notifying the user of the generated revision proposal, means for receiving approval for the revision proposal from the user, means for automatically updating the user document based on the approval, means for operating manuals and work procedure manuals of industrial machinery, means for displaying the revision proposal through a user interface and requesting approval from the user, and means for adding new operating procedures and safety guidelines to the manuals if the revision proposal is approved. This automates the updating of operating manuals and work procedure manuals of industrial machinery, reflecting the latest information in a timely manner, thereby improving worker safety and production efficiency.

[1090] "Reference documents" are documents that are the source of updates for industrial machinery operation manuals and work procedures, and include information sources on the Internet and internal documents.

[1091] The "means for analyzing the updated content" refers to a device or software that allows the server to use natural language processing technology to extract the differences between the old and new documents and identify the changes.

[1092] The "means for generating suggested revisions" refers to a device or software that has the function of generating a proposal that specifically indicates the parts of the user document that need to be changed or added, based on the analysis results.

[1093] "Means for notifying the user" refers to a system by which the server sends suggested revisions to the user via email or pop-up notification.

[1094] The "means for receiving approval" is a device or software that allows the server to receive information that allows the user to review the proposed revision and take action to approve or reject it.

[1095] An "automatic updating means" is a device or software that allows the server to automatically modify, add, or delete user documents based on user approval.

[1096] An "industrial machinery operation manual" refers to a document that contains operating procedures and safety guidelines for robots and machinery used in factories.

[1097] A "work procedure manual" is a document that details the operation and maintenance procedures of industrial machinery, and serves as a supplement to the operation manual.

[1098] A "user interface" is a screen or application that allows a user to review and approve proposed revisions, and is an interface that is displayed on a smartphone or computer.

[1099] The present invention relates to an automatic update system for operating manuals and work procedures for industrial machines. This system operates in cooperation with three parties: a server, a terminal, and a user.

[1100] System configuration

[1101] The system of the present invention includes the following components:

[1102] 1. Server

[1103] The server periodically checks for updates to the referenced documents. Specifically, it periodically retrieves the referenced documents from URL lists of Internet information sources and internal documents, and analyzes their contents. The analysis is performed using natural language processing techniques (e.g., NLTK or spaCy).

[1104] When a referenced document is updated, the server analyzes the update and generates specific suggested modifications to the user document, such as adding, modifying, or deleting text.

[1105] After generating the suggested revision, the server sends a notification to the user, which includes the suggested revision and its background.

[1106] 2. Terminal

[1107] Users receive notifications using a terminal, which may include an email client or an interface that displays pop-up notifications.

[1108] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. The approved proposed revision is transmitted to the server.

[1109] After the user approves, the terminal displays the updated document, allowing the user to confirm that the latest information is reflected.

[1110] 3. Users

[1111] The user receives a notification of the update of the referenced document and checks the contents of the proposed revision.

[1112] If the proposed revision is deemed appropriate, the user takes the action of approving it, which is done through the terminal interface.

[1113] After approval, the user can check the automatically updated document and apply it to their work.

[1114] Program processing explanation

[1115] Check and retrieve updates to referenced documents

[1116] The server periodically accesses the URLs of the factory's operational guidelines and work procedures to retrieve the latest content. This process uses Python and the requests library. For example, the BeautifulSoup library is used to parse the HTML content retrieved from the URL and extract the required text.

[1117] Update analysis

[1118] The server compares the old and new data and uses natural language processing technology to extract changes. The analysis results are a list of added, modified, and deleted information. Python and the difflib library are used here. NLTK and spaCy are also used for natural language analysis.

[1119] Generate correction suggestions

[1120] The server generates proposed revisions based on the analysis results, specifically by automatically creating revisions that include specific wording and changes, such as "add a new sensor installation method to the third paragraph of the document." This process may involve the use of generative AI models.

[1121] Sending notifications

[1122] The server notifies the user of the proposed changes via email or a popup on the device, explaining the proposed changes and the reasons for them. This is done using the smtplib library.

[1123] Specific examples

[1124] For example, if a new sensor installation procedure is added, the flow is as follows:

[1125] 1. The server retrieves the new guideline document.

[1126] URL: https: / / example.com / robot_manual.html

[1127] 2. The server compares the old and new documents and identifies the new procedure.

[1128] Additional steps: "How to install a new sensor: Step 1: [Details] ..."

[1129] 3. The server generates a correction proposal

[1130] Proposed fix: "Add new sensor placement instructions to Chapter 3: [Details]"

[1131] 4. Notify the user

[1132] Email subject: "Operation manual update proposal"

[1133] Email body: "New sensor installation instructions have been added to Chapter 3. Please review the contents."

[1134] 5. User Approval

[1135] Check the notification on your smartphone app and tap the "Approve" button.

[1136] 6. The server automatically updates the document

[1137] The operation manual is automatically updated and the latest information is displayed on your smartphone.

[1138] Prompt Sentence Examples

[1139] The prompt to periodically check for updates is:

[1140] "Get the latest content from the source document URL and compare it with the previous version to analyze the changes."

[1141] "If new operating procedures or guidelines are added, generate specific revisions based on them."

[1142] By utilizing this system, robot operations within factories can be quickly updated based on the latest guidelines and procedures, improving efficiency and safety.

[1143] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1144] Step 1:

[1145] The server periodically checks for updates to the referenced document.

[1146] Input: A list of URLs pre-registered on the server

[1147] How it works: The server periodically accesses each URL using the requests library and retrieves the HTML content.

[1148] Output: Latest document content

[1149] Step 2:

[1150] The server compares the old and new data of the document it has acquired and analyzes the updated content.

[1151] Input: Old and new document contents

[1152] How it works: The server uses the difflib library to extract the differences between the old and new documents, and uses natural language processing techniques (NLTK and spaCy) to identify the changes.

[1153] Output: List of changes (additions, modifications, deletions)

[1154] Step 3:

[1155] The server generates suggested modifications based on the analysis results.

[1156] Input: List of changes

[1157] How it works: The server automatically generates specific revision suggestions based on the analysis results. For example, it generates revision suggestions such as "Add a new sensor installation method to this paragraph." Generative AI models may also be used.

[1158] Output: A list of suggested fixes

[1159] Step 4:

[1160] The server notifies the user of the proposed revisions.

[1161] Input: List of proposed amendments

[1162] How it works: The server uses the smtplib library or other notification system to send suggested fixes to the user via email or popup notification.

[1163] Output: A message to inform the user

[1164] Step 5:

[1165] The user receives the notification on their device and checks the proposed changes.

[1166] Input: Notification message sent by the server

[1167] How it works: A notification appears on the user's device, and the user can review the suggested fix.

[1168] Output: User action (approve or reject)

[1169] Step 6:

[1170] The user takes action to approve or reject the proposed amendment.

[1171] Input: Proposed amendment

[1172] How it works: The user uses the device interface to accept or reject the proposed amendment.

[1173] Output: User authorization information

[1174] Step 7:

[1175] The server receives the user's authorization information and automatically updates the user document.

[1176] Input: User authorization information

[1177] Action: The server automatically updates the user documentation with the approved modifications, specifically adding the new sensor placement instructions to the operations manual and updating any other modifications.

[1178] Output: Latest user documents

[1179] Step 8:

[1180] The terminal displays the updated document to the user.

[1181] Input: Latest user document

[1182] What it does: The updated document appears on the user's device, allowing them to see the latest information.

[1183] Output: User-readable, up-to-date operating manual or work instructions

[1184] 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.

[1185] This invention combines emotion recognition technology with a system for automatically checking and analyzing updates to source documents and maintaining up-to-date user documents. The system works in cooperation with four parties: a server, a terminal, a user, and an emotion engine.

[1186] System Embodiments

[1187] The system of the present invention includes the following configuration.

[1188] 1. Server

[1189] The server periodically checks for updates to the referencing documents. Specifically, the server periodically retrieves the referencing documents from a pre-registered URL list and analyzes their contents. The analysis is performed using natural language processing (NLP) technology.

[1190] When a referenced document is updated, the server analyzes the update and generates specific suggested modifications to the user document, such as adding, modifying, or deleting text.

[1191] After generating the suggested revision, the server sends a notification to the user, which includes the suggested revision and its background.

[1192] 2. Emotion Engine

[1193] The emotion engine recognizes the user's emotions in real time. It uses facial expression recognition and voice analysis technologies to identify multiple emotional states, such as joy, sadness, surprise, and anger.

[1194] Adapt the content and format of notifications based on the user's emotional state. For example, if the user is tired, shorten the notification and add an uplifting message.

[1195] 3. Terminal

[1196] Users receive notifications using a terminal, which may include an email client or an interface that displays pop-up notifications.

[1197] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. The approved proposed revision is transmitted to the server.

[1198] After the user approves, the terminal displays the updated document, allowing the user to confirm that the latest information is reflected.

[1199] 4. Users

[1200] The user receives a notification of the update of the referenced document and checks the contents of the proposed revision.

[1201] If the proposed revision is deemed appropriate, the user takes the action of approving it, which is done through the terminal interface.

[1202] After approval, the user can check the automatically updated document and apply it to their work.

[1203] Program processing explanation

[1204] Check and retrieve updates to referenced documents

[1205] The server periodically accesses the list of URLs of the referencing documents to retrieve the latest content, for example, from internet news sites or an internal document management system.

[1206] Update analysis

[1207] The server compares the old and new data and uses natural language processing technology to extract changes. The analysis results are a list of added, modified, and deleted information.

[1208] Generate correction suggestions

[1209] The server generates suggested revisions based on the analysis results, including specific wording and changes, such as "add new statistical data to the third paragraph of the document."

[1210] Sending notifications

[1211] The server notifies the user of the generated revision suggestions, either by sending them to the user's email address or by displaying them as a pop-up notification on the device.

[1212] Emotional engine regulation

[1213] The emotion engine recognizes the user's emotions when receiving a notification and fine-tunes the content of the notification accordingly: for example, if the user is feeling tired, the notification will be brief and an encouraging message will be added.

[1214] Approval of the amendment

[1215] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. If the proposed revision is approved, the information is sent to the server.

[1216] Automatic document updates

[1217] After receiving approval from the user, the server automatically updates the user document with all the changes specified in the proposed revision. Once the update is complete, the terminal displays the latest document.

[1218] Specific examples

[1219] For example, consider the case where a new health guideline is added to a company's guideline document.

[1220] 1. The server detects updates to the guideline document.

[1221] Access the "referred URL" and obtain the new guideline document.

[1222] 2. The server compares the old and new guideline documents and identifies the changes.

[1223] Analyze the addition of new health guidelines and extract the differences.

[1224] 3. The server generates specific fix suggestions

[1225] "Added the following new health guideline to Chapter 2: 'Employees are encouraged to undergo regular health checks.'"

[1226] 4. Emotion engine analyzes user emotions

[1227] Recognize that the user is in a fatigued state when receiving a suggested revision notification.

[1228] 5. Tailor notification content with an emotion engine

[1229] Adapt it to be concise and easy to understand, and add encouragement such as, "Thank you for your hard work. Please check back for new health guidelines."

[1230] 6. Notify users

[1231] The user will be notified of the proposed fix via email and also via a pop-up.

[1232] 7. The user approves the proposed revision

[1233] The user checks the notification using the device and clicks the approval button.

[1234] 8. The server updates the document

[1235] The server that receives the approval automatically updates the guideline document and displays the latest document on the terminal.

[1236] In this way, by combining emotion recognition technology, the DocuGuardian system can provide a more personalized experience for users and make information retention more efficient.

[1237] The processing flow will be explained below.

[1238] Step 1:

[1239] The server periodically retrieves a list of referencing document URLs, which determines which documents to check for updates.

[1240] Step 2:

[1241] The server accesses each URL in the obtained URL list. The server sends an HTTP request to obtain the latest document data. This may involve using an API or web scraping technology.

[1242] Step 3:

[1243] The server temporarily stores the latest document data, which is then used in subsequent processing.

[1244] Step 4:

[1245] The server compares the latest saved data with previously acquired data and analyzes the differences, specifically extracting added, deleted, and modified text.

[1246] Step 5:

[1247] The server uses natural language processing (NLP) techniques to rate the importance of the extracted changes, thereby determining how much impact they will have on the user's document.

[1248] Step 6:

[1249] The server generates suggested modifications to user documents based on the most significant changes, such as adding new statistical data and generating text to insert the data into the appropriate places in the document.

[1250] Step 7:

[1251] The server notifies the user of the generated revision suggestions, which may be sent to the user's email address or displayed as a pop-up notification on the device.

[1252] Step 8:

[1253] The terminal receives the notification and displays it to the user, who then checks the content of the notification and views the details of the proposed revision via the terminal.

[1254] Step 9:

[1255] The emotion engine analyzes the user's emotions in real time, for example, by analyzing the user's facial expressions and voice to identify their emotional state (e.g., joy, sadness, surprise, anger, etc.).

[1256] Step 10:

[1257] The emotion engine fine-tunes notification content based on the user's emotional state: for example, if the user is tired, it will shorten the notification text and add an uplifting message.

[1258] Step 11:

[1259] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. If the proposed revision is approved, the information is sent to the server.

[1260] Step 12:

[1261] After receiving approval from the user, the server automatically updates the user document with all the changes specified in the proposed amendment.

[1262] Step 13:

[1263] The terminal displays the updated user document, allowing the user to confirm the latest status.

[1264] In this way, the DocuGuardian system, combined with emotion recognition technology, can provide users with more personalized notifications and make information retention more efficient.

[1265] Example 2

[1266] 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."

[1267] In conventional document management systems, users had to manually check for updates to the source documents and manually update the user documents accordingly, which was time-consuming. Furthermore, the system did not respond to the user's feelings or situation when receiving the update notification, which placed a heavy burden on the user and made efficient information management difficult.

[1268] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for periodically checking for updates to the referencing document, means for analyzing the update content, means for generating a revision proposal based on the analysis result, means for notifying the user of the generated revision proposal, means for recognizing the user's emotional state in real time and adjusting the notification content, means for receiving approval of the revision proposal from the user, and means for automatically updating the user document based on the approval. This makes it possible to automatically check for and analyze updates to the referencing document, notify the user in an appropriate manner that takes into consideration the user's emotions, and efficiently keep the user document up to date.

[1269] A "reference document" is a document that the system periodically checks for updates and is an information source that users refer to.

[1270] "Updates" refers to information that has been newly added, modified, or deleted from the referenced document.

[1271] "Analysis Method" refers to the technology or algorithm used to identify updates to the source document and extract the differences.

[1272] "Proposed revisions" refers to specific proposed changes to a user document generated based on analytical measures.

[1273] "Notification means" refers to the methods or techniques used to notify the user of generated revision suggestions.

[1274] "Emotional state" refers to the psychological state or emotion that can be read from the user's facial expression, voice, etc.

[1275] "Real-time recognition" refers to technology that instantly analyzes user behavior and reactions and provides results.

[1276] "Approval means" refers to an interface or process that allows a user to take action to approve or reject a proposed amendment.

[1277] "Automatically updating" refers to the system bringing user documents up to date without manual intervention, subject to user approval.

[1278] This invention combines emotion recognition technology with a system for automatically checking and analyzing updates to source documents and maintaining up-to-date user documents. The system works in cooperation with four parties: a server, a terminal, a user, and an emotion engine.

[1279] System configuration

[1280] The system of the present invention includes the following configuration.

[1281] server

[1282] The server is responsible for periodically checking for updates to the referenced documents and analyzing their contents. Based on a pre-registered URL list, the server periodically retrieves documents from online news sites and the company's internal document management system. To do this, the server uses HTTP requests. Natural language processing (NLP) technology is used to analyze the documents, and the Python NLP libraries spaCy and NLTK are used as specific analysis tools.

[1283] Emotion Engine

[1284] The emotion engine uses technology to analyze the user's facial expressions and voice to recognize their emotions in real time. It uses a camera and microphone to capture the user's emotional state. Based on the results, it can adjust the content of notifications, such as sending a briefer notification if the user is fatigued.

[1285] Terminal

[1286] The user receives a notification via their device and checks the proposed revision. The device includes an interface that displays an email client or a pop-up notification, through which the user can accept or reject the proposed revision. The user's action is transmitted to the server via an API.

[1287] User

[1288] The user receives a notification that the referenced document has been updated and checks the proposed revisions. If the proposed revisions are deemed appropriate, the user approves them via their terminal. The automatically updated document can then be reviewed and reflected in the business.

[1289] Hardware and software used

[1290] The specific implementation of the system uses the following hardware and software:

[1291] Server: A physical or virtual server with a high-performance processor (e.g., AWS EC2, Google Cloud Compute Engine)

[1292] Natural language processing libraries: spaCy and NLTK implemented in Python

[1293] Facial expression and voice analysis: Camera module, microphone, image analysis library such as OpenCV, and voice analysis library

[1294] Notification systems: SMTP protocol, Firebase Cloud Messaging (FCM), WebSocket

[1295] Specific examples

[1296] For example, consider a case where a new health guideline is added to a company's guideline document.

[1297] 1. Obtaining the referenced document: The server periodically accesses the "referenced URL" and obtains new guideline documents.

[1298] 2. Analysis of update content: The server compares the old and new guideline documents to identify changes. It analyzes the addition of new health guidelines and extracts the differences.

[1299] 3. Generate amendments: The server generates amendments such as "Add the following new health guideline to Chapter 2: 'Employees are encouraged to undergo regular health checks.'"

[1300] 4. Using the emotion engine: When the user receives the proposed revision notification, the emotion engine recognizes that the user is in a fatigued state.

[1301] 5. Notification content adjustment: The emotion engine will shorten the notification content and add encouraging messages such as, "Good job, please check the new health guidelines."

[1302] 6. Notify the user: The server will send a notification of the proposed fix to the user's email and display a pop-up notification on the device.

[1303] 7. Approval of proposed amendment: The user checks the notification via their device and clicks the approval button.

[1304] 8. Automatic document update: After the server receives approval, it automatically updates the guideline document and displays the latest document on the terminal.

[1305] Prompt Sentence Examples

[1306] Using a concrete example of this system, please explain in detail the process by which users actually review and approve proposed revisions.

[1307] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1308] Step 1: Check for and obtain updates to the referenced documents

[1309] The server periodically retrieves the referenced documents based on a pre-registered URL list. The input is a list of URLs, and the output is the most recent retrieved document. Specifically, it sends an HTTP request to download data from news sites on the Internet or an internal document management system. This process is scheduled, for example, every day at 9:00 AM.

[1310] Step 2: Analyze the updates

[1311] The server analyzes the acquired new and old document data using natural language processing technology. The input is the new document and the old document, and the output is an analysis result that identifies the changes. Specifically, it uses a text comparison algorithm to list added, deleted, and modified information. It uses Python NLP libraries spaCy and NLTK.

[1312] Step 3: Generate correction suggestions

[1313] The server generates specific revision suggestions based on the analysis results. The input is the analyzed changes, and the output is the revision suggestions. Specific actions include creating a revision suggestion with detailed instructions, such as "add new statistics to the third paragraph of the document." The revision suggestions can be formatted in Markdown or HTML.

[1314] Step 4: Sending notifications

[1315] The server notifies the user of the generated proposed corrections. The input is the proposed corrections, and the output is the notification email or popup notification. Specifically, it sends a notification to the user's email address using the SMTP protocol, or displays a popup notification in real time using Firebase Cloud Messaging (FCM) or WebSocket.

[1316] Step 5: Emotional Engine Adjustment

[1317] The emotion engine recognizes the emotional state of the user who received the notification in real time and adjusts the notification content accordingly. The input is the user's facial expression data and voice data, and the output is the adjusted notification content. Specifically, it analyzes facial expression data captured by the camera and voice data acquired by the microphone, and if the user is tired, it simplifies the notification text and adds an encouraging message.

[1318] Step 6: Approval of amendments

[1319] The user uses the device to check the proposed revision and take action to approve or reject it. The input is the notified revision proposal, and the output is the user's action to approve or reject it. Specifically, the user views the revision proposal through the device interface (web browser or mobile app) and clicks the approve or reject button.

[1320] Step 7: Automatically update documents

[1321] The server automatically updates the user document after receiving approval from the user. The input is the user's approved revision proposal, and the output is the updated user document. Specifically, the original document is edited based on the approved revision proposal to reflect the updates. The updated document is committed to a version control system (e.g., Git). After the update is complete, the latest document is displayed on the terminal.

[1322] (Application example 2)

[1323] 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."

[1324] In modern factories, changes to production processes and operation manuals occur frequently, requiring rapid response. However, quickly updating the workplace with updated information is extremely cumbersome and labor-intensive. In particular, issuing notifications without considering employees' emotions and states can lead to reduced efficiency. To improve this situation, there is a need for a system that automatically checks and analyzes updates to referenced documents, maintains the latest information on user documents, and recognizes users' emotions to provide appropriate notifications.

[1325] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1326] In this invention, the server includes means for periodically checking for updates to the referenced document, means for analyzing the updates to the referenced document, means for generating proposed revisions to the user document based on the analysis results, means for notifying the user of the generated proposed revisions, means for receiving approval of the proposed revisions from the user, means for automatically updating the user document based on the approval, means for recognizing the user's emotions, and means for adjusting the notification content based on the emotions. This enables efficient updates of the latest information on production processes and manuals in the factory and personalized notifications according to the user's emotional state.

[1327] A "referenced document" is a document that the system periodically checks and analyzes for updates.

[1328] "Means for analyzing update content" refers to the processes and techniques for extracting changes in the source document and understanding their content.

[1329] A "user document" is a document that is modified based on the updated content of the referencing document.

[1330] A "proposed revision" is a specific change proposed to a user document to reflect an update to a referenced document.

[1331] "Means of notification" refers to the interface or technology used to notify the user of the proposed revisions.

[1332] "Means for receiving approval" refers to the interface or process by which a user reviews the proposed revision and communicates approval or rejection to the system.

[1333] "Automatic updating means" refers to the process or technology for automatically updating user documents with the latest information upon user approval.

[1334] "Means for recognizing emotions" refers to techniques and processes for identifying a user's emotional state and obtaining that information.

[1335] "Means for adjusting notification content" refers to techniques or processes for changing the content or format of notification text depending on the user's emotional state.

[1336] This invention is a system that automatically updates the latest information on production processes and operation manuals in factories, recognizes the user's emotions, and notifies them appropriately. This system works in cooperation with four parties: a server, a terminal, a user, and an emotion engine.

[1337] System configuration

[1338] The system of the present invention includes the following configuration.

[1339] 1. Server

[1340] The server periodically checks for updates to the referencing document. Specifically, the server periodically retrieves the referencing document from a pre-registered URL list and analyzes its contents. The analysis is performed using natural language processing (NLP) technology. When the referencing document is updated, the server analyzes the update content and generates specific suggested modifications to the user document. Suggested modifications include adding, correcting, or deleting text. After generating the suggested modifications, the server sends a notification to the user. This notification includes the content of the suggested modifications and their background. As a specific example, if a factory safety manual has been updated, the server will notify the user that "a new safety procedure has been added to Chapter 2."

[1341] 2. Emotion Engine

[1342] The emotion engine recognizes the user's emotions in real time. It uses facial expression recognition and voice analysis technology to identify multiple emotional states, such as joy, sadness, surprise, and anger. It adjusts the content and format of notifications based on the user's emotional state. For example, if the user is tired, it shortens the notification and adds an encouraging message. The specific software used is "EmotionRecognition."

[1343] 3. Terminal

[1344] A terminal is a device through which a user receives notifications. The terminal includes an interface that displays a mail client and pop-up notifications. The user uses the terminal to check the contents of the proposed amendment and take action to approve or reject it. The approved amendment is transmitted to the server. After the user approves it, the terminal displays the updated document, allowing the user to confirm that the latest information is reflected. For example, the terminal displays a pop-up notification saying, "Please review the new safety procedures."

[1345] 4. Users

[1346] The user receives a notification that the referenced document has been updated and checks the proposed revisions. If the proposed revisions are deemed appropriate, the user takes action to approve them. This is done through the terminal interface. After approval, the user checks the automatically updated document and incorporates it into their work.

[1347] Specific examples

[1348] For example, if a new health guideline is added to a factory safety manual, the server detects the change and generates a correction suggestion. If the emotion engine detects the user's fatigue, it shortens the notification to "Thank you for your hard work. Please check the new health guideline." An example of a prompt is as follows:

[1349] Example prompt sentence:

[1350] Input to the generative AI model:

[1351] "A new procedure has been added to the factory safety manual. Analyze the update and generate specific suggested fixes. Also, use emotion recognition to tailor notification messages. If the user is feeling fatigued, keep the message brief."

[1352] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1353] Step 1:

[1354] The server checks for updates to the referencing document.

[1355] Input: A list of pre-registered URLs.

[1356] The server periodically accesses the list of URLs to retrieve the latest document content, for example by downloading data from a news feed or an internal document management system.

[1357] Output: The latest retrieved document content.

[1358] Step 2:

[1359] The server parses the updates.

[1360] Input: The latest document content obtained in step 1.

[1361] The server uses natural language processing (NLP) technology to compare the old and new data and extract changes.

[1362] Specifically, it uses BeautifulSoup to parse the HTML, and spacy to tokenize the document and identify additions, modifications, and deletions of text.

[1363] Output: A list of changes.

[1364] Step 3:

[1365] The server generates a revision suggestion.

[1366] Input: The list of changes identified in step 2.

[1367] The server automatically generates specific suggested revisions to the user's document based on the changes.

[1368] For example, include specific revisions such as "Add a new procedure to the third paragraph."

[1369] Output: The generated correction suggestions.

[1370] Step 4:

[1371] The server will notify you of the proposed revision.

[1372] Input: The proposed fix generated in step 3.

[1373] The server will send suggested revisions to the user via email or pop-up notification.

[1374] Specifically, it sends emails using the SMTP protocol and provides real-time notifications using WebSocket.

[1375] Output: Notification sent to the user.

[1376] Step 5:

[1377] The emotion engine recognizes the user's emotions.

[1378] Input: Camera video and audio data when the user receives a notification.

[1379] The emotion engine uses facial expression recognition and voice analysis techniques to identify the user's emotional state.

[1380] Specifically, it uses EmotionRecognition software to analyze the user's emotions in real time.

[1381] Output: The perceived emotional state of the user.

[1382] Step 6:

[1383] The server adjusts the notification content based on the emotional state.

[1384] Input: The user's emotional state recognized in step 5, and the notification sent in step 4.

[1385] The server fine-tunes the content and format of the notification message depending on the user's emotions.

[1386] For example, if the user is tired, change the message to something more concise like "Great work, check out the new steps."

[1387] Output: The adjusted notification message.

[1388] Step 7:

[1389] The terminal receives the user's approval.

[1390] Input: The notification message adjusted in step 6.

[1391] The user can review the notification through the device interface and accept or reject the proposed changes.

[1392] Specifically, approval information is sent to the server by clicking a UI button on the terminal.

[1393] Output: User approval or denial information.

[1394] Step 8:

[1395] The server automatically updates the user document.

[1396] Input: User approval information received in step 7 and correction proposal generated in step 3.

[1397] The server automatically updates the user document based on the approved amendments.

[1398] For example, updating a MySQL database to reflect the latest information in a document management system.

[1399] Output: The latest updated user documentation.

[1400] 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.

[1401] 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.

[1402] 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.

[1403] [Fourth embodiment]

[1404] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1405] 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.

[1406] 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).

[1407] 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.

[1408] 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.

[1409] 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).

[1410] 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.

[1411] 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.

[1412] 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.

[1413] 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.

[1414] 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.

[1415] 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.

[1416] 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."

[1417] The present invention relates to a system for automatically checking and analyzing updates to referenced documents and maintaining up-to-date information for user documents. The system operates in cooperation with a server, a terminal, and a user.

[1418] System Embodiments

[1419] The system of the present invention includes the following configuration.

[1420] 1. Server

[1421] The server periodically checks for updates to the referencing documents. Specifically, the server periodically retrieves the referencing documents from a pre-registered URL list and analyzes their contents. The analysis is performed using natural language processing (NLP) technology.

[1422] When a referenced document is updated, the server analyzes the update and generates specific suggested modifications to the user document, such as adding, modifying, or deleting text.

[1423] After generating the suggested revision, the server sends a notification to the user, which includes the suggested revision and its background.

[1424] 2. Terminal

[1425] Users receive notifications using a terminal, which may include an email client or an interface that displays pop-up notifications.

[1426] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. The approved proposed revision is transmitted to the server.

[1427] After the user approves, the terminal displays the updated document, allowing the user to confirm that the latest information is reflected.

[1428] 3. Users

[1429] The user receives a notification of the update of the referenced document and checks the contents of the proposed revision.

[1430] If the proposed revision is deemed appropriate, the user takes the action of approving it, which is done through the terminal interface.

[1431] After approval, the user can check the automatically updated document and apply it to their work.

[1432] Program processing explanation

[1433] Check and retrieve updates to referenced documents

[1434] The server periodically accesses the URL of the referenced document to retrieve the latest content, for example, from an internet news site or an internal document management system.

[1435] Update analysis

[1436] The server compares the old and new data and uses natural language processing technology to extract changes. The analysis results are a list of added, modified, and deleted information.

[1437] Generate correction suggestions

[1438] The server then generates suggested revisions based on the analysis results, including specific wording and changes, such as "add new statistical data to the third paragraph of the document."

[1439] Sending notifications

[1440] The server notifies the user of the proposed changes via email or a pop-up on the device, explaining the proposed changes and the reasons for them.

[1441] Approval of the amendment

[1442] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. If the proposed revision is approved, the information is sent to the server.

[1443] Automatic document updates

[1444] The server automatically updates the user document after receiving approval from the user. Updates include adding, modifying, or deleting specific text. Once the update is complete, the updated document is displayed on the terminal.

[1445] Specific examples

[1446] For example, consider the case where a new health guideline is added to a company's guideline document.

[1447] 1. The server detects updates to the guideline document.

[1448] Access the "referred URL" and obtain the new guideline document.

[1449] 2. The server compares the old and new guideline documents and identifies the changes.

[1450] Analyze the addition of new health guidelines and extract the differences.

[1451] 3. The server generates specific fix suggestions

[1452] "Added the following new health guideline to Chapter 2: 'Employees are encouraged to undergo regular health checks.'"

[1453] 4. Notify users

[1454] The user will be notified of the proposed fix via email and also via a pop-up.

[1455] 5. The user approves the proposed revision

[1456] The user checks the notification using the device and clicks the approval button.

[1457] 6. The server updates the document

[1458] The server that receives the approval automatically updates the guideline document and displays the latest document on the terminal.

[1459] This allows users to easily maintain up-to-date information and ensures efficient document maintenance. This system is an effective means of dealing with frequent changes in information and maintaining accurate information.

[1460] The processing flow will be explained below.

[1461] Step 1:

[1462] The server periodically retrieves a list of referencing document URLs, which determines which documents to check for updates.

[1463] Step 2:

[1464] The server accesses each URL in the obtained URL list. The server sends an HTTP request to obtain the latest document data. This may involve using an API or web scraping technology.

[1465] Step 3:

[1466] The server temporarily stores the latest document data, which is then used in subsequent processing.

[1467] Step 4:

[1468] The server compares the latest stored data with the previously acquired data, analyzes the differences, and identifies changes. Specifically, it extracts added, deleted, and modified text.

[1469] Step 5:

[1470] The server uses natural language processing (NLP) techniques to assess the importance of the changes, thereby determining how much impact they will have on the user's documents.

[1471] Step 6:

[1472] The server generates suggested modifications to the user's document based on the identified changes, for example, if new statistical data has been added, it generates instructions to insert that data into the document at the appropriate point.

[1473] Step 7:

[1474] The server notifies the user of the generated revision suggestions, either by sending them to the user's email address or by displaying them as a pop-up notification on the device.

[1475] Step 8:

[1476] The terminal receives the notification and displays it to the user, who then checks the content of the notification and views the details of the proposed revision via the terminal.

[1477] Step 9:

[1478] The user checks the proposed amendment and takes action to approve or reject it. If the user selects approval, he clicks the approve button.

[1479] Step 10:

[1480] The terminal sends the user's approval action to the server, and the server receives the approval.

[1481] Step 11:

[1482] After receiving approval from the user, the server automatically updates the user document with all the changes specified in the proposed amendment.

[1483] Step 12:

[1484] The terminal displays the updated user document, allowing the user to confirm the latest status.

[1485] Through these steps, the DocuGuardian system automatically checks for updates to the source documents and keeps user documents up-to-date, ensuring the reliability and accuracy of information and reducing the maintenance burden on users.

[1486] Example 1

[1487] 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."

[1488] Currently, manually updating user documents every time a referenced document is updated is a time-consuming and laborious task. Furthermore, when documents are updated frequently, it is difficult to keep the information up-to-date, and there is a risk that important information will not be updated. Furthermore, when managing a large number of documents, manual updating is practically impossible. To solve these problems, an efficient and effective system is needed to automatically detect changes in referenced documents and maintain up-to-date user documents.

[1489] 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.

[1490] In this invention, the server includes means for periodically checking for updates to a referencing document, means for acquiring the latest content of the referencing document, means for analyzing the acquired latest content to compare and extract update details, means for generating specific revision proposals for the user document based on the analysis results, means for notifying the user of the generated revision proposals, means for receiving approval of the revision proposals from the user, and means for automatically updating the user document based on the approval, thereby enabling the user document to always maintain the latest information.

[1491] "Source documents" refers to external documents or information sources that the system uses to monitor update status.

[1492] "Means for periodic checking" refers to a mechanism that provides the system with the ability to set a time interval and automatically check for updates to the referenced document.

[1493] "Means of obtaining the latest content" refers to a mechanism that accesses the referrer URL, automatically downloads the latest information, and obtains the data necessary for analysis.

[1494] "Means for analyzing, comparing, and extracting updated content" refers to a mechanism for comparing the old and new data in the source document and identifying changes using natural language processing technology.

[1495] The "means for generating a specific revision proposal" refers to a mechanism for creating specific change instructions to be reflected in the user document based on the updated content.

[1496] "Means for notifying the user" refers to a mechanism for notifying the user of the generated revision proposal by means of email, pop-up notification, or the like.

[1497] The "means for receiving approval from the user" refers to a mechanism for providing an interface that enables the user to check the proposed revision and convey to the system their intention to approve or reject it.

[1498] "Means for automatic updating" refers to a mechanism for automatically reflecting necessary changes to user documents upon receiving approval from the user.

[1499] A "generative AI model" refers to a model that uses artificial intelligence technology to generate and analyze text data.

[1500] A "prompt" is an instruction or question entered into a generative AI model to cause it to generate a specific output.

[1501] "User document" refers to a document that is managed by the system and to which updates are reflected.

[1502] "Natural language processing technology" refers to all technologies that enable computers to understand, analyze, and generate human language.

[1503] The system of the present invention provides a technique for automatically checking and analyzing updates to referenced documents and maintaining the latest information on user documents. The system operates in cooperation with three parties: a server, a terminal, and a user.

[1504] Server Features

[1505] The server has the ability to periodically check for updates to the referenced documents and retrieve the latest content. The referenced documents are stored in information sources on the Internet or in an internal document management system. The server accesses the URL using the "requests" library and retrieves the HTML content. The server then parses this retrieved content using the "BeautifulSoup" library to extract the necessary data.

[1506] The acquired new and old data is compared using the "difflib" library to extract changes. These changes are then analyzed using natural language processing (NLP) technology. Specific tools used include "spaCy" and "NLTK." Based on the analysis results, the server generates suggested modifications. These suggested modifications are generated by inputting prompt sentences into a generative AI model such as "OpenAI GPT-4."

[1507] After generating the proposed changes, the server will send a notification to the user using SendGrid or Amazon SES, including the specific changes and the reasons for them.

[1508] Device Features

[1509] The terminal is a device through which the user receives notifications from the server. The terminal includes an interface that displays a mail client and pop-up notifications. The user can check the notifications through the terminal and accept or reject the proposed amendments. The accepted amendments are sent to the server, which automatically updates the user document based on the information.

[1510] User Roles

[1511] The user receives a notification on their device, checks the proposed revisions, and takes action to approve them. Based on the approved revisions, the user checks the updated document and incorporates them into their work. This allows the user to always have the latest information.

[1512] Specific examples

[1513] Below are some examples of how new health guidelines may be added to a company's guidance document:

[1514] 1. The server detects an update to the guideline document:

[1515] The server accesses "https: / / example.com / guidelines.html" and retrieves the new guideline document.

[1516] Use "requests" and "BeautifulSoup" for this operation.

[1517] 2. The server compares the old and new guideline documents and identifies the changes:

[1518] The server uses "difflib" to identify where new health guidelines should be added.

[1519] Analyze the context using "spaCy".

[1520] 3. The server generates a concrete fix:

[1521] The prompt sentence for the proposed correction is input to the generative AI model, which generates a correction suggestion such as:

[1522] "Added the following new health guideline to Chapter 2: 'Employees are encouraged to undergo regular health checks.'"

[1523] 4. Notify users:

[1524] The server uses SendGrid to send an email to the user and display a pop-up notification on the device.

[1525] 5. User accepts proposed amendment:

[1526] The user checks the proposed revisions using the terminal and clicks the approve button.

[1527] 6. The server updates the document:

[1528] The server updates the guideline document using the Google Docs API or the Microsoft Office 365 API.

[1529] The updated document is displayed on the terminal, allowing the user to view the latest document.

[1530] This effectively keeps user documents up to date and simplifies document maintenance.

[1531] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1532] Step 1: Check for updates to the referenced document

[1533] The server periodically checks a list of pre-registered URLs. The input is a list of each URL, and the server accesses each URL based on that. Specifically, a system scheduler (e.g., a cron job) is used to check for URL updates every day at 3:00 AM. Based on this check, an output is obtained that determines whether or not there have been any updates.

[1534] Step 2: Get the latest content

[1535] The server accesses the referrer URLs to retrieve HTML content. The input is a list of referrer URLs. The server accesses the URLs using the "requests" library and parses the retrieved HTML data using "BeautifulSoup." The output as a result of this processing is the extraction of the latest updated content.

[1536] Step 3: Analyze the updates

[1537] The server saves the latest content it has retrieved and compares it with the previous content. The input is the latest content and the previous content. The server uses the "difflib" library to extract the differences and analyzes them with natural language processing technology (such as "spaCy" or "NLTK"). This gives the output that identifies which parts have been added, modified, or deleted.

[1538] Step 4: Generate correction suggestions

[1539] The server generates specific revision suggestions based on the changes. The input is the analysis result of the update content. The server inputs a prompt sentence into a generative AI model (e.g., "OpenAI GPT-4") and outputs the generated revision suggestions. Specifically, it generates the revision suggestion, "Please add new statistical data to the third paragraph of the document."

[1540] Step 5: Sending notifications

[1541] The server notifies the user of the proposed revisions. The input is the proposed revisions. The notification is sent via email using "SendGrid" or "Amazon SES," and is also displayed as a pop-up notification on the device. The result of this processing is an output that tells the user the specific proposed revisions and the reasons for them.

[1542] Step 6: Review and approve proposed amendments

[1543] The user receives a notification on their device and checks the proposed revision. The input is the notification and the proposed revision received from the server. The user accepts or rejects the proposed revision using the interface on their device. Specific actions include pressing buttons on an email client or browser. The output resulting from this process is that information about the approved proposed revision is sent to the server.

[1544] Step 7: Automatically update user documents

[1545] The server receives approval from the user and automatically updates the user document. The input is the approved revision proposal from the user. The update process is performed using the Google Docs API or Microsoft Office 365 API, and specific text is added, modified, or deleted. The result of this process is an updated user document that is displayed on the terminal.

[1546] (Application example 1)

[1547] 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."

[1548] Updating operation manuals and work procedures for industrial machinery requires manual work, which is inefficient and does not reflect the latest information in a timely manner. Rapid technological innovation and changes in security requirements mean that it is especially important to quickly reflect accurate and up-to-date information. While this improves worker safety and production efficiency, it has been difficult to achieve this effectively using conventional methods.

[1549] 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.

[1550] In this invention, the server includes means for periodically checking for updates to a reference source document, means for analyzing the update content of the reference source document, means for generating a revision proposal for a user document based on the analysis result, means for notifying the user of the generated revision proposal, means for receiving approval for the revision proposal from the user, means for automatically updating the user document based on the approval, means for operating manuals and work procedure manuals of industrial machinery, means for displaying the revision proposal through a user interface and requesting approval from the user, and means for adding new operating procedures and safety guidelines to the manuals if the revision proposal is approved. This automates the updating of operating manuals and work procedure manuals of industrial machinery, reflecting the latest information in a timely manner, thereby improving worker safety and production efficiency.

[1551] "Reference documents" are documents that are the source of updates for industrial machinery operation manuals and work procedures, and include information sources on the Internet and internal documents.

[1552] The "means for analyzing the updated content" refers to a device or software that allows the server to use natural language processing technology to extract the differences between the old and new documents and identify the changes.

[1553] The "means for generating suggested revisions" refers to a device or software that has the function of generating a proposal that specifically indicates the parts of the user document that need to be changed or added, based on the analysis results.

[1554] "Means for notifying the user" refers to a system by which the server sends suggested revisions to the user via email or pop-up notification.

[1555] The "means for receiving approval" is a device or software that allows the server to receive information that allows the user to review the proposed revision and take action to approve or reject it.

[1556] An "automatic updating means" is a device or software that allows the server to automatically modify, add, or delete user documents based on user approval.

[1557] An "industrial machinery operation manual" refers to a document that contains operating procedures and safety guidelines for robots and machinery used in factories.

[1558] A "work procedure manual" is a document that details the operation and maintenance procedures of industrial machinery, and serves as a supplement to the operation manual.

[1559] A "user interface" is a screen or application that allows a user to review and approve proposed revisions, and is an interface that is displayed on a smartphone or computer.

[1560] The present invention relates to an automatic update system for operating manuals and work procedures for industrial machines. This system operates in cooperation with three parties: a server, a terminal, and a user.

[1561] System configuration

[1562] The system of the present invention includes the following components:

[1563] 1. Server

[1564] The server periodically checks for updates to the referenced documents. Specifically, it periodically retrieves the referenced documents from URL lists of Internet information sources and internal documents, and analyzes their contents. The analysis is performed using natural language processing techniques (e.g., NLTK or spaCy).

[1565] When a referenced document is updated, the server analyzes the update and generates specific suggested modifications to the user document, such as adding, modifying, or deleting text.

[1566] After generating the suggested revision, the server sends a notification to the user, which includes the suggested revision and its background.

[1567] 2. Terminal

[1568] Users receive notifications using a terminal, which may include an email client or an interface that displays pop-up notifications.

[1569] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. The approved proposed revision is transmitted to the server.

[1570] After the user approves, the terminal displays the updated document, allowing the user to confirm that the latest information is reflected.

[1571] 3. Users

[1572] The user receives a notification of the update of the referenced document and checks the contents of the proposed revision.

[1573] If the proposed revision is deemed appropriate, the user takes the action of approving it, which is done through the terminal interface.

[1574] After approval, the user can check the automatically updated document and apply it to their work.

[1575] Program processing explanation

[1576] Check and retrieve updates to referenced documents

[1577] The server periodically accesses the URLs of the factory's operational guidelines and work procedures to retrieve the latest content. This process uses Python and the requests library. For example, the BeautifulSoup library is used to parse the HTML content retrieved from the URL and extract the required text.

[1578] Update analysis

[1579] The server compares the old and new data and uses natural language processing technology to extract changes. The analysis results are a list of added, modified, and deleted information. Python and the difflib library are used here. NLTK and spaCy are also used for natural language analysis.

[1580] Generate correction suggestions

[1581] The server generates proposed revisions based on the analysis results, specifically by automatically creating revisions that include specific wording and changes, such as "add a new sensor installation method to the third paragraph of the document." This process may involve the use of generative AI models.

[1582] Sending notifications

[1583] The server notifies the user of the proposed changes via email or a popup on the device, explaining the proposed changes and the reasons for them. This is done using the smtplib library.

[1584] Specific examples

[1585] For example, if a new sensor installation procedure is added, the flow is as follows:

[1586] 1. The server retrieves the new guideline document.

[1587] URL: https: / / example.com / robot_manual.html

[1588] 2. The server compares the old and new documents and identifies the new procedure.

[1589] Additional steps: "How to install a new sensor: Step 1: [Details] ..."

[1590] 3. The server generates a correction proposal

[1591] Proposed fix: "Add new sensor placement instructions to Chapter 3: [Details]"

[1592] 4. Notify the user

[1593] Email subject: "Operation manual update proposal"

[1594] Email body: "New sensor installation instructions have been added to Chapter 3. Please review the contents."

[1595] 5. User Approval

[1596] Check the notification on your smartphone app and tap the "Approve" button.

[1597] 6. The server automatically updates the document

[1598] The operation manual is automatically updated and the latest information is displayed on your smartphone.

[1599] Prompt Sentence Examples

[1600] The prompt to periodically check for updates is:

[1601] "Get the latest content from the source document URL and compare it with the previous version to analyze the changes."

[1602] "If new operating procedures or guidelines are added, generate specific revisions based on them."

[1603] By utilizing this system, robot operations within factories can be quickly updated based on the latest guidelines and procedures, improving efficiency and safety.

[1604] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1605] Step 1:

[1606] The server periodically checks for updates to the referenced document.

[1607] Input: A list of URLs pre-registered on the server

[1608] How it works: The server periodically accesses each URL using the requests library and retrieves the HTML content.

[1609] Output: Latest document content

[1610] Step 2:

[1611] The server compares the old and new data of the document it has acquired and analyzes the updated content.

[1612] Input: Old and new document contents

[1613] How it works: The server uses the difflib library to extract the differences between the old and new documents, and uses natural language processing techniques (NLTK and spaCy) to identify the changes.

[1614] Output: List of changes (additions, modifications, deletions)

[1615] Step 3:

[1616] The server generates suggested modifications based on the analysis results.

[1617] Input: List of changes

[1618] How it works: The server automatically generates specific revision suggestions based on the analysis results. For example, it generates revision suggestions such as "Add a new sensor installation method to this paragraph." Generative AI models may also be used.

[1619] Output: A list of suggested fixes

[1620] Step 4:

[1621] The server notifies the user of the proposed revisions.

[1622] Input: List of proposed amendments

[1623] How it works: The server uses the smtplib library or other notification system to send suggested fixes to the user via email or popup notification.

[1624] Output: A message to inform the user

[1625] Step 5:

[1626] The user receives the notification on their device and checks the proposed changes.

[1627] Input: Notification message sent by the server

[1628] How it works: A notification appears on the user's device, and the user can review the suggested fix.

[1629] Output: User action (approve or reject)

[1630] Step 6:

[1631] The user takes action to approve or reject the proposed amendment.

[1632] Input: Proposed amendment

[1633] How it works: The user uses the device interface to accept or reject the proposed amendment.

[1634] Output: User authorization information

[1635] Step 7:

[1636] The server receives the user's authorization information and automatically updates the user document.

[1637] Input: User authorization information

[1638] Action: The server automatically updates the user documentation with the approved modifications, specifically adding the new sensor placement instructions to the operations manual and updating any other modifications.

[1639] Output: Latest user documents

[1640] Step 8:

[1641] The terminal displays the updated document to the user.

[1642] Input: Latest user document

[1643] What it does: The updated document appears on the user's device, allowing them to see the latest information.

[1644] Output: User-readable, up-to-date operating manual or work instructions

[1645] 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.

[1646] This invention combines emotion recognition technology with a system for automatically checking and analyzing updates to source documents and maintaining up-to-date user documents. The system works in cooperation with four parties: a server, a terminal, a user, and an emotion engine.

[1647] System Embodiments

[1648] The system of the present invention includes the following configuration.

[1649] 1. Server

[1650] The server periodically checks for updates to the referencing documents. Specifically, the server periodically retrieves the referencing documents from a pre-registered URL list and analyzes their contents. The analysis is performed using natural language processing (NLP) technology.

[1651] When a referenced document is updated, the server analyzes the update and generates specific suggested modifications to the user document, such as adding, modifying, or deleting text.

[1652] After generating the suggested revision, the server sends a notification to the user, which includes the suggested revision and its background.

[1653] 2. Emotion Engine

[1654] The emotion engine recognizes the user's emotions in real time. It uses facial expression recognition and voice analysis technologies to identify multiple emotional states, such as joy, sadness, surprise, and anger.

[1655] Adapt the content and format of notifications based on the user's emotional state. For example, if the user is tired, shorten the notification and add an uplifting message.

[1656] 3. Terminal

[1657] Users receive notifications using a terminal, which may include an email client or an interface that displays pop-up notifications.

[1658] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. The approved proposed revision is transmitted to the server.

[1659] After the user approves, the terminal displays the updated document, allowing the user to confirm that the latest information is reflected.

[1660] 4. Users

[1661] The user receives a notification of the update of the referenced document and checks the contents of the proposed revision.

[1662] If the proposed revision is deemed appropriate, the user takes the action of approving it, which is done through the terminal interface.

[1663] After approval, the user can check the automatically updated document and apply it to their work.

[1664] Program processing explanation

[1665] Check and retrieve updates to referenced documents

[1666] The server periodically accesses the list of URLs of the referencing documents to retrieve the latest content, for example, from internet news sites or an internal document management system.

[1667] Update analysis

[1668] The server compares the old and new data and uses natural language processing technology to extract changes. The analysis results are a list of added, modified, and deleted information.

[1669] Generate correction suggestions

[1670] The server generates suggested revisions based on the analysis results, including specific wording and changes, such as "add new statistical data to the third paragraph of the document."

[1671] Sending notifications

[1672] The server notifies the user of the generated revision suggestions, either by sending them to the user's email address or by displaying them as a pop-up notification on the device.

[1673] Emotional engine regulation

[1674] The emotion engine recognizes the user's emotions when receiving a notification and fine-tunes the content of the notification accordingly: for example, if the user is feeling tired, the notification will be brief and an encouraging message will be added.

[1675] Approval of the amendment

[1676] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. If the proposed revision is approved, the information is sent to the server.

[1677] Automatic document updates

[1678] After receiving approval from the user, the server automatically updates the user document with all the changes specified in the proposed revision. Once the update is complete, the terminal displays the latest document.

[1679] Specific examples

[1680] For example, consider the case where a new health guideline is added to a company's guideline document.

[1681] 1. The server detects updates to the guideline document.

[1682] Access the "referred URL" and obtain the new guideline document.

[1683] 2. The server compares the old and new guideline documents and identifies the changes.

[1684] Analyze the addition of new health guidelines and extract the differences.

[1685] 3. The server generates specific fix suggestions

[1686] "Added the following new health guideline to Chapter 2: 'Employees are encouraged to undergo regular health checks.'"

[1687] 4. Emotion engine analyzes user emotions

[1688] Recognize that the user is in a fatigued state when receiving a suggested revision notification.

[1689] 5. Tailor notification content with an emotion engine

[1690] Adapt it to be concise and easy to understand, and add encouragement such as, "Thank you for your hard work. Please check back for new health guidelines."

[1691] 6. Notify users

[1692] The user will be notified of the proposed fix via email and also via a pop-up.

[1693] 7. The user approves the proposed revision

[1694] The user checks the notification using the device and clicks the approval button.

[1695] 8. The server updates the document

[1696] The server that receives the approval automatically updates the guideline document and displays the latest document on the terminal.

[1697] In this way, by combining emotion recognition technology, the DocuGuardian system can provide a more personalized experience for users and make information retention more efficient.

[1698] The processing flow will be explained below.

[1699] Step 1:

[1700] The server periodically retrieves a list of referencing document URLs, which determines which documents to check for updates.

[1701] Step 2:

[1702] The server accesses each URL in the obtained URL list. The server sends an HTTP request to obtain the latest document data. This may involve using an API or web scraping technology.

[1703] Step 3:

[1704] The server temporarily stores the latest document data, which is then used in subsequent processing.

[1705] Step 4:

[1706] The server compares the latest saved data with previously acquired data and analyzes the differences, specifically extracting added, deleted, and modified text.

[1707] Step 5:

[1708] The server uses natural language processing (NLP) techniques to rate the importance of the extracted changes, thereby determining how much impact they will have on the user's document.

[1709] Step 6:

[1710] The server generates suggested modifications to user documents based on the most significant changes, such as adding new statistical data and generating text to insert the data into the appropriate places in the document.

[1711] Step 7:

[1712] The server notifies the user of the generated revision suggestions, which may be sent to the user's email address or displayed as a pop-up notification on the device.

[1713] Step 8:

[1714] The terminal receives the notification and displays it to the user, who then checks the content of the notification and views the details of the proposed revision via the terminal.

[1715] Step 9:

[1716] The emotion engine analyzes the user's emotions in real time, for example, by analyzing the user's facial expressions and voice to identify their emotional state (e.g., joy, sadness, surprise, anger, etc.).

[1717] Step 10:

[1718] The emotion engine fine-tunes notification content based on the user's emotional state: for example, if the user is tired, it will shorten the notification text and add an uplifting message.

[1719] Step 11:

[1720] The user uses the terminal to check the contents of the proposed revision and take action to approve or reject it. If the proposed revision is approved, the information is sent to the server.

[1721] Step 12:

[1722] After receiving approval from the user, the server automatically updates the user document with all the changes specified in the proposed amendment.

[1723] Step 13:

[1724] The terminal displays the updated user document, allowing the user to confirm the latest status.

[1725] In this way, the DocuGuardian system, combined with emotion recognition technology, can provide users with more personalized notifications and make information retention more efficient.

[1726] Example 2

[1727] 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."

[1728] In conventional document management systems, users had to manually check for updates to the source documents and manually update the user documents accordingly, which was time-consuming. Furthermore, the system did not respond to the user's feelings or situation when receiving the update notification, which placed a heavy burden on the user and made efficient information management difficult.

[1729] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for periodically checking for updates to the referencing document, means for analyzing the update content, means for generating a revision proposal based on the analysis result, means for notifying the user of the generated revision proposal, means for recognizing the user's emotional state in real time and adjusting the notification content, means for receiving approval of the revision proposal from the user, and means for automatically updating the user document based on the approval. This makes it possible to automatically check for and analyze updates to the referencing document, notify the user in an appropriate manner that takes into consideration the user's emotions, and efficiently keep the user document up to date.

[1730] A "reference document" is a document that the system periodically checks for updates and is an information source that users refer to.

[1731] "Updates" refers to information that has been newly added, modified, or deleted from the referenced document.

[1732] "Analysis Method" refers to the technology or algorithm used to identify updates to the source document and extract the differences.

[1733] "Proposed revisions" refers to specific proposed changes to a user document generated based on analytical measures.

[1734] "Notification means" refers to the methods or techniques used to notify the user of generated revision suggestions.

[1735] "Emotional state" refers to the psychological state or emotion that can be read from the user's facial expression, voice, etc.

[1736] "Real-time recognition" refers to technology that instantly analyzes user behavior and reactions and provides results.

[1737] "Approval means" refers to an interface or process that allows a user to take action to approve or reject a proposed amendment.

[1738] "Automatically updating" refers to the system bringing user documents up to date without manual intervention, subject to user approval.

[1739] This invention combines emotion recognition technology with a system for automatically checking and analyzing updates to source documents and maintaining up-to-date user documents. The system works in cooperation with four parties: a server, a terminal, a user, and an emotion engine.

[1740] System configuration

[1741] The system of the present invention includes the following configuration.

[1742] server

[1743] The server is responsible for periodically checking for updates to the referenced documents and analyzing their contents. Based on a pre-registered URL list, the server periodically retrieves documents from online news sites and the company's internal document management system. To do this, the server uses HTTP requests. Natural language processing (NLP) technology is used to analyze the documents, and the Python NLP libraries spaCy and NLTK are used as specific analysis tools.

[1744] Emotion Engine

[1745] The emotion engine uses technology to analyze the user's facial expressions and voice to recognize their emotions in real time. It uses a camera and microphone to capture the user's emotional state. Based on the results, it can adjust the content of notifications, such as sending a briefer notification if the user is fatigued.

[1746] Terminal

[1747] The user receives a notification via their device and checks the proposed revision. The device includes an interface that displays an email client or a pop-up notification, through which the user can accept or reject the proposed revision. The user's action is transmitted to the server via an API.

[1748] User

[1749] The user receives a notification that the referenced document has been updated and checks the proposed revisions. If the proposed revisions are deemed appropriate, the user approves them via their terminal. The automatically updated document can then be reviewed and reflected in the business.

[1750] Hardware and software used

[1751] The specific implementation of the system uses the following hardware and software:

[1752] Server: A physical or virtual server with a high-performance processor (e.g., AWS EC2, Google Cloud Compute Engine)

[1753] Natural language processing libraries: spaCy and NLTK implemented in Python

[1754] Facial expression and voice analysis: Camera module, microphone, image analysis library such as OpenCV, and voice analysis library

[1755] Notification systems: SMTP protocol, Firebase Cloud Messaging (FCM), WebSocket

[1756] Specific examples

[1757] For example, consider a case where a new health guideline is added to a company's guideline document.

[1758] 1. Obtaining the referenced document: The server periodically accesses the "referenced URL" and obtains new guideline documents.

[1759] 2. Analysis of update content: The server compares the old and new guideline documents to identify changes. It analyzes the addition of new health guidelines and extracts the differences.

[1760] 3. Generate amendments: The server generates amendments such as "Add the following new health guideline to Chapter 2: 'Employees are encouraged to undergo regular health checks.'"

[1761] 4. Using the emotion engine: When the user receives the proposed revision notification, the emotion engine recognizes that the user is in a fatigued state.

[1762] 5. Notification content adjustment: The emotion engine will shorten the notification content and add encouraging messages such as, "Good job, please check the new health guidelines."

[1763] 6. Notify the user: The server will send a notification of the proposed fix to the user's email and display a pop-up notification on the device.

[1764] 7. Approval of proposed amendment: The user checks the notification via their device and clicks the approval button.

[1765] 8. Automatic document update: After the server receives approval, it automatically updates the guideline document and displays the latest document on the terminal.

[1766] Prompt Sentence Examples

[1767] Using a concrete example of this system, please explain in detail the process by which users actually review and approve proposed revisions.

[1768] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1769] Step 1: Check for and obtain updates to the referenced documents

[1770] The server periodically retrieves the referenced documents based on a pre-registered URL list. The input is a list of URLs, and the output is the most recent retrieved document. Specifically, it sends an HTTP request to download data from news sites on the Internet or an internal document management system. This process is scheduled, for example, every day at 9:00 AM.

[1771] Step 2: Analyze the updates

[1772] The server analyzes the acquired new and old document data using natural language processing technology. The input is the new document and the old document, and the output is an analysis result that identifies the changes. Specifically, it uses a text comparison algorithm to list added, deleted, and modified information. It uses Python NLP libraries spaCy and NLTK.

[1773] Step 3: Generate correction suggestions

[1774] The server generates specific revision suggestions based on the analysis results. The input is the analyzed changes, and the output is the revision suggestions. Specific actions include creating a revision suggestion with detailed instructions, such as "add new statistics to the third paragraph of the document." The revision suggestions can be formatted in Markdown or HTML.

[1775] Step 4: Sending notifications

[1776] The server notifies the user of the generated proposed corrections. The input is the proposed corrections, and the output is the notification email or popup notification. Specifically, it sends a notification to the user's email address using the SMTP protocol, or displays a popup notification in real time using Firebase Cloud Messaging (FCM) or WebSocket.

[1777] Step 5: Emotional Engine Adjustment

[1778] The emotion engine recognizes the emotional state of the user who received the notification in real time and adjusts the notification content accordingly. The input is the user's facial expression data and voice data, and the output is the adjusted notification content. Specifically, it analyzes facial expression data captured by the camera and voice data acquired by the microphone, and if the user is tired, it simplifies the notification text and adds an encouraging message.

[1779] Step 6: Approval of amendments

[1780] The user uses the device to check the proposed revision and take action to approve or reject it. The input is the notified revision proposal, and the output is the user's action to approve or reject it. Specifically, the user views the revision proposal through the device interface (web browser or mobile app) and clicks the approve or reject button.

[1781] Step 7: Automatically update documents

[1782] The server automatically updates the user document after receiving approval from the user. The input is the user's approved revision proposal, and the output is the updated user document. Specifically, the original document is edited based on the approved revision proposal to reflect the updates. The updated document is committed to a version control system (e.g., Git). After the update is complete, the latest document is displayed on the terminal.

[1783] (Application example 2)

[1784] 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."

[1785] In modern factories, changes to production processes and operation manuals occur frequently, requiring rapid response. However, quickly updating the workplace with updated information is extremely cumbersome and labor-intensive. In particular, issuing notifications without considering employees' emotions and states can lead to reduced efficiency. To improve this situation, there is a need for a system that automatically checks and analyzes updates to referenced documents, maintains the latest information on user documents, and recognizes users' emotions to provide appropriate notifications.

[1786] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1787] In this invention, the server includes means for periodically checking for updates to the referenced document, means for analyzing the updates to the referenced document, means for generating proposed revisions to the user document based on the analysis results, means for notifying the user of the generated proposed revisions, means for receiving approval of the proposed revisions from the user, means for automatically updating the user document based on the approval, means for recognizing the user's emotions, and means for adjusting the notification content based on the emotions. This enables efficient updates of the latest information on production processes and manuals in the factory and personalized notifications according to the user's emotional state.

[1788] A "referenced document" is a document that the system periodically checks and analyzes for updates.

[1789] "Means for analyzing update content" refers to the processes and techniques for extracting changes in the source document and understanding their content.

[1790] A "user document" is a document that is modified based on the updated content of the referencing document.

[1791] A "proposed revision" is a specific change proposed to a user document to reflect an update to a referenced document.

[1792] "Means of notification" refers to the interface or technology used to notify the user of the proposed revisions.

[1793] "Means for receiving approval" refers to the interface or process by which a user reviews the proposed revision and communicates approval or rejection to the system.

[1794] "Automatic updating means" refers to the process or technology for automatically updating user documents with the latest information upon user approval.

[1795] "Means for recognizing emotions" refers to techniques and processes for identifying a user's emotional state and obtaining that information.

[1796] "Means for adjusting notification content" refers to techniques or processes for changing the content or format of notification text depending on the user's emotional state.

[1797] This invention is a system that automatically updates the latest information on production processes and operation manuals in factories, recognizes the user's emotions, and notifies them appropriately. This system works in cooperation with four parties: a server, a terminal, a user, and an emotion engine.

[1798] System configuration

[1799] The system of the present invention includes the following configuration.

[1800] 1. Server

[1801] The server periodically checks for updates to the referencing document. Specifically, the server periodically retrieves the referencing document from a pre-registered URL list and analyzes its contents. The analysis is performed using natural language processing (NLP) technology. When the referencing document is updated, the server analyzes the update content and generates specific suggested modifications to the user document. Suggested modifications include adding, correcting, or deleting text. After generating the suggested modifications, the server sends a notification to the user. This notification includes the content of the suggested modifications and their background. As a specific example, if a factory safety manual has been updated, the server will notify the user that "a new safety procedure has been added to Chapter 2."

[1802] 2. Emotion Engine

[1803] The emotion engine recognizes the user's emotions in real time. It uses facial expression recognition and voice analysis technology to identify multiple emotional states, such as joy, sadness, surprise, and anger. It adjusts the content and format of notifications based on the user's emotional state. For example, if the user is tired, it shortens the notification and adds an encouraging message. The specific software used is "EmotionRecognition."

[1804] 3. Terminal

[1805] A terminal is a device through which a user receives notifications. The terminal includes an interface that displays a mail client and pop-up notifications. The user uses the terminal to check the contents of the proposed amendment and take action to approve or reject it. The approved amendment is transmitted to the server. After the user approves it, the terminal displays the updated document, allowing the user to confirm that the latest information is reflected. For example, the terminal displays a pop-up notification saying, "Please review the new safety procedures."

[1806] 4. Users

[1807] The user receives a notification that the referenced document has been updated and checks the proposed revisions. If the proposed revisions are deemed appropriate, the user takes action to approve them. This is done through the terminal interface. After approval, the user checks the automatically updated document and incorporates it into their work.

[1808] Specific examples

[1809] For example, if a new health guideline is added to a factory safety manual, the server detects the change and generates a correction suggestion. If the emotion engine detects the user's fatigue, it shortens the notification to "Thank you for your hard work. Please check the new health guideline." An example of a prompt is as follows:

[1810] Example prompt sentence:

[1811] Input to the generative AI model:

[1812] "A new procedure has been added to the factory safety manual. Analyze the update and generate specific suggested fixes. Also, use emotion recognition to tailor notification messages. If the user is feeling fatigued, keep the message brief."

[1813] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1814] Step 1:

[1815] The server checks for updates to the referencing document.

[1816] Input: A list of pre-registered URLs.

[1817] The server periodically accesses the list of URLs to retrieve the latest document content, for example by downloading data from a news feed or an internal document management system.

[1818] Output: The latest retrieved document content.

[1819] Step 2:

[1820] The server parses the updates.

[1821] Input: The latest document content obtained in step 1.

[1822] The server uses natural language processing (NLP) technology to compare the old and new data and extract changes.

[1823] Specifically, it uses BeautifulSoup to parse the HTML, and spacy to tokenize the document and identify additions, modifications, and deletions of text.

[1824] Output: A list of changes.

[1825] Step 3:

[1826] The server generates a revision suggestion.

[1827] Input: The list of changes identified in step 2.

[1828] The server automatically generates specific suggested revisions to the user's document based on the changes.

[1829] For example, include specific revisions such as "Add a new procedure to the third paragraph."

[1830] Output: The generated correction suggestions.

[1831] Step 4:

[1832] The server will notify you of the proposed revision.

[1833] Input: The proposed fix generated in step 3.

[1834] The server will send suggested revisions to the user via email or pop-up notification.

[1835] Specifically, it sends emails using the SMTP protocol and provides real-time notifications using WebSocket.

[1836] Output: Notification sent to the user.

[1837] Step 5:

[1838] The emotion engine recognizes the user's emotions.

[1839] Input: Camera video and audio data when the user receives a notification.

[1840] The emotion engine uses facial expression recognition and voice analysis techniques to identify the user's emotional state.

[1841] Specifically, it uses EmotionRecognition software to analyze the user's emotions in real time.

[1842] Output: The perceived emotional state of the user.

[1843] Step 6:

[1844] The server adjusts the notification content based on the emotional state.

[1845] Input: The user's emotional state recognized in step 5, and the notification sent in step 4.

[1846] The server fine-tunes the content and format of the notification message depending on the user's emotions.

[1847] For example, if the user is tired, change the message to something more concise like "Great work, check out the new steps."

[1848] Output: The adjusted notification message.

[1849] Step 7:

[1850] The terminal receives the user's approval.

[1851] Input: The notification message adjusted in step 6.

[1852] The user can review the notification through the device interface and accept or reject the proposed changes.

[1853] Specifically, approval information is sent to the server by clicking a UI button on the terminal.

[1854] Output: User approval or denial information.

[1855] Step 8:

[1856] The server automatically updates the user document.

[1857] Input: User approval information received in step 7 and correction proposal generated in step 3.

[1858] The server automatically updates the user document based on the approved amendments.

[1859] For example, updating a MySQL database to reflect the latest information in a document management system.

[1860] Output: The latest updated user documentation.

[1861] 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.

[1862] 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.

[1863] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1864] 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.

[1865] 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.

[1866] 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.

[1867] 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).

[1868] 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.

[1869] 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."

[1870] 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.

[1871] 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).

[1872] 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.

[1873] 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.

[1874] 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.

[1875] 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.

[1876] 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.

[1877] 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.

[1878] 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.

[1879] 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.

[1880] 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.

[1881] 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.

[1882] The following is further disclosed regarding the above embodiment.

[1883] (Claim 1)

[1884] A means of regularly checking for updates to the referenced documents;

[1885] means for analyzing the update content of the referencing document;

[1886] means for generating suggested modifications to the user document based on the analysis results;

[1887] means for notifying a user of the generated revision proposal;

[1888] means for receiving approval of the proposed revision from the user;

[1889] means for automatically updating user documents based on said approval;

[1890] A system including:

[1891] (Claim 2)

[1892] 10. The system of claim 1, wherein the system tracks both internet sources and internal documents.

[1893] (Claim 3)

[1894] The system according to claim 1, wherein the update content of the referenced document is analyzed using natural language processing technology.

[1895] "Example 1"

[1896] (Claim 1)

[1897] A means of regularly checking for updates to the referenced documents;

[1898] means for obtaining the latest content of the referencing document;

[1899] means for analyzing the acquired latest content and comparing and extracting updated content;

[1900] means for generating specific suggested modifications to the user document based on the analysis results;

[1901] means for notifying a user of the generated revision proposal;

[1902] means for receiving approval of the proposed revision from the user;

[1903] means for automatically updating user documents based on said approval;

[1904] A system including:

[1905] (Claim 2)

[1906] 10. The system of claim 1, wherein the system tracks both internet sources and internal documents.

[1907] (Claim 3)

[1908] The system according to claim 1 analyzes the update content of the referenced document using natural language processing technology, and generates a revision proposal by inputting a prompt sentence into the generative AI model based on the analysis results.

[1909] "Application Example 1"

[1910] (Claim 1)

[1911] A means of regularly checking for updates to the referenced documents;

[1912] means for analyzing the update content of the referencing document;

[1913] means for generating suggested modifications to the user document based on the analysis results;

[1914] means for notifying a user of the generated revision proposal;

[1915] means for receiving approval of the proposed revision from the user;

[1916] means for automatically updating user documents based on said approval;

[1917] Measures targeting industrial machine operating manuals and work procedures;

[1918] means for displaying the proposed revisions through a user interface for user approval;

[1919] If the proposed amendments are approved, they will provide a means to add new operating procedures and safety guidelines to the manual;

[1920] A system including:

[1921] (Claim 2)

[1922] 10. The system of claim 1, wherein the system tracks both internet sources and internal documents to automatically update an industrial machine operating manual.

[1923] (Claim 3)

[1924] The system according to claim 1, which uses natural language processing technology to analyze the updated content of the referenced document and generate suggested revisions to the operation manual or work procedure manual of industrial machinery.

[1925] "Example 2: Combining Emotion Engines"

[1926] (Claim 1)

[1927] A means of regularly checking for updates to the referenced documents;

[1928] means for analyzing the update content of the referencing document;

[1929] means for generating suggested modifications to the user document based on the analysis results;

[1930] means for notifying a user of the generated revision proposal;

[1931] A means for recognizing the user's emotional state in real time and adjusting the notification content;

[1932] means for receiving approval of the proposed revision from the user;

[1933] means for automatically updating user documents based on said approval;

[1934] A system including:

[1935] (Claim 2)

[1936] 10. The system of claim 1, wherein the system tracks both internet sources and internal documents.

[1937] (Claim 3)

[1938] The system according to claim 1, wherein the update content of the referenced document is analyzed using natural language processing technology.

[1939] "Application example 2 when combining emotion engines"

[1940] (Claim 1)

[1941] A means of regularly checking for updates to the referenced documents;

[1942] means for analyzing the update content of the referencing document;

[1943] means for generating suggested modifications to the user document based on the analysis results;

[1944] means for notifying a user of the generated revision proposal;

[1945] means for receiving approval of the proposed revision from the user;

[1946] means for automatically updating user documents based on said approval;

[1947] means for recognizing a user's emotion;

[1948] means for adjusting notification content based on the emotion;

[1949] A system including:

[1950] (Claim 2)

[1951] 10. The system of claim 1, wherein the system tracks both internet sources and internal documents.

[1952] (Claim 3)

[1953] The system according to claim 1, wherein the update content of the referenced document is analyzed using natural language processing technology. [Explanation of symbols]

[1954] 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 of regularly checking for updates to the referenced documents; means for analyzing the update content of the referencing document; means for generating suggested modifications to the user document based on the analysis results; means for notifying a user of the generated revision proposal; means for receiving approval of the proposed revision from the user; means for automatically updating user documents based on said approval; A system including:

2. 10. The system of claim 1, wherein the system tracks both internet sources and internal documents.

3. The system according to claim 1, wherein the update content of the referencing document is analyzed using natural language processing technology.

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