system

Abstract

We provide the system. [Solution] A means by which the user inputs the creation and its purpose, The server analyzes the input information and identifies the necessary legal verification items, For each legal verification item where a server has been identified, a means of providing the corresponding verification contact point and procedure will be presented. A means for users to provide feedback on the results of legal review, The server has means for receiving, storing, and updating the aforementioned feedback, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern times, when creating a website or tool, multiple legal confirmations are required. However, these legal confirmations are usually distributed among multiple departments or windows, resulting in problems such as cumbersome confirmation work, time-consuming processes, and a high likelihood of errors. Such decentralized confirmation procedures are significant factors that can greatly reduce efficiency and accuracy, especially in large-scale projects. Additionally, it is difficult to grasp and manage all confirmations at once, imposing a heavy burden on users and stakeholders.

Means for Solving the Problems

[0005] To solve the aforementioned problems, this invention provides a system. Specifically, it includes means for the user to input a creation and its purpose, and means for a server to analyze the input information and identify the necessary legal verification items. Furthermore, the server provides means for presenting the corresponding verification window or procedure for each identified legal verification item, and means for the user to provide feedback on the legal verification results. Means for receiving, saving, and updating the feedback are also included. By using this system, it becomes possible to centrally manage and efficiently process multiple legal verifications. In addition, by further including display means for the server to guide users through specific verification procedures and necessary documents according to the legal verification items, and means for the user to manage the verification status and track progress within the system, the efficiency and accuracy of the verification work can be improved.

[0006] A "user" refers to an individual or organization that accesses the system and enters its creations and purposes.

[0007] A "server" refers to a computer system that receives, analyzes, and processes information sent by users, identifies necessary legal verification items, and presents corresponding verification procedures.

[0008] "Created works" refer to things that users intend to create, such as websites or tools.

[0009] "Purpose" refers to the primary reason or use for which a user will use the created work.

[0010] "Legal review items" refer to the legal requirements and regulations that users should review in accordance with their creations and their purpose.

[0011] A "confirmation contact point" refers to the contact information for the department or external organization responsible for conducting confirmations regarding the specified legal confirmation items.

[0012] "Procedure" refers to the necessary verification work and steps for each legal verification item.

[0013] "Feedback" refers to the act or information that a user returns to the system, such as confirmation results or additional information.

[0014] "Saving" refers to the process of recording the feedback the system receives.

[0015] "Update" refers to the process by which a system changes or modifies its status or information based on stored data. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the language used in the following description will be explained.

[0019] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] This invention is a system that allows users to input a creation and its purpose, and then efficiently perform the necessary legal checks based on that input. This system analyzes the input information and centrally manages multiple checkpoints and procedures, thereby reducing the burden on the user and improving the efficiency of the check process.

[0038] System Overview

[0039] This system includes a server that analyzes information provided by the user, a terminal where the user inputs information, and means for managing feedback.

[0040] Program processing

[0041] 1. The user enters information into the input form.

[0042] The user accesses a web form and enters the creation (e.g., a website) and its purpose (e.g., marketing).

[0043] 2. The server receives and analyzes the input information.

[0044] The server receives and analyzes information sent by the user. Based on the input information, it identifies the necessary legal verification items. For example, if the user enters "Website creation, purpose is marketing," then verification of the Act against Unjustifiable Premiums and Misleading Representations, privacy policy, and terms of service will be required.

[0045] 3. The server generates a legal checklist.

[0046] The server generates a legal checklist based on the analysis results, listing the corresponding contact point and procedure for each item. For example, it displays "Confirm with the Marketing Department" for the Act against Unjustifiable Premiums and Misleading Representations, "Confirm with the Legal Department" for the Privacy Policy, and "Confirm with the Legal Department regarding the content" for the content of the document.

[0047] 4. Provide the user with confirmation steps.

[0048] The server generates a legal checklist and procedures, which are then displayed on the user's terminal. This allows the user to review the specific steps and required documents for each check item and take action themselves.

[0049] 5. The user performs the verification.

[0050] The user will follow the instructions provided and carry out the necessary verification procedures at each stage. For example, the user will contact the marketing department to confirm compliance with the Act against Unjustifiable Premiums and Misleading Representations.

[0051] 6. The user provides feedback on the verification results.

[0052] The user enters their results into a form to provide feedback to the system and sends it to the server.

[0053] 7. The server saves and updates the results.

[0054] The server saves the confirmation results received from the user to a database and updates the status on the system. This allows the user to track the progress of the confirmation process in real time.

[0055] Specific example

[0056] 1. Example: Confirmation under the Act against Unjustifiable Premiums and Misleading Representations

[0057] User input: "Website creation, purpose is marketing."

[0058] Server analysis: The server determined that "confirmation regarding the Act against Unjustifiable Premiums and Misleading Representations is required."

[0059] Server generation list: "Act against Unjustifiable Premiums and Misleading Representations: Confirm with Marketing Department" "Content of Description: Confirm with Legal Department" "Internal Confirmation: Confirm with ISC"

[0060] User verification: The user contacts the marketing and legal departments to obtain the necessary verifications.

[0061] Result Feedback: The user enters the results into the system.

[0062] Server save and display: The server saves the results to the database and displays a confirmation completion message to the user.

[0063] 2. Example: Checking the Privacy Policy

[0064] User input: "I'm creating a mobile app; the purpose is data collection."

[0065] Server analysis: The server determined that "confirmation of the privacy policy is required."

[0066] Server generation list: "Privacy Policy: Confirm with Legal Department" "Data Collection Details: Confirm with Data Department"

[0067] User verification: The user contacts the legal department and the data department to obtain the necessary verifications.

[0068] Result Feedback: The user enters the results into the system.

[0069] Server save and display: The server saves the results to the database and displays a confirmation completion message to the user.

[0070] This system allows users to centrally manage and efficiently process multiple legal verification procedures. This significantly improves the efficiency and accuracy of the verification process.

[0071] The following describes the processing flow.

[0072] Step 1:

[0073] The user accesses the input form. Through a web browser, the user accesses the system's input form and enters the creation (e.g., website) and its purpose (e.g., marketing).

[0074] Step 2:

[0075] The user enters information. The user fills in the necessary information in the input form, such as "Development = Website" and "Purpose = Marketing."

[0076] Step 3:

[0077] The user clicks the submit button. When the user clicks the submit button, the entered information is sent to the server.

[0078] Step 4:

[0079] The server receives the input information. The server receives the information sent by the user and prepares it for analysis.

[0080] Step 5:

[0081] The server analyzes the input information. The server uses a natural language processing algorithm to analyze the received information. Based on the analysis results, it identifies the necessary legal compliance items (e.g., the Act against Unjustifiable Premiums and Misleading Representations, privacy policy, etc.).

[0082] Step 6:

[0083] The server generates a legal checklist. Based on the analysis results, the server generates a list of necessary legal check items. For each item, it lists the corresponding contact point and procedure.

[0084] Step 7:

[0085] The server displays a legal confirmation list. The server displays the generated legal confirmation list on the user's terminal. The list includes details of each confirmation contact and procedure.

[0086] Step 8:

[0087] The user performs the verification procedure. Based on the instructions provided by the server, the user completes the necessary verification procedures at each relevant contact point. For example, they might request the marketing department to verify compliance with the Act against Unjustifiable Premiums and Misleading Representations.

[0088] Step 9:

[0089] The user collects the verification results. The user receives feedback from the verification channel and prepares to return it to the system.

[0090] Step 10:

[0091] The user provides feedback on the verification results. The user enters the verification results into the feedback form and submits it to the system.

[0092] Step 11:

[0093] The server receives the confirmation result. The server receives the confirmation result sent by the user and proceeds to the next step.

[0094] Step 12:

[0095] The server saves the verification results. The server saves the verification results to a database and updates that information to the latest version.

[0096] Step 13:

[0097] The server displays update information. The server updates the user's confirmation status and displays the progress on the terminal. The user receives a confirmation message and information about the next steps.

[0098] In this way, users can efficiently manage various legal checks and complete the necessary procedures.

[0099] (Example 1)

[0100] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0101] Traditional legal verification processes are complex and time-consuming, requiring the individual management of multiple verification channels and procedures. Maintaining accuracy and efficiency is also difficult. This is especially true when legal regulations are diverse and require coordination across various departments. An efficient, centralized system is needed to address these problems.

[0102] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0103] In this invention, the server includes means for the user to input a creation and its purpose; means for the server to receive and analyze the input information and identify necessary legal confirmation items; means for the server to generate a legal confirmation list based on the analysis results using a generation AI model; means for the server to list the corresponding confirmation contacts and procedures for each identified legal confirmation item; means for the user to display the confirmation procedure and provide feedback on the legal confirmation results; and means for the server to receive, save, and update the feedback. This makes it possible to efficiently centrally manage legal confirmation procedures and track the progress of confirmation work in real time.

[0104] A "user" is anyone who accesses this system and enters information about their creations and their purpose.

[0105] A "server" is a device that receives and analyzes information sent by users, identifies necessary legal verification items, and generates and manages legal verification lists.

[0106] "Created works" refers to deliverables such as websites and mobile applications created by users.

[0107] "Purpose" refers to the role or use that the creation is intended to fulfill, and includes, for example, marketing and data collection.

[0108] "Legal confirmation items" refer to items related to the creation of a document that require legal confirmation, and specifically include the Premiums and Representations Act and privacy policies.

[0109] A "generative AI model" is a type of artificial intelligence used to analyze input information and identify legal compliance items.

[0110] The "Legal Confirmation List" is a list of the corresponding confirmation contacts and procedures for each legal confirmation item, generated by the server based on the analysis results.

[0111] A "confirmation desk" refers to the department or person responsible for confirming legal compliance items.

[0112] "Procedures" refer to the specific actions and tasks required in response to legal verification items.

[0113] "Feedback" refers to the user submitting legal review results to the system.

[0114] Modes for carrying out the invention

[0115] This invention is a system that allows users to input a creation and its purpose, and then analyzes that input information to efficiently perform necessary legal checks. By analyzing the input information and centrally managing multiple checkpoints and procedures, this system reduces the burden on the user and improves the efficiency of the check process.

[0116] System Configuration

[0117] This system consists mainly of the following elements.

[0118] 1. A terminal where the user enters information.

[0119] 2. A server that receives and analyzes information sent by the user.

[0120] 3. Generative AI models within the server

[0121] 4. Legal confirmation list generated on the server

[0122] 5. Means for users to provide feedback

[0123] 6. Database to receive, store, and update feedback

[0124] The user is using a terminal to enter information.

[0125] Users access a web form and enter information about their creation (e.g., a website) and its purpose (e.g., marketing). This data is then sent to the system.

[0126] The server receives and analyzes the input information.

[0127] The server receives information sent by the user. It then analyzes the input information using a generation AI model and identifies the necessary legal checks based on the entered data. For example, if the user enters "Website creation, purpose is marketing," the server will determine that checks on the Premiums and Representations Act and the privacy policy are necessary.

[0128] Legal confirmation list generated on the server

[0129] The server generates a legal checklist based on the analysis results, listing the necessary contact points and procedures. For example, it includes specific instructions such as "Confirm with the Marketing Department" for the Premiums and Representations Act and "Confirm with the Legal Department" for the Privacy Policy.

[0130] Provide the user with a verification procedure.

[0131] The server displays the generated legal checklist on the user's terminal. The user reviews it and follows the instructions to perform the necessary legal checks. Specifically, they request the marketing department to review the Premiums and Representations Act and the legal department to review the privacy policy.

[0132] The user provides feedback on the verification results.

[0133] The user enters the results into a dedicated form within the system to provide feedback on the verification process. This information is then sent to the server.

[0134] The server saves and updates the results.

[0135] The server saves the confirmation results received from the user to the database and updates the status on the system. This allows the user to track the progress of the confirmation process in real time.

[0136] Specific example

[0137] Example 1: Confirmation of the Premiums and Representations Act

[0138] User input: "Website creation, purpose is marketing."

[0139] Server analysis: The server determines that "confirmation regarding the Premiums and Representations Act is required."

[0140] Server generation list: "Act against Unjustifiable Premiums and Misleading Representations: Confirm with Marketing Department" "Contents of Description: Confirm with Legal Department"

[0141] User verification: The user contacts the marketing and legal departments to complete any necessary verifications.

[0142] Result Feedback: The user enters the results into the system.

[0143] Server save and display: The server saves the results to the database and displays a confirmation message to the user.

[0144] Example 2: Checking the Privacy Policy

[0145] User input: "I'm creating a mobile app; the purpose is data collection."

[0146] Server analysis: The server determines that "confirmation of the privacy policy is required."

[0147] Server generation list: "Privacy Policy: Confirm with Legal Department" "Data Collection Details: Confirm with Data Department"

[0148] User verification: The user contacts the legal department and the data department to perform the necessary verifications.

[0149] Result Feedback: The user enters the results into the system.

[0150] Server save and display: The server saves the results to the database and displays a confirmation message to the user.

[0151] This system allows users to centrally manage and efficiently process multiple legal verification procedures. This significantly improves the efficiency and accuracy of the verification process.

[0152] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0153] Step 1:

[0154] A user accesses a web form and enters information about their creation (e.g., a website) and its purpose (e.g., marketing). The entered information is sent from the user's device to the server. This input information becomes the basis for subsequent processing.

[0155] Step 2:

[0156] The server receives information sent by the user. After receiving the information, the server analyzes the input data using a generative AI model. The information extracted through this analysis is used to identify subsequent legal review items. Specifically, it performs natural language processing to understand the intent of the user's input.

[0157] Step 3:

[0158] The server identifies the necessary legal checks based on the analysis results. For example, if the analysis indicates "website creation, purpose is marketing," the server will identify the need to check the Premiums and Representations Act and the privacy policy. The output of this step is a list of the specific legal items that need to be checked.

[0159] Step 4:

[0160] For each legal verification item identified by the server, a list of the corresponding verification contacts and procedures is created. This list includes instructions on which department to contact for each item. For example, "Confirm the Premiums and Representations Act with the Marketing Department" or "Confirm the Privacy Policy with the Legal Department."

[0161] Step 5:

[0162] The server generates a legal checklist, which is then displayed on the user's terminal. By reviewing this list, the user can learn about the necessary procedures. The output specifically shows the checklist items, their corresponding contact points, and detailed steps.

[0163] Step 6:

[0164] The user will conduct legal checks following the provided procedures. The user will contact each department based on the list and request the necessary checks. For example, the user might request the marketing department to check the Premiums and Representations Act and the legal department to check the privacy policy.

[0165] Step 7:

[0166] The user enters the results of the legal review into a dedicated form within the system to provide feedback. This information is then sent back to the server. The results entered by the user become the input data for this step.

[0167] Step 8:

[0168] The server saves the confirmation results received from the user to a database. Furthermore, it updates the status of the confirmation items and displays the progress on the system. This allows users to track the progress of their confirmation work in real time.

[0169] This series of processing steps allows users to efficiently complete legal verification procedures. Furthermore, the ability to manage the progress of the verification process within the system significantly improves the efficiency and accuracy of the verification work.

[0170] (Application Example 1)

[0171] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0172] Online platforms such as virtual stores require the efficient management of numerous legal verification items and the rapid coordination of verification processes with multiple contact points. Furthermore, tracking the progress and deadlines of these verification processes is often difficult, placing a significant burden on users. A comprehensive system is needed to address these issues.

[0173] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0174] In this invention, the server includes means for the user to input a creation and its purpose; means for the server to analyze the input information and identify necessary legal verification items; means for the server to present corresponding verification contacts and procedures for each identified legal verification item; means for the user to provide feedback on the legal verification results; means for the server to receive, save, and update the feedback; means for tracking the progress of the legal verification work; and means for notifying the user of the deadline and progress of the verification procedures. This enables the user to efficiently carry out legal verification work and appropriately manage progress and deadlines.

[0175] A "user" is an end-user who uses the system to input creations and their purposes.

[0176] "Created works" refer to specific projects, products, or services that users input.

[0177] "Purpose" refers to the achievement goals or intentions related to the creation.

[0178] "Means" refers to methods or mechanisms for performing a specific function or role.

[0179] A "server" refers to a computer system that receives, analyzes, stores, and manages information entered by users.

[0180] "Legal confirmation items" refer to legal confirmation matters necessary in relation to the created document and its purpose.

[0181] A "confirmation desk" refers to the contact point or department necessary to address specific legal confirmation items.

[0182] "Procedure" refers to the specific actions and steps required to confirm and approve certain legal verification items.

[0183] "Feedback" refers to the act of reporting the results and progress of legal checks performed by users to the server.

[0184] "Updating" refers to the act of updating data to the latest state based on information received by the server.

[0185] "Progress" refers to the status of the legal review process.

[0186] "Notifications" refer to alerts or messages that inform users about deadlines and progress of verification procedures.

[0187] This invention is a system for efficiently performing legal verification work. The system is designed so that the user inputs a creation and its purpose, and the server then performs the necessary legal verification based on that input. The following details specific embodiments of this system.

[0188] Hardware and software configuration

[0189] Hardware:

[0190] Server: Cloud servers such as AWS® EC2 are used to process data, including receiving, analyzing, storing, and updating it.

[0191] User terminal: A device such as a smartphone, PC, or tablet used by the user to input information and check the results.

[0192] software:

[0193] Framework: Implement the server analysis module using Python.

[0194] Database: Legal review results and progress data are stored using MySQL (registered trademark).

[0195] Frontend: Build the user interface using React.js.

[0196] Data processing and computation

[0197] Data entry and analysis:

[0198] User Terminal: Users enter their creation and its purpose through a web form. For example, they might enter "Type of virtual store: Health food sales, Purpose: Promotional campaign."

[0199] Server: Analyzes the received input data and identifies the necessary legal verification items. Based on the analysis results, it generates a verification list and displays it to the user.

[0200] Verification steps and feedback:

[0201] User: Follow the provided verification steps, complete the necessary verification procedures, and enter the results into the feedback form.

[0202] Server: Receives feedback and stores it in the database. Updates progress in real time and notifies the user.

[0203] Specific example

[0204] User input: "Virtual store type: Health food sales, Purpose: Promotional campaign"

[0205] Analysis results: The server determined that it was necessary to "check the Premiums and Representations Act" and "check the Privacy Policy".

[0206] Verification procedure: The server will provide users with specific contact points and procedures for "confirmation regarding the Premiums and Representations Act" and "confirmation regarding the Privacy Policy."

[0207] Feedback: The user enters the confirmation result, and the server saves the progress to the database.

[0208] Notification: The server sends alerts to the user regarding legal review deadlines and progress.

[0209] Example of a prompt

[0210] Virtual store type: Health food sales, Purpose: Promotional campaign

[0211] This system allows users to efficiently carry out legal review work and properly manage progress and deadlines.

[0212] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0213] Step 1:

[0214] The user enters information. The user uses a device to access a web form and enters information about the creation (e.g., a virtual store) and its purpose (e.g., a promotional campaign). This entered information is sent to the server.

[0215] Input: The user enters "Virtual store type: Health food sales, Purpose: Promotional campaign" into the input form.

[0216] Output: User input data is sent to the server.

[0217] Specific operation: The user accesses a web form from a device such as a smartphone or PC, enters the required information, and presses the submit button. This information is sent to the server.

[0218] Step 2:

[0219] The server analyzes the input information. The server analyzes the received input information and identifies the necessary legal verification items. A generative AI model can be used for this analysis.

[0220] Input: The server receives user input data.

[0221] Output: The server identifies the legal items that need to be checked (e.g., "Check the Premiums and Representations Act," "Check the Privacy Policy").

[0222] Specific operation: The server passes the received data to the analysis module, which uses the generated AI model to identify the necessary legal verification items.

[0223] Step 3:

[0224] The server generates a legal confirmation list. Based on the analysis results, the server lists the corresponding confirmation contacts and procedures for each required legal confirmation item.

[0225] Input: Legal verification items identified by the server.

[0226] Output: The server generates a confirmation list and displays it on the user's terminal (e.g., "Confirmation of Premiums and Representations Act: Contact Legal Department", "Confirmation of Privacy Policy: Contact Data Department").

[0227] Specific operation: The server identifies the contact point and procedure corresponding to each item based on the legal verification items, and generates a verification list.

[0228] Step 4:

[0229] The user performs the verification procedure. The user follows the provided verification steps and completes the necessary verification procedures.

[0230] Input: Confirmation list displayed from the server.

[0231] Output: The user provides feedback on the results for each verification item (e.g., "Confirmation of Premiums and Representations Act: Completed," "Confirmation of Privacy Policy: Pending").

[0232] Specific actions: The user contacts the relevant departments, such as the legal department or data department, completes the necessary verification procedures, and enters the results into the system.

[0233] Step 5:

[0234] The server receives, stores, and updates feedback. The server receives user feedback, stores it in the database, and updates the system status.

[0235] Input: Confirmation result entered by the user.

[0236] Output: The server saves the verification results to the database and updates the system status.

[0237] Specific operation: The server receives feedback data sent by the user, saves it to the database, and updates the confirmation status in real time.

[0238] Step 6:

[0239] The server tracks progress and provides notifications. The server periodically tracks the progress of legal review work and sends necessary notifications to the user (e.g., deadlines for review procedures, progress status).

[0240] Input: Updated confirmation status.

[0241] Output: Sends notifications to the user's terminal regarding progress and deadlines.

[0242] Specific operation: The server periodically checks the database information, generates notifications based on progress and deadlines for verification procedures, and sends alerts to the user.

[0243] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0244] This invention is a system that allows users to input a creation and its purpose, and then efficiently performs the necessary legal checks based on that input. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides a more flexible and adaptable check procedure.

[0245] System Overview

[0246] This system includes a server that analyzes information provided by the user, a terminal where the user inputs information, an emotion engine that recognizes the user's emotional state, and means for managing feedback.

[0247] Program processing

[0248] 1. The user enters information into the input form.

[0249] The user accesses a web form and enters the creation (e.g., a website) and its purpose (e.g., marketing).

[0250] 2. The server receives and analyzes the input information.

[0251] The server receives and analyzes information sent by the user. Based on the input information, it identifies necessary legal compliance items (e.g., the Act against Unjustifiable Premiums and Misleading Representations, privacy policy, etc.).

[0252] 3. The emotion engine analyzes the user's emotions.

[0253] An emotion engine embedded in the server analyzes the user's emotional state from their input information and actions. This allows it to recognize emotions such as stress and confusion.

[0254] 4. The server generates a legal checklist.

[0255] The server generates a list of necessary legal verification items based on the analysis results. For each item, it lists the corresponding verification contacts and procedures.

[0256] 5. The emotion engine adjusts the procedural methods.

[0257] The emotion engine adjusts the priority and method of procedures based on the user's emotional state. For example, if the user is stressed, it may simplify procedures or send reminders and support messages.

[0258] 6. The server displays the legal confirmation list.

[0259] The server generates a legal review list, which is then displayed on the user's terminal. Adjustments made by the emotion engine are reflected in this list.

[0260] 7. The user completes the verification process.

[0261] The user will follow the instructions provided and complete the necessary verification procedures at each relevant department. For example, they might request the marketing department to verify compliance with the Act against Unjustifiable Premiums and Misleading Representations.

[0262] 8. The user provides feedback on the verification results.

[0263] The user enters their results into a form to provide feedback to the system and sends it to the server.

[0264] 9. The server receives the confirmation result.

[0265] The server receives the confirmation result sent by the user and proceeds to the next step.

[0266] 10. The server saves and updates the verification results.

[0267] The server saves the verification results to a database and updates that information to the latest version.

[0268] 11. The server displays update information.

[0269] The server updates the user's verification status and displays the progress on the terminal. The user receives a message confirming verification and information about the next steps.

[0270] Specific example

[0271] 1. Verification of the Act against Unjustifiable Premiums and Misleading Representations using an emotional engine.

[0272] User input: "Website creation, purpose is marketing."

[0273] Server analysis: The server determined that "confirmation regarding the Act against Unjustifiable Premiums and Misleading Representations is required."

[0274] Emotional Engine Analysis: Detects when a user is experiencing stress while submitting input information.

[0275] Server generation list: "Act against Unjustifiable Premiums and Misleading Representations: Confirm with Marketing Department" "Content of Description: Confirm with Legal Department" "Internal Confirmation: Confirm with ISC"

[0276] Emotional Engine Adjustment: Send a reminder along with a simplified procedure.

[0277] User Confirmation Execution: The user contacts the marketing department and the legal department to obtain the necessary confirmations.

[0278] Result Feedback: The user inputs the results into the system.

[0279] Server Saving and Display: The server saves the results in the database and displays a confirmation completion message to the user.

[0280] 2. Confirmation of Privacy Policy Using the Emotional Engine

[0281] User Input: "Create a mobile app for data collection"

[0282] Server Analysis: The server determines that "confirmation of the privacy policy is required".

[0283] Emotional Engine Analysis: Detect that the user is feeling confused when proceeding with the confirmation procedure.

[0284] Server Generated List: "Privacy Policy: Confirmation to the legal department", "Content of Data Collection: Confirmation to the data department"

[0285] Emotional Engine Adjustment: Display an easy-to-understand explanation and a support message.

[0286] User Confirmation Execution: The user contacts the legal department and the data department to obtain the necessary confirmations.

[0287] Result Feedback: The user inputs the results into the system.

[0288] Server Saving and Display: The server saves the results in the database and displays a confirmation completion message to the user.

[0289] This system allows users to centrally manage and efficiently process multiple legal verification procedures. The introduction of an emotion engine enables flexible responses tailored to the user's emotional state, reducing the burden of verification work.

[0290] The following describes the processing flow.

[0291] Step 1:

[0292] The user accesses the input form. Through a web browser, the user accesses the system's input form and enters the creation (e.g., website) and its purpose (e.g., marketing).

[0293] Step 2:

[0294] The user enters information. The user fills in the necessary information in the input form, such as "Development = Website" and "Purpose = Marketing."

[0295] Step 3:

[0296] The user clicks the submit button. When the user clicks the submit button, the entered information is sent to the server.

[0297] Step 4:

[0298] The server receives the input information. The server receives the information sent by the user and prepares it for analysis.

[0299] Step 5:

[0300] The server analyzes the input information. The server uses a natural language processing algorithm to analyze the received information. Based on the analysis results, it identifies the necessary legal compliance items (e.g., the Act against Unjustifiable Premiums and Misleading Representations, privacy policy, etc.).

[0301] Step 6:

[0302] The emotion engine analyzes the user's emotions. The emotion engine incorporated in the server analyzes the emotional state from the input information and the user's operation actions.

[0303] Step 7:

[0304] The server generates a legal review list. Based on the analysis results, the server generates a list of necessary legal review items. For each item, the corresponding review contact and procedures are listed.

[0305] <​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​The user provides feedback on the verification results. The user enters the verification results into the feedback form and sends it to the server.

[0315] Step 13:

[0316] The server receives the confirmation result. The server receives the confirmation result sent by the user and proceeds to the next step.

[0317] Step 14:

[0318] The server saves the verification results. The server records the received verification results in the database and updates the progress of the verification process.

[0319] Step 15:

[0320] The server displays update information. The server updates the user's confirmation status and displays the progress on the user's device. The user receives a confirmation message and information about the next steps.

[0321] This system allows users to efficiently manage legal verification procedures, and by using an emotion engine, it enables flexible responses tailored to the user's emotional state.

[0322] (Example 2)

[0323] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0324] The current legal review system has problems such as making procedures stressful and inefficient because it does not take into account the user's emotional state. In addition, there is no way to centrally manage multiple legal reviews and properly track their progress, making it difficult for users to proceed with the procedures smoothly.

[0325] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0326] In this invention, the server includes means for the user to input a creation and its purpose; means for the server to analyze the input information and identify necessary legal confirmation items; means for the server to analyze the user's emotional state; means for the server to present corresponding confirmation windows and procedures for each identified legal confirmation item; means for the server to adjust the priority and procedures of legal confirmation procedures according to the user's emotional state; means for the user to provide feedback on the legal confirmation results; and means for the server to receive, store, and update the feedback. This makes it possible to provide flexible legal confirmation procedures that take into account the user's emotional state and to improve the efficiency of the confirmation procedures.

[0327] "Created works" refers to all objects that users create and input into the system. Examples include websites and mobile applications.

[0328] "Purpose" refers to the intention or use that a user sets for their creation. Examples include marketing and data collection.

[0329] "Legal confirmation items" refer to the legal matters that need to be confirmed for the created document. For example, these include the Act against Unjustifiable Premiums and Misleading Representations and privacy policies.

[0330] A "confirmation desk" refers to the department or person in charge of handling legal confirmation items. For example, this could include the marketing department or the legal department.

[0331] "Procedures" refer to the steps and methods necessary to carry out legal verification. For example, this includes submitting documents and contacting the relevant personnel.

[0332] "Emotional state" refers to the emotional state a user exhibits while using the system. Examples include stress, confusion, and relief.

[0333] "Feedback" refers to the act of a user reporting the results of a legal review to the system. This includes, for example, reporting the progress and results of the review.

[0334] This invention is a system that allows users to input a creation and its purpose, and then efficiently performs the necessary legal checks based on that input. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides a more flexible and adaptable check procedure.

[0335] System Overview

[0336] This system includes a server that analyzes information provided by the user, a terminal where the user inputs information, an emotion engine that recognizes the user's emotional state, and means for managing feedback.

[0337] Hardware and software used

[0338] The main components of this system are as follows:

[0339] User devices (e.g., personal computers, smartphones)

[0340] Servers (e.g., AWS, Google Cloud)

[0341] Emotion engine (e.g., Microsoft® Azure® Emotion API)

[0342] Databases (e.g., MySQL, PostgreSQL)

[0343] System Functions

[0344] 1. Entering information

[0345] Users access the system's web form using devices such as PCs or smartphones and enter their creations and their purposes. For example, they access "https: / / example.com / form" using a browser and enter the necessary information using text boxes or dropdown menus.

[0346] 2. Information Reception and Analysis

[0347] The server analyzes the received information and identifies the necessary legal compliance items. This analysis is performed by a script running on the server side (e.g., Python or Node.js). Identified legal compliance items include compliance with the Act against Unjustifiable Premiums and Misleading Representations and privacy policies. Furthermore, an emotion engine (e.g., Microsoft Azure Emotion API) analyzes the user's input information and behavior to determine their emotional state, recognizing stress, confusion, etc.

[0348] 3. Generating a legal checklist

[0349] Based on the analysis results, the server generates a list of items requiring legal review. This list includes details of the corresponding review channels and procedures. The emotion engine adjusts the priority and method of the procedures according to the user's emotional state. For example, if the user is stressed, the procedures may be simplified or support messages added.

[0350] 4. Display and implementation of verification procedures

[0351] The server displays the generated legal checklist on the user's terminal, and the user performs the necessary checks according to the list. For example, they might contact the marketing department to request a check regarding the Act against Unjustifiable Premiums and Misleading Representations. Once the checks are complete, the user feeds the results back into the system and sends them to the server.

[0352] 5. Saving and updating verification results

[0353] The server receives the confirmation results sent by the user and stores them in the database. This updates the confirmation status, and the user's progress is displayed on the terminal. The user receives a confirmation completion message and information about the next steps.

[0354] Specific example

[0355] 1. Verification of the Act against Unjustifiable Premiums and Misleading Representations using an emotional engine.

[0356] User input: "Website creation, purpose is marketing."

[0357] Server analysis: The server determined that "confirmation regarding the Act against Unjustifiable Premiums and Misleading Representations is required."

[0358] Emotional Engine Analysis: Detects when a user is experiencing stress while submitting input information.

[0359] Server generation list: "Act against Unjustifiable Premiums and Misleading Representations: Confirm with Marketing Department", "Content of Description: Confirm with Legal Department", "Internal Confirmation: Confirm with General Affairs Department"

[0360] Emotional Engine Tuning: Send reminders with simplified steps.

[0361] User verification: The user contacts the marketing and legal departments to obtain the necessary verifications.

[0362] Result Feedback: Users enter their results into the system.

[0363] Server save and display: The server saves the results to the database and displays a confirmation message to the user.

[0364] 2. Reviewing the Privacy Policy using an Emotion Engine

[0365] User input: "I'm creating a mobile app; the purpose is data collection."

[0366] Server analysis: The server determined that "confirmation of the privacy policy is required."

[0367] Emotional Engine Analysis: Detects when a user is experiencing confusion while proceeding with the verification process.

[0368] Server generation list: "Privacy Policy: Confirm with Legal Department" "Data Collection Details: Confirm with Data Department"

[0369] Emotional Engine Adjustment: Displays clear explanations and support messages.

[0370] User verification: The user contacts the legal and data departments to obtain the necessary verifications.

[0371] Result Feedback: Users enter their results into the system.

[0372] Server save and display: The server saves the results to the database and displays a confirmation message to the user.

[0373] This system allows users to centrally manage and efficiently process multiple legal verification procedures. The introduction of an emotion engine enables flexible responses tailored to the user's emotional state, reducing the burden of verification work.

[0374] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0375] Step 1:

[0376] The user enters information on the device.

[0377] The user accesses the system's web form using their device and enters information about their creation and its purpose. Specifically, they access "https: / / example.com / form" using a browser and enter information such as "Website creation, purpose is marketing" into the text box. Once the input is submitted, the server receives the information.

[0378] Input: The user enters the creation and its purpose in the input form.

[0379] Output: The information entered by the user is sent to the server.

[0380] Step 2:

[0381] The server receives and analyzes the input information.

[0382] The server receives and analyzes information sent by the user. This analysis uses, for example, a Python script to identify the necessary legal checks based on the creation and purpose. For example, based on the purpose of "marketing," it might determine that "checking the Act against Unjustifiable Premiums and Misleading Representations is necessary."

[0383] Input: Information submitted by the user

[0384] Output: Required legal verification items as analysis results

[0385] Step 3:

[0386] The emotion engine built into the server analyzes the emotional state.

[0387] An emotion engine (e.g., Microsoft Azure Emotion API) analyzes a user's emotional state based on received user input and behavioral data. This helps determine whether the user is experiencing stress or distress.

[0388] Input: User input information and behavioral data

[0389] Output: Data on the user's emotional state

[0390] Step 4:

[0391] The server generates a legal checklist.

[0392] Based on the analysis results, the server generates a list of necessary legal verification items. This list includes details of the relevant contact point and procedures for each item. For example, it might list items such as "Act against Unjustifiable Premiums and Misleading Representations: Confirm with the Marketing Department" and "Content of Description: Confirm with the Legal Department."

[0393] Input: Analysis results and emotional state data

[0394] Output: List of legal review items

[0395] Step 5:

[0396] The emotion engine adjusts the procedure.

[0397] The emotion engine adjusts the procedure based on the user's emotional state. For example, if the user is stressed, it might simplify the procedure, send a reminder, or add a support message.

[0398] Input: Data on the user's emotional state

[0399] Output: Adjusted legal confirmation procedure

[0400] Step 6:

[0401] The server displays the legal checklist on the user's terminal.

[0402] The server sends the generated legal checklist to the user's terminal for display. This list also reflects the results of adjustments made by the sentiment engine, such as simplified procedures, reminders, and support messages.

[0403] Input: Adjusted legal confirmation procedure

[0404] Output: Legal confirmation list displayed on the user terminal

[0405] Step 7:

[0406] The user performs the verification procedure.

[0407] The user will perform the necessary verification procedures based on the displayed legal checklist. For example, they might contact the marketing department to request verification regarding the Act against Unjustifiable Premiums and Misleading Representations.

[0408] Input: Legal confirmation list

[0409] Output: Implementation of verification procedure

[0410] Step 8:

[0411] The user enters the confirmation result as feedback and sends it to the server.

[0412] After completing the verification process, users enter the results into the system and send them to the server. Specifically, they access a web form for feedback, enter the results, and press the submit button.

[0413] Input: Enter confirmation result

[0414] Output: Sending confirmation results

[0415] Step 9:

[0416] The server receives the confirmation result.

[0417] The server receives the confirmation result sent by the user and retrieves the data necessary to proceed to the next step.

[0418] Input: Confirmation result

[0419] Output: Received confirmation result

[0420] Step 10:

[0421] The server saves and updates the verification results.

[0422] The server saves the received confirmation results to a database and updates it with the latest information. For example, it saves them to a database such as MySQL or PostgreSQL.

[0423] Input: Confirmation result received

[0424] Output: Verification results saved in the database

[0425] Step 11:

[0426] The server displays update information on the user's terminal.

[0427] The server displays the updated confirmation status on the user's device. The user receives a confirmation completion message and information about the next steps.

[0428] Input: Verification results stored in the database

[0429] Output: Update information displayed on the user's terminal

[0430] (Application Example 2)

[0431] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0432] The implementation and management of modern security systems involve numerous legal review procedures, which are complex and place a significant burden on users. Furthermore, user emotional states (e.g., confusion, stress) can reduce the efficiency of these procedures. Therefore, it is necessary to enable users to conduct legal review efficiently.

[0433] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0434] In this invention, the server includes means for the user to input a creation and its purpose; means for the server to analyze the input information and identify necessary legal verification items; means for the server to present corresponding verification windows and procedures for each identified legal verification item; means for an emotion analysis engine to analyze the user's emotional state and adjust the procedure; means for the user to provide feedback on the legal verification results; and means for the server to receive, save, and update the feedback. This makes it possible to perform legal verification efficiently while taking the user's emotional state into consideration.

[0435] A "user" is an individual or company that uses the system.

[0436] "Created work" refers to a system, software, or other technical device that the user intends to create or implement.

[0437] "Purpose" refers to the main reason or goal for a user to use the creation.

[0438] A "server" is a central processing unit that receives, analyzes, stores, and updates user input information.

[0439] "Means of analyzing information" refers to algorithms and programs used by a server to analyze information entered by a user and identify necessary legal verification items.

[0440] "Legal verification items" refer to matters that need to be verified based on laws and regulations related to a specific document or purpose.

[0441] A "confirmation desk" refers to a department or person responsible for handling or confirming specific legal confirmation items.

[0442] "Means for adjusting the procedure" refers to functions that allow the emotion analysis engine to adjust the flow and difficulty level of procedures presented based on the user's emotional state.

[0443] An "emotion analysis engine" is software or an algorithm used to identify and analyze a user's emotional state (e.g., stress, confusion).

[0444] "Feedback" refers to the act of a user entering the results of a verification process into the system and sending them to the server.

[0445] "Means of saving and updating" refers to the function of a server to save the feedback it receives in a database and update the information to the latest version based on that data.

[0446] This invention is a system that enables users to efficiently perform legal verification procedures related to the introduction and management of security systems. The system comprises a terminal used by the user, a server for analyzing information, an emotion analysis engine for recognizing the user's emotional state, and means for managing feedback from the legal verification procedures.

[0447] The server integrates multiple functions, receiving and analyzing information about creations and their purpose entered by the user via the terminal. Based on the input information, it identifies necessary legal verification items and presents the corresponding verification channels and procedures. Furthermore, it incorporates an emotion analysis engine that analyzes the user's emotional state based on their input behavior and adjusts the procedure accordingly. For example, if the user is experiencing stress, the server simplifies the procedure and sends a reminder.

[0448] The sentiment analysis engine is installed on devices such as smartphones, tablets, smart glasses (e.g., Google Glass®), and head-mounted displays (e.g., Microsoft HoloLens®). This allows for the adjustment of procedures based on the user's emotional state. The server interacts with web servers such as Apache® HTTP Server and databases such as MySQL to analyze input information and perform internal processing. Furthermore, sentiment analysis engines such as IBM Watson® Tone Analyzer are used for sentiment analysis.

[0449] For example, if a user plans to install a new surveillance camera system with the goal of enhancing office security, the server receiving the input information will identify relevant legal verification items (e.g., GDPR compliance). The sentiment analysis engine will analyze the user's emotional state, and if it detects that the user is experiencing stress or confusion, it will provide a supportive message with a clear explanation to simplify the process. After the user has confirmed with the relevant legal and technical departments, the results are fed back into the system, the server updates the database, and a confirmation message is displayed to the user.

[0450] Specific examples of input prompts for a generative AI model:

[0451] The purpose of introducing the new surveillance camera system is to enhance office security. Legal compliance checks related to GDPR are required. Please simplify the workflow, taking into consideration any potential user confusion.

[0452] In this way, users can efficiently conduct legal reviews in a manner that takes their emotional state into consideration, and the security system implementation process can proceed smoothly.

[0453] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0454] Step 1:

[0455] The user enters information into the input form.

[0456] The user uses a device (smartphone, tablet, etc.) to input the creation (e.g., a surveillance camera system) and its purpose (e.g., enhancing office security). The input data includes the specific type and purpose of the system.

[0457] Step 2:

[0458] The server receives and analyzes the input information.

[0459] The server receives information sent by the user and begins analysis. Using the input data, it identifies the necessary legal verification items (e.g., GDPR-related verifications). At this stage, the server analyzes the data received from the frontend in the backend and extracts the appropriate legal verification items. Specifically, it analyzes the input data using natural language processing (NLP) algorithms.

[0460] Step 3:

[0461] The emotion analysis engine analyzes the user's emotions.

[0462] A sentiment analysis engine embedded in the server analyzes the user's emotional state from user input information and interactions. For example, it can detect signs of confusion or stress from input speed and content. Input includes user input actions and text information, while output generates emotional state evaluation data. Specifically, it uses sentiment analysis engines such as IBM Watson Tone Analyzer.

[0463] Step 4:

[0464] The server generates a legal checklist.

[0465] Based on the analysis results obtained in the previous step, the server generates a list of necessary legal confirmation items. This list includes the corresponding contact point and procedure for each item. The inputs are the data for the legal confirmation items and the sentiment analysis results, and the output is the generated legal confirmation list. Specifically, it retrieves relevant information from the database and compiles instructions for the user in a list format.

[0466] Step 5:

[0467] The emotion analysis engine adjusts the procedure.

[0468] The emotion analysis engine adjusts the procedure based on the user's emotional state. For example, if the user is stressed, it simplifies the procedure and sends reminders and support messages. The input is emotional state evaluation data, and the output is the generated adjusted procedure. Specifically, it dynamically changes the content displayed in the user interface and the content of messages.

[0469] Step 6:

[0470] The server displays a legal review list.

[0471] The server displays a refined legal checklist on the user's terminal. The user is then guided through the process, with adjustments made by the sentiment analysis engine reflected in the content. This step generates a refined legal checklist as input and display data on the terminal as output. Specifically, the list content is displayed on the user interface via a web page or application interface.

[0472] Step 7:

[0473] The user performs the verification procedure.

[0474] The user follows the displayed instructions and completes the verification process at each relevant department. For example, they might contact the legal or technical department to obtain the necessary verifications. The input is a displayed legal verification list, and the output is a status indicating that the verification process has been completed. Specifically, they contact each department using email or internal tools.

[0475] Step 8:

[0476] The user provides feedback on the verification results.

[0477] The user enters their results into a form to provide feedback to the system and sends it to the server. The server receives the confirmation result data as input and the feedback data as output. Specifically, a web form or application feedback screen is used.

[0478] Step 9:

[0479] The server receives the confirmation result.

[0480] The server receives the confirmation result sent by the user and proceeds to the next process. The input is feedback data, and the output is the reception status. Specifically, it performs parsing processing to register the received data in the database.

[0481] Step 10:

[0482] The server saves and updates the verification results.

[0483] The server saves the verification results to the database and updates that information to the latest version. The input is the received feedback data, and the output is the updated database information. Specifically, the database update process is performed using SQL queries.

[0484] Step 11:

[0485] The server displays update information.

[0486] The server updates the user's confirmation status and displays the progress on the terminal. The input is the updated database information, and the output is the status display data. Specifically, it displays information about the progress and the next steps to the user on the screen.

[0487] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0488] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0489] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0490] [Second Embodiment]

[0491] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0492] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0493] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0494] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0495] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0496] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0497] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0498] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0499] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0500] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0501] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0502] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0503] This invention is a system that allows users to input a creation and its purpose, and then efficiently perform the necessary legal checks based on that input. This system analyzes the input information and centrally manages multiple checkpoints and procedures, thereby reducing the burden on the user and improving the efficiency of the check process.

[0504] System Overview

[0505] This system includes a server that analyzes information provided by the user, a terminal where the user inputs information, and means for managing feedback.

[0506] Program processing

[0507] 1. The user enters information into the input form.

[0508] The user accesses a web form and enters the creation (e.g., a website) and its purpose (e.g., marketing).

[0509] 2. The server receives and analyzes the input information.

[0510] The server receives and analyzes information sent by the user. Based on the input information, it identifies the necessary legal verification items. For example, if the user enters "Website creation, purpose is marketing," then verification of the Act against Unjustifiable Premiums and Misleading Representations, privacy policy, and terms of service will be required.

[0511] 3. The server generates a legal checklist.

[0512] The server generates a legal checklist based on the analysis results, listing the corresponding contact point and procedure for each item. For example, it displays "Confirm with the Marketing Department" for the Act against Unjustifiable Premiums and Misleading Representations, "Confirm with the Legal Department" for the Privacy Policy, and "Confirm with the Legal Department regarding the content" for the content of the document.

[0513] 4. Provide the user with confirmation steps.

[0514] The server generates a legal checklist and procedures, which are then displayed on the user's terminal. This allows the user to review the specific steps and required documents for each check item and take action themselves.

[0515] 5. The user performs the verification.

[0516] The user will follow the instructions provided and carry out the necessary verification procedures at each stage. For example, the user will contact the marketing department to confirm compliance with the Act against Unjustifiable Premiums and Misleading Representations.

[0517] 6. The user provides feedback on the verification results.

[0518] The user enters their results into a form to provide feedback to the system and sends it to the server.

[0519] 7. The server saves and updates the results.

[0520] The server saves the confirmation results received from the user to a database and updates the status on the system. This allows the user to track the progress of the confirmation process in real time.

[0521] Specific example

[0522] 1. Example: Confirmation under the Act against Unjustifiable Premiums and Misleading Representations

[0523] User input: "Website creation, purpose is marketing."

[0524] Server analysis: The server determined that "confirmation regarding the Act against Unjustifiable Premiums and Misleading Representations is required."

[0525] Server generation list: "Act against Unjustifiable Premiums and Misleading Representations: Confirm with Marketing Department" "Content of Description: Confirm with Legal Department" "Internal Confirmation: Confirm with ISC"

[0526] User verification: The user contacts the marketing and legal departments to obtain the necessary verifications.

[0527] Result Feedback: The user enters the results into the system.

[0528] Server save and display: The server saves the results to the database and displays a confirmation completion message to the user.

[0529] 2. Example: Checking the Privacy Policy

[0530] User input: "I'm creating a mobile app; the purpose is data collection."

[0531] Server analysis: The server determined that "confirmation of the privacy policy is required."

[0532] Server generation list: "Privacy Policy: Confirm with Legal Department" "Data Collection Details: Confirm with Data Department"

[0533] User verification: The user contacts the legal department and the data department to obtain the necessary verifications.

[0534] Result Feedback: The user enters the results into the system.

[0535] Server save and display: The server saves the results to the database and displays a confirmation completion message to the user.

[0536] This system allows users to centrally manage and efficiently process multiple legal verification procedures. This significantly improves the efficiency and accuracy of the verification process.

[0537] The following describes the processing flow.

[0538] Step 1:

[0539] The user accesses the input form. Through a web browser, the user accesses the system's input form and enters the creation (e.g., website) and its purpose (e.g., marketing).

[0540] Step 2:

[0541] The user enters information. The user fills in the necessary information in the input form, such as "Development = Website" and "Purpose = Marketing."

[0542] Step 3:

[0543] The user clicks the submit button. When the user clicks the submit button, the entered information is sent to the server.

[0544] Step 4:

[0545] The server receives the input information. The server receives the information sent by the user and prepares it for analysis.

[0546] Step 5:

[0547] The server analyzes the input information. The server uses a natural language processing algorithm to analyze the received information. Based on the analysis results, it identifies the necessary legal compliance items (e.g., the Act against Unjustifiable Premiums and Misleading Representations, privacy policy, etc.).

[0548] Step 6:

[0549] The server generates a legal checklist. Based on the analysis results, the server generates a list of necessary legal check items. For each item, it lists the corresponding contact point and procedure.

[0550] Step 7:

[0551] The server displays a legal confirmation list. The server displays the generated legal confirmation list on the user's terminal. The list includes details of each confirmation contact and procedure.

[0552] Step 8:

[0553] The user performs the verification procedure. Based on the instructions provided by the server, the user completes the necessary verification procedures at each relevant contact point. For example, they might request the marketing department to verify compliance with the Act against Unjustifiable Premiums and Misleading Representations.

[0554] Step 9:

[0555] The user collects the verification results. The user receives feedback from the verification channel and prepares to return it to the system.

[0556] Step 10:

[0557] The user provides feedback on the verification results. The user enters the verification results into the feedback form and submits it to the system.

[0558] Step 11:

[0559] The server receives the confirmation result. The server receives the confirmation result sent by the user and proceeds to the next step.

[0560] Step 12:

[0561] The server saves the verification results. The server saves the verification results to a database and updates that information to the latest version.

[0562] Step 13:

[0563] The server displays update information. The server updates the user's confirmation status and displays the progress on the terminal. The user receives a confirmation message and information about the next steps.

[0564] In this way, users can efficiently manage various legal checks and complete the necessary procedures.

[0565] (Example 1)

[0566] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0567] Traditional legal verification processes are complex and time-consuming, requiring the individual management of multiple verification channels and procedures. Maintaining accuracy and efficiency is also difficult. This is especially true when legal regulations are diverse and require coordination across various departments. An efficient, centralized system is needed to address these problems.

[0568] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0569] In this invention, the server includes means for the user to input a creation and its purpose; means for the server to receive and analyze the input information and identify necessary legal confirmation items; means for the server to generate a legal confirmation list based on the analysis results using a generation AI model; means for the server to list the corresponding confirmation contacts and procedures for each identified legal confirmation item; means for the user to display the confirmation procedure and provide feedback on the legal confirmation results; and means for the server to receive, save, and update the feedback. This makes it possible to efficiently centrally manage legal confirmation procedures and track the progress of confirmation work in real time.

[0570] A "user" is anyone who accesses this system and enters information about their creations and their purpose.

[0571] A "server" is a device that receives and analyzes information sent by users, identifies necessary legal verification items, and generates and manages legal verification lists.

[0572] "Created works" refers to deliverables such as websites and mobile applications created by users.

[0573] "Purpose" refers to the role or use that the creation is intended to fulfill, and includes, for example, marketing and data collection.

[0574] "Legal confirmation items" refer to items related to the creation of a document that require legal confirmation, and specifically include the Premiums and Representations Act and privacy policies.

[0575] A "generative AI model" is a type of artificial intelligence used to analyze input information and identify legal compliance items.

[0576] The "Legal Confirmation List" is a list of the corresponding confirmation contacts and procedures for each legal confirmation item, generated by the server based on the analysis results.

[0577] A "confirmation desk" refers to the department or person responsible for confirming legal compliance items.

[0578] "Procedures" refer to the specific actions and tasks required in response to legal verification items.

[0579] "Feedback" refers to the user submitting legal review results to the system.

[0580] Modes for carrying out the invention

[0581] This invention is a system that allows users to input a creation and its purpose, and then analyzes that input information to efficiently perform necessary legal checks. By analyzing the input information and centrally managing multiple checkpoints and procedures, this system reduces the burden on the user and improves the efficiency of the check process.

[0582] System Configuration

[0583] This system consists mainly of the following elements.

[0584] 1. A terminal where the user enters information.

[0585] 2. A server that receives and analyzes information sent by the user.

[0586] 3. Generative AI models within the server

[0587] 4. Legal confirmation list generated on the server

[0588] 5. Means for users to provide feedback

[0589] 6. Database to receive, store, and update feedback

[0590] The user is using a terminal to enter information.

[0591] Users access a web form and enter information about their creation (e.g., a website) and its purpose (e.g., marketing). This data is then sent to the system.

[0592] The server receives and analyzes the input information.

[0593] The server receives information sent by the user. It then analyzes the input information using a generation AI model and identifies the necessary legal checks based on the entered data. For example, if the user enters "Website creation, purpose is marketing," the server will determine that checks on the Premiums and Representations Act and the privacy policy are necessary.

[0594] Legal confirmation list generated on the server

[0595] The server generates a legal checklist based on the analysis results, listing the necessary contact points and procedures. For example, it includes specific instructions such as "Confirm with the Marketing Department" for the Premiums and Representations Act and "Confirm with the Legal Department" for the Privacy Policy.

[0596] Provide the user with a verification procedure.

[0597] The server displays the generated legal checklist on the user's terminal. The user reviews it and follows the instructions to perform the necessary legal checks. Specifically, they request the marketing department to review the Premiums and Representations Act and the legal department to review the privacy policy.

[0598] The user provides feedback on the verification results.

[0599] The user enters the results into a dedicated form within the system to provide feedback on the verification process. This information is then sent to the server.

[0600] The server saves and updates the results.

[0601] The server saves the confirmation results received from the user to the database and updates the status on the system. This allows the user to track the progress of the confirmation process in real time.

[0602] Specific example

[0603] Example 1: Confirmation of the Premiums and Representations Act

[0604] User input: "Website creation, purpose is marketing."

[0605] Server analysis: The server determines that "confirmation regarding the Premiums and Representations Act is required."

[0606] Server generation list: "Act against Unjustifiable Premiums and Misleading Representations: Confirm with Marketing Department" "Contents of Description: Confirm with Legal Department"

[0607] User verification: The user contacts the marketing and legal departments to complete any necessary verifications.

[0608] Result Feedback: The user enters the results into the system.

[0609] Server save and display: The server saves the results to the database and displays a confirmation message to the user.

[0610] Example 2: Checking the Privacy Policy

[0611] User input: "I'm creating a mobile app; the purpose is data collection."

[0612] Server analysis: The server determines that "confirmation of the privacy policy is required."

[0613] Server generation list: "Privacy Policy: Confirm with Legal Department" "Data Collection Details: Confirm with Data Department"

[0614] User verification: The user contacts the legal department and the data department to perform the necessary verifications.

[0615] Result Feedback: The user enters the results into the system.

[0616] Server save and display: The server saves the results to the database and displays a confirmation message to the user.

[0617] This system allows users to centrally manage and efficiently process multiple legal verification procedures. This significantly improves the efficiency and accuracy of the verification process.

[0618] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0619] Step 1:

[0620] A user accesses a web form and enters information about their creation (e.g., a website) and its purpose (e.g., marketing). The entered information is sent from the user's device to the server. This input information becomes the basis for subsequent processing.

[0621] Step 2:

[0622] The server receives information sent by the user. After receiving the information, the server analyzes the input data using a generative AI model. The information extracted through this analysis is used to identify subsequent legal review items. Specifically, it performs natural language processing to understand the intent of the user's input.

[0623] Step 3:

[0624] The server identifies the necessary legal checks based on the analysis results. For example, if the analysis indicates "website creation, purpose is marketing," the server will identify the need to check the Premiums and Representations Act and the privacy policy. The output of this step is a list of the specific legal items that need to be checked.

[0625] Step 4:

[0626] For each legal verification item identified by the server, a list of the corresponding verification contacts and procedures is created. This list includes instructions on which department to contact for each item. For example, "Confirm the Premiums and Representations Act with the Marketing Department" or "Confirm the Privacy Policy with the Legal Department."

[0627] Step 5:

[0628] The server generates a legal checklist, which is then displayed on the user's terminal. By reviewing this list, the user can learn about the necessary procedures. The output specifically shows the checklist items, their corresponding contact points, and detailed steps.

[0629] Step 6:

[0630] The user will conduct legal checks following the provided procedures. The user will contact each department based on the list and request the necessary checks. For example, the user might request the marketing department to check the Premiums and Representations Act and the legal department to check the privacy policy.

[0631] Step 7:

[0632] The user enters the results of the legal review into a dedicated form within the system to provide feedback. This information is then sent back to the server. The results entered by the user become the input data for this step.

[0633] Step 8:

[0634] The server saves the confirmation results received from the user to a database. Furthermore, it updates the status of the confirmation items and displays the progress on the system. This allows users to track the progress of their confirmation work in real time.

[0635] This series of processing steps allows users to efficiently complete legal verification procedures. Furthermore, the ability to manage the progress of the verification process within the system significantly improves the efficiency and accuracy of the verification work.

[0636] (Application Example 1)

[0637] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0638] Online platforms such as virtual stores require the efficient management of numerous legal verification items and the rapid coordination of verification processes with multiple contact points. Furthermore, tracking the progress and deadlines of these verification processes is often difficult, placing a significant burden on users. A comprehensive system is needed to address these issues.

[0639] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0640] In this invention, the server includes means for the user to input a creation and its purpose; means for the server to analyze the input information and identify necessary legal verification items; means for the server to present corresponding verification contacts and procedures for each identified legal verification item; means for the user to provide feedback on the legal verification results; means for the server to receive, save, and update the feedback; means for tracking the progress of the legal verification work; and means for notifying the user of the deadline and progress of the verification procedures. This enables the user to efficiently carry out legal verification work and appropriately manage progress and deadlines.

[0641] A "user" is an end-user who uses the system to input creations and their purposes.

[0642] "Created works" refer to specific projects, products, or services that users input.

[0643] "Purpose" refers to the achievement goals or intentions related to the creation.

[0644] "Means" refers to methods or mechanisms for performing a specific function or role.

[0645] A "server" refers to a computer system that receives, analyzes, stores, and manages information entered by users.

[0646] "Legal confirmation items" refer to legal confirmation matters necessary in relation to the created document and its purpose.

[0647] A "confirmation desk" refers to the contact point or department necessary to address specific legal confirmation items.

[0648] "Procedure" refers to the specific actions and steps required to confirm and approve certain legal verification items.

[0649] "Feedback" refers to the act of reporting the results and progress of legal checks performed by users to the server.

[0650] "Updating" refers to the act of updating data to the latest state based on information received by the server.

[0651] "Progress" refers to the status of the legal review process.

[0652] "Notifications" refer to alerts or messages that inform users about deadlines and progress of verification procedures.

[0653] This invention is a system for efficiently performing legal verification work. The system is designed so that the user inputs a creation and its purpose, and the server then performs the necessary legal verification based on that input. The following details specific embodiments of this system.

[0654] Hardware and software configuration

[0655] Hardware:

[0656] Server: Cloud servers such as AWS EC2 are used to process data, including receiving, analyzing, storing, and updating it.

[0657] User terminal: A device such as a smartphone, PC, or tablet used by the user to input information and check the results.

[0658] software:

[0659] Framework: Implement the server analysis module using Python.

[0660] Database: MySQL is used to store legal review results and progress data.

[0661] Frontend: Build the user interface using React.js.

[0662] Data processing and computation

[0663] Data entry and analysis:

[0664] User Terminal: Users enter their creation and its purpose through a web form. For example, they might enter "Type of virtual store: Health food sales, Purpose: Promotional campaign."

[0665] Server: Analyzes the received input data and identifies the necessary legal verification items. Based on the analysis results, it generates a verification list and displays it to the user.

[0666] Verification steps and feedback:

[0667] User: Follow the provided verification steps, complete the necessary verification procedures, and enter the results into the feedback form.

[0668] Server: Receives feedback and stores it in the database. Updates progress in real time and notifies the user.

[0669] Specific example

[0670] User input: "Virtual store type: Health food sales, Purpose: Promotional campaign"

[0671] Analysis results: The server determined that it was necessary to "check the Premiums and Representations Act" and "check the Privacy Policy".

[0672] Verification procedure: The server will provide users with specific contact points and procedures for "confirmation regarding the Premiums and Representations Act" and "confirmation regarding the Privacy Policy."

[0673] Feedback: The user enters the confirmation result, and the server saves the progress to the database.

[0674] Notification: The server sends alerts to the user regarding legal review deadlines and progress.

[0675] Example of a prompt

[0676] Virtual store type: Health food sales, Purpose: Promotional campaign

[0677] This system allows users to efficiently carry out legal review work and properly manage progress and deadlines.

[0678] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0679] Step 1:

[0680] The user enters information. The user uses a device to access a web form and enters information about the creation (e.g., a virtual store) and its purpose (e.g., a promotional campaign). This entered information is sent to the server.

[0681] Input: The user enters "Virtual store type: Health food sales, Purpose: Promotional campaign" into the input form.

[0682] Output: User input data is sent to the server.

[0683] Specific operation: The user accesses a web form from a device such as a smartphone or PC, enters the required information, and presses the submit button. This information is sent to the server.

[0684] Step 2:

[0685] The server analyzes the input information. The server analyzes the received input information and identifies the necessary legal verification items. A generative AI model can be used for this analysis.

[0686] Input: The server receives user input data.

[0687] Output: The server identifies the legal items that need to be checked (e.g., "Check the Premiums and Representations Act," "Check the Privacy Policy").

[0688] Specific operation: The server passes the received data to the analysis module, which uses the generated AI model to identify the necessary legal verification items.

[0689] Step 3:

[0690] The server generates a legal confirmation list. Based on the analysis results, the server lists the corresponding confirmation contacts and procedures for each required legal confirmation item.

[0691] Input: Legal verification items identified by the server.

[0692] Output: The server generates a confirmation list and displays it on the user's terminal (e.g., "Confirmation of Premiums and Representations Act: Contact Legal Department", "Confirmation of Privacy Policy: Contact Data Department").

[0693] Specific operation: The server identifies the contact point and procedure corresponding to each item based on the legal verification items, and generates a verification list.

[0694] Step 4:

[0695] The user performs the verification procedure. The user follows the provided verification steps and completes the necessary verification procedures.

[0696] Input: Confirmation list displayed from the server.

[0697] Output: The user provides feedback on the results for each verification item (e.g., "Confirmation of Premiums and Representations Act: Completed," "Confirmation of Privacy Policy: Pending").

[0698] Specific actions: The user contacts the relevant departments, such as the legal department or data department, completes the necessary verification procedures, and enters the results into the system.

[0699] Step 5:

[0700] The server receives, stores, and updates feedback. The server receives user feedback, stores it in the database, and updates the system status.

[0701] Input: Confirmation result entered by the user.

[0702] Output: The server saves the verification results to the database and updates the system status.

[0703] Specific operation: The server receives feedback data sent by the user, saves it to the database, and updates the confirmation status in real time.

[0704] Step 6:

[0705] The server tracks progress and provides notifications. The server periodically tracks the progress of legal review work and sends necessary notifications to the user (e.g., deadlines for review procedures, progress status).

[0706] Input: Updated confirmation status.

[0707] Output: Sends notifications to the user's terminal regarding progress and deadlines.

[0708] Specific operation: The server periodically checks the database information, generates notifications based on progress and deadlines for verification procedures, and sends alerts to the user.

[0709] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0710] This invention is a system that allows users to input a creation and its purpose, and then efficiently performs the necessary legal checks based on that input. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides a more flexible and adaptable check procedure.

[0711] System Overview

[0712] This system includes a server that analyzes information provided by the user, a terminal where the user inputs information, an emotion engine that recognizes the user's emotional state, and means for managing feedback.

[0713] Program processing

[0714] 1. The user enters information into the input form.

[0715] The user accesses a web form and enters the creation (e.g., a website) and its purpose (e.g., marketing).

[0716] 2. The server receives and analyzes the input information.

[0717] The server receives and analyzes information sent by the user. Based on the input information, it identifies necessary legal compliance items (e.g., the Act against Unjustifiable Premiums and Misleading Representations, privacy policy, etc.).

[0718] 3. The emotion engine analyzes the user's emotions.

[0719] An emotion engine embedded in the server analyzes the user's emotional state from their input information and actions. This allows it to recognize emotions such as stress and confusion.

[0720] 4. The server generates a legal checklist.

[0721] The server generates a list of necessary legal verification items based on the analysis results. For each item, it lists the corresponding verification contacts and procedures.

[0722] 5. The emotion engine adjusts the procedural methods.

[0723] The emotion engine adjusts the priority and method of procedures based on the user's emotional state. For example, if the user is stressed, it may simplify procedures or send reminders and support messages.

[0724] 6. The server displays the legal confirmation list.

[0725] The server generates a legal review list, which is then displayed on the user's terminal. Adjustments made by the emotion engine are reflected in this list.

[0726] 7. The user completes the verification process.

[0727] The user will follow the instructions provided and complete the necessary verification procedures at each relevant department. For example, they might request the marketing department to verify compliance with the Act against Unjustifiable Premiums and Misleading Representations.

[0728] 8. The user provides feedback on the verification results.

[0729] The user enters their results into a form to provide feedback to the system and sends it to the server.

[0730] 9. The server receives the confirmation result.

[0731] The server receives the confirmation result sent by the user and proceeds to the next step.

[0732] 10. The server saves and updates the verification results.

[0733] The server saves the verification results to a database and updates that information to the latest version.

[0734] 11. The server displays update information.

[0735] The server updates the user's verification status and displays the progress on the terminal. The user receives a message confirming verification and information about the next steps.

[0736] Specific example

[0737] 1. Verification of the Act against Unjustifiable Premiums and Misleading Representations using an emotional engine.

[0738] User input: "Website creation, purpose is marketing."

[0739] Server analysis: The server determined that "confirmation regarding the Act against Unjustifiable Premiums and Misleading Representations is required."

[0740] Emotional Engine Analysis: Detects when a user is experiencing stress while submitting input information.

[0741] Server generation list: "Act against Unjustifiable Premiums and Misleading Representations: Confirm with Marketing Department" "Content of Description: Confirm with Legal Department" "Internal Confirmation: Confirm with ISC"

[0742] Emotional Engine Tuning: Send reminders with simplified instructions.

[0743] User verification: The user contacts the marketing and legal departments to obtain the necessary verifications.

[0744] Result Feedback: The user enters the results into the system.

[0745] Server save and display: The server saves the results to the database and displays a confirmation completion message to the user.

[0746] 2. Reviewing the Privacy Policy using an Emotion Engine

[0747] User input: "I'm creating a mobile app; the purpose is data collection."

[0748] Server analysis: The server determined that "confirmation of the privacy policy is required."

[0749] Emotional Engine Analysis: Detects when a user is feeling confused while proceeding with the verification process.

[0750] Server generation list: "Privacy Policy: Confirm with Legal Department" "Data Collection Details: Confirm with Data Department"

[0751] Emotional Engine Adjustment: Displays clear explanations and support messages.

[0752] User verification: The user contacts the legal department and the data department to obtain the necessary verifications.

[0753] Result Feedback: The user enters the results into the system.

[0754] Server save and display: The server saves the results to the database and displays a confirmation completion message to the user.

[0755] This system allows users to centrally manage and efficiently process multiple legal verification procedures. The introduction of an emotion engine enables flexible responses tailored to the user's emotional state, reducing the burden of verification work.

[0756] The following describes the processing flow.

[0757] Step 1:

[0758] The user accesses the input form. Through a web browser, the user accesses the system's input form and enters the creation (e.g., website) and its purpose (e.g., marketing).

[0759] Step 2:

[0760] The user enters information. The user fills in the necessary information in the input form, such as "Development = Website" and "Purpose = Marketing."

[0761] Step 3:

[0762] The user clicks the submit button. When the user clicks the submit button, the entered information is sent to the server.

[0763] Step 4:

[0764] The server receives the input information. The server receives the information sent by the user and prepares it for analysis.

[0765] Step 5:

[0766] The server analyzes the input information. The server uses a natural language processing algorithm to analyze the received information. Based on the analysis results, it identifies the necessary legal compliance items (e.g., the Act against Unjustifiable Premiums and Misleading Representations, privacy policy, etc.).

[0767] Step 6:

[0768] The emotion engine analyzes the user's emotions. The emotion engine, embedded in the server, analyzes the emotional state from the input information and the user's actions.

[0769] Step 7:

[0770] The server generates a legal checklist. Based on the analysis results, the server generates a list of necessary legal check items. For each item, it lists the corresponding contact point and procedure.

[0771] Step 8:

[0772] The emotion engine adjusts the procedure. The emotion engine adjusts the priority and method of procedures based on the user's emotional state. For example, if the user is stressed, it might simplify the procedure or send reminders and support messages.

[0773] Step 9:

[0774] The server displays the legal checklist. The server-generated legal checklist is displayed on the user's terminal. Details of the coordinated procedures and required documents are displayed.

[0775] Step 10:

[0776] The user performs the verification procedure. The user follows the instructions provided and completes the necessary verification procedures at each relevant department. For example, they might request the marketing department to verify compliance with the Act against Unjustifiable Premiums and Misleading Representations.

[0777] Step 11:

[0778] The user collects the verification results. The user collects feedback results from each verification channel and verifies the content themselves.

[0779] Step 12:

[0780] The user provides feedback on the verification results. The user enters the verification results into the feedback form and sends it to the server.

[0781] Step 13:

[0782] The server receives the confirmation result. The server receives the confirmation result sent by the user and proceeds to the next step.

[0783] Step 14:

[0784] The server saves the verification results. The server records the received verification results in the database and updates the progress of the verification process.

[0785] Step 15:

[0786] The server displays update information. The server updates the user's confirmation status and displays the progress on the user's device. The user receives a confirmation message and information about the next steps.

[0787] This system allows users to efficiently manage legal verification procedures, and by using an emotion engine, it enables flexible responses tailored to the user's emotional state.

[0788] (Example 2)

[0789] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0790] The current legal review system has problems such as making procedures stressful and inefficient because it does not take into account the user's emotional state. In addition, there is no way to centrally manage multiple legal reviews and properly track their progress, making it difficult for users to proceed with the procedures smoothly.

[0791] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0792] In this invention, the server includes means for the user to input a creation and its purpose; means for the server to analyze the input information and identify necessary legal confirmation items; means for the server to analyze the user's emotional state; means for the server to present corresponding confirmation windows and procedures for each identified legal confirmation item; means for the server to adjust the priority and procedures of legal confirmation procedures according to the user's emotional state; means for the user to provide feedback on the legal confirmation results; and means for the server to receive, store, and update the feedback. This makes it possible to provide flexible legal confirmation procedures that take into account the user's emotional state and to improve the efficiency of the confirmation procedures.

[0793] "Created works" refers to all objects that users create and input into the system. Examples include websites and mobile applications.

[0794] "Purpose" refers to the intention or use that a user sets for their creation. Examples include marketing and data collection.

[0795] "Legal confirmation items" refer to the legal matters that need to be confirmed for the created document. For example, these include the Act against Unjustifiable Premiums and Misleading Representations and privacy policies.

[0796] A "confirmation desk" refers to the department or person in charge of handling legal confirmation items. For example, this could include the marketing department or the legal department.

[0797] "Procedures" refer to the steps and methods necessary to carry out legal verification. For example, this includes submitting documents and contacting the relevant personnel.

[0798] "Emotional state" refers to the emotional state a user exhibits while using the system. Examples include stress, confusion, and relief.

[0799] "Feedback" refers to the act of a user reporting the results of a legal review to the system. This includes, for example, reporting the progress and results of the review.

[0800] This invention is a system that allows users to input a creation and its purpose, and then efficiently performs the necessary legal checks based on that input. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides a more flexible and adaptable check procedure.

[0801] System Overview

[0802] This system includes a server that analyzes information provided by the user, a terminal where the user inputs information, an emotion engine that recognizes the user's emotional state, and means for managing feedback.

[0803] Hardware and software used

[0804] The main components of this system are as follows:

[0805] User devices (e.g., personal computers, smartphones)

[0806] Servers (e.g., AWS, Google Cloud)

[0807] Emotion engine (e.g., Microsoft Azure Emotion API)

[0808] Databases (e.g., MySQL, PostgreSQL)

[0809] System Functions

[0810] 1. Entering information

[0811] Users access the system's web form using devices such as PCs or smartphones and enter their creations and their purposes. For example, they access "https: / / example.com / form" using a browser and enter the necessary information using text boxes or dropdown menus.

[0812] 2. Information Reception and Analysis

[0813] The server analyzes the received information and identifies the necessary legal compliance items. This analysis is performed by a script running on the server side (e.g., Python or Node.js). Identified legal compliance items include compliance with the Act against Unjustifiable Premiums and Misleading Representations and privacy policies. Furthermore, an emotion engine (e.g., Microsoft Azure Emotion API) analyzes the user's input information and behavior to determine their emotional state, recognizing stress, confusion, etc.

[0814] 3. Generating a legal checklist

[0815] Based on the analysis results, the server generates a list of items requiring legal review. This list includes details of the corresponding review channels and procedures. The emotion engine adjusts the priority and method of the procedures according to the user's emotional state. For example, if the user is stressed, the procedures may be simplified or support messages added.

[0816] 4. Display and implementation of verification procedures

[0817] The server displays the generated legal checklist on the user's terminal, and the user performs the necessary checks according to the list. For example, they might contact the marketing department to request a check regarding the Act against Unjustifiable Premiums and Misleading Representations. Once the checks are complete, the user feeds the results back into the system and sends them to the server.

[0818] 5. Saving and updating verification results

[0819] The server receives the confirmation results sent by the user and stores them in the database. This updates the confirmation status, and the user's progress is displayed on the terminal. The user receives a confirmation completion message and information about the next steps.

[0820] Specific example

[0821] 1. Verification of the Act against Unjustifiable Premiums and Misleading Representations using an emotional engine.

[0822] User input: "Website creation, purpose is marketing."

[0823] Server analysis: The server determined that "confirmation regarding the Act against Unjustifiable Premiums and Misleading Representations is required."

[0824] Emotional Engine Analysis: Detects when a user is experiencing stress while submitting input information.

[0825] Server generation list: "Act against Unjustifiable Premiums and Misleading Representations: Confirm with Marketing Department", "Content of Description: Confirm with Legal Department", "Internal Confirmation: Confirm with General Affairs Department"

[0826] Emotional Engine Tuning: Send reminders with simplified steps.

[0827] User verification: The user contacts the marketing and legal departments to obtain the necessary verifications.

[0828] Result Feedback: Users enter their results into the system.

[0829] Server save and display: The server saves the results to the database and displays a confirmation message to the user.

[0830] 2. Reviewing the Privacy Policy using an Emotion Engine

[0831] User input: "I'm creating a mobile app; the purpose is data collection."

[0832] Server analysis: The server determined that "confirmation of the privacy policy is required."

[0833] Emotional Engine Analysis: Detects when a user is experiencing confusion while proceeding with the verification process.

[0834] Server generation list: "Privacy Policy: Confirm with Legal Department" "Data Collection Details: Confirm with Data Department"

[0835] Emotional Engine Adjustment: Displays clear explanations and support messages.

[0836] User verification: The user contacts the legal and data departments to obtain the necessary verifications.

[0837] Result Feedback: Users enter their results into the system.

[0838] Server save and display: The server saves the results to the database and displays a confirmation message to the user.

[0839] This system allows users to centrally manage and efficiently process multiple legal verification procedures. The introduction of an emotion engine enables flexible responses tailored to the user's emotional state, reducing the burden of verification work.

[0840] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0841] Step 1:

[0842] The user enters information on the device.

[0843] The user accesses the system's web form using their device and enters information about their creation and its purpose. Specifically, they access "https: / / example.com / form" using a browser and enter information such as "Website creation, purpose is marketing" into the text box. Once the input is submitted, the server receives the information.

[0844] Input: The user enters the creation and its purpose in the input form.

[0845] Output: The information entered by the user is sent to the server.

[0846] Step 2:

[0847] The server receives and analyzes the input information.

[0848] The server receives and analyzes information sent by the user. This analysis uses, for example, a Python script to identify the necessary legal checks based on the creation and purpose. For example, based on the purpose of "marketing," it might determine that "checking the Act against Unjustifiable Premiums and Misleading Representations is necessary."

[0849] Input: Information submitted by the user

[0850] Output: Required legal verification items as analysis results

[0851] Step 3:

[0852] The emotion engine built into the server analyzes the emotional state.

[0853] An emotion engine (e.g., Microsoft Azure Emotion API) analyzes a user's emotional state based on received user input and behavioral data. This helps determine whether the user is experiencing stress or distress.

[0854] Input: User input information and behavioral data

[0855] Output: Data on the user's emotional state

[0856] Step 4:

[0857] The server generates a legal checklist.

[0858] Based on the analysis results, the server generates a list of necessary legal verification items. This list includes details of the relevant contact point and procedures for each item. For example, it might list items such as "Act against Unjustifiable Premiums and Misleading Representations: Confirm with the Marketing Department" and "Content of Description: Confirm with the Legal Department."

[0859] Input: Analysis results and emotional state data

[0860] Output: List of legal review items

[0861] Step 5:

[0862] The emotion engine adjusts the procedure.

[0863] The emotion engine adjusts the procedure based on the user's emotional state. For example, if the user is stressed, it might simplify the procedure, send a reminder, or add a support message.

[0864] Input: Data on the user's emotional state

[0865] Output: Adjusted legal confirmation procedure

[0866] Step 6:

[0867] The server displays the legal checklist on the user's terminal.

[0868] The server sends the generated legal checklist to the user's terminal for display. This list also reflects the results of adjustments made by the sentiment engine, such as simplified procedures, reminders, and support messages.

[0869] Input: Adjusted legal confirmation procedure

[0870] Output: Legal confirmation list displayed on the user terminal

[0871] Step 7:

[0872] The user performs the verification procedure.

[0873] The user will perform the necessary verification procedures based on the displayed legal checklist. For example, they might contact the marketing department to request verification regarding the Act against Unjustifiable Premiums and Misleading Representations.

[0874] Input: Legal confirmation list

[0875] Output: Implementation of verification procedure

[0876] Step 8:

[0877] The user enters the confirmation result as feedback and sends it to the server.

[0878] After completing the verification process, users enter the results into the system and send them to the server. Specifically, they access a web form for feedback, enter the results, and press the submit button.

[0879] Input: Enter confirmation result

[0880] Output: Sending confirmation results

[0881] Step 9:

[0882] The server receives the confirmation result.

[0883] The server receives the confirmation result sent by the user and retrieves the data necessary to proceed to the next step.

[0884] Input: Confirmation result

[0885] Output: Received confirmation result

[0886] Step 10:

[0887] The server saves and updates the verification results.

[0888] The server saves the received confirmation results to a database and updates it with the latest information. For example, it saves them to a database such as MySQL or PostgreSQL.

[0889] Input: Confirmation result received

[0890] Output: Verification results saved in the database

[0891] Step 11:

[0892] The server displays update information on the user's terminal.

[0893] The server displays the updated confirmation status on the user's device. The user receives a confirmation completion message and information about the next steps.

[0894] Input: Verification results stored in the database

[0895] Output: Update information displayed on the user's terminal

[0896] (Application Example 2)

[0897] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0898] The implementation and management of modern security systems involve numerous legal review procedures, which are complex and place a significant burden on users. Furthermore, user emotional states (e.g., confusion, stress) can reduce the efficiency of these procedures. Therefore, it is necessary to enable users to conduct legal review efficiently.

[0899] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0900] In this invention, the server includes means for the user to input a creation and its purpose; means for the server to analyze the input information and identify necessary legal verification items; means for the server to present corresponding verification windows and procedures for each identified legal verification item; means for an emotion analysis engine to analyze the user's emotional state and adjust the procedure; means for the user to provide feedback on the legal verification results; and means for the server to receive, save, and update the feedback. This makes it possible to perform legal verification efficiently while taking the user's emotional state into consideration.

[0901] A "user" is an individual or company that uses the system.

[0902] "Created work" refers to a system, software, or other technical device that the user intends to create or implement.

[0903] "Purpose" refers to the main reason or goal for a user to use the creation.

[0904] A "server" is a central processing unit that receives, analyzes, stores, and updates user input information.

[0905] "Means of analyzing information" refers to algorithms and programs used by a server to analyze information entered by a user and identify necessary legal verification items.

[0906] "Legal verification items" refer to matters that need to be verified based on laws and regulations related to a specific document or purpose.

[0907] A "confirmation desk" refers to a department or person responsible for handling or confirming specific legal confirmation items.

[0908] "Means for adjusting the procedure" refers to functions that allow the emotion analysis engine to adjust the flow and difficulty level of procedures presented based on the user's emotional state.

[0909] An "emotion analysis engine" is software or an algorithm used to identify and analyze a user's emotional state (e.g., stress, confusion).

[0910] "Feedback" refers to the act of a user entering the results of a verification process into the system and sending them to the server.

[0911] "Means of saving and updating" refers to the function of a server to save the feedback it receives in a database and update the information to the latest version based on that data.

[0912] This invention is a system that enables users to efficiently perform legal verification procedures related to the introduction and management of security systems. The system comprises a terminal used by the user, a server for analyzing information, an emotion analysis engine for recognizing the user's emotional state, and means for managing feedback from the legal verification procedures.

[0913] The server integrates multiple functions, receiving and analyzing information about creations and their purpose entered by the user via the terminal. Based on the input information, it identifies necessary legal verification items and presents the corresponding verification channels and procedures. Furthermore, it incorporates an emotion analysis engine that analyzes the user's emotional state based on their input behavior and adjusts the procedure accordingly. For example, if the user is experiencing stress, the server simplifies the procedure and sends a reminder.

[0914] The sentiment analysis engine is installed on devices such as smartphones, tablets, smart glasses (e.g., Google Glass), and head-mounted displays (e.g., Microsoft HoloLens). This allows for the adjustment of procedures based on the user's emotional state. The server interacts with web servers such as Apache HTTP Server and databases such as MySQL to analyze input information and perform internal processing. Furthermore, sentiment analysis engines such as IBM Watson Tone Analyzer are used for sentiment analysis.

[0915] For example, if a user plans to install a new surveillance camera system with the goal of enhancing office security, the server receiving the input information will identify relevant legal verification items (e.g., GDPR compliance). The sentiment analysis engine will analyze the user's emotional state, and if it detects that the user is experiencing stress or confusion, it will provide a supportive message with a clear explanation to simplify the process. After the user has confirmed with the relevant legal and technical departments, the results are fed back into the system, the server updates the database, and a confirmation message is displayed to the user.

[0916] Specific examples of input prompts for a generative AI model:

[0917] The purpose of introducing the new surveillance camera system is to enhance office security. Legal compliance checks related to GDPR are required. Please simplify the workflow, taking into consideration any potential user confusion.

[0918] In this way, users can efficiently conduct legal reviews in a manner that takes their emotional state into consideration, and the security system implementation process can proceed smoothly.

[0919] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0920] Step 1:

[0921] The user enters information into the input form.

[0922] The user uses a device (smartphone, tablet, etc.) to input the creation (e.g., a surveillance camera system) and its purpose (e.g., enhancing office security). The input data includes the specific type and purpose of the system.

[0923] Step 2:

[0924] The server receives and analyzes the input information.

[0925] The server receives information sent by the user and begins analysis. Using the input data, it identifies the necessary legal verification items (e.g., GDPR-related verifications). At this stage, the server analyzes the data received from the frontend in the backend and extracts the appropriate legal verification items. Specifically, it analyzes the input data using natural language processing (NLP) algorithms.

[0926] Step 3:

[0927] The emotion analysis engine analyzes the user's emotions.

[0928] A sentiment analysis engine embedded in the server analyzes the user's emotional state from user input information and interactions. For example, it can detect signs of confusion or stress from input speed and content. Input includes user input actions and text information, while output generates emotional state evaluation data. Specifically, it uses sentiment analysis engines such as IBM Watson Tone Analyzer.

[0929] Step 4:

[0930] The server generates a legal checklist.

[0931] Based on the analysis results obtained in the previous step, the server generates a list of necessary legal confirmation items. This list includes the corresponding contact point and procedure for each item. The inputs are the data for the legal confirmation items and the sentiment analysis results, and the output is the generated legal confirmation list. Specifically, it retrieves relevant information from the database and compiles instructions for the user in a list format.

[0932] Step 5:

[0933] The emotion analysis engine adjusts the procedure.

[0934] The emotion analysis engine adjusts the procedure based on the user's emotional state. For example, if the user is stressed, it simplifies the procedure and sends reminders and support messages. The input is emotional state evaluation data, and the output is the generated adjusted procedure. Specifically, it dynamically changes the content displayed in the user interface and the content of messages.

[0935] Step 6:

[0936] The server displays a legal review list.

[0937] The server displays a refined legal checklist on the user's terminal. The user is then guided through the process, with adjustments made by the sentiment analysis engine reflected in the content. This step generates a refined legal checklist as input and display data on the terminal as output. Specifically, the list content is displayed on the user interface via a web page or application interface.

[0938] Step 7:

[0939] The user performs the verification procedure.

[0940] The user follows the displayed instructions and completes the verification process at each relevant department. For example, they might contact the legal or technical department to obtain the necessary verifications. The input is a displayed legal verification list, and the output is a status indicating that the verification process has been completed. Specifically, they contact each department using email or internal tools.

[0941] Step 8:

[0942] The user provides feedback on the verification results.

[0943] The user enters their results into a form to provide feedback to the system and sends it to the server. The server receives the confirmation result data as input and the feedback data as output. Specifically, a web form or application feedback screen is used.

[0944] Step 9:

[0945] The server receives the confirmation result.

[0946] The server receives the confirmation result sent by the user and proceeds to the next process. The input is feedback data, and the output is the reception status. Specifically, it performs parsing processing to register the received data in the database.

[0947] Step 10:

[0948] The server saves and updates the verification results.

[0949] The server saves the verification results to the database and updates that information to the latest version. The input is the received feedback data, and the output is the updated database information. Specifically, the database update process is performed using SQL queries.

[0950] Step 11:

[0951] The server displays update information.

[0952] The server updates the user's confirmation status and displays the progress on the terminal. The input is the updated database information, and the output is the status display data. Specifically, it displays information about the progress and the next steps to the user on the screen.

[0953] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0954] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0955] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0956] [Third Embodiment]

[0957] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0958] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0959] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0960] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0961] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0962] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0963] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0964] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0965] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0966] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0967] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0968] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0969] This invention is a system that allows users to input a creation and its purpose, and then efficiently perform the necessary legal checks based on that input. This system analyzes the input information and centrally manages multiple checkpoints and procedures, thereby reducing the burden on the user and improving the efficiency of the check process.

[0970] System Overview

[0971] This system includes a server that analyzes information provided by the user, a terminal where the user inputs information, and means for managing feedback.

[0972] Program processing

[0973] 1. The user enters information into the input form.

[0974] The user accesses a web form and enters the creation (e.g., a website) and its purpose (e.g., marketing).

[0975] 2. The server receives and analyzes the input information.

[0976] The server receives and analyzes information sent by the user. Based on the input information, it identifies the necessary legal verification items. For example, if the user enters "Website creation, purpose is marketing," then verification of the Act against Unjustifiable Premiums and Misleading Representations, privacy policy, and terms of service will be required.

[0977] 3. The server generates a legal checklist.

[0978] The server generates a legal checklist based on the analysis results, listing the corresponding contact point and procedure for each item. For example, it displays "Confirm with the Marketing Department" for the Act against Unjustifiable Premiums and Misleading Representations, "Confirm with the Legal Department" for the Privacy Policy, and "Confirm with the Legal Department regarding the content" for the content of the document.

[0979] 4. Provide the user with confirmation steps.

[0980] The server generates a legal checklist and procedures, which are then displayed on the user's terminal. This allows the user to review the specific steps and required documents for each check item and take action themselves.

[0981] 5. The user performs the verification.

[0982] The user will follow the instructions provided and carry out the necessary verification procedures at each stage. For example, the user will contact the marketing department to confirm compliance with the Act against Unjustifiable Premiums and Misleading Representations.

[0983] 6. The user provides feedback on the verification results.

[0984] The user enters their results into a form to provide feedback to the system and sends it to the server.

[0985] 7. The server saves and updates the results.

[0986] The server saves the confirmation results received from the user to a database and updates the status on the system. This allows the user to track the progress of the confirmation process in real time.

[0987] Specific example

[0988] 1. Example: Confirmation under the Act against Unjustifiable Premiums and Misleading Representations

[0989] User input: "Website creation, purpose is marketing."

[0990] Server analysis: The server determined that "confirmation regarding the Act against Unjustifiable Premiums and Misleading Representations is required."

[0991] Server generation list: "Act against Unjustifiable Premiums and Misleading Representations: Confirm with Marketing Department" "Content of Description: Confirm with Legal Department" "Internal Confirmation: Confirm with ISC"

[0992] User verification: The user contacts the marketing and legal departments to obtain the necessary verifications.

[0993] Result Feedback: The user enters the results into the system.

[0994] Server save and display: The server saves the results to the database and displays a confirmation completion message to the user.

[0995] 2. Example: Checking the Privacy Policy

[0996] User input: "I'm creating a mobile app; the purpose is data collection."

[0997] Server analysis: The server determined that "confirmation of the privacy policy is required."

[0998] Server generation list: "Privacy Policy: Confirm with Legal Department" "Data Collection Details: Confirm with Data Department"

[0999] User verification: The user contacts the legal department and the data department to obtain the necessary verifications.

[1000] Result Feedback: The user enters the results into the system.

[1001] Server save and display: The server saves the results to the database and displays a confirmation completion message to the user.

[1002] This system allows users to centrally manage and efficiently process multiple legal verification procedures. This significantly improves the efficiency and accuracy of the verification process.

[1003] The following describes the processing flow.

[1004] Step 1:

[1005] The user accesses the input form. Through a web browser, the user accesses the system's input form and enters the creation (e.g., website) and its purpose (e.g., marketing).

[1006] Step 2:

[1007] The user enters information. The user fills in the necessary information in the input form, such as "Development = Website" and "Purpose = Marketing."

[1008] Step 3:

[1009] The user clicks the submit button. When the user clicks the submit button, the entered information is sent to the server.

[1010] Step 4:

[1011] The server receives the input information. The server receives the information sent by the user and prepares it for analysis.

[1012] Step 5:

[1013] The server analyzes the input information. The server uses a natural language processing algorithm to analyze the received information. Based on the analysis results, it identifies the necessary legal compliance items (e.g., the Act against Unjustifiable Premiums and Misleading Representations, privacy policy, etc.).

[1014] Step 6:

[1015] The server generates a legal checklist. Based on the analysis results, the server generates a list of necessary legal check items. For each item, it lists the corresponding contact point and procedure.

[1016] Step 7:

[1017] The server displays a legal confirmation list. The server displays the generated legal confirmation list on the user's terminal. The list includes details of each confirmation contact and procedure.

[1018] Step 8:

[1019] The user performs the verification procedure. Based on the instructions provided by the server, the user completes the necessary verification procedures at each relevant contact point. For example, they might request the marketing department to verify compliance with the Act against Unjustifiable Premiums and Misleading Representations.

[1020] Step 9:

[1021] The user collects the verification results. The user receives feedback from the verification channel and prepares to return it to the system.

[1022] Step 10:

[1023] The user provides feedback on the verification results. The user enters the verification results into the feedback form and submits it to the system.

[1024] Step 11:

[1025] The server receives the confirmation result. The server receives the confirmation result sent by the user and proceeds to the next step.

[1026] Step 12:

[1027] The server saves the verification results. The server saves the verification results to a database and updates that information to the latest version.

[1028] Step 13:

[1029] The server displays update information. The server updates the user's confirmation status and displays the progress on the terminal. The user receives a confirmation message and information about the next steps.

[1030] In this way, users can efficiently manage various legal checks and complete the necessary procedures.

[1031] (Example 1)

[1032] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1033] Traditional legal verification processes are complex and time-consuming, requiring the individual management of multiple verification channels and procedures. Maintaining accuracy and efficiency is also difficult. This is especially true when legal regulations are diverse and require coordination across various departments. An efficient, centralized system is needed to address these problems.

[1034] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1035] In this invention, the server includes means for the user to input a creation and its purpose; means for the server to receive and analyze the input information and identify necessary legal confirmation items; means for the server to generate a legal confirmation list based on the analysis results using a generation AI model; means for the server to list the corresponding confirmation contacts and procedures for each identified legal confirmation item; means for the user to display the confirmation procedure and provide feedback on the legal confirmation results; and means for the server to receive, save, and update the feedback. This makes it possible to efficiently centrally manage legal confirmation procedures and track the progress of confirmation work in real time.

[1036] A "user" is anyone who accesses this system and enters information about their creations and their purpose.

[1037] A "server" is a device that receives and analyzes information sent by users, identifies necessary legal verification items, and generates and manages legal verification lists.

[1038] "Created works" refers to deliverables such as websites and mobile applications created by users.

[1039] "Purpose" refers to the role or use that the creation is intended to fulfill, and includes, for example, marketing and data collection.

[1040] "Legal confirmation items" refer to items related to the creation of a document that require legal confirmation, and specifically include the Premiums and Representations Act and privacy policies.

[1041] A "generative AI model" is a type of artificial intelligence used to analyze input information and identify legal compliance items.

[1042] The "Legal Confirmation List" is a list of the corresponding confirmation contacts and procedures for each legal confirmation item, generated by the server based on the analysis results.

[1043] A "confirmation desk" refers to the department or person responsible for confirming legal compliance items.

[1044] "Procedures" refer to the specific actions and tasks required in response to legal verification items.

[1045] "Feedback" refers to the user submitting legal review results to the system.

[1046] Modes for carrying out the invention

[1047] This invention is a system that allows users to input a creation and its purpose, and then analyzes that input information to efficiently perform necessary legal checks. By analyzing the input information and centrally managing multiple checkpoints and procedures, this system reduces the burden on the user and improves the efficiency of the check process.

[1048] System Configuration

[1049] This system consists mainly of the following elements.

[1050] 1. A terminal where the user enters information.

[1051] 2. A server that receives and analyzes information sent by the user.

[1052] 3. Generative AI models within the server

[1053] 4. Legal confirmation list generated on the server

[1054] 5. Means for users to provide feedback

[1055] 6. Database to receive, store, and update feedback

[1056] The user is using a terminal to enter information.

[1057] Users access a web form and enter information about their creation (e.g., a website) and its purpose (e.g., marketing). This data is then sent to the system.

[1058] The server receives and analyzes the input information.

[1059] The server receives information sent by the user. It then analyzes the input information using a generation AI model and identifies the necessary legal checks based on the entered data. For example, if the user enters "Website creation, purpose is marketing," the server will determine that checks on the Premiums and Representations Act and the privacy policy are necessary.

[1060] Legal confirmation list generated on the server

[1061] The server generates a legal checklist based on the analysis results, listing the necessary contact points and procedures. For example, it includes specific instructions such as "Confirm with the Marketing Department" for the Premiums and Representations Act and "Confirm with the Legal Department" for the Privacy Policy.

[1062] Provide the user with a verification procedure.

[1063] The server displays the generated legal checklist on the user's terminal. The user reviews it and follows the instructions to perform the necessary legal checks. Specifically, they request the marketing department to review the Premiums and Representations Act and the legal department to review the privacy policy.

[1064] The user provides feedback on the verification results.

[1065] The user enters the results into a dedicated form within the system to provide feedback on the verification process. This information is then sent to the server.

[1066] The server saves and updates the results.

[1067] The server saves the confirmation results received from the user to the database and updates the status on the system. This allows the user to track the progress of the confirmation process in real time.

[1068] Specific example

[1069] Example 1: Confirmation of the Premiums and Representations Act

[1070] User input: "Website creation, purpose is marketing."

[1071] Server analysis: The server determines that "confirmation regarding the Premiums and Representations Act is required."

[1072] Server generation list: "Act against Unjustifiable Premiums and Misleading Representations: Confirm with Marketing Department" "Contents of Description: Confirm with Legal Department"

[1073] User verification: The user contacts the marketing and legal departments to complete any necessary verifications.

[1074] Result Feedback: The user enters the results into the system.

[1075] Server save and display: The server saves the results to the database and displays a confirmation message to the user.

[1076] Example 2: Checking the Privacy Policy

[1077] User input: "I'm creating a mobile app; the purpose is data collection."

[1078] Server analysis: The server determines that "confirmation of the privacy policy is required."

[1079] Server generation list: "Privacy Policy: Confirm with Legal Department" "Data Collection Details: Confirm with Data Department"

[1080] User verification: The user contacts the legal department and the data department to perform the necessary verifications.

[1081] Result Feedback: The user enters the results into the system.

[1082] Server save and display: The server saves the results to the database and displays a confirmation message to the user.

[1083] This system allows users to centrally manage and efficiently process multiple legal verification procedures. This significantly improves the efficiency and accuracy of the verification process.

[1084] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1085] Step 1:

[1086] A user accesses a web form and enters information about their creation (e.g., a website) and its purpose (e.g., marketing). The entered information is sent from the user's device to the server. This input information becomes the basis for subsequent processing.

[1087] Step 2:

[1088] The server receives information sent by the user. After receiving the information, the server analyzes the input data using a generative AI model. The information extracted through this analysis is used to identify subsequent legal review items. Specifically, it performs natural language processing to understand the intent of the user's input.

[1089] Step 3:

[1090] The server identifies the necessary legal checks based on the analysis results. For example, if the analysis indicates "website creation, purpose is marketing," the server will identify the need to check the Premiums and Representations Act and the privacy policy. The output of this step is a list of the specific legal items that need to be checked.

[1091] Step 4:

[1092] For each legal verification item identified by the server, a list of the corresponding verification contacts and procedures is created. This list includes instructions on which department to contact for each item. For example, "Confirm the Premiums and Representations Act with the Marketing Department" or "Confirm the Privacy Policy with the Legal Department."

[1093] Step 5:

[1094] The server generates a legal checklist, which is then displayed on the user's terminal. By reviewing this list, the user can learn about the necessary procedures. The output specifically shows the checklist items, their corresponding contact points, and detailed steps.

[1095] Step 6:

[1096] The user will conduct legal checks following the provided procedures. The user will contact each department based on the list and request the necessary checks. For example, the user might request the marketing department to check the Premiums and Representations Act and the legal department to check the privacy policy.

[1097] Step 7:

[1098] The user enters the results of the legal review into a dedicated form within the system to provide feedback. This information is then sent back to the server. The results entered by the user become the input data for this step.

[1099] Step 8:

[1100] The server saves the confirmation results received from the user to a database. Furthermore, it updates the status of the confirmation items and displays the progress on the system. This allows users to track the progress of their confirmation work in real time.

[1101] This series of processing steps allows users to efficiently complete legal verification procedures. Furthermore, the ability to manage the progress of the verification process within the system significantly improves the efficiency and accuracy of the verification work.

[1102] (Application Example 1)

[1103] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1104] Online platforms such as virtual stores require the efficient management of numerous legal verification items and the rapid coordination of verification processes with multiple contact points. Furthermore, tracking the progress and deadlines of these verification processes is often difficult, placing a significant burden on users. A comprehensive system is needed to address these issues.

[1105] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1106] In this invention, the server includes means for the user to input a creation and its purpose; means for the server to analyze the input information and identify necessary legal verification items; means for the server to present corresponding verification contacts and procedures for each identified legal verification item; means for the user to provide feedback on the legal verification results; means for the server to receive, save, and update the feedback; means for tracking the progress of the legal verification work; and means for notifying the user of the deadline and progress of the verification procedures. This enables the user to efficiently carry out legal verification work and appropriately manage progress and deadlines.

[1107] A "user" is an end-user who uses the system to input creations and their purposes.

[1108] "Created works" refer to specific projects, products, or services that users input.

[1109] "Purpose" refers to the achievement goals or intentions related to the creation.

[1110] "Means" refers to methods or mechanisms for performing a specific function or role.

[1111] A "server" refers to a computer system that receives, analyzes, stores, and manages information entered by users.

[1112] "Legal confirmation items" refer to legal confirmation matters necessary in relation to the created document and its purpose.

[1113] A "confirmation desk" refers to the contact point or department necessary to address specific legal confirmation items.

[1114] "Procedure" refers to the specific actions and steps required to confirm and approve certain legal verification items.

[1115] "Feedback" refers to the act of reporting the results and progress of legal checks performed by users to the server.

[1116] "Updating" refers to the act of updating data to the latest state based on information received by the server.

[1117] "Progress" refers to the status of the legal review process.

[1118] "Notifications" refer to alerts or messages that inform users about deadlines and progress of verification procedures.

[1119] This invention is a system for efficiently performing legal verification work. The system is designed so that the user inputs a creation and its purpose, and the server then performs the necessary legal verification based on that input. The following details specific embodiments of this system.

[1120] Hardware and software configuration

[1121] Hardware:

[1122] Server: Cloud servers such as AWS EC2 are used to process data, including receiving, analyzing, storing, and updating it.

[1123] User terminal: A device such as a smartphone, PC, or tablet used by the user to input information and check the results.

[1124] software:

[1125] Framework: Implement the server analysis module using Python.

[1126] Database: MySQL is used to store legal review results and progress data.

[1127] Frontend: Build the user interface using React.js.

[1128] Data processing and computation

[1129] Data entry and analysis:

[1130] User Terminal: Users enter their creation and its purpose through a web form. For example, they might enter "Type of virtual store: Health food sales, Purpose: Promotional campaign."

[1131] Server: Analyzes the received input data and identifies the necessary legal verification items. Based on the analysis results, it generates a verification list and displays it to the user.

[1132] Verification steps and feedback:

[1133] User: Follow the provided verification steps, complete the necessary verification procedures, and enter the results into the feedback form.

[1134] Server: Receives feedback and stores it in the database. Updates progress in real time and notifies the user.

[1135] Specific example

[1136] User input: "Virtual store type: Health food sales, Purpose: Promotional campaign"

[1137] Analysis results: The server determined that it was necessary to "check the Premiums and Representations Act" and "check the Privacy Policy".

[1138] Verification procedure: The server will provide users with specific contact points and procedures for "confirmation regarding the Premiums and Representations Act" and "confirmation regarding the Privacy Policy."

[1139] Feedback: The user enters the confirmation result, and the server saves the progress to the database.

[1140] Notification: The server sends alerts to the user regarding legal review deadlines and progress.

[1141] Example of a prompt

[1142] Virtual store type: Health food sales, Purpose: Promotional campaign

[1143] This system allows users to efficiently carry out legal review work and properly manage progress and deadlines.

[1144] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1145] Step 1:

[1146] The user enters information. The user uses a device to access a web form and enters information about the creation (e.g., a virtual store) and its purpose (e.g., a promotional campaign). This entered information is sent to the server.

[1147] Input: The user enters "Virtual store type: Health food sales, Purpose: Promotional campaign" into the input form.

[1148] Output: User input data is sent to the server.

[1149] Specific operation: The user accesses a web form from a device such as a smartphone or PC, enters the required information, and presses the submit button. This information is sent to the server.

[1150] Step 2:

[1151] The server analyzes the input information. The server analyzes the received input information and identifies the necessary legal verification items. A generative AI model can be used for this analysis.

[1152] Input: The server receives user input data.

[1153] Output: The server identifies the legal items that need to be checked (e.g., "Check the Premiums and Representations Act," "Check the Privacy Policy").

[1154] Specific operation: The server passes the received data to the analysis module, which uses the generated AI model to identify the necessary legal verification items.

[1155] Step 3:

[1156] The server generates a legal confirmation list. Based on the analysis results, the server lists the corresponding confirmation contacts and procedures for each required legal confirmation item.

[1157] Input: Legal verification items identified by the server.

[1158] Output: The server generates a confirmation list and displays it on the user's terminal (e.g., "Confirmation of Premiums and Representations Act: Contact Legal Department", "Confirmation of Privacy Policy: Contact Data Department").

[1159] Specific operation: The server identifies the contact point and procedure corresponding to each item based on the legal verification items, and generates a verification list.

[1160] Step 4:

[1161] The user performs the verification procedure. The user follows the provided verification steps and completes the necessary verification procedures.

[1162] Input: Confirmation list displayed from the server.

[1163] Output: The user provides feedback on the results for each verification item (e.g., "Confirmation of Premiums and Representations Act: Completed," "Confirmation of Privacy Policy: Pending").

[1164] Specific actions: The user contacts the relevant departments, such as the legal department or data department, completes the necessary verification procedures, and enters the results into the system.

[1165] Step 5:

[1166] The server receives, stores, and updates feedback. The server receives user feedback, stores it in the database, and updates the system status.

[1167] Input: Confirmation result entered by the user.

[1168] Output: The server saves the verification results to the database and updates the system status.

[1169] Specific operation: The server receives feedback data sent by the user, saves it to the database, and updates the confirmation status in real time.

[1170] Step 6:

[1171] The server tracks progress and provides notifications. The server periodically tracks the progress of legal review work and sends necessary notifications to the user (e.g., deadlines for review procedures, progress status).

[1172] Input: Updated confirmation status.

[1173] Output: Sends notifications to the user's terminal regarding progress and deadlines.

[1174] Specific operation: The server periodically checks the database information, generates notifications based on progress and deadlines for verification procedures, and sends alerts to the user.

[1175] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1176] This invention is a system that allows users to input a creation and its purpose, and then efficiently performs the necessary legal checks based on that input. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides a more flexible and adaptable check procedure.

[1177] System Overview

[1178] This system includes a server that analyzes information provided by the user, a terminal where the user inputs information, an emotion engine that recognizes the user's emotional state, and means for managing feedback.

[1179] Program processing

[1180] 1. The user enters information into the input form.

[1181] The user accesses a web form and enters the creation (e.g., a website) and its purpose (e.g., marketing).

[1182] 2. The server receives and analyzes the input information.

[1183] The server receives and analyzes information sent by the user. Based on the input information, it identifies necessary legal compliance items (e.g., the Act against Unjustifiable Premiums and Misleading Representations, privacy policy, etc.).

[1184] 3. The emotion engine analyzes the user's emotions.

[1185] An emotion engine embedded in the server analyzes the user's emotional state from their input information and actions. This allows it to recognize emotions such as stress and confusion.

[1186] 4. The server generates a legal checklist.

[1187] The server generates a list of necessary legal verification items based on the analysis results. For each item, it lists the corresponding verification contacts and procedures.

[1188] 5. The emotion engine adjusts the procedural methods.

[1189] The emotion engine adjusts the priority and method of procedures based on the user's emotional state. For example, if the user is stressed, it may simplify procedures or send reminders and support messages.

[1190] 6. The server displays the legal confirmation list.

[1191] The server generates a legal review list, which is then displayed on the user's terminal. Adjustments made by the emotion engine are reflected in this list.

[1192] 7. The user completes the verification process.

[1193] The user will follow the instructions provided and complete the necessary verification procedures at each relevant department. For example, they might request the marketing department to verify compliance with the Act against Unjustifiable Premiums and Misleading Representations.

[1194] 8. The user provides feedback on the verification results.

[1195] The user enters their results into a form to provide feedback to the system and sends it to the server.

[1196] 9. The server receives the confirmation result.

[1197] The server receives the confirmation result sent by the user and proceeds to the next step.

[1198] 10. The server saves and updates the verification results.

[1199] The server saves the verification results to a database and updates that information to the latest version.

[1200] 11. The server displays update information.

[1201] The server updates the user's verification status and displays the progress on the terminal. The user receives a message confirming verification and information about the next steps.

[1202] Specific example

[1203] 1. Verification of the Act against Unjustifiable Premiums and Misleading Representations using an emotional engine.

[1204] User input: "Website creation, purpose is marketing."

[1205] Server analysis: The server determined that "confirmation regarding the Act against Unjustifiable Premiums and Misleading Representations is required."

[1206] Emotional Engine Analysis: Detects when a user is experiencing stress while submitting input information.

[1207] Server generation list: "Act against Unjustifiable Premiums and Misleading Representations: Confirm with Marketing Department" "Content of Description: Confirm with Legal Department" "Internal Confirmation: Confirm with ISC"

[1208] Emotional Engine Tuning: Send reminders with simplified instructions.

[1209] User verification: The user contacts the marketing and legal departments to obtain the necessary verifications.

[1210] Result Feedback: The user enters the results into the system.

[1211] Server save and display: The server saves the results to the database and displays a confirmation completion message to the user.

[1212] 2. Reviewing the Privacy Policy using an Emotion Engine

[1213] User input: "I'm creating a mobile app; the purpose is data collection."

[1214] Server analysis: The server determined that "confirmation of the privacy policy is required."

[1215] Emotional Engine Analysis: Detects when a user is feeling confused while proceeding with the verification process.

[1216] Server generation list: "Privacy Policy: Confirm with Legal Department" "Data Collection Details: Confirm with Data Department"

[1217] Emotional Engine Adjustment: Displays clear explanations and support messages.

[1218] User verification: The user contacts the legal department and the data department to obtain the necessary verifications.

[1219] Result Feedback: The user enters the results into the system.

[1220] Server save and display: The server saves the results to the database and displays a confirmation completion message to the user.

[1221] This system allows users to centrally manage and efficiently process multiple legal verification procedures. The introduction of an emotion engine enables flexible responses tailored to the user's emotional state, reducing the burden of verification work.

[1222] The following describes the processing flow.

[1223] Step 1:

[1224] The user accesses the input form. Through a web browser, the user accesses the system's input form and enters the creation (e.g., website) and its purpose (e.g., marketing).

[1225] Step 2:

[1226] The user enters information. The user fills in the necessary information in the input form, such as "Development = Website" and "Purpose = Marketing."

[1227] Step 3:

[1228] The user clicks the submit button. When the user clicks the submit button, the entered information is sent to the server.

[1229] Step 4:

[1230] The server receives the input information. The server receives the information sent by the user and prepares it for analysis.

[1231] Step 5:

[1232] The server analyzes the input information. The server uses a natural language processing algorithm to analyze the received information. Based on the analysis results, it identifies the necessary legal compliance items (e.g., the Act against Unjustifiable Premiums and Misleading Representations, privacy policy, etc.).

[1233] Step 6:

[1234] The emotion engine analyzes the user's emotions. The emotion engine, embedded in the server, analyzes the emotional state from the input information and the user's actions.

[1235] Step 7:

[1236] The server generates a legal checklist. Based on the analysis results, the server generates a list of necessary legal check items. For each item, it lists the corresponding contact point and procedure.

[1237] Step 8:

[1238] The emotion engine adjusts the procedure. The emotion engine adjusts the priority and method of procedures based on the user's emotional state. For example, if the user is stressed, it might simplify the procedure or send reminders and support messages.

[1239] Step 9:

[1240] The server displays the legal checklist. The server-generated legal checklist is displayed on the user's terminal. Details of the coordinated procedures and required documents are displayed.

[1241] Step 10:

[1242] The user performs the verification procedure. The user follows the instructions provided and completes the necessary verification procedures at each relevant department. For example, they might request the marketing department to verify compliance with the Act against Unjustifiable Premiums and Misleading Representations.

[1243] Step 11:

[1244] The user collects the verification results. The user collects feedback results from each verification channel and verifies the content themselves.

[1245] Step 12:

[1246] The user provides feedback on the verification results. The user enters the verification results into the feedback form and sends it to the server.

[1247] Step 13:

[1248] The server receives the confirmation result. The server receives the confirmation result sent by the user and proceeds to the next step.

[1249] Step 14:

[1250] The server saves the verification results. The server records the received verification results in the database and updates the progress of the verification process.

[1251] Step 15:

[1252] The server displays update information. The server updates the user's confirmation status and displays the progress on the user's device. The user receives a confirmation message and information about the next steps.

[1253] This system allows users to efficiently manage legal verification procedures, and by using an emotion engine, it enables flexible responses tailored to the user's emotional state.

[1254] (Example 2)

[1255] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1256] The current legal review system has problems such as making procedures stressful and inefficient because it does not take into account the user's emotional state. In addition, there is no way to centrally manage multiple legal reviews and properly track their progress, making it difficult for users to proceed with the procedures smoothly.

[1257] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1258] In this invention, the server includes means for the user to input a creation and its purpose; means for the server to analyze the input information and identify necessary legal confirmation items; means for the server to analyze the user's emotional state; means for the server to present corresponding confirmation windows and procedures for each identified legal confirmation item; means for the server to adjust the priority and procedures of legal confirmation procedures according to the user's emotional state; means for the user to provide feedback on the legal confirmation results; and means for the server to receive, store, and update the feedback. This makes it possible to provide flexible legal confirmation procedures that take into account the user's emotional state and to improve the efficiency of the confirmation procedures.

[1259] "Created works" refers to all objects that users create and input into the system. Examples include websites and mobile applications.

[1260] "Purpose" refers to the intention or use that a user sets for their creation. Examples include marketing and data collection.

[1261] "Legal confirmation items" refer to the legal matters that need to be confirmed for the created document. For example, these include the Act against Unjustifiable Premiums and Misleading Representations and privacy policies.

[1262] A "confirmation desk" refers to the department or person in charge of handling legal confirmation items. For example, this could include the marketing department or the legal department.

[1263] "Procedures" refer to the steps and methods necessary to carry out legal verification. For example, this includes submitting documents and contacting the relevant personnel.

[1264] "Emotional state" refers to the emotional state a user exhibits while using the system. Examples include stress, confusion, and relief.

[1265] "Feedback" refers to the act of a user reporting the results of a legal review to the system. This includes, for example, reporting the progress and results of the review.

[1266] This invention is a system that allows users to input a creation and its purpose, and then efficiently performs the necessary legal checks based on that input. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides a more flexible and adaptable check procedure.

[1267] System Overview

[1268] This system includes a server that analyzes information provided by the user, a terminal where the user inputs information, an emotion engine that recognizes the user's emotional state, and means for managing feedback.

[1269] Hardware and software used

[1270] The main components of this system are as follows:

[1271] User devices (e.g., personal computers, smartphones)

[1272] Servers (e.g., AWS, Google Cloud)

[1273] Emotion engine (e.g., Microsoft Azure Emotion API)

[1274] Databases (e.g., MySQL, PostgreSQL)

[1275] System Functions

[1276] 1. Entering information

[1277] Users access the system's web form using devices such as PCs or smartphones and enter their creations and their purposes. For example, they access "https: / / example.com / form" using a browser and enter the necessary information using text boxes or dropdown menus.

[1278] 2. Information Reception and Analysis

[1279] The server analyzes the received information and identifies the necessary legal compliance items. This analysis is performed by a script running on the server side (e.g., Python or Node.js). Identified legal compliance items include compliance with the Act against Unjustifiable Premiums and Misleading Representations and privacy policies. Furthermore, an emotion engine (e.g., Microsoft Azure Emotion API) analyzes the user's input information and behavior to determine their emotional state, recognizing stress, confusion, etc.

[1280] 3. Generating a legal checklist

[1281] Based on the analysis results, the server generates a list of items requiring legal review. This list includes details of the corresponding review channels and procedures. The emotion engine adjusts the priority and method of the procedures according to the user's emotional state. For example, if the user is stressed, the procedures may be simplified or support messages added.

[1282] 4. Display and implementation of verification procedures

[1283] The server displays the generated legal checklist on the user's terminal, and the user performs the necessary checks according to the list. For example, they might contact the marketing department to request a check regarding the Act against Unjustifiable Premiums and Misleading Representations. Once the checks are complete, the user feeds the results back into the system and sends them to the server.

[1284] 5. Saving and updating verification results

[1285] The server receives the confirmation results sent by the user and stores them in the database. This updates the confirmation status, and the user's progress is displayed on the terminal. The user receives a confirmation completion message and information about the next steps.

[1286] Specific example

[1287] 1. Verification of the Act against Unjustifiable Premiums and Misleading Representations using an emotional engine.

[1288] User input: "Website creation, purpose is marketing."

[1289] Server analysis: The server determined that "confirmation regarding the Act against Unjustifiable Premiums and Misleading Representations is required."

[1290] Emotional Engine Analysis: Detects when a user is experiencing stress while submitting input information.

[1291] Server generation list: "Act against Unjustifiable Premiums and Misleading Representations: Confirm with Marketing Department", "Content of Description: Confirm with Legal Department", "Internal Confirmation: Confirm with General Affairs Department"

[1292] Emotional Engine Tuning: Send reminders with simplified steps.

[1293] User verification: The user contacts the marketing and legal departments to obtain the necessary verifications.

[1294] Result Feedback: Users enter their results into the system.

[1295] Server save and display: The server saves the results to the database and displays a confirmation message to the user.

[1296] 2. Reviewing the Privacy Policy using an Emotion Engine

[1297] User input: "I'm creating a mobile app; the purpose is data collection."

[1298] Server analysis: The server determined that "confirmation of the privacy policy is required."

[1299] Emotional Engine Analysis: Detects when a user is experiencing confusion while proceeding with the verification process.

[1300] Server generation list: "Privacy Policy: Confirm with Legal Department" "Data Collection Details: Confirm with Data Department"

[1301] Emotional Engine Adjustment: Displays clear explanations and support messages.

[1302] User verification: The user contacts the legal and data departments to obtain the necessary verifications.

[1303] Result Feedback: Users enter their results into the system.

[1304] Server save and display: The server saves the results to the database and displays a confirmation message to the user.

[1305] This system allows users to centrally manage and efficiently process multiple legal verification procedures. The introduction of an emotion engine enables flexible responses tailored to the user's emotional state, reducing the burden of verification work.

[1306] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1307] Step 1:

[1308] The user enters information on the device.

[1309] The user accesses the system's web form using their device and enters information about their creation and its purpose. Specifically, they access "https: / / example.com / form" using a browser and enter information such as "Website creation, purpose is marketing" into the text box. Once the input is submitted, the server receives the information.

[1310] Input: The user enters the creation and its purpose in the input form.

[1311] Output: The information entered by the user is sent to the server.

[1312] Step 2:

[1313] The server receives and analyzes the input information.

[1314] The server receives and analyzes information sent by the user. This analysis uses, for example, a Python script to identify the necessary legal checks based on the creation and purpose. For example, based on the purpose of "marketing," it might determine that "checking the Act against Unjustifiable Premiums and Misleading Representations is necessary."

[1315] Input: Information submitted by the user

[1316] Output: Required legal verification items as analysis results

[1317] Step 3:

[1318] The emotion engine built into the server analyzes the emotional state.

[1319] An emotion engine (e.g., Microsoft Azure Emotion API) analyzes a user's emotional state based on received user input and behavioral data. This helps determine whether the user is experiencing stress or distress.

[1320] Input: User input information and behavioral data

[1321] Output: Data on the user's emotional state

[1322] Step 4:

[1323] The server generates a legal checklist.

[1324] Based on the analysis results, the server generates a list of necessary legal verification items. This list includes details of the relevant contact point and procedures for each item. For example, it might list items such as "Act against Unjustifiable Premiums and Misleading Representations: Confirm with the Marketing Department" and "Content of Description: Confirm with the Legal Department."

[1325] Input: Analysis results and emotional state data

[1326] Output: List of legal review items

[1327] Step 5:

[1328] The emotion engine adjusts the procedure.

[1329] The emotion engine adjusts the procedure based on the user's emotional state. For example, if the user is stressed, it might simplify the procedure, send a reminder, or add a support message.

[1330] Input: Data on the user's emotional state

[1331] Output: Adjusted legal confirmation procedure

[1332] Step 6:

[1333] The server displays the legal checklist on the user's terminal.

[1334] The server sends the generated legal checklist to the user's terminal for display. This list also reflects the results of adjustments made by the sentiment engine, such as simplified procedures, reminders, and support messages.

[1335] Input: Adjusted legal confirmation procedure

[1336] Output: Legal confirmation list displayed on the user terminal

[1337] Step 7:

[1338] The user performs the verification procedure.

[1339] The user will perform the necessary verification procedures based on the displayed legal checklist. For example, they might contact the marketing department to request verification regarding the Act against Unjustifiable Premiums and Misleading Representations.

[1340] Input: Legal confirmation list

[1341] Output: Implementation of verification procedure

[1342] Step 8:

[1343] The user enters the confirmation result as feedback and sends it to the server.

[1344] After completing the verification process, users enter the results into the system and send them to the server. Specifically, they access a web form for feedback, enter the results, and press the submit button.

[1345] Input: Enter confirmation result

[1346] Output: Sending confirmation results

[1347] Step 9:

[1348] The server receives the confirmation result.

[1349] The server receives the confirmation result sent by the user and retrieves the data necessary to proceed to the next step.

[1350] Input: Confirmation result

[1351] Output: Received confirmation result

[1352] Step 10:

[1353] The server saves and updates the verification results.

[1354] The server saves the received confirmation results to a database and updates it with the latest information. For example, it saves them to a database such as MySQL or PostgreSQL.

[1355] Input: Confirmation result received

[1356] Output: Verification results saved in the database

[1357] Step 11:

[1358] The server displays update information on the user's terminal.

[1359] The server displays the updated confirmation status on the user's device. The user receives a confirmation completion message and information about the next steps.

[1360] Input: Verification results stored in the database

[1361] Output: Update information displayed on the user's terminal

[1362] (Application Example 2)

[1363] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1364] The implementation and management of modern security systems involve numerous legal review procedures, which are complex and place a significant burden on users. Furthermore, user emotional states (e.g., confusion, stress) can reduce the efficiency of these procedures. Therefore, it is necessary to enable users to conduct legal review efficiently.

[1365] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1366] In this invention, the server includes means for the user to input a creation and its purpose; means for the server to analyze the input information and identify necessary legal verification items; means for the server to present corresponding verification windows and procedures for each identified legal verification item; means for an emotion analysis engine to analyze the user's emotional state and adjust the procedure; means for the user to provide feedback on the legal verification results; and means for the server to receive, save, and update the feedback. This makes it possible to perform legal verification efficiently while taking the user's emotional state into consideration.

[1367] A "user" is an individual or company that uses the system.

[1368] "Created work" refers to a system, software, or other technical device that the user intends to create or implement.

[1369] "Purpose" refers to the main reason or goal for a user to use the creation.

[1370] A "server" is a central processing unit that receives, analyzes, stores, and updates user input information.

[1371] "Means of analyzing information" refers to algorithms and programs used by a server to analyze information entered by a user and identify necessary legal verification items.

[1372] "Legal verification items" refer to matters that need to be verified based on laws and regulations related to a specific document or purpose.

[1373] A "confirmation desk" refers to a department or person responsible for handling or confirming specific legal confirmation items.

[1374] "Means for adjusting the procedure" refers to functions that allow the emotion analysis engine to adjust the flow and difficulty level of procedures presented based on the user's emotional state.

[1375] An "emotion analysis engine" is software or an algorithm used to identify and analyze a user's emotional state (e.g., stress, confusion).

[1376] "Feedback" refers to the act of a user entering the results of a verification process into the system and sending them to the server.

[1377] "Means of saving and updating" refers to the function of a server to save the feedback it receives in a database and update the information to the latest version based on that data.

[1378] This invention is a system that enables users to efficiently perform legal verification procedures related to the introduction and management of security systems. The system comprises a terminal used by the user, a server for analyzing information, an emotion analysis engine for recognizing the user's emotional state, and means for managing feedback from the legal verification procedures.

[1379] The server integrates multiple functions, receiving and analyzing information about creations and their purpose entered by the user via the terminal. Based on the input information, it identifies necessary legal verification items and presents the corresponding verification channels and procedures. Furthermore, it incorporates an emotion analysis engine that analyzes the user's emotional state based on their input behavior and adjusts the procedure accordingly. For example, if the user is experiencing stress, the server simplifies the procedure and sends a reminder.

[1380] The sentiment analysis engine is installed on devices such as smartphones, tablets, smart glasses (e.g., Google Glass), and head-mounted displays (e.g., Microsoft HoloLens). This allows for the adjustment of procedures based on the user's emotional state. The server interacts with web servers such as Apache HTTP Server and databases such as MySQL to analyze input information and perform internal processing. Furthermore, sentiment analysis engines such as IBM Watson Tone Analyzer are used for sentiment analysis.

[1381] For example, if a user plans to install a new surveillance camera system with the goal of enhancing office security, the server receiving the input information will identify relevant legal verification items (e.g., GDPR compliance). The sentiment analysis engine will analyze the user's emotional state, and if it detects that the user is experiencing stress or confusion, it will provide a supportive message with a clear explanation to simplify the process. After the user has confirmed with the relevant legal and technical departments, the results are fed back into the system, the server updates the database, and a confirmation message is displayed to the user.

[1382] Specific examples of input prompts for a generative AI model:

[1383] The purpose of introducing the new surveillance camera system is to enhance office security. Legal compliance checks related to GDPR are required. Please simplify the workflow, taking into consideration any potential user confusion.

[1384] In this way, users can efficiently conduct legal reviews in a manner that takes their emotional state into consideration, and the security system implementation process can proceed smoothly.

[1385] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1386] Step 1:

[1387] The user enters information into the input form.

[1388] The user uses a device (smartphone, tablet, etc.) to input the creation (e.g., a surveillance camera system) and its purpose (e.g., enhancing office security). The input data includes the specific type and purpose of the system.

[1389] Step 2:

[1390] The server receives and analyzes the input information.

[1391] The server receives information sent by the user and begins analysis. Using the input data, it identifies the necessary legal verification items (e.g., GDPR-related verifications). At this stage, the server analyzes the data received from the frontend in the backend and extracts the appropriate legal verification items. Specifically, it analyzes the input data using natural language processing (NLP) algorithms.

[1392] Step 3:

[1393] The emotion analysis engine analyzes the user's emotions.

[1394] A sentiment analysis engine embedded in the server analyzes the user's emotional state from user input information and interactions. For example, it can detect signs of confusion or stress from input speed and content. Input includes user input actions and text information, while output generates emotional state evaluation data. Specifically, it uses sentiment analysis engines such as IBM Watson Tone Analyzer.

[1395] Step 4:

[1396] The server generates a legal checklist.

[1397] Based on the analysis results obtained in the previous step, the server generates a list of necessary legal confirmation items. This list includes the corresponding contact point and procedure for each item. The inputs are the data for the legal confirmation items and the sentiment analysis results, and the output is the generated legal confirmation list. Specifically, it retrieves relevant information from the database and compiles instructions for the user in a list format.

[1398] Step 5:

[1399] The emotion analysis engine adjusts the procedure.

[1400] The emotion analysis engine adjusts the procedure based on the user's emotional state. For example, if the user is stressed, it simplifies the procedure and sends reminders and support messages. The input is emotional state evaluation data, and the output is the generated adjusted procedure. Specifically, it dynamically changes the content displayed in the user interface and the content of messages.

[1401] Step 6:

[1402] The server displays a legal review list.

[1403] The server displays a refined legal checklist on the user's terminal. The user is then guided through the process, with adjustments made by the sentiment analysis engine reflected in the content. This step generates a refined legal checklist as input and display data on the terminal as output. Specifically, the list content is displayed on the user interface via a web page or application interface.

[1404] Step 7:

[1405] The user performs the verification procedure.

[1406] The user follows the displayed instructions and completes the verification process at each relevant department. For example, they might contact the legal or technical department to obtain the necessary verifications. The input is a displayed legal verification list, and the output is a status indicating that the verification process has been completed. Specifically, they contact each department using email or internal tools.

[1407] Step 8:

[1408] The user provides feedback on the verification results.

[1409] The user enters their results into a form to provide feedback to the system and sends it to the server. The server receives the confirmation result data as input and the feedback data as output. Specifically, a web form or application feedback screen is used.

[1410] Step 9:

[1411] The server receives the confirmation result.

[1412] The server receives the confirmation result sent by the user and proceeds to the next process. The input is feedback data, and the output is the reception status. Specifically, it performs parsing processing to register the received data in the database.

[1413] Step 10:

[1414] The server saves and updates the verification results.

[1415] The server saves the verification results to the database and updates that information to the latest version. The input is the received feedback data, and the output is the updated database information. Specifically, the database update process is performed using SQL queries.

[1416] Step 11:

[1417] The server displays update information.

[1418] The server updates the user's confirmation status and displays the progress on the terminal. The input is the updated database information, and the output is the status display data. Specifically, it displays information about the progress and the next steps to the user on the screen.

[1419] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1420] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1421] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1422] [Fourth Embodiment]

[1423] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1424] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1425] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1426] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1427] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1428] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1429] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1430] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1431] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1432] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1433] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1434] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1435] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1436] This invention is a system that allows users to input a creation and its purpose, and then efficiently perform the necessary legal checks based on that input. This system analyzes the input information and centrally manages multiple checkpoints and procedures, thereby reducing the burden on the user and improving the efficiency of the check process.

[1437] System Overview

[1438] This system includes a server that analyzes information provided by the user, a terminal where the user inputs information, and means for managing feedback.

[1439] Program processing

[1440] 1. The user enters information into the input form.

[1441] The user accesses a web form and enters the creation (e.g., a website) and its purpose (e.g., marketing).

[1442] 2. The server receives and analyzes the input information.

[1443] The server receives and analyzes information sent by the user. Based on the input information, it identifies the necessary legal verification items. For example, if the user enters "Website creation, purpose is marketing," then verification of the Act against Unjustifiable Premiums and Misleading Representations, privacy policy, and terms of service will be required.

[1444] 3. The server generates a legal checklist.

[1445] The server generates a legal checklist based on the analysis results, listing the corresponding contact point and procedure for each item. For example, it displays "Confirm with the Marketing Department" for the Act against Unjustifiable Premiums and Misleading Representations, "Confirm with the Legal Department" for the Privacy Policy, and "Confirm with the Legal Department regarding the content" for the content of the document.

[1446] 4. Provide the user with confirmation steps.

[1447] The server generates a legal checklist and procedures, which are then displayed on the user's terminal. This allows the user to review the specific steps and required documents for each check item and take action themselves.

[1448] 5. The user performs the verification.

[1449] The user will follow the instructions provided and carry out the necessary verification procedures at each stage. For example, the user will contact the marketing department to confirm compliance with the Act against Unjustifiable Premiums and Misleading Representations.

[1450] 6. The user provides feedback on the verification results.

[1451] The user enters their results into a form to provide feedback to the system and sends it to the server.

[1452] 7. The server saves and updates the results.

[1453] The server saves the confirmation results received from the user to a database and updates the status on the system. This allows the user to track the progress of the confirmation process in real time.

[1454] Specific example

[1455] 1. Example: Confirmation under the Act against Unjustifiable Premiums and Misleading Representations

[1456] User input: "Website creation, purpose is marketing."

[1457] Server analysis: The server determined that "confirmation regarding the Act against Unjustifiable Premiums and Misleading Representations is required."

[1458] Server generation list: "Act against Unjustifiable Premiums and Misleading Representations: Confirm with Marketing Department" "Content of Description: Confirm with Legal Department" "Internal Confirmation: Confirm with ISC"

[1459] User verification: The user contacts the marketing and legal departments to obtain the necessary verifications.

[1460] Result Feedback: The user enters the results into the system.

[1461] Server save and display: The server saves the results to the database and displays a confirmation completion message to the user.

[1462] 2. Example: Checking the Privacy Policy

[1463] User input: "I'm creating a mobile app; the purpose is data collection."

[1464] Server analysis: The server determined that "confirmation of the privacy policy is required."

[1465] Server generation list: "Privacy Policy: Confirm with Legal Department" "Data Collection Details: Confirm with Data Department"

[1466] User verification: The user contacts the legal department and the data department to obtain the necessary verifications.

[1467] Result Feedback: The user enters the results into the system.

[1468] Server save and display: The server saves the results to the database and displays a confirmation completion message to the user.

[1469] This system allows users to centrally manage and efficiently process multiple legal verification procedures. This significantly improves the efficiency and accuracy of the verification process.

[1470] The following describes the processing flow.

[1471] Step 1:

[1472] The user accesses the input form. Through a web browser, the user accesses the system's input form and enters the creation (e.g., website) and its purpose (e.g., marketing).

[1473] Step 2:

[1474] The user enters information. The user fills in the necessary information in the input form, such as "Development = Website" and "Purpose = Marketing."

[1475] Step 3:

[1476] The user clicks the submit button. When the user clicks the submit button, the entered information is sent to the server.

[1477] Step 4:

[1478] The server receives the input information. The server receives the information sent by the user and prepares it for analysis.

[1479] Step 5:

[1480] The server analyzes the input information. The server uses a natural language processing algorithm to analyze the received information. Based on the analysis results, it identifies the necessary legal compliance items (e.g., the Act against Unjustifiable Premiums and Misleading Representations, privacy policy, etc.).

[1481] Step 6:

[1482] The server generates a legal checklist. Based on the analysis results, the server generates a list of necessary legal check items. For each item, it lists the corresponding contact point and procedure.

[1483] Step 7:

[1484] The server displays a legal confirmation list. The server displays the generated legal confirmation list on the user's terminal. The list includes details of each confirmation contact and procedure.

[1485] Step 8:

[1486] The user performs the verification procedure. Based on the instructions provided by the server, the user completes the necessary verification procedures at each relevant contact point. For example, they might request the marketing department to verify compliance with the Act against Unjustifiable Premiums and Misleading Representations.

[1487] Step 9:

[1488] The user collects the verification results. The user receives feedback from the verification channel and prepares to return it to the system.

[1489] Step 10:

[1490] The user provides feedback on the verification results. The user enters the verification results into the feedback form and submits it to the system.

[1491] Step 11:

[1492] The server receives the confirmation result. The server receives the confirmation result sent by the user and proceeds to the next step.

[1493] Step 12:

[1494] The server saves the verification results. The server saves the verification results to a database and updates that information to the latest version.

[1495] Step 13:

[1496] The server displays update information. The server updates the user's confirmation status and displays the progress on the terminal. The user receives a confirmation message and information about the next steps.

[1497] In this way, users can efficiently manage various legal checks and complete the necessary procedures.

[1498] (Example 1)

[1499] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1500] Traditional legal verification processes are complex and time-consuming, requiring the individual management of multiple verification channels and procedures. Maintaining accuracy and efficiency is also difficult. This is especially true when legal regulations are diverse and require coordination across various departments. An efficient, centralized system is needed to address these problems.

[1501] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1502] In this invention, the server includes means for the user to input a creation and its purpose; means for the server to receive and analyze the input information and identify necessary legal confirmation items; means for the server to generate a legal confirmation list based on the analysis results using a generation AI model; means for the server to list the corresponding confirmation contacts and procedures for each identified legal confirmation item; means for the user to display the confirmation procedure and provide feedback on the legal confirmation results; and means for the server to receive, save, and update the feedback. This makes it possible to efficiently centrally manage legal confirmation procedures and track the progress of confirmation work in real time.

[1503] A "user" is anyone who accesses this system and enters information about their creations and their purpose.

[1504] A "server" is a device that receives and analyzes information sent by users, identifies necessary legal verification items, and generates and manages legal verification lists.

[1505] "Created works" refers to deliverables such as websites and mobile applications created by users.

[1506] "Purpose" refers to the role or use that the creation is intended to fulfill, and includes, for example, marketing and data collection.

[1507] "Legal confirmation items" refer to items related to the creation of a document that require legal confirmation, and specifically include the Premiums and Representations Act and privacy policies.

[1508] A "generative AI model" is a type of artificial intelligence used to analyze input information and identify legal compliance items.

[1509] The "Legal Confirmation List" is a list of the corresponding confirmation contacts and procedures for each legal confirmation item, generated by the server based on the analysis results.

[1510] A "confirmation desk" refers to the department or person responsible for confirming legal compliance items.

[1511] "Procedures" refer to the specific actions and tasks required in response to legal verification items.

[1512] "Feedback" refers to the user submitting legal review results to the system.

[1513] Modes for carrying out the invention

[1514] This invention is a system that allows users to input a creation and its purpose, and then analyzes that input information to efficiently perform necessary legal checks. By analyzing the input information and centrally managing multiple checkpoints and procedures, this system reduces the burden on the user and improves the efficiency of the check process.

[1515] System Configuration

[1516] This system consists mainly of the following elements.

[1517] 1. A terminal where the user enters information.

[1518] 2. A server that receives and analyzes information sent by the user.

[1519] 3. Generative AI models within the server

[1520] 4. Legal confirmation list generated on the server

[1521] 5. Means for users to provide feedback

[1522] 6. Database to receive, store, and update feedback

[1523] The user is using a terminal to enter information.

[1524] Users access a web form and enter information about their creation (e.g., a website) and its purpose (e.g., marketing). This data is then sent to the system.

[1525] The server receives and analyzes the input information.

[1526] The server receives information sent by the user. It then analyzes the input information using a generation AI model and identifies the necessary legal checks based on the entered data. For example, if the user enters "Website creation, purpose is marketing," the server will determine that checks on the Premiums and Representations Act and the privacy policy are necessary.

[1527] Legal confirmation list generated on the server

[1528] The server generates a legal checklist based on the analysis results, listing the necessary contact points and procedures. For example, it includes specific instructions such as "Confirm with the Marketing Department" for the Premiums and Representations Act and "Confirm with the Legal Department" for the Privacy Policy.

[1529] Provide the user with a verification procedure.

[1530] The server displays the generated legal checklist on the user's terminal. The user reviews it and follows the instructions to perform the necessary legal checks. Specifically, they request the marketing department to review the Premiums and Representations Act and the legal department to review the privacy policy.

[1531] The user provides feedback on the verification results.

[1532] The user enters the results into a dedicated form within the system to provide feedback on the verification process. This information is then sent to the server.

[1533] The server saves and updates the results.

[1534] The server saves the confirmation results received from the user to the database and updates the status on the system. This allows the user to track the progress of the confirmation process in real time.

[1535] Specific example

[1536] Example 1: Confirmation of the Premiums and Representations Act

[1537] User input: "Website creation, purpose is marketing."

[1538] Server analysis: The server determines that "confirmation regarding the Premiums and Representations Act is required."

[1539] Server generation list: "Act against Unjustifiable Premiums and Misleading Representations: Confirm with Marketing Department" "Contents of Description: Confirm with Legal Department"

[1540] User verification: The user contacts the marketing and legal departments to complete any necessary verifications.

[1541] Result Feedback: The user enters the results into the system.

[1542] Server save and display: The server saves the results to the database and displays a confirmation message to the user.

[1543] Example 2: Checking the Privacy Policy

[1544] User input: "I'm creating a mobile app; the purpose is data collection."

[1545] Server analysis: The server determines that "confirmation of the privacy policy is required."

[1546] Server generation list: "Privacy Policy: Confirm with Legal Department" "Data Collection Details: Confirm with Data Department"

[1547] User verification: The user contacts the legal department and the data department to perform the necessary verifications.

[1548] Result Feedback: The user enters the results into the system.

[1549] Server save and display: The server saves the results to the database and displays a confirmation message to the user.

[1550] This system allows users to centrally manage and efficiently process multiple legal verification procedures. This significantly improves the efficiency and accuracy of the verification process.

[1551] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1552] Step 1:

[1553] A user accesses a web form and enters information about their creation (e.g., a website) and its purpose (e.g., marketing). The entered information is sent from the user's device to the server. This input information becomes the basis for subsequent processing.

[1554] Step 2:

[1555] The server receives information sent by the user. After receiving the information, the server analyzes the input data using a generative AI model. The information extracted through this analysis is used to identify subsequent legal review items. Specifically, it performs natural language processing to understand the intent of the user's input.

[1556] Step 3:

[1557] The server identifies the necessary legal checks based on the analysis results. For example, if the analysis indicates "website creation, purpose is marketing," the server will identify the need to check the Premiums and Representations Act and the privacy policy. The output of this step is a list of the specific legal items that need to be checked.

[1558] Step 4:

[1559] For each legal verification item identified by the server, a list of the corresponding verification contacts and procedures is created. This list includes instructions on which department to contact for each item. For example, "Confirm the Premiums and Representations Act with the Marketing Department" or "Confirm the Privacy Policy with the Legal Department."

[1560] Step 5:

[1561] The server generates a legal checklist, which is then displayed on the user's terminal. By reviewing this list, the user can learn about the necessary procedures. The output specifically shows the checklist items, their corresponding contact points, and detailed steps.

[1562] Step 6:

[1563] The user will conduct legal checks following the provided procedures. The user will contact each department based on the list and request the necessary checks. For example, the user might request the marketing department to check the Premiums and Representations Act and the legal department to check the privacy policy.

[1564] Step 7:

[1565] The user enters the results of the legal review into a dedicated form within the system to provide feedback. This information is then sent back to the server. The results entered by the user become the input data for this step.

[1566] Step 8:

[1567] The server saves the confirmation results received from the user to a database. Furthermore, it updates the status of the confirmation items and displays the progress on the system. This allows users to track the progress of their confirmation work in real time.

[1568] This series of processing steps allows users to efficiently complete legal verification procedures. Furthermore, the ability to manage the progress of the verification process within the system significantly improves the efficiency and accuracy of the verification work.

[1569] (Application Example 1)

[1570] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1571] Online platforms such as virtual stores require the efficient management of numerous legal verification items and the rapid coordination of verification processes with multiple contact points. Furthermore, tracking the progress and deadlines of these verification processes is often difficult, placing a significant burden on users. A comprehensive system is needed to address these issues.

[1572] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1573] In this invention, the server includes means for the user to input a creation and its purpose; means for the server to analyze the input information and identify necessary legal verification items; means for the server to present corresponding verification contacts and procedures for each identified legal verification item; means for the user to provide feedback on the legal verification results; means for the server to receive, save, and update the feedback; means for tracking the progress of the legal verification work; and means for notifying the user of the deadline and progress of the verification procedures. This enables the user to efficiently carry out legal verification work and appropriately manage progress and deadlines.

[1574] A "user" is an end-user who uses the system to input creations and their purposes.

[1575] "Created works" refer to specific projects, products, or services that users input.

[1576] "Purpose" refers to the achievement goals or intentions related to the creation.

[1577] "Means" refers to methods or mechanisms for performing a specific function or role.

[1578] A "server" refers to a computer system that receives, analyzes, stores, and manages information entered by users.

[1579] "Legal confirmation items" refer to legal confirmation matters necessary in relation to the created document and its purpose.

[1580] A "confirmation desk" refers to the contact point or department necessary to address specific legal confirmation items.

[1581] "Procedure" refers to the specific actions and steps required to confirm and approve certain legal verification items.

[1582] "Feedback" refers to the act of reporting the results and progress of legal checks performed by users to the server.

[1583] "Updating" refers to the act of updating data to the latest state based on information received by the server.

[1584] "Progress" refers to the status of the legal review process.

[1585] "Notifications" refer to alerts or messages that inform users about deadlines and progress of verification procedures.

[1586] This invention is a system for efficiently performing legal verification work. The system is designed so that the user inputs a creation and its purpose, and the server then performs the necessary legal verification based on that input. The following details specific embodiments of this system.

[1587] Hardware and software configuration

[1588] Hardware:

[1589] Server: Cloud servers such as AWS EC2 are used to process data, including receiving, analyzing, storing, and updating it.

[1590] User terminal: A device such as a smartphone, PC, or tablet used by the user to input information and check the results.

[1591] software:

[1592] Framework: Implement the server analysis module using Python.

[1593] Database: MySQL is used to store legal review results and progress data.

[1594] Frontend: Build the user interface using React.js.

[1595] Data processing and computation

[1596] Data entry and analysis:

[1597] User Terminal: Users enter their creation and its purpose through a web form. For example, they might enter "Type of virtual store: Health food sales, Purpose: Promotional campaign."

[1598] Server: Analyzes the received input data and identifies the necessary legal verification items. Based on the analysis results, it generates a verification list and displays it to the user.

[1599] Verification steps and feedback:

[1600] User: Follow the provided verification steps, complete the necessary verification procedures, and enter the results into the feedback form.

[1601] Server: Receives feedback and stores it in the database. Updates progress in real time and notifies the user.

[1602] Specific example

[1603] User input: "Virtual store type: Health food sales, Purpose: Promotional campaign"

[1604] Analysis results: The server determined that it was necessary to "check the Premiums and Representations Act" and "check the Privacy Policy".

[1605] Verification procedure: The server will provide users with specific contact points and procedures for "confirmation regarding the Premiums and Representations Act" and "confirmation regarding the Privacy Policy."

[1606] Feedback: The user enters the confirmation result, and the server saves the progress to the database.

[1607] Notification: The server sends alerts to the user regarding legal review deadlines and progress.

[1608] Example of a prompt

[1609] Virtual store type: Health food sales, Purpose: Promotional campaign

[1610] This system allows users to efficiently carry out legal review work and properly manage progress and deadlines.

[1611] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1612] Step 1:

[1613] The user enters information. The user uses a device to access a web form and enters information about the creation (e.g., a virtual store) and its purpose (e.g., a promotional campaign). This entered information is sent to the server.

[1614] Input: The user enters "Virtual store type: Health food sales, Purpose: Promotional campaign" into the input form.

[1615] Output: User input data is sent to the server.

[1616] Specific operation: The user accesses a web form from a device such as a smartphone or PC, enters the required information, and presses the submit button. This information is sent to the server.

[1617] Step 2:

[1618] The server analyzes the input information. The server analyzes the received input information and identifies the necessary legal verification items. A generative AI model can be used for this analysis.

[1619] Input: The server receives user input data.

[1620] Output: The server identifies the legal items that need to be checked (e.g., "Check the Premiums and Representations Act," "Check the Privacy Policy").

[1621] Specific operation: The server passes the received data to the analysis module, which uses the generated AI model to identify the necessary legal verification items.

[1622] Step 3:

[1623] The server generates a legal confirmation list. Based on the analysis results, the server lists the corresponding confirmation contacts and procedures for each required legal confirmation item.

[1624] Input: Legal verification items identified by the server.

[1625] Output: The server generates a confirmation list and displays it on the user's terminal (e.g., "Confirmation of Premiums and Representations Act: Contact Legal Department", "Confirmation of Privacy Policy: Contact Data Department").

[1626] Specific operation: The server identifies the contact point and procedure corresponding to each item based on the legal verification items, and generates a verification list.

[1627] Step 4:

[1628] The user performs the verification procedure. The user follows the provided verification steps and completes the necessary verification procedures.

[1629] Input: Confirmation list displayed from the server.

[1630] Output: The user provides feedback on the results for each verification item (e.g., "Confirmation of Premiums and Representations Act: Completed," "Confirmation of Privacy Policy: Pending").

[1631] Specific actions: The user contacts the relevant departments, such as the legal department or data department, completes the necessary verification procedures, and enters the results into the system.

[1632] Step 5:

[1633] The server receives, stores, and updates feedback. The server receives user feedback, stores it in the database, and updates the system status.

[1634] Input: Confirmation result entered by the user.

[1635] Output: The server saves the verification results to the database and updates the system status.

[1636] Specific operation: The server receives feedback data sent by the user, saves it to the database, and updates the confirmation status in real time.

[1637] Step 6:

[1638] The server tracks progress and provides notifications. The server periodically tracks the progress of legal review work and sends necessary notifications to the user (e.g., deadlines for review procedures, progress status).

[1639] Input: Updated confirmation status.

[1640] Output: Sends notifications to the user's terminal regarding progress and deadlines.

[1641] Specific operation: The server periodically checks the database information, generates notifications based on progress and deadlines for verification procedures, and sends alerts to the user.

[1642] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1643] This invention is a system that allows users to input a creation and its purpose, and then efficiently performs the necessary legal checks based on that input. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides a more flexible and adaptable check procedure.

[1644] System Overview

[1645] This system includes a server that analyzes information provided by the user, a terminal where the user inputs information, an emotion engine that recognizes the user's emotional state, and means for managing feedback.

[1646] Program processing

[1647] 1. The user enters information into the input form.

[1648] The user accesses a web form and enters the creation (e.g., a website) and its purpose (e.g., marketing).

[1649] 2. The server receives and analyzes the input information.

[1650] The server receives and analyzes information sent by the user. Based on the input information, it identifies necessary legal compliance items (e.g., the Act against Unjustifiable Premiums and Misleading Representations, privacy policy, etc.).

[1651] 3. The emotion engine analyzes the user's emotions.

[1652] An emotion engine embedded in the server analyzes the user's emotional state from their input information and actions. This allows it to recognize emotions such as stress and confusion.

[1653] 4. The server generates a legal checklist.

[1654] The server generates a list of necessary legal verification items based on the analysis results. For each item, it lists the corresponding verification contacts and procedures.

[1655] 5. The emotion engine adjusts the procedural methods.

[1656] The emotion engine adjusts the priority and method of procedures based on the user's emotional state. For example, if the user is stressed, it may simplify procedures or send reminders and support messages.

[1657] 6. The server displays the legal confirmation list.

[1658] The server generates a legal review list, which is then displayed on the user's terminal. Adjustments made by the emotion engine are reflected in this list.

[1659] 7. The user completes the verification process.

[1660] The user will follow the instructions provided and complete the necessary verification procedures at each relevant department. For example, they might request the marketing department to verify compliance with the Act against Unjustifiable Premiums and Misleading Representations.

[1661] 8. The user provides feedback on the verification results.

[1662] The user enters their results into a form to provide feedback to the system and sends it to the server.

[1663] 9. The server receives the confirmation result.

[1664] The server receives the confirmation result sent by the user and proceeds to the next step.

[1665] 10. The server saves and updates the verification results.

[1666] The server saves the verification results to a database and updates that information to the latest version.

[1667] 11. The server displays update information.

[1668] The server updates the user's verification status and displays the progress on the terminal. The user receives a message confirming verification and information about the next steps.

[1669] Specific example

[1670] 1. Verification of the Act against Unjustifiable Premiums and Misleading Representations using an emotional engine.

[1671] User input: "Website creation, purpose is marketing."

[1672] Server analysis: The server determined that "confirmation regarding the Act against Unjustifiable Premiums and Misleading Representations is required."

[1673] Emotional Engine Analysis: Detects when a user is experiencing stress while submitting input information.

[1674] Server generation list: "Act against Unjustifiable Premiums and Misleading Representations: Confirm with Marketing Department" "Content of Description: Confirm with Legal Department" "Internal Confirmation: Confirm with ISC"

[1675] Emotional Engine Tuning: Send reminders with simplified instructions.

[1676] User verification: The user contacts the marketing and legal departments to obtain the necessary verifications.

[1677] Result Feedback: The user enters the results into the system.

[1678] Server save and display: The server saves the results to the database and displays a confirmation completion message to the user.

[1679] 2. Reviewing the Privacy Policy using an Emotion Engine

[1680] User input: "I'm creating a mobile app; the purpose is data collection."

[1681] Server analysis: The server determined that "confirmation of the privacy policy is required."

[1682] Emotional Engine Analysis: Detects when a user is feeling confused while proceeding with the verification process.

[1683] Server generation list: "Privacy Policy: Confirm with Legal Department" "Data Collection Details: Confirm with Data Department"

[1684] Emotional Engine Adjustment: Displays clear explanations and support messages.

[1685] User verification: The user contacts the legal department and the data department to obtain the necessary verifications.

[1686] Result Feedback: The user enters the results into the system.

[1687] Server save and display: The server saves the results to the database and displays a confirmation completion message to the user.

[1688] This system allows users to centrally manage and efficiently process multiple legal verification procedures. The introduction of an emotion engine enables flexible responses tailored to the user's emotional state, reducing the burden of verification work.

[1689] The following describes the processing flow.

[1690] Step 1:

[1691] The user accesses the input form. Through a web browser, the user accesses the system's input form and enters the creation (e.g., website) and its purpose (e.g., marketing).

[1692] Step 2:

[1693] The user enters information. The user fills in the necessary information in the input form, such as "Development = Website" and "Purpose = Marketing."

[1694] Step 3:

[1695] The user clicks the submit button. When the user clicks the submit button, the entered information is sent to the server.

[1696] Step 4:

[1697] The server receives the input information. The server receives the information sent by the user and prepares it for analysis.

[1698] Step 5:

[1699] The server analyzes the input information. The server uses a natural language processing algorithm to analyze the received information. Based on the analysis results, it identifies the necessary legal compliance items (e.g., the Act against Unjustifiable Premiums and Misleading Representations, privacy policy, etc.).

[1700] Step 6:

[1701] The emotion engine analyzes the user's emotions. The emotion engine, embedded in the server, analyzes the emotional state from the input information and the user's actions.

[1702] Step 7:

[1703] The server generates a legal checklist. Based on the analysis results, the server generates a list of necessary legal check items. For each item, it lists the corresponding contact point and procedure.

[1704] Step 8:

[1705] The emotion engine adjusts the procedure. The emotion engine adjusts the priority and method of procedures based on the user's emotional state. For example, if the user is stressed, it might simplify the procedure or send reminders and support messages.

[1706] Step 9:

[1707] The server displays the legal checklist. The server-generated legal checklist is displayed on the user's terminal. Details of the coordinated procedures and required documents are displayed.

[1708] Step 10:

[1709] The user performs the verification procedure. The user follows the instructions provided and completes the necessary verification procedures at each relevant department. For example, they might request the marketing department to verify compliance with the Act against Unjustifiable Premiums and Misleading Representations.

[1710] Step 11:

[1711] The user collects the verification results. The user collects feedback results from each verification channel and verifies the content themselves.

[1712] Step 12:

[1713] The user provides feedback on the verification results. The user enters the verification results into the feedback form and sends it to the server.

[1714] Step 13:

[1715] The server receives the confirmation result. The server receives the confirmation result sent by the user and proceeds to the next step.

[1716] Step 14:

[1717] The server saves the verification results. The server records the received verification results in the database and updates the progress of the verification process.

[1718] Step 15:

[1719] The server displays update information. The server updates the user's confirmation status and displays the progress on the user's device. The user receives a confirmation message and information about the next steps.

[1720] This system allows users to efficiently manage legal verification procedures, and by using an emotion engine, it enables flexible responses tailored to the user's emotional state.

[1721] (Example 2)

[1722] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1723] The current legal review system has problems such as making procedures stressful and inefficient because it does not take into account the user's emotional state. In addition, there is no way to centrally manage multiple legal reviews and properly track their progress, making it difficult for users to proceed with the procedures smoothly.

[1724] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1725] In this invention, the server includes means for the user to input a creation and its purpose; means for the server to analyze the input information and identify necessary legal confirmation items; means for the server to analyze the user's emotional state; means for the server to present corresponding confirmation windows and procedures for each identified legal confirmation item; means for the server to adjust the priority and procedures of legal confirmation procedures according to the user's emotional state; means for the user to provide feedback on the legal confirmation results; and means for the server to receive, store, and update the feedback. This makes it possible to provide flexible legal confirmation procedures that take into account the user's emotional state and to improve the efficiency of the confirmation procedures.

[1726] "Created works" refers to all objects that users create and input into the system. Examples include websites and mobile applications.

[1727] "Purpose" refers to the intention or use that a user sets for their creation. Examples include marketing and data collection.

[1728] "Legal confirmation items" refer to the legal matters that need to be confirmed for the created document. For example, these include the Act against Unjustifiable Premiums and Misleading Representations and privacy policies.

[1729] A "confirmation desk" refers to the department or person in charge of handling legal confirmation items. For example, this could include the marketing department or the legal department.

[1730] "Procedures" refer to the steps and methods necessary to carry out legal verification. For example, this includes submitting documents and contacting the relevant personnel.

[1731] "Emotional state" refers to the emotional state a user exhibits while using the system. Examples include stress, confusion, and relief.

[1732] "Feedback" refers to the act of a user reporting the results of a legal review to the system. This includes, for example, reporting the progress and results of the review.

[1733] This invention is a system that allows users to input a creation and its purpose, and then efficiently performs the necessary legal checks based on that input. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides a more flexible and adaptable check procedure.

[1734] System Overview

[1735] This system includes a server that analyzes information provided by the user, a terminal where the user inputs information, an emotion engine that recognizes the user's emotional state, and means for managing feedback.

[1736] Hardware and software used

[1737] The main components of this system are as follows:

[1738] User devices (e.g., personal computers, smartphones)

[1739] Servers (e.g., AWS, Google Cloud)

[1740] Emotion engine (e.g., Microsoft Azure Emotion API)

[1741] Databases (e.g., MySQL, PostgreSQL)

[1742] System Functions

[1743] 1. Entering information

[1744] Users access the system's web form using devices such as PCs or smartphones and enter their creations and their purposes. For example, they access "https: / / example.com / form" using a browser and enter the necessary information using text boxes or dropdown menus.

[1745] 2. Information Reception and Analysis

[1746] The server analyzes the received information and identifies the necessary legal compliance items. This analysis is performed by a script running on the server side (e.g., Python or Node.js). Identified legal compliance items include compliance with the Act against Unjustifiable Premiums and Misleading Representations and privacy policies. Furthermore, an emotion engine (e.g., Microsoft Azure Emotion API) analyzes the user's input information and behavior to determine their emotional state, recognizing stress, confusion, etc.

[1747] 3. Generating a legal checklist

[1748] Based on the analysis results, the server generates a list of items requiring legal review. This list includes details of the corresponding review channels and procedures. The emotion engine adjusts the priority and method of the procedures according to the user's emotional state. For example, if the user is stressed, the procedures may be simplified or support messages added.

[1749] 4. Display and implementation of verification procedures

[1750] The server displays the generated legal checklist on the user's terminal, and the user performs the necessary checks according to the list. For example, they might contact the marketing department to request a check regarding the Act against Unjustifiable Premiums and Misleading Representations. Once the checks are complete, the user feeds the results back into the system and sends them to the server.

[1751] 5. Saving and updating verification results

[1752] The server receives the confirmation results sent by the user and stores them in the database. This updates the confirmation status, and the user's progress is displayed on the terminal. The user receives a confirmation completion message and information about the next steps.

[1753] Specific example

[1754] 1. Verification of the Act against Unjustifiable Premiums and Misleading Representations using an emotional engine.

[1755] User input: "Website creation, purpose is marketing."

[1756] Server analysis: The server determined that "confirmation regarding the Act against Unjustifiable Premiums and Misleading Representations is required."

[1757] Emotional Engine Analysis: Detects when a user is experiencing stress while submitting input information.

[1758] Server generation list: "Act against Unjustifiable Premiums and Misleading Representations: Confirm with Marketing Department", "Content of Description: Confirm with Legal Department", "Internal Confirmation: Confirm with General Affairs Department"

[1759] Emotional Engine Tuning: Send reminders with simplified steps.

[1760] User verification: The user contacts the marketing and legal departments to obtain the necessary verifications.

[1761] Result Feedback: Users enter their results into the system.

[1762] Server save and display: The server saves the results to the database and displays a confirmation message to the user.

[1763] 2. Reviewing the Privacy Policy using an Emotion Engine

[1764] User input: "I'm creating a mobile app; the purpose is data collection."

[1765] Server analysis: The server determined that "confirmation of the privacy policy is required."

[1766] Emotional Engine Analysis: Detects when a user is experiencing confusion while proceeding with the verification process.

[1767] Server generation list: "Privacy Policy: Confirm with Legal Department" "Data Collection Details: Confirm with Data Department"

[1768] Emotional Engine Adjustment: Displays clear explanations and support messages.

[1769] User verification: The user contacts the legal and data departments to obtain the necessary verifications.

[1770] Result Feedback: Users enter their results into the system.

[1771] Server save and display: The server saves the results to the database and displays a confirmation message to the user.

[1772] This system allows users to centrally manage and efficiently process multiple legal verification procedures. The introduction of an emotion engine enables flexible responses tailored to the user's emotional state, reducing the burden of verification work.

[1773] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1774] Step 1:

[1775] The user enters information on the device.

[1776] The user accesses the system's web form using their device and enters information about their creation and its purpose. Specifically, they access "https: / / example.com / form" using a browser and enter information such as "Website creation, purpose is marketing" into the text box. Once the input is submitted, the server receives the information.

[1777] Input: The user enters the creation and its purpose in the input form.

[1778] Output: The information entered by the user is sent to the server.

[1779] Step 2:

[1780] The server receives and analyzes the input information.

[1781] The server receives and analyzes information sent by the user. This analysis uses, for example, a Python script to identify the necessary legal checks based on the creation and purpose. For example, based on the purpose of "marketing," it might determine that "checking the Act against Unjustifiable Premiums and Misleading Representations is necessary."

[1782] Input: Information submitted by the user

[1783] Output: Required legal verification items as analysis results

[1784] Step 3:

[1785] The emotion engine built into the server analyzes the emotional state.

[1786] An emotion engine (e.g., Microsoft Azure Emotion API) analyzes a user's emotional state based on received user input and behavioral data. This helps determine whether the user is experiencing stress or distress.

[1787] Input: User input information and behavioral data

[1788] Output: Data on the user's emotional state

[1789] Step 4:

[1790] The server generates a legal checklist.

[1791] Based on the analysis results, the server generates a list of necessary legal verification items. This list includes details of the relevant contact point and procedures for each item. For example, it might list items such as "Act against Unjustifiable Premiums and Misleading Representations: Confirm with the Marketing Department" and "Content of Description: Confirm with the Legal Department."

[1792] Input: Analysis results and emotional state data

[1793] Output: List of legal review items

[1794] Step 5:

[1795] The emotion engine adjusts the procedure.

[1796] The emotion engine adjusts the procedure based on the user's emotional state. For example, if the user is stressed, it might simplify the procedure, send a reminder, or add a support message.

[1797] Input: Data on the user's emotional state

[1798] Output: Adjusted legal confirmation procedure

[1799] Step 6:

[1800] The server displays the legal checklist on the user's terminal.

[1801] The server sends the generated legal checklist to the user's terminal for display. This list also reflects the results of adjustments made by the sentiment engine, such as simplified procedures, reminders, and support messages.

[1802] Input: Adjusted legal confirmation procedure

[1803] Output: Legal confirmation list displayed on the user terminal

[1804] Step 7:

[1805] The user performs the verification procedure.

[1806] The user will perform the necessary verification procedures based on the displayed legal checklist. For example, they might contact the marketing department to request verification regarding the Act against Unjustifiable Premiums and Misleading Representations.

[1807] Input: Legal confirmation list

[1808] Output: Implementation of verification procedure

[1809] Step 8:

[1810] The user enters the confirmation result as feedback and sends it to the server.

[1811] After completing the verification process, users enter the results into the system and send them to the server. Specifically, they access a web form for feedback, enter the results, and press the submit button.

[1812] Input: Enter confirmation result

[1813] Output: Sending confirmation results

[1814] Step 9:

[1815] The server receives the confirmation result.

[1816] The server receives the confirmation result sent by the user and retrieves the data necessary to proceed to the next step.

[1817] Input: Confirmation result

[1818] Output: Received confirmation result

[1819] Step 10:

[1820] The server saves and updates the verification results.

[1821] The server saves the received confirmation results to a database and updates it with the latest information. For example, it saves them to a database such as MySQL or PostgreSQL.

[1822] Input: Confirmation result received

[1823] Output: Verification results saved in the database

[1824] Step 11:

[1825] The server displays update information on the user's terminal.

[1826] The server displays the updated confirmation status on the user's device. The user receives a confirmation completion message and information about the next steps.

[1827] Input: Verification results stored in the database

[1828] Output: Update information displayed on the user's terminal

[1829] (Application Example 2)

[1830] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1831] The implementation and management of modern security systems involve numerous legal review procedures, which are complex and place a significant burden on users. Furthermore, user emotional states (e.g., confusion, stress) can reduce the efficiency of these procedures. Therefore, it is necessary to enable users to conduct legal review efficiently.

[1832] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1833] In this invention, the server includes means for the user to input a creation and its purpose; means for the server to analyze the input information and identify necessary legal verification items; means for the server to present corresponding verification windows and procedures for each identified legal verification item; means for an emotion analysis engine to analyze the user's emotional state and adjust the procedure; means for the user to provide feedback on the legal verification results; and means for the server to receive, save, and update the feedback. This makes it possible to perform legal verification efficiently while taking the user's emotional state into consideration.

[1834] A "user" is an individual or company that uses the system.

[1835] "Created work" refers to a system, software, or other technical device that the user intends to create or implement.

[1836] "Purpose" refers to the main reason or goal for a user to use the creation.

[1837] A "server" is a central processing unit that receives, analyzes, stores, and updates user input information.

[1838] "Means of analyzing information" refers to algorithms and programs used by a server to analyze information entered by a user and identify necessary legal verification items.

[1839] "Legal verification items" refer to matters that need to be verified based on laws and regulations related to a specific document or purpose.

[1840] A "confirmation desk" refers to a department or person responsible for handling or confirming specific legal confirmation items.

[1841] "Means for adjusting the procedure" refers to functions that allow the emotion analysis engine to adjust the flow and difficulty level of procedures presented based on the user's emotional state.

[1842] An "emotion analysis engine" is software or an algorithm used to identify and analyze a user's emotional state (e.g., stress, confusion).

[1843] "Feedback" refers to the act of a user entering the results of a verification process into the system and sending them to the server.

[1844] "Means of saving and updating" refers to the function of a server to save the feedback it receives in a database and update the information to the latest version based on that data.

[1845] This invention is a system that enables users to efficiently perform legal verification procedures related to the introduction and management of security systems. The system comprises a terminal used by the user, a server for analyzing information, an emotion analysis engine for recognizing the user's emotional state, and means for managing feedback from the legal verification procedures.

[1846] The server integrates multiple functions, receiving and analyzing information about creations and their purpose entered by the user via the terminal. Based on the input information, it identifies necessary legal verification items and presents the corresponding verification channels and procedures. Furthermore, it incorporates an emotion analysis engine that analyzes the user's emotional state based on their input behavior and adjusts the procedure accordingly. For example, if the user is experiencing stress, the server simplifies the procedure and sends a reminder.

[1847] The sentiment analysis engine is installed on devices such as smartphones, tablets, smart glasses (e.g., Google Glass), and head-mounted displays (e.g., Microsoft HoloLens). This allows for the adjustment of procedures based on the user's emotional state. The server interacts with web servers such as Apache HTTP Server and databases such as MySQL to analyze input information and perform internal processing. Furthermore, sentiment analysis engines such as IBM Watson Tone Analyzer are used for sentiment analysis.

[1848] For example, if a user plans to install a new surveillance camera system with the goal of enhancing office security, the server receiving the input information will identify relevant legal verification items (e.g., GDPR compliance). The sentiment analysis engine will analyze the user's emotional state, and if it detects that the user is experiencing stress or confusion, it will provide a supportive message with a clear explanation to simplify the process. After the user has confirmed with the relevant legal and technical departments, the results are fed back into the system, the server updates the database, and a confirmation message is displayed to the user.

[1849] Specific examples of input prompts for a generative AI model:

[1850] The purpose of introducing the new surveillance camera system is to enhance office security. Legal compliance checks related to GDPR are required. Please simplify the workflow, taking into consideration any potential user confusion.

[1851] In this way, users can efficiently conduct legal reviews in a manner that takes their emotional state into consideration, and the security system implementation process can proceed smoothly.

[1852] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1853] Step 1:

[1854] The user enters information into the input form.

[1855] The user uses a device (smartphone, tablet, etc.) to input the creation (e.g., a surveillance camera system) and its purpose (e.g., enhancing office security). The input data includes the specific type and purpose of the system.

[1856] Step 2:

[1857] The server receives and analyzes the input information.

[1858] The server receives information sent by the user and begins analysis. Using the input data, it identifies the necessary legal verification items (e.g., GDPR-related verifications). At this stage, the server analyzes the data received from the frontend in the backend and extracts the appropriate legal verification items. Specifically, it analyzes the input data using natural language processing (NLP) algorithms.

[1859] Step 3:

[1860] The emotion analysis engine analyzes the user's emotions.

[1861] A sentiment analysis engine embedded in the server analyzes the user's emotional state from user input information and interactions. For example, it can detect signs of confusion or stress from input speed and content. Input includes user input actions and text information, while output generates emotional state evaluation data. Specifically, it uses sentiment analysis engines such as IBM Watson Tone Analyzer.

[1862] Step 4:

[1863] The server generates a legal checklist.

[1864] Based on the analysis results obtained in the previous step, the server generates a list of necessary legal confirmation items. This list includes the corresponding contact point and procedure for each item. The inputs are the data for the legal confirmation items and the sentiment analysis results, and the output is the generated legal confirmation list. Specifically, it retrieves relevant information from the database and compiles instructions for the user in a list format.

[1865] Step 5:

[1866] The emotion analysis engine adjusts the procedure.

[1867] The emotion analysis engine adjusts the procedure based on the user's emotional state. For example, if the user is stressed, it simplifies the procedure and sends reminders and support messages. The input is emotional state evaluation data, and the output is the generated adjusted procedure. Specifically, it dynamically changes the content displayed in the user interface and the content of messages.

[1868] Step 6:

[1869] The server displays a legal review list.

[1870] The server displays a refined legal checklist on the user's terminal. The user is then guided through the process, with adjustments made by the sentiment analysis engine reflected in the content. This step generates a refined legal checklist as input and display data on the terminal as output. Specifically, the list content is displayed on the user interface via a web page or application interface.

[1871] Step 7:

[1872] The user performs the verification procedure.

[1873] The user follows the displayed instructions and completes the verification process at each relevant department. For example, they might contact the legal or technical department to obtain the necessary verifications. The input is a displayed legal verification list, and the output is a status indicating that the verification process has been completed. Specifically, they contact each department using email or internal tools.

[1874] Step 8:

[1875] The user provides feedback on the verification results.

[1876] The user enters their results into a form to provide feedback to the system and sends it to the server. The server receives the confirmation result data as input and the feedback data as output. Specifically, a web form or application feedback screen is used.

[1877] Step 9:

[1878] The server receives the confirmation result.

[1879] The server receives the confirmation result sent by the user and proceeds to the next process. The input is feedback data, and the output is the reception status. Specifically, it performs parsing processing to register the received data in the database.

[1880] Step 10:

[1881] The server saves and updates the verification results.

[1882] The server saves the verification results to the database and updates that information to the latest version. The input is the received feedback data, and the output is the updated database information. Specifically, the database update process is performed using SQL queries.

[1883] Step 11:

[1884] The server displays update information.

[1885] The server updates the user's confirmation status and displays the progress on the terminal. The input is the updated database information, and the output is the status display data. Specifically, it displays information about the progress and the next steps to the user on the screen.

[1886] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1887] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1888] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1889] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1890] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1891] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1892] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1893] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1894] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1895] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1896] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1897] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1898] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1899] 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.

[1900] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1901] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1902] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1903] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1904] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1905] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1906] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[1907] The following is further disclosed regarding the embodiments described above.

[1908] (Claim 1)

[1909] A means by which the user inputs the creation and its purpose,

[1910] The server analyzes the input information and identifies the necessary legal verification items,

[1911] For each legal verification item where a server has been identified, a means of providing the corresponding verification contact point and procedure will be presented.

[1912] A means for users to provide feedback on the results of legal review,

[1913] The server has means for receiving, storing, and updating the aforementioned feedback,

[1914] A system that includes this.

[1915] (Claim 2)

[1916] The system according to claim 1, further comprising a server and a display means for guiding users through specific verification procedures and required documents corresponding to the legal verification items.

[1917] (Claim 3)

[1918] The system according to claim 1, further comprising means for a user to manage and track the progress of the confirmation status of the legal confirmation items within the system.

[1919] "Example 1"

[1920] (Claim 1)

[1921] A means by which the user inputs the creation and its purpose,

[1922] The server receives and analyzes the input information and has a means to identify the necessary legal verification items.

[1923] The server uses a generation AI model to generate a legal checklist based on the analysis results,

[1924] A means to list the corresponding verification contacts and procedures for each legal verification item for which a server has been identified,

[1925] A means for users to view the verification procedure and provide feedback on the legal verification results,

[1926] The server has means for receiving, storing, and updating the aforementioned feedback,

[1927] A system that includes this.

[1928] (Claim 2)

[1929] The system according to claim 1, further comprising a server and a display means for guiding users through specific verification procedures and required documents corresponding to the legal verification items.

[1930] (Claim 3)

[1931] The system according to claim 1, further comprising means for a user to manage and track the progress of the confirmation status of the legal confirmation items within the system.

[1932] "Application Example 1"

[1933] (Claim 1)

[1934] A means by which the user inputs the creation and its purpose,

[1935] The server analyzes the input information and identifies the necessary legal verification items,

[1936] For each legal verification item where a server has been identified, a means of providing the corresponding verification contact point and procedure will be presented.

[1937] A means for users to provide feedback on the results of legal review,

[1938] The server has means for receiving, storing, and updating the aforementioned feedback,

[1939] A means of tracking the progress of legal review work,

[1940] A means of notifying the deadline and progress of the verification process,

[1941] A system that includes this.

[1942] (Claim 2)

[1943] The system according to claim 1, further comprising a server and a display means for guiding users through specific verification procedures and required documents corresponding to the legal verification items.

[1944] (Claim 3)

[1945] The system according to claim 1, further comprising means for a user to manage and track the progress of the confirmation status of the legal confirmation items within the system.

[1946] "Example 2 of combining an emotion engine"

[1947] (Claim 1)

[1948] A means by which the user inputs the creation and its purpose,

[1949] The server analyzes the input information and identifies the necessary legal verification items,

[1950] A means for the server to analyze the user's emotional state,

[1951] For each legal verification item where a server has been identified, a means of providing the corresponding verification contact point and procedure will be presented.

[1952] A means by which the server adjusts the priority and procedures of legal verification procedures according to the user's emotional state,

[1953] A means for users to provide feedback on the results of legal review,

[1954] The server has means for receiving, storing, and updating the aforementioned feedback,

[1955] A system that includes this.

[1956] (Claim 2)

[1957] The system according to claim 1, further comprising a server and a display means for guiding users through specific verification procedures and required documents corresponding to the legal verification items.

[1958] (Claim 3)

[1959] The system according to claim 1, further comprising means for a user to manage and track the progress of the confirmation status of the legal confirmation items within the system.

[1960] "Application example 2 when combining with an emotional engine"

[1961] (Claim 1)

[1962] A means by which the user inputs the creation and its purpose,

[1963] The server analyzes the input information and identifies the necessary legal verification items,

[1964] For each legal verification item where a server has been identified, a means of providing the corresponding verification contact point and procedure will be presented.

[1965] A means by which an emotion analysis engine analyzes the user's emotional state and adjusts the procedure accordingly,

[1966] A means for users to provide feedback on the results of legal review,

[1967] The server has means for receiving, storing, and updating the aforementioned feedback,

[1968] A system that includes this.

[1969] (Claim 2)

[1970] The system according to claim 1, further comprising a server and a display means for guiding users through specific verification procedures and required documents corresponding to the legal verification items.

[1971] (Claim 3)

[1972] The system according to claim 1, further comprising means for a user to manage and track the progress of the confirmation status of the legal confirmation items within the system. [Explanation of Symbols]

[1973] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means by which the user inputs the creation and its purpose, The server analyzes the input information and identifies the necessary legal verification items, For each legal verification item where a server has been identified, a means of providing the corresponding verification contact point and procedure will be presented. A means for users to provide feedback on the results of legal review, The server has means for receiving, storing, and updating the aforementioned feedback, A system that includes this.

2. The system according to claim 1, further comprising a server and a display means for guiding users through specific verification procedures and required documents corresponding to the legal verification items.

3. The system according to claim 1, further comprising means for a user to manage and track the progress of the confirmation status of the legal confirmation items within the system.

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