System

Abstract

A system is provided.SOLUTION: A system comprising: means for analyzing a message received from a user; means for proposing a highly relevant chat room candidate based on a result of the analysis; and means for notifying the user of the proposed chat room candidate.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional business communication tools have the drawback of requiring a great deal of effort for users to select an appropriate chat room or create a new one. Users often miss important notifications and updates due to being buried in a large volume of messages. Furthermore, it is difficult to summarize and understand the contents of past conversations, making it difficult to track information efficiently. [Means for solving the problem]

[0005] The present invention provides a system including a means for analyzing messages received from a user, a means for proposing highly relevant chat room candidates based on the analysis results, and a means for notifying the user of the proposed chat room candidates. The system also includes a means for analyzing a chat room creation request from a user, a means for comparing existing chat rooms based on the analysis results, and a means for proposing the creation or merging of a new chat room based on the comparison results. The system further includes a means for analyzing and setting the importance and priority of received messages and a means for notifying the user of important messages based on the set priority. The system also includes a means for analyzing messages in a specified chat room, extracting important points, and generating a summary, and a means for providing the generated summary to the user. These means reduce the burden on the user and improve work efficiency.

[0006] "User" refers to an individual or member of an organization who uses the chat system.

[0007] "Message" refers to content such as text, images, and files that users send or receive within a chat system.

[0008] "Analysis" refers to the process of using a generative AI model to read the content of a message and extract keywords, key points, etc.

[0009] A "chat room" is a virtual space for exchanging messages based on a specific topic or group.

[0010] "Chat room candidates" refers to a list of chat rooms that the system recommends to the user based on the message analysis results.

[0011] "Notification" refers to alerts and messages sent by the system to the user to provide information or draw attention to the user.

[0012] A "chat room creation request" refers to a request by a user to inform the system that they wish to establish a new chat room.

[0013] "Suggestion" refers to the system presenting the optimal option to the user based on the analysis and comparison results.

[0014] "Importance" refers to a measure of the urgency or priority of a message or notification.

[0015] "Summary" refers to information that summarizes the content of a long message using a generative AI model.

[0016] "Points" refer to the main information or important items contained in messages within a chat room. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9]1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0022] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

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

[0027] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0034] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] The present invention provides a system that enables users to efficiently use business communication tools, and includes a chat management function that utilizes AI generation. Specific embodiments for implementing the present invention will be described below.

[0039] Message analysis and chat room suggestions

[0040] 1. Message reception and analysis

[0041] A user sends a message using a business chat tool.

[0042] The terminal receives this message and sends it to the server.

[0043] The server uses a generative AI model to analyze the content of the message, extracting keywords and important topics.

[0044] 2. Chat room suggestions

[0045] The server generates suitable chat room candidates based on the message analysis results.

[0046] The server sends chat room candidates to the terminal.

[0047] The terminal displays chat room candidates to the user and prompts the user to select one.

[0048] Examples:

[0049] If a user sends a message saying "New project progress report," the server will suggest related chat rooms such as "Project progress report" and "New project."

[0050] Suggest and create new chat rooms

[0051] 1. Parsing chat room creation requests

[0052] The user inputs a message indicating their intention to create a new chat room and sends it.

[0053] The terminal receives the request and sends it to the server.

[0054] The server uses the generated AI model to analyze the request content and extract relevant keywords.

[0055] 2. Comparison with existing chat rooms and proposals

[0056] The server compares the received request with existing chat rooms.

[0057] If the server finds no duplicate entries, it will propose creating a new chat room, otherwise it will propose merging.

[0058] The proposal results are sent to the terminal and displayed to the user.

[0059] Examples:

[0060] When a user submits a request to create a chat room for "Regular Marketing Team Meetings," the server checks to see if there is an existing "Marketing Team" chat room and makes appropriate suggestions.

[0061] Message priority organization and notification

[0062] 1. Message Reception and Priority Analysis

[0063] The user receives the message.

[0064] The terminal sends this message to the server.

[0065] The server uses the generated AI model to analyze the urgency and importance of the message.

[0066] 2. Prioritization and Notifications

[0067] The server sets the priority of the message based on the analysis results.

[0068] The server creates a dedicated notification for high priority messages and sends it to the device.

[0069] The device displays a notification to the user.

[0070] Examples:

[0071] When a user receives a message saying "Please respond to an order from a client as soon as possible," the server analyzes the importance of the message and notifies the user as a high priority.

[0072] Chat room summary

[0073] 1. Processing Abstract Requests

[0074] A user enters and submits a request for a summary of the chat room.

[0075] The terminal receives the request and sends it to the server.

[0076] 2. Generating and serving summaries

[0077] The server uses the generated AI model to analyze past messages in a specified chat room.

[0078] The server extracts the key points and creates a summary.

[0079] The summary is sent to the terminal and presented to the user.

[0080] Examples:

[0081] When a user sends a request such as "Please send me a summary of the weekly report chat room," the server analyzes all messages in that chat room, creates a summary including important progress, decisions, and next steps, and sends it to the device.

[0082] In this way, the present invention provides support for users to improve work efficiency and quickly grasp important information.

[0083] The processing flow will be explained below.

[0084] Message analysis and chat room suggestions

[0085] Processing Steps:

[0086] Step 1:

[0087] The user enters a message and presses the "Send" button. The device receives the message and sends it to the server.

[0088] Step 2:

[0089] The server receives the message. The server then launches a generative AI model to analyze the message content. Through analysis, keywords and key points from the message are extracted.

[0090] Step 3:

[0091] Based on the analysis results, the server evaluates the relevance to existing chat rooms and generates highly relevant chat room candidates.

[0092] Step 4:

[0093] The server sends the generated chat room candidate list to the terminal, which displays the chat room candidates to the user and prompts them to make a selection.

[0094] Suggest and create new chat rooms

[0095] Processing Steps:

[0096] Step 1:

[0097] The user enters a message about the new chat room they wish to create and presses the "Send" button. The device receives this message and sends it to the server.

[0098] Step 2:

[0099] The server receives the request, activates the generative AI model, and analyzes the request. Keywords and topics are extracted as a result of the analysis.

[0100] Step 3:

[0101] The server compares the request with existing chat rooms based on extracted keywords and topics, and evaluates relevance and overlap.

[0102] Step 4:

[0103] Based on the comparison, the server makes a suggestion to the user: either to create a new chat room or to merge into an existing chat room.

[0104] Step 5:

[0105] The server sends the proposal results to the device, which displays the proposals to the user and prompts them to make a selection.

[0106] Message priority organization and notification

[0107] Processing Steps:

[0108] Step 1:

[0109] The user receives a message from a team member. The device receives the message and forwards it to the server.

[0110] Step 2:

[0111] The server receives the message and uses a generative AI model to analyze the message content and assess its urgency and importance.

[0112] Step 3:

[0113] The server assigns a priority to the message based on the analysis results, categorizing it into high, medium, and low priority categories.

[0114] Step 4:

[0115] The server generates a dedicated notification for high-priority messages and sends it to the device, which displays a notification of the important message to the user.

[0116] Chat room summary

[0117] Processing Steps:

[0118] Step 1:

[0119] A user sends a message requesting a summary of the chat room contents. The terminal receives the request and sends it to the server.

[0120] Step 2:

[0121] The server receives the request, launches the generative AI model, and analyzes past messages in the specified chat room.

[0122] Step 3:

[0123] The server extracts key points from the analysis and creates a summary, including key progress, decisions, and next steps.

[0124] Step 4:

[0125] The server sends the created summary to the terminal, which displays the summary to the user.

[0126] Through the specific processing steps of this system, users can efficiently manage messages and quickly grasp important information.

[0127] Example 1

[0128] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0129] Conventional business communication tools have limited capabilities for analyzing received messages, making it difficult to quickly and accurately present appropriate chat room or collaboration room candidates. Furthermore, they often lack the functionality to quickly determine the urgency and importance of users' messages and provide immediate notifications for high-priority messages. As a result, users are at greater risk of overlooking important information, which can lead to reduced work efficiency. Furthermore, when users create a new chat room, it is difficult to avoid overlaps with existing chat rooms and to suggest appropriate rooms. Therefore, the present invention aims to solve these problems.

[0130] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0131] In this invention, the server includes means for analyzing messages received from users, means for proposing highly relevant communication room candidates based on the analysis results, means for notifying users of the proposed communication room candidates, means for analyzing the content of messages using a generative AI model and extracting important keywords and topics, means for generating appropriate collaboration rooms based on the extracted information, and means for transmitting and displaying the generated collaboration room proposals to user terminals, thereby enabling users to conduct business communication quickly and effectively without overlooking important information.

[0132] "User" refers to an individual or organization that uses the business communication tools of this system.

[0133] "Message" refers to text information sent by a user through a business chat tool.

[0134] "Terminal" refers to the hardware device used by a User to access the System.

[0135] "Server" refers to a remotely located computer system that performs central processing for the System.

[0136] "Means of analysis" refers to the process of using a generative AI model to understand the content of a message and extract key elements.

[0137] A "generative AI model" refers to an algorithm that applies artificial intelligence technology to analyze text data and generate or extract specific information.

[0138] A "communication room" is a virtual room for exchanging messages about a specific topic or project.

[0139] "Collaboration Room" refers to a virtual room where users can collaborate on a specific team or project.

[0140] "Means of suggestion" refers to the process of showing users appropriate communication or collaboration rooms based on the analysis results.

[0141] "Means for notifying" refers to the process for displaying suggested rooms and important messages to users.

[0142] "Importance" refers to an index that indicates how urgent or important the content of a message is to the user.

[0143] "Priority" refers to an index that determines the priority of processing or notification based on the importance of a message.

[0144] "Comparison method" refers to the process of checking user requests against existing information to identify overlaps and relevance.

[0145] A "request" refers to a message that a user sends to the system to inform the system that they wish to create a new collaboration room.

[0146] "Proposal Results" refers to action plans or recommendations to users that are generated as a result of the analysis and comparison.

[0147] The present invention provides a system that enables users to efficiently use business communication tools, and includes a chat management function that utilizes a generative AI model. Specific embodiments for implementing the present invention will be described below.

[0148] Configuration and operation overview

[0149] In this invention, when a user sends and receives messages using a business chat tool, a server and a terminal work together to provide advanced functions such as analysis, suggestions, notifications, and summaries. The server uses a generative AI model (e.g., OpenAI's GPT-4) to analyze the content of the messages and extract and process important information.

[0150] Hardware and software used

[0151] Terminal: A device used by a user, such as a personal computer or smartphone.

[0152] Server: A remotely located computer system that handles message analysis and notification processing.

[0153] Generative AI models: Algorithms for natural language processing (e.g., GPT-4).

[0154] Message analysis and chat room suggestions

[0155] When a user sends a message using a business chat tool saying, "Report on the progress of a new project," the device receives the message and sends it to the server, which then uses a generative AI model to analyze the message and extract important keywords and topics.

[0156] Based on the extracted information, the server generates appropriate communication room candidates (e.g., "Project Progress Report" or "New Project") and sends them to the terminal. The terminal displays the candidates to the user, who then selects an appropriate chat room.

[0157] Suggest and create new chat rooms

[0158] When a user inputs and sends a request to create a chat room for "Regular Marketing Team Meetings," the device receives the request and sends it to the server, which uses a generative AI model to analyze the request and extract relevant keywords.

[0159] The server compares the extracted keywords with existing collaboration room information and makes a proposal to create a new room or use an existing room. The proposal results are sent to the user's terminal and displayed to the user.

[0160] Message priority organization and notification

[0161] If a user receives a message saying, "Please handle an order from a client urgently," the device sends this message to the server, which uses a generative AI model to analyze the urgency and importance of the message and sets it as high priority.

[0162] For the set high-priority messages, the server creates a dedicated notification and sends it to the terminal, which displays the notification to the user and prompts them to respond promptly.

[0163] Chat room summary

[0164] When a user sends a request such as "Please send me a summary of the weekly chat room report," the device receives the request and sends it to the server, which uses a generative AI model to analyze past messages in the specified chat room, extract key points, and create a summary.

[0165] The created summary is sent to the terminal and provided to the user, allowing the user to quickly grasp important information and carry out work efficiently.

[0166] Specific examples

[0167] As a concrete example, the following prompt sentence is used:

[0168] "Do you want to create a new chat room or view an existing chat room?"

[0169] "Does this message require urgent attention?"

[0170] As a result, the present invention provides support for users to efficiently use business communication tools and quickly grasp important information.

[0171] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0172] Step 1:

[0173] A user sends a message using a business chat tool. Specifically, the user enters text such as "Report on the progress of a new project" and clicks the send button. This input text is sent to the device.

[0174] Step 2:

[0175] The device receives the message sent by the user. The received message is temporarily stored in the internal memory.

[0176] Step 3:

[0177] The terminal sends the received message to the server. Specifically, the message data is sent in packet format to the server's address. At this stage, the input data is the message text, and the output data is the text data sent to the server.

[0178] Step 4:

[0179] The server analyzes the received message. A generative AI model (e.g., GPT-4) is used to analyze the message content and extract keywords and important topics. The input is the message text data, and the output is a list of extracted keywords.

[0180] Step 5:

[0181] The server generates appropriate communication room candidates based on the extracted keywords and topics. Specifically, it generates candidate room names such as "Project Progress Report" and "New Project." The input of this process is a keyword list, and the output is a communication room candidate list.

[0182] Step 6:

[0183] The server sends the created communication room candidate list to the terminal, and the sent data arrives at the terminal as the room candidate list.

[0184] Step 7:

[0185] The device displays chat room candidates to the user and prompts them to select one. Specifically, a list of candidates such as "Project Progress Report" and "New Project" is displayed on the user's screen. The user selects an appropriate chat room from these candidates.

[0186] Step 8:

[0187] When a user wishes to create a new chat room, he or she inputs a request such as "Regular meeting of the marketing team" in a message and sends it. This input data is sent to the terminal.

[0188] Step 9:

[0189] The terminal receives the request and sends it to the server. The request data is sent to the server in packet format.

[0190] Step 10:

[0191] The server analyzes the request content using a generative AI model and extracts related keywords (e.g., "marketing" or "regular meeting"). The input is the request text data, and the output is a list of related keywords.

[0192] Step 11:

[0193] The server compares the extracted keywords with existing collaboration room information and makes proposals for creating new rooms or merging existing rooms. The input is a list of keywords and existing room information, and the output is the proposal results.

[0194] Step 12:

[0195] The proposal result is sent to the terminal, which displays it to the user. Specifically, it displays the prompt "Do you want to use the existing marketing team chat room?" The user can take appropriate action based on this proposal.

[0196] Step 13:

[0197] When a user receives a message saying "Please handle the client's order as soon as possible," the terminal sends this message to the server. The input is the message text, and the output is the data to be sent to the server.

[0198] Step 14:

[0199] The server uses a generative AI model to analyze the urgency and importance of messages and set them as high priority. The input is message text data, and the output is priority setting information.

[0200] Step 15:

[0201] The server creates a dedicated notification for the high-priority message and sends it to the terminal as notification data containing the important message.

[0202] Step 16:

[0203] The device displays a notification to the user to prompt them to take action. Specifically, a notification such as "You have an important message" is displayed on the user's screen.

[0204] Step 17:

[0205] When a user sends a request such as "Please give me a summary of the weekly report chat room," the terminal receives the request and sends it to the server. The input is the summary request text, and the output is the data to be sent to the server.

[0206] Step 18:

[0207] The server uses a generative AI model to analyze past messages in a specified chat room, extract important points, and create a summary. The input is past message data, and the output is summary data.

[0208] Step 19:

[0209] The server sends the summary to the terminal, which then provides it to the user. Specifically, the summarized content is displayed on the user's screen.

[0210] The above are the specific processing steps of the system according to the present invention.

[0211] (Application example 1)

[0212] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0213] In today's content distribution services, it is difficult for users to easily find information and communication forums related to the content they are viewing. Therefore, a system is needed that allows users to efficiently obtain the information they need and to quickly and smoothly engage in related communication.

[0214] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0215] In this invention, the server includes means for analyzing messages received from users, means for proposing highly relevant chat room candidates based on the analysis results, means for notifying users of the proposed chat room candidates, means for analyzing content currently being viewed by users and extracting related keywords, means for proposing related forums or chat rooms based on the extracted keywords, and means for notifying users of the proposed forums or chat rooms, thereby enabling users to instantly find forums or chat rooms related to the content currently being viewed, improving information sharing and communication.

[0216] The "means for analyzing messages" is a function for analyzing the contents of messages sent by users and extracting specific keywords and important topics.

[0217] The "means for proposing chat room candidates" is a function for displaying chat room candidates that are highly relevant to the user based on the results of the analysis.

[0218] The "means for notifying users of chat room candidates" is a function for notifying the user of proposed chat room candidates on the user's terminal and displaying them to the user.

[0219] The "means for analyzing content" is a function that analyzes the content of videos and other content that a user is watching and extracts related keywords and topics.

[0220] The "means for extracting keywords" is a function for identifying and extracting important keywords and topics from the information obtained by analyzing the content.

[0221] The "means for suggesting forums or chat rooms" is a function that suggests related forums or chat rooms to the user based on the extracted keywords.

[0222] The "means for notifying a user of a forum or chat room" is a function for notifying a user of a proposed forum or chat room on the user's terminal and displaying it to the user.

[0223] The present invention provides a system for suggesting and informing users of forums and chat rooms related to the content they are currently viewing, and includes an analysis means using a generative AI model. Specific embodiments for implementing the present invention will be described below.

[0224] First, the server at the center of the system includes a means for analyzing messages received from users, a means for proposing highly relevant chat room candidates based on the analysis results, and a means for notifying users of the proposed chat room candidates.Furthermore, the system includes a means for analyzing the content being viewed by users and extracting related keywords, a means for proposing related forums or chat rooms based on the extracted keywords, and a means for notifying users of the same.

[0225] The system runs on devices such as smartphones, smart glasses, or head-mounted displays. The devices are connected to the internet and can communicate with the server. It uses OpenAI's GPT-4 as a generative AI model for analysis, and is written in Python.

[0226] Specifically, when a user inputs the ID of the content they are watching, the server retrieves the content and uses a generative AI model (GPT-4) to extract keywords and topics. An example of a prompt sentence is "Extract the main topics and keywords from the following content: This video is about AI advancements in healthcare."

[0227] The server then suggests related forums or chat rooms based on the extracted keywords. This suggestion information is sent to the user's device, allowing the user to access related forums or chat rooms. For example, if a user is watching a video titled "Advancements in Medical Care Through AI," the server analyzes the content, extracts keywords such as "Healthcare AI" and "Advancements in AI," and suggests related forums and chat rooms.

[0228] This allows users to easily obtain information and discussions related to the content they are viewing, facilitating efficient information sharing and communication. The overall system processing flow is based on natural language processing technology and machine learning models, aiming to improve the content experience.

[0229] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0230] Step 1:

[0231] The user selects the content to view and enters the ID of that content into the device. The device then sends this content ID to the server. The input is the content ID, and the output is sending the content ID to the server.

[0232] Step 2:

[0233] The server retrieves the details of the related content based on the received content ID, including the content title, description, tags, etc. The input is the content ID, and the output is the detailed content information.

[0234] Step 3:

[0235] The server uses a generative AI model (GPT-4) to analyze the detailed information of the content and extract the main topics and keywords. In this process, a prompt is created for the generative AI model and the results are analyzed. The input is the detailed information of the content, and the output is a list of the main topics and keywords. An example of a prompt is "Extract the main topics and keywords from the following content: [Detailed information of the content]".

[0236] Step 4:

[0237] The server generates a list of related forums and chat rooms based on the extracted keywords. It compares them with an existing forum database and selects the most relevant ones. The input is the extracted keywords, and the output is a list of related forums and chat rooms.

[0238] Step 5:

[0239] The server sends the generated list of forums and chat rooms to the terminal. The input is the list of forums and chat rooms, and the output is sending the list to the terminal.

[0240] Step 6:

[0241] The terminal displays the received list of forums and chat rooms to the user, who selects the forums and chat rooms of interest from the suggested list. The input is the list of forums and chat rooms, and the output is the user's selection.

[0242] Step 7:

[0243] Instantly joins a forum or chat room selected by the user. The device sends the selected chat room ID to the server, which then connects the user to that chat room. The input is the selected chat room ID, and the output is the user's connection to the chat room.

[0244] This allows users to quickly find information and discussions related to the content they are viewing, enabling efficient information sharing and communication.

[0245] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0246] The present invention provides a system that enables users to efficiently use business communication tools, and includes a chat management function that utilizes generative AI and an emotion engine. Specific embodiments for implementing the present invention will be described below.

[0247] Message analysis and chat room suggestions

[0248] 1. Message reception and analysis

[0249] A user sends a message using a business chat tool.

[0250] The terminal receives this message and sends it to the server.

[0251] The server runs a generative AI model to analyze the content of the message, extracting keywords and important topics.

[0252] 2. Chat room suggestions

[0253] The server generates suitable chat room candidates based on the message analysis results.

[0254] The server sends chat room candidates to the terminal.

[0255] The terminal displays chat room candidates to the user and prompts the user to select one.

[0256] Examples:

[0257] If a user sends a message saying "New project progress report," the server will suggest related chat rooms such as "Project progress report" and "New project."

[0258] Suggest and create new chat rooms

[0259] 1. Parsing chat room creation requests

[0260] The user inputs a message indicating their intention to create a new chat room and sends it.

[0261] The terminal receives the request and sends it to the server.

[0262] The server uses the generated AI model to analyze the request content and extract relevant keywords.

[0263] 2. Comparison with existing chat rooms and proposals

[0264] The server compares the received request with existing chat rooms.

[0265] If the server finds no duplicate entries, it will propose creating a new chat room, otherwise it will propose merging.

[0266] The proposal results are sent to the terminal and displayed to the user.

[0267] Examples:

[0268] When a user submits a request to create a chat room for "Regular Marketing Team Meetings," the server checks to see if there is an existing "Marketing Team" chat room and makes appropriate suggestions.

[0269] Message priority organization and notification

[0270] 1. Message Reception and Priority Analysis

[0271] The user receives a message from a team member. The device receives the message and forwards it to the server.

[0272] 2. Prioritization and Notifications

[0273] The server uses the generated AI model to analyze the content of the message and assess its urgency and importance.

[0274] The server assigns a priority to the message based on the analysis results, categorizing it as high priority, medium priority, or low priority.

[0275] The server generates a dedicated notification for high-priority messages and sends it to the device, which displays a notification of the important message to the user.

[0276] Examples:

[0277] When a user receives a message saying "Please respond to an order from a client as soon as possible," the server analyzes the urgency of the message and issues a notification with high priority.

[0278] Chat room summary

[0279] 1. Processing Abstract Requests

[0280] A user sends a message requesting a summary of the chat room contents. The terminal receives the request and sends it to the server.

[0281] 2. Generating and serving summaries

[0282] The server launches the generative AI model and analyzes past messages in the specified chat room.

[0283] The server extracts key points from the analysis and creates a summary, including key progress, decisions, and next steps.

[0284] The server sends the created summary to the terminal, which displays the summary to the user.

[0285] Examples:

[0286] When a user sends a request such as "Please send me a summary of the weekly report chat room," the server analyzes the messages in the chat room, generates a summary including important progress, decisions, next steps, etc., and sends it to the terminal.

[0287] Combining Emotion Engines

[0288] 1. Sentiment Analysis and Action

[0289] When a user sends or receives a message, the emotion engine analyzes the message's emotion, and the server suggests or executes an action based on the results of the emotion analysis.

[0290] The server adjusts chat room suggestions, priorities, and notification content based on the emotions recognized.

[0291] Examples:

[0292] If a user sends a message expressing stress or tension (e.g., "This task is really difficult!"), the emotion engine recognizes this emotion and the server suggests appropriate support messages and resources.

[0293] Through the specific processing steps of this system, users can efficiently manage messages, quickly grasp important information, and receive emotionally sensitive responses and suggestions.

[0294] The processing flow will be explained below.

[0295] Message analysis and chat room suggestions

[0296] Processing Steps:

[0297] Step 1:

[0298] A user uses a business chat tool to type a message and presses the "Send" button. The device receives the message and sends it to the server.

[0299] Step 2:

[0300] The server receives the message, activates a generative AI model, and analyzes the message content, extracting keywords and important topics.

[0301] Step 3:

[0302] Based on the analysis results, the server evaluates the relevance to existing chat rooms and generates highly relevant chat room candidates.

[0303] Step 4:

[0304] The server sends the generated chat room candidate list to the terminal, which displays the chat room candidates to the user and prompts them to make a selection.

[0305] Suggest and create new chat rooms

[0306] Processing Steps:

[0307] Step 1:

[0308] The user enters a message about the new chat room they wish to create and presses the "Send" button. The device receives this message and sends it to the server.

[0309] Step 2:

[0310] The server receives the request, activates the generative AI model, and analyzes the request. Keywords and topics are extracted as a result of the analysis.

[0311] Step 3:

[0312] The server compares the request with existing chat rooms based on extracted keywords and topics, and evaluates relevance and overlap.

[0313] Step 4:

[0314] Based on the comparison, the server makes a suggestion to the user: either to create a new chat room or to merge into an existing chat room.

[0315] Step 5:

[0316] The server sends the proposal results to the device, which displays the proposals to the user and prompts them to make a selection.

[0317] Message priority organization and notification

[0318] Processing Steps:

[0319] Step 1:

[0320] The user receives a message from a team member. The device receives the message and forwards it to the server.

[0321] Step 2:

[0322] The server receives the message and uses a generative AI model to analyze the message content and assess its urgency and importance.

[0323] Step 3:

[0324] The server assigns a priority to the message based on the analysis results, categorizing it into high, medium, and low priority categories.

[0325] Step 4:

[0326] The server generates a dedicated notification for high-priority messages and sends it to the device, which displays a notification of the important message to the user.

[0327] Chat room summary

[0328] Processing Steps:

[0329] Step 1:

[0330] A user sends a message requesting a summary of the chat room contents. The terminal receives the request and sends it to the server.

[0331] Step 2:

[0332] The server receives the request, launches the generative AI model, and analyzes past messages in the specified chat room.

[0333] Step 3:

[0334] The server extracts key points from the analysis and creates a summary, including key progress, decisions, and next steps.

[0335] Step 4:

[0336] The server sends the created summary to the terminal, which displays the summary to the user.

[0337] Combining Emotion Engines

[0338] Processing Steps:

[0339] Step 1:

[0340] When a user sends a message, the device sends the message to the server, which receives the message and uses the emotion engine to analyze the emotion of the message.

[0341] Step 2:

[0342] The server receives the analysis results of the emotion engine and suggests or executes actions based on the recognized emotions. For example, if the user is feeling stressed, it generates an appropriate support message.

[0343] Step 3:

[0344] The server adjusts chat room suggestions and notification content based on the recognized emotion. For example, if the user is feeling stressed, chat room suggestions are adjusted to address issues that can be easily resolved.

[0345] Step 4:

[0346] The server sends the adjusted chat room suggestions and notification content to the terminal, which displays them to the user and prompts them to make a selection or confirm.

[0347] Examples:

[0348] Message Parsing:

[0349] When a user sends a message saying "New project progress report," the server suggests chat rooms related to "Project progress report" and "New project."

[0350] New chat room suggestions:

[0351] When a user submits a request to create a chat room for "Regular Marketing Team Meetings," the server checks to see if there is an existing "Marketing Team" chat room and makes a suggestion.

[0352] Message priority organization:

[0353] When a user receives a message saying "Please respond to an order from a client as soon as possible," the server analyzes the urgency of the message and issues a notification with high priority.

[0354] Emotion Engine:

[0355] If a user sends a message such as "This task is really difficult!", the emotion engine will recognize the stress and the server will suggest an appropriate support message.

[0356] Example 2

[0357] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0358] Current business chat tools make it difficult for users to efficiently manage messages and join or create new chat rooms. They also lack the functionality to quickly evaluate and notify the importance and urgency of received messages. Furthermore, functions such as message sentiment analysis and summary generation are inadequate. Therefore, there is a need to provide a stress-free communication environment for users.

[0359] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0360] In this invention, the server includes: means for analyzing messages received from a user; means for suggesting relevant chat room candidates based on the analysis results; means for notifying the user of the suggested chat room candidates; means for analyzing the sentiment of messages using a sentiment analysis engine and suggesting appropriate actions based on the analysis results; means for analyzing and setting the importance and priority of received messages; means for notifying the user of important messages based on the set priority; means for analyzing messages in a specified chat room and generating summaries; means for notifying the user of the generated summaries; means for analyzing messages using a generative AI model; and means for inputting prompts to the generative AI model to instruct analysis. This allows users to efficiently manage messages and join appropriate chat rooms or create new chat rooms. Furthermore, by quickly evaluating the importance and urgency of messages and performing sentiment analysis and summaries, a stress-free communication environment can be provided.

[0361] "User" means an individual or legal entity that uses the business communication tool to send or receive messages.

[0362] A "message" is data such as text, images, and audio that a user sends or receives through a business chat tool.

[0363] "Means of analysis" refers to the technology that analyzes the content of received messages and extracts keywords and important topics.

[0364] "Chat Room Suggestion" refers to a suggestion of a relevant existing or new chat room based on the analyzed content of the message.

[0365] "Means of notification" refers to technology that provides analysis results and notification content to users and encourages them to take the next action.

[0366] An "emotion analysis engine" refers to technology that analyzes the emotions contained in the content of a message and suggests appropriate actions based on the analysis results.

[0367] "Importance and priority" refers to the criteria for assessing and classifying the urgency and importance of received messages.

[0368] "Means for generating a summary" refers to a technology that analyzes past messages in a specified chat room, extracts key information, and creates a summary.

[0369] A "generative AI model" refers to a machine learning model that uses artificial intelligence technology to analyze messages and generate summaries.

[0370] A "prompt" refers to text that is entered to give specific instructions to a generative AI model.

[0371] The present invention provides a system that enables users to efficiently use business communication tools, and includes a chat management function that utilizes a generative AI model and an emotion engine. Specific embodiments for implementing the present invention will be described below.

[0372] Message analysis and chat room suggestions

[0373] 1. Message reception and analysis

[0374] A user uses a business chat tool to send a message such as "Report on the progress of a new project."

[0375] The terminal receives this message and sends it to the server.

[0376] The server launches a generative AI model (e.g., OpenAI's GPT-4) to analyze the message content. This analysis uses the prompt "Please extract keywords and topics from the following message." This results in the extraction of the keywords "new project," "progress," and "report."

[0377] 2. Chat room suggestions

[0378] The server generates appropriate chat room candidates based on the extracted keywords. For example, it compares the keywords with a list of existing chat rooms and suggests related chat rooms such as "project progress report" and "new project."

[0379] The server sends chat room candidates to the terminal.

[0380] The terminal displays chat room candidates to the user and prompts the user to select one.

[0381] Suggest and create new chat rooms

[0382] 1. Parsing chat room creation requests

[0383] A user enters a message stating that they want to create a new chat room, such as "Regular Marketing Team Meetings," and sends it.

[0384] The terminal receives the request and sends it to the server.

[0385] The server uses a generative AI model and prompts the user with the following sentence: "Analyze a new chat room request and extract relevant keywords." The server extracts keywords such as "marketing team" and "regular meeting" from the request.

[0386] 2. Comparison with existing chat rooms and proposals

[0387] The server compares the extracted keywords with the existing chat room list to check for overlapping content.

[0388] If the server has an existing chat room for "Marketing Team", it will suggest to the user, "Do you want to use the existing chat room?" If there is no overlap, it will suggest creating a new chat room.

[0389] The device displays the proposed results to the user, who can then choose to accept the proposal or create a new one.

[0390] Message priority organization and notification

[0391] 1. Message Reception and Priority Analysis

[0392] The user receives a message from a team member saying, "Please handle the client's order as soon as possible." The terminal receives this message and sends it to the server.

[0393] 2. Prioritization and Notifications

[0394] The server uses a generative AI model to analyze the message content by setting a prompt sentence: "Please rate the urgency and importance of this message." This determines the message to be of high urgency.

[0395] The server sets the message priority to "high" based on this result.

[0396] The server generates a dedicated notification for high-priority messages and sends it to the device. The device displays a notification of the important message to the user. The user checks the notification and responds promptly.

[0397] Chat room summary

[0398] 1. Processing Abstract Requests

[0399] A user requests a summary of the chat room contents by sending the message "Please give me a summary of the weekly chat room report." The terminal receives this request and sends it to the server.

[0400] 2. Generating and serving summaries

[0401] The server launches the generative AI model and uses the prompt, "Analyze the past messages in this chat room and summarize the key points." The server analyzes the past messages in the specified chat room and extracts key progress, decisions, next steps, etc.

[0402] The server creates a summary and sends it to the terminal, which displays the summary to the user, who reviews the summary and plans next steps.

[0403] Combining Emotion Engines

[0404] 1. Sentiment Analysis and Action

[0405] When a user sends or receives a message such as "This task is really difficult!", the emotion engine analyzes the emotion of the message. The server then suggests actions based on the results of this emotion analysis.

[0406] The server suggests appropriate support messages and resources based on the emotions it recognizes. Specifically, it generates support messages such as "Do you need additional resources for this task?"

[0407] The terminal displays a support message to the user, and the user requests resources as needed.

[0408] Through these processing steps, users can efficiently manage messages, join appropriate chat rooms, create new chat rooms, prioritize messages, generate summaries, and analyze sentiment, thereby providing a stress-free communication environment for users.

[0409] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0410] Message analysis and chat room suggestions

[0411] Step 1:

[0412] Receiving messages

[0413] A user types and sends a message via a business chat tool saying, "Report on the progress of a new project."

[0414] Input: User's message

[0415] Output: Request to send message to terminal

[0416] Step 2:

[0417] Message relay by terminal

[0418] The terminal transmits the message received from the user to the server.

[0419] Input: The user's sent message

[0420] Output: Message transfer request to server

[0421] Step 3:

[0422] Server parsing of messages

[0423] The server launches a generative AI model (e.g., GPT-4) and analyzes the message content using the prompt, "Please extract keywords and topics from the message below."

[0424] Input: Message received from the terminal, prompt text

[0425] Output: Extracted keywords "new project", "progress", "report"

[0426] Step 4:

[0427] Generate chat room candidates

[0428] The server compares the extracted keywords with a list of past chat rooms to generate highly relevant chat room candidates.

[0429] Input: Extracted keywords

[0430] Output: List of chat room candidates (e.g. "Project progress report", "New project")

[0431] Step 5:

[0432] Device notifications

[0433] The server transmits the generated chat room candidates to the terminal, and the terminal displays the chat room candidates to the user.

[0434] Input: Chat room candidate list

[0435] Output: Chat room suggestions displayed to the user

[0436] Suggest and create new chat rooms

[0437] Step 1:

[0438] Sending a chat room creation request

[0439] A user sends a message requesting the creation of a chat room called "Marketing Team Regular Meetings."

[0440] Input: User creation request message

[0441] Output: Request to send message to terminal

[0442] Step 2:

[0443] Terminal relays requests

[0444] The terminal transmits the request message received from the user to the server.

[0445] Input: User request message

[0446] Output: Request forwarded to server

[0447] Step 3:

[0448] Request analysis by the server

[0449] The server launches the generative AI model and analyzes the content of the request using the prompt "Analyze a new chat room request and extract relevant keywords."

[0450] Input: Request received from the terminal, prompt text

[0451] Output: Extracted keywords "marketing team" and "regular meeting"

[0452] Step 4:

[0453] Comparison with existing chat rooms

[0454] The server checks the extracted keywords against the existing chat room list to see if there are any overlaps.

[0455] Input: Extracted keywords

[0456] Output: Existing chat rooms

[0457] Step 5:

[0458] Proposal generation and notification

[0459] The server generates a proposal to create a new chat room or to merge with an existing chat room based on the request content and the comparison result, and sends it to the terminal. The terminal displays the proposal to the user.

[0460] Input: Request details, whether or not there is an existing chat room

[0461] Output: Proposal displayed to the user

[0462] Message priority organization and notification

[0463] Step 1:

[0464] Receiving messages

[0465] The user receives a message saying, "Please handle the order from the client as soon as possible." The terminal receives the message and sends it to the server.

[0466] Input: Incoming message

[0467] Output: Message transfer request to server

[0468] Step 2:

[0469] Message Priority Analysis

[0470] The server uses a generative AI model to set a prompt such as "Please rate the urgency and importance of this message" and analyze the message content.

[0471] Input: message, prompt

[0472] Output: Set priority (e.g. High)

[0473] Step 3:

[0474] Generate notifications based on priority

[0475] The server generates a dedicated notification for high-priority messages and sends it to the device, which displays a notification of the important message to the user.

[0476] Input: Set priority

[0477] Output: Important message notification to the user

[0478] Chat room summary

[0479] Step 1:

[0480] Submitting a Summary Request

[0481] The user sends a request saying, "Please send me a summary of the weekly chat room report." The device receives the request and forwards it to the server.

[0482] Input: User request message

[0483] Output: Request forwarded to server

[0484] Step 2:

[0485] Generate a summary

[0486] The server uses the generative AI model to set a prompt such as "Analyze the past messages in this chat room and summarize the important points," and analyzes the past messages in the specified chat room.

[0487] Input: Request, prompt, past message

[0488] Output: Generated summary

[0489] Step 3:

[0490] Provision to users

[0491] The server sends the generated summary to the terminal, which displays the summary to the user.

[0492] Input: Generated summary

[0493] Output: Summary displayed to the user

[0494] Combining Emotion Engines

[0495] Step 1:

[0496] Message sentiment analysis

[0497] When a user sends or receives a message such as "This task is really difficult!", the emotion engine analyzes the emotion of the message.

[0498] Input: Message sent or received

[0499] Output: Analysis results (e.g. stress, tension)

[0500] Step 2:

[0501] Suggestions for appropriate actions

[0502] Based on the results of the sentiment analysis, the server generates a support message asking, "Do you need additional resources for this task?" and sends it to the device. The device then displays the support message to the user.

[0503] Input: Sentiment analysis results

[0504] Output: Display support message to user

[0505] Through the above specific processing steps, users can efficiently manage messages and ensure smooth operation of the chat room. Furthermore, emotion analysis can reduce users' psychological burden and provide appropriate support.

[0506] (Application example 2)

[0507] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0508] Conventional business communication tools have limited functionality, such as message analysis and chat room suggestions, limiting the ways for users to quickly and efficiently obtain the information they need. Furthermore, systems for appropriately classifying message urgency and importance and for advanced communication are inadequate. In particular, systems requiring advanced operational management, such as autonomous vehicles, often require real-time emergency response and appropriate instructions based on emotion analysis, and existing systems have difficulty meeting these requirements.

[0509] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0510] In this invention, the server includes means for analyzing messages received from users, means for proposing highly relevant chat room candidates based on the analysis results, means for notifying users of the proposed chat room candidates, means for analyzing the sentiment of the messages, means for adjusting the chat room candidates based on the sentiment analysis results, and means for setting message priorities and generating notifications according to urgency, thereby enabling users to quickly and efficiently obtain necessary information and appropriately respond to emergencies and important messages.

[0511] "Analysis of messages received from users" is a process of automatically analyzing the contents of messages sent by users and extracting important keywords and contexts.

[0512] "Suggesting relevant chat room candidates" is a function that identifies and suggests appropriate chat rooms for the user to join based on the results of message analysis.

[0513] "Emotion analysis" is an analytical process for determining the emotional state of the sender and receiver from the content of a message.

[0514] "Adjusting chat room candidates" is a process of optimizing the list of chat rooms suggested to the user based on the results of sentiment analysis.

[0515] "Message priority setting" is a function that evaluates the importance and urgency of received messages and automatically sets the priority accordingly.

[0516] "Generating notifications according to urgency" is a function that sends special notifications to users for messages that are important and urgent based on the set priority.

[0517] "Analysis of chat room creation requests" is a process that automatically analyzes new chat room creation requests from users and understands their intent.

[0518] "Compare with existing chat rooms" refers to the process of comparing a new chat room creation request with existing chat rooms to determine if the request overlaps with an existing chat room.

[0519] "Proposal to create or merge a new chat room" is a function that suggests to the user to create a new chat room or merge with an existing chat room based on the analysis results.

[0520] "Quick suggestion of appropriate responses in emergencies" is a function that quickly suggests to users the actions and countermeasures required in emergencies.

[0521] As a mode for carrying out the present invention, an embodiment of a communication and operation management system for an autonomous driving vehicle will be described below.

[0522] The system analyzes messages received from users and suggests appropriate chat rooms based on the results of the analysis. It can also analyze the sentiment of messages, generate notifications based on urgency, and compare existing chat rooms.

[0523] Receiving and parsing messages

[0524] The server receives messages sent by users, which are then analyzed using a generative AI model (e.g., the Sentiment Analysis model from HuggingFace's transformers library) to extract important keywords and context and suggest appropriate chat rooms based on the content.

[0525] Emotion analysis

[0526] The server uses a generative AI model to analyze the sentiment of the message. Based on this analysis, it adjusts chat room suggestions and optimizes the suggestions as needed. For example, if a message is sent saying, "An accident has occurred. Immediate action is required," the server will determine this message as "negative" and suggest a chat room that requires a high level of urgency.

[0527] Prioritization and Notifications

[0528] The server classifies received messages based on importance and urgency, and generates special notifications based on the set priority and sends them to the user's device, allowing the user to quickly understand important messages and urgent actions.

[0529] Creating and comparing chat rooms

[0530] When a user requests to create a new chat room, the server analyzes the request and compares it with existing chat rooms. If there are no overlaps, the server proposes the creation of a new chat room, and if there are overlaps, it proposes merging. For example, if a request comes in to "report on the progress of a new project," the server checks whether there is an existing "project progress report" chat room and makes an appropriate proposal.

[0531] Specific examples

[0532] When an autonomous vehicle sends a message saying, "Left front tire pressure is low," the message is analyzed by a generative AI model. As a result, the message is determined to be "negative," a notification is sent to the maintenance team's chat room, and a prompt is generated: "New maintenance request: Left front tire pressure is low," suggesting an appropriate response.

[0533] Prompt Sentence Examples

[0534] A new maintenance request has arrived:

[0535] Vehicle ID: Vehicle1234

[0536] Message: Left front tire pressure low

[0537] In this way, the system of the present invention realizes efficient business communication by analyzing the user's messages in detail and making appropriate suggestions and notifications that take into account the user's emotions and urgency.

[0538] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0539] Step 1:

[0540] A user sends a message from a device inside an autonomous vehicle.

[0541] The user inputs a message and presses the send button to send it to the terminal. An input message might be something like "The air pressure in the left front tire is low." The output is the message data that was sent.

[0542] Step 2:

[0543] The terminal transfers the received message to the server.

[0544] When a terminal receives a message from a user, it sends the contents of the message to the server. The input is the received message data, and the output is the message data transferred to the server.

[0545] Step 3:

[0546] The server analyzes the message content using a generative AI model.

[0547] The server inputs the received message data into the generative AI model and performs an analysis to extract keywords and context. This analysis extracts important information. The input is the message data, and the output is the keywords and context information that are the analysis results.

[0548] Step 4:

[0549] The server performs sentiment analysis.

[0550] The server uses the generative AI model to analyze the sentiment of the message. The input is the analysis result from step 3, and the output is the analyzed sentiment data (e.g., negative or positive classification and its confidence score).

[0551] Step 5:

[0552] The server proposes chat room candidates based on the analysis results.

[0553] The server identifies relevant chat room candidates based on the message keywords and sentiment analysis results and generates a list. The input is the analysis results of steps 3 and 4, and the output is a list of chat room candidates.

[0554] Step 6:

[0555] The server notifies the terminal of chat room candidates.

[0556] The server sends the generated list of chat room candidates to the terminal and displays it to the user. The input is the list of chat room candidates, and the output is a notification displayed on the user's terminal.

[0557] Step 7:

[0558] The user selects a chat room.

[0559] The user selects the most suitable chat room from the chat room candidates displayed on the terminal. The input is the chat room candidate list displayed on the terminal, and the output is the selected chat room.

[0560] Step 8:

[0561] The server parses the request to create a new chat room.

[0562] When a user sends a request, the server receives it and analyzes the content using a generative AI model. The input is the request message from the user, and the output is the analyzed request data.

[0563] Step 9:

[0564] The server compares the new request with existing chat rooms.

[0565] The server compares the parsed request data with the existing chat room database to check for duplicates. The input is the parsed request data and existing chat room data, and the output is the presence or absence of duplicates and new proposed data.

[0566] Step 10:

[0567] The server will propose the creation or merging of new chat rooms.

[0568] Based on the comparison results, the server proposes a future action (creating a new chat room or merging into an existing chat room) to the user. The input is the comparison result data, and the output is a proposal notification.

[0569] Step 11:

[0570] The server prioritizes messages and generates notifications based on urgency.

[0571] The server evaluates the importance and urgency of messages and generates special notifications for high-priority messages. The input is the analysis results and importance rating data, and the output is the generated special notifications.

[0572] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0573] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0574] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0575] [Second embodiment]

[0576] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0577] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0578] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0579] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0580] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0581] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0582] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0583] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0584] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0585] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0586] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0587] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0588] The present invention provides a system that enables users to efficiently use business communication tools, and includes a chat management function that utilizes AI generation. Specific embodiments for implementing the present invention will be described below.

[0589] Message analysis and chat room suggestions

[0590] 1. Message reception and analysis

[0591] A user sends a message using a business chat tool.

[0592] The terminal receives this message and sends it to the server.

[0593] The server uses a generative AI model to analyze the content of the message, extracting keywords and important topics.

[0594] 2. Chat room suggestions

[0595] The server generates suitable chat room candidates based on the message analysis results.

[0596] The server sends chat room candidates to the terminal.

[0597] The terminal displays chat room candidates to the user and prompts the user to select one.

[0598] Examples:

[0599] If a user sends a message saying "New project progress report," the server will suggest related chat rooms such as "Project progress report" and "New project."

[0600] Suggest and create new chat rooms

[0601] 1. Parsing chat room creation requests

[0602] The user inputs a message indicating their intention to create a new chat room and sends it.

[0603] The terminal receives the request and sends it to the server.

[0604] The server uses the generated AI model to analyze the request content and extract relevant keywords.

[0605] 2. Comparison with existing chat rooms and proposals

[0606] The server compares the received request with existing chat rooms.

[0607] If the server finds no duplicate entries, it will propose creating a new chat room, otherwise it will propose merging.

[0608] The proposal results are sent to the terminal and displayed to the user.

[0609] Examples:

[0610] When a user submits a request to create a chat room for "Regular Marketing Team Meetings," the server checks to see if there is an existing "Marketing Team" chat room and makes appropriate suggestions.

[0611] Message priority organization and notification

[0612] 1. Message Reception and Priority Analysis

[0613] The user receives the message.

[0614] The terminal sends this message to the server.

[0615] The server uses the generated AI model to analyze the urgency and importance of the message.

[0616] 2. Prioritization and Notifications

[0617] The server sets the priority of the message based on the analysis results.

[0618] The server creates a dedicated notification for high priority messages and sends it to the device.

[0619] The device displays a notification to the user.

[0620] Examples:

[0621] When a user receives a message saying "Please respond to an order from a client as soon as possible," the server analyzes the importance of the message and notifies the user as a high priority.

[0622] Chat room summary

[0623] 1. Processing Abstract Requests

[0624] A user enters and submits a request for a summary of the chat room.

[0625] The terminal receives the request and sends it to the server.

[0626] 2. Generating and serving summaries

[0627] The server uses the generated AI model to analyze past messages in a specified chat room.

[0628] The server extracts the key points and creates a summary.

[0629] The summary is sent to the terminal and presented to the user.

[0630] Examples:

[0631] When a user sends a request such as "Please send me a summary of the weekly report chat room," the server analyzes all messages in that chat room, creates a summary including important progress, decisions, and next steps, and sends it to the device.

[0632] In this way, the present invention provides support for users to improve work efficiency and quickly grasp important information.

[0633] The processing flow will be explained below.

[0634] Message analysis and chat room suggestions

[0635] Processing Steps:

[0636] Step 1:

[0637] The user enters a message and presses the "Send" button. The device receives the message and sends it to the server.

[0638] Step 2:

[0639] The server receives the message. The server then launches a generative AI model to analyze the message content. Through analysis, keywords and key points from the message are extracted.

[0640] Step 3:

[0641] Based on the analysis results, the server evaluates the relevance to existing chat rooms and generates highly relevant chat room candidates.

[0642] Step 4:

[0643] The server sends the generated chat room candidate list to the terminal, which displays the chat room candidates to the user and prompts them to make a selection.

[0644] Suggest and create new chat rooms

[0645] Processing Steps:

[0646] Step 1:

[0647] The user enters a message about the new chat room they wish to create and presses the "Send" button. The device receives this message and sends it to the server.

[0648] Step 2:

[0649] The server receives the request, activates the generative AI model, and analyzes the request. Keywords and topics are extracted as a result of the analysis.

[0650] Step 3:

[0651] The server compares the request with existing chat rooms based on extracted keywords and topics, and evaluates relevance and overlap.

[0652] Step 4:

[0653] Based on the comparison, the server makes a suggestion to the user: either to create a new chat room or to merge into an existing chat room.

[0654] Step 5:

[0655] The server sends the proposal results to the device, which displays the proposals to the user and prompts them to make a selection.

[0656] Message priority organization and notification

[0657] Processing Steps:

[0658] Step 1:

[0659] The user receives a message from a team member. The device receives the message and forwards it to the server.

[0660] Step 2:

[0661] The server receives the message and uses a generative AI model to analyze the message content and assess its urgency and importance.

[0662] Step 3:

[0663] The server assigns a priority to the message based on the analysis results, categorizing it into high, medium, and low priority categories.

[0664] Step 4:

[0665] The server generates a dedicated notification for high-priority messages and sends it to the device, which displays a notification of the important message to the user.

[0666] Chat room summary

[0667] Processing Steps:

[0668] Step 1:

[0669] A user sends a message requesting a summary of the chat room contents. The terminal receives the request and sends it to the server.

[0670] Step 2:

[0671] The server receives the request, launches the generative AI model, and analyzes past messages in the specified chat room.

[0672] Step 3:

[0673] The server extracts key points from the analysis and creates a summary, including key progress, decisions, and next steps.

[0674] Step 4:

[0675] The server sends the created summary to the terminal, which displays the summary to the user.

[0676] Through the specific processing steps of this system, users can efficiently manage messages and quickly grasp important information.

[0677] Example 1

[0678] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0679] Conventional business communication tools have limited capabilities for analyzing received messages, making it difficult to quickly and accurately present appropriate chat room or collaboration room candidates. Furthermore, they often lack the functionality to quickly determine the urgency and importance of users' messages and provide immediate notifications for high-priority messages. As a result, users are at greater risk of overlooking important information, which can lead to reduced work efficiency. Furthermore, when users create a new chat room, it is difficult to avoid overlaps with existing chat rooms and to suggest appropriate rooms. Therefore, the present invention aims to solve these problems.

[0680] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0681] In this invention, the server includes means for analyzing messages received from users, means for proposing highly relevant communication room candidates based on the analysis results, means for notifying users of the proposed communication room candidates, means for analyzing the content of messages using a generative AI model and extracting important keywords and topics, means for generating appropriate collaboration rooms based on the extracted information, and means for transmitting and displaying the generated collaboration room proposals to user terminals, thereby enabling users to conduct business communication quickly and effectively without overlooking important information.

[0682] "User" refers to an individual or organization that uses the business communication tools of this system.

[0683] "Message" refers to text information sent by a user through a business chat tool.

[0684] "Terminal" refers to the hardware device used by a User to access the System.

[0685] "Server" refers to a remotely located computer system that performs central processing for the System.

[0686] "Means of analysis" refers to the process of using a generative AI model to understand the content of a message and extract key elements.

[0687] A "generative AI model" refers to an algorithm that applies artificial intelligence technology to analyze text data and generate or extract specific information.

[0688] A "communication room" is a virtual room for exchanging messages about a specific topic or project.

[0689] "Collaboration Room" refers to a virtual room where users can collaborate on a specific team or project.

[0690] "Means of suggestion" refers to the process of showing users appropriate communication or collaboration rooms based on the analysis results.

[0691] "Means for notifying" refers to the process for displaying suggested rooms and important messages to users.

[0692] "Importance" refers to an index that indicates how urgent or important the content of a message is to the user.

[0693] "Priority" refers to an index that determines the priority of processing or notification based on the importance of a message.

[0694] "Comparison method" refers to the process of checking user requests against existing information to identify overlaps and relevance.

[0695] A "request" refers to a message that a user sends to the system to inform the system that they wish to create a new collaboration room.

[0696] "Proposal Results" refers to action plans or recommendations to users that are generated as a result of the analysis and comparison.

[0697] The present invention provides a system that enables users to efficiently use business communication tools, and includes a chat management function that utilizes a generative AI model. Specific embodiments for implementing the present invention will be described below.

[0698] Configuration and operation overview

[0699] In this invention, when a user sends and receives messages using a business chat tool, a server and a terminal work together to provide advanced functions such as analysis, suggestions, notifications, and summaries. The server uses a generative AI model (e.g., OpenAI's GPT-4) to analyze the content of the messages and extract and process important information.

[0700] Hardware and software used

[0701] Terminal: A device used by a user, such as a personal computer or smartphone.

[0702] Server: A remotely located computer system that handles message analysis and notification processing.

[0703] Generative AI models: Algorithms for natural language processing (e.g., GPT-4).

[0704] Message analysis and chat room suggestions

[0705] When a user sends a message using a business chat tool saying, "Report on the progress of a new project," the device receives the message and sends it to the server, which then uses a generative AI model to analyze the message and extract important keywords and topics.

[0706] Based on the extracted information, the server generates appropriate communication room candidates (e.g., "Project Progress Report" or "New Project") and sends them to the terminal. The terminal displays the candidates to the user, who then selects an appropriate chat room.

[0707] Suggest and create new chat rooms

[0708] When a user inputs and sends a request to create a chat room for "Regular Marketing Team Meetings," the device receives the request and sends it to the server, which uses a generative AI model to analyze the request and extract relevant keywords.

[0709] The server compares the extracted keywords with existing collaboration room information and makes a proposal to create a new room or use an existing room. The proposal results are sent to the user's terminal and displayed to the user.

[0710] Message priority organization and notification

[0711] If a user receives a message saying, "Please handle an order from a client urgently," the device sends this message to the server, which uses a generative AI model to analyze the urgency and importance of the message and sets it as high priority.

[0712] For the set high-priority messages, the server creates a dedicated notification and sends it to the terminal, which displays the notification to the user and prompts them to respond promptly.

[0713] Chat room summary

[0714] When a user sends a request such as "Please send me a summary of the weekly chat room report," the device receives the request and sends it to the server, which uses a generative AI model to analyze past messages in the specified chat room, extract key points, and create a summary.

[0715] The created summary is sent to the terminal and provided to the user, allowing the user to quickly grasp important information and carry out work efficiently.

[0716] Specific examples

[0717] As a concrete example, the following prompt sentence is used:

[0718] "Do you want to create a new chat room or view an existing chat room?"

[0719] "Does this message require urgent attention?"

[0720] As a result, the present invention provides support for users to efficiently use business communication tools and quickly grasp important information.

[0721] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0722] Step 1:

[0723] A user sends a message using a business chat tool. Specifically, the user enters text such as "Report on the progress of a new project" and clicks the send button. This input text is sent to the device.

[0724] Step 2:

[0725] The device receives the message sent by the user. The received message is temporarily stored in the internal memory.

[0726] Step 3:

[0727] The terminal sends the received message to the server. Specifically, the message data is sent in packet format to the server's address. At this stage, the input data is the message text, and the output data is the text data sent to the server.

[0728] Step 4:

[0729] The server analyzes the received message. A generative AI model (e.g., GPT-4) is used to analyze the message content and extract keywords and important topics. The input is the message text data, and the output is a list of extracted keywords.

[0730] Step 5:

[0731] The server generates appropriate communication room candidates based on the extracted keywords and topics. Specifically, it generates candidate room names such as "Project Progress Report" and "New Project." The input of this process is a keyword list, and the output is a communication room candidate list.

[0732] Step 6:

[0733] The server sends the created communication room candidate list to the terminal, and the sent data arrives at the terminal as the room candidate list.

[0734] Step 7:

[0735] The device displays chat room candidates to the user and prompts them to select one. Specifically, a list of candidates such as "Project Progress Report" and "New Project" is displayed on the user's screen. The user selects an appropriate chat room from these candidates.

[0736] Step 8:

[0737] When a user wishes to create a new chat room, he or she inputs a request such as "Regular meeting of the marketing team" in a message and sends it. This input data is sent to the terminal.

[0738] Step 9:

[0739] The terminal receives the request and sends it to the server. The request data is sent to the server in packet format.

[0740] Step 10:

[0741] The server analyzes the request content using a generative AI model and extracts related keywords (e.g., "marketing" or "regular meeting"). The input is the request text data, and the output is a list of related keywords.

[0742] Step 11:

[0743] The server compares the extracted keywords with existing collaboration room information and makes proposals for creating new rooms or merging existing rooms. The input is a list of keywords and existing room information, and the output is the proposal results.

[0744] Step 12:

[0745] The proposal result is sent to the terminal, which displays it to the user. Specifically, it displays the prompt "Do you want to use the existing marketing team chat room?" The user can take appropriate action based on this proposal.

[0746] Step 13:

[0747] When a user receives a message saying "Please handle the client's order as soon as possible," the terminal sends this message to the server. The input is the message text, and the output is the data to be sent to the server.

[0748] Step 14:

[0749] The server uses a generative AI model to analyze the urgency and importance of messages and set them as high priority. The input is message text data, and the output is priority setting information.

[0750] Step 15:

[0751] The server creates a dedicated notification for the high-priority message and sends it to the terminal as notification data containing the important message.

[0752] Step 16:

[0753] The device displays a notification to the user to prompt them to take action. Specifically, a notification such as "You have an important message" is displayed on the user's screen.

[0754] Step 17:

[0755] When a user sends a request such as "Please give me a summary of the weekly report chat room," the terminal receives the request and sends it to the server. The input is the summary request text, and the output is the data to be sent to the server.

[0756] Step 18:

[0757] The server uses a generative AI model to analyze past messages in a specified chat room, extract important points, and create a summary. The input is past message data, and the output is summary data.

[0758] Step 19:

[0759] The server sends the summary to the terminal, which then provides it to the user. Specifically, the summarized content is displayed on the user's screen.

[0760] The above are the specific processing steps of the system according to the present invention.

[0761] (Application example 1)

[0762] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0763] In today's content distribution services, it is difficult for users to easily find information and communication forums related to the content they are viewing. Therefore, a system is needed that allows users to efficiently obtain the information they need and to quickly and smoothly engage in related communication.

[0764] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0765] In this invention, the server includes means for analyzing messages received from users, means for proposing highly relevant chat room candidates based on the analysis results, means for notifying users of the proposed chat room candidates, means for analyzing content currently being viewed by users and extracting related keywords, means for proposing related forums or chat rooms based on the extracted keywords, and means for notifying users of the proposed forums or chat rooms, thereby enabling users to instantly find forums or chat rooms related to the content currently being viewed, improving information sharing and communication.

[0766] The "means for analyzing messages" is a function for analyzing the contents of messages sent by users and extracting specific keywords and important topics.

[0767] The "means for proposing chat room candidates" is a function for displaying chat room candidates that are highly relevant to the user based on the results of the analysis.

[0768] The "means for notifying users of chat room candidates" is a function for notifying the user of proposed chat room candidates on the user's terminal and displaying them to the user.

[0769] The "means for analyzing content" is a function that analyzes the content of videos and other content that a user is watching and extracts related keywords and topics.

[0770] The "means for extracting keywords" is a function for identifying and extracting important keywords and topics from the information obtained by analyzing the content.

[0771] The "means for suggesting forums or chat rooms" is a function that suggests related forums or chat rooms to the user based on the extracted keywords.

[0772] The "means for notifying a user of a forum or chat room" is a function for notifying a user of a proposed forum or chat room on the user's terminal and displaying it to the user.

[0773] The present invention provides a system for suggesting and informing users of forums and chat rooms related to the content they are currently viewing, and includes an analysis means using a generative AI model. Specific embodiments for implementing the present invention will be described below.

[0774] First, the server at the center of the system includes a means for analyzing messages received from users, a means for proposing highly relevant chat room candidates based on the analysis results, and a means for notifying users of the proposed chat room candidates.Furthermore, the system includes a means for analyzing the content being viewed by users and extracting related keywords, a means for proposing related forums or chat rooms based on the extracted keywords, and a means for notifying users of the same.

[0775] The system runs on devices such as smartphones, smart glasses, or head-mounted displays. The devices are connected to the internet and can communicate with the server. It uses OpenAI's GPT-4 as a generative AI model for analysis, and is written in Python.

[0776] Specifically, when a user inputs the ID of the content they are watching, the server retrieves the content and uses a generative AI model (GPT-4) to extract keywords and topics. An example of a prompt sentence is "Extract the main topics and keywords from the following content: This video is about AI advancements in healthcare."

[0777] The server then suggests related forums or chat rooms based on the extracted keywords. This suggestion information is sent to the user's device, allowing the user to access related forums or chat rooms. For example, if a user is watching a video titled "Advancements in Medical Care Through AI," the server analyzes the content, extracts keywords such as "Healthcare AI" and "Advancements in AI," and suggests related forums and chat rooms.

[0778] This allows users to easily obtain information and discussions related to the content they are viewing, facilitating efficient information sharing and communication. The overall system processing flow is based on natural language processing technology and machine learning models, aiming to improve the content experience.

[0779] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0780] Step 1:

[0781] The user selects the content to view and enters the ID of that content into the device. The device then sends this content ID to the server. The input is the content ID, and the output is sending the content ID to the server.

[0782] Step 2:

[0783] The server retrieves the details of the related content based on the received content ID, including the content title, description, tags, etc. The input is the content ID, and the output is the detailed content information.

[0784] Step 3:

[0785] The server uses a generative AI model (GPT-4) to analyze the detailed information of the content and extract the main topics and keywords. In this process, a prompt is created for the generative AI model and the results are analyzed. The input is the detailed information of the content, and the output is a list of the main topics and keywords. An example of a prompt is "Extract the main topics and keywords from the following content: [Detailed information of the content]".

[0786] Step 4:

[0787] The server generates a list of related forums and chat rooms based on the extracted keywords. It compares them with an existing forum database and selects the most relevant ones. The input is the extracted keywords, and the output is a list of related forums and chat rooms.

[0788] Step 5:

[0789] The server sends the generated list of forums and chat rooms to the terminal. The input is the list of forums and chat rooms, and the output is sending the list to the terminal.

[0790] Step 6:

[0791] The terminal displays the received list of forums and chat rooms to the user, who selects the forums and chat rooms of interest from the suggested list. The input is the list of forums and chat rooms, and the output is the user's selection.

[0792] Step 7:

[0793] Instantly joins a forum or chat room selected by the user. The device sends the selected chat room ID to the server, which then connects the user to that chat room. The input is the selected chat room ID, and the output is the user's connection to the chat room.

[0794] This allows users to quickly find information and discussions related to the content they are viewing, enabling efficient information sharing and communication.

[0795] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0796] The present invention provides a system that enables users to efficiently use business communication tools, and includes a chat management function that utilizes generative AI and an emotion engine. Specific embodiments for implementing the present invention will be described below.

[0797] Message analysis and chat room suggestions

[0798] 1. Message reception and analysis

[0799] A user sends a message using a business chat tool.

[0800] The terminal receives this message and sends it to the server.

[0801] The server runs a generative AI model to analyze the content of the message, extracting keywords and important topics.

[0802] 2. Chat room suggestions

[0803] The server generates suitable chat room candidates based on the message analysis results.

[0804] The server sends chat room candidates to the terminal.

[0805] The terminal displays chat room candidates to the user and prompts the user to select one.

[0806] Examples:

[0807] If a user sends a message saying "New project progress report," the server will suggest related chat rooms such as "Project progress report" and "New project."

[0808] Suggest and create new chat rooms

[0809] 1. Parsing chat room creation requests

[0810] The user inputs a message indicating their intention to create a new chat room and sends it.

[0811] The terminal receives the request and sends it to the server.

[0812] The server uses the generated AI model to analyze the request content and extract relevant keywords.

[0813] 2. Comparison with existing chat rooms and proposals

[0814] The server compares the received request with existing chat rooms.

[0815] If the server finds no duplicate entries, it will propose creating a new chat room, otherwise it will propose merging.

[0816] The proposal results are sent to the terminal and displayed to the user.

[0817] Examples:

[0818] When a user submits a request to create a chat room for "Regular Marketing Team Meetings," the server checks to see if there is an existing "Marketing Team" chat room and makes appropriate suggestions.

[0819] Message priority organization and notification

[0820] 1. Message Reception and Priority Analysis

[0821] The user receives a message from a team member. The device receives the message and forwards it to the server.

[0822] 2. Prioritization and Notifications

[0823] The server uses the generated AI model to analyze the content of the message and assess its urgency and importance.

[0824] The server assigns a priority to the message based on the analysis results, categorizing it as high priority, medium priority, or low priority.

[0825] The server generates a dedicated notification for high-priority messages and sends it to the device, which displays a notification of the important message to the user.

[0826] Examples:

[0827] When a user receives a message saying "Please respond to an order from a client as soon as possible," the server analyzes the urgency of the message and issues a notification with high priority.

[0828] Chat room summary

[0829] 1. Processing Abstract Requests

[0830] A user sends a message requesting a summary of the chat room contents. The terminal receives the request and sends it to the server.

[0831] 2. Generating and serving summaries

[0832] The server launches the generative AI model and analyzes past messages in the specified chat room.

[0833] The server extracts key points from the analysis and creates a summary, including key progress, decisions, and next steps.

[0834] The server sends the created summary to the terminal, which displays the summary to the user.

[0835] Examples:

[0836] When a user sends a request such as "Please send me a summary of the weekly report chat room," the server analyzes the messages in the chat room, generates a summary including important progress, decisions, next steps, etc., and sends it to the terminal.

[0837] Combining Emotion Engines

[0838] 1. Sentiment Analysis and Action

[0839] When a user sends or receives a message, the emotion engine analyzes the message's emotion, and the server suggests or executes an action based on the results of the emotion analysis.

[0840] The server adjusts chat room suggestions, priorities, and notification content based on the emotions recognized.

[0841] Examples:

[0842] If a user sends a message expressing stress or tension (e.g., "This task is really difficult!"), the emotion engine recognizes this emotion and the server suggests appropriate support messages and resources.

[0843] Through the specific processing steps of this system, users can efficiently manage messages, quickly grasp important information, and receive emotionally sensitive responses and suggestions.

[0844] The processing flow will be explained below.

[0845] Message analysis and chat room suggestions

[0846] Processing Steps:

[0847] Step 1:

[0848] A user uses a business chat tool to type a message and presses the "Send" button. The device receives the message and sends it to the server.

[0849] Step 2:

[0850] The server receives the message, activates a generative AI model, and analyzes the message content, extracting keywords and important topics.

[0851] Step 3:

[0852] Based on the analysis results, the server evaluates the relevance to existing chat rooms and generates highly relevant chat room candidates.

[0853] Step 4:

[0854] The server sends the generated chat room candidate list to the terminal, which displays the chat room candidates to the user and prompts them to make a selection.

[0855] Suggest and create new chat rooms

[0856] Processing Steps:

[0857] Step 1:

[0858] The user enters a message about the new chat room they wish to create and presses the "Send" button. The device receives this message and sends it to the server.

[0859] Step 2:

[0860] The server receives the request, activates the generative AI model, and analyzes the request. Keywords and topics are extracted as a result of the analysis.

[0861] Step 3:

[0862] The server compares the request with existing chat rooms based on extracted keywords and topics, and evaluates relevance and overlap.

[0863] Step 4:

[0864] Based on the comparison, the server makes a suggestion to the user: either to create a new chat room or to merge into an existing chat room.

[0865] Step 5:

[0866] The server sends the proposal results to the device, which displays the proposals to the user and prompts them to make a selection.

[0867] Message priority organization and notification

[0868] Processing Steps:

[0869] Step 1:

[0870] The user receives a message from a team member. The device receives the message and forwards it to the server.

[0871] Step 2:

[0872] The server receives the message and uses a generative AI model to analyze the message content and assess its urgency and importance.

[0873] Step 3:

[0874] The server assigns a priority to the message based on the analysis results, categorizing it into high, medium, and low priority categories.

[0875] Step 4:

[0876] The server generates a dedicated notification for high-priority messages and sends it to the device, which displays a notification of the important message to the user.

[0877] Chat room summary

[0878] Processing Steps:

[0879] Step 1:

[0880] A user sends a message requesting a summary of the chat room contents. The terminal receives the request and sends it to the server.

[0881] Step 2:

[0882] The server receives the request, launches the generative AI model, and analyzes past messages in the specified chat room.

[0883] Step 3:

[0884] The server extracts key points from the analysis and creates a summary, including key progress, decisions, and next steps.

[0885] Step 4:

[0886] The server sends the created summary to the terminal, which displays the summary to the user.

[0887] Combining Emotion Engines

[0888] Processing Steps:

[0889] Step 1:

[0890] When a user sends a message, the device sends the message to the server, which receives the message and uses the emotion engine to analyze the emotion of the message.

[0891] Step 2:

[0892] The server receives the analysis results of the emotion engine and suggests or executes actions based on the recognized emotions. For example, if the user is feeling stressed, it generates an appropriate support message.

[0893] Step 3:

[0894] The server adjusts chat room suggestions and notification content based on the recognized emotion. For example, if the user is feeling stressed, chat room suggestions are adjusted to address issues that can be easily resolved.

[0895] Step 4:

[0896] The server sends the adjusted chat room suggestions and notification content to the terminal, which displays them to the user and prompts them to make a selection or confirm.

[0897] Examples:

[0898] Message Parsing:

[0899] When a user sends a message saying "New project progress report," the server suggests chat rooms related to "Project progress report" and "New project."

[0900] New chat room suggestions:

[0901] When a user submits a request to create a chat room for "Regular Marketing Team Meetings," the server checks to see if there is an existing "Marketing Team" chat room and makes a suggestion.

[0902] Message priority organization:

[0903] When a user receives a message saying "Please respond to an order from a client as soon as possible," the server analyzes the urgency of the message and issues a notification with high priority.

[0904] Emotion Engine:

[0905] If a user sends a message such as "This task is really difficult!", the emotion engine will recognize the stress and the server will suggest an appropriate support message.

[0906] Example 2

[0907] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0908] Current business chat tools make it difficult for users to efficiently manage messages and join or create new chat rooms. They also lack the functionality to quickly evaluate and notify the importance and urgency of received messages. Furthermore, functions such as message sentiment analysis and summary generation are inadequate. Therefore, there is a need to provide a stress-free communication environment for users.

[0909] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0910] In this invention, the server includes: means for analyzing messages received from a user; means for suggesting relevant chat room candidates based on the analysis results; means for notifying the user of the suggested chat room candidates; means for analyzing the sentiment of messages using a sentiment analysis engine and suggesting appropriate actions based on the analysis results; means for analyzing and setting the importance and priority of received messages; means for notifying the user of important messages based on the set priority; means for analyzing messages in a specified chat room and generating summaries; means for notifying the user of the generated summaries; means for analyzing messages using a generative AI model; and means for inputting prompts to the generative AI model to instruct analysis. This allows users to efficiently manage messages and join appropriate chat rooms or create new chat rooms. Furthermore, by quickly evaluating the importance and urgency of messages and performing sentiment analysis and summaries, a stress-free communication environment can be provided.

[0911] "User" means an individual or legal entity that uses the business communication tool to send or receive messages.

[0912] A "message" is data such as text, images, and audio that a user sends or receives through a business chat tool.

[0913] "Means of analysis" refers to the technology that analyzes the content of received messages and extracts keywords and important topics.

[0914] "Chat Room Suggestion" refers to a suggestion of a relevant existing or new chat room based on the analyzed content of the message.

[0915] "Means of notification" refers to technology that provides analysis results and notification content to users and encourages them to take the next action.

[0916] An "emotion analysis engine" refers to technology that analyzes the emotions contained in the content of a message and suggests appropriate actions based on the analysis results.

[0917] "Importance and priority" refers to the criteria for assessing and classifying the urgency and importance of received messages.

[0918] "Means for generating a summary" refers to a technology that analyzes past messages in a specified chat room, extracts key information, and creates a summary.

[0919] A "generative AI model" refers to a machine learning model that uses artificial intelligence technology to analyze messages and generate summaries.

[0920] A "prompt" refers to text that is entered to give specific instructions to a generative AI model.

[0921] The present invention provides a system that enables users to efficiently use business communication tools, and includes a chat management function that utilizes a generative AI model and an emotion engine. Specific embodiments for implementing the present invention will be described below.

[0922] Message analysis and chat room suggestions

[0923] 1. Message reception and analysis

[0924] A user uses a business chat tool to send a message such as "Report on the progress of a new project."

[0925] The terminal receives this message and sends it to the server.

[0926] The server launches a generative AI model (e.g., OpenAI's GPT-4) to analyze the message content. This analysis uses the prompt "Please extract keywords and topics from the following message." This results in the extraction of the keywords "new project," "progress," and "report."

[0927] 2. Chat room suggestions

[0928] The server generates appropriate chat room candidates based on the extracted keywords. For example, it compares the keywords with a list of existing chat rooms and suggests related chat rooms such as "project progress report" and "new project."

[0929] The server sends chat room candidates to the terminal.

[0930] The terminal displays chat room candidates to the user and prompts the user to select one.

[0931] Suggest and create new chat rooms

[0932] 1. Parsing chat room creation requests

[0933] A user enters a message stating that they want to create a new chat room, such as "Regular Marketing Team Meetings," and sends it.

[0934] The terminal receives the request and sends it to the server.

[0935] The server uses a generative AI model and prompts the user with the following sentence: "Analyze a new chat room request and extract relevant keywords." The server extracts keywords such as "marketing team" and "regular meeting" from the request.

[0936] 2. Comparison with existing chat rooms and proposals

[0937] The server compares the extracted keywords with the existing chat room list to check for overlapping content.

[0938] If the server has an existing chat room for "Marketing Team", it will suggest to the user, "Do you want to use the existing chat room?" If there is no overlap, it will suggest creating a new chat room.

[0939] The device displays the proposed results to the user, who can then choose to accept the proposal or create a new one.

[0940] Message priority organization and notification

[0941] 1. Message Reception and Priority Analysis

[0942] The user receives a message from a team member saying, "Please handle the client's order as soon as possible." The terminal receives this message and sends it to the server.

[0943] 2. Prioritization and Notifications

[0944] The server uses a generative AI model to analyze the message content by setting a prompt sentence: "Please rate the urgency and importance of this message." This determines the message to be of high urgency.

[0945] The server sets the message priority to "high" based on this result.

[0946] The server generates a dedicated notification for high-priority messages and sends it to the device. The device displays a notification of the important message to the user. The user checks the notification and responds promptly.

[0947] Chat room summary

[0948] 1. Processing Abstract Requests

[0949] A user requests a summary of the chat room contents by sending the message "Please give me a summary of the weekly chat room report." The terminal receives this request and sends it to the server.

[0950] 2. Generating and serving summaries

[0951] The server launches the generative AI model and uses the prompt, "Analyze the past messages in this chat room and summarize the key points." The server analyzes the past messages in the specified chat room and extracts key progress, decisions, next steps, etc.

[0952] The server creates a summary and sends it to the terminal, which displays the summary to the user, who reviews the summary and plans next steps.

[0953] Combining Emotion Engines

[0954] 1. Sentiment Analysis and Action

[0955] When a user sends or receives a message such as "This task is really difficult!", the emotion engine analyzes the emotion of the message. The server then suggests actions based on the results of this emotion analysis.

[0956] The server suggests appropriate support messages and resources based on the emotions it recognizes. Specifically, it generates support messages such as "Do you need additional resources for this task?"

[0957] The terminal displays a support message to the user, and the user requests resources as needed.

[0958] Through these processing steps, users can efficiently manage messages, join appropriate chat rooms, create new chat rooms, prioritize messages, generate summaries, and analyze sentiment, thereby providing a stress-free communication environment for users.

[0959] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0960] Message analysis and chat room suggestions

[0961] Step 1:

[0962] Receiving messages

[0963] A user types and sends a message via a business chat tool saying, "Report on the progress of a new project."

[0964] Input: User's message

[0965] Output: Request to send message to terminal

[0966] Step 2:

[0967] Message relay by terminal

[0968] The terminal transmits the message received from the user to the server.

[0969] Input: The user's sent message

[0970] Output: Message transfer request to server

[0971] Step 3:

[0972] Server parsing of messages

[0973] The server launches a generative AI model (e.g., GPT-4) and analyzes the message content using the prompt, "Please extract keywords and topics from the message below."

[0974] Input: Message received from the terminal, prompt text

[0975] Output: Extracted keywords "new project", "progress", "report"

[0976] Step 4:

[0977] Generate chat room candidates

[0978] The server compares the extracted keywords with a list of past chat rooms to generate highly relevant chat room candidates.

[0979] Input: Extracted keywords

[0980] Output: List of chat room candidates (e.g. "Project progress report", "New project")

[0981] Step 5:

[0982] Device notifications

[0983] The server transmits the generated chat room candidates to the terminal, and the terminal displays the chat room candidates to the user.

[0984] Input: Chat room candidate list

[0985] Output: Chat room suggestions displayed to the user

[0986] Suggest and create new chat rooms

[0987] Step 1:

[0988] Sending a chat room creation request

[0989] A user sends a message requesting the creation of a chat room called "Marketing Team Regular Meetings."

[0990] Input: User creation request message

[0991] Output: Request to send message to terminal

[0992] Step 2:

[0993] Terminal relays requests

[0994] The terminal transmits the request message received from the user to the server.

[0995] Input: User request message

[0996] Output: Request forwarded to server

[0997] Step 3:

[0998] Request analysis by the server

[0999] The server launches the generative AI model and analyzes the content of the request using the prompt "Analyze a new chat room request and extract relevant keywords."

[1000] Input: Request received from the terminal, prompt text

[1001] Output: Extracted keywords "marketing team" and "regular meeting"

[1002] Step 4:

[1003] Comparison with existing chat rooms

[1004] The server checks the extracted keywords against the existing chat room list to see if there are any overlaps.

[1005] Input: Extracted keywords

[1006] Output: Existing chat rooms

[1007] Step 5:

[1008] Proposal generation and notification

[1009] The server generates a proposal to create a new chat room or to merge with an existing chat room based on the request content and the comparison result, and sends it to the terminal. The terminal displays the proposal to the user.

[1010] Input: Request details, whether or not there is an existing chat room

[1011] Output: Proposal displayed to the user

[1012] Message priority organization and notification

[1013] Step 1:

[1014] Receiving messages

[1015] The user receives a message saying, "Please handle the order from the client as soon as possible." The terminal receives the message and sends it to the server.

[1016] Input: Incoming message

[1017] Output: Message transfer request to server

[1018] Step 2:

[1019] Message Priority Analysis

[1020] The server uses a generative AI model to set a prompt such as "Please rate the urgency and importance of this message" and analyze the message content.

[1021] Input: message, prompt

[1022] Output: Set priority (e.g. High)

[1023] Step 3:

[1024] Generate notifications based on priority

[1025] The server generates a dedicated notification for high-priority messages and sends it to the device, which displays a notification of the important message to the user.

[1026] Input: Set priority

[1027] Output: Important message notification to the user

[1028] Chat room summary

[1029] Step 1:

[1030] Submitting a Summary Request

[1031] The user sends a request saying, "Please send me a summary of the weekly chat room report." The device receives the request and forwards it to the server.

[1032] Input: User request message

[1033] Output: Request forwarded to server

[1034] Step 2:

[1035] Generate a summary

[1036] The server uses the generative AI model to set a prompt such as "Analyze the past messages in this chat room and summarize the important points," and analyzes the past messages in the specified chat room.

[1037] Input: Request, prompt, past message

[1038] Output: Generated summary

[1039] Step 3:

[1040] Provision to users

[1041] The server sends the generated summary to the terminal, which displays the summary to the user.

[1042] Input: Generated summary

[1043] Output: Summary displayed to the user

[1044] Combining Emotion Engines

[1045] Step 1:

[1046] Message sentiment analysis

[1047] When a user sends or receives a message such as "This task is really difficult!", the emotion engine analyzes the emotion of the message.

[1048] Input: Message sent or received

[1049] Output: Analysis results (e.g. stress, tension)

[1050] Step 2:

[1051] Suggestions for appropriate actions

[1052] Based on the results of the sentiment analysis, the server generates a support message asking, "Do you need additional resources for this task?" and sends it to the device. The device then displays the support message to the user.

[1053] Input: Sentiment analysis results

[1054] Output: Display support message to user

[1055] Through the above specific processing steps, users can efficiently manage messages and ensure smooth operation of the chat room. Furthermore, emotion analysis can reduce users' psychological burden and provide appropriate support.

[1056] (Application example 2)

[1057] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1058] Conventional business communication tools have limited functionality, such as message analysis and chat room suggestions, limiting the ways for users to quickly and efficiently obtain the information they need. Furthermore, systems for appropriately classifying message urgency and importance and for advanced communication are inadequate. In particular, systems requiring advanced operational management, such as autonomous vehicles, often require real-time emergency response and appropriate instructions based on emotion analysis, and existing systems have difficulty meeting these requirements.

[1059] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1060] In this invention, the server includes means for analyzing messages received from users, means for proposing highly relevant chat room candidates based on the analysis results, means for notifying users of the proposed chat room candidates, means for analyzing the sentiment of the messages, means for adjusting the chat room candidates based on the sentiment analysis results, and means for setting message priorities and generating notifications according to urgency, thereby enabling users to quickly and efficiently obtain necessary information and appropriately respond to emergencies and important messages.

[1061] "Analysis of messages received from users" is a process of automatically analyzing the contents of messages sent by users and extracting important keywords and contexts.

[1062] "Suggesting relevant chat room candidates" is a function that identifies and suggests appropriate chat rooms for the user to join based on the results of message analysis.

[1063] "Emotion analysis" is an analytical process for determining the emotional state of the sender and receiver from the content of a message.

[1064] "Adjusting chat room candidates" is a process of optimizing the list of chat rooms suggested to the user based on the results of sentiment analysis.

[1065] "Message priority setting" is a function that evaluates the importance and urgency of received messages and automatically sets the priority accordingly.

[1066] "Generating notifications according to urgency" is a function that sends special notifications to users for messages that are important and urgent based on the set priority.

[1067] "Analysis of chat room creation requests" is a process that automatically analyzes new chat room creation requests from users and understands their intent.

[1068] "Compare with existing chat rooms" refers to the process of comparing a new chat room creation request with existing chat rooms to determine if the request overlaps with an existing chat room.

[1069] "Proposal to create or merge a new chat room" is a function that suggests to the user to create a new chat room or merge with an existing chat room based on the analysis results.

[1070] "Quick suggestion of appropriate responses in emergencies" is a function that quickly suggests to users the actions and countermeasures required in emergencies.

[1071] As a mode for carrying out the present invention, an embodiment of a communication and operation management system for an autonomous driving vehicle will be described below.

[1072] The system analyzes messages received from users and suggests appropriate chat rooms based on the results of the analysis. It can also analyze the sentiment of messages, generate notifications based on urgency, and compare existing chat rooms.

[1073] Receiving and parsing messages

[1074] The server receives messages sent by users, which are then analyzed using a generative AI model (e.g., the Sentiment Analysis model from HuggingFace's transformers library) to extract important keywords and context and suggest appropriate chat rooms based on the content.

[1075] Emotion analysis

[1076] The server uses a generative AI model to analyze the sentiment of the message. Based on this analysis, it adjusts chat room suggestions and optimizes the suggestions as needed. For example, if a message is sent saying, "An accident has occurred. Immediate action is required," the server will determine this message as "negative" and suggest a chat room that requires a high level of urgency.

[1077] Prioritization and Notifications

[1078] The server classifies received messages based on importance and urgency, and generates special notifications based on the set priority and sends them to the user's device, allowing the user to quickly understand important messages and urgent actions.

[1079] Creating and comparing chat rooms

[1080] When a user requests to create a new chat room, the server analyzes the request and compares it with existing chat rooms. If there are no overlaps, the server proposes the creation of a new chat room, and if there are overlaps, it proposes merging. For example, if a request comes in to "report on the progress of a new project," the server checks whether there is an existing "project progress report" chat room and makes an appropriate proposal.

[1081] Specific examples

[1082] When an autonomous vehicle sends a message saying, "Left front tire pressure is low," the message is analyzed by a generative AI model. As a result, the message is determined to be "negative," a notification is sent to the maintenance team's chat room, and a prompt is generated: "New maintenance request: Left front tire pressure is low," suggesting an appropriate response.

[1083] Prompt Sentence Examples

[1084] A new maintenance request has arrived:

[1085] Vehicle ID: Vehicle1234

[1086] Message: Left front tire pressure low

[1087] In this way, the system of the present invention realizes efficient business communication by analyzing the user's messages in detail and making appropriate suggestions and notifications that take into account the user's emotions and urgency.

[1088] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1089] Step 1:

[1090] A user sends a message from a device inside an autonomous vehicle.

[1091] The user inputs a message and presses the send button to send it to the terminal. An input message might be something like "The air pressure in the left front tire is low." The output is the message data that was sent.

[1092] Step 2:

[1093] The terminal transfers the received message to the server.

[1094] When a terminal receives a message from a user, it sends the contents of the message to the server. The input is the received message data, and the output is the message data transferred to the server.

[1095] Step 3:

[1096] The server analyzes the message content using a generative AI model.

[1097] The server inputs the received message data into the generative AI model and performs an analysis to extract keywords and context. This analysis extracts important information. The input is the message data, and the output is the keywords and context information that are the analysis results.

[1098] Step 4:

[1099] The server performs sentiment analysis.

[1100] The server uses the generative AI model to analyze the sentiment of the message. The input is the analysis result from step 3, and the output is the analyzed sentiment data (e.g., negative or positive classification and its confidence score).

[1101] Step 5:

[1102] The server proposes chat room candidates based on the analysis results.

[1103] The server identifies relevant chat room candidates based on the message keywords and sentiment analysis results and generates a list. The input is the analysis results of steps 3 and 4, and the output is a list of chat room candidates.

[1104] Step 6:

[1105] The server notifies the terminal of chat room candidates.

[1106] The server sends the generated list of chat room candidates to the terminal and displays it to the user. The input is the list of chat room candidates, and the output is a notification displayed on the user's terminal.

[1107] Step 7:

[1108] The user selects a chat room.

[1109] The user selects the most suitable chat room from the chat room candidates displayed on the terminal. The input is the chat room candidate list displayed on the terminal, and the output is the selected chat room.

[1110] Step 8:

[1111] The server parses the request to create a new chat room.

[1112] When a user sends a request, the server receives it and analyzes the content using a generative AI model. The input is the request message from the user, and the output is the analyzed request data.

[1113] Step 9:

[1114] The server compares the new request with existing chat rooms.

[1115] The server compares the parsed request data with the existing chat room database to check for duplicates. The input is the parsed request data and existing chat room data, and the output is the presence or absence of duplicates and new proposed data.

[1116] Step 10:

[1117] The server will propose the creation or merging of new chat rooms.

[1118] Based on the comparison results, the server proposes a future action (creating a new chat room or merging into an existing chat room) to the user. The input is the comparison result data, and the output is a proposal notification.

[1119] Step 11:

[1120] The server prioritizes messages and generates notifications based on urgency.

[1121] The server evaluates the importance and urgency of messages and generates special notifications for high-priority messages. The input is the analysis results and importance rating data, and the output is the generated special notifications.

[1122] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1123] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1124] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1125] [Third embodiment]

[1126] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1127] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1128] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1129] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1130] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1131] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1132] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1133] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1134] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1135] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1136] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1137] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1138] The present invention provides a system that enables users to efficiently use business communication tools, and includes a chat management function that utilizes AI generation. Specific embodiments for implementing the present invention will be described below.

[1139] Message analysis and chat room suggestions

[1140] 1. Message reception and analysis

[1141] A user sends a message using a business chat tool.

[1142] The terminal receives this message and sends it to the server.

[1143] The server uses a generative AI model to analyze the content of the message, extracting keywords and important topics.

[1144] 2. Chat room suggestions

[1145] The server generates suitable chat room candidates based on the message analysis results.

[1146] The server sends chat room candidates to the terminal.

[1147] The terminal displays chat room candidates to the user and prompts the user to select one.

[1148] Examples:

[1149] If a user sends a message saying "New project progress report," the server will suggest related chat rooms such as "Project progress report" and "New project."

[1150] Suggest and create new chat rooms

[1151] 1. Parsing chat room creation requests

[1152] The user inputs a message indicating their intention to create a new chat room and sends it.

[1153] The terminal receives the request and sends it to the server.

[1154] The server uses the generated AI model to analyze the request content and extract relevant keywords.

[1155] 2. Comparison with existing chat rooms and proposals

[1156] The server compares the received request with existing chat rooms.

[1157] If the server finds no duplicate entries, it will propose creating a new chat room, otherwise it will propose merging.

[1158] The proposal results are sent to the terminal and displayed to the user.

[1159] Examples:

[1160] When a user submits a request to create a chat room for "Regular Marketing Team Meetings," the server checks to see if there is an existing "Marketing Team" chat room and makes appropriate suggestions.

[1161] Message priority organization and notification

[1162] 1. Message Reception and Priority Analysis

[1163] The user receives the message.

[1164] The terminal sends this message to the server.

[1165] The server uses the generated AI model to analyze the urgency and importance of the message.

[1166] 2. Prioritization and Notifications

[1167] The server sets the priority of the message based on the analysis results.

[1168] The server creates a dedicated notification for high priority messages and sends it to the device.

[1169] The device displays a notification to the user.

[1170] Examples:

[1171] When a user receives a message saying "Please respond to an order from a client as soon as possible," the server analyzes the importance of the message and notifies the user as a high priority.

[1172] Chat room summary

[1173] 1. Processing Abstract Requests

[1174] A user enters and submits a request for a summary of the chat room.

[1175] The terminal receives the request and sends it to the server.

[1176] 2. Generating and serving summaries

[1177] The server uses the generated AI model to analyze past messages in a specified chat room.

[1178] The server extracts the key points and creates a summary.

[1179] The summary is sent to the terminal and presented to the user.

[1180] Examples:

[1181] When a user sends a request such as "Please send me a summary of the weekly report chat room," the server analyzes all messages in that chat room, creates a summary including important progress, decisions, and next steps, and sends it to the device.

[1182] In this way, the present invention provides support for users to improve work efficiency and quickly grasp important information.

[1183] The processing flow will be explained below.

[1184] Message analysis and chat room suggestions

[1185] Processing Steps:

[1186] Step 1:

[1187] The user enters a message and presses the "Send" button. The device receives the message and sends it to the server.

[1188] Step 2:

[1189] The server receives the message. The server then launches a generative AI model to analyze the message content. Through analysis, keywords and key points from the message are extracted.

[1190] Step 3:

[1191] Based on the analysis results, the server evaluates the relevance to existing chat rooms and generates highly relevant chat room candidates.

[1192] Step 4:

[1193] The server sends the generated chat room candidate list to the terminal, which displays the chat room candidates to the user and prompts them to make a selection.

[1194] Suggest and create new chat rooms

[1195] Processing Steps:

[1196] Step 1:

[1197] The user enters a message about the new chat room they wish to create and presses the "Send" button. The device receives this message and sends it to the server.

[1198] Step 2:

[1199] The server receives the request, activates the generative AI model, and analyzes the request. Keywords and topics are extracted as a result of the analysis.

[1200] Step 3:

[1201] The server compares the request with existing chat rooms based on extracted keywords and topics, and evaluates relevance and overlap.

[1202] Step 4:

[1203] Based on the comparison, the server makes a suggestion to the user: either to create a new chat room or to merge into an existing chat room.

[1204] Step 5:

[1205] The server sends the proposal results to the device, which displays the proposals to the user and prompts them to make a selection.

[1206] Message priority organization and notification

[1207] Processing Steps:

[1208] Step 1:

[1209] The user receives a message from a team member. The device receives the message and forwards it to the server.

[1210] Step 2:

[1211] The server receives the message and uses a generative AI model to analyze the message content and assess its urgency and importance.

[1212] Step 3:

[1213] The server assigns a priority to the message based on the analysis results, categorizing it into high, medium, and low priority categories.

[1214] Step 4:

[1215] The server generates a dedicated notification for high-priority messages and sends it to the device, which displays a notification of the important message to the user.

[1216] Chat room summary

[1217] Processing Steps:

[1218] Step 1:

[1219] A user sends a message requesting a summary of the chat room contents. The terminal receives the request and sends it to the server.

[1220] Step 2:

[1221] The server receives the request, launches the generative AI model, and analyzes past messages in the specified chat room.

[1222] Step 3:

[1223] The server extracts key points from the analysis and creates a summary, including key progress, decisions, and next steps.

[1224] Step 4:

[1225] The server sends the created summary to the terminal, which displays the summary to the user.

[1226] Through the specific processing steps of this system, users can efficiently manage messages and quickly grasp important information.

[1227] Example 1

[1228] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1229] Conventional business communication tools have limited capabilities for analyzing received messages, making it difficult to quickly and accurately present appropriate chat room or collaboration room candidates. Furthermore, they often lack the functionality to quickly determine the urgency and importance of users' messages and provide immediate notifications for high-priority messages. As a result, users are at greater risk of overlooking important information, which can lead to reduced work efficiency. Furthermore, when users create a new chat room, it is difficult to avoid overlaps with existing chat rooms and to suggest appropriate rooms. Therefore, the present invention aims to solve these problems.

[1230] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1231] In this invention, the server includes means for analyzing messages received from users, means for proposing highly relevant communication room candidates based on the analysis results, means for notifying users of the proposed communication room candidates, means for analyzing the content of messages using a generative AI model and extracting important keywords and topics, means for generating appropriate collaboration rooms based on the extracted information, and means for transmitting and displaying the generated collaboration room proposals to user terminals, thereby enabling users to conduct business communication quickly and effectively without overlooking important information.

[1232] "User" refers to an individual or organization that uses the business communication tools of this system.

[1233] "Message" refers to text information sent by a user through a business chat tool.

[1234] "Terminal" refers to the hardware device used by a User to access the System.

[1235] "Server" refers to a remotely located computer system that performs central processing for the System.

[1236] "Means of analysis" refers to the process of using a generative AI model to understand the content of a message and extract key elements.

[1237] A "generative AI model" refers to an algorithm that applies artificial intelligence technology to analyze text data and generate or extract specific information.

[1238] A "communication room" is a virtual room for exchanging messages about a specific topic or project.

[1239] "Collaboration Room" refers to a virtual room where users can collaborate on a specific team or project.

[1240] "Means of suggestion" refers to the process of showing users appropriate communication or collaboration rooms based on the analysis results.

[1241] "Means for notifying" refers to the process for displaying suggested rooms and important messages to users.

[1242] "Importance" refers to an index that indicates how urgent or important the content of a message is to the user.

[1243] "Priority" refers to an index that determines the priority of processing or notification based on the importance of a message.

[1244] "Comparison method" refers to the process of checking user requests against existing information to identify overlaps and relevance.

[1245] A "request" refers to a message that a user sends to the system to inform the system that they wish to create a new collaboration room.

[1246] "Proposal Results" refers to action plans or recommendations to users that are generated as a result of the analysis and comparison.

[1247] The present invention provides a system that enables users to efficiently use business communication tools, and includes a chat management function that utilizes a generative AI model. Specific embodiments for implementing the present invention will be described below.

[1248] Configuration and operation overview

[1249] In this invention, when a user sends and receives messages using a business chat tool, a server and a terminal work together to provide advanced functions such as analysis, suggestions, notifications, and summaries. The server uses a generative AI model (e.g., OpenAI's GPT-4) to analyze the content of the messages and extract and process important information.

[1250] Hardware and software used

[1251] Terminal: A device used by a user, such as a personal computer or smartphone.

[1252] Server: A remotely located computer system that handles message analysis and notification processing.

[1253] Generative AI models: Algorithms for natural language processing (e.g., GPT-4).

[1254] Message analysis and chat room suggestions

[1255] When a user sends a message using a business chat tool saying, "Report on the progress of a new project," the device receives the message and sends it to the server, which then uses a generative AI model to analyze the message and extract important keywords and topics.

[1256] Based on the extracted information, the server generates appropriate communication room candidates (e.g., "Project Progress Report" or "New Project") and sends them to the terminal. The terminal displays the candidates to the user, who then selects an appropriate chat room.

[1257] Suggest and create new chat rooms

[1258] When a user inputs and sends a request to create a chat room for "Regular Marketing Team Meetings," the device receives the request and sends it to the server, which uses a generative AI model to analyze the request and extract relevant keywords.

[1259] The server compares the extracted keywords with existing collaboration room information and makes a proposal to create a new room or use an existing room. The proposal results are sent to the user's terminal and displayed to the user.

[1260] Message priority organization and notification

[1261] If a user receives a message saying, "Please handle an order from a client urgently," the device sends this message to the server, which uses a generative AI model to analyze the urgency and importance of the message and sets it as high priority.

[1262] For the set high-priority messages, the server creates a dedicated notification and sends it to the terminal, which displays the notification to the user and prompts them to respond promptly.

[1263] Chat room summary

[1264] When a user sends a request such as "Please send me a summary of the weekly chat room report," the device receives the request and sends it to the server, which uses a generative AI model to analyze past messages in the specified chat room, extract key points, and create a summary.

[1265] The created summary is sent to the terminal and provided to the user, allowing the user to quickly grasp important information and carry out work efficiently.

[1266] Specific examples

[1267] As a concrete example, the following prompt sentence is used:

[1268] "Do you want to create a new chat room or view an existing chat room?"

[1269] "Does this message require urgent attention?"

[1270] As a result, the present invention provides support for users to efficiently use business communication tools and quickly grasp important information.

[1271] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1272] Step 1:

[1273] A user sends a message using a business chat tool. Specifically, the user enters text such as "Report on the progress of a new project" and clicks the send button. This input text is sent to the device.

[1274] Step 2:

[1275] The device receives the message sent by the user. The received message is temporarily stored in the internal memory.

[1276] Step 3:

[1277] The terminal sends the received message to the server. Specifically, the message data is sent in packet format to the server's address. At this stage, the input data is the message text, and the output data is the text data sent to the server.

[1278] Step 4:

[1279] The server analyzes the received message. A generative AI model (e.g., GPT-4) is used to analyze the message content and extract keywords and important topics. The input is the message text data, and the output is a list of extracted keywords.

[1280] Step 5:

[1281] The server generates appropriate communication room candidates based on the extracted keywords and topics. Specifically, it generates candidate room names such as "Project Progress Report" and "New Project." The input of this process is a keyword list, and the output is a communication room candidate list.

[1282] Step 6:

[1283] The server sends the created communication room candidate list to the terminal, and the sent data arrives at the terminal as the room candidate list.

[1284] Step 7:

[1285] The device displays chat room candidates to the user and prompts them to select one. Specifically, a list of candidates such as "Project Progress Report" and "New Project" is displayed on the user's screen. The user selects an appropriate chat room from these candidates.

[1286] Step 8:

[1287] When a user wishes to create a new chat room, he or she inputs a request such as "Regular meeting of the marketing team" in a message and sends it. This input data is sent to the terminal.

[1288] Step 9:

[1289] The terminal receives the request and sends it to the server. The request data is sent to the server in packet format.

[1290] Step 10:

[1291] The server analyzes the request content using a generative AI model and extracts related keywords (e.g., "marketing" or "regular meeting"). The input is the request text data, and the output is a list of related keywords.

[1292] Step 11:

[1293] The server compares the extracted keywords with existing collaboration room information and makes proposals for creating new rooms or merging existing rooms. The input is a list of keywords and existing room information, and the output is the proposal results.

[1294] Step 12:

[1295] The proposal result is sent to the terminal, which displays it to the user. Specifically, it displays the prompt "Do you want to use the existing marketing team chat room?" The user can take appropriate action based on this proposal.

[1296] Step 13:

[1297] When a user receives a message saying "Please handle the client's order as soon as possible," the terminal sends this message to the server. The input is the message text, and the output is the data to be sent to the server.

[1298] Step 14:

[1299] The server uses a generative AI model to analyze the urgency and importance of messages and set them as high priority. The input is message text data, and the output is priority setting information.

[1300] Step 15:

[1301] The server creates a dedicated notification for the high-priority message and sends it to the terminal as notification data containing the important message.

[1302] Step 16:

[1303] The device displays a notification to the user to prompt them to take action. Specifically, a notification such as "You have an important message" is displayed on the user's screen.

[1304] Step 17:

[1305] When a user sends a request such as "Please give me a summary of the weekly report chat room," the terminal receives the request and sends it to the server. The input is the summary request text, and the output is the data to be sent to the server.

[1306] Step 18:

[1307] The server uses a generative AI model to analyze past messages in a specified chat room, extract important points, and create a summary. The input is past message data, and the output is summary data.

[1308] Step 19:

[1309] The server sends the summary to the terminal, which then provides it to the user. Specifically, the summarized content is displayed on the user's screen.

[1310] The above are the specific processing steps of the system according to the present invention.

[1311] (Application example 1)

[1312] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1313] In today's content distribution services, it is difficult for users to easily find information and communication forums related to the content they are viewing. Therefore, a system is needed that allows users to efficiently obtain the information they need and to quickly and smoothly engage in related communication.

[1314] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1315] In this invention, the server includes means for analyzing messages received from users, means for proposing highly relevant chat room candidates based on the analysis results, means for notifying users of the proposed chat room candidates, means for analyzing content currently being viewed by users and extracting related keywords, means for proposing related forums or chat rooms based on the extracted keywords, and means for notifying users of the proposed forums or chat rooms, thereby enabling users to instantly find forums or chat rooms related to the content currently being viewed, improving information sharing and communication.

[1316] The "means for analyzing messages" is a function for analyzing the contents of messages sent by users and extracting specific keywords and important topics.

[1317] The "means for proposing chat room candidates" is a function for displaying chat room candidates that are highly relevant to the user based on the results of the analysis.

[1318] The "means for notifying users of chat room candidates" is a function for notifying the user of proposed chat room candidates on the user's terminal and displaying them to the user.

[1319] The "means for analyzing content" is a function that analyzes the content of videos and other content that a user is watching and extracts related keywords and topics.

[1320] The "means for extracting keywords" is a function for identifying and extracting important keywords and topics from the information obtained by analyzing the content.

[1321] The "means for suggesting forums or chat rooms" is a function that suggests related forums or chat rooms to the user based on the extracted keywords.

[1322] The "means for notifying a user of a forum or chat room" is a function for notifying a user of a proposed forum or chat room on the user's terminal and displaying it to the user.

[1323] The present invention provides a system for suggesting and informing users of forums and chat rooms related to the content they are currently viewing, and includes an analysis means using a generative AI model. Specific embodiments for implementing the present invention will be described below.

[1324] First, the server at the center of the system includes a means for analyzing messages received from users, a means for proposing highly relevant chat room candidates based on the analysis results, and a means for notifying users of the proposed chat room candidates.Furthermore, the system includes a means for analyzing the content being viewed by users and extracting related keywords, a means for proposing related forums or chat rooms based on the extracted keywords, and a means for notifying users of the same.

[1325] The system runs on devices such as smartphones, smart glasses, or head-mounted displays. The devices are connected to the internet and can communicate with the server. It uses OpenAI's GPT-4 as a generative AI model for analysis, and is written in Python.

[1326] Specifically, when a user inputs the ID of the content they are watching, the server retrieves the content and uses a generative AI model (GPT-4) to extract keywords and topics. An example of a prompt sentence is "Extract the main topics and keywords from the following content: This video is about AI advancements in healthcare."

[1327] The server then suggests related forums or chat rooms based on the extracted keywords. This suggestion information is sent to the user's device, allowing the user to access related forums or chat rooms. For example, if a user is watching a video titled "Advancements in Medical Care Through AI," the server analyzes the content, extracts keywords such as "Healthcare AI" and "Advancements in AI," and suggests related forums and chat rooms.

[1328] This allows users to easily obtain information and discussions related to the content they are viewing, facilitating efficient information sharing and communication. The overall system processing flow is based on natural language processing technology and machine learning models, aiming to improve the content experience.

[1329] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1330] Step 1:

[1331] The user selects the content to view and enters the ID of that content into the device. The device then sends this content ID to the server. The input is the content ID, and the output is sending the content ID to the server.

[1332] Step 2:

[1333] The server retrieves the details of the related content based on the received content ID, including the content title, description, tags, etc. The input is the content ID, and the output is the detailed content information.

[1334] Step 3:

[1335] The server uses a generative AI model (GPT-4) to analyze the detailed information of the content and extract the main topics and keywords. In this process, a prompt is created for the generative AI model and the results are analyzed. The input is the detailed information of the content, and the output is a list of the main topics and keywords. An example of a prompt is "Extract the main topics and keywords from the following content: [Detailed information of the content]".

[1336] Step 4:

[1337] The server generates a list of related forums and chat rooms based on the extracted keywords. It compares them with an existing forum database and selects the most relevant ones. The input is the extracted keywords, and the output is a list of related forums and chat rooms.

[1338] Step 5:

[1339] The server sends the generated list of forums and chat rooms to the terminal. The input is the list of forums and chat rooms, and the output is sending the list to the terminal.

[1340] Step 6:

[1341] The terminal displays the received list of forums and chat rooms to the user, who selects the forums and chat rooms of interest from the suggested list. The input is the list of forums and chat rooms, and the output is the user's selection.

[1342] Step 7:

[1343] Instantly joins a forum or chat room selected by the user. The device sends the selected chat room ID to the server, which then connects the user to that chat room. The input is the selected chat room ID, and the output is the user's connection to the chat room.

[1344] This allows users to quickly find information and discussions related to the content they are viewing, enabling efficient information sharing and communication.

[1345] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1346] The present invention provides a system that enables users to efficiently use business communication tools, and includes a chat management function that utilizes generative AI and an emotion engine. Specific embodiments for implementing the present invention will be described below.

[1347] Message analysis and chat room suggestions

[1348] 1. Message reception and analysis

[1349] A user sends a message using a business chat tool.

[1350] The terminal receives this message and sends it to the server.

[1351] The server runs a generative AI model to analyze the content of the message, extracting keywords and important topics.

[1352] 2. Chat room suggestions

[1353] The server generates suitable chat room candidates based on the message analysis results.

[1354] The server sends chat room candidates to the terminal.

[1355] The terminal displays chat room candidates to the user and prompts the user to select one.

[1356] Examples:

[1357] If a user sends a message saying "New project progress report," the server will suggest related chat rooms such as "Project progress report" and "New project."

[1358] Suggest and create new chat rooms

[1359] 1. Parsing chat room creation requests

[1360] The user inputs a message indicating their intention to create a new chat room and sends it.

[1361] The terminal receives the request and sends it to the server.

[1362] The server uses the generated AI model to analyze the request content and extract relevant keywords.

[1363] 2. Comparison with existing chat rooms and proposals

[1364] The server compares the received request with existing chat rooms.

[1365] If the server finds no duplicate entries, it will propose creating a new chat room, otherwise it will propose merging.

[1366] The proposal results are sent to the terminal and displayed to the user.

[1367] Examples:

[1368] When a user submits a request to create a chat room for "Regular Marketing Team Meetings," the server checks to see if there is an existing "Marketing Team" chat room and makes appropriate suggestions.

[1369] Message priority organization and notification

[1370] 1. Message Reception and Priority Analysis

[1371] The user receives a message from a team member. The device receives the message and forwards it to the server.

[1372] 2. Prioritization and Notifications

[1373] The server uses the generated AI model to analyze the content of the message and assess its urgency and importance.

[1374] The server assigns a priority to the message based on the analysis results, categorizing it as high priority, medium priority, or low priority.

[1375] The server generates a dedicated notification for high-priority messages and sends it to the device, which displays a notification of the important message to the user.

[1376] Examples:

[1377] When a user receives a message saying "Please respond to an order from a client as soon as possible," the server analyzes the urgency of the message and issues a notification with high priority.

[1378] Chat room summary

[1379] 1. Processing Abstract Requests

[1380] A user sends a message requesting a summary of the chat room contents. The terminal receives the request and sends it to the server.

[1381] 2. Generating and serving summaries

[1382] The server launches the generative AI model and analyzes past messages in the specified chat room.

[1383] The server extracts key points from the analysis and creates a summary, including key progress, decisions, and next steps.

[1384] The server sends the created summary to the terminal, which displays the summary to the user.

[1385] Examples:

[1386] When a user sends a request such as "Please send me a summary of the weekly report chat room," the server analyzes the messages in the chat room, generates a summary including important progress, decisions, next steps, etc., and sends it to the terminal.

[1387] Combining Emotion Engines

[1388] 1. Sentiment Analysis and Action

[1389] When a user sends or receives a message, the emotion engine analyzes the message's emotion, and the server suggests or executes an action based on the results of the emotion analysis.

[1390] The server adjusts chat room suggestions, priorities, and notification content based on the emotions recognized.

[1391] Examples:

[1392] If a user sends a message expressing stress or tension (e.g., "This task is really difficult!"), the emotion engine recognizes this emotion and the server suggests appropriate support messages and resources.

[1393] Through the specific processing steps of this system, users can efficiently manage messages, quickly grasp important information, and receive emotionally sensitive responses and suggestions.

[1394] The processing flow will be explained below.

[1395] Message analysis and chat room suggestions

[1396] Processing Steps:

[1397] Step 1:

[1398] A user uses a business chat tool to type a message and presses the "Send" button. The device receives the message and sends it to the server.

[1399] Step 2:

[1400] The server receives the message, activates a generative AI model, and analyzes the message content, extracting keywords and important topics.

[1401] Step 3:

[1402] Based on the analysis results, the server evaluates the relevance to existing chat rooms and generates highly relevant chat room candidates.

[1403] Step 4:

[1404] The server sends the generated chat room candidate list to the terminal, which displays the chat room candidates to the user and prompts them to make a selection.

[1405] Suggest and create new chat rooms

[1406] Processing Steps:

[1407] Step 1:

[1408] The user enters a message about the new chat room they wish to create and presses the "Send" button. The device receives this message and sends it to the server.

[1409] Step 2:

[1410] The server receives the request, activates the generative AI model, and analyzes the request. Keywords and topics are extracted as a result of the analysis.

[1411] Step 3:

[1412] The server compares the request with existing chat rooms based on extracted keywords and topics, and evaluates relevance and overlap.

[1413] Step 4:

[1414] Based on the comparison, the server makes a suggestion to the user: either to create a new chat room or to merge into an existing chat room.

[1415] Step 5:

[1416] The server sends the proposal results to the device, which displays the proposals to the user and prompts them to make a selection.

[1417] Message priority organization and notification

[1418] Processing Steps:

[1419] Step 1:

[1420] The user receives a message from a team member. The device receives the message and forwards it to the server.

[1421] Step 2:

[1422] The server receives the message and uses a generative AI model to analyze the message content and assess its urgency and importance.

[1423] Step 3:

[1424] The server assigns a priority to the message based on the analysis results, categorizing it into high, medium, and low priority categories.

[1425] Step 4:

[1426] The server generates a dedicated notification for high-priority messages and sends it to the device, which displays a notification of the important message to the user.

[1427] Chat room summary

[1428] Processing Steps:

[1429] Step 1:

[1430] A user sends a message requesting a summary of the chat room contents. The terminal receives the request and sends it to the server.

[1431] Step 2:

[1432] The server receives the request, launches the generative AI model, and analyzes past messages in the specified chat room.

[1433] Step 3:

[1434] The server extracts key points from the analysis and creates a summary, including key progress, decisions, and next steps.

[1435] Step 4:

[1436] The server sends the created summary to the terminal, which displays the summary to the user.

[1437] Combining Emotion Engines

[1438] Processing Steps:

[1439] Step 1:

[1440] When a user sends a message, the device sends the message to the server, which receives the message and uses the emotion engine to analyze the emotion of the message.

[1441] Step 2:

[1442] The server receives the analysis results of the emotion engine and suggests or executes actions based on the recognized emotions. For example, if the user is feeling stressed, it generates an appropriate support message.

[1443] Step 3:

[1444] The server adjusts chat room suggestions and notification content based on the recognized emotion. For example, if the user is feeling stressed, chat room suggestions are adjusted to address issues that can be easily resolved.

[1445] Step 4:

[1446] The server sends the adjusted chat room suggestions and notification content to the terminal, which displays them to the user and prompts them to make a selection or confirm.

[1447] Examples:

[1448] Message Parsing:

[1449] When a user sends a message saying "New project progress report," the server suggests chat rooms related to "Project progress report" and "New project."

[1450] New chat room suggestions:

[1451] When a user submits a request to create a chat room for "Regular Marketing Team Meetings," the server checks to see if there is an existing "Marketing Team" chat room and makes a suggestion.

[1452] Message priority organization:

[1453] When a user receives a message saying "Please respond to an order from a client as soon as possible," the server analyzes the urgency of the message and issues a notification with high priority.

[1454] Emotion Engine:

[1455] If a user sends a message such as "This task is really difficult!", the emotion engine will recognize the stress and the server will suggest an appropriate support message.

[1456] Example 2

[1457] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1458] Current business chat tools make it difficult for users to efficiently manage messages and join or create new chat rooms. They also lack the functionality to quickly evaluate and notify the importance and urgency of received messages. Furthermore, functions such as message sentiment analysis and summary generation are inadequate. Therefore, there is a need to provide a stress-free communication environment for users.

[1459] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1460] In this invention, the server includes: means for analyzing messages received from a user; means for suggesting relevant chat room candidates based on the analysis results; means for notifying the user of the suggested chat room candidates; means for analyzing the sentiment of messages using a sentiment analysis engine and suggesting appropriate actions based on the analysis results; means for analyzing and setting the importance and priority of received messages; means for notifying the user of important messages based on the set priority; means for analyzing messages in a specified chat room and generating summaries; means for notifying the user of the generated summaries; means for analyzing messages using a generative AI model; and means for inputting prompts to the generative AI model to instruct analysis. This allows users to efficiently manage messages and join appropriate chat rooms or create new chat rooms. Furthermore, by quickly evaluating the importance and urgency of messages and performing sentiment analysis and summaries, a stress-free communication environment can be provided.

[1461] "User" means an individual or legal entity that uses the business communication tool to send or receive messages.

[1462] A "message" is data such as text, images, and audio that a user sends or receives through a business chat tool.

[1463] "Means of analysis" refers to the technology that analyzes the content of received messages and extracts keywords and important topics.

[1464] "Chat Room Suggestion" refers to a suggestion of a relevant existing or new chat room based on the analyzed content of the message.

[1465] "Means of notification" refers to technology that provides analysis results and notification content to users and encourages them to take the next action.

[1466] An "emotion analysis engine" refers to technology that analyzes the emotions contained in the content of a message and suggests appropriate actions based on the analysis results.

[1467] "Importance and priority" refers to the criteria for assessing and classifying the urgency and importance of received messages.

[1468] "Means for generating a summary" refers to a technology that analyzes past messages in a specified chat room, extracts key information, and creates a summary.

[1469] A "generative AI model" refers to a machine learning model that uses artificial intelligence technology to analyze messages and generate summaries.

[1470] A "prompt" refers to text that is entered to give specific instructions to a generative AI model.

[1471] The present invention provides a system that enables users to efficiently use business communication tools, and includes a chat management function that utilizes a generative AI model and an emotion engine. Specific embodiments for implementing the present invention will be described below.

[1472] Message analysis and chat room suggestions

[1473] 1. Message reception and analysis

[1474] A user uses a business chat tool to send a message such as "Report on the progress of a new project."

[1475] The terminal receives this message and sends it to the server.

[1476] The server launches a generative AI model (e.g., OpenAI's GPT-4) to analyze the message content. This analysis uses the prompt "Please extract keywords and topics from the following message." This results in the extraction of the keywords "new project," "progress," and "report."

[1477] 2. Chat room suggestions

[1478] The server generates appropriate chat room candidates based on the extracted keywords. For example, it compares the keywords with a list of existing chat rooms and suggests related chat rooms such as "project progress report" and "new project."

[1479] The server sends chat room candidates to the terminal.

[1480] The terminal displays chat room candidates to the user and prompts the user to select one.

[1481] Suggest and create new chat rooms

[1482] 1. Parsing chat room creation requests

[1483] A user enters a message stating that they want to create a new chat room, such as "Regular Marketing Team Meetings," and sends it.

[1484] The terminal receives the request and sends it to the server.

[1485] The server uses a generative AI model and prompts the user with the following sentence: "Analyze a new chat room request and extract relevant keywords." The server extracts keywords such as "marketing team" and "regular meeting" from the request.

[1486] 2. Comparison with existing chat rooms and proposals

[1487] The server compares the extracted keywords with the existing chat room list to check for overlapping content.

[1488] If the server has an existing chat room for "Marketing Team", it will suggest to the user, "Do you want to use the existing chat room?" If there is no overlap, it will suggest creating a new chat room.

[1489] The device displays the proposed results to the user, who can then choose to accept the proposal or create a new one.

[1490] Message priority organization and notification

[1491] 1. Message Reception and Priority Analysis

[1492] The user receives a message from a team member saying, "Please handle the client's order as soon as possible." The terminal receives this message and sends it to the server.

[1493] 2. Prioritization and Notifications

[1494] The server uses a generative AI model to analyze the message content by setting a prompt sentence: "Please rate the urgency and importance of this message." This determines the message to be of high urgency.

[1495] The server sets the message priority to "high" based on this result.

[1496] The server generates a dedicated notification for high-priority messages and sends it to the device. The device displays a notification of the important message to the user. The user checks the notification and responds promptly.

[1497] Chat room summary

[1498] 1. Processing Abstract Requests

[1499] A user requests a summary of the chat room contents by sending the message "Please give me a summary of the weekly chat room report." The terminal receives this request and sends it to the server.

[1500] 2. Generating and serving summaries

[1501] The server launches the generative AI model and uses the prompt, "Analyze the past messages in this chat room and summarize the key points." The server analyzes the past messages in the specified chat room and extracts key progress, decisions, next steps, etc.

[1502] The server creates a summary and sends it to the terminal, which displays the summary to the user, who reviews the summary and plans next steps.

[1503] Combining Emotion Engines

[1504] 1. Sentiment Analysis and Action

[1505] When a user sends or receives a message such as "This task is really difficult!", the emotion engine analyzes the emotion of the message. The server then suggests actions based on the results of this emotion analysis.

[1506] The server suggests appropriate support messages and resources based on the emotions it recognizes. Specifically, it generates support messages such as "Do you need additional resources for this task?"

[1507] The terminal displays a support message to the user, and the user requests resources as needed.

[1508] Through these processing steps, users can efficiently manage messages, join appropriate chat rooms, create new chat rooms, prioritize messages, generate summaries, and analyze sentiment, thereby providing a stress-free communication environment for users.

[1509] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1510] Message analysis and chat room suggestions

[1511] Step 1:

[1512] Receiving messages

[1513] A user types and sends a message via a business chat tool saying, "Report on the progress of a new project."

[1514] Input: User's message

[1515] Output: Request to send message to terminal

[1516] Step 2:

[1517] Message relay by terminal

[1518] The terminal transmits the message received from the user to the server.

[1519] Input: The user's sent message

[1520] Output: Message transfer request to server

[1521] Step 3:

[1522] Server parsing of messages

[1523] The server launches a generative AI model (e.g., GPT-4) and analyzes the message content using the prompt, "Please extract keywords and topics from the message below."

[1524] Input: Message received from the terminal, prompt text

[1525] Output: Extracted keywords "new project", "progress", "report"

[1526] Step 4:

[1527] Generate chat room candidates

[1528] The server compares the extracted keywords with a list of past chat rooms to generate highly relevant chat room candidates.

[1529] Input: Extracted keywords

[1530] Output: List of chat room candidates (e.g. "Project progress report", "New project")

[1531] Step 5:

[1532] Device notifications

[1533] The server transmits the generated chat room candidates to the terminal, and the terminal displays the chat room candidates to the user.

[1534] Input: Chat room candidate list

[1535] Output: Chat room suggestions displayed to the user

[1536] Suggest and create new chat rooms

[1537] Step 1:

[1538] Sending a chat room creation request

[1539] A user sends a message requesting the creation of a chat room called "Marketing Team Regular Meetings."

[1540] Input: User creation request message

[1541] Output: Request to send message to terminal

[1542] Step 2:

[1543] Terminal relays requests

[1544] The terminal transmits the request message received from the user to the server.

[1545] Input: User request message

[1546] Output: Request forwarded to server

[1547] Step 3:

[1548] Request analysis by the server

[1549] The server launches the generative AI model and analyzes the content of the request using the prompt "Analyze a new chat room request and extract relevant keywords."

[1550] Input: Request received from the terminal, prompt text

[1551] Output: Extracted keywords "marketing team" and "regular meeting"

[1552] Step 4:

[1553] Comparison with existing chat rooms

[1554] The server checks the extracted keywords against the existing chat room list to see if there are any overlaps.

[1555] Input: Extracted keywords

[1556] Output: Existing chat rooms

[1557] Step 5:

[1558] Proposal generation and notification

[1559] The server generates a proposal to create a new chat room or to merge with an existing chat room based on the request content and the comparison result, and sends it to the terminal. The terminal displays the proposal to the user.

[1560] Input: Request details, whether or not there is an existing chat room

[1561] Output: Proposal displayed to the user

[1562] Message priority organization and notification

[1563] Step 1:

[1564] Receiving messages

[1565] The user receives a message saying, "Please handle the order from the client as soon as possible." The terminal receives the message and sends it to the server.

[1566] Input: Incoming message

[1567] Output: Message transfer request to server

[1568] Step 2:

[1569] Message Priority Analysis

[1570] The server uses a generative AI model to set a prompt such as "Please rate the urgency and importance of this message" and analyze the message content.

[1571] Input: message, prompt

[1572] Output: Set priority (e.g. High)

[1573] Step 3:

[1574] Generate notifications based on priority

[1575] The server generates a dedicated notification for high-priority messages and sends it to the device, which displays a notification of the important message to the user.

[1576] Input: Set priority

[1577] Output: Important message notification to the user

[1578] Chat room summary

[1579] Step 1:

[1580] Submitting a Summary Request

[1581] The user sends a request saying, "Please send me a summary of the weekly chat room report." The device receives the request and forwards it to the server.

[1582] Input: User request message

[1583] Output: Request forwarded to server

[1584] Step 2:

[1585] Generate a summary

[1586] The server uses the generative AI model to set a prompt such as "Analyze the past messages in this chat room and summarize the important points," and analyzes the past messages in the specified chat room.

[1587] Input: Request, prompt, past message

[1588] Output: Generated summary

[1589] Step 3:

[1590] Provision to users

[1591] The server sends the generated summary to the terminal, which displays the summary to the user.

[1592] Input: Generated summary

[1593] Output: Summary displayed to the user

[1594] Combining Emotion Engines

[1595] Step 1:

[1596] Message sentiment analysis

[1597] When a user sends or receives a message such as "This task is really difficult!", the emotion engine analyzes the emotion of the message.

[1598] Input: Message sent or received

[1599] Output: Analysis results (e.g. stress, tension)

[1600] Step 2:

[1601] Suggestions for appropriate actions

[1602] Based on the results of the sentiment analysis, the server generates a support message asking, "Do you need additional resources for this task?" and sends it to the device. The device then displays the support message to the user.

[1603] Input: Sentiment analysis results

[1604] Output: Display support message to user

[1605] Through the above specific processing steps, users can efficiently manage messages and ensure smooth operation of the chat room. Furthermore, emotion analysis can reduce users' psychological burden and provide appropriate support.

[1606] (Application example 2)

[1607] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1608] Conventional business communication tools have limited functionality, such as message analysis and chat room suggestions, limiting the ways for users to quickly and efficiently obtain the information they need. Furthermore, systems for appropriately classifying message urgency and importance and for advanced communication are inadequate. In particular, systems requiring advanced operational management, such as autonomous vehicles, often require real-time emergency response and appropriate instructions based on emotion analysis, and existing systems have difficulty meeting these requirements.

[1609] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1610] In this invention, the server includes means for analyzing messages received from users, means for proposing highly relevant chat room candidates based on the analysis results, means for notifying users of the proposed chat room candidates, means for analyzing the sentiment of the messages, means for adjusting the chat room candidates based on the sentiment analysis results, and means for setting message priorities and generating notifications according to urgency, thereby enabling users to quickly and efficiently obtain necessary information and appropriately respond to emergencies and important messages.

[1611] "Analysis of messages received from users" is a process of automatically analyzing the contents of messages sent by users and extracting important keywords and contexts.

[1612] "Suggesting relevant chat room candidates" is a function that identifies and suggests appropriate chat rooms for the user to join based on the results of message analysis.

[1613] "Emotion analysis" is an analytical process for determining the emotional state of the sender and receiver from the content of a message.

[1614] "Adjusting chat room candidates" is a process of optimizing the list of chat rooms suggested to the user based on the results of sentiment analysis.

[1615] "Message priority setting" is a function that evaluates the importance and urgency of received messages and automatically sets the priority accordingly.

[1616] "Generating notifications according to urgency" is a function that sends special notifications to users for messages that are important and urgent based on the set priority.

[1617] "Analysis of chat room creation requests" is a process that automatically analyzes new chat room creation requests from users and understands their intent.

[1618] "Compare with existing chat rooms" refers to the process of comparing a new chat room creation request with existing chat rooms to determine if the request overlaps with an existing chat room.

[1619] "Proposal to create or merge a new chat room" is a function that suggests to the user to create a new chat room or merge with an existing chat room based on the analysis results.

[1620] "Quick suggestion of appropriate responses in emergencies" is a function that quickly suggests to users the actions and countermeasures required in emergencies.

[1621] As a mode for carrying out the present invention, an embodiment of a communication and operation management system for an autonomous driving vehicle will be described below.

[1622] The system analyzes messages received from users and suggests appropriate chat rooms based on the results of the analysis. It can also analyze the sentiment of messages, generate notifications based on urgency, and compare existing chat rooms.

[1623] Receiving and parsing messages

[1624] The server receives messages sent by users, which are then analyzed using a generative AI model (e.g., the Sentiment Analysis model from HuggingFace's transformers library) to extract important keywords and context and suggest appropriate chat rooms based on the content.

[1625] Emotion analysis

[1626] The server uses a generative AI model to analyze the sentiment of the message. Based on this analysis, it adjusts chat room suggestions and optimizes the suggestions as needed. For example, if a message is sent saying, "An accident has occurred. Immediate action is required," the server will determine this message as "negative" and suggest a chat room that requires a high level of urgency.

[1627] Prioritization and Notifications

[1628] The server classifies received messages based on importance and urgency, and generates special notifications based on the set priority and sends them to the user's device, allowing the user to quickly understand important messages and urgent actions.

[1629] Creating and comparing chat rooms

[1630] When a user requests to create a new chat room, the server analyzes the request and compares it with existing chat rooms. If there are no overlaps, the server proposes the creation of a new chat room, and if there are overlaps, it proposes merging. For example, if a request comes in to "report on the progress of a new project," the server checks whether there is an existing "project progress report" chat room and makes an appropriate proposal.

[1631] Specific examples

[1632] When an autonomous vehicle sends a message saying, "Left front tire pressure is low," the message is analyzed by a generative AI model. As a result, the message is determined to be "negative," a notification is sent to the maintenance team's chat room, and a prompt is generated: "New maintenance request: Left front tire pressure is low," suggesting an appropriate response.

[1633] Prompt Sentence Examples

[1634] A new maintenance request has arrived:

[1635] Vehicle ID: Vehicle1234

[1636] Message: Left front tire pressure low

[1637] In this way, the system of the present invention realizes efficient business communication by analyzing the user's messages in detail and making appropriate suggestions and notifications that take into account the user's emotions and urgency.

[1638] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1639] Step 1:

[1640] A user sends a message from a device inside an autonomous vehicle.

[1641] The user inputs a message and presses the send button to send it to the terminal. An input message might be something like "The air pressure in the left front tire is low." The output is the message data that was sent.

[1642] Step 2:

[1643] The terminal transfers the received message to the server.

[1644] When a terminal receives a message from a user, it sends the contents of the message to the server. The input is the received message data, and the output is the message data transferred to the server.

[1645] Step 3:

[1646] The server analyzes the message content using a generative AI model.

[1647] The server inputs the received message data into the generative AI model and performs an analysis to extract keywords and context. This analysis extracts important information. The input is the message data, and the output is the keywords and context information that are the analysis results.

[1648] Step 4:

[1649] The server performs sentiment analysis.

[1650] The server uses the generative AI model to analyze the sentiment of the message. The input is the analysis result from step 3, and the output is the analyzed sentiment data (e.g., negative or positive classification and its confidence score).

[1651] Step 5:

[1652] The server proposes chat room candidates based on the analysis results.

[1653] The server identifies relevant chat room candidates based on the message keywords and sentiment analysis results and generates a list. The input is the analysis results of steps 3 and 4, and the output is a list of chat room candidates.

[1654] Step 6:

[1655] The server notifies the terminal of chat room candidates.

[1656] The server sends the generated list of chat room candidates to the terminal and displays it to the user. The input is the list of chat room candidates, and the output is a notification displayed on the user's terminal.

[1657] Step 7:

[1658] The user selects a chat room.

[1659] The user selects the most suitable chat room from the chat room candidates displayed on the terminal. The input is the chat room candidate list displayed on the terminal, and the output is the selected chat room.

[1660] Step 8:

[1661] The server parses the request to create a new chat room.

[1662] When a user sends a request, the server receives it and analyzes the content using a generative AI model. The input is the request message from the user, and the output is the analyzed request data.

[1663] Step 9:

[1664] The server compares the new request with existing chat rooms.

[1665] The server compares the parsed request data with the existing chat room database to check for duplicates. The input is the parsed request data and existing chat room data, and the output is the presence or absence of duplicates and new proposed data.

[1666] Step 10:

[1667] The server will propose the creation or merging of new chat rooms.

[1668] Based on the comparison results, the server proposes a future action (creating a new chat room or merging into an existing chat room) to the user. The input is the comparison result data, and the output is a proposal notification.

[1669] Step 11:

[1670] The server prioritizes messages and generates notifications based on urgency.

[1671] The server evaluates the importance and urgency of messages and generates special notifications for high-priority messages. The input is the analysis results and importance rating data, and the output is the generated special notifications.

[1672] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1673] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1674] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1675] [Fourth embodiment]

[1676] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1677] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1678] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1679] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1680] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1681] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1682] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1683] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1684] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1685] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1686] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1687] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1688] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1689] The present invention provides a system that enables users to efficiently use business communication tools, and includes a chat management function that utilizes AI generation. Specific embodiments for implementing the present invention will be described below.

[1690] Message analysis and chat room suggestions

[1691] 1. Message reception and analysis

[1692] A user sends a message using a business chat tool.

[1693] The terminal receives this message and sends it to the server.

[1694] The server uses a generative AI model to analyze the content of the message, extracting keywords and important topics.

[1695] 2. Chat room suggestions

[1696] The server generates suitable chat room candidates based on the message analysis results.

[1697] The server sends chat room candidates to the terminal.

[1698] The terminal displays chat room candidates to the user and prompts the user to select one.

[1699] Examples:

[1700] If a user sends a message saying "New project progress report," the server will suggest related chat rooms such as "Project progress report" and "New project."

[1701] Suggest and create new chat rooms

[1702] 1. Parsing chat room creation requests

[1703] The user inputs a message indicating their intention to create a new chat room and sends it.

[1704] The terminal receives the request and sends it to the server.

[1705] The server uses the generated AI model to analyze the request content and extract relevant keywords.

[1706] 2. Comparison with existing chat rooms and proposals

[1707] The server compares the received request with existing chat rooms.

[1708] If the server finds no duplicate entries, it will propose creating a new chat room, otherwise it will propose merging.

[1709] The proposal results are sent to the terminal and displayed to the user.

[1710] Examples:

[1711] When a user submits a request to create a chat room for "Regular Marketing Team Meetings," the server checks to see if there is an existing "Marketing Team" chat room and makes appropriate suggestions.

[1712] Message priority organization and notification

[1713] 1. Message Reception and Priority Analysis

[1714] The user receives the message.

[1715] The terminal sends this message to the server.

[1716] The server uses the generated AI model to analyze the urgency and importance of the message.

[1717] 2. Prioritization and Notifications

[1718] The server sets the priority of the message based on the analysis results.

[1719] The server creates a dedicated notification for high priority messages and sends it to the device.

[1720] The device displays a notification to the user.

[1721] Examples:

[1722] When a user receives a message saying "Please respond to an order from a client as soon as possible," the server analyzes the importance of the message and notifies the user as a high priority.

[1723] Chat room summary

[1724] 1. Processing Abstract Requests

[1725] A user enters and submits a request for a summary of the chat room.

[1726] The terminal receives the request and sends it to the server.

[1727] 2. Generating and serving summaries

[1728] The server uses the generated AI model to analyze past messages in a specified chat room.

[1729] The server extracts the key points and creates a summary.

[1730] The summary is sent to the terminal and presented to the user.

[1731] Examples:

[1732] When a user sends a request such as "Please send me a summary of the weekly report chat room," the server analyzes all messages in that chat room, creates a summary including important progress, decisions, and next steps, and sends it to the device.

[1733] In this way, the present invention provides support for users to improve work efficiency and quickly grasp important information.

[1734] The processing flow will be explained below.

[1735] Message analysis and chat room suggestions

[1736] Processing Steps:

[1737] Step 1:

[1738] The user enters a message and presses the "Send" button. The device receives the message and sends it to the server.

[1739] Step 2:

[1740] The server receives the message. The server then launches a generative AI model to analyze the message content. Through analysis, keywords and key points from the message are extracted.

[1741] Step 3:

[1742] Based on the analysis results, the server evaluates the relevance to existing chat rooms and generates highly relevant chat room candidates.

[1743] Step 4:

[1744] The server sends the generated chat room candidate list to the terminal, which displays the chat room candidates to the user and prompts them to make a selection.

[1745] Suggest and create new chat rooms

[1746] Processing Steps:

[1747] Step 1:

[1748] The user enters a message about the new chat room they wish to create and presses the "Send" button. The device receives this message and sends it to the server.

[1749] Step 2:

[1750] The server receives the request, activates the generative AI model, and analyzes the request. Keywords and topics are extracted as a result of the analysis.

[1751] Step 3:

[1752] The server compares the request with existing chat rooms based on extracted keywords and topics, and evaluates relevance and overlap.

[1753] Step 4:

[1754] Based on the comparison, the server makes a suggestion to the user: either to create a new chat room or to merge into an existing chat room.

[1755] Step 5:

[1756] The server sends the proposal results to the device, which displays the proposals to the user and prompts them to make a selection.

[1757] Message priority organization and notification

[1758] Processing Steps:

[1759] Step 1:

[1760] The user receives a message from a team member. The device receives the message and forwards it to the server.

[1761] Step 2:

[1762] The server receives the message and uses a generative AI model to analyze the message content and assess its urgency and importance.

[1763] Step 3:

[1764] The server assigns a priority to the message based on the analysis results, categorizing it into high, medium, and low priority categories.

[1765] Step 4:

[1766] The server generates a dedicated notification for high-priority messages and sends it to the device, which displays a notification of the important message to the user.

[1767] Chat room summary

[1768] Processing Steps:

[1769] Step 1:

[1770] A user sends a message requesting a summary of the chat room contents. The terminal receives the request and sends it to the server.

[1771] Step 2:

[1772] The server receives the request, launches the generative AI model, and analyzes past messages in the specified chat room.

[1773] Step 3:

[1774] The server extracts key points from the analysis and creates a summary, including key progress, decisions, and next steps.

[1775] Step 4:

[1776] The server sends the created summary to the terminal, which displays the summary to the user.

[1777] Through the specific processing steps of this system, users can efficiently manage messages and quickly grasp important information.

[1778] Example 1

[1779] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1780] Conventional business communication tools have limited capabilities for analyzing received messages, making it difficult to quickly and accurately present appropriate chat room or collaboration room candidates. Furthermore, they often lack the functionality to quickly determine the urgency and importance of users' messages and provide immediate notifications for high-priority messages. As a result, users are at greater risk of overlooking important information, which can lead to reduced work efficiency. Furthermore, when users create a new chat room, it is difficult to avoid overlaps with existing chat rooms and to suggest appropriate rooms. Therefore, the present invention aims to solve these problems.

[1781] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1782] In this invention, the server includes means for analyzing messages received from users, means for proposing highly relevant communication room candidates based on the analysis results, means for notifying users of the proposed communication room candidates, means for analyzing the content of messages using a generative AI model and extracting important keywords and topics, means for generating appropriate collaboration rooms based on the extracted information, and means for transmitting and displaying the generated collaboration room proposals to user terminals, thereby enabling users to conduct business communication quickly and effectively without overlooking important information.

[1783] "User" refers to an individual or organization that uses the business communication tools of this system.

[1784] "Message" refers to text information sent by a user through a business chat tool.

[1785] "Terminal" refers to the hardware device used by a User to access the System.

[1786] "Server" refers to a remotely located computer system that performs central processing for the System.

[1787] "Means of analysis" refers to the process of using a generative AI model to understand the content of a message and extract key elements.

[1788] A "generative AI model" refers to an algorithm that applies artificial intelligence technology to analyze text data and generate or extract specific information.

[1789] A "communication room" is a virtual room for exchanging messages about a specific topic or project.

[1790] "Collaboration Room" refers to a virtual room where users can collaborate on a specific team or project.

[1791] "Means of suggestion" refers to the process of showing users appropriate communication or collaboration rooms based on the analysis results.

[1792] "Means for notifying" refers to the process for displaying suggested rooms and important messages to users.

[1793] "Importance" refers to an index that indicates how urgent or important the content of a message is to the user.

[1794] "Priority" refers to an index that determines the priority of processing or notification based on the importance of a message.

[1795] "Comparison method" refers to the process of checking user requests against existing information to identify overlaps and relevance.

[1796] A "request" refers to a message that a user sends to the system to inform the system that they wish to create a new collaboration room.

[1797] "Proposal Results" refers to action plans or recommendations to users that are generated as a result of the analysis and comparison.

[1798] The present invention provides a system that enables users to efficiently use business communication tools, and includes a chat management function that utilizes a generative AI model. Specific embodiments for implementing the present invention will be described below.

[1799] Configuration and operation overview

[1800] In this invention, when a user sends and receives messages using a business chat tool, a server and a terminal work together to provide advanced functions such as analysis, suggestions, notifications, and summaries. The server uses a generative AI model (e.g., OpenAI's GPT-4) to analyze the content of the messages and extract and process important information.

[1801] Hardware and software used

[1802] Terminal: A device used by a user, such as a personal computer or smartphone.

[1803] Server: A remotely located computer system that handles message analysis and notification processing.

[1804] Generative AI models: Algorithms for natural language processing (e.g., GPT-4).

[1805] Message analysis and chat room suggestions

[1806] When a user sends a message using a business chat tool saying, "Report on the progress of a new project," the device receives the message and sends it to the server, which then uses a generative AI model to analyze the message and extract important keywords and topics.

[1807] Based on the extracted information, the server generates appropriate communication room candidates (e.g., "Project Progress Report" or "New Project") and sends them to the terminal. The terminal displays the candidates to the user, who then selects an appropriate chat room.

[1808] Suggest and create new chat rooms

[1809] When a user inputs and sends a request to create a chat room for "Regular Marketing Team Meetings," the device receives the request and sends it to the server, which uses a generative AI model to analyze the request and extract relevant keywords.

[1810] The server compares the extracted keywords with existing collaboration room information and makes a proposal to create a new room or use an existing room. The proposal results are sent to the user's terminal and displayed to the user.

[1811] Message priority organization and notification

[1812] If a user receives a message saying, "Please handle an order from a client urgently," the device sends this message to the server, which uses a generative AI model to analyze the urgency and importance of the message and sets it as high priority.

[1813] For the set high-priority messages, the server creates a dedicated notification and sends it to the terminal, which displays the notification to the user and prompts them to respond promptly.

[1814] Chat room summary

[1815] When a user sends a request such as "Please send me a summary of the weekly chat room report," the device receives the request and sends it to the server, which uses a generative AI model to analyze past messages in the specified chat room, extract key points, and create a summary.

[1816] The created summary is sent to the terminal and provided to the user, allowing the user to quickly grasp important information and carry out work efficiently.

[1817] Specific examples

[1818] As a concrete example, the following prompt sentence is used:

[1819] "Do you want to create a new chat room or view an existing chat room?"

[1820] "Does this message require urgent attention?"

[1821] As a result, the present invention provides support for users to efficiently use business communication tools and quickly grasp important information.

[1822] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1823] Step 1:

[1824] A user sends a message using a business chat tool. Specifically, the user enters text such as "Report on the progress of a new project" and clicks the send button. This input text is sent to the device.

[1825] Step 2:

[1826] The device receives the message sent by the user. The received message is temporarily stored in the internal memory.

[1827] Step 3:

[1828] The terminal sends the received message to the server. Specifically, the message data is sent in packet format to the server's address. At this stage, the input data is the message text, and the output data is the text data sent to the server.

[1829] Step 4:

[1830] The server analyzes the received message. A generative AI model (e.g., GPT-4) is used to analyze the message content and extract keywords and important topics. The input is the message text data, and the output is a list of extracted keywords.

[1831] Step 5:

[1832] The server generates appropriate communication room candidates based on the extracted keywords and topics. Specifically, it generates candidate room names such as "Project Progress Report" and "New Project." The input of this process is a keyword list, and the output is a communication room candidate list.

[1833] Step 6:

[1834] The server sends the created communication room candidate list to the terminal, and the sent data arrives at the terminal as the room candidate list.

[1835] Step 7:

[1836] The device displays chat room candidates to the user and prompts them to select one. Specifically, a list of candidates such as "Project Progress Report" and "New Project" is displayed on the user's screen. The user selects an appropriate chat room from these candidates.

[1837] Step 8:

[1838] When a user wishes to create a new chat room, he or she inputs a request such as "Regular meeting of the marketing team" in a message and sends it. This input data is sent to the terminal.

[1839] Step 9:

[1840] The terminal receives the request and sends it to the server. The request data is sent to the server in packet format.

[1841] Step 10:

[1842] The server analyzes the request content using a generative AI model and extracts related keywords (e.g., "marketing" or "regular meeting"). The input is the request text data, and the output is a list of related keywords.

[1843] Step 11:

[1844] The server compares the extracted keywords with existing collaboration room information and makes proposals for creating new rooms or merging existing rooms. The input is a list of keywords and existing room information, and the output is the proposal results.

[1845] Step 12:

[1846] The proposal result is sent to the terminal, which displays it to the user. Specifically, it displays the prompt "Do you want to use the existing marketing team chat room?" The user can take appropriate action based on this proposal.

[1847] Step 13:

[1848] When a user receives a message saying "Please handle the client's order as soon as possible," the terminal sends this message to the server. The input is the message text, and the output is the data to be sent to the server.

[1849] Step 14:

[1850] The server uses a generative AI model to analyze the urgency and importance of messages and set them as high priority. The input is message text data, and the output is priority setting information.

[1851] Step 15:

[1852] The server creates a dedicated notification for the high-priority message and sends it to the terminal as notification data containing the important message.

[1853] Step 16:

[1854] The device displays a notification to the user to prompt them to take action. Specifically, a notification such as "You have an important message" is displayed on the user's screen.

[1855] Step 17:

[1856] When a user sends a request such as "Please give me a summary of the weekly report chat room," the terminal receives the request and sends it to the server. The input is the summary request text, and the output is the data to be sent to the server.

[1857] Step 18:

[1858] The server uses a generative AI model to analyze past messages in a specified chat room, extract important points, and create a summary. The input is past message data, and the output is summary data.

[1859] Step 19:

[1860] The server sends the summary to the terminal, which then provides it to the user. Specifically, the summarized content is displayed on the user's screen.

[1861] The above are the specific processing steps of the system according to the present invention.

[1862] (Application example 1)

[1863] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1864] In today's content distribution services, it is difficult for users to easily find information and communication forums related to the content they are viewing. Therefore, a system is needed that allows users to efficiently obtain the information they need and to quickly and smoothly engage in related communication.

[1865] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1866] In this invention, the server includes means for analyzing messages received from users, means for proposing highly relevant chat room candidates based on the analysis results, means for notifying users of the proposed chat room candidates, means for analyzing content currently being viewed by users and extracting related keywords, means for proposing related forums or chat rooms based on the extracted keywords, and means for notifying users of the proposed forums or chat rooms, thereby enabling users to instantly find forums or chat rooms related to the content currently being viewed, improving information sharing and communication.

[1867] The "means for analyzing messages" is a function for analyzing the contents of messages sent by users and extracting specific keywords and important topics.

[1868] The "means for proposing chat room candidates" is a function for displaying chat room candidates that are highly relevant to the user based on the results of the analysis.

[1869] The "means for notifying users of chat room candidates" is a function for notifying the user of proposed chat room candidates on the user's terminal and displaying them to the user.

[1870] The "means for analyzing content" is a function that analyzes the content of videos and other content that a user is watching and extracts related keywords and topics.

[1871] The "means for extracting keywords" is a function for identifying and extracting important keywords and topics from the information obtained by analyzing the content.

[1872] The "means for suggesting forums or chat rooms" is a function that suggests related forums or chat rooms to the user based on the extracted keywords.

[1873] The "means for notifying a user of a forum or chat room" is a function for notifying a user of a proposed forum or chat room on the user's terminal and displaying it to the user.

[1874] The present invention provides a system for suggesting and informing users of forums and chat rooms related to the content they are currently viewing, and includes an analysis means using a generative AI model. Specific embodiments for implementing the present invention will be described below.

[1875] First, the server at the center of the system includes a means for analyzing messages received from users, a means for proposing highly relevant chat room candidates based on the analysis results, and a means for notifying users of the proposed chat room candidates.Furthermore, the system includes a means for analyzing the content being viewed by users and extracting related keywords, a means for proposing related forums or chat rooms based on the extracted keywords, and a means for notifying users of the same.

[1876] The system runs on devices such as smartphones, smart glasses, or head-mounted displays. The devices are connected to the internet and can communicate with the server. It uses OpenAI's GPT-4 as a generative AI model for analysis, and is written in Python.

[1877] Specifically, when a user inputs the ID of the content they are watching, the server retrieves the content and uses a generative AI model (GPT-4) to extract keywords and topics. An example of a prompt sentence is "Extract the main topics and keywords from the following content: This video is about AI advancements in healthcare."

[1878] The server then suggests related forums or chat rooms based on the extracted keywords. This suggestion information is sent to the user's device, allowing the user to access related forums or chat rooms. For example, if a user is watching a video titled "Advancements in Medical Care Through AI," the server analyzes the content, extracts keywords such as "Healthcare AI" and "Advancements in AI," and suggests related forums and chat rooms.

[1879] This allows users to easily obtain information and discussions related to the content they are viewing, facilitating efficient information sharing and communication. The overall system processing flow is based on natural language processing technology and machine learning models, aiming to improve the content experience.

[1880] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1881] Step 1:

[1882] The user selects the content to view and enters the ID of that content into the device. The device then sends this content ID to the server. The input is the content ID, and the output is sending the content ID to the server.

[1883] Step 2:

[1884] The server retrieves the details of the related content based on the received content ID, including the content title, description, tags, etc. The input is the content ID, and the output is the detailed content information.

[1885] Step 3:

[1886] The server uses a generative AI model (GPT-4) to analyze the detailed information of the content and extract the main topics and keywords. In this process, a prompt is created for the generative AI model and the results are analyzed. The input is the detailed information of the content, and the output is a list of the main topics and keywords. An example of a prompt is "Extract the main topics and keywords from the following content: [Detailed information of the content]".

[1887] Step 4:

[1888] The server generates a list of related forums and chat rooms based on the extracted keywords. It compares them with an existing forum database and selects the most relevant ones. The input is the extracted keywords, and the output is a list of related forums and chat rooms.

[1889] Step 5:

[1890] The server sends the generated list of forums and chat rooms to the terminal. The input is the list of forums and chat rooms, and the output is sending the list to the terminal.

[1891] Step 6:

[1892] The terminal displays the received list of forums and chat rooms to the user, who selects the forums and chat rooms of interest from the suggested list. The input is the list of forums and chat rooms, and the output is the user's selection.

[1893] Step 7:

[1894] Instantly joins a forum or chat room selected by the user. The device sends the selected chat room ID to the server, which then connects the user to that chat room. The input is the selected chat room ID, and the output is the user's connection to the chat room.

[1895] This allows users to quickly find information and discussions related to the content they are viewing, enabling efficient information sharing and communication.

[1896] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1897] The present invention provides a system that enables users to efficiently use business communication tools, and includes a chat management function that utilizes generative AI and an emotion engine. Specific embodiments for implementing the present invention will be described below.

[1898] Message analysis and chat room suggestions

[1899] 1. Message reception and analysis

[1900] A user sends a message using a business chat tool.

[1901] The terminal receives this message and sends it to the server.

[1902] The server runs a generative AI model to analyze the content of the message, extracting keywords and important topics.

[1903] 2. Chat room suggestions

[1904] The server generates suitable chat room candidates based on the message analysis results.

[1905] The server sends chat room candidates to the terminal.

[1906] The terminal displays chat room candidates to the user and prompts the user to select one.

[1907] Examples:

[1908] If a user sends a message saying "New project progress report," the server will suggest related chat rooms such as "Project progress report" and "New project."

[1909] Suggest and create new chat rooms

[1910] 1. Parsing chat room creation requests

[1911] The user inputs a message indicating their intention to create a new chat room and sends it.

[1912] The terminal receives the request and sends it to the server.

[1913] The server uses the generated AI model to analyze the request content and extract relevant keywords.

[1914] 2. Comparison with existing chat rooms and proposals

[1915] The server compares the received request with existing chat rooms.

[1916] If the server finds no duplicate entries, it will propose creating a new chat room, otherwise it will propose merging.

[1917] The proposal results are sent to the terminal and displayed to the user.

[1918] Examples:

[1919] When a user submits a request to create a chat room for "Regular Marketing Team Meetings," the server checks to see if there is an existing "Marketing Team" chat room and makes appropriate suggestions.

[1920] Message priority organization and notification

[1921] 1. Message Reception and Priority Analysis

[1922] The user receives a message from a team member. The device receives the message and forwards it to the server.

[1923] 2. Prioritization and Notifications

[1924] The server uses the generated AI model to analyze the content of the message and assess its urgency and importance.

[1925] The server assigns a priority to the message based on the analysis results, categorizing it as high priority, medium priority, or low priority.

[1926] The server generates a dedicated notification for high-priority messages and sends it to the device, which displays a notification of the important message to the user.

[1927] Examples:

[1928] When a user receives a message saying "Please respond to an order from a client as soon as possible," the server analyzes the urgency of the message and issues a notification with high priority.

[1929] Chat room summary

[1930] 1. Processing Abstract Requests

[1931] A user sends a message requesting a summary of the chat room contents. The terminal receives the request and sends it to the server.

[1932] 2. Generating and serving summaries

[1933] The server launches the generative AI model and analyzes past messages in the specified chat room.

[1934] The server extracts key points from the analysis and creates a summary, including key progress, decisions, and next steps.

[1935] The server sends the created summary to the terminal, which displays the summary to the user.

[1936] Examples:

[1937] When a user sends a request such as "Please send me a summary of the weekly report chat room," the server analyzes the messages in the chat room, generates a summary including important progress, decisions, next steps, etc., and sends it to the terminal.

[1938] Combining Emotion Engines

[1939] 1. Sentiment Analysis and Action

[1940] When a user sends or receives a message, the emotion engine analyzes the message's emotion, and the server suggests or executes an action based on the results of the emotion analysis.

[1941] The server adjusts chat room suggestions, priorities, and notification content based on the emotions recognized.

[1942] Examples:

[1943] If a user sends a message expressing stress or tension (e.g., "This task is really difficult!"), the emotion engine recognizes this emotion and the server suggests appropriate support messages and resources.

[1944] Through the specific processing steps of this system, users can efficiently manage messages, quickly grasp important information, and receive emotionally sensitive responses and suggestions.

[1945] The processing flow will be explained below.

[1946] Message analysis and chat room suggestions

[1947] Processing Steps:

[1948] Step 1:

[1949] A user uses a business chat tool to type a message and presses the "Send" button. The device receives the message and sends it to the server.

[1950] Step 2:

[1951] The server receives the message, activates a generative AI model, and analyzes the message content, extracting keywords and important topics.

[1952] Step 3:

[1953] Based on the analysis results, the server evaluates the relevance to existing chat rooms and generates highly relevant chat room candidates.

[1954] Step 4:

[1955] The server sends the generated chat room candidate list to the terminal, which displays the chat room candidates to the user and prompts them to make a selection.

[1956] Suggest and create new chat rooms

[1957] Processing Steps:

[1958] Step 1:

[1959] The user enters a message about the new chat room they wish to create and presses the "Send" button. The device receives this message and sends it to the server.

[1960] Step 2:

[1961] The server receives the request, activates the generative AI model, and analyzes the request. Keywords and topics are extracted as a result of the analysis.

[1962] Step 3:

[1963] The server compares the request with existing chat rooms based on extracted keywords and topics, and evaluates relevance and overlap.

[1964] Step 4:

[1965] Based on the comparison, the server makes a suggestion to the user: either to create a new chat room or to merge into an existing chat room.

[1966] Step 5:

[1967] The server sends the proposal results to the device, which displays the proposals to the user and prompts them to make a selection.

[1968] Message priority organization and notification

[1969] Processing Steps:

[1970] Step 1:

[1971] The user receives a message from a team member. The device receives the message and forwards it to the server.

[1972] Step 2:

[1973] The server receives the message and uses a generative AI model to analyze the message content and assess its urgency and importance.

[1974] Step 3:

[1975] The server assigns a priority to the message based on the analysis results, categorizing it into high, medium, and low priority categories.

[1976] Step 4:

[1977] The server generates a dedicated notification for high-priority messages and sends it to the device, which displays a notification of the important message to the user.

[1978] Chat room summary

[1979] Processing Steps:

[1980] Step 1:

[1981] A user sends a message requesting a summary of the chat room contents. The terminal receives the request and sends it to the server.

[1982] Step 2:

[1983] The server receives the request, launches the generative AI model, and analyzes past messages in the specified chat room.

[1984] Step 3:

[1985] The server extracts key points from the analysis and creates a summary, including key progress, decisions, and next steps.

[1986] Step 4:

[1987] The server sends the created summary to the terminal, which displays the summary to the user.

[1988] Combining Emotion Engines

[1989] Processing Steps:

[1990] Step 1:

[1991] When a user sends a message, the device sends the message to the server, which receives the message and uses the emotion engine to analyze the emotion of the message.

[1992] Step 2:

[1993] The server receives the analysis results of the emotion engine and suggests or executes actions based on the recognized emotions. For example, if the user is feeling stressed, it generates an appropriate support message.

[1994] Step 3:

[1995] The server adjusts chat room suggestions and notification content based on the recognized emotion. For example, if the user is feeling stressed, chat room suggestions are adjusted to address issues that can be easily resolved.

[1996] Step 4:

[1997] The server sends the adjusted chat room suggestions and notification content to the terminal, which displays them to the user and prompts them to make a selection or confirm.

[1998] Examples:

[1999] Message Parsing:

[2000] When a user sends a message saying "New project progress report," the server suggests chat rooms related to "Project progress report" and "New project."

[2001] New chat room suggestions:

[2002] When a user submits a request to create a chat room for "Regular Marketing Team Meetings," the server checks to see if there is an existing "Marketing Team" chat room and makes a suggestion.

[2003] Message priority organization:

[2004] When a user receives a message saying "Please respond to an order from a client as soon as possible," the server analyzes the urgency of the message and issues a notification with high priority.

[2005] Emotion Engine:

[2006] If a user sends a message such as "This task is really difficult!", the emotion engine will recognize the stress and the server will suggest an appropriate support message.

[2007] Example 2

[2008] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2009] Current business chat tools make it difficult for users to efficiently manage messages and join or create new chat rooms. They also lack the functionality to quickly evaluate and notify the importance and urgency of received messages. Furthermore, functions such as message sentiment analysis and summary generation are inadequate. Therefore, there is a need to provide a stress-free communication environment for users.

[2010] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2011] In this invention, the server includes: means for analyzing messages received from a user; means for suggesting relevant chat room candidates based on the analysis results; means for notifying the user of the suggested chat room candidates; means for analyzing the sentiment of messages using a sentiment analysis engine and suggesting appropriate actions based on the analysis results; means for analyzing and setting the importance and priority of received messages; means for notifying the user of important messages based on the set priority; means for analyzing messages in a specified chat room and generating summaries; means for notifying the user of the generated summaries; means for analyzing messages using a generative AI model; and means for inputting prompts to the generative AI model to instruct analysis. This allows users to efficiently manage messages and join appropriate chat rooms or create new chat rooms. Furthermore, by quickly evaluating the importance and urgency of messages and performing sentiment analysis and summaries, a stress-free communication environment can be provided.

[2012] "User" means an individual or legal entity that uses the business communication tool to send or receive messages.

[2013] A "message" is data such as text, images, and audio that a user sends or receives through a business chat tool.

[2014] "Means of analysis" refers to the technology that analyzes the content of received messages and extracts keywords and important topics.

[2015] "Chat Room Suggestion" refers to a suggestion of a relevant existing or new chat room based on the analyzed content of the message.

[2016] "Means of notification" refers to technology that provides analysis results and notification content to users and encourages them to take the next action.

[2017] An "emotion analysis engine" refers to technology that analyzes the emotions contained in the content of a message and suggests appropriate actions based on the analysis results.

[2018] "Importance and priority" refers to the criteria for assessing and classifying the urgency and importance of received messages.

[2019] "Means for generating a summary" refers to a technology that analyzes past messages in a specified chat room, extracts key information, and creates a summary.

[2020] A "generative AI model" refers to a machine learning model that uses artificial intelligence technology to analyze messages and generate summaries.

[2021] A "prompt" refers to text that is entered to give specific instructions to a generative AI model.

[2022] The present invention provides a system that enables users to efficiently use business communication tools, and includes a chat management function that utilizes a generative AI model and an emotion engine. Specific embodiments for implementing the present invention will be described below.

[2023] Message analysis and chat room suggestions

[2024] 1. Message reception and analysis

[2025] A user uses a business chat tool to send a message such as "Report on the progress of a new project."

[2026] The terminal receives this message and sends it to the server.

[2027] The server launches a generative AI model (e.g., OpenAI's GPT-4) to analyze the message content. This analysis uses the prompt "Please extract keywords and topics from the following message." This results in the extraction of the keywords "new project," "progress," and "report."

[2028] 2. Chat room suggestions

[2029] The server generates appropriate chat room candidates based on the extracted keywords. For example, it compares the keywords with a list of existing chat rooms and suggests related chat rooms such as "project progress report" and "new project."

[2030] The server sends chat room candidates to the terminal.

[2031] The terminal displays chat room candidates to the user and prompts the user to select one.

[2032] Suggest and create new chat rooms

[2033] 1. Parsing chat room creation requests

[2034] A user enters a message stating that they want to create a new chat room, such as "Regular Marketing Team Meetings," and sends it.

[2035] The terminal receives the request and sends it to the server.

[2036] The server uses a generative AI model and prompts the user with the following sentence: "Analyze a new chat room request and extract relevant keywords." The server extracts keywords such as "marketing team" and "regular meeting" from the request.

[2037] 2. Comparison with existing chat rooms and proposals

[2038] The server compares the extracted keywords with the existing chat room list to check for overlapping content.

[2039] If the server has an existing chat room for "Marketing Team", it will suggest to the user, "Do you want to use the existing chat room?" If there is no overlap, it will suggest creating a new chat room.

[2040] The device displays the proposed results to the user, who can then choose to accept the proposal or create a new one.

[2041] Message priority organization and notification

[2042] 1. Message Reception and Priority Analysis

[2043] The user receives a message from a team member saying, "Please handle the client's order as soon as possible." The terminal receives this message and sends it to the server.

[2044] 2. Prioritization and Notifications

[2045] The server uses a generative AI model to analyze the message content by setting a prompt sentence: "Please rate the urgency and importance of this message." This determines the message to be of high urgency.

[2046] The server sets the message priority to "high" based on this result.

[2047] The server generates a dedicated notification for high-priority messages and sends it to the device. The device displays a notification of the important message to the user. The user checks the notification and responds promptly.

[2048] Chat room summary

[2049] 1. Processing Abstract Requests

[2050] A user requests a summary of the chat room contents by sending the message "Please give me a summary of the weekly chat room report." The terminal receives this request and sends it to the server.

[2051] 2. Generating and serving summaries

[2052] The server launches the generative AI model and uses the prompt, "Analyze the past messages in this chat room and summarize the key points." The server analyzes the past messages in the specified chat room and extracts key progress, decisions, next steps, etc.

[2053] The server creates a summary and sends it to the terminal, which displays the summary to the user, who reviews the summary and plans next steps.

[2054] Combining Emotion Engines

[2055] 1. Sentiment Analysis and Action

[2056] When a user sends or receives a message such as "This task is really difficult!", the emotion engine analyzes the emotion of the message. The server then suggests actions based on the results of this emotion analysis.

[2057] The server suggests appropriate support messages and resources based on the emotions it recognizes. Specifically, it generates support messages such as "Do you need additional resources for this task?"

[2058] The terminal displays a support message to the user, and the user requests resources as needed.

[2059] Through these processing steps, users can efficiently manage messages, join appropriate chat rooms, create new chat rooms, prioritize messages, generate summaries, and analyze sentiment, thereby providing a stress-free communication environment for users.

[2060] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2061] Message analysis and chat room suggestions

[2062] Step 1:

[2063] Receiving messages

[2064] A user types and sends a message via a business chat tool saying, "Report on the progress of a new project."

[2065] Input: User's message

[2066] Output: Request to send message to terminal

[2067] Step 2:

[2068] Message relay by terminal

[2069] The terminal transmits the message received from the user to the server.

[2070] Input: The user's sent message

[2071] Output: Message transfer request to server

[2072] Step 3:

[2073] Server parsing of messages

[2074] The server launches a generative AI model (e.g., GPT-4) and analyzes the message content using the prompt, "Please extract keywords and topics from the message below."

[2075] Input: Message received from the terminal, prompt text

[2076] Output: Extracted keywords "new project", "progress", "report"

[2077] Step 4:

[2078] Generate chat room candidates

[2079] The server compares the extracted keywords with a list of past chat rooms to generate highly relevant chat room candidates.

[2080] Input: Extracted keywords

[2081] Output: List of chat room candidates (e.g. "Project progress report", "New project")

[2082] Step 5:

[2083] Device notifications

[2084] The server transmits the generated chat room candidates to the terminal, and the terminal displays the chat room candidates to the user.

[2085] Input: Chat room candidate list

[2086] Output: Chat room suggestions displayed to the user

[2087] Suggest and create new chat rooms

[2088] Step 1:

[2089] Sending a chat room creation request

[2090] A user sends a message requesting the creation of a chat room called "Marketing Team Regular Meetings."

[2091] Input: User creation request message

[2092] Output: Request to send message to terminal

[2093] Step 2:

[2094] Terminal relays requests

[2095] The terminal transmits the request message received from the user to the server.

[2096] Input: User request message

[2097] Output: Request forwarded to server

[2098] Step 3:

[2099] Request analysis by the server

[2100] The server launches the generative AI model and analyzes the content of the request using the prompt "Analyze a new chat room request and extract relevant keywords."

[2101] Input: Request received from the terminal, prompt text

[2102] Output: Extracted keywords "marketing team" and "regular meeting"

[2103] Step 4:

[2104] Comparison with existing chat rooms

[2105] The server checks the extracted keywords against the existing chat room list to see if there are any overlaps.

[2106] Input: Extracted keywords

[2107] Output: Existing chat rooms

[2108] Step 5:

[2109] Proposal generation and notification

[2110] The server generates a proposal to create a new chat room or to merge with an existing chat room based on the request content and the comparison result, and sends it to the terminal. The terminal displays the proposal to the user.

[2111] Input: Request details, whether or not there is an existing chat room

[2112] Output: Proposal displayed to the user

[2113] Message priority organization and notification

[2114] Step 1:

[2115] Receiving messages

[2116] The user receives a message saying, "Please handle the order from the client as soon as possible." The terminal receives the message and sends it to the server.

[2117] Input: Incoming message

[2118] Output: Message transfer request to server

[2119] Step 2:

[2120] Message Priority Analysis

[2121] The server uses a generative AI model to set a prompt such as "Please rate the urgency and importance of this message" and analyze the message content.

[2122] Input: message, prompt

[2123] Output: Set priority (e.g. High)

[2124] Step 3:

[2125] Generate notifications based on priority

[2126] The server generates a dedicated notification for high-priority messages and sends it to the device, which displays a notification of the important message to the user.

[2127] Input: Set priority

[2128] Output: Important message notification to the user

[2129] Chat room summary

[2130] Step 1:

[2131] Submitting a Summary Request

[2132] The user sends a request saying, "Please send me a summary of the weekly chat room report." The device receives the request and forwards it to the server.

[2133] Input: User request message

[2134] Output: Request forwarded to server

[2135] Step 2:

[2136] Generate a summary

[2137] The server uses the generative AI model to set a prompt such as "Analyze the past messages in this chat room and summarize the important points," and analyzes the past messages in the specified chat room.

[2138] Input: Request, prompt, past message

[2139] Output: Generated summary

[2140] Step 3:

[2141] Provision to users

[2142] The server sends the generated summary to the terminal, which displays the summary to the user.

[2143] Input: Generated summary

[2144] Output: Summary displayed to the user

[2145] Combining Emotion Engines

[2146] Step 1:

[2147] Message sentiment analysis

[2148] When a user sends or receives a message such as "This task is really difficult!", the emotion engine analyzes the emotion of the message.

[2149] Input: Message sent or received

[2150] Output: Analysis results (e.g. stress, tension)

[2151] Step 2:

[2152] Suggestions for appropriate actions

[2153] Based on the results of the sentiment analysis, the server generates a support message asking, "Do you need additional resources for this task?" and sends it to the device. The device then displays the support message to the user.

[2154] Input: Sentiment analysis results

[2155] Output: Display support message to user

[2156] Through the above specific processing steps, users can efficiently manage messages and ensure smooth operation of the chat room. Furthermore, emotion analysis can reduce users' psychological burden and provide appropriate support.

[2157] (Application example 2)

[2158] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2159] Conventional business communication tools have limited functionality, such as message analysis and chat room suggestions, limiting the ways for users to quickly and efficiently obtain the information they need. Furthermore, systems for appropriately classifying message urgency and importance and for advanced communication are inadequate. In particular, systems requiring advanced operational management, such as autonomous vehicles, often require real-time emergency response and appropriate instructions based on emotion analysis, and existing systems have difficulty meeting these requirements.

[2160] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2161] In this invention, the server includes means for analyzing messages received from users, means for proposing highly relevant chat room candidates based on the analysis results, means for notifying users of the proposed chat room candidates, means for analyzing the sentiment of the messages, means for adjusting the chat room candidates based on the sentiment analysis results, and means for setting message priorities and generating notifications according to urgency, thereby enabling users to quickly and efficiently obtain necessary information and appropriately respond to emergencies and important messages.

[2162] "Analysis of messages received from users" is a process of automatically analyzing the contents of messages sent by users and extracting important keywords and contexts.

[2163] "Suggesting relevant chat room candidates" is a function that identifies and suggests appropriate chat rooms for the user to join based on the results of message analysis.

[2164] "Emotion analysis" is an analytical process for determining the emotional state of the sender and receiver from the content of a message.

[2165] "Adjusting chat room candidates" is a process of optimizing the list of chat rooms suggested to the user based on the results of sentiment analysis.

[2166] "Message priority setting" is a function that evaluates the importance and urgency of received messages and automatically sets the priority accordingly.

[2167] "Generating notifications according to urgency" is a function that sends special notifications to users for messages that are important and urgent based on the set priority.

[2168] "Analysis of chat room creation requests" is a process that automatically analyzes new chat room creation requests from users and understands their intent.

[2169] "Compare with existing chat rooms" refers to the process of comparing a new chat room creation request with existing chat rooms to determine if the request overlaps with an existing chat room.

[2170] "Proposal to create or merge a new chat room" is a function that suggests to the user to create a new chat room or merge with an existing chat room based on the analysis results.

[2171] "Quick suggestion of appropriate responses in emergencies" is a function that quickly suggests to users the actions and countermeasures required in emergencies.

[2172] As a mode for carrying out the present invention, an embodiment of a communication and operation management system for an autonomous driving vehicle will be described below.

[2173] The system analyzes messages received from users and suggests appropriate chat rooms based on the results of the analysis. It can also analyze the sentiment of messages, generate notifications based on urgency, and compare existing chat rooms.

[2174] Receiving and parsing messages

[2175] The server receives messages sent by users, which are then analyzed using a generative AI model (e.g., the Sentiment Analysis model from HuggingFace's transformers library) to extract important keywords and context and suggest appropriate chat rooms based on the content.

[2176] Emotion analysis

[2177] The server uses a generative AI model to analyze the sentiment of the message. Based on this analysis, it adjusts chat room suggestions and optimizes the suggestions as needed. For example, if a message is sent saying, "An accident has occurred. Immediate action is required," the server will determine this message as "negative" and suggest a chat room that requires a high level of urgency.

[2178] Prioritization and Notifications

[2179] The server classifies received messages based on importance and urgency, and generates special notifications based on the set priority and sends them to the user's device, allowing the user to quickly understand important messages and urgent actions.

[2180] Creating and comparing chat rooms

[2181] When a user requests to create a new chat room, the server analyzes the request and compares it with existing chat rooms. If there are no overlaps, the server proposes the creation of a new chat room, and if there are overlaps, it proposes merging. For example, if a request comes in to "report on the progress of a new project," the server checks whether there is an existing "project progress report" chat room and makes an appropriate proposal.

[2182] Specific examples

[2183] When an autonomous vehicle sends a message saying, "Left front tire pressure is low," the message is analyzed by a generative AI model. As a result, the message is determined to be "negative," a notification is sent to the maintenance team's chat room, and a prompt is generated: "New maintenance request: Left front tire pressure is low," suggesting an appropriate response.

[2184] Prompt Sentence Examples

[2185] A new maintenance request has arrived:

[2186] Vehicle ID: Vehicle1234

[2187] Message: Left front tire pressure low

[2188] In this way, the system of the present invention realizes efficient business communication by analyzing the user's messages in detail and making appropriate suggestions and notifications that take into account the user's emotions and urgency.

[2189] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2190] Step 1:

[2191] A user sends a message from a device inside an autonomous vehicle.

[2192] The user inputs a message and presses the send button to send it to the terminal. An input message might be something like "The air pressure in the left front tire is low." The output is the message data that was sent.

[2193] Step 2:

[2194] The terminal transfers the received message to the server.

[2195] When a terminal receives a message from a user, it sends the contents of the message to the server. The input is the received message data, and the output is the message data transferred to the server.

[2196] Step 3:

[2197] The server analyzes the message content using a generative AI model.

[2198] The server inputs the received message data into the generative AI model and performs an analysis to extract keywords and context. This analysis extracts important information. The input is the message data, and the output is the keywords and context information that are the analysis results.

[2199] Step 4:

[2200] The server performs sentiment analysis.

[2201] The server uses the generative AI model to analyze the sentiment of the message. The input is the analysis result from step 3, and the output is the analyzed sentiment data (e.g., negative or positive classification and its confidence score).

[2202] Step 5:

[2203] The server proposes chat room candidates based on the analysis results.

[2204] The server identifies relevant chat room candidates based on the message keywords and sentiment analysis results and generates a list. The input is the analysis results of steps 3 and 4, and the output is a list of chat room candidates.

[2205] Step 6:

[2206] The server notifies the terminal of chat room candidates.

[2207] The server sends the generated list of chat room candidates to the terminal and displays it to the user. The input is the list of chat room candidates, and the output is a notification displayed on the user's terminal.

[2208] Step 7:

[2209] The user selects a chat room.

[2210] The user selects the most suitable chat room from the chat room candidates displayed on the terminal. The input is the chat room candidate list displayed on the terminal, and the output is the selected chat room.

[2211] Step 8:

[2212] The server parses the request to create a new chat room.

[2213] When a user sends a request, the server receives it and analyzes the content using a generative AI model. The input is the request message from the user, and the output is the analyzed request data.

[2214] Step 9:

[2215] The server compares the new request with existing chat rooms.

[2216] The server compares the parsed request data with the existing chat room database to check for duplicates. The input is the parsed request data and existing chat room data, and the output is the presence or absence of duplicates and new proposed data.

[2217] Step 10:

[2218] The server will propose the creation or merging of new chat rooms.

[2219] Based on the comparison results, the server proposes a future action (creating a new chat room or merging into an existing chat room) to the user. The input is the comparison result data, and the output is a proposal notification.

[2220] Step 11:

[2221] The server prioritizes messages and generates notifications based on urgency.

[2222] The server evaluates the importance and urgency of messages and generates special notifications for high-priority messages. The input is the analysis results and importance rating data, and the output is the generated special notifications.

[2223] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2224] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2225] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2226] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2227] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2228] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2229] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2230] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2231] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2232] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2233] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2234] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2235] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2236] 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.

[2237] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2238] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2239] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2240] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2241] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2242] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2243] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2244] The following is further disclosed regarding the above embodiment.

[2245] (Claim 1)

[2246] means for analyzing messages received from users;

[2247] means for proposing highly relevant chat room candidates based on the analysis results;

[2248] means for notifying a user of the proposed chat room candidates;

[2249] A system including:

[2250] (Claim 2)

[2251] means for analyzing chat room creation requests from users;

[2252] A means for comparing the analysis result with existing chat rooms;

[2253] means for proposing the creation or merging of a new chat room based on the comparison result;

[2254] 10. The system of claim 1, comprising:

[2255] (Claim 3)

[2256] means for analyzing and setting the importance and priority of received messages;

[2257] means for notifying a user of an important message based on the set priority;

[2258] 10. The system of claim 1, comprising:

[2259] (Claim 4)

[2260] means for analyzing messages in a specified chat room, extracting important points, and generating a summary;

[2261] means for providing the generated summary to a user;

[2262] 10. The system of claim 1, comprising:

[2263] "Example 1"

[2264] (Claim 1)

[2265] means for analyzing messages received from users;

[2266] means for proposing highly relevant communication room candidates based on the analysis results;

[2267] means for notifying a user of the proposed communication room candidate;

[2268] A means to analyze message content using generative AI models and extract important keywords and topics;

[2269] means for generating an appropriate collaboration room based on the extracted information;

[2270] means for transmitting the generated proposal for the collaboration room to a user terminal and displaying the proposal;

[2271] A system including:

[2272] (Claim 2)

[2273] means for analyzing a collaboration room creation request from a user;

[2274] A means for comparing the analysis result with an existing collaboration room;

[2275] means for proposing the creation or merging of a new collaboration room based on the comparison result;

[2276] A means to analyze the request content using a generative AI model and extract relevant keywords;

[2277] means for comparing the extracted keywords with existing collaboration room information;

[2278] means for transmitting and displaying an appropriate suggestion to a user terminal based on the comparison result;

[2279] 10. The system of claim 1, comprising:

[2280] (Claim 3)

[2281] means for analyzing and setting the importance and priority of received messages;

[2282] means for notifying a user of an important message based on the set priority;

[2283] A means to determine the urgency and importance of messages using generative AI models;

[2284] means for prioritizing messages based on said determination and generating dedicated notifications for high priority messages;

[2285] means for transmitting and displaying the dedicated notification on a user terminal;

[2286] 10. The system of claim 1, comprising:

[2287] "Application Example 1"

[2288] (Claim 1)

[2289] means for analyzing messages received from users;

[2290] means for proposing highly relevant chat room candidates based on the analysis results;

[2291] means for notifying a user of the proposed chat room candidates;

[2292] A means for analyzing ...

Claims

1. means for analyzing messages received from users; means for proposing highly relevant chat room candidates based on the analysis results; means for notifying a user of the proposed chat room candidates; A system including:

2. means for analyzing chat room creation requests from users; A means for comparing the analysis result with existing chat rooms; means for proposing the creation or merging of a new chat room based on the comparison result; The system of claim 1 , comprising:

3. means for analyzing and setting the importance and priority of received messages; means for notifying a user of an important message based on the set priority; The system of claim 1 , comprising:

4. means for analyzing messages in a specified chat room, extracting important points, and generating a summary; means for providing the generated summary to a user; The system of claim 1 , comprising:

Images