system

Abstract

We provide the system. [Solution] An input means for receiving information from the user, A storage means for storing the received information in an information storage device, Information relevance evaluation means for analyzing the stored information and automatically retrieving other related information, A summary generation means for summarizing the analyzed information and converting it into a format that is easy for the user to understand, Output means for providing the summarized information and related information to the user, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, while a large amount of information is generated daily, it is difficult for individuals and organizations to effectively utilize ideas and make new creations. Under such circumstances, the lack of a system for efficiently accumulating, organizing, analyzing information, and creating new ideas based on it is an issue. In particular, a function for quickly evaluating the relevance of information, extracting important content, and presenting it to the user is required, but this is not fully realized by current technologies.

Means for Solving the Problems

[0005] This invention provides a system that receives information from users, effectively stores and classifies it, and evaluates the relevance of that information. Specifically, it supports the user's process of generating new ideas by automatically summarizing information and searching for related information. Furthermore, it embodies a system that can streamline the user's creative activities by summarizing information using natural language processing technology and providing it to the user in an optimal format.

[0006] A "user" is an entity that inputs information into a system and receives output from that system.

[0007] An "input method" is an interface designed to receive information from the user.

[0008] An "information storage device" is a database or storage device used to store information received from a user.

[0009] A "storage means" is a module that has the function of storing received information in an information storage device.

[0010] An "information relevance evaluation means" is a module that has the function of automatically searching for other related information based on stored information and analyzing its relationships.

[0011] A "summary generation means" is a module that has the function of summarizing received or stored information in order to convert the information into a format that is easy for the user to understand.

[0012] An "output means" is an interface for conveying summarized information and related information to the user.

[0013] An "information processing device" is a computer system used for inputting, storing, analyzing, and outputting information.

[0014] "Natural language processing technology" refers to computer technology used to understand, interpret, and generate human language.

Brief Description of the Drawings

[0015] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Modes for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

[0018] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0019] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

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

[0025] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0032] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0035] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0036] This invention is a system that supports the creation of new ideas by allowing users to input information using a terminal they have on hand, and then having a server receive, store, and analyze that information. Users input their ideas and notes into their terminal and send them to the server in a structured manner. The server stores this information in an information storage device and indexes it in a database to make it quickly accessible.

[0037] The server performs an information relevance assessment based on the input information and analyzes its relationships with other information stored in the database. This includes relationships based on the context and level of the information. Furthermore, the server utilizes natural language processing technology to generate a summary of the input information. This summary extracts the essence and is provided to the user in a format that can be understood quickly.

[0038] Furthermore, the server evaluates relevant information and combinations with other already stored information, suggesting new perspectives to the user. This allows users to construct new ideas and hypotheses they hadn't considered before, enabling them to think more efficiently and innovatively.

[0039] For example, when a user inputs information such as "ideas for a sales strategy for a new product," the server automatically references and analyzes similar past success stories and marketing methods, and proposes a new strategy that is useful to the user. In this way, the system of the present invention makes effective use of vast amounts of information and strongly supports the creative activities of users.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The user inputs information such as ideas and notes into the terminal in text format. The terminal formats the input information and prepares it for transmission to the server.

[0043] Step 2:

[0044] The device sends information to the server. The information is transferred to the server via an API using a secure communication protocol.

[0045] Step 3:

[0046] The server receives information sent from the terminal and immediately saves it to its storage device. During saving, metadata such as date, tags, and categories are attached to the information, and an index is created in the database.

[0047] Step 4:

[0048] The server automatically analyzes the stored information and uses information relevance evaluation tools to assess its relationship with other stored information. It searches for similar or related information through text mining and keyword matching.

[0049] Step 5:

[0050] The server generates a concise summary of the received information through a summary generation mechanism. Using natural language processing techniques, it extracts key points and saves them as a summary.

[0051] Step 6:

[0052] The server prepares data to suggest new ideas and perspectives to the user, based on the results and summaries of the information relevance assessment. This data is generated by utilizing similar past cases and patterns.

[0053] Step 7:

[0054] The terminal receives summaries and suggestions from the server and presents them to the user through an interface. The user can use this as a reference to generate new ideas or develop existing ones.

[0055] (Example 1)

[0056] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0057] In today's information society, it is difficult for users to generate new ideas from vast amounts of data. In particular, there is a lack of effective means to summarize information and appropriately present related information, creating a need for mechanisms that support users' creative thinking. Furthermore, existing methods make it difficult to accurately evaluate the relevance of information, and the provision of new perspectives is limited.

[0058] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0059] In this invention, the server includes communication means for receiving information from a user, recording means for storing the received information in a data storage device, and data evaluation means for analyzing the recorded information and automatically identifying other relevant information. This makes it possible to support the user's creative thinking and efficiently generate new ideas.

[0060] "Communication means" refers to technologies or devices used to provide an interface for receiving information from users and for transmitting data from a terminal to a server.

[0061] A "recording means" refers to a process or device for permanently storing received information, such as writing to a database or storage device.

[0062] "Data evaluation means" refers to methods or techniques for analyzing recorded information and automatically identifying other relevant information. This includes algorithms and criteria for determining the relevance of information.

[0063] "Information conversion means" refers to technologies or processes for summarizing analyzed information and converting it into a format that is easy for users to understand. Natural language processing technologies are an example of this.

[0064] "Information presentation means" refers to output interfaces or media for providing users with summarized information and related information.

[0065] A "perspective presentation method" is a technology or process that provides a new perspective tailored to a specified use, in order to support the user's creative thinking.

[0066] This invention is an information processing system designed to support users in generating ideas. Users first input new ideas or notes using their own terminal. Input is possible using a keyboard or voice input. The input information is then transmitted from the terminal to a server via the internet.

[0067] The server verifies the received information to ensure its format is correct before saving it to data storage. A database management system is used for data storage, with technologies such as PostgreSQL and MongoDB being applied.

[0068] After the information is stored, the server analyzes the relationships between the pieces of information. Here, it identifies related information using evaluation criteria and templates built into the information processing device. SpaCy and NLTK are often used as natural language processing libraries.

[0069] Next, the server uses a generative AI model that performs natural language processing to summarize the information. In this process, the essence of the information is extracted and converted into a form that users can quickly understand. Open-source natural language processing models are used for summary generation.

[0070] Ultimately, the server presents the user with new perspectives along with relevant information. Through this process, users can develop new ideas and hypotheses they hadn't considered before.

[0071] For example, if a user is thinking of ideas for a sales strategy for a new product, the server can analyze past marketing success stories and suggest useful strategies to the user. To achieve this, a prompt such as "Suggest an innovative application that utilizes artificial intelligence" is input to the generative AI model, and by analyzing the results, it is possible to present new ideas.

[0072] This system provides an effective means of generating new ideas based on vast amounts of data in today's information society.

[0073] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0074] Step 1:

[0075] Users input ideas and notes using their own devices. Specifically, they might type "ideas regarding a sales strategy for a new product" using the keyboard. The entered information is then formatted by the device into JSON or XML format and prepared for transmission to the server. The input data is structured text data.

[0076] Step 2:

[0077] The server receives information sent from the terminal. First, the server checks the format of the received data to ensure there are no defects. This check is performed using a script such as Python. After verification, the data is registered in the database. The input is structured data, and the output returns a success status.

[0078] Step 3:

[0079] Based on the stored information, the server analyzes its relationships with other information in the database. This process uses spaCy as a natural language processing library to perform classification and extraction, and calculates a relevance score. The input is information stored in an existing database, and the output is a list of highly similar information.

[0080] Step 4:

[0081] The server uses a generative AI model to summarize relevant information. Specifically, it takes prompts such as "Propose an innovative application that utilizes artificial intelligence" as input to the AI ​​model and extracts key points in a short amount of time. The input is a list of highly relevant information, and the output provides a concise summary.

[0082] Step 5:

[0083] The server generates new suggestions for the user based on the summary results. It extracts past success stories and marketing methods from a vast amount of data, providing new strategic perspectives. The input is the summary results and related information, and the output is concrete suggestions that stimulate the user's creative activity.

[0084] (Application Example 1)

[0085] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0086] Content providers face the challenge of effectively utilizing existing information and trends to gain new insights and ideas when creating new content. In particular, quickly finding useful information from a vast amount of data and using it to gain new perspectives requires time and effort.

[0087] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0088] In this invention, the server includes input means for receiving information from a user, storage means for storing the received information in an information storage device, information relevance evaluation means for analyzing the stored information and automatically searching for other related information, summary generation means for summarizing the analyzed information and converting it into a format that is easy for the user to understand, and new suggestion generation means for generating new insights for content providers to create new content. This enables content providers to effectively obtain new ideas and perspectives and efficiently create innovative content.

[0089] A "user" refers to a person who uses this system to input information and engage in creative activities.

[0090] An "information storage device" is a device that stores information received from users in a database format and manages it so that it can be accessed quickly later.

[0091] An "information relevance evaluation means" is a processing means that analyzes stored information and automatically explores its relationships with other information.

[0092] A "summary generation method" is a means that uses natural language processing technology to concisely summarize information entered by a user and convert it into an easily understandable format.

[0093] A "new proposal generation tool" is a tool that provides new insights for content providers to create new content based on analyzed and related information.

[0094] An embodiment of the present invention is a system consisting of a user, a terminal, and a server.

[0095] Users input information for creative activities using devices such as smartphones or smart glasses. The input information is recorded on the device in text or audio format. The device then transmits this information to a server via the internet.

[0096] The server stores the received information in a cloud-based database and manages it in an indexed format by an information storage device. The server is equipped with either Python's NLTK or spaCy as a natural language processing library, which is used to summarize the information.

[0097] The information relevance evaluation means automatically searches for the relationship between the received information and other information in the database. This utilizes existing templates or detection criteria within the information processing device. Once relevant information is found, the server uses a generative AI model to generate suggestions from the novel suggestion generation means.

[0098] The device displays summary information and new insights sent from the server to the user in a visual format. This allows the user to efficiently acquire new content ideas.

[0099] For example, if a user uses the prompt "I'm thinking of ideas for a new YouTube® video about environmental protection," the server can analyze the accumulated environmental information and, based on the results, suggest new ideas such as "plan a viewer-participation challenge event and video their efforts."

[0100] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0101] Step 1:

[0102] Users input information using smartphones or smart glasses. The input information is in text or audio format and relates to creative content such as ideas and notes. This information is temporarily stored on the device.

[0103] Step 2:

[0104] The terminal transmits the entered information to the server via the internet. The transmitted data is formatted as text and securely delivered to the server using a data transfer protocol.

[0105] Step 3:

[0106] The server stores the received text in a cloud-based database. The data is indexed by an information storage device and managed to facilitate searching and access. A database management system (e.g., MySQL®) is used for the storage process.

[0107] Step 4:

[0108] The server uses a natural language processing library (e.g., Python's NLTK or spaCy) to generate a summary of the received information. This process extracts the subject matter of the text and summarizes the main points into a few sentences. The summary results are stored in a database for later use.

[0109] Step 5:

[0110] The information relevance assessment tool uses an indexed database to search for other related information. Templates or detection criteria are used for the search. The server finds relevant information and stores it along with a summary.

[0111] Step 6:

[0112] The generative AI model generates new suggestions based on the analyzed and related information. The server uses this model to build new insights and ideas for content providers. The output suggestions are specific approaches and insights that help users create content.

[0113] Step 7:

[0114] The terminal displays summary information and new suggestions sent from the server on its screen. Users can visually review and incorporate this information. The display is designed with a user-friendly interface in mind.

[0115] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0116] This invention relates to a system that recognizes the user's emotional state using an emotion engine based on user input information and presents information accordingly. The user inputs information through a terminal, providing ideas and opinions to the system. The input information is transmitted from the terminal to a server and stored in an information storage device. During this process, the information is tagged and stored in a database.

[0117] The server analyzes the input information and uses information relevance evaluation tools to extract other relevant information. The results of this analysis form the basis for facilitating the creation of meaningful new ideas for the user. Furthermore, the input information is summarized using natural language processing technology and presented in an easily understandable format for the user.

[0118] The emotion engine uses natural language processing technology to analyze the user's emotional state from their input and appropriately selects the information to present based on that state. For example, if the user is feeling stressed, the system can present more supportive messages or ideas. In this way, by providing information that matches the user's emotions, the system maximizes the utilization of that information.

[0119] As a concrete example, suppose a user enters a "problem related to project progress," and the emotion engine recognizes the user's anxiety. In this case, the server proposes solutions based on similar past cases and provides advice to the user through the terminal. This proposal is tailored to the user's emotional state and helps them approach problem-solving in a more relaxed manner.

[0120] This invention provides a system that more effectively supports users' creative activities through an information presentation function that incorporates emotions.

[0121] The following describes the processing flow.

[0122] Step 1:

[0123] The user inputs ideas and notes into the device. The device then formats this information and prepares it for transmission to the server.

[0124] Step 2:

[0125] The terminal sends the entered information to the server. This information is transferred securely using an API.

[0126] Step 3:

[0127] The server stores the received information in its data storage device. During storage, metadata such as tags and dates are added to the database.

[0128] Step 4:

[0129] The server analyzes the stored information using information relevance evaluation tools. This analysis evaluates the relevance of the information to other information, and similar or related information is automatically searched for.

[0130] Step 5:

[0131] The emotion engine analyzes input information on the server using natural language processing technology to recognize the user's emotional state. This analysis enables the provision of information based on the user's emotions.

[0132] Step 6:

[0133] The server generates a summary of the received information using a summary generation mechanism. The summarized information is output in a format optimized for the user.

[0134] Step 7:

[0135] The server fine-tunes the information presented based on the emotion engine's recognition results. If the analysis indicates that the user is experiencing stress, it prepares information that includes gentler language and encouraging messages.

[0136] Step 8:

[0137] The device receives summaries and sentiment-based suggestions from the server and presents them to the user. This allows the user to decide on their next action based on information that suits their situation and emotions.

[0138] (Example 2)

[0139] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0140] In processing and presenting information, there is a need for flexible information delivery that takes into account the user's emotional state. Existing information presentation systems struggle to dynamically adjust information in response to user emotions, making improving the user experience a challenge. In particular, when users are experiencing stress or anxiety, there is a need to provide more appropriate information and support.

[0141] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0142] In this invention, the server includes an input means for receiving information from a user, an information relevance evaluation means for analyzing the received information and searching for related information, and a summary generation means for summarizing the information using natural language processing technology and generating suggestions using an AI model. This makes it possible to provide information that is tailored to the user's emotional state.

[0143] An "input means" is a device or mechanism for receiving information from a user and incorporating it into the system.

[0144] An "information storage device" is a device that stores received information and keeps it in a state where it can be accessed as needed.

[0145] "Storage means" refers to a function or process for storing received information in an information storage device.

[0146] "Information relevance evaluation means" refers to a mechanism or procedure used to analyze stored information and automatically retrieve other related information.

[0147] A "summary generation means" is a technique or method for summarizing analyzed information and converting it into a short, concise form.

[0148] "Output means" refers to a device or configuration for providing summarized information and related information to the user.

[0149] "Emotional analysis means" refers to a procedure or mechanism for analyzing a user's emotional state from their input information and selecting appropriate information based on that emotion.

[0150] A "generative AI model" is a model that uses machine learning and artificial intelligence technologies to generate suggestions and information based on prompt text.

[0151] A "prompt sentence" is a sentence containing instructions or questions that is input into a generative AI model, and it functions as a trigger for information generation.

[0152] This invention is an information presentation system that takes into account the user's emotional state. This system transmits information entered by the user via a terminal to a server, which then analyzes, stores, summarizes, and performs sentiment analysis on the received information. By utilizing appropriate hardware and software at each stage, the system improves the user experience.

[0153] The server uses information storage devices and databases to store and manage input information. The input information is tagged and, after storage, analyzed by an information relevance evaluation system. This system extracts relevant information by comparing it with existing information in the database.

[0154] In addition, the server uses natural language processing technology and a summary generation mechanism to summarize the input information. This allows the user to receive concise and easy-to-understand information. The sentiment analysis mechanism uses a dedicated sentiment engine to determine the user's emotional state. This analysis result is used to select the information to be presented in subsequent steps.

[0155] For example, if a user enters their anxieties about being the leader of a new project into the terminal, the server will present past success stories and project management tips. Using a generative AI model, it is possible to generate specific suggestions based on the prompt text.

[0156] For example, if the user enters the prompt message, "I'm worried because the project is behind schedule. Please tell me what I can do to improve it," the system can provide information that will alleviate the user's anxiety.

[0157] In this way, the present invention makes it possible to more effectively support the user's creative activities through an information presentation function that incorporates emotions.

[0158] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0159] Step 1:

[0160] The user inputs information using a terminal. Specifically, the user enters a message in text format and sends it to the server via a send button or similar. The input data is text information including the user's issues and opinions. The output is the data sent to the server.

[0161] Step 2:

[0162] The server stores the information received from the terminal in its information storage device. This process temporarily holds the received information in memory and prepares it for permanent storage in the database. During this process, the information is tagged based on categories and keywords. The input is the user information sent in step 1, and the output is the tagged information stored in the database.

[0163] Step 3:

[0164] The server analyzes the stored information using information relevance evaluation tools. Specifically, it compares it with existing information in the database and searches for and extracts relevant information. In this process, relevant information is identified based on similar keywords and past cases. The input is the information stored in step 2, and the output is the extracted relevant information.

[0165] Step 4:

[0166] The server utilizes natural language processing technology to summarize information using a summary generation mechanism. This process involves shortening long texts and converting them into an easily understandable format. Using code and algorithms, it extracts key points and creates a summary. The input is the relevant information from step 3, and the output is the summarized information.

[0167] Step 5:

[0168] The server uses an emotion engine to analyze the user's emotional state. It analyzes the user's text data using natural language processing techniques to identify emotional states (e.g., anxiety, joy). Based on the emotion analysis results, more supportive information is selected. The input is user information from step 1, and the output is the analyzed emotional state.

[0169] Step 6:

[0170] The server uses a generative AI model to generate suggestions based on the prompt text, selecting and presenting appropriate information to the user. Specifically, the prompt text is input into the model, and individually customized suggestions are generated. The results are displayed to the user via the terminal. The input is the sentiment analysis results from step 5 and the summary information from step 4, and the output is the generated suggestions.

[0171] (Application Example 2)

[0172] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0173] Modern information distribution systems face the challenge of providing content and information appropriately tailored to the user's emotional state. In particular, amidst the vast amount of information available, providing information that considers the individual user's emotional state is crucial for improving the user experience. Therefore, there is a need to realize a system that analyzes the user's emotional state and provides optimal content accordingly.

[0174] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0175] In this invention, the server includes an input means for receiving information from a user, a storage means for storing the received information in an information storage device, and an emotion analysis means for analyzing the user's emotional state and selecting content to be provided based on that state. This makes it possible to provide appropriate information according to the user's emotional state.

[0176] "Input means" refers to a device or module provided for receiving information from a user.

[0177] "Storage means" refers to information storage devices and related technologies for storing received information.

[0178] "Information relevance evaluation means" refers to a process and apparatus for analyzing stored information and automatically retrieving and evaluating other related information.

[0179] A "summary generation method" is a natural language processing-based technology that summarizes analyzed information and converts it into a format that is easy for users to understand.

[0180] "Emotional analysis means" refers to a technology or device that analyzes the emotional state from the user's input information and selects content to provide based on that state.

[0181] "Output means" refers to a device or method provided for delivering optimized information to the user.

[0182] The system for realizing this invention consists of a user, a terminal, and a server. The user can input information into the system using the terminal. The input information is stored in an information storage device via a storage means.

[0183] Upon receiving input information, the server automatically searches for relevant information using an information relevance evaluation tool and analyzes the user's emotional state from the information using an emotion analysis tool. Specifically, it uses the Google® Cloud Natural Language API to perform emotion analysis on text. Based on these results, it selects content best suited to the user's emotions and searches for the corresponding information in databases such as Firebase. This information is then converted into a format easily understood by the user by a summarization generation tool.

[0184] The terminal receives information from the server and presents it to the user via an output device. This presentation method is adjusted as needed based on the user's current emotional state. For example, in situations where the user wants to relax, soothing music or nature videos are often recommended.

[0185] For example, if a user inputs "I'm tired today," the server uses emotion analysis to detect an emotional state that seeks "relaxation," selects an appropriate video, and provides it to the user. In this process, by using a prompt message in the generative AI model such as, "If the user inputs 'I'm tired today,' please output specific content examples based on the emotion analysis results, what kind of content should be suggested?", effective information provision can be achieved.

[0186] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0187] Step 1:

[0188] The user enters information using the device. This input is done via keyboard or voice recognition and is saved as text data on the device. For example, if the user enters "I'm tired today," this text data is saved on the device.

[0189] Step 2:

[0190] The terminal sends the entered text data to the server. During this process, the terminal securely transmits the data to the server via network communication. The server stores the received data in its information storage device.

[0191] Step 3:

[0192] The server analyzes the stored text data using information relevance assessment tools. This analysis retrieves relevant information using the Google Cloud Natural Language API and performs sentiment analysis. The result of the analysis is that the user is in an emotional state of needing "relaxation."

[0193] Step 4:

[0194] Based on the sentiment analysis results, the server selects content related to "relaxation" from the Firebase database. The selected information is summarized in the most appropriate format, often including links to nature videos or healing music.

[0195] Step 5:

[0196] The server sends summarized information to the terminal, which then presents it to the user. The information is displayed in a user-friendly interface; for example, if it includes a video link, a play button will be displayed.

[0197] Step 6:

[0198] Users use the information displayed on their device to select and view the desired content. Viewing the content allows users to relax and feel satisfied with how they receive the information.

[0199] In this process, the prompt "If the user enters 'I'm tired today,' please output specific content examples based on the sentiment analysis results, and provide the most appropriate information" is used through the generating AI model.

[0200] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0201] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0202] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0203] [Second Embodiment]

[0204] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0205] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0206] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0207] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0208] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0209] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0210] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0211] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0212] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0213] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0214] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0215] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0216] This invention is a system that supports the creation of new ideas by allowing users to input information using a terminal they have on hand, and then having a server receive, store, and analyze that information. Users input their ideas and notes into their terminal and send them to the server in a structured manner. The server stores this information in an information storage device and indexes it in a database to make it quickly accessible.

[0217] The server performs an information relevance assessment based on the input information and analyzes its relationships with other information stored in the database. This includes relationships based on the context and level of the information. Furthermore, the server utilizes natural language processing technology to generate a summary of the input information. This summary extracts the essence and is provided to the user in a format that can be understood quickly.

[0218] Furthermore, the server evaluates relevant information and combinations with other already stored information, suggesting new perspectives to the user. This allows users to construct new ideas and hypotheses they hadn't considered before, enabling them to think more efficiently and innovatively.

[0219] For example, when a user inputs information such as "ideas for a sales strategy for a new product," the server automatically references and analyzes similar past success stories and marketing methods, and proposes a new strategy that is useful to the user. In this way, the system of the present invention makes effective use of vast amounts of information and strongly supports the creative activities of users.

[0220] The following describes the processing flow.

[0221] Step 1:

[0222] The user inputs information such as ideas and notes into the terminal in text format. The terminal formats the input information and prepares it for transmission to the server.

[0223] Step 2:

[0224] The terminal sends information to the server. The information is transferred to the server via an API using a secure communication protocol.

[0225] Step 3:

[0226] The server receives information sent from the terminal and immediately saves it to its storage device. During saving, metadata such as date, tags, and categories are attached to the information, and an index is created in the database.

[0227] Step 4:

[0228] The server automatically analyzes the stored information and uses information relevance evaluation tools to assess its relationship with other stored information. It searches for similar or related information through text mining and keyword matching.

[0229] Step 5:

[0230] The server generates a concise summary of the received information through a summary generation mechanism. Using natural language processing techniques, it extracts key points and saves them as a summary.

[0231] Step 6:

[0232] The server prepares data to suggest new ideas and perspectives to the user, based on the results and summaries of the information relevance assessment. This data is generated by utilizing similar past cases and patterns.

[0233] Step 7:

[0234] The terminal receives summaries and suggestions from the server and presents them to the user through an interface. The user can use this as a reference to generate new ideas or develop existing ones.

[0235] (Example 1)

[0236] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0237] In today's information society, it is difficult for users to generate new ideas from vast amounts of data. In particular, there is a lack of effective means to summarize information and appropriately present related information, creating a need for mechanisms that support users' creative thinking. Furthermore, existing methods make it difficult to accurately evaluate the relevance of information, and the provision of new perspectives is limited.

[0238] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0239] In this invention, the server includes communication means for receiving information from a user, recording means for storing the received information in a data storage device, and data evaluation means for analyzing the recorded information and automatically identifying other relevant information. This makes it possible to support the user's creative thinking and efficiently generate new ideas.

[0240] "Communication means" refers to technologies or devices used to provide an interface for receiving information from users and for transmitting data from a terminal to a server.

[0241] A "recording means" refers to a process or device for permanently storing received information, such as writing to a database or storage device.

[0242] "Data evaluation means" refers to methods or techniques for analyzing recorded information and automatically identifying other relevant information. This includes algorithms and criteria for determining the relevance of information.

[0243] "Information conversion means" refers to technologies or processes for summarizing analyzed information and converting it into a format that is easy for users to understand. Natural language processing technologies are an example of this.

[0244] "Information presentation means" refers to output interfaces or media for providing users with summarized information and related information.

[0245] A "perspective presentation method" is a technology or process that provides a new perspective tailored to a specified use, in order to support the user's creative thinking.

[0246] This invention is an information processing system designed to support users in generating ideas. Users first input new ideas or notes using their own terminal. Input is possible using a keyboard or voice input. The input information is then transmitted from the terminal to a server via the internet.

[0247] The server verifies the received information to ensure its format is correct before saving it to data storage. A database management system is used for data storage, with technologies such as PostgreSQL and MongoDB being applied.

[0248] After the information is stored, the server analyzes the relationships between the pieces of information. Here, it identifies related information using evaluation criteria and templates built into the information processing device. SpaCy and NLTK are often used as natural language processing libraries.

[0249] Next, the server uses a generative AI model that performs natural language processing to summarize the information. In this process, the essence of the information is extracted and converted into a form that users can quickly understand. Open-source natural language processing models are used for summary generation.

[0250] Ultimately, the server presents the user with new perspectives along with relevant information. Through this process, users can develop new ideas and hypotheses they hadn't considered before.

[0251] For example, if a user is thinking of ideas for a sales strategy for a new product, the server can analyze past marketing success stories and suggest useful strategies to the user. To achieve this, a prompt such as "Suggest an innovative application that utilizes artificial intelligence" is input to the generative AI model, and by analyzing the results, it is possible to present new ideas.

[0252] This system provides an effective means of generating new ideas based on vast amounts of data in today's information society.

[0253] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0254] Step 1:

[0255] Users input ideas and notes using their own devices. Specifically, they might type "ideas regarding a sales strategy for a new product" using the keyboard. The entered information is then formatted by the device into JSON or XML format and prepared for transmission to the server. The input data is structured text data.

[0256] Step 2:

[0257] The server receives information sent from the terminal. First, the server checks the format of the received data to ensure there are no defects. This check is performed using a script such as Python. After verification, the data is registered in the database. The input is structured data, and the output returns a success status.

[0258] Step 3:

[0259] Based on the stored information, the server analyzes its relationships with other information in the database. This process uses spaCy as a natural language processing library to perform classification and extraction, and calculates a relevance score. The input is information stored in an existing database, and the output is a list of highly similar information.

[0260] Step 4:

[0261] The server uses a generative AI model to summarize relevant information. Specifically, it takes prompts such as "Propose an innovative application that utilizes artificial intelligence" as input to the AI ​​model and extracts key points in a short amount of time. The input is a list of highly relevant information, and the output provides a concise summary.

[0262] Step 5:

[0263] The server generates new suggestions for the user based on the summary results. It extracts past success stories and marketing methods from a vast amount of data, providing new strategic perspectives. The input is the summary results and related information, and the output is concrete suggestions that stimulate the user's creative activity.

[0264] (Application Example 1)

[0265] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0266] Content providers face the challenge of effectively utilizing existing information and trends to gain new insights and ideas when creating new content. In particular, quickly finding useful information from a vast amount of data and using it to gain new perspectives requires time and effort.

[0267] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0268] In this invention, the server includes input means for receiving information from a user, storage means for storing the received information in an information storage device, information relevance evaluation means for analyzing the stored information and automatically searching for other related information, summary generation means for summarizing the analyzed information and converting it into a format that is easy for the user to understand, and new suggestion generation means for generating new insights for content providers to create new content. This enables content providers to effectively obtain new ideas and perspectives and efficiently create innovative content.

[0269] A "user" refers to a person who uses this system to input information and engage in creative activities.

[0270] An "information storage device" is a device that stores information received from users in a database format and manages it so that it can be accessed quickly later.

[0271] An "information relevance evaluation means" is a processing means that analyzes stored information and automatically explores its relationships with other information.

[0272] A "summary generation method" is a means that uses natural language processing technology to concisely summarize information entered by a user and convert it into an easily understandable format.

[0273] A "new proposal generation tool" is a tool that provides new insights for content providers to create new content based on analyzed and related information.

[0274] An embodiment of the present invention is a system consisting of a user, a terminal, and a server.

[0275] Users input information for creative activities using devices such as smartphones or smart glasses. The input information is recorded on the device in text or audio format. The device then transmits this information to a server via the internet.

[0276] The server stores the received information in a cloud-based database and manages it in an indexed format by an information storage device. The server is equipped with either Python's NLTK or spaCy as a natural language processing library, which is used to summarize the information.

[0277] The information relevance evaluation means automatically searches for the relationship between the received information and other information in the database. This utilizes existing templates or detection criteria within the information processing device. Once relevant information is found, the server uses a generative AI model to generate suggestions from the novel suggestion generation means.

[0278] The device displays summary information and new insights sent from the server to the user in a visual format. This allows the user to efficiently acquire new content ideas.

[0279] For example, if a user uses the prompt "I'm thinking of ideas for a new YouTube video about environmental protection," the server can analyze the accumulated environmental information and, based on the results, suggest new ideas such as "plan a viewer-participation challenge event and video their efforts."

[0280] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0281] Step 1:

[0282] Users input information using smartphones or smart glasses. The input information is in text or audio format and relates to creative content such as ideas and notes. This information is temporarily stored on the device.

[0283] Step 2:

[0284] The terminal sends the input information to the server via the Internet. The data to be sent is formatted as text and securely transmitted to the server using a data transfer protocol.

[0285] Step 3:

[0286] The server stores the received text in a database on the cloud. The data is indexed by an information storage device and managed to facilitate searching and access. A database management system (e.g., MySQL) is used for the storage process.

[0287] Step 4:

[0288] The server uses a natural language processing library (e.g., NLTK or spaCy for Python) to generate a summary of the received information. In this process, the theme of the text is extracted and the main points are summarized into a few sentences. The summary result is stored in the database for later use.

[0289] Step 5:

[0290] The information relevance evaluation means uses the indexed database to search for other relevant information. Templates or detection criteria are used for the search. The server finds relevant information and stores that information together with the summary.

[0291] Step 6:

[0292] The generative AI model generates new proposals based on the analyzed information and related information. The server uses this model to construct new suggestions and ideas for content providers. The output proposals are specific approaches and insights useful for the user's content creation.

[0293] Step 7:

[0294] The terminal displays summary information and new suggestions sent from the server on its screen. Users can visually review and incorporate this information. The display is designed with a user-friendly interface in mind.

[0295] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0296] This invention relates to a system that recognizes the user's emotional state using an emotion engine based on user input information and presents information accordingly. The user inputs information through a terminal, providing ideas and opinions to the system. The input information is transmitted from the terminal to a server and stored in an information storage device. During this process, the information is tagged and stored in a database.

[0297] The server analyzes the input information and uses information relevance evaluation tools to extract other relevant information. The results of this analysis form the basis for facilitating the creation of meaningful new ideas for the user. Furthermore, the input information is summarized using natural language processing technology and presented in an easily understandable format for the user.

[0298] The emotion engine uses natural language processing technology to analyze the user's emotional state from their input and appropriately selects the information to present based on that state. For example, if the user is feeling stressed, the system can present more supportive messages or ideas. In this way, by providing information that matches the user's emotions, the system maximizes the utilization of that information.

[0299] As a specific example, assume that when a user enters "problems regarding project progress", the emotion engine recognizes the user's anxiety. In this case, the server proposes a solution based on past similar cases and provides advice to the user through the terminal. This proposal is tailored to the user's emotional state and serves as assistance for the user to approach problem-solving in a more relaxed manner.

[0300] The present invention provides a system that more effectively supports the creative activities of users through an information presentation function incorporating emotions.

[0301] The processing flow will be described below.

[0302] Step 1:

[0303] The user inputs ideas and memos into the terminal. The terminal formats this information and prepares to send it to the server.

[0304] Step 2:

[0305] The terminal sends the input information to the server. At this time, the information is securely transferred using the API.

[0306] Step 3:

[0307] The server saves the received information in the information storage device. When saving, metadata such as tags and dates are assigned to the database.

[0308] Step 4:

[0309] The server analyzes the saved information using the information relevance evaluation means. In this analysis, the relevance with other information is evaluated, and similar or related information is automatically searched.

[0310] Step 5:

[0311] The emotion engine analyzes input information on the server using natural language processing technology to recognize the user's emotional state. This analysis enables the provision of information based on the user's emotions.

[0312] Step 6:

[0313] The server generates a summary of the received information using a summary generation mechanism. The summarized information is output in a format optimized for the user.

[0314] Step 7:

[0315] The server fine-tunes the information presented based on the emotion engine's recognition results. If the analysis indicates that the user is experiencing stress, it prepares information that includes gentler language and encouraging messages.

[0316] Step 8:

[0317] The device receives summaries and sentiment-based suggestions from the server and presents them to the user. This allows the user to decide on their next action based on information that suits their situation and emotions.

[0318] (Example 2)

[0319] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0320] In processing and presenting information, there is a need for flexible information delivery that takes into account the user's emotional state. Existing information presentation systems struggle to dynamically adjust information in response to user emotions, making improving the user experience a challenge. In particular, when users are experiencing stress or anxiety, there is a need to provide more appropriate information and support.

[0321] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0322] In this invention, the server includes an input means for receiving information from a user, an information relevance evaluation means for analyzing the received information and searching for related information, and a summary generation means for summarizing the information using natural language processing technology and generating suggestions using an AI model. This makes it possible to provide information that is tailored to the user's emotional state.

[0323] An "input means" is a device or mechanism for receiving information from a user and incorporating it into the system.

[0324] An "information storage device" is a device that stores received information and keeps it in a state where it can be accessed as needed.

[0325] "Storage means" refers to a function or process for storing received information in an information storage device.

[0326] "Information relevance evaluation means" refers to a mechanism or procedure used to analyze stored information and automatically retrieve other related information.

[0327] A "summary generation means" is a technique or method for summarizing analyzed information and converting it into a short, concise form.

[0328] "Output means" refers to a device or configuration for providing summarized information and related information to the user.

[0329] "Emotional analysis means" refers to a procedure or mechanism for analyzing a user's emotional state from their input information and selecting appropriate information based on that emotion.

[0330] A "generative AI model" is a model that uses machine learning and artificial intelligence technologies to generate suggestions and information based on prompt text.

[0331] A "prompt sentence" is a sentence containing instructions or questions that is input into a generative AI model, and it functions as a trigger for information generation.

[0332] This invention is an information presentation system that takes into account the user's emotional state. This system transmits information entered by the user via a terminal to a server, which then analyzes, stores, summarizes, and performs sentiment analysis on the received information. By utilizing appropriate hardware and software at each stage, the system improves the user experience.

[0333] The server uses information storage devices and databases to store and manage input information. The input information is tagged and, after storage, analyzed by an information relevance evaluation system. This system extracts relevant information by comparing it with existing information in the database.

[0334] In addition, the server uses natural language processing technology and a summary generation mechanism to summarize the input information. This allows the user to receive concise and easy-to-understand information. The sentiment analysis mechanism uses a dedicated sentiment engine to determine the user's emotional state. This analysis result is used to select the information to be presented in subsequent steps.

[0335] For example, if a user enters their anxieties about being the leader of a new project into the terminal, the server will present past success stories and project management tips. Using a generative AI model, it is possible to generate specific suggestions based on the prompt text.

[0336] For example, if the user enters the prompt message, "I'm worried because the project is behind schedule. Please tell me what I can do to improve it," the system can provide information that will alleviate the user's anxiety.

[0337] In this way, the present invention makes it possible to more effectively support the user's creative activities through an information presentation function that incorporates emotions.

[0338] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0339] Step 1:

[0340] The user inputs information using a terminal. Specifically, the user enters a message in text format and sends it to the server via a send button or similar. The input data is text information including the user's issues and opinions. The output is the data sent to the server.

[0341] Step 2:

[0342] The server stores the information received from the terminal in its information storage device. This process temporarily holds the received information in memory and prepares it for permanent storage in the database. During this process, the information is tagged based on categories and keywords. The input is the user information sent in step 1, and the output is the tagged information stored in the database.

[0343] Step 3:

[0344] The server analyzes the stored information using information relevance evaluation tools. Specifically, it compares it with existing information in the database and searches for and extracts relevant information. In this process, relevant information is identified based on similar keywords and past cases. The input is the information stored in step 2, and the output is the extracted relevant information.

[0345] Step 4:

[0346] The server utilizes natural language processing technology to summarize information using a summary generation mechanism. This process involves shortening long texts and converting them into an easily understandable format. Using code and algorithms, it extracts key points and creates a summary. The input is the relevant information from step 3, and the output is the summarized information.

[0347] Step 5:

[0348] The server uses an emotion engine to analyze the user's emotional state. It analyzes the user's text data using natural language processing techniques to identify emotional states (e.g., anxiety, joy). Based on the emotion analysis results, more supportive information is selected. The input is user information from step 1, and the output is the analyzed emotional state.

[0349] Step 6:

[0350] The server uses a generative AI model to generate suggestions based on the prompt text, selecting and presenting appropriate information to the user. Specifically, the prompt text is input into the model, and individually customized suggestions are generated. The results are displayed to the user via the terminal. The input is the sentiment analysis results from step 5 and the summary information from step 4, and the output is the generated suggestions.

[0351] (Application Example 2)

[0352] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0353] Modern information distribution systems face the challenge of providing content and information appropriately tailored to the user's emotional state. In particular, amidst the vast amount of information available, providing information that considers the individual user's emotional state is crucial for improving the user experience. Therefore, there is a need to realize a system that analyzes the user's emotional state and provides optimal content accordingly.

[0354] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0355] In this invention, the server includes an input means for receiving information from a user, a storage means for storing the received information in an information storage device, and an emotion analysis means for analyzing the user's emotional state and selecting content to be provided based on that state. This makes it possible to provide appropriate information according to the user's emotional state.

[0356] "Input means" refers to a device or module provided for receiving information from a user.

[0357] "Storage means" refers to information storage devices and related technologies for storing received information.

[0358] "Information relevance evaluation means" refers to a process and apparatus for analyzing stored information and automatically retrieving and evaluating other related information.

[0359] A "summary generation method" is a natural language processing-based technology that summarizes analyzed information and converts it into a format that is easy for users to understand.

[0360] "Emotional analysis means" refers to a technology or device that analyzes the emotional state from the user's input information and selects content to provide based on that state.

[0361] "Output means" refers to a device or method provided for delivering optimized information to the user.

[0362] The system for realizing this invention consists of a user, a terminal, and a server. The user can input information into the system using the terminal. The input information is stored in an information storage device via a storage means.

[0363] Upon receiving input information, the server automatically searches for relevant information using an information relevance evaluation tool and analyzes the user's emotional state from the information using an emotion analysis tool. Specifically, it uses the Google Cloud Natural Language API to perform emotion analysis on text. Based on these results, it selects content best suited to the user's emotions and searches for the corresponding information in databases such as Firebase. This information is then converted into a format easily understood by the user by a summarization generation tool.

[0364] The terminal receives information from the server and presents it to the user via an output device. This presentation method is adjusted as needed based on the user's current emotional state. For example, in situations where the user wants to relax, soothing music or nature videos are often recommended.

[0365] For example, if a user inputs "I'm tired today," the server uses emotion analysis to detect an emotional state that seeks "relaxation," selects an appropriate video, and provides it to the user. In this process, by using a prompt message in the generative AI model such as, "If the user inputs 'I'm tired today,' please output specific content examples based on the emotion analysis results, what kind of content should be suggested?", effective information provision can be achieved.

[0366] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0367] Step 1:

[0368] The user enters information using the device. This input is done via keyboard or voice recognition and is saved as text data on the device. For example, if the user enters "I'm tired today," this text data is saved on the device.

[0369] Step 2:

[0370] The terminal sends the entered text data to the server. During this process, the terminal securely transmits the data to the server via network communication. The server stores the received data in its information storage device.

[0371] Step 3:

[0372] The server analyzes the stored text data using information relevance assessment tools. This analysis retrieves relevant information using the Google Cloud Natural Language API and performs sentiment analysis. The result of the analysis is that the user is in an emotional state of needing "relaxation."

[0373] Step 4:

[0374] Based on the sentiment analysis results, the server selects content related to "relaxation" from the Firebase database. The selected information is summarized in the most appropriate format, often including links to nature videos or healing music.

[0375] Step 5:

[0376] The server sends summarized information to the terminal, which then presents it to the user. The information is displayed in a user-friendly interface; for example, if it includes a video link, a play button will be displayed.

[0377] Step 6:

[0378] Users use the information displayed on their device to select and view the desired content. Viewing the content allows users to relax and feel satisfied with how they receive the information.

[0379] In this process, the prompt "If the user enters 'I'm tired today,' please output specific content examples based on the sentiment analysis results, and provide the most appropriate information" is used through the generating AI model.

[0380] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0381] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0382] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0383] [Third Embodiment]

[0384] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0385] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0386] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0387] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0388] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0389] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0390] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0391] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0392] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0393] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0394] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0395] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0396] This invention is a system that supports the creation of new ideas by allowing users to input information using a terminal they have on hand, and then having a server receive, store, and analyze that information. Users input their ideas and notes into their terminal and send them to the server in a structured manner. The server stores this information in an information storage device and indexes it in a database to make it quickly accessible.

[0397] The server performs an information relevance assessment based on the input information and analyzes its relationships with other information stored in the database. This includes relationships based on the context and level of the information. Furthermore, the server utilizes natural language processing technology to generate a summary of the input information. This summary extracts the essence and is provided to the user in a format that can be understood quickly.

[0398] Furthermore, the server evaluates relevant information and combinations with other already stored information, suggesting new perspectives to the user. This allows users to construct new ideas and hypotheses they hadn't considered before, enabling them to think more efficiently and innovatively.

[0399] For example, when a user inputs information such as "ideas for a sales strategy for a new product," the server automatically references and analyzes similar past success stories and marketing methods, and proposes a new strategy that is useful to the user. In this way, the system of the present invention makes effective use of vast amounts of information and strongly supports the creative activities of users.

[0400] The following describes the processing flow.

[0401] Step 1:

[0402] The user inputs information such as ideas and notes into the terminal in text format. The terminal formats the input information and prepares it for transmission to the server.

[0403] Step 2:

[0404] The terminal sends information to the server. The information is transferred to the server via an API using a secure communication protocol.

[0405] Step 3:

[0406] The server receives information sent from the terminal and immediately saves it to its storage device. During saving, metadata such as date, tags, and categories are attached to the information, and an index is created in the database.

[0407] Step 4:

[0408] The server automatically analyzes the stored information and uses information relevance evaluation tools to assess its relationship with other stored information. It searches for similar or related information through text mining and keyword matching.

[0409] Step 5:

[0410] The server generates a concise summary of the received information through a summary generation mechanism. Using natural language processing techniques, it extracts key points and saves them as a summary.

[0411] Step 6:

[0412] The server prepares data to suggest new ideas and perspectives to the user, based on the results and summaries of the information relevance assessment. This data is generated by utilizing similar past cases and patterns.

[0413] Step 7:

[0414] The terminal receives summaries and suggestions from the server and presents them to the user through an interface. The user can use this as a reference to generate new ideas or develop existing ones.

[0415] (Example 1)

[0416] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0417] In today's information society, it is difficult for users to generate new ideas from vast amounts of data. In particular, there is a lack of effective means to summarize information and appropriately present related information, creating a need for mechanisms that support users' creative thinking. Furthermore, existing methods make it difficult to accurately evaluate the relevance of information, and the provision of new perspectives is limited.

[0418] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0419] In this invention, the server includes communication means for receiving information from a user, recording means for storing the received information in a data storage device, and data evaluation means for analyzing the recorded information and automatically identifying other relevant information. This makes it possible to support the user's creative thinking and efficiently generate new ideas.

[0420] "Communication means" refers to technologies or devices used to provide an interface for receiving information from users and for transmitting data from a terminal to a server.

[0421] A "recording means" refers to a process or device for permanently storing received information, such as writing to a database or storage device.

[0422] "Data evaluation means" refers to methods or techniques for analyzing recorded information and automatically identifying other relevant information. This includes algorithms and criteria for determining the relevance of information.

[0423] "Information conversion means" refers to technologies or processes for summarizing analyzed information and converting it into a format that is easy for users to understand. Natural language processing technologies are an example of this.

[0424] "Information presentation means" refers to output interfaces or media for providing users with summarized information and related information.

[0425] A "perspective presentation method" is a technology or process that provides a new perspective tailored to a specified use, in order to support the user's creative thinking.

[0426] This invention is an information processing system designed to support users in generating ideas. Users first input new ideas or notes using their own terminal. Input is possible using a keyboard or voice input. The input information is then transmitted from the terminal to a server via the internet.

[0427] The server verifies the received information to ensure its format is correct before saving it to data storage. A database management system is used for data storage, with technologies such as PostgreSQL and MongoDB being applied.

[0428] After the information is stored, the server analyzes the relationships between the pieces of information. Here, it identifies related information using evaluation criteria and templates built into the information processing device. SpaCy and NLTK are often used as natural language processing libraries.

[0429] Next, the server uses a generative AI model that performs natural language processing to summarize the information. In this process, the essence of the information is extracted and converted into a form that users can quickly understand. Open-source natural language processing models are used for summary generation.

[0430] Ultimately, the server presents the user with new perspectives along with relevant information. Through this process, users can develop new ideas and hypotheses they hadn't considered before.

[0431] For example, if a user is thinking of ideas for a sales strategy for a new product, the server can analyze past marketing success stories and suggest useful strategies to the user. To achieve this, a prompt such as "Suggest an innovative application that utilizes artificial intelligence" is input to the generative AI model, and by analyzing the results, it is possible to present new ideas.

[0432] This system provides an effective means of generating new ideas based on vast amounts of data in today's information society.

[0433] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0434] Step 1:

[0435] Users input ideas and notes using their own devices. Specifically, they might type "ideas regarding a sales strategy for a new product" using the keyboard. The entered information is then formatted by the device into JSON or XML format and prepared for transmission to the server. The input data is structured text data.

[0436] Step 2:

[0437] The server receives information sent from the terminal. First, the server checks the format of the received data to ensure there are no defects. This check is performed using a script such as Python. After verification, the data is registered in the database. The input is structured data, and the output returns a success status.

[0438] Step 3:

[0439] Based on the stored information, the server analyzes its relationships with other information in the database. This process uses spaCy as a natural language processing library to perform classification and extraction, and calculates a relevance score. The input is information stored in an existing database, and the output is a list of highly similar information.

[0440] Step 4:

[0441] The server uses a generative AI model to summarize relevant information. Specifically, it takes prompts such as "Propose an innovative application that utilizes artificial intelligence" as input to the AI ​​model and extracts key points in a short amount of time. The input is a list of highly relevant information, and the output provides a concise summary.

[0442] Step 5:

[0443] The server generates new suggestions for the user based on the summary results. It extracts past success stories and marketing methods from a vast amount of data, providing new strategic perspectives. The input is the summary results and related information, and the output is concrete suggestions that stimulate the user's creative activity.

[0444] (Application Example 1)

[0445] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0446] Content providers face the challenge of effectively utilizing existing information and trends to gain new insights and ideas when creating new content. In particular, quickly finding useful information from a vast amount of data and using it to gain new perspectives requires time and effort.

[0447] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0448] In this invention, the server includes input means for receiving information from a user, storage means for storing the received information in an information storage device, information relevance evaluation means for analyzing the stored information and automatically searching for other related information, summary generation means for summarizing the analyzed information and converting it into a format that is easy for the user to understand, and new suggestion generation means for generating new insights for content providers to create new content. This enables content providers to effectively obtain new ideas and perspectives and efficiently create innovative content.

[0449] A "user" refers to a person who uses this system to input information and engage in creative activities.

[0450] An "information storage device" is a device that stores information received from users in a database format and manages it so that it can be accessed quickly later.

[0451] An "information relevance evaluation means" is a processing means that analyzes stored information and automatically explores its relationships with other information.

[0452] A "summary generation method" is a means that uses natural language processing technology to concisely summarize information entered by a user and convert it into an easily understandable format.

[0453] A "new proposal generation tool" is a tool that provides new insights for content providers to create new content based on analyzed and related information.

[0454] An embodiment of the present invention is a system consisting of a user, a terminal, and a server.

[0455] Users input information for creative activities using devices such as smartphones or smart glasses. The input information is recorded on the device in text or audio format. The device then transmits this information to a server via the internet.

[0456] The server stores the received information in a cloud-based database and manages it in an indexed format by an information storage device. The server is equipped with either Python's NLTK or spaCy as a natural language processing library, which is used to summarize the information.

[0457] The information relevance evaluation means automatically searches for the relationship between the received information and other information in the database. This utilizes existing templates or detection criteria within the information processing device. Once relevant information is found, the server uses a generative AI model to generate suggestions from the novel suggestion generation means.

[0458] The device displays summary information and new insights sent from the server to the user in a visual format. This allows the user to efficiently acquire new content ideas.

[0459] For example, if a user uses the prompt "I'm thinking of ideas for a new YouTube video about environmental protection," the server can analyze the accumulated environmental information and, based on the results, suggest new ideas such as "plan a viewer-participation challenge event and video their efforts."

[0460] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0461] Step 1:

[0462] Users input information using smartphones or smart glasses. The input information is in text or audio format and relates to creative content such as ideas and notes. This information is temporarily stored on the device.

[0463] Step 2:

[0464] The terminal transmits the entered information to the server via the internet. The transmitted data is formatted as text and securely delivered to the server using a data transfer protocol.

[0465] Step 3:

[0466] The server stores the received text in a cloud-based database. The data is indexed by an information storage device and managed to facilitate searching and access. A database management system (e.g., MySQL) is used for the storage process.

[0467] Step 4:

[0468] The server uses a natural language processing library (e.g., Python's NLTK or spaCy) to generate a summary of the received information. This process extracts the subject matter of the text and summarizes the main points into a few sentences. The summary results are stored in a database for later use.

[0469] Step 5:

[0470] The information relevance assessment tool uses an indexed database to search for other related information. Templates or detection criteria are used for the search. The server finds relevant information and stores it along with a summary.

[0471] Step 6:

[0472] The generative AI model generates new suggestions based on the analyzed and related information. The server uses this model to build new insights and ideas for content providers. The output suggestions are specific approaches and insights that help users create content.

[0473] Step 7:

[0474] The terminal displays summary information and new suggestions sent from the server on its screen. Users can visually review and incorporate this information. The display is designed with a user-friendly interface in mind.

[0475] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0476] This invention relates to a system that recognizes the user's emotional state using an emotion engine based on user input information and presents information accordingly. The user inputs information through a terminal, providing ideas and opinions to the system. The input information is transmitted from the terminal to a server and stored in an information storage device. During this process, the information is tagged and stored in a database.

[0477] The server analyzes the input information and uses information relevance evaluation tools to extract other relevant information. The results of this analysis form the basis for facilitating the creation of meaningful new ideas for the user. Furthermore, the input information is summarized using natural language processing technology and presented in an easily understandable format for the user.

[0478] The emotion engine uses natural language processing technology to analyze the user's emotional state from their input and appropriately selects the information to present based on that state. For example, if the user is feeling stressed, the system can present more supportive messages or ideas. In this way, by providing information that matches the user's emotions, the system maximizes the utilization of that information.

[0479] As a concrete example, suppose a user enters a "problem related to project progress," and the emotion engine recognizes the user's anxiety. In this case, the server proposes solutions based on similar past cases and provides advice to the user through the terminal. This proposal is tailored to the user's emotional state and helps them approach problem-solving in a more relaxed manner.

[0480] This invention provides a system that more effectively supports users' creative activities through an information presentation function that incorporates emotions.

[0481] The following describes the processing flow.

[0482] Step 1:

[0483] The user inputs ideas and notes into the device. The device then formats this information and prepares it for transmission to the server.

[0484] Step 2:

[0485] The terminal sends the entered information to the server. This information is transferred securely using an API.

[0486] Step 3:

[0487] The server stores the received information in its data storage device. During storage, metadata such as tags and dates are added to the database.

[0488] Step 4:

[0489] The server analyzes the stored information using information relevance evaluation tools. This analysis assesses the relevance of the information to other information, and similar or related information is automatically searched for.

[0490] Step 5:

[0491] The emotion engine analyzes input information on the server using natural language processing technology to recognize the user's emotional state. This analysis enables the provision of information based on the user's emotions.

[0492] Step 6:

[0493] The server generates a summary of the received information using a summary generation mechanism. The summarized information is output in a format optimized for the user.

[0494] Step 7:

[0495] The server fine-tunes the information presented based on the emotion engine's recognition results. If the analysis indicates that the user is experiencing stress, it prepares information that includes gentler language and encouraging messages.

[0496] Step 8:

[0497] The device receives summaries and sentiment-based suggestions from the server and presents them to the user. This allows the user to decide on their next action based on information that suits their situation and emotions.

[0498] (Example 2)

[0499] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0500] In processing and presenting information, there is a need for flexible information delivery that takes into account the user's emotional state. Existing information presentation systems struggle to dynamically adjust information in response to user emotions, making improving the user experience a challenge. In particular, when users are experiencing stress or anxiety, there is a need to provide more appropriate information and support.

[0501] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0502] In this invention, the server includes an input means for receiving information from a user, an information relevance evaluation means for analyzing the received information and searching for related information, and a summary generation means for summarizing the information using natural language processing technology and generating suggestions using an AI model. This makes it possible to provide information that is tailored to the user's emotional state.

[0503] An "input means" is a device or mechanism for receiving information from a user and incorporating it into the system.

[0504] An "information storage device" is a device that stores received information and keeps it in a state where it can be accessed as needed.

[0505] "Storage means" refers to a function or process for storing received information in an information storage device.

[0506] "Information relevance evaluation means" refers to a mechanism or procedure used to analyze stored information and automatically retrieve other related information.

[0507] A "summary generation means" is a technique or method for summarizing analyzed information and converting it into a short, concise form.

[0508] "Output means" refers to a device or configuration for providing summarized information and related information to the user.

[0509] "Emotional analysis means" refers to a procedure or mechanism for analyzing a user's emotional state from their input information and selecting appropriate information based on that emotion.

[0510] A "generative AI model" is a model that uses machine learning and artificial intelligence technologies to generate suggestions and information based on prompt text.

[0511] A "prompt sentence" is a sentence containing instructions or questions that is input into a generative AI model, and it functions as a trigger for information generation.

[0512] This invention is an information presentation system that takes into account the user's emotional state. This system transmits information entered by the user via a terminal to a server, which then analyzes, stores, summarizes, and performs sentiment analysis on the received information. By utilizing appropriate hardware and software at each stage, the system improves the user experience.

[0513] The server uses information storage devices and databases to store and manage input information. The input information is tagged and, after storage, analyzed by an information relevance evaluation system. This system extracts relevant information by comparing it with existing information in the database.

[0514] In addition, the server uses natural language processing technology and a summary generation mechanism to summarize the input information. This allows the user to receive concise and easy-to-understand information. The sentiment analysis mechanism uses a dedicated sentiment engine to determine the user's emotional state. This analysis result is used to select the information to be presented in subsequent steps.

[0515] For example, if a user enters their anxieties about being the leader of a new project into the terminal, the server will present past success stories and project management tips. It is possible to use a generative AI model to generate specific suggestions based on the prompt text.

[0516] For example, if the user enters the prompt message, "I'm worried because the project is behind schedule. Please tell me what I can do to improve it," the system can provide information that will alleviate the user's anxiety.

[0517] In this way, the present invention makes it possible to more effectively support the user's creative activities through an information presentation function that incorporates emotions.

[0518] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0519] Step 1:

[0520] The user inputs information using a terminal. Specifically, the user enters a message in text format and sends it to the server via a send button or similar. The input data is text information including the user's issues and opinions. The output is the data sent to the server.

[0521] Step 2:

[0522] The server stores the information received from the terminal in its information storage device. This process temporarily holds the received information in memory and prepares it for permanent storage in the database. During this process, the information is tagged based on categories and keywords. The input is the user information sent in step 1, and the output is the tagged information stored in the database.

[0523] Step 3:

[0524] The server analyzes the stored information using information relevance evaluation tools. Specifically, it compares it with existing information in the database and searches for and extracts relevant information. In this process, relevant information is identified based on similar keywords and past cases. The input is the information stored in step 2, and the output is the extracted relevant information.

[0525] Step 4:

[0526] The server utilizes natural language processing technology to summarize information using a summary generation mechanism. This process involves shortening long texts and converting them into an easily understandable format. Using code and algorithms, it extracts key points and creates a summary. The input is the relevant information from step 3, and the output is the summarized information.

[0527] Step 5:

[0528] The server uses an emotion engine to analyze the user's emotional state. It analyzes the user's text data using natural language processing techniques to identify emotional states (e.g., anxiety, joy). Based on the emotion analysis results, more supportive information is selected. The input is user information from step 1, and the output is the analyzed emotional state.

[0529] Step 6:

[0530] The server uses a generative AI model to generate suggestions based on the prompt text, selecting and presenting appropriate information to the user. Specifically, the prompt text is input into the model, and individually customized suggestions are generated. The results are displayed to the user via the terminal. The input is the sentiment analysis results from step 5 and the summary information from step 4, and the output is the generated suggestions.

[0531] (Application Example 2)

[0532] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0533] Modern information distribution systems face the challenge of providing content and information appropriately tailored to the user's emotional state. In particular, amidst the vast amount of information available, providing information that considers the individual user's emotional state is crucial for improving the user experience. Therefore, there is a need to realize a system that analyzes the user's emotional state and provides optimal content accordingly.

[0534] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0535] In this invention, the server includes an input means for receiving information from a user, a storage means for storing the received information in an information storage device, and an emotion analysis means for analyzing the user's emotional state and selecting content to be provided based on that state. This makes it possible to provide appropriate information according to the user's emotional state.

[0536] "Input means" refers to a device or module provided for receiving information from a user.

[0537] "Storage means" refers to information storage devices and related technologies for storing received information.

[0538] "Information relevance evaluation means" refers to a process and apparatus for analyzing stored information and automatically retrieving and evaluating other related information.

[0539] A "summary generation method" is a natural language processing-based technology that summarizes analyzed information and converts it into a format that is easy for users to understand.

[0540] "Emotional analysis means" refers to a technology or device that analyzes the emotional state from the user's input information and selects content to provide based on that state.

[0541] "Output means" refers to a device or method provided for delivering optimized information to the user.

[0542] The system for realizing this invention consists of a user, a terminal, and a server. The user can input information into the system using the terminal. The input information is stored in an information storage device via a storage means.

[0543] Upon receiving input information, the server automatically searches for relevant information using an information relevance evaluation tool and analyzes the user's emotional state from the information using an emotion analysis tool. Specifically, it uses the Google Cloud Natural Language API to perform emotion analysis on text. Based on these results, it selects content best suited to the user's emotions and searches for the corresponding information in databases such as Firebase. This information is then converted into a format easily understood by the user by a summarization generation tool.

[0544] The terminal receives information provided by the server and presents it to the user via an output device. This presentation method is adjusted as appropriate based on the user's current emotional state. For example, in situations where the user wants to relax, soothing music or nature videos are often recommended.

[0545] For example, if a user inputs "I'm tired today," the server uses emotion analysis to detect an emotional state that seeks "relaxation," selects an appropriate video, and provides it to the user. In this process, by using a prompt message in the generative AI model such as, "If the user inputs 'I'm tired today,' please output specific content examples based on the emotion analysis results, what kind of content should be suggested?", effective information provision can be achieved.

[0546] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0547] Step 1:

[0548] The user enters information using the device. This input is done via keyboard or voice recognition and is saved as text data on the device. For example, if the user enters "I'm tired today," this text data is saved on the device.

[0549] Step 2:

[0550] The terminal sends the entered text data to the server. During this process, the terminal securely transmits the data to the server via network communication. The server stores the received data in its information storage device.

[0551] Step 3:

[0552] The server analyzes the stored text data using information relevance assessment tools. This analysis retrieves relevant information using the Google Cloud Natural Language API and performs sentiment analysis. The result of the analysis is that the user is in an emotional state of needing "relaxation."

[0553] Step 4:

[0554] Based on the sentiment analysis results, the server selects content related to "relaxation" from the Firebase database. The selected information is summarized in the most appropriate format, often including links to nature videos or healing music.

[0555] Step 5:

[0556] The server sends summarized information to the terminal, which then presents it to the user. The information is displayed in a user-friendly interface; for example, if it includes a video link, a play button will be displayed.

[0557] Step 6:

[0558] Users use the information displayed on their device to select and view the desired content. Viewing the content allows users to relax and feel satisfied with how they receive the information.

[0559] In this process, the prompt "If the user enters 'I'm tired today,' please output specific content examples based on the sentiment analysis results, and provide the most appropriate information" is used through the generating AI model.

[0560] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0561] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0562] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0563] [Fourth Embodiment]

[0564] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0565] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0566] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0567] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0568] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0569] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0570] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0571] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0572] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0573] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0574] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0575] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0576] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0577] This invention is a system that supports the creation of new ideas by allowing users to input information using a terminal they have on hand, and then having a server receive, store, and analyze that information. Users input their ideas and notes into their terminal and send them to the server in a structured manner. The server stores this information in an information storage device and indexes it in a database to make it quickly accessible.

[0578] The server performs an information relevance assessment based on the input information and analyzes its relationships with other information stored in the database. This includes relationships based on the context and level of the information. Furthermore, the server utilizes natural language processing technology to generate a summary of the input information. This summary extracts the essence and is provided to the user in a format that can be understood quickly.

[0579] Furthermore, the server evaluates relevant information and combinations with other already stored information, suggesting new perspectives to the user. This allows users to construct new ideas and hypotheses they hadn't considered before, enabling them to think more efficiently and innovatively.

[0580] For example, when a user inputs information such as "ideas for a sales strategy for a new product," the server automatically references and analyzes similar past success stories and marketing methods, and proposes a new strategy that is useful to the user. In this way, the system of the present invention makes effective use of vast amounts of information and strongly supports the creative activities of users.

[0581] The following describes the processing flow.

[0582] Step 1:

[0583] The user inputs information such as ideas and notes into the terminal in text format. The terminal formats the input information and prepares it for transmission to the server.

[0584] Step 2:

[0585] The terminal sends information to the server. The information is transferred to the server via an API using a secure communication protocol.

[0586] Step 3:

[0587] The server receives information sent from the terminal and immediately saves it to its storage device. During saving, metadata such as date, tags, and categories are attached to the information, and an index is created in the database.

[0588] Step 4:

[0589] The server automatically analyzes the stored information and uses information relevance evaluation tools to assess its relationship with other stored information. It searches for similar or related information through text mining and keyword matching.

[0590] Step 5:

[0591] The server generates a concise summary of the received information through a summary generation mechanism. Using natural language processing techniques, it extracts key points and saves them as a summary.

[0592] Step 6:

[0593] The server prepares data to suggest new ideas and perspectives to the user, based on the results and summaries of the information relevance assessment. This data is generated by utilizing similar past cases and patterns.

[0594] Step 7:

[0595] The terminal receives summaries and suggestions from the server and presents them to the user through an interface. The user can use this as a reference to generate new ideas or develop existing ones.

[0596] (Example 1)

[0597] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0598] In today's information society, it is difficult for users to generate new ideas from vast amounts of data. In particular, there is a lack of effective means to summarize information and appropriately present related information, creating a need for mechanisms that support users' creative thinking. Furthermore, existing methods make it difficult to accurately evaluate the relevance of information, and the provision of new perspectives is limited.

[0599] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0600] In this invention, the server includes communication means for receiving information from a user, recording means for storing the received information in a data storage device, and data evaluation means for analyzing the recorded information and automatically identifying other relevant information. This makes it possible to support the user's creative thinking and efficiently generate new ideas.

[0601] "Communication means" refers to technologies or devices used to provide an interface for receiving information from users and for transmitting data from a terminal to a server.

[0602] A "recording means" refers to a process or device for permanently storing received information, such as writing to a database or storage device.

[0603] "Data evaluation means" refers to methods or techniques for analyzing recorded information and automatically identifying other relevant information. This includes algorithms and criteria for determining the relevance of information.

[0604] "Information conversion means" refers to technologies or processes for summarizing analyzed information and converting it into a format that is easy for users to understand. Natural language processing technologies are an example of this.

[0605] "Information presentation means" refers to output interfaces or media for providing users with summarized information and related information.

[0606] A "perspective presentation method" is a technology or process that provides a new perspective tailored to a specified use, in order to support the user's creative thinking.

[0607] This invention is an information processing system designed to support users in generating ideas. Users first input new ideas or notes using their own terminal. Input is possible using a keyboard or voice input. The input information is then transmitted from the terminal to a server via the internet.

[0608] The server verifies the received information to ensure its format is correct before saving it to data storage. A database management system is used for data storage, with technologies such as PostgreSQL and MongoDB being applied.

[0609] After the information is stored, the server analyzes the relationships between the pieces of information. Here, it identifies related information using evaluation criteria and templates built into the information processing device. SpaCy and NLTK are often used as natural language processing libraries.

[0610] Next, the server uses a generative AI model that performs natural language processing to summarize the information. In this process, the essence of the information is extracted and converted into a form that users can quickly understand. Open-source natural language processing models are used for summary generation.

[0611] Ultimately, the server presents the user with new perspectives along with relevant information. Through this process, users can develop new ideas and hypotheses they hadn't considered before.

[0612] For example, if a user is thinking of ideas for a sales strategy for a new product, the server can analyze past marketing success stories and suggest useful strategies to the user. To achieve this, a prompt such as "Suggest an innovative application that utilizes artificial intelligence" is input to the generative AI model, and by analyzing the results, it is possible to present new ideas.

[0613] This system provides an effective means of generating new ideas based on vast amounts of data in today's information society.

[0614] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0615] Step 1:

[0616] Users input ideas and notes using their own devices. Specifically, they might type "ideas regarding a sales strategy for a new product" using the keyboard. The entered information is then formatted by the device into JSON or XML format and prepared for transmission to the server. The input data is structured text data.

[0617] Step 2:

[0618] The server receives information sent from the terminal. First, the server checks the format of the received data to ensure there are no defects. This check is performed using a script such as Python. After verification, the data is registered in the database. The input is structured data, and the output returns a success status.

[0619] Step 3:

[0620] Based on the stored information, the server analyzes its relationships with other information in the database. This process uses spaCy as a natural language processing library to perform classification and extraction, and calculates a relevance score. The input is information stored in an existing database, and the output is a list of highly similar information.

[0621] Step 4:

[0622] The server uses a generative AI model to summarize relevant information. Specifically, it takes prompts such as "Propose an innovative application that utilizes artificial intelligence" as input to the AI ​​model and extracts key points in a short amount of time. The input is a list of highly relevant information, and the output provides a concise summary.

[0623] Step 5:

[0624] The server generates new suggestions for the user based on the summary results. It extracts past success stories and marketing methods from a vast amount of data, providing new strategic perspectives. The input is the summary results and related information, and the output is concrete suggestions that stimulate the user's creative activity.

[0625] (Application Example 1)

[0626] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0627] Content providers face the challenge of effectively utilizing existing information and trends to gain new insights and ideas when creating new content. In particular, quickly finding useful information from a vast amount of data and using it to gain new perspectives requires time and effort.

[0628] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0629] In this invention, the server includes input means for receiving information from a user, storage means for storing the received information in an information storage device, information relevance evaluation means for analyzing the stored information and automatically searching for other related information, summary generation means for summarizing the analyzed information and converting it into a format that is easy for the user to understand, and new suggestion generation means for generating new insights for content providers to create new content. This enables content providers to effectively obtain new ideas and perspectives and efficiently create innovative content.

[0630] A "user" refers to a person who uses this system to input information and engage in creative activities.

[0631] An "information storage device" is a device that stores information received from users in a database format and manages it so that it can be accessed quickly later.

[0632] An "information relevance evaluation means" is a processing means that analyzes stored information and automatically explores its relationships with other information.

[0633] A "summary generation method" is a means that uses natural language processing technology to concisely summarize information entered by a user and convert it into an easily understandable format.

[0634] A "new proposal generation tool" is a tool that provides new insights for content providers to create new content based on analyzed and related information.

[0635] An embodiment of the present invention is a system consisting of a user, a terminal, and a server.

[0636] Users input information for creative activities using devices such as smartphones or smart glasses. The input information is recorded on the device in text or audio format. The device then transmits this information to a server via the internet.

[0637] The server stores the received information in a cloud-based database and manages it in an indexed format by an information storage device. The server is equipped with either Python's NLTK or spaCy as a natural language processing library, which is used to summarize the information.

[0638] The information relevance evaluation means automatically searches for the relationship between the received information and other information in the database. This utilizes existing templates or detection criteria within the information processing device. Once relevant information is found, the server uses a generative AI model to generate suggestions from the novel suggestion generation means.

[0639] The device displays summary information and new insights sent from the server to the user in a visual format. This allows the user to efficiently acquire new content ideas.

[0640] For example, if a user uses the prompt "I'm thinking of ideas for a new YouTube video about environmental protection," the server can analyze the accumulated environmental information and, based on the results, suggest new ideas such as "plan a viewer-participation challenge event and video their efforts."

[0641] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0642] Step 1:

[0643] Users input information using smartphones or smart glasses. The input information is in text or audio format and relates to creative content such as ideas and notes. This information is temporarily stored on the device.

[0644] Step 2:

[0645] The terminal transmits the entered information to the server via the internet. The transmitted data is formatted as text and securely delivered to the server using a data transfer protocol.

[0646] Step 3:

[0647] The server stores the received text in a cloud-based database. The data is indexed by an information storage device and managed to facilitate searching and access. A database management system (e.g., MySQL) is used for the storage process.

[0648] Step 4:

[0649] The server uses a natural language processing library (e.g., Python's NLTK or spaCy) to generate a summary of the received information. This process extracts the subject matter of the text and summarizes the main points into a few sentences. The summary results are stored in a database for later use.

[0650] Step 5:

[0651] The information relevance assessment tool uses an indexed database to search for other related information. Templates or detection criteria are used for the search. The server finds relevant information and stores it along with a summary.

[0652] Step 6:

[0653] The generative AI model generates new suggestions based on the analyzed and related information. The server uses this model to build new insights and ideas for content providers. The output suggestions are specific approaches and insights that help users create content.

[0654] Step 7:

[0655] The terminal displays summary information and new suggestions sent from the server on its screen. Users can visually review and incorporate this information. The display is designed with a user-friendly interface in mind.

[0656] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0657] This invention relates to a system that recognizes the user's emotional state using an emotion engine based on user input information and presents information accordingly. The user inputs information through a terminal, providing ideas and opinions to the system. The input information is transmitted from the terminal to a server and stored in an information storage device. During this process, the information is tagged and stored in a database.

[0658] The server analyzes the input information and uses information relevance evaluation tools to extract other relevant information. The results of this analysis form the basis for facilitating the creation of meaningful new ideas for the user. Furthermore, the input information is summarized using natural language processing technology and presented in an easily understandable format for the user.

[0659] The emotion engine uses natural language processing technology to analyze the user's emotional state from their input and appropriately selects the information to present based on that state. For example, if the user is feeling stressed, the system can present more supportive messages or ideas. In this way, by providing information that matches the user's emotions, the system maximizes the utilization of that information.

[0660] As a concrete example, suppose a user enters a "problem related to project progress," and the emotion engine recognizes the user's anxiety. In this case, the server proposes solutions based on similar past cases and provides advice to the user through the terminal. This proposal is tailored to the user's emotional state and helps them approach problem-solving in a more relaxed manner.

[0661] This invention provides a system that more effectively supports users' creative activities through an information presentation function that incorporates emotions.

[0662] The following describes the processing flow.

[0663] Step 1:

[0664] The user inputs ideas and notes into the device. The device then formats this information and prepares it for transmission to the server.

[0665] Step 2:

[0666] The terminal sends the entered information to the server. This information is transferred securely using an API.

[0667] Step 3:

[0668] The server stores the received information in its data storage device. During storage, metadata such as tags and dates are added to the database.

[0669] Step 4:

[0670] The server analyzes the stored information using information relevance evaluation tools. This analysis assesses the relevance of the information to other information, and similar or related information is automatically searched for.

[0671] Step 5:

[0672] The emotion engine analyzes input information on the server using natural language processing technology to recognize the user's emotional state. This analysis enables the provision of information based on the user's emotions.

[0673] Step 6:

[0674] The server generates a summary of the received information using a summary generation mechanism. The summarized information is output in a format optimized for the user.

[0675] Step 7:

[0676] The server fine-tunes the information presented based on the emotion engine's recognition results. If the analysis indicates that the user is experiencing stress, it prepares information that includes gentler language and encouraging messages.

[0677] Step 8:

[0678] The device receives summaries and sentiment-based suggestions from the server and presents them to the user. This allows the user to decide on their next action based on information that suits their situation and emotions.

[0679] (Example 2)

[0680] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0681] In processing and presenting information, there is a need for flexible information delivery that takes into account the user's emotional state. Existing information presentation systems struggle to dynamically adjust information in response to user emotions, making improving the user experience a challenge. In particular, when users are experiencing stress or anxiety, there is a need to provide more appropriate information and support.

[0682] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0683] In this invention, the server includes an input means for receiving information from a user, an information relevance evaluation means for analyzing the received information and searching for related information, and a summary generation means for summarizing the information using natural language processing technology and generating suggestions using an AI model. This makes it possible to provide information that is tailored to the user's emotional state.

[0684] An "input means" is a device or mechanism for receiving information from a user and incorporating it into the system.

[0685] An "information storage device" is a device that stores received information and keeps it in a state where it can be accessed as needed.

[0686] "Storage means" refers to a function or process for storing received information in an information storage device.

[0687] "Information relevance evaluation means" refers to a mechanism or procedure used to analyze stored information and automatically retrieve other related information.

[0688] A "summary generation means" is a technique or method for summarizing analyzed information and converting it into a short, concise form.

[0689] "Output means" refers to a device or configuration for providing summarized information and related information to the user.

[0690] "Emotional analysis means" refers to a procedure or mechanism for analyzing a user's emotional state from their input information and selecting appropriate information based on that emotion.

[0691] A "generative AI model" is a model that uses machine learning and artificial intelligence technologies to generate suggestions and information based on prompt text.

[0692] A "prompt sentence" is a sentence containing instructions or questions that is input into a generative AI model, and it functions as a trigger for information generation.

[0693] This invention is an information presentation system that takes into account the user's emotional state. This system transmits information entered by the user via a terminal to a server, which then analyzes, stores, summarizes, and performs sentiment analysis on the received information. By utilizing appropriate hardware and software at each stage, the system improves the user experience.

[0694] The server uses information storage devices and databases to store and manage input information. The input information is tagged and, after storage, analyzed by an information relevance evaluation system. This system extracts relevant information by comparing it with existing information in the database.

[0695] In addition, the server uses natural language processing technology and a summary generation mechanism to summarize the input information. This allows the user to receive concise and easy-to-understand information. The sentiment analysis mechanism uses a dedicated sentiment engine to determine the user's emotional state. This analysis result is used to select the information to be presented in subsequent steps.

[0696] For example, if a user enters their anxieties about being the leader of a new project into the terminal, the server will present past success stories and project management tips. It is possible to use a generative AI model to generate specific suggestions based on the prompt text.

[0697] For example, if the user enters the prompt message, "I'm worried because the project is behind schedule. Please tell me what I can do to improve it," the system can provide information that will alleviate the user's anxiety.

[0698] In this way, the present invention makes it possible to more effectively support the user's creative activities through an information presentation function that incorporates emotions.

[0699] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0700] Step 1:

[0701] The user inputs information using a terminal. Specifically, the user enters a message in text format and sends it to the server via a send button or similar. The input data is text information including the user's issues and opinions. The output is the data sent to the server.

[0702] Step 2:

[0703] The server stores the information received from the terminal in its information storage device. This process temporarily holds the received information in memory and prepares it for permanent storage in the database. During this process, the information is tagged based on categories and keywords. The input is the user information sent in step 1, and the output is the tagged information stored in the database.

[0704] Step 3:

[0705] The server analyzes the stored information using information relevance evaluation tools. Specifically, it compares it with existing information in the database and searches for and extracts relevant information. In this process, relevant information is identified based on similar keywords and past cases. The input is the information stored in step 2, and the output is the extracted relevant information.

[0706] Step 4:

[0707] The server utilizes natural language processing technology to summarize information using a summary generation mechanism. This process involves shortening long texts and converting them into an easily understandable format. Using code and algorithms, it extracts key points and creates a summary. The input is the relevant information from step 3, and the output is the summarized information.

[0708] Step 5:

[0709] The server uses an emotion engine to analyze the user's emotional state. It analyzes the user's text data using natural language processing techniques to identify emotional states (e.g., anxiety, joy). Based on the emotion analysis results, more supportive information is selected. The input is user information from step 1, and the output is the analyzed emotional state.

[0710] Step 6:

[0711] The server uses a generative AI model to generate suggestions based on the prompt text, selecting and presenting appropriate information to the user. Specifically, the prompt text is input into the model, and individually customized suggestions are generated. The results are displayed to the user via the terminal. The input is the sentiment analysis results from step 5 and the summary information from step 4, and the output is the generated suggestions.

[0712] (Application Example 2)

[0713] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0714] Modern information distribution systems face the challenge of providing content and information appropriately tailored to the user's emotional state. In particular, amidst the vast amount of information available, providing information that considers the individual user's emotional state is crucial for improving the user experience. Therefore, there is a need to realize a system that analyzes the user's emotional state and provides optimal content accordingly.

[0715] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0716] In this invention, the server includes an input means for receiving information from a user, a storage means for storing the received information in an information storage device, and an emotion analysis means for analyzing the user's emotional state and selecting content to be provided based on that state. This makes it possible to provide appropriate information according to the user's emotional state.

[0717] "Input means" refers to a device or module provided for receiving information from a user.

[0718] "Storage means" refers to information storage devices and related technologies for storing received information.

[0719] "Information relevance evaluation means" refers to a process and apparatus for analyzing stored information and automatically retrieving and evaluating other related information.

[0720] A "summary generation method" is a natural language processing-based technology that summarizes analyzed information and converts it into a format that is easy for users to understand.

[0721] "Emotional analysis means" refers to a technology or device that analyzes the emotional state from the user's input information and selects content to provide based on that state.

[0722] "Output means" refers to a device or method provided for delivering optimized information to the user.

[0723] The system for realizing this invention consists of a user, a terminal, and a server. The user can input information into the system using the terminal. The input information is stored in an information storage device via a storage means.

[0724] Upon receiving input information, the server automatically searches for relevant information using an information relevance evaluation tool and analyzes the user's emotional state from the information using an emotion analysis tool. Specifically, it uses the Google Cloud Natural Language API to perform emotion analysis on text. Based on these results, it selects content best suited to the user's emotions and searches for the corresponding information in databases such as Firebase. This information is then converted into a format easily understood by the user by a summarization generation tool.

[0725] The terminal receives information provided by the server and presents it to the user via an output device. This presentation method is adjusted as appropriate based on the user's current emotional state. For example, in situations where the user wants to relax, soothing music or nature videos are often recommended.

[0726] For example, if a user inputs "I'm tired today," the server uses emotion analysis to detect an emotional state that seeks "relaxation," selects an appropriate video, and provides it to the user. In this process, by using a prompt message in the generative AI model such as, "If the user inputs 'I'm tired today,' please output specific content examples based on the emotion analysis results, what kind of content should be suggested?", effective information provision can be achieved.

[0727] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0728] Step 1:

[0729] The user enters information using the device. This input is done via keyboard or voice recognition and is saved as text data on the device. For example, if the user enters "I'm tired today," this text data is saved on the device.

[0730] Step 2:

[0731] The terminal sends the entered text data to the server. During this process, the terminal securely transmits the data to the server via network communication. The server stores the received data in its information storage device.

[0732] Step 3:

[0733] The server analyzes the stored text data using information relevance assessment tools. This analysis retrieves relevant information using the Google Cloud Natural Language API and performs sentiment analysis. The result of the analysis is that the user is in an emotional state of needing "relaxation."

[0734] Step 4:

[0735] Based on the sentiment analysis results, the server selects content related to "relaxation" from the Firebase database. The selected information is summarized in the most appropriate format, often including links to nature videos or healing music.

[0736] Step 5:

[0737] The server sends summarized information to the terminal, which then presents it to the user. The information is displayed in a user-friendly interface; for example, if it includes a video link, a play button will be displayed.

[0738] Step 6:

[0739] Users use the information displayed on their device to select and view the desired content. Viewing the content allows users to relax and feel satisfied with how they receive the information.

[0740] In this process, the prompt "If the user enters 'I'm tired today,' please output specific content examples based on the sentiment analysis results, and provide the most appropriate information" is used through the generating AI model.

[0741] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0742] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0743] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0744] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0745] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0746] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0747] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0748] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0749] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0750] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0751] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0752] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0753] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0754] 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.

[0755] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0756] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0757] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0758] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0759] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0760] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0761] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0762] The following is further disclosed regarding the embodiments described above.

[0763] (Claim 1)

[0764] An input means for receiving information from the user,

[0765] A storage means for storing the received information in an information storage device,

[0766] Information relevance evaluation means for analyzing the stored information and automatically retrieving other related information,

[0767] A summary generation means for summarizing the analyzed information and converting it into a format that is easy for the user to understand,

[0768] Output means for providing the summarized information and related information to the user,

[0769] A system that includes this.

[0770] (Claim 2)

[0771] The system according to claim 1, characterized in that the information relevance evaluation means evaluates related information based on an existing template or detection criterion within the information processing device.

[0772] (Claim 3)

[0773] The system according to claim 1, characterized in that the summarization generation means summarizes information using natural language processing technology.

[0774] "Example 1"

[0775] (Claim 1)

[0776] A means of communication for receiving information from the user,

[0777] Recording means for storing the received information in a data storage device,

[0778] A data evaluation means for analyzing the recorded information and automatically identifying other relevant information,

[0779] Information conversion means for summarizing the analyzed information and converting it into a format that is easy for the user to understand,

[0780] Information presentation means for providing the user with the summarized information and related information,

[0781] A means of presenting perspectives to support the user's creative thinking by providing new perspectives tailored to the specified use,

[0782] A system that includes this.

[0783] (Claim 2)

[0784] The system according to claim 1, characterized in that the data evaluation means evaluates relevant data based on existing standards or judgment criteria within the information collection device.

[0785] (Claim 3)

[0786] The system according to claim 1, characterized in that the information conversion means summarizes information using language processing technology.

[0787] "Application Example 1"

[0788] (Claim 1)

[0789] An input means for receiving information from the user,

[0790] A storage means for storing the received information in an information storage device,

[0791] Information relevance evaluation means for analyzing the stored information and automatically searching for other related information,

[0792] A summary generation means for summarizing the analyzed information and converting it into a format that is easy for the user to understand,

[0793] Output means for providing the summarized information and related information to the user,

[0794] A new proposal generation method for generating new insights for content providers to create new content,

[0795] A system that includes this.

[0796] (Claim 2)

[0797] The system according to claim 1, characterized in that the information relevance evaluation means evaluates related information based on an existing format or detection criterion within the information processing device.

[0798] (Claim 3)

[0799] The system according to claim 1, characterized in that the summarization generation means summarizes information using natural language processing technology.

[0800] "Example 2 of combining an emotion engine"

[0801] (Claim 1)

[0802] An input means for receiving information from the user,

[0803] A storage means for storing the received information in an information storage device,

[0804] Information relevance evaluation means for analyzing the stored information and automatically retrieving other related information,

[0805] A summary generation means for summarizing the analyzed information and converting it into a format that is easy for the user to understand,

[0806] Output means for providing the summarized information and related information to the user,

[0807] A means for analyzing the emotional state from user input information and selecting information to present based on the analysis results,

[0808] A system that includes this.

[0809] (Claim 2)

[0810] The system according to claim 1, characterized in that the information relevance evaluation means evaluates relevant information based on an existing template or detection criterion in the information processing device and adjusts the information according to the emotional state analyzed by the emotion analysis means.

[0811] (Claim 3)

[0812] The system according to claim 1, wherein the summarization generation means is characterized by summarizing information using natural language processing technology, and generates suggestions based on prompt sentences using a generation AI model.

[0813] "Application example 2 when combining with an emotional engine"

[0814] (Claim 1)

[0815] An input means for receiving information from the user,

[0816] A storage means for storing the received information in an information storage device,

[0817] Information relevance evaluation means for analyzing the stored information and automatically retrieving other related information,

[0818] A summary generation means for summarizing the analyzed information and converting it into a format that is easy for the user to understand,

[0819] A means for analyzing the user's emotional state and selecting content to provide based on that state,

[0820] Output means for providing the summarized information and related information in a format optimized according to the user's emotional state,

[0821] A system that includes this.

[0822] (Claim 2)

[0823] The system according to claim 1, characterized in that the information relevance evaluation means evaluates relevant information based on an existing template or detection criteria within the information processing device, and further evaluates the information taking into account the user's emotional state.

[0824] (Claim 3)

[0825] The system according to claim 1, characterized in that the summary generation means summarizes information using natural language processing technology and adjusts the summary information in a format corresponding to the emotional state identified by the emotion analysis means. [Explanation of Symbols]

[0826] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. An input means for receiving information from the user, A storage means for storing the received information in an information storage device, Information relevance evaluation means for analyzing the stored information and automatically retrieving other related information, A summary generation means for summarizing the analyzed information and converting it into a format that is easy for the user to understand, Output means for providing the summarized information and related information to the user, A system that includes this.

2. The system according to claim 1, characterized in that the information relevance evaluation means evaluates related information based on an existing template or detection criterion within the information processing device.

3. The system according to claim 1, characterized in that the summarization generation means summarizes information using natural language processing technology.

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