system

Abstract

We provide the system. [Solution] A means for receiving user requests, A means for generating information based on the aforementioned request using generative artificial intelligence, A means of summarizing the generated information and storing it in a database, A means of returning saved summary information to the user, A means of periodically checking for updates to the aforementioned information, A means for generating the update information using the aforementioned generative artificial intelligence and updating the database, A system that includes means for notifying users of update information.

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, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance that responds 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 a conventional information acquisition system using generative artificial intelligence, there is a problem that when the generated information is updated, the user cannot quickly grasp the change. Also, when the generated information is a large amount of data, there is a problem that it is difficult for the user to simply understand the necessary information. As a result, the user cannot always have the latest information, and efficient utilization of information is hindered.

Means for Solving the Problems

[0005] This invention proposes a system that includes means for receiving user requests, generating information based on those requests using generative artificial intelligence, summarizing the generated information, and storing it in a database. The system also includes means for returning the stored summary information to the user, for periodically checking for information updates, for generating updated information using generative artificial intelligence and updating the database, and for notifying the user of the update information. This system allows users to obtain necessary information concisely and always have access to the latest information. Furthermore, by accepting reconfirmation requests and reflecting updates by comparing them with existing information, user convenience is improved. In addition, the reliability of the information is ensured by including means for obtaining information from both generative artificial intelligence and reliable external sources to enhance the accuracy of the generated information.

[0006] A "user" is a person or entity that accesses a system and sends requests for the purpose of obtaining, verifying, or updating information.

[0007] A "terminal" is a device that forwards user requests to a server and displays the server's response to the user.

[0008] A "server" is a central computing device that uses generative artificial intelligence to generate, summarize, store in a database, and return information to the user based on requests.

[0009] "Generative artificial intelligence" refers to algorithms and models that generate information based on user requests, and specifically includes natural language processing technology.

[0010] A "request" is the content of a request that a user sends to a server through their device in order to obtain information.

[0011] A "summary" is information that has been extracted from a large amount of information generated by a generative artificial intelligence system and summarized into a short format.

[0012] A "database" is a system for storing and managing generated information and summaries.

[0013] "Response" refers to the information or summary that a server provides in response to a user's request.

[0014] "Update check" is a process that periodically verifies whether saved information has been changed.

[0015] "Update information" refers to information that adds new information or changes to the original information.

[0016] A "reconfirmation request" is an additional request that a user sends to the server to verify the latest status of information they previously obtained.

[0017] "Comparison" is the act of comparing newly generated information with existing information.

[0018] "Notification" is a means of informing users of updated information.

[0019] A "reliable source" is an information provider that is referenced to ensure the accuracy of information obtained from external sources. [Brief explanation of the drawing]

[0020] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] 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.

Embodiments for Carrying Out the Invention

[0021] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described according to the accompanying drawings.

[0022] First, the language used in the following description will be explained.

[0023] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), and APU (Accelerated Processing Unit).

[0024] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0025] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0026] 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).

[0027] 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."

[0028] [First Embodiment]

[0029] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0030] 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.

[0031] 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).

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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".

[0041] This invention relates to a system that generates information based on user requests, summarizes and stores it, periodically checks for updates, and notifies the user if updates are found. The program of this system consists of the functions and roles of the server, terminal, and user.

[0042] Processing user requests

[0043] First, if a user wants to obtain specific information, they input a request into the terminal via voice or text, such as "Please tell me about new products for 2023." The terminal receives this request, converts it to the appropriate format, and sends it to the server. At this stage, the user's input becomes the key to identifying what information the system as a whole needs to generate.

[0044] Information generation and summarization

[0045] The server analyzes the received request and extracts necessary keywords and context. For example, if the request is for "new product information for 2023," it will extract keywords such as "2023" and "new products." Based on this analysis, the server uses generative artificial intelligence to generate relevant data.

[0046] Because the generated information often contains a large amount of data, the server uses a summarization engine to make the information concise. This results in summaries such as, "A new smartphone will be released in 2023, and that model will feature the latest processor."

[0047] Saving summary information and returning it to the user.

[0048] Next, the server saves the generated summary information to the database. This saving process also saves identifying information such as the request ID, making it easy to re-verify and update later. After saving, the server sends the saved summary information back to the terminal. The terminal receives this information, converts it into a display format, and presents it to the user.

[0049] Information update check and notification

[0050] After a certain period of time has passed, or if a manual check is requested, the server will perform an update check on the information. This involves using generative artificial intelligence again to retrieve new relevant information and comparing it with the existing information in the database. For example, if the original information was "A new smartphone will be released in 2023," and then an update is found stating "A new color has been added," the server will update the database with this information.

[0051] When an update is detected, the server sends the update information to the device, and the device uses its notification function to inform the user of the update. In this way, users can always efficiently obtain the latest information.

[0052] For example, if a user requests "Please tell me about new products for 2023," the server generates the latest information and provides the user with a summary such as "A new smartphone will be released in September 2023." Then, after a few months, if the user sends a follow-up request, the server retrieves the latest information again and notifies the user of updates such as "A new color has been added to the new smartphone." This ensures that the user always has the most up-to-date information.

[0053] Through the above program and process, the present invention provides a system that efficiently generates, summarizes, updates, and automatically notifies users of the information they request.

[0054] The following describes the processing flow.

[0055] Step 1:

[0056] The user enters their information retrieval request into the device. For example, they might enter a request such as "Please tell me about new products for 2023" via voice or text.

[0057] Step 2:

[0058] The terminal receives the user's request, converts it into the appropriate format, and sends it to the server. During this process, the request is formatted to ensure accurate transmission of its contents.

[0059] Step 3:

[0060] The server receives the request and parses it. It extracts keywords such as "2023" and "new product" from the request. This identifies what information should be generated.

[0061] Step 4:

[0062] The server uses generative artificial intelligence to generate information based on extracted keywords. For example, it collects and processes relevant data from related news articles and databases.

[0063] Step 5:

[0064] The server passes the large amount of generated information to the summarization engine. The summarization engine extracts the key points and creates a concise summary. For example, it might generate a summary such as, "A new smartphone will be released in 2023, featuring the latest processor."

[0065] Step 6:

[0066] The server stores the generated summary information and identification information such as the request ID in a database. This allows for later update checks and re-verification.

[0067] Step 7:

[0068] The server returns the stored summary information to the terminal. The information returned includes a summary of what the user requested.

[0069] Step 8:

[0070] The device receives summary information, converts it into a display format, and presents it to the user. For example, the device screen might display "A new smartphone will be released in 2023."

[0071] Step 9:

[0072] After a certain period, or upon a user request for reconfirmation, the server checks for updates to the information. It then uses generative artificial intelligence again to retrieve the latest relevant information.

[0073] Step 10:

[0074] The server compares the newly retrieved information with existing information in the database to check for updates. For example, it checks if there is new information such as "a new color has been added."

[0075] Step 11:

[0076] When an update is detected, the server updates the corresponding entry in the database and sends the update information to the terminal. This ensures that the information in the database remains up-to-date.

[0077] Step 12:

[0078] The device receives update information and notifies the user. For example, the screen might display, "New smartphone information has been updated: New colors have been added."

[0079] In this way, users can always obtain the latest information, and the entire system operates efficiently and accurately.

[0080] (Example 1)

[0081] 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."

[0082] Conventional information acquisition systems have faced challenges in providing users with the information they need appropriately and quickly, and in notifying users in a timely manner when information is updated. Furthermore, when the amount of information generated is large, users may spend a considerable amount of time finding the information they need. To solve these problems, a system is needed that generates relevant information based on user requests, summarizes and efficiently manages that information, and immediately notifies users when it is updated.

[0083] 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.

[0084] In this invention, the server includes means for receiving a user request, converting the request into an appropriate format and sending it to the server; means for generating information based on the request using generative artificial intelligence; and means for summarizing the generated information and storing it in a database. This allows the user to efficiently obtain the necessary information and receive updated information quickly.

[0085] "User" refers to an individual or organization that wishes to obtain information.

[0086] A "request" refers to a voice or text instruction that a user enters through their device to ask for information.

[0087] A "terminal" refers to an electronic device used by a user to enter requests and receive information.

[0088] A "server" refers to a computer system that processes user requests and is responsible for generating, summarizing, storing, updating, and notifying information.

[0089] "Generative artificial intelligence" refers to an algorithm or model that generates information based on input prompts.

[0090] A "prompt message" refers to a sentence that is input to a generative artificial intelligence system to generate information.

[0091] A "summary" refers to a concise compilation of information, extracting the most important parts from the generated data.

[0092] A "database" refers to a system for storing generated summary information and related data.

[0093] "Update" refers to the addition or modification of new information to the generated information.

[0094] "Notification" refers to the act of informing a user that information has been updated.

[0095] This invention relates to a system that generates information based on user requests, summarizes and stores it, periodically checks for updates, and notifies the user if updates are found. This system is composed of the functions and roles of a server, a terminal, and a user.

[0096] Processing user requests

[0097] First, if a user wants to obtain specific information, they input a request into the terminal via voice or text, such as "Please tell me about new products for 2023." The terminal receives this request, converts it to an appropriate format (e.g., JSON), and sends it to the server. At this stage, the user's input becomes the key to identifying what information the system as a whole needs to generate.

[0098] Information generation and summarization

[0099] The server analyzes the received request and extracts necessary keywords and context. For example, if the request is for "new product information for 2023," it will extract keywords such as "2023" and "new products." Based on this analysis, the server uses generative artificial intelligence (e.g., OpenAI®, GPT-4®, etc.) to generate relevant data.

[0100] Because the generated information often contains a large amount of data, the server uses a summarization engine (e.g., BERT) to simplify the information. This results in summaries such as, "A new smartphone will be released in 2023, and that model will feature the latest processor."

[0101] Saving summary information and returning it to the user.

[0102] Next, the server saves the generated summary information to the database. This saving process also saves identifying information such as the request ID, making it easy to re-verify and update later. After saving, the server sends the saved summary information back to the terminal. The terminal receives this information, converts it into a display format, and presents it to the user.

[0103] Information update check and notification

[0104] After a certain period of time has passed, or if a manual check is requested, the server will perform an update check on the information. This involves using generative artificial intelligence again to retrieve new relevant information and comparing it with the existing information in the database. For example, if the original information was "A new smartphone will be released in 2023," and then an update is found stating "A new color has been added," the server will update the database with this information.

[0105] When an update is detected, the server sends the update information to the device, and the device uses its notification function to inform the user of the update. In this way, users can always efficiently obtain the latest information.

[0106] Examples of specific cases and prompt statements

[0107] For example, if a user requests "Please tell me about new products for 2023," the server generates the latest information and provides the user with a summary such as "A new smartphone will be released in September 2023." Then, after a few months, if the user sends a follow-up request, the server retrieves the latest information again and notifies the user of updates such as "A new color has been added to the new smartphone." This ensures that the user always has the most up-to-date information.

[0108] Example of a prompt:

[0109] "Please tell me about new product information for 2023."

[0110] The above describes the specific forms for carrying out the invention.

[0111] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0112] Step 1:

[0113] When a user wants to obtain specific information, they enter a request into the terminal, such as "Please tell me about new products for 2023." The input format is either voice or text. Input: User's voice or text request. Output: Request as text data.

[0114] Step 2:

[0115] The terminal receives a request from the user and converts it into a format that can be processed (e.g., JSON). After converting to the appropriate data format, the terminal sends this data to the server over the internet. Input: User request in text format. Output: Data in JSON format.

[0116] Step 3:

[0117] The server analyzes the received request data and extracts the necessary keywords and context. Specifically, the server uses natural language processing to extract keywords such as "2023" and "new products" from a request like "new product information for 2023". Input: Request data in JSON format. Output: Extracted keywords and context information.

[0118] Step 4:

[0119] The server uses generative artificial intelligence (e.g., a generative AI model) to generate information based on the extracted keywords. In this process, it generates a prompt and inputs it into the generative AI model. For example, it might create a prompt such as "Please provide the latest information on new products for 2023" and input it into the generative AI model. Input: Extracted keywords and contextual information. Output: Generated information.

[0120] Step 5:

[0121] If the amount of information generated is large, the server uses a summarization engine (e.g., BERT) to summarize the information. For example, it might create a summary such as, "A new smartphone will be released in 2023, and this model will feature the latest processor." Input: Generated information. Output: Summarized information.

[0122] Step 6:

[0123] The server saves the summarized information to the database. The request ID and user ID are also saved at this time to allow for easy retrieval of the information later. Input: Summarized information. Output: Information saved in the database.

[0124] Step 7:

[0125] The server resends the saved summary information to the terminal. The terminal converts the received information into a display format and presents it to the user. Input: Summary information stored in the database. Output: Information presented to the user.

[0126] Step 8:

[0127] After a certain period of time has passed, or when a user submits a reconfirmation request, the server checks for updates to the information. It uses the generative AI model again to retrieve new relevant information and compares it to existing information in the database. Input: User reconfirmation request or timer event. Output: New relevant information.

[0128] Step 9:

[0129] The server compares the new update information with existing information in the database. Once an update is confirmed, it sends the information to the terminal, which then uses its notification function to inform the user of the update. Input: New related information. Output: Update notification to the user.

[0130] The above describes the specific processing steps of the program in this system.

[0131] (Application Example 1)

[0132] 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."

[0133] For modern users, staying up-to-date on the latest information about products and services they are interested in is crucial. However, quickly and accurately obtaining the latest information from a vast amount of data, and regularly checking for updates, is difficult. Furthermore, acquiring information from diverse sources and ensuring its accuracy is also a challenge. In this situation, there is a need for a system that allows users to efficiently and reliably obtain the latest information they require.

[0134] 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.

[0135] In this invention, the server includes means for receiving user requests, means for generating information based on requests using generative artificial intelligence, means for summarizing the generated information and storing it in a database, means for returning the stored summary information to the user, means for periodically checking for updates to the information, means for generating updated information using generative artificial intelligence and updating the database, means for notifying the terminal when the latest information is generated, means for sending a prompt message to the generative artificial intelligence, means for generating relevant information based on product categories, and means for displaying the latest information to the user. As a result, the user can always quickly and reliably obtain the latest information on products of interest and automatically receive update information.

[0136] "Means of receiving user requests" refers to an interface that allows users to input specific information and the functionality of the system that processes that input.

[0137] "Generative artificial intelligence" refers to artificial intelligence technology that has the ability to generate relevant information based on input data.

[0138] "Means for summarizing information and storing it in a database" refers to the functions of a storage device and system for converting generated information into a concise format and accumulating that summarized information.

[0139] "Means for returning saved summary information to the user" refers to a system function that retrieves summary information stored in a database and provides it to the user.

[0140] "Means of regularly checking for updates to information" refers to a system function that checks at regular intervals whether the stored information is up-to-date.

[0141] "A means of generating update information and updating a database using generative artificial intelligence" refers to a system function that uses artificial intelligence technology to generate new information and replace existing information in a database with it.

[0142] "Means of notifying the device when new information is generated" refers to a system function that sends a notification to the user's device when new information is generated.

[0143] "Means for sending prompt messages to a generative artificial intelligence" refers to a function of a system that inputs instruction messages for information generation to a generative artificial intelligence.

[0144] "Means for generating relevant information based on product categories" refers to a system function that acquires and generates relevant information based on product categories that the user is interested in.

[0145] "Means of displaying the latest information to the user" refers to a system function that displays the generated latest information on the user's interface.

[0146] To implement this invention, a system is required in which a server, a terminal, and a user each have their own respective roles.

[0147] Processing user requests

[0148] First, if a user wants to obtain specific information, they enter a request through a smartphone application, such as "Please tell me the information about the new smartphone." This request is received by the device, converted into the appropriate format, and sent to the server.

[0149] Information generation and summarization

[0150] The server analyzes the received request and extracts necessary keywords and context. For example, if the request is for "information on a new smartphone," keywords such as "smartphone" and "new" will be extracted. Based on this analysis, the server uses a generative AI model (e.g., GPT-4) to generate relevant information. Because the generated information may be complex, the server uses a summarization engine (e.g., PEGASUS) to create a concise summary.

[0151] Saving summary information and returning it to the user.

[0152] The server saves the summarized information to a database. At this stage, the request ID and related metadata are also saved, making it easier to review and check for updates later. The saved information is sent back to the user's terminal, which then displays it to the user.

[0153] Information update check and notification

[0154] After a certain period of time, or when a manual check is requested, the server performs an information update check. It uses the generated AI model again to retrieve new relevant information and compares it with existing information in the database. If an update is found, the database is updated, and the server sends the update to the user's terminal. The terminal then notifies the user of the latest information.

[0155] Hardware and software usage

[0156] This system uses devices such as smartphones and tablets, centralized cloud servers (e.g., AWS®, Google® Cloud), and generative AI models (e.g., GPT-4) and summarization engines (e.g., PEGASUS).

[0157] Specific example

[0158] When a user enters a request into the application, such as "Please tell me about the new smartphone," the server receives the request and uses a generative AI model to generate information such as, "A new smartphone is scheduled to be released in 2023. This model will feature the latest processor and enhanced camera capabilities." This information is then summarized concisely by a summarizing engine and stored in a database. When the information is updated, the server notifies the user's device of the new information, such as, "A new color has since been added." A concrete example of a prompt sent to the generative AI model is, "Please tell me about the new smartphone coming in 2023."

[0159] This system allows users to efficiently obtain the latest and most accurate information.

[0160] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0161] Step 1:

[0162] The user opens a smartphone application and enters a specific information request (e.g., "Please tell me information about my new smartphone") via voice or text.

[0163] Input: User's voice or text request

[0164] Output: Formatted request data sent to the terminal

[0165] Operation: The application converts the user's speech into text (using speech recognition software) and then converts the acquired text data into an appropriate format.

[0166] Step 2:

[0167] The terminal sends the formatted request data to the server.

[0168] Input: Formatted request data

[0169] Output: Request data sent to the server

[0170] Operation: The terminal sends the request data to the server as an HTTP request and waits for a response.

[0171] Step 3:

[0172] The server receives and parses the request data. Specifically, it extracts necessary keywords and context from the request.

[0173] Input: Request data sent to the server

[0174] Output: Extracted keywords and contextual information

[0175] Operation: The analysis engine on the server (using natural language processing software) analyzes the data and extracts keywords and context.

[0176] Step 4:

[0177] The server uses a generative AI model (e.g., GPT-4) to generate relevant information based on extracted keywords and context.

[0178] Input: Extracted keywords and contextual information

[0179] Output: Generated information

[0180] Operation: Input prompts into the generative AI model and retrieve the generated information.

[0181] Step 5:

[0182] If the generated information is complex, the server uses a summarization engine (e.g., PEGASUS) to create a concise summary.

[0183] Input: Generated details

[0184] Output: Summarized information

[0185] Operation: Starts the summarization engine and creates a concise summary using the generated information as input.

[0186] Step 6:

[0187] The server stores the summarized information in the database.

[0188] Input: Summarized information, request ID, related metadata

[0189] Output: Summary information stored in the database

[0190] Operation: Saves summary information to a database management system (e.g., MySQL®).

[0191] Step 7:

[0192] The server sends the saved summary information back to the terminal.

[0193] Input: Summary information stored in the database

[0194] Output: Summary information sent to the terminal

[0195] Operation: Sends summary information to the terminal as an HTTP response.

[0196] Step 8:

[0197] The terminal displays the returned summary information to the user.

[0198] Input: Summary information sent from the server

[0199] Output: Summary information displayed to the user

[0200] Operation: The application displays the received summary information in the user interface.

[0201] Step 9:

[0202] The server periodically checks for updates to the information, and if new information is available, it reuses the generated AI model to retrieve the relevant information.

[0203] Input: Time interval for periodic checks, existing information

[0204] Output: New generated information

[0205] Operation: Sends an update request to the generative AI model and generates new information.

[0206] Step 10:

[0207] The server compares new information with existing information and updates the database if there are any differences.

[0208] Input: New generated information, existing information

[0209] Output: Updated database

[0210] Operation: Compares new information with existing information and updates the database if differences are detected.

[0211] Step 11:

[0212] When the server detects an information update, it notifies the user's device of the update details.

[0213] Input: Update details

[0214] Output: Notification to user terminal

[0215] Operation: Notifies the user's terminal of the latest information using the notification system.

[0216] A concrete example of a prompt is, "Please tell me about the new smartphone." This prompt prompt prompts the AI ​​model to generate the latest relevant information.

[0217] 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.

[0218] This invention provides a system that generates information based on user requests, summarizes and stores it, periodically checks for updates, and notifies the user if updates are found, in addition to utilizing an emotion engine that recognizes the user's emotions. The program of this system is composed of the functions and roles of the server, terminal, and user.

[0219] User request processing and sentiment recognition

[0220] First, the user enters a request for information into the device. For example, when a user enters a request such as "Please tell me about new products for 2023" via voice or text, the emotion engine analyzes emotional data from the user's voice tone and the content of the text message. It identifies emotional states such as joy, sadness, anger, and anxiety.

[0221] Information generation and summarization

[0222] The terminal retrieves user requests and sentiment data, converts them into an appropriate format, and sends them to the server. The server receives the requests and sentiment data, analyzes the request content, and extracts necessary keywords, such as "2023" and "new product."

[0223] Next, the server generates information based on keywords extracted using generative artificial intelligence. For example, it collects and processes relevant news and data. The large amount of generated information is then passed to a summarization engine, where key points are extracted and a concise summary is created. The content and format of the summary are adjusted based on information analyzed from sentiment data. For instance, if the user is excited, a summary containing more detailed technical information might be provided.

[0224] Saving summary information and returning it to the user.

[0225] The server saves the generated summary information and identification information such as the request ID to a database. After saving, the server sends the summary information back to the terminal. The terminal converts the received summary information into a display format and presents it to the user. For example, it might display "A new smartphone will be released in 2023" in a format that suits the user's mood.

[0226] Information update check and notification

[0227] After a certain period of time has passed, or if a user requests reconfirmation, the server checks for updates to the information. It uses generative artificial intelligence again to retrieve the latest relevant information and compares it with the existing information in the database. For example, if the original information was "A new smartphone will be released in 2023," and then an update is found such as "A new color has been added," the server will record this information in the database and update it.

[0228] Once an update is detected, the server sends the update information to the device, and the device notifies the user of the update at the appropriate time and in the appropriate style based on sentiment data. For example, it might display on the screen, "New smartphone information has been updated: New colors have been added." If the user is happy, the message will be displayed in a bright design.

[0229] By combining these emotion engines, it becomes possible to provide information that adapts to the user's emotional state, enabling the entire system to deliver a more personalized information experience.

[0230] The following describes the processing flow.

[0231] Step 1:

[0232] The user enters a request for information into the device. For example, they might enter a request such as "Please tell me about new products for 2023" via voice or text. During this process, the device collects emotional data from the user's voice tone and the nuances of their text.

[0233] Step 2:

[0234] The terminal retrieves the user's request and sentiment data, converts it into the appropriate format, and sends it to the server. The formatting ensures that the request and sentiment data are accurately conveyed.

[0235] Step 3:

[0236] The server receives the request and analyzes it. Keywords such as "2023" and "new product" are extracted from the request. At the same time, emotional data is analyzed to identify the user's emotional state. This analysis determines whether the user is excited, calm, anxious, etc.

[0237] Step 4:

[0238] The server uses generative artificial intelligence to generate information based on extracted keywords. For example, it collects relevant data from news articles and databases and generates information based on that data. Sentimental data is also taken into consideration when generating the information.

[0239] Step 5:

[0240] The server passes the large amount of generated information to the summarization engine. The summarization engine extracts the key points and creates a concise summary. Based on sentiment data, the content and format of the summary are adjusted. For example, if the user is excited, a summary containing more detailed technical information will be provided.

[0241] Step 6:

[0242] The server stores the generated summary information and identification information such as the request ID in a database. This makes it easy to perform update checks and re-verifications later.

[0243] Step 7:

[0244] The server sends the saved summary information back to the terminal. The terminal receives the summary information, converts it into a display format, and presents it to the user. For example, it might display "A new smartphone will be released in 2023" in a format that suits the user's mood.

[0245] Step 8:

[0246] After a certain period, or upon a user request for reconfirmation, the server checks for updates to the information. It then uses generative artificial intelligence again to retrieve the latest relevant information.

[0247] Step 9:

[0248] The server compares the newly retrieved information with existing information in the database to check for updates. For example, it checks for new information such as "a new color has been added."

[0249] Step 10:

[0250] When an update is detected, the server updates the corresponding entry in the database and sends the update information to the terminal. This ensures that the information in the database is always up-to-date.

[0251] Step 11:

[0252] The device receives update information and notifies the user. For example, it might display "New smartphone information has been updated: New colors have been added" on the screen. When a notification is displayed, the display method is adjusted according to the user's emotions; for example, a brighter design is used if the user is happy.

[0253] In this way, it becomes possible to recognize the user's emotions and provide information that is adapted to them, thereby improving the user experience.

[0254] (Example 2)

[0255] 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".

[0256] Traditional information delivery systems often failed to consider user emotions, resulting in a lack of information tailored to user needs and inappropriate presentation methods. Furthermore, the generated information was not frequently updated, making it difficult for users to access the latest information. Accuracy was also a challenge, as data collection from reliable external sources was insufficient.

[0257] 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.

[0258] In this invention, the server includes means for receiving user requests, means for analyzing requests and collecting sentiment data, means for generating information based on the requests and sentiment data using generative artificial intelligence, means for summarizing the generated information, means for storing the summarized information in a database, means for returning the stored summarized information to the user, means for periodically checking for updates to the stored information, means for generating the updated information using the generative artificial intelligence and updating the database, and means for notifying the user of the updated information. This enables the provision of information adapted to the user's emotions and allows the user to be provided with the latest information that is updated regularly. Furthermore, the accuracy of the information provided is enhanced by collecting data from reliable external sources.

[0259] "Means for receiving user requests" refers to devices or interfaces for receiving information retrieval requests from users. Specifically, this refers to voice input devices and text input interfaces.

[0260] "Means for analyzing requests and collecting sentiment data" refers to a system that analyzes the content of a user's request and collects the user's emotional state from the tone of voice and text content at that time. Specifically, it uses a natural language processing engine and sentiment analysis algorithm.

[0261] "Means for generating information based on the aforementioned request and sentiment data using generative artificial intelligence" refers to a technology for generating relevant information based on user requests and sentiment data using generative artificial intelligence. Specifically, it refers to a generative AI model.

[0262] "Methods for summarizing generated information" refer to techniques for extracting important parts from large amounts of generated information and creating a concise summary. This utilizes the summarization capabilities of generative artificial intelligence.

[0263] "Means for storing summarized information in a database" refers to a device or system that records and stores summarized information and associated identification information in a database. Specifically, it refers to a database management system.

[0264] "Means for returning stored summary information to the user" refers to means for notifying or providing stored summary information to the user. Specifically, it refers to servers or interfaces that transmit information over a network.

[0265] "Means for periodically checking for updates to stored information" refers to technologies for periodically verifying whether stored information is up-to-date. Specifically, this refers to scheduling systems and information gathering engines.

[0266] "Means for generating the update information and updating the database using the generative artificial intelligence" refers to a technology for generating new information and updating existing database information using generative artificial intelligence.

[0267] "Means of notifying users of updates" refers to means of informing users of updates when information is updated. Specifically, this refers to notification systems and alert functions.

[0268] "Means for receiving requests for information reconfirmation" refers to devices or interfaces for receiving reconfirmation requests from users.

[0269] "Means for sending the reconfirmation request to the generative artificial intelligence and comparing it with the existing information" refers to a technique for sending a reconfirmation request to the generative artificial intelligence and comparing the new information with the existing information.

[0270] "Means for generating new summary information when an update is detected" refers to means for generating new summary information when it is confirmed that the information has been updated.

[0271] "Means of improving the accuracy of generated information by acquiring information from generative artificial intelligence and reliable external sources" refers to technologies that use generative artificial intelligence and collect information from reliable external data sources to improve the accuracy of the information provided.

[0272] This invention is an information provision system that generates information based on user requests, summarizes and stores it, periodically checks for updates, and notifies the user if there are any updates. Furthermore, by incorporating an emotion engine that recognizes the user's emotional state, the system achieves more appropriate and personalized information provision. This invention is composed of the functions and roles of the server, terminal, and user.

[0273] First, the user enters a request for information into the device. For example, if the user enters a request such as "Please tell me about new products for 2023" via voice or text, the emotion engine analyzes emotional data from the user's voice tone and the content of the text message. The emotion engine uses emotion analysis algorithms and natural language processing engines (e.g., Microsoft® Azure® Cognitive Services). This engine identifies emotional states such as joy, sadness, anger, and anxiety.

[0274] Next, the terminal retrieves the user's request and sentiment data, converts it into an appropriate format, and sends it to the server. At this stage, the JSON format is used as the data conversion method, and it is sent via the HTTPS protocol.

[0275] The server analyzes the received request and sentiment data to extract necessary keywords. For example, a natural language processing engine (e.g., SpaCy) is used to identify the keywords "2023" and "new product." Then, a generative artificial intelligence (e.g., OpenAI GPT-4) is used to generate information based on the extracted keywords. Specifically, it collects and processes relevant news and data. Because the amount of information generated is large, it is passed to a summarization engine (e.g., GPT-4's summarization function) to create a concise summary with the key points extracted. Based on sentiment data, the content and format of the summary are adjusted; for example, if the user is excited, a summary containing more detailed technical information is provided.

[0276] The following are specific examples of prompt statements for a generative AI model:

[0277] "Research the new product information for 2023 and create a summary that includes detailed technical information suitable for users who are excited about the product."

[0278] The generated summary information is stored by the server in a database (e.g., MySQL). After saving, the server sends the summary information back to the terminal, which converts the received summary information into a display format and presents it to the user. For example, it might display "A new smartphone will be released in 2023."

[0279] After a certain period of time has passed, or if a user requests reconfirmation, the server checks for updates to the information. In this process, generative artificial intelligence (e.g., OpenAI GPT-4) is used to retrieve the latest relevant information and compare it with existing information in the database. For example, if the original information was "A new smartphone will be released in 2023," and an update is found later stating "A new color has been added," the server will record this information in the database and update it.

[0280] When an update is confirmed, the server sends the update information to the terminal, and the terminal notifies the user of the update information at an appropriate timing and style based on the emotion data. As an example, "The information of the new smartphone has been updated: A new color has been added" is displayed on the screen. At this time, if the user is happy, it is displayed in a bright design.

[0281] Thus, according to the present invention, it is possible to provide information adapted to the emotional state of the user, and the entire system can provide a more personalized information experience.

[0282] The flow of the specific process in Example 2 will be described with reference to FIG. 13.

[0283] Step 1:

[0284] The user inputs an information acquisition request. For example, the request is input in voice or text such as "I want to know the information of new products in 2023". This request becomes the input data of the system.

[0285] Step 2:

[0286] The terminal collects the request and emotion data. After receiving the user's input, the emotion engine (e.g., natural language processing algorithm) is used to analyze the user's voice tone and text content, and emotion data such as joy, sadness, anger, and anxiety is obtained. The input data is the user's request and emotional state, and the output data is the analyzed emotion information.

[0287] Step 3:

[0288] The terminal sends the request and emotion data to the server. The obtained request and emotion data are converted into JSON format and sent to the server using the HTTPS protocol. The input data is the request and emotion information, and the output data is the notification of the completion of transmission to the server.

[0289] Step 4:

[0290] The server parses the request. It analyzes the received request using a natural language processing engine (e.g., SpaCy) and extracts necessary keywords (e.g., "2023", "new product"). The input data is the request data in JSON format, and the output data is the extracted keywords.

[0291] Step 5:

[0292] The server generates information using generative artificial intelligence. Generative AI such as GPT-4 is used to generate relevant information based on extracted keywords. In this process, relevant news and data are collected and processed. The input data consists of extracted keywords, and the output data consists of the generated information.

[0293] Step 6:

[0294] The server summarizes the generated information. The generated information is passed to a summarization engine (e.g., GPT-4's summarization function), which extracts key points and creates a concise summary. The input data is the generated information, and the output data is the summary. This summary is adjusted based on sentiment data. For example, if the user is excited, the summary will include more technical details.

[0295] Step 7:

[0296] The server saves summary information to the database. The summary information and identification information such as the request ID are saved to the database (e.g., MySQL). The input data consists of the summary information and identification information, while the output data is a notification that the database save is complete.

[0297] Step 8:

[0298] The server sends summary information back to the terminal. The summary information stored in the database is sent to the terminal using the HTTPS protocol. The input data is the summary information, and the output data is a notification that transmission to the terminal is complete.

[0299] Step 9:

[0300] The terminal displays the summary information in an appropriate format. It converts the received summary information into a format for display on the user interface. For example, it explicitly displays on the screen information such as "A new smartphone will be released in 2023". The input data is the summary information from the server, and the output data is the display on the user interface.

[0301] Step 10:

[0302] The server periodically checks for information updates. After a certain period has elapsed, or when there is a reconfirmation request from the user, it uses generative artificial intelligence to obtain the latest relevant information and compares it with the existing information. The input data is the existing information in the database, and the output data is the presence or absence of updates and new information.

[0303] Step 11:

[0304] The server saves the updated information to the database. If new information is found, it saves it to the database and updates the existing information. The input data is the new information, and the output data is a notification of successful saving to the database.

[0305] Step 12:

[0306] The server sends the updated information to the terminal. It sends the updated information to the terminal using the HTTPS protocol. The input data is the updated information, and the output data is a notification of successful sending to the terminal.

[0307] Step 13:

[0308] The terminal notifies the user of the updated information. It converts the received updated information into a display format suitable for the user and notifies the user. For example, it displays on the screen "The information about the new smartphone has been updated: A new color has been added". At this time, it adjusts the display style based on the emotion data. For example, if the user is happy, it displays in a bright design. The input data is the updated information, and the output data is a notification to the user interface.

[0309] (Application Example 2)

[0310] 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".

[0311] Conventional electronic payment systems have a problem in that information provision based on user requests is one-way, and they cannot provide personalized advice or notifications that are tailored to the user's emotions or state. Furthermore, when users make electronic payments while experiencing various emotional states such as anxiety or excitement, they are not provided with spending management or campaign information that is adapted to their emotions, resulting in a poor user experience. The present invention aims to solve these problems and realize personalized information provision that is adapted to the user's emotions.

[0312] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for receiving user requests, means for generating information based on the request using generative artificial intelligence, means for summarizing the generated information and storing it in a database, means for returning the stored summary information to the user, means for periodically checking for updates to the information, means for generating the updated information using the generative artificial intelligence and updating the database, means for notifying the user of the updated information, means including an emotion engine for analyzing the user's emotions, and means for personalizing the summary information and notification content based on the emotion data. This makes it possible to provide expenditure management advice and campaign information notifications adapted to the user's emotional state.

[0313] A "user request" is a specific instruction or inquiry from a user requesting information from the system.

[0314] "Generative artificial intelligence" refers to artificial intelligence technology used to generate information based on user requests.

[0315] A "database" is a repository of information that stores information and summaries generated within a system, making it accessible and updatable at a later date.

[0316] An "emotion engine" is an engine that analyzes emotional data from a user's voice and text to identify the user's emotional state.

[0317] "Personalization" refers to adjusting the content of information and notifications according to the individual characteristics and circumstances of each user.

[0318] A "request ID" is an identifier used to uniquely identify each user request.

[0319] A "summarization engine" is an engine that extracts important points from generated information and creates a concise summary.

[0320] "Update information" refers to information that has been generated and saved once, and is regenerated to show subsequent changes or additions.

[0321] A "notification" is a message or alert used to inform users of updates or important information.

[0322] This invention relates to an electronic payment system that provides personalized information in response to the user's emotions. The system includes multiple means to receive user requests, generate information using generative artificial intelligence, and summarize, store, and update that information. It then provides information based on the user's emotions.

[0323] First, the user enters a request for information retrieval into the device using their smartphone. For example, when a user enters a request such as "I'm worried about how I've been spending money lately" via voice or text, the emotion engine analyzes emotional data from the user's voice tone and the content of the text message. As a result of the analysis, an emotional state such as joy, sadness, anger, or anxiety is identified.

[0324] Next, the terminal retrieves the user's request and sentiment data, converts it into an appropriate format, and sends it to the server. The server receives the request and sentiment data, analyzes the request content, and extracts necessary keywords. For example, keywords such as "recently," "money," and "worry."

[0325] The server generates information based on keywords extracted using generative artificial intelligence. For example, it collects and processes relevant news and spending advice. The large amount of generated information is then passed to a summarization engine, where key points are extracted and a concise summary is created. The content and format of the summary are adjusted based on information analyzed from sentiment data. For instance, if the user is feeling anxious, advice on reducing spending might be provided.

[0326] The server saves the generated summary information and identification information such as the request ID to a database. After saving, the server sends the summary information back to the terminal. The terminal converts the received summary information into a display format and presents it to the user. For example, it might display "Are you okay? Here are some tips for managing your spending: The best way to manage your spending is to set a budget," in a format that suits the user's mood.

[0327] After a certain period of time has passed, or if the user requests reconfirmation, the server checks for updates to the information. It uses generative artificial intelligence again to retrieve the latest relevant information and compares it with the existing information in the database. For example, if the original information was "Tips for managing your expenses," and then an update is found such as "A new expense management app is out," the server records this information in the database and updates it. Once the update is confirmed, the server sends the update information to the device, and the device notifies the user of the update information at an appropriate time and in an appropriate style based on sentiment data. For example, "A new expense management app is out" might be displayed on the screen. In this case, if the user is happy, it will be displayed in a bright design.

[0328] As a concrete example, if the user input is "I'm worried about how I've been spending money lately," the prompt message from the generating AI model would be as follows:

[0329] "Analyze the sentiment of this text: I'm worried about how I've been spending money lately."

[0330] This enables the delivery of personalized information that matches the user's emotions. The entire system is designed to improve the user experience.

[0331] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0332] Step 1:

[0333] The user enters an information request using their smartphone. The input can be via voice or text, and may be a specific request such as "I'm worried about how I've been spending money lately." The input data (voice or text) is sent to an emotion engine, which analyzes the user's emotional state (joy, sadness, anger, anxiety, etc.). The results of this analysis are obtained as emotion data. The input data is the user's request, and the output data is the emotion data.

[0334] Step 2:

[0335] The device sends the user's request and sentiment data to the server. The server receives the request and sentiment data, analyzes the request, and extracts necessary keywords. For example, it might extract keywords such as "recently," "money," and "worry." This analysis is performed using natural language processing techniques. The input data consists of the request and sentiment data, and the output data consists of the extracted keywords.

[0336] Step 3:

[0337] The server generates information based on keywords extracted using generative artificial intelligence. Specifically, it collects relevant news and expense management advice, and generates information using generative artificial intelligence (e.g., GPT-3®). The input data is the extracted keywords, and the output data is the generated information.

[0338] Step 4:

[0339] The server passes the generated information to the summarization engine, which extracts key points and creates a concise summary. The summary content and format are adjusted based on sentiment data. For example, if the user is feeling anxious, the generated summary will contain more advice on reducing spending. The input data consists of the generated information and sentiment data, while the output data is the summarized information.

[0340] Step 5:

[0341] The server saves summary information and identification information such as the request ID to the database. The input data is the summary information and the request ID, and the output data is a notification that the data has been saved to the database.

[0342] Step 6:

[0343] The server sends summary information back to the terminal. The terminal converts the received summary information into a display format and presents it to the user. The information is displayed in a format that suits the user's mood. The input data is summary information, and the output data is the information presented to the user.

[0344] Step 7:

[0345] The server checks for updates to information after a certain period of time has elapsed or when a user requests reconfirmation. Generative artificial intelligence is used to retrieve the latest relevant information and compare it with existing information in the database. Input data is the reconfirmation request or notification of the elapsed period, and output data is the updated information.

[0346] Step 8:

[0347] The server notifies the user of update information. The device notifies the user of the update information at the appropriate time and in the appropriate style based on sentiment data. For example, a notification such as "A new expense management app is available" might be sent. In this case, if the user is happy, it will be displayed in a bright design. The input data is the update information, and the output data is the information that is notified to the user.

[0348] 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.

[0349] 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.

[0350] 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.

[0351] [Second Embodiment]

[0352] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0353] 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.

[0354] 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).

[0355] 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.

[0356] 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.

[0357] 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).

[0358] 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.

[0359] 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.

[0360] 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.

[0361] 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.

[0362] 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.

[0363] 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".

[0364] This invention relates to a system that generates information based on user requests, summarizes and stores it, periodically checks for updates, and notifies the user if updates are found. The program of this system consists of the functions and roles of the server, terminal, and user.

[0365] Processing user requests

[0366] First, if a user wants to obtain specific information, they input a request into the terminal via voice or text, such as "Please tell me about new products for 2023." The terminal receives this request, converts it to the appropriate format, and sends it to the server. At this stage, the user's input becomes the key to identifying what information the system as a whole needs to generate.

[0367] Information generation and summarization

[0368] The server analyzes the received request and extracts necessary keywords and context. For example, if the request is for "new product information for 2023," it will extract keywords such as "2023" and "new products." Based on this analysis, the server uses generative artificial intelligence to generate relevant data.

[0369] Because the generated information often contains a large amount of data, the server uses a summarization engine to make the information concise. This results in summaries such as, "A new smartphone will be released in 2023, and that model will feature the latest processor."

[0370] Saving summary information and returning it to the user.

[0371] Next, the server saves the generated summary information to the database. This saving process also saves identifying information such as the request ID, making it easy to re-verify and update later. After saving, the server sends the saved summary information back to the terminal. The terminal receives this information, converts it into a display format, and presents it to the user.

[0372] Information update check and notification

[0373] After a certain period of time has passed, or if a manual check is requested, the server will perform an update check on the information. This involves using generative artificial intelligence again to retrieve new relevant information and comparing it with the existing information in the database. For example, if the original information was "A new smartphone will be released in 2023," and then an update is found stating "A new color has been added," the server will update the database with this information.

[0374] When an update is detected, the server sends the update information to the device, and the device uses its notification function to inform the user of the update. In this way, users can always efficiently obtain the latest information.

[0375] For example, if a user requests "Please tell me about new products for 2023," the server generates the latest information and provides the user with a summary such as "A new smartphone will be released in September 2023." Then, after a few months, if the user sends a follow-up request, the server retrieves the latest information again and notifies the user of updates such as "A new color has been added to the new smartphone." This ensures that the user always has the most up-to-date information.

[0376] Through the above program and process, the present invention provides a system that efficiently generates, summarizes, updates, and automatically notifies users of the information they request.

[0377] The following describes the processing flow.

[0378] Step 1:

[0379] The user enters their information retrieval request into the device. For example, they might enter a request such as "Please tell me about new products for 2023" via voice or text.

[0380] Step 2:

[0381] The terminal receives the user's request, converts it into the appropriate format, and sends it to the server. During this process, the request is formatted to ensure accurate transmission of its contents.

[0382] Step 3:

[0383] The server receives the request and parses it. It extracts keywords such as "2023" and "new product" from the request. This identifies what information should be generated.

[0384] Step 4:

[0385] The server uses generative artificial intelligence to generate information based on extracted keywords. For example, it collects and processes relevant data from related news articles and databases.

[0386] Step 5:

[0387] The server passes the large amount of generated information to the summarization engine. The summarization engine extracts the key points and creates a concise summary. For example, it might generate a summary such as, "A new smartphone will be released in 2023, featuring the latest processor."

[0388] Step 6:

[0389] The server stores the generated summary information and identification information such as the request ID in a database. This allows for later update checks and re-verification.

[0390] Step 7:

[0391] The server returns the stored summary information to the terminal. The information returned includes a summary of what the user requested.

[0392] Step 8:

[0393] The device receives summary information, converts it into a display format, and presents it to the user. For example, the device screen might display "A new smartphone will be released in 2023."

[0394] Step 9:

[0395] After a certain period, or upon a user request for reconfirmation, the server checks for updates to the information. It then uses generative artificial intelligence again to retrieve the latest relevant information.

[0396] Step 10:

[0397] The server compares the newly retrieved information with existing information in the database to check for updates. For example, it checks if there is new information such as "a new color has been added."

[0398] Step 11:

[0399] When an update is detected, the server updates the corresponding entry in the database and sends the update information to the terminal. This ensures that the information in the database remains up-to-date.

[0400] Step 12:

[0401] The device receives update information and notifies the user. For example, the screen might display, "New smartphone information has been updated: New colors have been added."

[0402] In this way, users can always obtain the latest information, and the entire system operates efficiently and accurately.

[0403] (Example 1)

[0404] 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."

[0405] Conventional information acquisition systems have faced challenges in providing users with the information they need appropriately and quickly, and in notifying users in a timely manner when information is updated. Furthermore, when the amount of information generated is large, users may spend a considerable amount of time finding the information they need. To solve these problems, a system is needed that generates relevant information based on user requests, summarizes and efficiently manages that information, and immediately notifies users when it is updated.

[0406] 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.

[0407] In this invention, the server includes means for receiving a user request, converting the request into an appropriate format and sending it to the server; means for generating information based on the request using generative artificial intelligence; and means for summarizing the generated information and storing it in a database. This allows the user to efficiently obtain the necessary information and receive updated information quickly.

[0408] "User" refers to an individual or organization that wishes to obtain information.

[0409] A "request" refers to a voice or text instruction that a user enters through their device to ask for information.

[0410] A "terminal" refers to an electronic device used by a user to enter requests and receive information.

[0411] A "server" refers to a computer system that processes user requests and is responsible for generating, summarizing, storing, updating, and notifying information.

[0412] "Generative artificial intelligence" refers to an algorithm or model that generates information based on input prompts.

[0413] A "prompt message" refers to a sentence that is input to a generative artificial intelligence system to generate information.

[0414] A "summary" refers to a concise compilation of information, extracting the most important parts from the generated data.

[0415] A "database" refers to a system for storing generated summary information and related data.

[0416] "Update" refers to the addition or modification of new information to the generated information.

[0417] "Notification" refers to the act of informing a user that information has been updated.

[0418] This invention relates to a system that generates information based on user requests, summarizes and stores it, periodically checks for updates, and notifies the user if updates are found. This system is composed of the functions and roles of a server, a terminal, and a user.

[0419] Processing user requests

[0420] First, if a user wants to obtain specific information, they input a request into the terminal via voice or text, such as "Please tell me about new products for 2023." The terminal receives this request, converts it to an appropriate format (e.g., JSON), and sends it to the server. At this stage, the user's input becomes the key to identifying what information the system as a whole needs to generate.

[0421] Information generation and summarization

[0422] The server analyzes the received request and extracts necessary keywords and context. For example, if the request is for "new product information for 2023," it will extract keywords such as "2023" and "new products." Based on this analysis, the server uses generative artificial intelligence (e.g., OpenAI GPT-4) to generate relevant data.

[0423] Because the generated information often contains a large amount of data, the server uses a summarization engine (e.g., BERT) to simplify the information. This results in summaries such as, "A new smartphone will be released in 2023, and that model will feature the latest processor."

[0424] Saving summary information and returning it to the user.

[0425] Next, the server saves the generated summary information to the database. This saving process also saves identifying information such as the request ID, making it easy to re-verify and update later. After saving, the server sends the saved summary information back to the terminal. The terminal receives this information, converts it into a display format, and presents it to the user.

[0426] Information update check and notification

[0427] After a certain period of time has passed, or if a manual check is requested, the server will perform an update check on the information. This involves using generative artificial intelligence again to retrieve new relevant information and comparing it with the existing information in the database. For example, if the original information was "A new smartphone will be released in 2023," and then an update is found stating "A new color has been added," the server will update the database with this information.

[0428] When an update is detected, the server sends the update information to the device, and the device uses its notification function to inform the user of the update. In this way, users can always efficiently obtain the latest information.

[0429] Examples of specific cases and prompt statements

[0430] For example, if a user requests "Please tell me about new products for 2023," the server generates the latest information and provides the user with a summary such as "A new smartphone will be released in September 2023." Then, after a few months, if the user sends a follow-up request, the server retrieves the latest information again and notifies the user of updates such as "A new color has been added to the new smartphone." This ensures that the user always has the most up-to-date information.

[0431] Example of a prompt:

[0432] "Please tell me about new product information for 2023."

[0433] The above describes the specific forms for carrying out the invention.

[0434] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0435] Step 1:

[0436] When a user wants to obtain specific information, they enter a request into the terminal, such as "Please tell me about new products for 2023." The input format is either voice or text. Input: User's voice or text request. Output: Request as text data.

[0437] Step 2:

[0438] The terminal receives a request from the user and converts it into a format that can be processed (e.g., JSON). After converting to the appropriate data format, the terminal sends this data to the server over the internet. Input: User request in text format. Output: Data in JSON format.

[0439] Step 3:

[0440] The server analyzes the received request data and extracts the necessary keywords and context. Specifically, the server uses natural language processing to extract keywords such as "2023" and "new products" from a request like "new product information for 2023". Input: Request data in JSON format. Output: Extracted keywords and context information.

[0441] Step 4:

[0442] The server uses generative artificial intelligence (e.g., a generative AI model) to generate information based on the extracted keywords. In this process, it generates a prompt and inputs it into the generative AI model. For example, it might create a prompt such as "Please provide the latest information on new products for 2023" and input it into the generative AI model. Input: Extracted keywords and contextual information. Output: Generated information.

[0443] Step 5:

[0444] If the amount of information generated is large, the server uses a summarization engine (e.g., BERT) to summarize the information. For example, it might create a summary such as, "A new smartphone will be released in 2023, and this model will feature the latest processor." Input: Generated information. Output: Summarized information.

[0445] Step 6:

[0446] The server saves the summarized information to the database. The request ID and user ID are also saved at this time to allow for easy retrieval of the information later. Input: Summarized information. Output: Information saved in the database.

[0447] Step 7:

[0448] The server resends the saved summary information to the terminal. The terminal converts the received information into a display format and presents it to the user. Input: Summary information stored in the database. Output: Information presented to the user.

[0449] Step 8:

[0450] After a certain period of time has passed, or when a user submits a reconfirmation request, the server checks for updates to the information. It uses the generative AI model again to retrieve new relevant information and compares it to existing information in the database. Input: User reconfirmation request or timer event. Output: New relevant information.

[0451] Step 9:

[0452] The server compares the new update information with existing information in the database. Once an update is confirmed, it sends the information to the terminal, which then uses its notification function to inform the user of the update. Input: New related information. Output: Update notification to the user.

[0453] The above describes the specific processing steps of the program in this system.

[0454] (Application Example 1)

[0455] 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."

[0456] For modern users, staying up-to-date on the latest information about products and services they are interested in is crucial. However, quickly and accurately obtaining the latest information from a vast amount of data, and regularly checking for updates, is difficult. Furthermore, acquiring information from diverse sources and ensuring its accuracy is also a challenge. In this situation, there is a need for a system that allows users to efficiently and reliably obtain the latest information they require.

[0457] 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.

[0458] In this invention, the server includes means for receiving user requests, means for generating information based on requests using generative artificial intelligence, means for summarizing the generated information and storing it in a database, means for returning the stored summary information to the user, means for periodically checking for updates to the information, means for generating updated information using generative artificial intelligence and updating the database, means for notifying the terminal when the latest information is generated, means for sending a prompt message to the generative artificial intelligence, means for generating relevant information based on product categories, and means for displaying the latest information to the user. As a result, the user can always quickly and reliably obtain the latest information on products of interest and automatically receive update information.

[0459] "Means of receiving user requests" refers to an interface that allows users to input specific information and the functionality of the system that processes that input.

[0460] "Generative artificial intelligence" refers to artificial intelligence technology that has the ability to generate relevant information based on input data.

[0461] "Means for summarizing information and storing it in a database" refers to the functions of a storage device and system for converting generated information into a concise format and accumulating that summarized information.

[0462] "Means for returning saved summary information to the user" refers to a system function that retrieves summary information stored in a database and provides it to the user.

[0463] "Means of regularly checking for updates to information" refers to a system function that checks at regular intervals whether the stored information is up-to-date.

[0464] "A means of generating update information and updating a database using generative artificial intelligence" refers to a system function that uses artificial intelligence technology to generate new information and replace existing information in a database with it.

[0465] "Means of notifying the device when new information is generated" refers to a system function that sends a notification to the user's device when new information is generated.

[0466] "Means for sending prompt messages to a generative artificial intelligence" refers to a function of a system that inputs instruction messages for information generation to a generative artificial intelligence.

[0467] "Means for generating relevant information based on product categories" refers to a system function that acquires and generates relevant information based on product categories that the user is interested in.

[0468] "Means of displaying the latest information to the user" refers to a system function that displays the generated latest information on the user's interface.

[0469] To implement this invention, a system is required in which a server, a terminal, and a user each have their own respective roles.

[0470] Processing user requests

[0471] First, if a user wants to obtain specific information, they enter a request through a smartphone application, such as "Please tell me the information about the new smartphone." This request is received by the device, converted into the appropriate format, and sent to the server.

[0472] Information generation and summarization

[0473] The server analyzes the received request and extracts necessary keywords and context. For example, if the request is for "information on a new smartphone," keywords such as "smartphone" and "new" will be extracted. Based on this analysis, the server uses a generative AI model (e.g., GPT-4) to generate relevant information. Because the generated information may be complex, the server uses a summarization engine (e.g., PEGASUS) to create a concise summary.

[0474] Saving summary information and returning it to the user.

[0475] The server saves the summarized information to a database. At this stage, the request ID and related metadata are also saved, making it easier to review and check for updates later. The saved information is sent back to the user's terminal, which then displays it to the user.

[0476] Information update check and notification

[0477] After a certain period of time, or when a manual check is requested, the server performs an information update check. It uses the generated AI model again to retrieve new relevant information and compares it with existing information in the database. If an update is found, the database is updated, and the server sends the update to the user's terminal. The terminal then notifies the user of the latest information.

[0478] Hardware and software usage

[0479] This system uses devices such as smartphones and tablets, centralized cloud servers (e.g., AWS, Google Cloud), and generative AI models (e.g., GPT-4) and summarization engines (e.g., PEGASUS).

[0480] Specific example

[0481] When a user enters a request into the application, such as "Please tell me about the new smartphone," the server receives the request and uses a generative AI model to generate information such as, "A new smartphone is scheduled to be released in 2023. This model will feature the latest processor and enhanced camera capabilities." This information is then summarized concisely by a summarizing engine and stored in a database. When the information is updated, the server notifies the user's device of the new information, such as, "A new color has since been added." A concrete example of a prompt sent to the generative AI model is, "Please tell me about the new smartphone coming in 2023."

[0482] This system allows users to efficiently obtain the latest and most accurate information.

[0483] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0484] Step 1:

[0485] The user opens a smartphone application and enters a specific information request (e.g., "Please tell me information about my new smartphone") via voice or text.

[0486] Input: User's voice or text request

[0487] Output: Formatted request data sent to the terminal

[0488] Operation: The application converts the user's speech into text (using speech recognition software) and then converts the acquired text data into an appropriate format.

[0489] Step 2:

[0490] The terminal sends the formatted request data to the server.

[0491] Input: Formatted request data

[0492] Output: Request data sent to the server

[0493] Operation: The terminal sends the request data to the server as an HTTP request and waits for a response.

[0494] Step 3:

[0495] The server receives and parses the request data. Specifically, it extracts necessary keywords and context from the request.

[0496] Input: Request data sent to the server

[0497] Output: Extracted keywords and contextual information

[0498] Operation: The analysis engine on the server (using natural language processing software) analyzes the data and extracts keywords and context.

[0499] Step 4:

[0500] The server uses a generative AI model (e.g., GPT-4) to generate relevant information based on extracted keywords and context.

[0501] Input: Extracted keywords and contextual information

[0502] Output: Generated information

[0503] Operation: Input prompts into the generative AI model and retrieve the generated information.

[0504] Step 5:

[0505] If the generated information is complex, the server uses a summarization engine (e.g., PEGASUS) to create a concise summary.

[0506] Input: Generated details

[0507] Output: Summarized information

[0508] Operation: Starts the summarization engine and creates a concise summary using the generated information as input.

[0509] Step 6:

[0510] The server stores the summarized information in the database.

[0511] Input: Summarized information, request ID, related metadata

[0512] Output: Summary information stored in the database

[0513] Function: Saves summary information to a database management system (e.g., MySQL).

[0514] Step 7:

[0515] The server sends the saved summary information back to the terminal.

[0516] Input: Summary information stored in the database

[0517] Output: Summary information sent to the terminal

[0518] Operation: Sends summary information to the terminal as an HTTP response.

[0519] Step 8:

[0520] The terminal displays the returned summary information to the user.

[0521] Input: Summary information sent from the server

[0522] Output: Summary information displayed to the user

[0523] Operation: The application displays the received summary information in the user interface.

[0524] Step 9:

[0525] The server periodically checks for updates to the information, and if new information is available, it reuses the generated AI model to retrieve the relevant information.

[0526] Input: Time interval for periodic checks, existing information

[0527] Output: New generated information

[0528] Operation: Sends an update request to the generative AI model and generates new information.

[0529] Step 10:

[0530] The server compares new information with existing information and updates the database if there are any differences.

[0531] Input: New generated information, existing information

[0532] Output: Updated database

[0533] Operation: Compares new information with existing information and updates the database if differences are detected.

[0534] Step 11:

[0535] When the server detects an information update, it notifies the user's device of the update details.

[0536] Input: Update details

[0537] Output: Notification to user terminal

[0538] Operation: Notifies the user's terminal of the latest information using the notification system.

[0539] A concrete example of a prompt is, "Please tell me about the new smartphone." This prompt prompt prompts the AI ​​model to generate the latest relevant information.

[0540] 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.

[0541] This invention provides a system that generates information based on user requests, summarizes and stores it, periodically checks for updates, and notifies the user if updates are found, in addition to utilizing an emotion engine that recognizes the user's emotions. The program of this system is composed of the functions and roles of the server, terminal, and user.

[0542] User request processing and sentiment recognition

[0543] First, the user enters a request for information into the device. For example, when a user enters a request such as "Please tell me about new products for 2023" via voice or text, the emotion engine analyzes emotional data from the user's voice tone and the content of the text message. It identifies emotional states such as joy, sadness, anger, and anxiety.

[0544] Information generation and summarization

[0545] The terminal retrieves user requests and sentiment data, converts them into an appropriate format, and sends them to the server. The server receives the requests and sentiment data, analyzes the request content, and extracts necessary keywords, such as "2023" and "new product."

[0546] Next, the server generates information based on keywords extracted using generative artificial intelligence. For example, it collects and processes relevant news and data. The large amount of generated information is then passed to a summarization engine, where key points are extracted and a concise summary is created. The content and format of the summary are adjusted based on information analyzed from sentiment data. For instance, if the user is excited, a summary containing more detailed technical information might be provided.

[0547] Saving summary information and returning it to the user.

[0548] The server saves the generated summary information and identification information such as the request ID to a database. After saving, the server sends the summary information back to the terminal. The terminal converts the received summary information into a display format and presents it to the user. For example, it might display "A new smartphone will be released in 2023" in a format that suits the user's mood.

[0549] Information update check and notification

[0550] After a certain period of time has passed, or if a user requests reconfirmation, the server checks for updates to the information. It uses generative artificial intelligence again to retrieve the latest relevant information and compares it with the existing information in the database. For example, if the original information was "A new smartphone will be released in 2023," and then an update is found such as "A new color has been added," the server will record this information in the database and update it.

[0551] Once an update is detected, the server sends the update information to the device, and the device notifies the user of the update at the appropriate time and in the appropriate style based on sentiment data. For example, it might display on the screen, "New smartphone information has been updated: New colors have been added." If the user is happy, the message will be displayed in a bright design.

[0552] By combining these emotion engines, it becomes possible to provide information that adapts to the user's emotional state, enabling the entire system to deliver a more personalized information experience.

[0553] The following describes the processing flow.

[0554] Step 1:

[0555] The user enters a request for information into the device. For example, they might enter a request such as "Please tell me about new products for 2023" via voice or text. During this process, the device collects emotional data from the user's voice tone and the nuances of their text.

[0556] Step 2:

[0557] The terminal retrieves the user's request and sentiment data, converts it into the appropriate format, and sends it to the server. The formatting ensures that the request and sentiment data are accurately conveyed.

[0558] Step 3:

[0559] The server receives the request and analyzes it. Keywords such as "2023" and "new product" are extracted from the request. At the same time, emotional data is analyzed to identify the user's emotional state. This analysis determines whether the user is excited, calm, anxious, etc.

[0560] Step 4:

[0561] The server uses generative artificial intelligence to generate information based on extracted keywords. For example, it collects relevant data from news articles and databases and generates information based on that data. Sentimental data is also taken into consideration when generating the information.

[0562] Step 5:

[0563] The server passes the large amount of generated information to the summarization engine. The summarization engine extracts the key points and creates a concise summary. Based on sentiment data, the content and format of the summary are adjusted. For example, if the user is excited, a summary containing more detailed technical information will be provided.

[0564] Step 6:

[0565] The server stores the generated summary information and identification information such as the request ID in a database. This makes it easy to perform update checks and re-verifications later.

[0566] Step 7:

[0567] The server sends the saved summary information back to the terminal. The terminal receives the summary information, converts it into a display format, and presents it to the user. For example, it might display "A new smartphone will be released in 2023" in a format that suits the user's mood.

[0568] Step 8:

[0569] After a certain period, or upon a user request for reconfirmation, the server checks for updates to the information. It then uses generative artificial intelligence again to retrieve the latest relevant information.

[0570] Step 9:

[0571] The server compares the newly retrieved information with existing information in the database to check for updates. For example, it checks for new information such as "a new color has been added."

[0572] Step 10:

[0573] When an update is detected, the server updates the corresponding entry in the database and sends the update information to the terminal. This ensures that the information in the database is always up-to-date.

[0574] Step 11:

[0575] The device receives update information and notifies the user. For example, it might display "New smartphone information has been updated: New colors have been added" on the screen. When a notification is displayed, the display method is adjusted according to the user's emotions; for example, a brighter design is used if the user is happy.

[0576] In this way, it becomes possible to recognize the user's emotions and provide information that is adapted to them, thereby improving the user experience.

[0577] (Example 2)

[0578] 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".

[0579] Traditional information delivery systems often failed to consider user emotions, resulting in a lack of information tailored to user needs and inappropriate presentation methods. Furthermore, the generated information was not frequently updated, making it difficult for users to access the latest information. Accuracy was also a challenge, as data collection from reliable external sources was insufficient.

[0580] 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.

[0581] In this invention, the server includes means for receiving user requests, means for analyzing requests and collecting sentiment data, means for generating information based on the requests and sentiment data using generative artificial intelligence, means for summarizing the generated information, means for storing the summarized information in a database, means for returning the stored summarized information to the user, means for periodically checking for updates to the stored information, means for generating the updated information using the generative artificial intelligence and updating the database, and means for notifying the user of the updated information. This enables the provision of information adapted to the user's emotions and allows the user to be provided with the latest information that is updated regularly. Furthermore, the accuracy of the information provided is enhanced by collecting data from reliable external sources.

[0582] "Means for receiving user requests" refers to devices or interfaces for receiving information retrieval requests from users. Specifically, this refers to voice input devices and text input interfaces.

[0583] "Means for analyzing requests and collecting sentiment data" refers to a system that analyzes the content of a user's request and collects the user's emotional state from the tone of voice and text content at that time. Specifically, it uses a natural language processing engine and sentiment analysis algorithm.

[0584] "Means for generating information based on the aforementioned request and sentiment data using generative artificial intelligence" refers to a technology for generating relevant information based on user requests and sentiment data using generative artificial intelligence. Specifically, it refers to a generative AI model.

[0585] "Methods for summarizing generated information" refer to techniques for extracting important parts from large amounts of generated information and creating a concise summary. This utilizes the summarization capabilities of generative artificial intelligence.

[0586] "Means for storing summarized information in a database" refers to a device or system that records and stores summarized information and associated identification information in a database. Specifically, it refers to a database management system.

[0587] "Means for returning stored summary information to the user" refers to means for notifying or providing stored summary information to the user. Specifically, it refers to servers or interfaces that transmit information over a network.

[0588] "Means for periodically checking for updates to stored information" refers to technologies for periodically verifying whether stored information is up-to-date. Specifically, this refers to scheduling systems and information gathering engines.

[0589] "Means for generating the update information and updating the database using the generative artificial intelligence" refers to a technology for generating new information and updating existing database information using generative artificial intelligence.

[0590] "Means of notifying users of updates" refers to means of informing users of updates when information is updated. Specifically, this refers to notification systems and alert functions.

[0591] "Means for receiving requests for information reconfirmation" refers to devices or interfaces for receiving reconfirmation requests from users.

[0592] "Means for sending the reconfirmation request to the generative artificial intelligence and comparing it with the existing information" refers to a technique for sending a reconfirmation request to the generative artificial intelligence and comparing the new information with the existing information.

[0593] "Means for generating new summary information when an update is detected" refers to means for generating new summary information when it is confirmed that the information has been updated.

[0594] "Means of improving the accuracy of generated information by acquiring information from generative artificial intelligence and reliable external sources" refers to technologies that use generative artificial intelligence and collect information from reliable external data sources to improve the accuracy of the information provided.

[0595] This invention is an information provision system that generates information based on user requests, summarizes and stores it, periodically checks for updates, and notifies the user if there are any updates. Furthermore, by incorporating an emotion engine that recognizes the user's emotional state, the system achieves more appropriate and personalized information provision. This invention is composed of the functions and roles of the server, terminal, and user.

[0596] First, the user enters a request for information into the device. For example, if the user enters a request such as "Please tell me about new products for 2023" via voice or text, the emotion engine analyzes emotional data from the user's voice tone and the content of the text message. The emotion engine uses an emotion analysis algorithm and a natural language processing engine (e.g., Microsoft Azure Cognitive Services). This engine identifies emotional states such as joy, sadness, anger, and anxiety.

[0597] Next, the terminal retrieves the user's request and sentiment data, converts it into an appropriate format, and sends it to the server. At this stage, the JSON format is used as the data conversion method, and it is sent via the HTTPS protocol.

[0598] The server analyzes the received request and sentiment data to extract necessary keywords. For example, a natural language processing engine (e.g., SpaCy) is used to identify the keywords "2023" and "new product." Then, a generative artificial intelligence (e.g., OpenAI GPT-4) is used to generate information based on the extracted keywords. Specifically, it collects and processes relevant news and data. Because the amount of information generated is large, it is passed to a summarization engine (e.g., GPT-4's summarization function) to create a concise summary with the key points extracted. Based on sentiment data, the content and format of the summary are adjusted; for example, if the user is excited, a summary containing more detailed technical information is provided.

[0599] The following are specific examples of prompt statements for a generative AI model:

[0600] "Research the new product information for 2023 and create a summary that includes detailed technical information suitable for users who are excited about the product."

[0601] The generated summary information is stored by the server in a database (e.g., MySQL). After saving, the server sends the summary information back to the terminal, which converts the received summary information into a display format and presents it to the user. For example, it might display "A new smartphone will be released in 2023."

[0602] After a certain period of time has passed, or if a user requests reconfirmation, the server checks for updates to the information. In this process, generative artificial intelligence (e.g., OpenAI GPT-4) is used to retrieve the latest relevant information and compare it with existing information in the database. For example, if the original information was "A new smartphone will be released in 2023," and an update is found later stating "A new color has been added," the server will record this information in the database and update it.

[0603] Once an update is detected, the server sends the update information to the device, and the device notifies the user of the update at the appropriate time and in the appropriate style based on sentiment data. For example, the screen might display, "New smartphone information has been updated: New colors have been added." If the user is happy, the message will be displayed in a bright design.

[0604] Thus, the present invention makes it possible to provide information that is adapted to the user's emotional state, enabling the entire system to provide a more personalized information experience.

[0605] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0606] Step 1:

[0607] The user enters an information retrieval request. For example, they might enter a request via voice or text, such as, "Please tell me about new products for 2023." This request becomes the input data for the system.

[0608] Step 2:

[0609] The device collects requests and emotional data. After receiving user input, it uses an emotion engine (e.g., a natural language processing algorithm) to analyze the user's voice tone and text content to obtain emotional data such as joy, sadness, anger, and anxiety. The input data consists of the user's request and emotional state, while the output data is the analyzed emotional information.

[0610] Step 3:

[0611] The device sends the request and sentiment data to the server. The retrieved request and sentiment data are converted to JSON format and sent to the server using the HTTPS protocol. The input data consists of the request and sentiment information, and the output data is a notification that the transmission to the server is complete.

[0612] Step 4:

[0613] The server parses the request. It analyzes the received request using a natural language processing engine (e.g., SpaCy) and extracts necessary keywords (e.g., "2023", "new product"). The input data is the request data in JSON format, and the output data is the extracted keywords.

[0614] Step 5:

[0615] The server generates information using generative artificial intelligence. Generative AI such as GPT-4 is used to generate relevant information based on extracted keywords. In this process, relevant news and data are collected and processed. The input data consists of extracted keywords, and the output data consists of the generated information.

[0616] Step 6:

[0617] The server summarizes the generated information. The generated information is passed to a summarization engine (e.g., GPT-4's summarization function), which extracts key points and creates a concise summary. The input data is the generated information, and the output data is the summary. This summary is adjusted based on sentiment data. For example, if the user is excited, the summary will include more technical details.

[0618] Step 7:

[0619] The server saves summary information to the database. The summary information and identification information such as the request ID are saved to the database (e.g., MySQL). The input data consists of the summary information and identification information, while the output data is a notification that the database save is complete.

[0620] Step 8:

[0621] The server sends summary information back to the terminal. The summary information stored in the database is sent to the terminal using the HTTPS protocol. The input data is the summary information, and the output data is a notification that transmission to the terminal is complete.

[0622] Step 9:

[0623] The terminal displays the summary information in an appropriate format. It converts the received summary information into a format suitable for display on the user interface. For example, it explicitly displays information such as "A new smartphone will be released in 2023" on the screen. The input data is the summary information from the server, and the output data is the display on the user interface.

[0624] Step 10:

[0625] The server periodically checks for updates to the information. After a certain period, or upon a user request for reconfirmation, it uses generative artificial intelligence to retrieve the latest relevant information and compare it with the existing information. The input data is the existing information in the database, and the output data is whether or not the information has been updated and the new information.

[0626] Step 11:

[0627] The server saves update information to the database. When new information is found, it is saved to the database and the existing information is updated. The input data is the new information, and the output data is a notification that the information has been saved to the database.

[0628] Step 12:

[0629] The server sends update information to the terminal. The updated information is sent to the terminal using the HTTPS protocol. The input data is the update information, and the output data is a notification that the transmission to the terminal is complete.

[0630] Step 13:

[0631] The device notifies the user of update information. The received update information is converted into a display format suitable for the user and then notified. For example, it might display "New smartphone information has been updated: New colors have been added" on the screen. The display style is adjusted based on sentiment data. For example, if the user is happy, a bright design is used. The input data is the update information, and the output data is the notification to the user interface.

[0632] (Application Example 2)

[0633] 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."

[0634] Conventional electronic payment systems have a problem in that information provision based on user requests is one-way, and they cannot provide personalized advice or notifications that are tailored to the user's emotions or state. Furthermore, when users make electronic payments while experiencing various emotional states such as anxiety or excitement, they are not provided with spending management or campaign information that is adapted to their emotions, resulting in a poor user experience. The present invention aims to solve these problems and realize personalized information provision that is adapted to the user's emotions.

[0635] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for receiving user requests, means for generating information based on the request using generative artificial intelligence, means for summarizing the generated information and storing it in a database, means for returning the stored summary information to the user, means for periodically checking for updates to the information, means for generating the updated information using the generative artificial intelligence and updating the database, means for notifying the user of the updated information, means including an emotion engine for analyzing the user's emotions, and means for personalizing the summary information and notification content based on the emotion data. This makes it possible to provide expenditure management advice and campaign information notifications adapted to the user's emotional state.

[0636] A "user request" is a specific instruction or inquiry from a user requesting information from the system.

[0637] "Generative artificial intelligence" refers to artificial intelligence technology used to generate information based on user requests.

[0638] A "database" is a repository of information that stores information and summaries generated within a system, making it accessible and updatable at a later date.

[0639] An "emotion engine" is an engine that analyzes emotional data from a user's voice and text to identify the user's emotional state.

[0640] "Personalization" refers to adjusting the content of information and notifications according to the individual characteristics and circumstances of each user.

[0641] A "request ID" is an identifier used to uniquely identify each user request.

[0642] A "summarization engine" is an engine that extracts important points from generated information and creates a concise summary.

[0643] "Update information" refers to information that has been generated and saved once, and is regenerated to show subsequent changes or additions.

[0644] A "notification" is a message or alert used to inform users of updates or important information.

[0645] This invention relates to an electronic payment system that provides personalized information in response to the user's emotions. The system includes multiple means to receive user requests, generate information using generative artificial intelligence, and summarize, store, and update that information. It then provides information based on the user's emotions.

[0646] First, the user enters a request for information retrieval into the device using their smartphone. For example, when a user enters a request such as "I'm worried about how I've been spending money lately" via voice or text, the emotion engine analyzes emotional data from the user's voice tone and the content of the text message. As a result of the analysis, an emotional state such as joy, sadness, anger, or anxiety is identified.

[0647] Next, the terminal retrieves the user's request and sentiment data, converts it into an appropriate format, and sends it to the server. The server receives the request and sentiment data, analyzes the request content, and extracts necessary keywords. For example, keywords such as "recently," "money," and "worry."

[0648] The server generates information based on keywords extracted using generative artificial intelligence. For example, it collects and processes relevant news and spending advice. The large amount of generated information is then passed to a summarization engine, where key points are extracted and a concise summary is created. The content and format of the summary are adjusted based on information analyzed from sentiment data. For instance, if the user is feeling anxious, advice on reducing spending might be provided.

[0649] The server saves the generated summary information and identification information such as the request ID to a database. After saving, the server sends the summary information back to the terminal. The terminal converts the received summary information into a display format and presents it to the user. For example, it might display "Are you okay? Here are some tips for managing your spending: The best way to manage your spending is to set a budget," in a format that suits the user's mood.

[0650] After a certain period of time has passed, or if the user requests reconfirmation, the server checks for updates to the information. It uses generative artificial intelligence again to retrieve the latest relevant information and compares it with the existing information in the database. For example, if the original information was "Tips for managing your expenses," and then an update is found such as "A new expense management app is out," the server records this information in the database and updates it. Once the update is confirmed, the server sends the update information to the device, and the device notifies the user of the update information at an appropriate time and in an appropriate style based on sentiment data. For example, "A new expense management app is out" might be displayed on the screen. In this case, if the user is happy, it will be displayed in a bright design.

[0651] As a concrete example, if the user input is "I'm worried about how I've been spending money lately," the prompt message from the generating AI model would be as follows:

[0652] "Analyze the sentiment of this text: I'm worried about how I've been spending money lately."

[0653] This enables the delivery of personalized information that matches the user's emotions. The entire system is designed to improve the user experience.

[0654] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0655] Step 1:

[0656] The user enters an information request using their smartphone. The input can be via voice or text, and may be a specific request such as "I'm worried about how I've been spending money lately." The input data (voice or text) is sent to an emotion engine, which analyzes the user's emotional state (joy, sadness, anger, anxiety, etc.). The results of this analysis are obtained as emotion data. The input data is the user's request, and the output data is the emotion data.

[0657] Step 2:

[0658] The device sends the user's request and sentiment data to the server. The server receives the request and sentiment data, analyzes the request, and extracts necessary keywords. For example, it might extract keywords such as "recently," "money," and "worry." This analysis is performed using natural language processing techniques. The input data consists of the request and sentiment data, and the output data consists of the extracted keywords.

[0659] Step 3:

[0660] The server generates information based on keywords extracted using generative artificial intelligence. Specifically, it collects relevant news and expense management advice, and generates information using generative artificial intelligence (e.g., GPT-3). The input data is the extracted keywords, and the output data is the generated information.

[0661] Step 4:

[0662] The server passes the generated information to the summarization engine, which extracts key points and creates a concise summary. The summary content and format are adjusted based on sentiment data. For example, if the user is feeling anxious, the generated summary will contain more advice on reducing spending. The input data consists of the generated information and sentiment data, while the output data is the summarized information.

[0663] Step 5:

[0664] The server saves summary information and identification information such as the request ID to the database. The input data is the summary information and the request ID, and the output data is a notification that the data has been saved to the database.

[0665] Step 6:

[0666] The server sends summary information back to the terminal. The terminal converts the received summary information into a display format and presents it to the user. The information is displayed in a format that suits the user's mood. The input data is summary information, and the output data is the information presented to the user.

[0667] Step 7:

[0668] The server checks for updates to information after a certain period of time has elapsed or when a user requests reconfirmation. Generative artificial intelligence is used to retrieve the latest relevant information and compare it with existing information in the database. Input data is the reconfirmation request or notification of the elapsed period, and output data is the updated information.

[0669] Step 8:

[0670] The server notifies the user of update information. The device notifies the user of the update information at the appropriate time and in the appropriate style based on sentiment data. For example, a notification such as "A new expense management app is available" might be sent. In this case, if the user is happy, it will be displayed in a bright design. The input data is the update information, and the output data is the information that is notified to the user.

[0671] 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.

[0672] 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.

[0673] 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.

[0674] [Third Embodiment]

[0675] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0676] 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.

[0677] 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).

[0678] 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.

[0679] 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.

[0680] 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).

[0681] 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.

[0682] 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.

[0683] 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.

[0684] 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.

[0685] 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.

[0686] 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".

[0687] This invention relates to a system that generates information based on user requests, summarizes and stores it, periodically checks for updates, and notifies the user if updates are found. The program of this system consists of the functions and roles of the server, terminal, and user.

[0688] Processing user requests

[0689] First, if a user wants to obtain specific information, they input a request into the terminal via voice or text, such as "Please tell me about new products for 2023." The terminal receives this request, converts it to the appropriate format, and sends it to the server. At this stage, the user's input becomes the key to identifying what information the system as a whole needs to generate.

[0690] Information generation and summarization

[0691] The server analyzes the received request and extracts necessary keywords and context. For example, if the request is for "new product information for 2023," it will extract keywords such as "2023" and "new products." Based on this analysis, the server uses generative artificial intelligence to generate relevant data.

[0692] Because the generated information often contains a large amount of data, the server uses a summarization engine to make the information concise. This results in summaries such as, "A new smartphone will be released in 2023, and that model will feature the latest processor."

[0693] Saving summary information and returning it to the user.

[0694] Next, the server saves the generated summary information to the database. This saving process also saves identifying information such as the request ID, making it easy to re-verify and update later. After saving, the server sends the saved summary information back to the terminal. The terminal receives this information, converts it into a display format, and presents it to the user.

[0695] Information update check and notification

[0696] After a certain period of time has passed, or if a manual check is requested, the server will perform an update check on the information. This involves using generative artificial intelligence again to retrieve new relevant information and comparing it with the existing information in the database. For example, if the original information was "A new smartphone will be released in 2023," and then an update is found stating "A new color has been added," the server will update the database with this information.

[0697] When an update is detected, the server sends the update information to the device, and the device uses its notification function to inform the user of the update. In this way, users can always efficiently obtain the latest information.

[0698] For example, if a user requests "Please tell me about new products for 2023," the server generates the latest information and provides the user with a summary such as "A new smartphone will be released in September 2023." Then, after a few months, if the user sends a follow-up request, the server retrieves the latest information again and notifies the user of updates such as "A new color has been added to the new smartphone." This ensures that the user always has the most up-to-date information.

[0699] Through the above program and process, the present invention provides a system that efficiently generates, summarizes, updates, and automatically notifies users of the information they request.

[0700] The following describes the processing flow.

[0701] Step 1:

[0702] The user enters their information retrieval request into the device. For example, they might enter a request such as "Please tell me about new products for 2023" via voice or text.

[0703] Step 2:

[0704] The terminal receives the user's request, converts it into the appropriate format, and sends it to the server. During this process, the request is formatted to ensure accurate transmission of its contents.

[0705] Step 3:

[0706] The server receives the request and parses it. It extracts keywords such as "2023" and "new product" from the request. This identifies what information should be generated.

[0707] Step 4:

[0708] The server uses generative artificial intelligence to generate information based on extracted keywords. For example, it collects and processes relevant data from related news articles and databases.

[0709] Step 5:

[0710] The server passes the large amount of generated information to the summarization engine. The summarization engine extracts the key points and creates a concise summary. For example, it might generate a summary such as, "A new smartphone will be released in 2023, featuring the latest processor."

[0711] Step 6:

[0712] The server stores the generated summary information and identification information such as the request ID in a database. This allows for later update checks and re-verification.

[0713] Step 7:

[0714] The server returns the stored summary information to the terminal. The information returned includes a summary of what the user requested.

[0715] Step 8:

[0716] The device receives summary information, converts it into a display format, and presents it to the user. For example, the device screen might display "A new smartphone will be released in 2023."

[0717] Step 9:

[0718] After a certain period, or upon a user request for reconfirmation, the server checks for updates to the information. It then uses generative artificial intelligence again to retrieve the latest relevant information.

[0719] Step 10:

[0720] The server compares the newly retrieved information with existing information in the database to check for updates. For example, it checks if there is new information such as "a new color has been added."

[0721] Step 11:

[0722] When an update is detected, the server updates the corresponding entry in the database and sends the update information to the terminal. This ensures that the information in the database remains up-to-date.

[0723] Step 12:

[0724] The device receives update information and notifies the user. For example, the screen might display, "New smartphone information has been updated: New colors have been added."

[0725] In this way, users can always obtain the latest information, and the entire system operates efficiently and accurately.

[0726] (Example 1)

[0727] 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."

[0728] Conventional information acquisition systems have faced challenges in providing users with the information they need appropriately and quickly, and in notifying users in a timely manner when information is updated. Furthermore, when the amount of information generated is large, users may spend a considerable amount of time finding the information they need. To solve these problems, a system is needed that generates relevant information based on user requests, summarizes and efficiently manages that information, and immediately notifies users when it is updated.

[0729] 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.

[0730] In this invention, the server includes means for receiving a user request, converting the request into an appropriate format and sending it to the server; means for generating information based on the request using generative artificial intelligence; and means for summarizing the generated information and storing it in a database. This allows the user to efficiently obtain the necessary information and receive updated information quickly.

[0731] "User" refers to an individual or organization that wishes to obtain information.

[0732] A "request" refers to a voice or text instruction that a user enters through their device to ask for information.

[0733] A "terminal" refers to an electronic device used by a user to enter requests and receive information.

[0734] A "server" refers to a computer system that processes user requests and is responsible for generating, summarizing, storing, updating, and notifying information.

[0735] "Generative artificial intelligence" refers to an algorithm or model that generates information based on input prompts.

[0736] A "prompt message" refers to a sentence that is input to a generative artificial intelligence system to generate information.

[0737] A "summary" refers to a concise compilation of information, extracting the most important parts from the generated data.

[0738] A "database" refers to a system for storing generated summary information and related data.

[0739] "Update" refers to the addition or modification of new information to the generated information.

[0740] "Notification" refers to the act of informing a user that information has been updated.

[0741] This invention relates to a system that generates information based on user requests, summarizes and stores it, periodically checks for updates, and notifies the user if updates are found. This system is composed of the functions and roles of a server, a terminal, and a user.

[0742] Processing user requests

[0743] First, if a user wants to obtain specific information, they input a request into the terminal via voice or text, such as "Please tell me about new products for 2023." The terminal receives this request, converts it to an appropriate format (e.g., JSON), and sends it to the server. At this stage, the user's input becomes the key to identifying what information the system as a whole needs to generate.

[0744] Information generation and summarization

[0745] The server analyzes the received request and extracts necessary keywords and context. For example, if the request is for "new product information for 2023," it will extract keywords such as "2023" and "new products." Based on this analysis, the server uses generative artificial intelligence (e.g., OpenAI GPT-4) to generate relevant data.

[0746] Because the generated information often contains a large amount of data, the server uses a summarization engine (e.g., BERT) to simplify the information. This results in summaries such as, "A new smartphone will be released in 2023, and that model will feature the latest processor."

[0747] Saving summary information and returning it to the user.

[0748] Next, the server saves the generated summary information to the database. This saving process also saves identifying information such as the request ID, making it easy to re-verify and update later. After saving, the server sends the saved summary information back to the terminal. The terminal receives this information, converts it into a display format, and presents it to the user.

[0749] Information update check and notification

[0750] After a certain period of time has passed, or if a manual check is requested, the server will perform an update check on the information. This involves using generative artificial intelligence again to retrieve new relevant information and comparing it with the existing information in the database. For example, if the original information was "A new smartphone will be released in 2023," and then an update is found stating "A new color has been added," the server will update the database with this information.

[0751] When an update is detected, the server sends the update information to the device, and the device uses its notification function to inform the user of the update. In this way, users can always efficiently obtain the latest information.

[0752] Examples of specific cases and prompt statements

[0753] For example, if a user requests "Please tell me about new products for 2023," the server generates the latest information and provides the user with a summary such as "A new smartphone will be released in September 2023." Then, after a few months, if the user sends a follow-up request, the server retrieves the latest information again and notifies the user of updates such as "A new color has been added to the new smartphone." This ensures that the user always has the most up-to-date information.

[0754] Example of a prompt:

[0755] "Please tell me about new product information for 2023."

[0756] The above describes the specific forms for carrying out the invention.

[0757] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0758] Step 1:

[0759] When a user wants to obtain specific information, they enter a request into the terminal, such as "Please tell me about new products for 2023." The input format is either voice or text. Input: User's voice or text request. Output: Request as text data.

[0760] Step 2:

[0761] The terminal receives a request from the user and converts it into a format that can be processed (e.g., JSON). After converting to the appropriate data format, the terminal sends this data to the server over the internet. Input: User request in text format. Output: Data in JSON format.

[0762] Step 3:

[0763] The server analyzes the received request data and extracts the necessary keywords and context. Specifically, the server uses natural language processing to extract keywords such as "2023" and "new products" from a request like "new product information for 2023". Input: Request data in JSON format. Output: Extracted keywords and context information.

[0764] Step 4:

[0765] The server uses generative artificial intelligence (e.g., a generative AI model) to generate information based on the extracted keywords. In this process, it generates a prompt and inputs it into the generative AI model. For example, it might create a prompt such as "Please provide the latest information on new products for 2023" and input it into the generative AI model. Input: Extracted keywords and contextual information. Output: Generated information.

[0766] Step 5:

[0767] If the amount of information generated is large, the server uses a summarization engine (e.g., BERT) to summarize the information. For example, it might create a summary such as, "A new smartphone will be released in 2023, and this model will feature the latest processor." Input: Generated information. Output: Summarized information.

[0768] Step 6:

[0769] The server saves the summarized information to the database. The request ID and user ID are also saved at this time to allow for easy retrieval of the information later. Input: Summarized information. Output: Information saved in the database.

[0770] Step 7:

[0771] The server resends the saved summary information to the terminal. The terminal converts the received information into a display format and presents it to the user. Input: Summary information stored in the database. Output: Information presented to the user.

[0772] Step 8:

[0773] After a certain period of time has passed, or when a user submits a reconfirmation request, the server checks for updates to the information. It uses the generative AI model again to retrieve new relevant information and compares it to existing information in the database. Input: User reconfirmation request or timer event. Output: New relevant information.

[0774] Step 9:

[0775] The server compares the new update information with existing information in the database. Once an update is confirmed, it sends the information to the terminal, which then uses its notification function to inform the user of the update. Input: New related information. Output: Update notification to the user.

[0776] The above describes the specific processing steps of the program in this system.

[0777] (Application Example 1)

[0778] 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."

[0779] For modern users, staying up-to-date on the latest information about products and services they are interested in is crucial. However, quickly and accurately obtaining the latest information from a vast amount of data, and regularly checking for updates, is difficult. Furthermore, acquiring information from diverse sources and ensuring its accuracy is also a challenge. In this situation, there is a need for a system that allows users to efficiently and reliably obtain the latest information they require.

[0780] 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.

[0781] In this invention, the server includes means for receiving user requests, means for generating information based on requests using generative artificial intelligence, means for summarizing the generated information and storing it in a database, means for returning the stored summary information to the user, means for periodically checking for updates to the information, means for generating updated information using generative artificial intelligence and updating the database, means for notifying the terminal when the latest information is generated, means for sending a prompt message to the generative artificial intelligence, means for generating relevant information based on product categories, and means for displaying the latest information to the user. As a result, the user can always quickly and reliably obtain the latest information on products of interest and automatically receive update information.

[0782] "Means of receiving user requests" refers to an interface that allows users to input specific information and the functionality of the system that processes that input.

[0783] "Generative artificial intelligence" refers to artificial intelligence technology that has the ability to generate relevant information based on input data.

[0784] "Means for summarizing information and storing it in a database" refers to the functions of a storage device and system for converting generated information into a concise format and accumulating that summarized information.

[0785] "Means for returning saved summary information to the user" refers to a system function that retrieves summary information stored in a database and provides it to the user.

[0786] "Means of regularly checking for updates to information" refers to a system function that checks at regular intervals whether the stored information is up-to-date.

[0787] "A means of generating update information and updating a database using generative artificial intelligence" refers to a system function that uses artificial intelligence technology to generate new information and replace existing information in a database with it.

[0788] "Means of notifying the device when new information is generated" refers to a system function that sends a notification to the user's device when new information is generated.

[0789] "Means for sending prompt messages to a generative artificial intelligence" refers to a function of a system that inputs instruction messages for information generation to a generative artificial intelligence.

[0790] "Means for generating relevant information based on product categories" refers to a system function that acquires and generates relevant information based on product categories that the user is interested in.

[0791] "Means of displaying the latest information to the user" refers to a system function that displays the generated latest information on the user's interface.

[0792] To implement this invention, a system is required in which a server, a terminal, and a user each have their own respective roles.

[0793] Processing user requests

[0794] First, if a user wants to obtain specific information, they enter a request through a smartphone application, such as "Please tell me the information about the new smartphone." This request is received by the device, converted into the appropriate format, and sent to the server.

[0795] Information generation and summarization

[0796] The server analyzes the received request and extracts necessary keywords and context. For example, if the request is for "information on a new smartphone," keywords such as "smartphone" and "new" will be extracted. Based on this analysis, the server uses a generative AI model (e.g., GPT-4) to generate relevant information. Because the generated information may be complex, the server uses a summarization engine (e.g., PEGASUS) to create a concise summary.

[0797] Saving summary information and returning it to the user.

[0798] The server saves the summarized information to a database. At this stage, the request ID and related metadata are also saved, making it easier to review and check for updates later. The saved information is sent back to the user's terminal, which then displays it to the user.

[0799] Information update check and notification

[0800] After a certain period of time, or when a manual check is requested, the server performs an information update check. It uses the generated AI model again to retrieve new relevant information and compares it with existing information in the database. If an update is found, the database is updated, and the server sends the update to the user's terminal. The terminal then notifies the user of the latest information.

[0801] Hardware and software usage

[0802] This system uses devices such as smartphones and tablets, centralized cloud servers (e.g., AWS, Google Cloud), and generative AI models (e.g., GPT-4) and summarization engines (e.g., PEGASUS).

[0803] Specific example

[0804] When a user enters a request into the application, such as "Please tell me about the new smartphone," the server receives the request and uses a generative AI model to generate information such as, "A new smartphone is scheduled to be released in 2023. This model will feature the latest processor and enhanced camera capabilities." This information is then summarized concisely by a summarizing engine and stored in a database. When the information is updated, the server notifies the user's device of the new information, such as, "A new color has since been added." A concrete example of a prompt sent to the generative AI model is, "Please tell me about the new smartphone coming in 2023."

[0805] This system allows users to efficiently obtain the latest and most accurate information.

[0806] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0807] Step 1:

[0808] The user opens a smartphone application and enters a specific information request (e.g., "Please tell me information about my new smartphone") via voice or text.

[0809] Input: User's voice or text request

[0810] Output: Formatted request data sent to the terminal

[0811] Operation: The application converts the user's speech into text (using speech recognition software) and then converts the acquired text data into an appropriate format.

[0812] Step 2:

[0813] The terminal sends the formatted request data to the server.

[0814] Input: Formatted request data

[0815] Output: Request data sent to the server

[0816] Operation: The terminal sends the request data to the server as an HTTP request and waits for a response.

[0817] Step 3:

[0818] The server receives and parses the request data. Specifically, it extracts necessary keywords and context from the request.

[0819] Input: Request data sent to the server

[0820] Output: Extracted keywords and contextual information

[0821] Operation: The analysis engine on the server (using natural language processing software) analyzes the data and extracts keywords and context.

[0822] Step 4:

[0823] The server uses a generative AI model (e.g., GPT-4) to generate relevant information based on extracted keywords and context.

[0824] Input: Extracted keywords and contextual information

[0825] Output: Generated information

[0826] Operation: Input prompts into the generative AI model and retrieve the generated information.

[0827] Step 5:

[0828] If the generated information is complex, the server uses a summarization engine (e.g., PEGASUS) to create a concise summary.

[0829] Input: Generated details

[0830] Output: Summarized information

[0831] Operation: Starts the summarization engine and creates a concise summary using the generated information as input.

[0832] Step 6:

[0833] The server stores the summarized information in the database.

[0834] Input: Summarized information, request ID, related metadata

[0835] Output: Summary information stored in the database

[0836] Function: Saves summary information to a database management system (e.g., MySQL).

[0837] Step 7:

[0838] The server sends the saved summary information back to the terminal.

[0839] Input: Summary information stored in the database

[0840] Output: Summary information sent to the terminal

[0841] Operation: Sends summary information to the terminal as an HTTP response.

[0842] Step 8:

[0843] The terminal displays the returned summary information to the user.

[0844] Input: Summary information sent from the server

[0845] Output: Summary information displayed to the user

[0846] Operation: The application displays the received summary information in the user interface.

[0847] Step 9:

[0848] The server periodically checks for updates to the information, and if new information is available, it reuses the generated AI model to retrieve the relevant information.

[0849] Input: Time interval for periodic checks, existing information

[0850] Output: New generated information

[0851] Operation: Sends an update request to the generative AI model and generates new information.

[0852] Step 10:

[0853] The server compares new information with existing information and updates the database if there are any differences.

[0854] Input: New generated information, existing information

[0855] Output: Updated database

[0856] Operation: Compares new information with existing information and updates the database if differences are detected.

[0857] Step 11:

[0858] When the server detects an information update, it notifies the user's device of the update details.

[0859] Input: Update details

[0860] Output: Notification to user terminal

[0861] Operation: Notifies the user's terminal of the latest information using the notification system.

[0862] A concrete example of a prompt is, "Please tell me about the new smartphone." This prompt prompt prompts the AI ​​model to generate the latest relevant information.

[0863] 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.

[0864] This invention provides a system that generates information based on user requests, summarizes and stores it, periodically checks for updates, and notifies the user if updates are found, in addition to utilizing an emotion engine that recognizes the user's emotions. The program of this system is composed of the functions and roles of the server, terminal, and user.

[0865] User request processing and sentiment recognition

[0866] First, the user enters a request for information into the device. For example, when a user enters a request such as "Please tell me about new products for 2023" via voice or text, the emotion engine analyzes emotional data from the user's voice tone and the content of the text message. It identifies emotional states such as joy, sadness, anger, and anxiety.

[0867] Information generation and summarization

[0868] The terminal retrieves user requests and sentiment data, converts them into an appropriate format, and sends them to the server. The server receives the requests and sentiment data, analyzes the request content, and extracts necessary keywords, such as "2023" and "new product."

[0869] Next, the server generates information based on keywords extracted using generative artificial intelligence. For example, it collects and processes relevant news and data. The large amount of generated information is then passed to a summarization engine, where key points are extracted and a concise summary is created. The content and format of the summary are adjusted based on information analyzed from sentiment data. For instance, if the user is excited, a summary containing more detailed technical information might be provided.

[0870] Saving summary information and returning it to the user.

[0871] The server saves the generated summary information and identification information such as the request ID to a database. After saving, the server sends the summary information back to the terminal. The terminal converts the received summary information into a display format and presents it to the user. For example, it might display "A new smartphone will be released in 2023" in a format that suits the user's mood.

[0872] Information update check and notification

[0873] After a certain period of time has passed, or if a user requests reconfirmation, the server checks for updates to the information. It uses generative artificial intelligence again to retrieve the latest relevant information and compares it with the existing information in the database. For example, if the original information was "A new smartphone will be released in 2023," and then an update is found such as "A new color has been added," the server will record this information in the database and update it.

[0874] Once an update is detected, the server sends the update information to the device, and the device notifies the user of the update at the appropriate time and in the appropriate style based on sentiment data. For example, it might display on the screen, "New smartphone information has been updated: New colors have been added." If the user is happy, the message will be displayed in a bright design.

[0875] By combining these emotion engines, it becomes possible to provide information that adapts to the user's emotional state, enabling the entire system to deliver a more personalized information experience.

[0876] The following describes the processing flow.

[0877] Step 1:

[0878] The user enters a request for information into the device. For example, they might enter a request such as "Please tell me about new products for 2023" via voice or text. During this process, the device collects emotional data from the user's voice tone and the nuances of their text.

[0879] Step 2:

[0880] The terminal retrieves the user's request and sentiment data, converts it into the appropriate format, and sends it to the server. The formatting ensures that the request and sentiment data are accurately conveyed.

[0881] Step 3:

[0882] The server receives the request and analyzes it. Keywords such as "2023" and "new product" are extracted from the request. At the same time, emotional data is analyzed to identify the user's emotional state. This analysis determines whether the user is excited, calm, anxious, etc.

[0883] Step 4:

[0884] The server uses generative artificial intelligence to generate information based on extracted keywords. For example, it collects relevant data from news articles and databases and generates information based on that data. Sentimental data is also taken into consideration when generating the information.

[0885] Step 5:

[0886] The server passes the large amount of generated information to the summarization engine. The summarization engine extracts the key points and creates a concise summary. Based on sentiment data, the content and format of the summary are adjusted. For example, if the user is excited, a summary containing more detailed technical information will be provided.

[0887] Step 6:

[0888] The server stores the generated summary information and identification information such as the request ID in a database. This makes it easy to perform update checks and re-verifications later.

[0889] Step 7:

[0890] The server sends the saved summary information back to the terminal. The terminal receives the summary information, converts it into a display format, and presents it to the user. For example, it might display "A new smartphone will be released in 2023" in a format that suits the user's mood.

[0891] Step 8:

[0892] After a certain period, or upon a user request for reconfirmation, the server checks for updates to the information. It then uses generative artificial intelligence again to retrieve the latest relevant information.

[0893] Step 9:

[0894] The server compares the newly retrieved information with existing information in the database to check for updates. For example, it checks for new information such as "a new color has been added."

[0895] Step 10:

[0896] When an update is detected, the server updates the corresponding entry in the database and sends the update information to the terminal. This ensures that the information in the database is always up-to-date.

[0897] Step 11:

[0898] The device receives update information and notifies the user. For example, it might display "New smartphone information has been updated: New colors have been added" on the screen. When a notification is displayed, the display method is adjusted according to the user's emotions; for example, a brighter design is used if the user is happy.

[0899] In this way, it becomes possible to recognize the user's emotions and provide information that is adapted to them, thereby improving the user experience.

[0900] (Example 2)

[0901] 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."

[0902] Traditional information delivery systems often failed to consider user emotions, resulting in a lack of information tailored to user needs and inappropriate presentation methods. Furthermore, the generated information was not frequently updated, making it difficult for users to access the latest information. Accuracy was also a challenge, as data collection from reliable external sources was insufficient.

[0903] 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.

[0904] In this invention, the server includes means for receiving user requests, means for analyzing requests and collecting sentiment data, means for generating information based on the requests and sentiment data using generative artificial intelligence, means for summarizing the generated information, means for storing the summarized information in a database, means for returning the stored summarized information to the user, means for periodically checking for updates to the stored information, means for generating the updated information using the generative artificial intelligence and updating the database, and means for notifying the user of the updated information. This enables the provision of information adapted to the user's emotions and allows the user to be provided with the latest information that is updated regularly. Furthermore, the accuracy of the information provided is enhanced by collecting data from reliable external sources.

[0905] "Means for receiving user requests" refers to devices or interfaces for receiving information retrieval requests from users. Specifically, this refers to voice input devices and text input interfaces.

[0906] "Means for analyzing requests and collecting sentiment data" refers to a system that analyzes the content of a user's request and collects the user's emotional state from the tone of voice and text content at that time. Specifically, it uses a natural language processing engine and sentiment analysis algorithm.

[0907] "Means for generating information based on the aforementioned request and sentiment data using generative artificial intelligence" refers to a technology for generating relevant information based on user requests and sentiment data using generative artificial intelligence. Specifically, it refers to a generative AI model.

[0908] "Methods for summarizing generated information" refer to techniques for extracting important parts from large amounts of generated information and creating a concise summary. This utilizes the summarization capabilities of generative artificial intelligence.

[0909] "Means for storing summarized information in a database" refers to a device or system that records and stores summarized information and associated identification information in a database. Specifically, it refers to a database management system.

[0910] "Means for returning stored summary information to the user" refers to means for notifying or providing stored summary information to the user. Specifically, it refers to servers or interfaces that transmit information over a network.

[0911] "Means for periodically checking for updates to stored information" refers to technologies for periodically verifying whether stored information is up-to-date. Specifically, this refers to scheduling systems and information gathering engines.

[0912] "Means for generating the update information and updating the database using the generative artificial intelligence" refers to a technology for generating new information and updating existing database information using generative artificial intelligence.

[0913] "Means of notifying users of updates" refers to means of informing users of updates when information is updated. Specifically, this refers to notification systems and alert functions.

[0914] "Means for receiving requests for information reconfirmation" refers to devices or interfaces for receiving reconfirmation requests from users.

[0915] "Means for sending the reconfirmation request to the generative artificial intelligence and comparing it with the existing information" refers to a technique for sending a reconfirmation request to the generative artificial intelligence and comparing the new information with the existing information.

[0916] "Means for generating new summary information when an update is detected" refers to means for generating new summary information when it is confirmed that the information has been updated.

[0917] "Means of improving the accuracy of generated information by acquiring information from generative artificial intelligence and reliable external sources" refers to technologies that use generative artificial intelligence and collect information from reliable external data sources to improve the accuracy of the information provided.

[0918] This invention is an information provision system that generates information based on user requests, summarizes and stores it, periodically checks for updates, and notifies the user if there are any updates. Furthermore, by incorporating an emotion engine that recognizes the user's emotional state, the system achieves more appropriate and personalized information provision. This invention is composed of the functions and roles of the server, terminal, and user.

[0919] First, the user enters a request for information into the device. For example, if the user enters a request such as "Please tell me about new products for 2023" via voice or text, the emotion engine analyzes emotional data from the user's voice tone and the content of the text message. The emotion engine uses an emotion analysis algorithm and a natural language processing engine (e.g., Microsoft Azure Cognitive Services). This engine identifies emotional states such as joy, sadness, anger, and anxiety.

[0920] Next, the terminal retrieves the user's request and sentiment data, converts it into an appropriate format, and sends it to the server. At this stage, the JSON format is used as the data conversion method, and it is sent via the HTTPS protocol.

[0921] The server analyzes the received request and sentiment data to extract necessary keywords. For example, a natural language processing engine (e.g., SpaCy) is used to identify the keywords "2023" and "new product." Then, a generative artificial intelligence (e.g., OpenAI GPT-4) is used to generate information based on the extracted keywords. Specifically, it collects and processes relevant news and data. Because the amount of information generated is large, it is passed to a summarization engine (e.g., GPT-4's summarization function) to create a concise summary with the key points extracted. Based on sentiment data, the content and format of the summary are adjusted; for example, if the user is excited, a summary containing more detailed technical information is provided.

[0922] The following are specific examples of prompt statements for a generative AI model:

[0923] "Research the new product information for 2023 and create a summary that includes detailed technical information suitable for users who are excited about the product."

[0924] The generated summary information is stored by the server in a database (e.g., MySQL). After saving, the server sends the summary information back to the terminal, which converts the received summary information into a display format and presents it to the user. For example, it might display "A new smartphone will be released in 2023."

[0925] After a certain period of time has passed, or if a user requests reconfirmation, the server checks for updates to the information. In this process, generative artificial intelligence (e.g., OpenAI GPT-4) is used to retrieve the latest relevant information and compare it with existing information in the database. For example, if the original information was "A new smartphone will be released in 2023," and an update is found later stating "A new color has been added," the server will record this information in the database and update it.

[0926] Once an update is detected, the server sends the update information to the device, and the device notifies the user of the update at the appropriate time and in the appropriate style based on sentiment data. For example, the screen might display, "New smartphone information has been updated: New colors have been added." If the user is happy, the message will be displayed in a bright design.

[0927] Thus, the present invention makes it possible to provide information that is adapted to the user's emotional state, enabling the entire system to provide a more personalized information experience.

[0928] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0929] Step 1:

[0930] The user enters an information retrieval request. For example, they might enter a request via voice or text, such as, "Please tell me about new products for 2023." This request becomes the input data for the system.

[0931] Step 2:

[0932] The device collects requests and emotional data. After receiving user input, it uses an emotion engine (e.g., a natural language processing algorithm) to analyze the user's voice tone and text content to obtain emotional data such as joy, sadness, anger, and anxiety. The input data consists of the user's request and emotional state, while the output data is the analyzed emotional information.

[0933] Step 3:

[0934] The device sends the request and sentiment data to the server. The retrieved request and sentiment data are converted to JSON format and sent to the server using the HTTPS protocol. The input data consists of the request and sentiment information, and the output data is a notification that the transmission to the server is complete.

[0935] Step 4:

[0936] The server parses the request. It analyzes the received request using a natural language processing engine (e.g., SpaCy) and extracts necessary keywords (e.g., "2023", "new product"). The input data is the request data in JSON format, and the output data is the extracted keywords.

[0937] Step 5:

[0938] The server generates information using generative artificial intelligence. Generative AI such as GPT-4 is used to generate relevant information based on extracted keywords. In this process, relevant news and data are collected and processed. The input data consists of extracted keywords, and the output data consists of the generated information.

[0939] Step 6:

[0940] The server summarizes the generated information. The generated information is passed to a summarization engine (e.g., GPT-4's summarization function), which extracts key points and creates a concise summary. The input data is the generated information, and the output data is the summary. This summary is adjusted based on sentiment data. For example, if the user is excited, the summary will include more technical details.

[0941] Step 7:

[0942] The server saves summary information to the database. The summary information and identification information such as the request ID are saved to the database (e.g., MySQL). The input data consists of the summary information and identification information, while the output data is a notification that the database save is complete.

[0943] Step 8:

[0944] The server sends summary information back to the terminal. The summary information stored in the database is sent to the terminal using the HTTPS protocol. The input data is the summary information, and the output data is a notification that transmission to the terminal is complete.

[0945] Step 9:

[0946] The terminal displays the summary information in an appropriate format. It converts the received summary information into a format suitable for display on the user interface. For example, it explicitly displays information such as "A new smartphone will be released in 2023" on the screen. The input data is the summary information from the server, and the output data is the display on the user interface.

[0947] Step 10:

[0948] The server periodically checks for updates to the information. After a certain period, or upon a user request for reconfirmation, it uses generative artificial intelligence to retrieve the latest relevant information and compare it with the existing information. The input data is the existing information in the database, and the output data is whether or not the information has been updated and the new information.

[0949] Step 11:

[0950] The server saves update information to the database. When new information is found, it is saved to the database and the existing information is updated. The input data is the new information, and the output data is a notification that the information has been saved to the database.

[0951] Step 12:

[0952] The server sends update information to the terminal. The updated information is sent to the terminal using the HTTPS protocol. The input data is the update information, and the output data is a notification that the transmission to the terminal is complete.

[0953] Step 13:

[0954] The device notifies the user of update information. The received update information is converted into a display format suitable for the user and then notified. For example, it might display "New smartphone information has been updated: New colors have been added" on the screen. The display style is adjusted based on sentiment data. For example, if the user is happy, a bright design is used. The input data is the update information, and the output data is the notification to the user interface.

[0955] (Application Example 2)

[0956] 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."

[0957] Conventional electronic payment systems have a problem in that information provision based on user requests is one-way, and they cannot provide personalized advice or notifications that are tailored to the user's emotions or state. Furthermore, when users make electronic payments while experiencing various emotional states such as anxiety or excitement, they are not provided with spending management or campaign information that is adapted to their emotions, resulting in a poor user experience. The present invention aims to solve these problems and realize personalized information provision that is adapted to the user's emotions.

[0958] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for receiving user requests, means for generating information based on the request using generative artificial intelligence, means for summarizing the generated information and storing it in a database, means for returning the stored summary information to the user, means for periodically checking for updates to the information, means for generating the updated information using the generative artificial intelligence and updating the database, means for notifying the user of the updated information, means including an emotion engine for analyzing the user's emotions, and means for personalizing the summary information and notification content based on the emotion data. This makes it possible to provide expenditure management advice and campaign information notifications adapted to the user's emotional state.

[0959] A "user request" is a specific instruction or inquiry from a user requesting information from the system.

[0960] "Generative artificial intelligence" refers to artificial intelligence technology used to generate information based on user requests.

[0961] A "database" is a repository of information that stores information and summaries generated within a system, making it accessible and updatable at a later date.

[0962] An "emotion engine" is an engine that analyzes emotional data from a user's voice and text to identify the user's emotional state.

[0963] "Personalization" refers to adjusting the content of information and notifications according to the individual characteristics and circumstances of each user.

[0964] A "request ID" is an identifier used to uniquely identify each user request.

[0965] A "summarization engine" is an engine that extracts important points from generated information and creates a concise summary.

[0966] "Update information" refers to information that has been generated and saved once, and is regenerated to show subsequent changes or additions.

[0967] A "notification" is a message or alert used to inform users of updates or important information.

[0968] This invention relates to an electronic payment system that provides personalized information in response to the user's emotions. The system includes multiple means to receive user requests, generate information using generative artificial intelligence, and summarize, store, and update that information. It then provides information based on the user's emotions.

[0969] First, the user enters a request for information retrieval into the device using their smartphone. For example, when a user enters a request such as "I'm worried about how I've been spending money lately" via voice or text, the emotion engine analyzes emotional data from the user's voice tone and the content of the text message. As a result of the analysis, an emotional state such as joy, sadness, anger, or anxiety is identified.

[0970] Next, the terminal retrieves the user's request and sentiment data, converts it into an appropriate format, and sends it to the server. The server receives the request and sentiment data, analyzes the request content, and extracts necessary keywords. For example, keywords such as "recently," "money," and "worry."

[0971] The server generates information based on keywords extracted using generative artificial intelligence. For example, it collects and processes relevant news and spending advice. The large amount of generated information is then passed to a summarization engine, where key points are extracted and a concise summary is created. The content and format of the summary are adjusted based on information analyzed from sentiment data. For instance, if the user is feeling anxious, advice on reducing spending might be provided.

[0972] The server saves the generated summary information and identification information such as the request ID to a database. After saving, the server sends the summary information back to the terminal. The terminal converts the received summary information into a display format and presents it to the user. For example, it might display "Are you okay? Here are some tips for managing your spending: The best way to manage your spending is to set a budget," in a format that suits the user's mood.

[0973] After a certain period of time has passed, or if the user requests reconfirmation, the server checks for updates to the information. It uses generative artificial intelligence again to retrieve the latest relevant information and compares it with the existing information in the database. For example, if the original information was "Tips for managing your expenses," and then an update is found such as "A new expense management app is out," the server records this information in the database and updates it. Once the update is confirmed, the server sends the update information to the device, and the device notifies the user of the update information at an appropriate time and in an appropriate style based on sentiment data. For example, "A new expense management app is out" might be displayed on the screen. In this case, if the user is happy, it will be displayed in a bright design.

[0974] As a concrete example, if the user input is "I'm worried about how I've been spending money lately," the prompt message from the generating AI model would be as follows:

[0975] "Analyze the sentiment of this text: I'm worried about how I've been spending money lately."

[0976] This enables the delivery of personalized information that matches the user's emotions. The entire system is designed to improve the user experience.

[0977] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0978] Step 1:

[0979] The user enters an information request using their smartphone. The input can be via voice or text, and may be a specific request such as "I'm worried about how I've been spending money lately." The input data (voice or text) is sent to an emotion engine, which analyzes the user's emotional state (joy, sadness, anger, anxiety, etc.). The results of this analysis are obtained as emotion data. The input data is the user's request, and the output data is the emotion data.

[0980] Step 2:

[0981] The device sends the user's request and sentiment data to the server. The server receives the request and sentiment data, analyzes the request, and extracts necessary keywords. For example, it might extract keywords such as "recently," "money," and "worry." This analysis is performed using natural language processing techniques. The input data consists of the request and sentiment data, and the output data consists of the extracted keywords.

[0982] Step 3:

[0983] The server generates information based on keywords extracted using generative artificial intelligence. Specifically, it collects relevant news and expense management advice, and generates information using generative artificial intelligence (e.g., GPT-3). The input data is the extracted keywords, and the output data is the generated information.

[0984] Step 4:

[0985] The server passes the generated information to the summarization engine, which extracts key points and creates a concise summary. The summary content and format are adjusted based on sentiment data. For example, if the user is feeling anxious, the generated summary will contain more advice on reducing spending. The input data consists of the generated information and sentiment data, while the output data is the summarized information.

[0986] Step 5:

[0987] The server saves summary information and identification information such as the request ID to the database. The input data is the summary information and the request ID, and the output data is a notification that the data has been saved to the database.

[0988] Step 6:

[0989] The server sends summary information back to the terminal. The terminal converts the received summary information into a display format and presents it to the user. The information is displayed in a format that suits the user's mood. The input data is summary information, and the output data is the information presented to the user.

[0990] Step 7:

[0991] The server checks for updates to information after a certain period of time has elapsed or when a user requests reconfirmation. Generative artificial intelligence is used to retrieve the latest relevant information and compare it with existing information in the database. Input data is the reconfirmation request or notification of the elapsed period, and output data is the updated information.

[0992] Step 8:

[0993] The server notifies the user of update information. The device notifies the user of the update information at the appropriate time and in the appropriate style based on sentiment data. For example, a notification such as "A new expense management app is available" might be sent. In this case, if the user is happy, it will be displayed in a bright design. The input data is the update information, and the output data is the information that is notified to the user.

[0994] 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.

[0995] 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.

[0996] 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.

[0997] [Fourth Embodiment]

[0998] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0999] 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.

[1000] 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).

[1001] 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.

[1002] 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.

[1003] 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).

[1004] 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.

[1005] 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.

[1006] 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.

[1007] 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.

[1008] 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.

[1009] 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.

[1010] 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".

[1011] This invention relates to a system that generates information based on user requests, summarizes and stores it, periodically checks for updates, and notifies the user if updates are found. The program of this system consists of the functions and roles of the server, terminal, and user.

[1012] Processing user requests

[1013] First, if a user wants to obtain specific information, they input a request into the terminal via voice or text, such as "Please tell me about new products for 2023." The terminal receives this request, converts it to the appropriate format, and sends it to the server. At this stage, the user's input becomes the key to identifying what information the system as a whole needs to generate.

[1014] Information generation and summarization

[1015] The server analyzes the received request and extracts necessary keywords and context. For example, if the request is for "new product information for 2023," it will extract keywords such as "2023" and "new products." Based on this analysis, the server uses generative artificial intelligence to generate relevant data.

[1016] Because the generated information often contains a large amount of data, the server uses a summarization engine to make the information concise. This results in summaries such as, "A new smartphone will be released in 2023, and that model will feature the latest processor."

[1017] Saving summary information and returning it to the user.

[1018] Next, the server saves the generated summary information to the database. This saving process also saves identifying information such as the request ID, making it easy to re-verify and update later. After saving, the server sends the saved summary information back to the terminal. The terminal receives this information, converts it into a display format, and presents it to the user.

[1019] Information update check and notification

[1020] After a certain period of time has passed, or if a manual check is requested, the server will perform an update check on the information. This involves using generative artificial intelligence again to retrieve new relevant information and comparing it with the existing information in the database. For example, if the original information was "A new smartphone will be released in 2023," and then an update is found stating "A new color has been added," the server will update the database with this information.

[1021] When an update is detected, the server sends the update information to the device, and the device uses its notification function to inform the user of the update. In this way, users can always efficiently obtain the latest information.

[1022] For example, if a user requests "Please tell me about new products for 2023," the server generates the latest information and provides the user with a summary such as "A new smartphone will be released in September 2023." Then, after a few months, if the user sends a follow-up request, the server retrieves the latest information again and notifies the user of updates such as "A new color has been added to the new smartphone." This ensures that the user always has the most up-to-date information.

[1023] Through the above program and process, the present invention provides a system that efficiently generates, summarizes, updates, and automatically notifies users of the information they request.

[1024] The following describes the processing flow.

[1025] Step 1:

[1026] The user enters their information retrieval request into the device. For example, they might enter a request such as "Please tell me about new products for 2023" via voice or text.

[1027] Step 2:

[1028] The terminal receives the user's request, converts it into the appropriate format, and sends it to the server. During this process, the request is formatted to ensure accurate transmission of its contents.

[1029] Step 3:

[1030] The server receives the request and parses it. It extracts keywords such as "2023" and "new product" from the request. This identifies what information should be generated.

[1031] Step 4:

[1032] The server uses generative artificial intelligence to generate information based on extracted keywords. For example, it collects and processes relevant data from related news articles and databases.

[1033] Step 5:

[1034] The server passes the large amount of generated information to the summarization engine. The summarization engine extracts the key points and creates a concise summary. For example, it might generate a summary such as, "A new smartphone will be released in 2023, featuring the latest processor."

[1035] Step 6:

[1036] The server stores the generated summary information and identification information such as the request ID in a database. This allows for later update checks and re-verification.

[1037] Step 7:

[1038] The server returns the stored summary information to the terminal. The information returned includes a summary of what the user requested.

[1039] Step 8:

[1040] The device receives summary information, converts it into a display format, and presents it to the user. For example, the device screen might display "A new smartphone will be released in 2023."

[1041] Step 9:

[1042] After a certain period, or upon a user request for reconfirmation, the server checks for updates to the information. It then uses generative artificial intelligence again to retrieve the latest relevant information.

[1043] Step 10:

[1044] The server compares the newly retrieved information with existing information in the database to check for updates. For example, it checks if there is new information such as "a new color has been added."

[1045] Step 11:

[1046] When an update is detected, the server updates the corresponding entry in the database and sends the update information to the terminal. This ensures that the information in the database remains up-to-date.

[1047] Step 12:

[1048] The device receives update information and notifies the user. For example, the screen might display, "New smartphone information has been updated: New colors have been added."

[1049] In this way, users can always obtain the latest information, and the entire system operates efficiently and accurately.

[1050] (Example 1)

[1051] 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".

[1052] Conventional information acquisition systems have faced challenges in providing users with the information they need appropriately and quickly, and in notifying users in a timely manner when information is updated. Furthermore, when the amount of information generated is large, users may spend a considerable amount of time finding the information they need. To solve these problems, a system is needed that generates relevant information based on user requests, summarizes and efficiently manages that information, and immediately notifies users when it is updated.

[1053] 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.

[1054] In this invention, the server includes means for receiving a user request, converting the request into an appropriate format and sending it to the server; means for generating information based on the request using generative artificial intelligence; and means for summarizing the generated information and storing it in a database. This allows the user to efficiently obtain the necessary information and receive updated information quickly.

[1055] "User" refers to an individual or organization that wishes to obtain information.

[1056] A "request" refers to a voice or text instruction that a user enters through their device to ask for information.

[1057] A "terminal" refers to an electronic device used by a user to enter requests and receive information.

[1058] A "server" refers to a computer system that processes user requests and is responsible for generating, summarizing, storing, updating, and notifying information.

[1059] "Generative artificial intelligence" refers to an algorithm or model that generates information based on input prompts.

[1060] A "prompt message" refers to a sentence that is input to a generative artificial intelligence system to generate information.

[1061] A "summary" refers to a concise compilation of information, extracting the most important parts from the generated data.

[1062] A "database" refers to a system for storing generated summary information and related data.

[1063] "Update" refers to the addition or modification of new information to the generated information.

[1064] "Notification" refers to the act of informing a user that information has been updated.

[1065] This invention relates to a system that generates information based on user requests, summarizes and stores it, periodically checks for updates, and notifies the user if updates are found. This system is composed of the functions and roles of a server, a terminal, and a user.

[1066] Processing user requests

[1067] First, if a user wants to obtain specific information, they input a request into the terminal via voice or text, such as "Please tell me about new products for 2023." The terminal receives this request, converts it to an appropriate format (e.g., JSON), and sends it to the server. At this stage, the user's input becomes the key to identifying what information the system as a whole needs to generate.

[1068] Information generation and summarization

[1069] The server analyzes the received request and extracts necessary keywords and context. For example, if the request is for "new product information for 2023," it will extract keywords such as "2023" and "new products." Based on this analysis, the server uses generative artificial intelligence (e.g., OpenAI GPT-4) to generate relevant data.

[1070] Because the generated information often contains a large amount of data, the server uses a summarization engine (e.g., BERT) to simplify the information. This results in summaries such as, "A new smartphone will be released in 2023, and that model will feature the latest processor."

[1071] Saving summary information and returning it to the user.

[1072] Next, the server saves the generated summary information to the database. This saving process also saves identifying information such as the request ID, making it easy to re-verify and update later. After saving, the server sends the saved summary information back to the terminal. The terminal receives this information, converts it into a display format, and presents it to the user.

[1073] Information update check and notification

[1074] After a certain period of time has passed, or if a manual check is requested, the server will perform an update check on the information. This involves using generative artificial intelligence again to retrieve new relevant information and comparing it with the existing information in the database. For example, if the original information was "A new smartphone will be released in 2023," and then an update is found stating "A new color has been added," the server will update the database with this information.

[1075] When an update is detected, the server sends the update information to the device, and the device uses its notification function to inform the user of the update. In this way, users can always efficiently obtain the latest information.

[1076] Examples of specific cases and prompt statements

[1077] For example, if a user requests "Please tell me about new products for 2023," the server generates the latest information and provides the user with a summary such as "A new smartphone will be released in September 2023." Then, after a few months, if the user sends a follow-up request, the server retrieves the latest information again and notifies the user of updates such as "A new color has been added to the new smartphone." This ensures that the user always has the most up-to-date information.

[1078] Example of a prompt:

[1079] "Please tell me about new product information for 2023."

[1080] The above describes the specific forms for carrying out the invention.

[1081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1082] Step 1:

[1083] When a user wants to obtain specific information, they enter a request into the terminal, such as "Please tell me about new products for 2023." The input format is either voice or text. Input: User's voice or text request. Output: Request as text data.

[1084] Step 2:

[1085] The terminal receives a request from the user and converts it into a format that can be processed (e.g., JSON). After converting to the appropriate data format, the terminal sends this data to the server over the internet. Input: User request in text format. Output: Data in JSON format.

[1086] Step 3:

[1087] The server analyzes the received request data and extracts the necessary keywords and context. Specifically, the server uses natural language processing to extract keywords such as "2023" and "new products" from a request like "new product information for 2023". Input: Request data in JSON format. Output: Extracted keywords and context information.

[1088] Step 4:

[1089] The server uses generative artificial intelligence (e.g., a generative AI model) to generate information based on the extracted keywords. In this process, it generates a prompt and inputs it into the generative AI model. For example, it might create a prompt such as "Please provide the latest information on new products for 2023" and input it into the generative AI model. Input: Extracted keywords and contextual information. Output: Generated information.

[1090] Step 5:

[1091] If the amount of information generated is large, the server uses a summarization engine (e.g., BERT) to summarize the information. For example, it might create a summary such as, "A new smartphone will be released in 2023, and this model will feature the latest processor." Input: Generated information. Output: Summarized information.

[1092] Step 6:

[1093] The server saves the summarized information to the database. The request ID and user ID are also saved at this time to allow for easy retrieval of the information later. Input: Summarized information. Output: Information saved in the database.

[1094] Step 7:

[1095] The server resends the saved summary information to the terminal. The terminal converts the received information into a display format and presents it to the user. Input: Summary information stored in the database. Output: Information presented to the user.

[1096] Step 8:

[1097] After a certain period of time has passed, or when a user submits a reconfirmation request, the server checks for updates to the information. It uses the generative AI model again to retrieve new relevant information and compares it to existing information in the database. Input: User reconfirmation request or timer event. Output: New relevant information.

[1098] Step 9:

[1099] The server compares the new update information with existing information in the database. Once an update is confirmed, it sends the information to the terminal, which then uses its notification function to inform the user of the update. Input: New related information. Output: Update notification to the user.

[1100] The above describes the specific processing steps of the program in this system.

[1101] (Application Example 1)

[1102] 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".

[1103] For modern users, staying up-to-date on the latest information about products and services they are interested in is crucial. However, quickly and accurately obtaining the latest information from a vast amount of data, and regularly checking for updates, is difficult. Furthermore, acquiring information from diverse sources and ensuring its accuracy is also a challenge. In this situation, there is a need for a system that allows users to efficiently and reliably obtain the latest information they require.

[1104] 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.

[1105] In this invention, the server includes means for receiving user requests, means for generating information based on requests using generative artificial intelligence, means for summarizing the generated information and storing it in a database, means for returning the stored summary information to the user, means for periodically checking for updates to the information, means for generating updated information using generative artificial intelligence and updating the database, means for notifying the terminal when the latest information is generated, means for sending a prompt message to the generative artificial intelligence, means for generating relevant information based on product categories, and means for displaying the latest information to the user. As a result, the user can always quickly and reliably obtain the latest information on products of interest and automatically receive update information.

[1106] "Means of receiving user requests" refers to an interface that allows users to input specific information and the functionality of the system that processes that input.

[1107] "Generative artificial intelligence" refers to artificial intelligence technology that has the ability to generate relevant information based on input data.

[1108] "Means for summarizing information and storing it in a database" refers to the functions of a storage device and system for converting generated information into a concise format and accumulating that summarized information.

[1109] "Means for returning saved summary information to the user" refers to a system function that retrieves summary information stored in a database and provides it to the user.

[1110] "Means of regularly checking for updates to information" refers to a system function that checks at regular intervals whether the stored information is up-to-date.

[1111] "A means of generating update information and updating a database using generative artificial intelligence" refers to a system function that uses artificial intelligence technology to generate new information and replace existing information in a database with it.

[1112] "Means of notifying the device when new information is generated" refers to a system function that sends a notification to the user's device when new information is generated.

[1113] "Means for sending prompt messages to a generative artificial intelligence" refers to a function of a system that inputs instruction messages for information generation to a generative artificial intelligence.

[1114] "Means for generating relevant information based on product categories" refers to a system function that acquires and generates relevant information based on product categories that the user is interested in.

[1115] "Means of displaying the latest information to the user" refers to a system function that displays the generated latest information on the user's interface.

[1116] To implement this invention, a system is required in which a server, a terminal, and a user each have their own respective roles.

[1117] Processing user requests

[1118] First, if a user wants to obtain specific information, they enter a request through a smartphone application, such as "Please tell me the information about the new smartphone." This request is received by the device, converted into the appropriate format, and sent to the server.

[1119] Information generation and summarization

[1120] The server analyzes the received request and extracts necessary keywords and context. For example, if the request is for "information on a new smartphone," keywords such as "smartphone" and "new" will be extracted. Based on this analysis, the server uses a generative AI model (e.g., GPT-4) to generate relevant information. Because the generated information may be complex, the server uses a summarization engine (e.g., PEGASUS) to create a concise summary.

[1121] Saving summary information and returning it to the user.

[1122] The server saves the summarized information to a database. At this stage, the request ID and related metadata are also saved, making it easier to review and check for updates later. The saved information is sent back to the user's terminal, which then displays it to the user.

[1123] Information update check and notification

[1124] After a certain period of time, or when a manual check is requested, the server performs an information update check. It uses the generated AI model again to retrieve new relevant information and compares it with existing information in the database. If an update is found, the database is updated, and the server sends the update to the user's terminal. The terminal then notifies the user of the latest information.

[1125] Hardware and software usage

[1126] This system uses devices such as smartphones and tablets, centralized cloud servers (e.g., AWS, Google Cloud), and generative AI models (e.g., GPT-4) and summarization engines (e.g., PEGASUS).

[1127] Specific example

[1128] When a user enters a request into the application, such as "Please tell me about the new smartphone," the server receives the request and uses a generative AI model to generate information such as, "A new smartphone is scheduled to be released in 2023. This model will feature the latest processor and enhanced camera capabilities." This information is then summarized concisely by a summarizing engine and stored in a database. When the information is updated, the server notifies the user's device of the new information, such as, "A new color has since been added." A concrete example of a prompt sent to the generative AI model is, "Please tell me about the new smartphone coming in 2023."

[1129] This system allows users to efficiently obtain the latest and most accurate information.

[1130] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1131] Step 1:

[1132] The user opens a smartphone application and enters a specific information request (e.g., "Please tell me information about my new smartphone") via voice or text.

[1133] Input: User's voice or text request

[1134] Output: Formatted request data sent to the terminal

[1135] Operation: The application converts the user's speech into text (using speech recognition software) and then converts the acquired text data into an appropriate format.

[1136] Step 2:

[1137] The terminal sends the formatted request data to the server.

[1138] Input: Formatted request data

[1139] Output: Request data sent to the server

[1140] Operation: The terminal sends the request data to the server as an HTTP request and waits for a response.

[1141] Step 3:

[1142] The server receives and parses the request data. Specifically, it extracts necessary keywords and context from the request.

[1143] Input: Request data sent to the server

[1144] Output: Extracted keywords and contextual information

[1145] Operation: The analysis engine on the server (using natural language processing software) analyzes the data and extracts keywords and context.

[1146] Step 4:

[1147] The server uses a generative AI model (e.g., GPT-4) to generate relevant information based on extracted keywords and context.

[1148] Input: Extracted keywords and contextual information

[1149] Output: Generated information

[1150] Operation: Input prompts into the generative AI model and retrieve the generated information.

[1151] Step 5:

[1152] If the generated information is complex, the server uses a summarization engine (e.g., PEGASUS) to create a concise summary.

[1153] Input: Generated details

[1154] Output: Summarized information

[1155] Operation: Starts the summarization engine and creates a concise summary using the generated information as input.

[1156] Step 6:

[1157] The server stores the summarized information in the database.

[1158] Input: Summarized information, request ID, related metadata

[1159] Output: Summary information stored in the database

[1160] Function: Saves summary information to a database management system (e.g., MySQL).

[1161] Step 7:

[1162] The server sends the saved summary information back to the terminal.

[1163] Input: Summary information stored in the database

[1164] Output: Summary information sent to the terminal

[1165] Operation: Sends summary information to the terminal as an HTTP response.

[1166] Step 8:

[1167] The terminal displays the returned summary information to the user.

[1168] Input: Summary information sent from the server

[1169] Output: Summary information displayed to the user

[1170] Operation: The application displays the received summary information in the user interface.

[1171] Step 9:

[1172] The server periodically checks for updates to the information, and if new information is available, it reuses the generated AI model to retrieve the relevant information.

[1173] Input: Time interval for periodic checks, existing information

[1174] Output: New generated information

[1175] Operation: Sends an update request to the generative AI model and generates new information.

[1176] Step 10:

[1177] The server compares new information with existing information and updates the database if there are any differences.

[1178] Input: New generated information, existing information

[1179] Output: Updated database

[1180] Operation: Compares new information with existing information and updates the database if differences are detected.

[1181] Step 11:

[1182] When the server detects an information update, it notifies the user's device of the update details.

[1183] Input: Update details

[1184] Output: Notification to user terminal

[1185] Operation: Notifies the user's terminal of the latest information using the notification system.

[1186] A concrete example of a prompt is, "Please tell me about the new smartphone." This prompt prompt prompts the AI ​​model to generate the latest relevant information.

[1187] 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.

[1188] This invention provides a system that generates information based on user requests, summarizes and stores it, periodically checks for updates, and notifies the user if updates are found, in addition to utilizing an emotion engine that recognizes the user's emotions. The program of this system is composed of the functions and roles of the server, terminal, and user.

[1189] User request processing and sentiment recognition

[1190] First, the user enters a request for information into the device. For example, when a user enters a request such as "Please tell me about new products for 2023" via voice or text, the emotion engine analyzes emotional data from the user's voice tone and the content of the text message. It identifies emotional states such as joy, sadness, anger, and anxiety.

[1191] Information generation and summarization

[1192] The terminal retrieves user requests and sentiment data, converts them into an appropriate format, and sends them to the server. The server receives the requests and sentiment data, analyzes the request content, and extracts necessary keywords, such as "2023" and "new product."

[1193] Next, the server generates information based on keywords extracted using generative artificial intelligence. For example, it collects and processes relevant news and data. The large amount of generated information is then passed to a summarization engine, where key points are extracted and a concise summary is created. The content and format of the summary are adjusted based on information analyzed from sentiment data. For instance, if the user is excited, a summary containing more detailed technical information might be provided.

[1194] Saving summary information and returning it to the user.

[1195] The server saves the generated summary information and identification information such as the request ID to a database. After saving, the server sends the summary information back to the terminal. The terminal converts the received summary information into a display format and presents it to the user. For example, it might display "A new smartphone will be released in 2023" in a format that suits the user's mood.

[1196] Information update check and notification

[1197] After a certain period of time has passed, or if a user requests reconfirmation, the server checks for updates to the information. It uses generative artificial intelligence again to retrieve the latest relevant information and compares it with the existing information in the database. For example, if the original information was "A new smartphone will be released in 2023," and then an update is found such as "A new color has been added," the server will record this information in the database and update it.

[1198] Once an update is detected, the server sends the update information to the device, and the device notifies the user of the update at the appropriate time and in the appropriate style based on sentiment data. For example, it might display on the screen, "New smartphone information has been updated: New colors have been added." If the user is happy, the message will be displayed in a bright design.

[1199] By combining these emotion engines, it becomes possible to provide information that adapts to the user's emotional state, enabling the entire system to deliver a more personalized information experience.

[1200] The following describes the processing flow.

[1201] Step 1:

[1202] The user enters a request for information into the device. For example, they might enter a request such as "Please tell me about new products for 2023" via voice or text. During this process, the device collects emotional data from the user's voice tone and the nuances of their text.

[1203] Step 2:

[1204] The terminal retrieves the user's request and sentiment data, converts it into the appropriate format, and sends it to the server. The formatting ensures that the request and sentiment data are accurately conveyed.

[1205] Step 3:

[1206] The server receives the request and analyzes it. Keywords such as "2023" and "new product" are extracted from the request. At the same time, emotional data is analyzed to identify the user's emotional state. This analysis determines whether the user is excited, calm, anxious, etc.

[1207] Step 4:

[1208] The server uses generative artificial intelligence to generate information based on extracted keywords. For example, it collects relevant data from news articles and databases and generates information based on that data. Sentimental data is also taken into consideration when generating the information.

[1209] Step 5:

[1210] The server passes the large amount of generated information to the summarization engine. The summarization engine extracts the key points and creates a concise summary. Based on sentiment data, the content and format of the summary are adjusted. For example, if the user is excited, a summary containing more detailed technical information will be provided.

[1211] Step 6:

[1212] The server stores the generated summary information and identification information such as the request ID in a database. This makes it easy to perform update checks and re-verifications later.

[1213] Step 7:

[1214] The server sends the saved summary information back to the terminal. The terminal receives the summary information, converts it into a display format, and presents it to the user. For example, it might display "A new smartphone will be released in 2023" in a format that suits the user's mood.

[1215] Step 8:

[1216] After a certain period, or upon a user request for reconfirmation, the server checks for updates to the information. It then uses generative artificial intelligence again to retrieve the latest relevant information.

[1217] Step 9:

[1218] The server compares the newly retrieved information with existing information in the database to check for updates. For example, it checks for new information such as "a new color has been added."

[1219] Step 10:

[1220] When an update is detected, the server updates the corresponding entry in the database and sends the update information to the terminal. This ensures that the information in the database is always up-to-date.

[1221] Step 11:

[1222] The device receives update information and notifies the user. For example, it might display "New smartphone information has been updated: New colors have been added" on the screen. When a notification is displayed, the display method is adjusted according to the user's emotions; for example, a brighter design is used if the user is happy.

[1223] In this way, it becomes possible to recognize the user's emotions and provide information that is adapted to them, thereby improving the user experience.

[1224] (Example 2)

[1225] 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".

[1226] Traditional information delivery systems often failed to consider user emotions, resulting in a lack of information tailored to user needs and inappropriate presentation methods. Furthermore, the generated information was not frequently updated, making it difficult for users to access the latest information. Accuracy was also a challenge, as data collection from reliable external sources was insufficient.

[1227] 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.

[1228] In this invention, the server includes means for receiving user requests, means for analyzing requests and collecting sentiment data, means for generating information based on the requests and sentiment data using generative artificial intelligence, means for summarizing the generated information, means for storing the summarized information in a database, means for returning the stored summarized information to the user, means for periodically checking for updates to the stored information, means for generating the updated information using the generative artificial intelligence and updating the database, and means for notifying the user of the updated information. This enables the provision of information adapted to the user's emotions and allows the user to be provided with the latest information that is updated regularly. Furthermore, the accuracy of the information provided is enhanced by collecting data from reliable external sources.

[1229] "Means for receiving user requests" refers to devices or interfaces for receiving information retrieval requests from users. Specifically, this refers to voice input devices and text input interfaces.

[1230] "Means for analyzing requests and collecting sentiment data" refers to a system that analyzes the content of a user's request and collects the user's emotional state from the tone of voice and text content at that time. Specifically, it uses a natural language processing engine and sentiment analysis algorithm.

[1231] "Means for generating information based on the aforementioned request and sentiment data using generative artificial intelligence" refers to a technology for generating relevant information based on user requests and sentiment data using generative artificial intelligence. Specifically, it refers to a generative AI model.

[1232] "Methods for summarizing generated information" refer to techniques for extracting important parts from large amounts of generated information and creating a concise summary. This utilizes the summarization capabilities of generative artificial intelligence.

[1233] "Means for storing summarized information in a database" refers to a device or system that records and stores summarized information and associated identification information in a database. Specifically, it refers to a database management system.

[1234] "Means for returning stored summary information to the user" refers to means for notifying or providing stored summary information to the user. Specifically, it refers to servers or interfaces that transmit information over a network.

[1235] "Means for periodically checking for updates to stored information" refers to technologies for periodically verifying whether stored information is up-to-date. Specifically, this refers to scheduling systems and information gathering engines.

[1236] "Means for generating the update information and updating the database using the generative artificial intelligence" refers to a technology for generating new information and updating existing database information using generative artificial intelligence.

[1237] "Means of notifying users of updates" refers to means of informing users of updates when information is updated. Specifically, this refers to notification systems and alert functions.

[1238] "Means for receiving requests for information reconfirmation" refers to devices or interfaces for receiving reconfirmation requests from users.

[1239] "Means for sending the reconfirmation request to the generative artificial intelligence and comparing it with the existing information" refers to a technique for sending a reconfirmation request to the generative artificial intelligence and comparing the new information with the existing information.

[1240] "Means for generating new summary information when an update is detected" refers to means for generating new summary information when it is confirmed that the information has been updated.

[1241] "Means of improving the accuracy of generated information by acquiring information from generative artificial intelligence and reliable external sources" refers to technologies that use generative artificial intelligence and collect information from reliable external data sources to improve the accuracy of the information provided.

[1242] This invention is an information provision system that generates information based on user requests, summarizes and stores it, periodically checks for updates, and notifies the user if there are any updates. Furthermore, by incorporating an emotion engine that recognizes the user's emotional state, the system achieves more appropriate and personalized information provision. This invention is composed of the functions and roles of the server, terminal, and user.

[1243] First, the user enters a request for information into the device. For example, if the user enters a request such as "Please tell me about new products for 2023" via voice or text, the emotion engine analyzes emotional data from the user's voice tone and the content of the text message. The emotion engine uses an emotion analysis algorithm and a natural language processing engine (e.g., Microsoft Azure Cognitive Services). This engine identifies emotional states such as joy, sadness, anger, and anxiety.

[1244] Next, the terminal retrieves the user's request and sentiment data, converts it into an appropriate format, and sends it to the server. At this stage, the JSON format is used as the data conversion method, and it is sent via the HTTPS protocol.

[1245] The server analyzes the received request and sentiment data to extract necessary keywords. For example, a natural language processing engine (e.g., SpaCy) is used to identify the keywords "2023" and "new product." Then, a generative artificial intelligence (e.g., OpenAI GPT-4) is used to generate information based on the extracted keywords. Specifically, it collects and processes relevant news and data. Because the amount of information generated is large, it is passed to a summarization engine (e.g., GPT-4's summarization function) to create a concise summary with the key points extracted. Based on sentiment data, the content and format of the summary are adjusted; for example, if the user is excited, a summary containing more detailed technical information is provided.

[1246] The following are specific examples of prompt statements for a generative AI model:

[1247] "Research the new product information for 2023 and create a summary that includes detailed technical information suitable for users who are excited about the product."

[1248] The generated summary information is stored by the server in a database (e.g., MySQL). After saving, the server sends the summary information back to the terminal, which converts the received summary information into a display format and presents it to the user. For example, it might display "A new smartphone will be released in 2023."

[1249] After a certain period of time has passed, or if a user requests reconfirmation, the server checks for updates to the information. In this process, generative artificial intelligence (e.g., OpenAI GPT-4) is used to retrieve the latest relevant information and compare it with existing information in the database. For example, if the original information was "A new smartphone will be released in 2023," and an update is found later stating "A new color has been added," the server will record this information in the database and update it.

[1250] Once an update is detected, the server sends the update information to the device, and the device notifies the user of the update at the appropriate time and in the appropriate style based on sentiment data. For example, the screen might display, "New smartphone information has been updated: New colors have been added." If the user is happy, the message will be displayed in a bright design.

[1251] Thus, the present invention makes it possible to provide information that is adapted to the user's emotional state, enabling the entire system to provide a more personalized information experience.

[1252] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1253] Step 1:

[1254] The user enters an information retrieval request. For example, they might enter a request via voice or text, such as, "Please tell me about new products for 2023." This request becomes the input data for the system.

[1255] Step 2:

[1256] The device collects requests and emotional data. After receiving user input, it uses an emotion engine (e.g., a natural language processing algorithm) to analyze the user's voice tone and text content to obtain emotional data such as joy, sadness, anger, and anxiety. The input data consists of the user's request and emotional state, while the output data is the analyzed emotional information.

[1257] Step 3:

[1258] The device sends the request and sentiment data to the server. The retrieved request and sentiment data are converted to JSON format and sent to the server using the HTTPS protocol. The input data consists of the request and sentiment information, and the output data is a notification that the transmission to the server is complete.

[1259] Step 4:

[1260] The server parses the request. It analyzes the received request using a natural language processing engine (e.g., SpaCy) and extracts necessary keywords (e.g., "2023", "new product"). The input data is the request data in JSON format, and the output data is the extracted keywords.

[1261] Step 5:

[1262] The server generates information using generative artificial intelligence. Generative AI such as GPT-4 is used to generate relevant information based on extracted keywords. In this process, relevant news and data are collected and processed. The input data consists of extracted keywords, and the output data consists of the generated information.

[1263] Step 6:

[1264] The server summarizes the generated information. The generated information is passed to a summarization engine (e.g., GPT-4's summarization function), which extracts key points and creates a concise summary. The input data is the generated information, and the output data is the summary. This summary is adjusted based on sentiment data. For example, if the user is excited, the summary will include more technical details.

[1265] Step 7:

[1266] The server saves summary information to the database. The summary information and identification information such as the request ID are saved to the database (e.g., MySQL). The input data consists of the summary information and identification information, while the output data is a notification that the database save is complete.

[1267] Step 8:

[1268] The server sends summary information back to the terminal. The summary information stored in the database is sent to the terminal using the HTTPS protocol. The input data is the summary information, and the output data is a notification that transmission to the terminal is complete.

[1269] Step 9:

[1270] The terminal displays the summary information in an appropriate format. It converts the received summary information into a format suitable for display on the user interface. For example, it explicitly displays information such as "A new smartphone will be released in 2023" on the screen. The input data is the summary information from the server, and the output data is the display on the user interface.

[1271] Step 10:

[1272] The server periodically checks for updates to the information. After a certain period, or upon a user request for reconfirmation, it uses generative artificial intelligence to retrieve the latest relevant information and compare it with the existing information. The input data is the existing information in the database, and the output data is whether or not the information has been updated and the new information.

[1273] Step 11:

[1274] The server saves update information to the database. When new information is found, it is saved to the database and the existing information is updated. The input data is the new information, and the output data is a notification that the information has been saved to the database.

[1275] Step 12:

[1276] The server sends update information to the terminal. The updated information is sent to the terminal using the HTTPS protocol. The input data is the update information, and the output data is a notification that the transmission to the terminal is complete.

[1277] Step 13:

[1278] The device notifies the user of update information. The received update information is converted into a display format suitable for the user and then notified. For example, it might display "New smartphone information has been updated: New colors have been added" on the screen. The display style is adjusted based on sentiment data. For example, if the user is happy, a bright design is used. The input data is the update information, and the output data is the notification to the user interface.

[1279] (Application Example 2)

[1280] 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".

[1281] Conventional electronic payment systems have a problem in that information provision based on user requests is one-way, and they cannot provide personalized advice or notifications that are tailored to the user's emotions or state. Furthermore, when users make electronic payments while experiencing various emotional states such as anxiety or excitement, they are not provided with spending management or campaign information that is adapted to their emotions, resulting in a poor user experience. The present invention aims to solve these problems and realize personalized information provision that is adapted to the user's emotions.

[1282] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for receiving user requests, means for generating information based on the request using generative artificial intelligence, means for summarizing the generated information and storing it in a database, means for returning the stored summary information to the user, means for periodically checking for updates to the information, means for generating the updated information using the generative artificial intelligence and updating the database, means for notifying the user of the updated information, means including an emotion engine for analyzing the user's emotions, and means for personalizing the summary information and notification content based on the emotion data. This makes it possible to provide expenditure management advice and campaign information notifications adapted to the user's emotional state.

[1283] A "user request" is a specific instruction or inquiry from a user requesting information from the system.

[1284] "Generative artificial intelligence" refers to artificial intelligence technology used to generate information based on user requests.

[1285] A "database" is a repository of information that stores information and summaries generated within a system, making it accessible and updatable at a later date.

[1286] An "emotion engine" is an engine that analyzes emotional data from a user's voice and text to identify the user's emotional state.

[1287] "Personalization" refers to adjusting the content of information and notifications according to the individual characteristics and circumstances of each user.

[1288] A "request ID" is an identifier used to uniquely identify each user request.

[1289] A "summarization engine" is an engine that extracts important points from generated information and creates a concise summary.

[1290] "Update information" refers to information that has been generated and saved once, and is regenerated to show subsequent changes or additions.

[1291] A "notification" is a message or alert used to inform users of updates or important information.

[1292] This invention relates to an electronic payment system that provides personalized information in response to the user's emotions. The system includes multiple means to receive user requests, generate information using generative artificial intelligence, and summarize, store, and update that information. It then provides information based on the user's emotions.

[1293] First, the user enters a request for information retrieval into the device using their smartphone. For example, when a user enters a request such as "I'm worried about how I've been spending money lately" via voice or text, the emotion engine analyzes emotional data from the user's voice tone and the content of the text message. As a result of the analysis, an emotional state such as joy, sadness, anger, or anxiety is identified.

[1294] Next, the terminal retrieves the user's request and sentiment data, converts it into an appropriate format, and sends it to the server. The server receives the request and sentiment data, analyzes the request content, and extracts necessary keywords. For example, keywords such as "recently," "money," and "worry."

[1295] The server generates information based on keywords extracted using generative artificial intelligence. For example, it collects and processes relevant news and spending advice. The large amount of generated information is then passed to a summarization engine, where key points are extracted and a concise summary is created. The content and format of the summary are adjusted based on information analyzed from sentiment data. For instance, if the user is feeling anxious, advice on reducing spending might be provided.

[1296] The server saves the generated summary information and identification information such as the request ID to a database. After saving, the server sends the summary information back to the terminal. The terminal converts the received summary information into a display format and presents it to the user. For example, it might display "Are you okay? Here are some tips for managing your spending: The best way to manage your spending is to set a budget," in a format that suits the user's mood.

[1297] After a certain period of time has passed, or if the user requests reconfirmation, the server checks for updates to the information. It uses generative artificial intelligence again to retrieve the latest relevant information and compares it with the existing information in the database. For example, if the original information was "Tips for managing your expenses," and then an update is found such as "A new expense management app is out," the server records this information in the database and updates it. Once the update is confirmed, the server sends the update information to the device, and the device notifies the user of the update information at an appropriate time and in an appropriate style based on sentiment data. For example, "A new expense management app is out" might be displayed on the screen. In this case, if the user is happy, it will be displayed in a bright design.

[1298] As a concrete example, if the user input is "I'm worried about how I've been spending money lately," the prompt message from the generating AI model would be as follows:

[1299] "Analyze the sentiment of this text: I'm worried about how I've been spending money lately."

[1300] This enables the delivery of personalized information that matches the user's emotions. The entire system is designed to improve the user experience.

[1301] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1302] Step 1:

[1303] The user enters an information request using their smartphone. The input can be via voice or text, and may be a specific request such as "I'm worried about how I've been spending money lately." The input data (voice or text) is sent to an emotion engine, which analyzes the user's emotional state (joy, sadness, anger, anxiety, etc.). The results of this analysis are obtained as emotion data. The input data is the user's request, and the output data is the emotion data.

[1304] Step 2:

[1305] The device sends the user's request and sentiment data to the server. The server receives the request and sentiment data, analyzes the request, and extracts necessary keywords. For example, it might extract keywords such as "recently," "money," and "worry." This analysis is performed using natural language processing techniques. The input data consists of the request and sentiment data, and the output data consists of the extracted keywords.

[1306] Step 3:

[1307] The server generates information based on keywords extracted using generative artificial intelligence. Specifically, it collects relevant news and expense management advice, and generates information using generative artificial intelligence (e.g., GPT-3). The input data is the extracted keywords, and the output data is the generated information.

[1308] Step 4:

[1309] The server passes the generated information to the summarization engine, which extracts key points and creates a concise summary. The summary content and format are adjusted based on sentiment data. For example, if the user is feeling anxious, the generated summary will contain more advice on reducing spending. The input data consists of the generated information and sentiment data, while the output data is the summarized information.

[1310] Step 5:

[1311] The server saves summary information and identification information such as the request ID to the database. The input data is the summary information and the request ID, and the output data is a notification that the data has been saved to the database.

[1312] Step 6:

[1313] The server sends summary information back to the terminal. The terminal converts the received summary information into a display format and presents it to the user. The information is displayed in a format that suits the user's mood. The input data is summary information, and the output data is the information presented to the user.

[1314] Step 7:

[1315] The server checks for updates to information after a certain period of time has elapsed or when a user requests reconfirmation. Generative artificial intelligence is used to retrieve the latest relevant information and compare it with existing information in the database. Input data is the reconfirmation request or notification of the elapsed period, and output data is the updated information.

[1316] Step 8:

[1317] The server notifies the user of update information. The device notifies the user of the update information at the appropriate time and in the appropriate style based on sentiment data. For example, a notification such as "A new expense management app is available" might be sent. In this case, if the user is happy, it will be displayed in a bright design. The input data is the update information, and the output data is the information that is notified to the user.

[1318] 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.

[1319] 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.

[1320] 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 robot 414.

[1321] 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.

[1322] 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.

[1323] 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.

[1324] 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.

[1325] 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.

[1326] 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."

[1327] 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.

[1328] 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.

[1329] 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.

[1330] 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.

[1331] 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.

[1332] 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.

[1333] 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.

[1334] 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.

[1335] 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.

[1336] 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.

[1337] 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.

[1338] 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.

[1339] The following is further disclosed regarding the embodiments described above.

[1340] (Claim 1)

[1341] A means of receiving user requests,

[1342] A means for generating information based on the aforementioned request using generative artificial intelligence,

[1343] A means of summarizing the generated information and storing it in a database,

[1344] A means of returning saved summary information to the user,

[1345] A means of periodically checking for updates to the aforementioned information,

[1346] A means for generating the update information using the aforementioned generative artificial intelligence and updating the database,

[1347] A system that includes means for notifying users of update information.

[1348] (Claim 2)

[1349] A means of receiving requests for reconfirmation of information,

[1350] A means for sending the aforementioned reconfirmation request to the generative artificial intelligence and comparing it with the existing information,

[1351] The means of generating new summary information when an update is detected further includes:

[1352] The system according to claim 1.

[1353] (Claim 3)

[1354] This further includes means of acquiring information from generative artificial intelligence and reliable external sources to improve the accuracy of the generated information.

[1355] The system according to claim 1.

[1356] "Example 1"

[1357] (Claim 1)

[1358] A means of obtaining a user request, converting that request into an appropriate format, and sending it to the server,

[1359] A means for generating information based on the aforementioned request using generative artificial intelligence,

[1360] A means of summarizing the generated information and storing it in a database,

[1361] A means of sending saved summary information to a terminal, and the terminal formatting that information and presenting it to the user,

[1362] A means of periodically checking for updates to the aforementioned information,

[1363] A means for generating the update information using the aforementioned generative artificial intelligence and updating the database,

[1364] A system that includes means for notifying users of update information.

[1365] (Claim 2)

[1366] A means of receiving requests for reconfirmation of information,

[1367] A means for sending the aforementioned reconfirmation request to the generative artificial intelligence and comparing it with the existing information,

[1368] The means of generating new summary information when an update is detected further includes:

[1369] The system according to claim 1.

[1370] (Claim 3)

[1371] This further includes means of acquiring information from generative artificial intelligence and reliable external sources to improve the accuracy of the generated information.

[1372] The system according to claim 1.

[1373] "Application Example 1"

[1374] (Claim 1)

[1375] A means of receiving user requests,

[1376] A means for generating information based on the aforementioned request using generative artificial intelligence,

[1377] A means of summarizing the generated information and storing it in a database,

[1378] A means of returning saved summary information to the user,

[1379] A means of periodically checking for updates to the aforementioned information,

[1380] A means for generating the update information using the aforementioned generative artificial intelligence and updating the database,

[1381] A means of notifying the device when the latest information is generated,

[1382] A means for sending a prompt message to the aforementioned generative artificial intelligence,

[1383] A means for generating relevant information based on product categories,

[1384] A system that includes means for displaying the latest information to the user.

[1385] (Claim 2)

[1386] A means of receiving requests for reconfirmation of information,

[1387] A means for sending the aforementioned reconfirmation request to the generative artificial intelligence and comparing it with the existing information,

[1388] The means of generating new summary information when an update is detected further includes:

[1389] The system according to claim 1.

[1390] (Claim 3)

[1391] This further includes means of acquiring information from generative artificial intelligence and reliable external sources to improve the accuracy of the generated information.

[1392] The system according to claim 1.

[1393] "Example 2 of combining an emotion engine"

[1394] (Claim 1)

[1395] A means of receiving user requests,

[1396] A means of analyzing requests and collecting sentiment data,

[1397] A means for generating information based on the aforementioned request and emotion data using generative artificial intelligence,

[1398] A means of summarizing the generated information,

[1399] A means of storing summarized information in a database,

[1400] A means of returning saved summary information to the user,

[1401] A means of periodically checking for updates to saved information,

[1402] A means for generating the update information using the aforementioned generative artificial intelligence and updating the database,

[1403] A system that includes means for notifying users of update information.

[1404] (Claim 2)

[1405] A means of receiving requests for reconfirmation of information,

[1406] A means for sending the aforementioned reconfirmation request to the generative artificial intelligence and comparing it with the existing information,

[1407] The means of generating new summary information when an update is detected further includes:

[1408] The system according to claim 1.

[1409] (Claim 3)

[1410] This further includes means of acquiring information from generative artificial intelligence and reliable external sources to improve the accuracy of the generated information.

[1411] The system according to claim 1.

[1412] "Application example 2 when combining with an emotional engine"

[1413] (Claim 1)

[1414] A means of receiving user requests,

[1415] A means for generating information based on the aforementioned request using generative artificial intelligence,

[1416] A means of summarizing the generated information and storing it in a database,

[1417] A means of returning saved summary information to the user,

[1418] A means of periodically checking for updates to the aforementioned information,

[1419] A means for generating the update information using the aforementioned generative artificial intelligence and updating the database,

[1420] A means of notifying users of update information,

[1421] A means including an emotion engine that analyzes user emotions,

[1422] A system including means for personalizing summary information and notification content based on the aforementioned sentiment data.

[1423] (Claim 2)

[1424] A means of receiving requests for reconfirmation of information,

[1425] A means for sending the aforementioned reconfirmation request to the generative artificial intelligence and comparing it with the existing information,

[1426] The means of generating new summary information when an update is detected further includes:

[1427] The system according to claim 1.

[1428] (Claim 3)

[1429] This further includes means of acquiring information from generative artificial intelligence and reliable external sources to improve the accuracy of the generated information.

[1430] The system according to claim 1. [Explanation of Symbols]

[1431] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving user requests, A means for generating information based on the aforementioned request using generative artificial intelligence, A means of summarizing the generated information and storing it in a database, A means of returning saved summary information to the user, A means of periodically checking for updates to the aforementioned information, A means for generating the update information using the aforementioned generative artificial intelligence and updating the database, A system that includes means for notifying users of update information.

2. A means of receiving requests for reconfirmation of information, A means for sending the aforementioned reconfirmation request to the generative artificial intelligence and comparing it with the existing information, The means of generating new summary information when an update is detected further includes: The system according to claim 1.

3. This further includes means of acquiring information from generative artificial intelligence and reliable external sources to improve the accuracy of the generated information. The system according to claim 1.

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