system

Abstract

We provide the system. [Solution] A means of regularly collecting update information from multiple data sources on the internet, A means of analyzing the collected update information and converting it into a standardized data format, A means of saving the converted data to a database, A means for automatically generating a document format (including slides or spreadsheets) based on saved data, A system that includes a means of notifying users when new update information is added.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a modern business environment, it is very important for enterprises to always grasp and quickly respond to update information of commercial products provided or used by them. However, the work of manually collecting, organizing, and reflecting this update information in documents or spreadsheets takes time and effort. In addition, there is a high possibility of human errors, and the problems are that the accuracy and real-time nature of the information cannot be guaranteed. The purpose of this invention is to provide a system that automatically collects, analyzes, generates documents, and notifies update information in order to solve these problems.

Means for Solving the Problems

[0005] The present invention is a system that includes means for periodically collecting update information from multiple data sources on the internet, means for analyzing the collected update information and converting it into a standardized data format, means for storing the converted data in a database, means for automatically generating a document format (including slides or spreadsheets) based on the stored data, and means for notifying users when new update information is added. This enables companies and users to quickly grasp the latest update information, improving the efficiency of operations and the accuracy of information. In particular, since the document format is generated using cloud-based presentation and spreadsheet services, users can easily access and share it. Furthermore, by using API requests or web scraping as the collection means, information can be collected from a wide range of data sources.

[0006] "Data sources" refer to multiple sources on the internet that provide update information.

[0007] "Update information" refers to information regarding the addition of new features, bug fixes, version changes, etc., for the target product.

[0008] "Means of collection" refers to methods and technologies for regularly obtaining update information from data sources on the internet.

[0009] "Means of analysis" refers to methods and techniques for understanding the meaning and content of collected update information using natural language processing and other technologies, and for extracting necessary information.

[0010] "Standardized data format" refers to converting analyzed information into a predefined format, creating a uniform and orderly structure.

[0011] "Means of saving to a database" refers to systems and technologies for continuously storing and managing analyzed and transformed data.

[0012] "Document format" refers to the output format, such as slides or spreadsheets.

[0013] "Means of generation" refers to methods and technologies for automatically creating document-formatted output based on stored data.

[0014] "Notification methods" refer to systems and technologies used to inform users when new update information is added.

[0015] "Cloud-based presentation and spreadsheet services" refer to services for creating, editing, and sharing presentations and spreadsheets that are provided on a cloud accessible via the internet.

[0016] An "API request" refers to a request sent to an Application Programming Interface (API) provided over the internet in order to retrieve specific data.

[0017] "Web scraping" refers to the technique of analyzing the HTML code of a website and automatically extracting the necessary data. [Brief explanation of the drawing]

[0018] [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.

Mode for Carrying Out the Invention

[0019] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0020] First, the language used in the following description will be explained.

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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).

[0025] 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."

[0026] [First Embodiment]

[0027] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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".

[0039] This invention relates to a system that automatically collects and analyzes product update information, generates related documents, and notifies users. In particular, it periodically collects update information, converts it into a standardized data format, stores it in a database, and further generates output in cloud-based presentation or spreadsheet format.

[0040] Program Processing Overview

[0041] 1. Data Collection

[0042] The server collects product update information from multiple data sources based on a regular schedule. For example, the server sends an HTTP request to the API endpoint of product A and receives JSON data as a response. The data obtained in this way includes the latest version information and corrections for that product.

[0043] 2. Information Analysis and Transformation

[0044] The server uses natural language processing (NLP) to analyze the collected JSON data and extract the necessary information. This analysis yields specific version numbers, types of changes (bug fixes, new features, etc.), and detailed descriptions. The analyzed information is then converted into a predefined standardized format.

[0045] 3. Storing in a database

[0046] The extracted and standardized data is stored in a database. Because the database is structured, the information can be retrieved and used quickly and efficiently later.

[0047] 4. Automatic output generation

[0048] The server automatically generates document formats (slides or spreadsheets) based on information stored in the database. For example, it uses the Google® Slides API to generate a new presentation and insert update information into the slides. Similarly, when outputting as a spreadsheet, the API is used to input the data.

[0049] 5. Update notification

[0050] When the server detects new update information, it sends a notification to the user. By using methods such as email and push notifications, users can quickly receive the latest information.

[0051] Specific example

[0052] For example, if the latest version 2.0.1 of product A is released, its release notes will include information such as "Login problem fixed" and "Dark mode added." The server collects this information via an API, analyzes it, and converts it into a standardized data format as follows.

[0053] json

[0054] {

[0055] "product": "A",

[0056] "version": "2.0.1",

[0057] "updates": [

[0058] {"type": "bugfix", "description": "Fixed login issue"},

[0059] {"type": "feature", "description": "Added dark mode"}

[0060] ]

[0061] }

[0062] This information is stored in a database and automatically updated whenever it is updated. Next, based on the output format selected by the user, a presentation is automatically generated, for example, using Google Slides. The generated slides include:

[0063] 1. Title Slide: "Product A Version 2.0.1 Update"

[0064] 2. Content slides: "1. Fixed login issues" "2. Added dark mode"

[0065] The data is entered in this format.

[0066] Finally, users are notified by email when new update information is added. The email body includes a brief summary and a link to further details. In this way, users can quickly and efficiently grasp new update information.

[0067] The following describes the processing flow.

[0068] Step 1:

[0069] The server sends an HTTP request to an API endpoint on the internet based on a schedule. This request is to retrieve the latest update information for a product; for example, it sends a request GET https: / / api.example.com / productA / updates to retrieve update information for product A.

[0070] Step 2:

[0071] The server receives JSON data as a response from the API. This response contains information such as new version information, changes, and bug fixes for the product, and is ready to be analyzed in the next step.

[0072] Step 3:

[0073] The server parses the received JSON data and uses natural language processing (NLP) tools to extract important information (version number, changes, etc.). For example, it might obtain information such as version "2.0.1", "login issue fixed", and "dark mode added".

[0074] Step 4:

[0075] The server converts the parsed information into a standardized data format. This standardized format is a unified format defined for use in the system, and may look like this:

[0076] json

[0077] {

[0078] "product": "A",

[0079] "version": "2.0.1",

[0080] "updates": [

[0081] {"type": "bugfix", "description": "Fixed login issue"},

[0082] {"type": "feature", "description": "Added dark mode"}

[0083] ]

[0084] }

[0085] Step 5:

[0086] The server saves the converted data to the database. It compares it with the already saved data and updates or adds any new information.

[0087] Step 6:

[0088] The server automatically generates output based on collected and analyzed information in response to user requests. For example, it can create a new presentation using the Google Slides API and insert update information into it. Specifically, it can add "Product A Version 2.0.1 Update" as the slide title and enter content such as "1. Fixed login issue" and "2. Added dark mode" on each slide.

[0089] Step 7:

[0090] The server saves the generated documents to designated cloud storage and generates a link that the user can access. Using this link, the user can access the latest update information from anywhere.

[0091] Step 8:

[0092] When the server detects new update information, it uses a means to notify users, such as sending emails or push notifications. For example, it might use an SMTP server to send an email to users stating, "New version 2.0.1 has been released." The email would include detailed release notes and links.

[0093] (Example 1)

[0094] 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."

[0095] Traditional methods of managing product update information were often manual, resulting in low efficiency and time-consuming updates. Furthermore, the analysis and standardization of information was labor-intensive, placing a heavy burden on workers. Additionally, it was sometimes difficult to notify users of updates in a timely manner, making it challenging for users to access the latest information.

[0096] 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.

[0097] In this invention, the server includes means for periodically collecting change information from multiple data sources on an information network, means for analyzing the collected change information and converting it into a standardized data format, means for storing the converted data in a storage device, means for automatically generating a document format (including display materials or calculation tables) based on the stored data, means for notifying the user when new change information is added, means for setting a periodic schedule, means for analyzing the collected data using natural language processing technology, means for creating the generated document format using a cloud service, and means for using email or push notifications as a notification method. This enables automatic collection, analysis, standardization, storage, automatic document generation, and rapid notification to users of product update information.

[0098] An "information network" refers to communication infrastructure used for sending and receiving data, such as the internet and local area networks.

[0099] "Change information" refers to data related to updates to merchandise or products, specifically including information such as the addition of new features, bug fixes, and performance improvements.

[0100] "Collection means" refers to functions and technologies for obtaining change information from data sources via an information network.

[0101] "Analysis means" refers to functions and technologies for processing collected change information and extracting necessary information. This includes natural language processing technologies, among others.

[0102] A "standardized data format" is a data structure that converts analyzed information into a specific format and stores it in a unified format.

[0103] A "storage device" is a physical or virtual storage device used to store data for extended periods.

[0104] "Document format" refers to the format used to present analyzed and standardized data, and includes presentation materials (slides) and calculation tables (spreadsheets).

[0105] "Generation means" refers to technologies and functions for automatically creating document formats based on stored data.

[0106] "Notification methods" refer to methods used to inform users when new changes are added, and include email and push notifications.

[0107] A "scheduling tool" is a function or technology that allows you to create a plan for performing tasks at regular, fixed times.

[0108] "Natural language processing technology" is a technique for analyzing collected text data and understanding its meaning and intent.

[0109] "Cloud services" refer to services such as software and storage that are provided on remote servers via the internet.

[0110] This invention is a system that automatically collects, analyzes, standardizes, and stores change information, generates documents based on that information, and notifies users. A specific embodiment of this system will be described below.

[0111] The server periodically collects change information from multiple data sources on the information network. These data sources include product API endpoints and various websites. For example, the server can send an HTTP request and receive data in JSON format as a response.

[0112] The server analyzes the collected JSON data and extracts the necessary information. Natural language processing (NLP) techniques are used as the specific analysis method. These NLP techniques include libraries such as spaCy and NLTK. This analysis yields information such as version numbers, types of changes (bug fixes, new features, etc.), and detailed descriptions, which are then converted into a standardized data format.

[0113] Standardized data is stored in storage by the server. A database is used as the storage device. Because the database is structured, the information can be retrieved and used quickly and efficiently later.

[0114] Next, the server automatically generates document formats (slides or spreadsheets) based on the stored data. Cloud services are used for document generation. Specifically, the Google Slides API and Google Sheets API are used. This automatically generates updated information in presentation or spreadsheet format.

[0115] When new changes are added, the server sends a notification to the user. Notifications are sent via email or push notifications, allowing users to quickly access the latest information.

[0116] For example, when the latest version 2.0.1 of product A is released, its release notes include information such as "Login problem fixed" and "Dark mode added." The server collects this information via an API, analyzes it, and converts it into a standardized data format. This information is then stored in a database, and new information is automatically reflected with each update. Next, a presentation using Google Slides is automatically generated based on the output format selected by the user. The generated slides may include content such as the following:

[0117] 1. Title Slide: "Product A Version 2.0.1 Update"

[0118] 2. Content slides: "1. Fixed login issues" "2. Added dark mode"

[0119] Furthermore, the server notifies users via email when new update information is added. The email body includes a brief summary and a link to further details. In this way, users can quickly and efficiently grasp new update information.

[0120] The following are specific examples of prompt statements to be input to a generative AI model:

[0121] "Product A has released its latest version, 2.0.1. Please describe a system that automatically collects, analyzes, and stores update information in a standardized data format, and then notifies users of this update. The information to be collected will include details of bug fixes and new features."

[0122] In this way, technical automation is achieved, and a system is built that allows users to efficiently obtain the latest change information.

[0123] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0124] Step 1:

[0125] The server sets a regular schedule. Based on this schedule, a task to collect product update information is automatically executed. The server uses crontab or Task Scheduler to set this schedule. The input is time information for scheduling, and the output is the set schedule information.

[0126] Specific actions:

[0127] The server sets a schedule in the format "0 1 / path / to / script.sh". This causes the script to run automatically every day at 1 AM.

[0128] Step 2:

[0129] The server collects change information from data sources on the information network based on a configured schedule. The server sends an HTTP request to the API endpoint and receives JSON data as a response. The input is the URL of the API endpoint, and the output is the retrieved JSON data.

[0130] Specific actions:

[0131] The server sends a GET request to the API endpoint and receives a response from "https: / / api.example.com / productA / version". This response contains the latest version information for product A.

[0132] Step 3:

[0133] The server parses the collected JSON data, extracting and standardizing the necessary information. The server uses natural language processing techniques to extract information such as version numbers and change types from the text data. The input is the acquired JSON data, and the output is in a standardized data format.

[0134] Specific actions:

[0135] The server uses a natural language processing library (e.g., spaCy) to identify version numbers and changes from JSON data and convert them into a standardized data structure. For example, it might extract "bug fixes" and "new features added" as changes for version 2.0.1.

[0136] Step 4:

[0137] The server analyzes and standardizes the data and stores it in storage. A structured database is used as the database. The input is standardized data, and the output is the information stored in the database.

[0138] Specific actions:

[0139] The server uses the SQLAlchemy library to analyze and standardize the data, then inserts it into the database. The database stores information such as "Product A," "Version 2.0.1," "Bug fixes," and "New features added."

[0140] Step 5:

[0141] The server automatically generates document formats (slides or spreadsheets) based on stored data. The server uses the Google Slides API and Google Sheets API to generate documents on cloud services. The input is information stored in a database, and the output is the generated document file.

[0142] Specific actions:

[0143] The server uses the Google Slides API to create a new presentation and insert update information into the slides. The generated slides include a title slide titled "Product A Version 2.0.1 Update" and detailed slides describing the changes.

[0144] Step 6:

[0145] The server sends a notification to users when new change information is added. Notification methods include email and push notifications. The input is the new change information, and the output is the notification sent to the user.

[0146] Specific actions:

[0147] The server uses an SMTP server to send an email to the user containing information about the new version update. The email includes a summary of "Product A Version 2.0.1 Update" and a link to the details.

[0148] (Application Example 1)

[0149] 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."

[0150] In modern brick-and-mortar stores, there is a need to quickly and accurately grasp updates on a wide variety of products and efficiently provide that information to staff and managers. However, manually collecting, analyzing, and notifying relevant parties of updates for numerous products is extremely time-consuming and prone to delays and errors. This challenge is particularly pronounced in brick-and-mortar stores that handle a large volume of products, and inefficient management of product update information can negatively impact the overall efficiency of operations and the quality of service.

[0151] 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.

[0152] In this invention, the server includes means for periodically collecting update information from multiple data sources on the internet, means for analyzing the collected update information and converting it into a standardized data format, means for storing the converted data in a database, means for automatically generating a document format (including slides or spreadsheets) based on the stored data, means for notifying the user when new update information is added, means for analyzing product update information and generating information to be displayed on a smart device, means for providing information to staff based on product update information, and means for generating and displaying cloud-based presentations or spreadsheets. This makes it possible to quickly and accurately grasp update information for a wide variety of products in physical stores and efficiently provide it to managers and staff.

[0153] A "data source" refers to multiple sources of information that provide update information on the internet.

[0154] "Update information" refers to detailed information about changes made to a product, such as the latest version, major fixes, and the addition of new features.

[0155] "Analysis" refers to the process of extracting useful information from collected data and converting it into a standardized format.

[0156] A "standardized data format" is a unified format that allows analyzed data to be stored and used consistently.

[0157] A "database" is a structured collection of data used to efficiently store, manage, and retrieve data.

[0158] "Document format" refers to the visual display format of information, including slides or spreadsheets.

[0159] A "cloud-based presentation" refers to a presentation document that can be accessed and edited via the internet.

[0160] A "spreadsheet service" refers to spreadsheet software that can be used online.

[0161] "Notification" refers to informing relevant parties when new update information becomes available.

[0162] A "smart device" refers to an internet-connected device with advanced features, such as a smartphone, tablet, or smart glasses.

[0163] This invention relates to a system for automatically collecting, analyzing, and notifying updates on merchandise in physical stores. The following describes how this system is specifically implemented.

[0164] Hardware and software to be used

[0165] The entire system uses the following hardware and software.

[0166] Server: Performs data collection, analysis, database management, document generation, and notification sending.

[0167] Main software used: Python, Requests library, sqlite3, Google API client library, smtplib, etc.

[0168] Smart devices: Smartphones, tablets, smart glasses, etc. Used for display and notification reception.

[0169] Data collection

[0170] The server periodically collects product update information from multiple data sources on the internet. This collection uses API requests and web scraping. For example, it obtains update information for product A in JSON format from an API endpoint.

[0171] Information analysis and transformation

[0172] The collected update information is analyzed using natural language processing (NLP) and converted into a standardized data format. This analysis extracts the version number, type of change (bug fixes, new features, etc.), and detailed descriptions. The converted data is then unified into a consistent format for post-processing.

[0173] Save to database

[0174] The analyzed data is stored in the server's database. This database is structured, allowing for fast and efficient retrieval of the stored information.

[0175] Automatic document generation

[0176] The server automatically generates documents based on the stored data. These documents are generated in cloud-based presentation or spreadsheet formats. For example, using the Google Slides API, slides that make up a presentation containing update information are automatically created.

[0177] notification

[0178] When new update information is added, the server sends a notification to smart devices. Email and push notifications are used to ensure users are quickly informed of the updates.

[0179] Information provision via smart devices

[0180] The analyzed update information is displayed on smart devices. Users can instantly check the latest information on products and take necessary actions quickly.

[0181] Specific example

[0182] For example, if the latest version 2.1.0 of product A is released, the information will be processed as follows.

[0183] 1. Collect update information for version 2.1.0 from the API endpoint.

[0184] 2. Analyze information such as "improved product page loading speed" and "added new recommendation features," and convert it into a standardized data format.

[0185] 3. Save to an SQLite database.

[0186] 4. Based on the collected information, the next slide will be automatically generated using the Google Slides API.

[0187] Title slide: "Product A Version 2.1.0 Update"

[0188] Presentation slides: "1. Improved product page loading speed" "2. Added a new recommendation feature"

[0189] 5. Notify users of new update information.

[0190] Examples of input prompts for a generative AI model

[0191] "Please analyze and process the update information for version 2.1.0 of product A, and generate a presentation. Also, please send an email to administrators and staff notifying them of the new update information."

[0192] In this way, by combining servers, smart devices, and cloud-based presentation and spreadsheet services, it is possible to achieve efficient product update management in physical stores.

[0193] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0194] Step 1:

[0195] The server periodically collects update information from multiple data sources on the internet. Specifically, it uses API requests to obtain product update information. The input is the URL of the API endpoint, and the output is update information data in JSON format. This data includes the version number and changes of the updated product.

[0196] Step 2:

[0197] The server parses the collected JSON-formatted update information and converts it into a standardized data format. Natural language processing (NLP) is used for this parsing. The input is JSON data, and the output is a standardized data format containing version number, type of change (bug fix, new feature added), and detailed description. Specifically, it extracts predetermined key information from the JSON data and converts it into a unified format.

[0198] Step 3:

[0199] The server saves the converted data to a local SQLite database. Standardized data is used as input, and the output is the addition of new records to the database. This saving process allows for fast and efficient retrieval and use of the information later. Specifically, data is added using SQL INSERT statements.

[0200] Step 4:

[0201] The server automatically generates a document format (slides or spreadsheets) based on the stored data. This primarily uses the Google Slides API. The input is updated information retrieved from the database, and the output is a new presentation generated on Google Slides. Specifically, the Google Slides API is called, and information is inserted into the slides according to the template.

[0202] Step 5:

[0203] The server sends notifications to users when new update information is added. Email and push notifications are used as notification methods. The input consists of the update information and a list of users who should receive notifications, and the output is a notification message. Specifically, this involves sending emails using an SMTP server or calling a push notification API.

[0204] Step 6:

[0205] The terminal (smart device) displays the analyzed update information. Users can immediately check the latest product information on their smartphones or tablets. The input is update information sent from the server, and the output is the latest information displayed on the device. Specifically, the device's notification function or application receives the new information and displays it on the screen.

[0206] Step 7:

[0207] The server uses updated product information to provide training and response instructions to staff. This method allows staff to quickly grasp new information and use it to assist customers. The input is the latest product information, and the output is instructions and training materials for staff. Specifically, it generates training materials based on new information and sends notifications.

[0208] 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.

[0209] This invention relates to a system that automatically collects and analyzes product update information, generates related documents, and further recognizes user emotions to adjust notification content. Specifically, it periodically collects update information, converts it into a standardized data format, stores it in a database, generates output in cloud-based presentation or spreadsheet format, and provides customized notifications based on user emotions using an emotion engine.

[0210] Program Processing Overview

[0211] 1. Data Collection

[0212] The server collects product update information from multiple data sources using API endpoints and web scraping, based on a schedule. For example, it sends an HTTP request to the API endpoint for product A, https: / / api.example.com / productA / updates, and receives JSON data as a response.

[0213] 2. Information Analysis and Transformation

[0214] The server parses the received JSON data and uses natural language processing (NLP) to extract important information (version number, changes, etc.). The extracted information is converted into a standardized data format and stored in the database as a unified format. For example, information such as "new version 2.0.1", "login problem fixed", and "dark mode added" can be obtained.

[0215] 3. Storing in a database

[0216] The server stores the analyzed and transformed data in the database. It compares it with the already stored data and updates or adds any new information.

[0217] 4. Automatic output generation

[0218] The server generates cloud-based presentations (such as Google Slides) or spreadsheets based on information in the database. For example, it can use the Google Slides API to generate a new presentation and insert update information into it. The generated slides will have the title "Product A Version 2.0.1 Update" and each slide will contain information such as "1. Fixed login issue" and "2. Added dark mode".

[0219] 5. Analysis using an emotion engine

[0220] The server analyzes user feedback and usage history using an emotion engine. The emotion engine estimates emotions from the user's facial expressions, voice, and text data, and stores the results.

[0221] 6. Customize update notifications

[0222] The server generates customized notifications based on the analysis results from the emotion engine, tailored to the user's emotions. For example, if the user is stressed, the notification will be concise and use positive language. Conversely, if the user is relaxed, the notification will also include detailed changes and recommended actions.

[0223] 7. Send update notifications

[0224] When the server detects new update information, it sends a notification to the user. Customized notifications, reflecting the results of the sentiment engine, are sent via email or push notification. For example, if the user is feeling stressed, a concise message such as "New version 2.0.1 has been released. Login issues have been fixed and dark mode has been added." might be sent.

[0225] Specific example

[0226] For example, if the latest version 2.0.1 of product A is released, its release notes will include information such as "Login problem fixed" and "Dark mode added." The server collects this information via an API, analyzes it, and converts it into a standardized data format as follows:

[0227] json

[0228] {

[0229] "product": "A",

[0230] "version": "2.0.1",

[0231] "updates": [

[0232] {"type": "bugfix", "description": "Fixed login issue"},

[0233] {"type": "feature", "description": "Added dark mode"}

[0234] ]

[0235] }

[0236] This information is stored in a database and automatically updated whenever it is updated. Then, the presentation automatically generated using Google Slides will have the aforementioned information placed on the slides.

[0237] Furthermore, based on user emotion assessment information, users experiencing stress receive the concise notification mentioned above, while users with ample free time receive a more detailed notification with a link stating, "A new version 2.0.1 has been released. Please see the detailed release notes here." In this way, the user experience can be improved.

[0238] The following describes the processing flow.

[0239] Step 1:

[0240] The server collects product update information from multiple data sources using API endpoints on the internet and web scraping, based on a schedule. Specifically, it sends an HTTP request GET https: / / api.example.com / productA / updates to the API endpoint for product A and receives JSON data as a response.

[0241] Step 2:

[0242] The server parses the response data received from the API. For example, if the JSON data received as a response is in the following format:

[0243] json

[0244] {

[0245] "version": "2.0.1",

[0246] "changes": [

[0247] {

[0248] "type": "bugfix",

[0249] "description": "Fixed login issue"

[0250] },

[0251] {

[0252] "type": "feature",

[0253] "description": "Added dark mode"

[0254] }

[0255] ]

[0256] }

[0257] The server will analyze this data.

[0258] Step 3:

[0259] The server uses natural language processing (NLP) tools to extract important information from the parsed data. Specifically, it identifies and extracts the "version number," "type of change," and "details of the change."

[0260] Step 4:

[0261] The server converts the extracted information into a standardized data format. For example, it converts it to a unified format such as the following:

[0262] json

[0263] {

[0264] "product": "A",

[0265] "version": "2.0.1",

[0266] "updates": [

[0267] {"type": "bugfix", "description": "Fixed login issue"},

[0268] {"type": "feature", "description": "Added dark mode"}

[0269] ]

[0270] }

[0271] Step 5:

[0272] The server saves the converted standardized data to the database. It checks for duplicates with existing data and adds or updates new information.

[0273] Step 6:

[0274] The server automatically generates output in response to user requests. For example, it creates a new presentation using the Google Slides API. Specifically, it adds "Product A Version 2.0.1 Update" as the slide title and enters the following information into each slide:

[0275] 1. Content of Slide 1: "Login problem fixed"

[0276] 2. Content of Slide 2: "Add Dark Mode"

[0277] Step 7:

[0278] The server analyzes the user's emotional data using the emotion engine. It processes data such as the user's feedback, expression, voice, and text with the emotion engine to determine the user's current emotional state (stress, relaxation, excitement, etc.).

[0279] Step 8:

[0280] Based on the analysis results of the emotion engine, the server generates customized notification content. For example, if the user is feeling stressed, a concise and positive notification is created, and if the user is relaxed, a notification including detailed release notes and recommended actions is created.

[0281] Step 9:

[0282] When the server detects new update information, it sends a notification to the user. A customized notification reflecting the results of the emotion engine is sent via email or push notification. For example, the following email content is sent:

[0283] For users with high stress: "New version 2.0.1 has been released. Login issues have been fixed and dark mode has been added."

[0284] For relaxed users: An email with a link saying "New version 2.0.1 has been released. Please view the detailed release notes here."

[0285] In the above way, the system automatically collects, analyzes, and stores the update information of the commercial product, and uses the emotion engine to notify the user in the optimal way. Thereby, the user experience can be improved.

[0286] (Example 2)

[0287] 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".

[0288] Traditional systems had problems with effectively managing and notifying users of product updates, requiring a lot of effort, and failing to provide appropriate notifications based on user sentiment. The difficulty in providing customized notifications tailored to user needs and circumstances resulted in a degraded user experience.

[0289] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for periodically collecting update information from multiple data sources on the internet, means for analyzing the collected update information and converting it into a standardized data format, means for storing the converted data in a database, means for analyzing the user's emotions using an emotion engine and customizing notification content based on the analysis results, and means for notifying the user when new update information is added. This enables automatic management of product update information and customized notifications based on emotions.

[0290] A "data source" is an information source that provides updated information about products on the internet.

[0291] "Update information" refers to information that indicates changes to a product, such as version upgrades, feature additions, and bug fixes.

[0292] "Analysis" refers to the process of breaking down collected update information, extracting important elements, and understanding them.

[0293] A "standardized data format" is a format that enhances data consistency and compatibility by converting analyzed information into a consistent format.

[0294] A "database" is a place to store and manage analyzed data for the long term.

[0295] A "document format" refers to the format of visual materials (such as presentation slides or spreadsheets) used to visually organize information and make it easier to understand.

[0296] An "emotion engine" is an algorithm or system that analyzes user feedback and usage history to estimate their emotional state.

[0297] "Customizing notification content" means adjusting and optimizing the content of update notifications according to the user's emotional state.

[0298] This invention relates to a system that automatically collects and analyzes product update information, generates related documents, and further recognizes user emotions to adjust notification content. Specifically, it periodically collects update information, converts it into a standardized data format, stores it in a database, and generates output in cloud-based presentation or spreadsheet format. It also uses an emotion engine to provide customized notifications based on user emotions.

[0299] First, the server collects product update information from multiple data sources based on a schedule, using API endpoints and web scraping. For example, it sends an HTTP request to the API endpoint for product A, https: / / api.example.com / productA / updates, and receives JSON data as a response. HTTP GET requests and scraping tools are used as collection methods.

[0300] The collected data is parsed by the server, and important information is extracted using natural language processing (NLP) algorithms. For example, information such as the version number "2.0.1" and changes such as "fixed login issue" and "added dark mode" is extracted. This information is converted into a standardized data format (e.g., JSON format) and stored in the database as a unified format.

[0301] Based on the information stored in the database, the server generates cloud-based presentations (such as Google Slides) or spreadsheets. Using the Google Slides API, a new presentation is generated and the update details are inserted into it. The generated slides will have the title "Product A Version 2.0.1 Update" and each slide will contain information such as "1. Fixed login issue" and "2. Added dark mode".

[0302] Next, user feedback and usage history are analyzed by the emotion engine. The emotion engine estimates the user's emotions from facial expressions, voice, and text data, and stores the results. This allows the system to determine whether the user is stressed or relaxed.

[0303] Based on the analysis results, the server generates customized notifications tailored to the user's emotions. For example, if the user is stressed, the notification will be concise and use positive language. Conversely, if the user is relaxed, the notification will also include detailed changes and recommended actions. This process improves the user experience and ensures that necessary information is effectively communicated.

[0304] Finally, when new update information is detected, the server sends a customized notification reflecting the results of the emotion engine to the user. The notification is sent in the form of an email or a push notification. As a specific example, a concise message such as "A new version 2.0.1 has been released. Login issues have been fixed and dark mode has been added." is sent.

[0305] As examples of the prompt text, they are input into the generative AI model in the following format:

[0306] "A new version 2.0.1 of the commercial product A has been released. This version includes 'fixing login issues' and 'adding dark mode'. Regarding these changes, please generate emotion-based notification content for the user."

[0307] With this invention, the management of update information for commercial products and notifications to users are automated, and by further providing optimal notifications according to the emotions of users, the user experience is significantly improved.

[0308] The flow of the specific process in Example 2 will be described using FIG. 13.

[0309] Step 1:

[0310] The server periodically collects update information from multiple data sources on the Internet. As inputs, there are schedule settings and the URLs of the data sources (e.g., https: / / api.example.com / productA / updates). Based on this, the server sends an HTTP GET request and receives update information in JSON format as a response. Specifically, a request is sent to the URL of commercial product A, and JSON data containing the version number and change details is obtained.

[0311] Step 2:

[0312] The server parses and analyzes the collected JSON data. The input is the acquired JSON data. The server uses natural language processing (NLP) algorithms to analyze the data and extract important information (e.g., version number, changes). Specifically, it extracts the keys "version" and "changes" from the JSON and retrieves their respective values. This data is then converted into a unified format.

[0313] Step 3:

[0314] The server stores the parsed and transformed data in a database. The input is a standardized data format (e.g., transformed JSON data). The server compares it with existing data and updates or adds new information if necessary. Specifically, it checks the entry for product A in the database and updates it if the version information and changes are new.

[0315] Step 4:

[0316] The server generates cloud-based presentations and spreadsheets based on information in the database. The input includes information stored in the database (e.g., version numbers and changes). The server uses the Google Slides API to generate a new presentation and insert the update details into it. Specifically, it creates a title slide such as "Product A Version 2.0.1 Update" and places the changes on each slide.

[0317] Step 5:

[0318] The server analyzes user feedback and usage history using an emotion engine. Input includes user feedback data and usage history data. The server uses the emotion engine to analyze this data and estimate the user's emotional state (e.g., stress, relaxation). Specifically, it identifies emotions from voice and text data and stores the results.

[0319] Step 6:

[0320] The server generates customized notifications based on the user's emotions, using the results of the emotion engine's analysis. Inputs include the emotion analysis results and update information from the database. The server adjusts the notification content according to each user's emotional state. Specifically, it creates concise notifications for stressed users and detailed notifications for relaxed users.

[0321] Step 7:

[0322] When the server detects new update information, it sends a notification to the user. The input is a customized notification message. The server sends the notification to the user using methods such as email or push notifications. Specifically, the notification might be in the format of, "New version 2.0.1 has been released. Login issues have been fixed and dark mode has been added."

[0323] In this way, the automatic collection, analysis, database management, document generation, and user notification of product update information are all realized in a single, streamlined process.

[0324] (Application Example 2)

[0325] 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".

[0326] Traditional update notification systems often simply relay collected information to users without considering their current emotional state or feedback, resulting in a lack of improved user experience. Furthermore, this could lead to users receiving unnecessary information, potentially causing stress. Additionally, important changes might be overlooked, leading to a lack of understanding of the update content.

[0327] 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 periodically collecting update information from multiple data sources on the internet, means for analyzing the collected update information and converting it into a standardized data format, means for storing the converted data in a database, means for automatically generating a document format (including slides or spreadsheets) based on the stored data, means for analyzing the user's emotions based on user feedback and usage history, means for customizing update notifications according to the user's emotions, and means for sending customized notifications to the user when new update information is added. This makes it possible to appropriately provide information according to the user's emotional state and to appropriately notify them without missing important information.

[0328] "Means of collecting update information from multiple data sources on the internet on a regular basis" refers to a function that automatically retrieves software and service update information from multiple websites and APIs based on a schedule set via the internet.

[0329] "Means for analyzing collected update information and converting it into a standardized data format" refers to a function that analyzes acquired update information using natural language processing and data analysis techniques and formats it into a unified format.

[0330] "Means of storing converted data in a database" refers to a function that stores analyzed and standardized data in a database so that it can be searched and referenced later.

[0331] "Means for automatically generating document formats (including slides or spreadsheets) based on saved data" refers to a function that automatically creates visual documents such as presentation slides and spreadsheets using information stored in a database.

[0332] "Means of analyzing user emotions based on user feedback and usage history" refers to a function that collects user input and operation history and uses an emotion analysis algorithm to estimate the user's current emotional state based on this data.

[0333] "Means of customizing update notifications according to user emotions" refers to a function that takes into account the analyzed emotional state of the user and modifies the notification content or presents it in a specific way to provide information in the most optimal format for the user.

[0334] "Means of sending customized notifications to users when new update information is added" refers to a function that sends a pre-customized notification message to users via email or push notification when new update information is added to the system.

[0335] This invention can be implemented by coordinating several system components and programs. The specific method is described below.

[0336] The server periodically collects update information from multiple data sources on the internet. This can be done using techniques such as Web APIs and Web scraping. For example, to collect the latest update information for product A, an HTTP request is sent to a specified API endpoint, and JSON data is received as a response. Since this collected data is difficult to use directly, it is analyzed using natural language processing (NLP) techniques and converted into a standardized data format. The analyzed data is then formatted into a unified format and stored in a database. Cloud services such as Amazon RDS and Google Cloud Firestore can be used for the database.

[0337] Next, a document format (slides or spreadsheet) is automatically generated based on this saved data. This can be achieved using cloud-based presentation tools such as the "Google Slides API" or "Google Sheets API". For example, based on the update information for the new version 2.0.1, a presentation titled "Product A Version 2.0.1 Update" is created in Google Slides, and information such as "Login problem fixed" and "Dark mode added" is inserted into its content.

[0338] Furthermore, user feedback and usage history are analyzed using an emotion engine. In this case, emotion analysis engines such as "Amazon Rekognition," "Google Cloud Vision," and "Microsoft® Azure® Face API" can be used to analyze the user's facial expressions, voice, and text data to estimate their emotional state. For example, if a user writes "It's become easier to use" in their feedback, the feedback text is analyzed using NLP technology to determine that the emotion is "positive."

[0339] Update notifications are customized based on the user's sentiment. If the sentiment is positive, a detailed notification is applied, such as "A new version 2.0.1 has been released. See the detailed release notes here." Conversely, if the sentiment is negative, a concise notification is sent, such as "A new version 2.0.1 has been released. Login issues have been fixed and dark mode has been added." This customized notification is sent to the user via email or push notification. Email services such as "Amazon SES" and "SendGrid" or "Firebase Cloud Messaging (FCM)" can be used.

[0340] For example, suppose user A is using the "EmotionPay" app and receives a notification about the latest update. The system first analyzes the user's feedback with its emotion engine and detects positive emotions. As a result, the system chooses to send a detailed notification, and user A receives a notification stating, "A new version 2.0.1 has been released. Click here for detailed release notes."

[0341] An example of a prompt statement is as follows:

[0342] "As an EmotionPay user, you will receive a notification when the latest version 2.0.1 is released. Based on your feedback and sentiment analysis, the notification will be customized and will determine whether or not it includes detailed release notes. Please write 'Positive' or 'Negative' in your feedback."

[0343] In this way, this invention can provide appropriate information according to the user's emotional state and improve the user experience.

[0344] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0345] Step 1:

[0346] The server periodically collects update information from multiple data sources on the internet. This is done by sending HTTP requests to API endpoints and websites according to a pre-configured schedule. As a result, data in JSON format is returned as a response. The input is the URL of the API endpoint or website, and the output is the collected update information in JSON format.

[0347] Step 2:

[0348] The server analyzes the collected update information and converts it into a standardized data format. This is done by parsing the acquired JSON data, using natural language processing (NLP) techniques to extract important information (e.g., version number and changes), and converting it into a unified format. The input is the collected JSON data, and the output is a standardized data format. Specifically, the system uses Python's json module to import data and then analyzes it using NLP libraries such as spaCy or NLTK.

[0349] Step 3:

[0350] The server stores the transformed data in a database. This is a process that uses a database connection module to parse and standardize the data, store it in the database, and update or add any new information by comparing it with existing data. The input is a standardized data format, and the output is the data stored in the database. Specifically, SQL queries are used to insert and update data in the database.

[0351] Step 4:

[0352] The server automatically generates document formats (slides or spreadsheets) based on the stored data. This is a process of creating automatically generated documents using cloud-based presentation tools such as the Google Slides API and the Google Sheets API. The input is update information stored in the database, and the output is the generated presentation or spreadsheet. Specifically, a new document is generated using the Google API client, and the update information is inserted.

[0353] Step 5:

[0354] The server analyzes user sentiment based on user feedback and usage history. This process involves processing user feedback text and usage history data using a sentiment analysis engine (e.g., Amazon Rekognition, Google Cloud Vision, Microsoft Azure Face API) to estimate the user's sentiment. The input is user feedback and usage history data, and the output is the analyzed sentiment data. Specifically, the server calls the sentiment analysis API and saves the results to a database.

[0355] Step 6:

[0356] The server customizes update notifications based on the user's emotions. This is a process that modifies the notification content based on the emotion analysis results. For example, if the emotion is "positive," a detailed notification is created, and if the emotion is "negative," a concise notification is created. The input is the emotion analysis result, and the output is the customized notification message. Specifically, multiple notification templates are prepared, and the appropriate template is selected according to the emotion analysis result.

[0357] Step 7:

[0358] The server sends customized notifications to users when new update information is added. This is done, for example, via email or push notifications. The input is the customized notification message, and the output is the notification sent to the user. Specifically, the server calls a notification service (e.g., Amazon SES, SendGrid, Firebase Cloud Messaging (FCM)) to send the notification message.

[0359] 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.

[0360] 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.

[0361] 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.

[0362] [Second Embodiment]

[0363] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0364] 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.

[0365] 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).

[0366] 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.

[0367] 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.

[0368] 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).

[0369] 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.

[0370] 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.

[0371] 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.

[0372] 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.

[0373] 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.

[0374] 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".

[0375] This invention relates to a system that automatically collects and analyzes product update information, generates related documents, and notifies users. In particular, it periodically collects update information, converts it into a standardized data format, stores it in a database, and further generates output in cloud-based presentation or spreadsheet format.

[0376] Program Processing Overview

[0377] 1. Data Collection

[0378] The server collects product update information from multiple data sources based on a regular schedule. For example, the server sends an HTTP request to the API endpoint of product A and receives JSON data as a response. The data obtained in this way includes the latest version information and corrections for that product.

[0379] 2. Information Analysis and Transformation

[0380] The server uses natural language processing (NLP) to analyze the collected JSON data and extract the necessary information. This analysis yields specific version numbers, types of changes (bug fixes, new features, etc.), and detailed descriptions. The analyzed information is then converted into a predefined standardized format.

[0381] 3. Storing in a database

[0382] The extracted and standardized data is stored in a database. Because the database is structured, the information can be retrieved and used quickly and efficiently later.

[0383] 4. Automatic output generation

[0384] The server automatically generates document formats (slides or spreadsheets) based on information stored in the database. For example, it can use the Google Slides API to generate a new presentation and insert update information into the slides. Similarly, when outputting as a spreadsheet, the API is used to input the data.

[0385] 5. Update notification

[0386] When the server detects new update information, it sends a notification to the user. By using methods such as email and push notifications, users can quickly receive the latest information.

[0387] Specific example

[0388] For example, if the latest version 2.0.1 of product A is released, its release notes will include information such as "Login problem fixed" and "Dark mode added." The server collects this information via an API, analyzes it, and converts it into a standardized data format as follows.

[0389] json

[0390] {

[0391] "product": "A",

[0392] "version": "2.0.1",

[0393] "updates": [

[0394] {"type": "bugfix", "description": "Fixed login issue"},

[0395] {"type": "feature", "description": "Added dark mode"}

[0396] ]

[0397] }

[0398] This information is stored in a database and automatically updated whenever it is updated. Next, based on the output format selected by the user, a presentation is automatically generated, for example, using Google Slides. The generated slides include:

[0399] 1. Title Slide: "Product A Version 2.0.1 Update"

[0400] 2. Content slides: "1. Fixed login issues" "2. Added dark mode"

[0401] The data is entered in this format.

[0402] Finally, users are notified by email when new update information is added. The email body includes a brief summary and a link to further details. In this way, users can quickly and efficiently grasp new update information.

[0403] The following describes the processing flow.

[0404] Step 1:

[0405] The server sends an HTTP request to an API endpoint on the internet based on a schedule. This request is to retrieve the latest update information for a product; for example, it sends a request GET https: / / api.example.com / productA / updates to retrieve update information for product A.

[0406] Step 2:

[0407] The server receives JSON data as a response from the API. This response contains information such as new version information, changes, and bug fixes for the product, and is ready to be analyzed in the next step.

[0408] Step 3:

[0409] The server parses the received JSON data and uses natural language processing (NLP) tools to extract important information (version number, changes, etc.). For example, it might obtain information such as version "2.0.1", "login issue fixed", and "dark mode added".

[0410] Step 4:

[0411] The server converts the parsed information into a standardized data format. This standardized format is a unified format defined for use in the system, and may look like this:

[0412] json

[0413] {

[0414] "product": "A",

[0415] "version": "2.0.1",

[0416] "updates": [

[0417] {"type": "bugfix", "description": "Fixed login issue"},

[0418] {"type": "feature", "description": "Added dark mode"}

[0419] ]

[0420] }

[0421] Step 5:

[0422] The server saves the converted data to the database. It compares it with the already saved data and updates or adds any new information.

[0423] Step 6:

[0424] The server automatically generates output based on collected and analyzed information in response to user requests. For example, it can create a new presentation using the Google Slides API and insert update information into it. Specifically, it can add "Product A Version 2.0.1 Update" as the slide title and enter content such as "1. Fixed login issue" and "2. Added dark mode" on each slide.

[0425] Step 7:

[0426] The server saves the generated documents to designated cloud storage and generates a link that the user can access. Using this link, the user can access the latest update information from anywhere.

[0427] Step 8:

[0428] When the server detects new update information, it uses a means to notify users, such as sending emails or push notifications. For example, it might use an SMTP server to send an email to users stating, "New version 2.0.1 has been released." The email would include detailed release notes and links.

[0429] (Example 1)

[0430] 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."

[0431] Traditional methods of managing product update information were often manual, resulting in low efficiency and time-consuming updates. Furthermore, the analysis and standardization of information was labor-intensive, placing a heavy burden on workers. Additionally, it was sometimes difficult to notify users of updates in a timely manner, making it challenging for users to access the latest information.

[0432] 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.

[0433] In this invention, the server includes means for periodically collecting change information from multiple data sources on an information network, means for analyzing the collected change information and converting it into a standardized data format, means for storing the converted data in a storage device, means for automatically generating a document format (including display materials or calculation tables) based on the stored data, means for notifying the user when new change information is added, means for setting a periodic schedule, means for analyzing the collected data using natural language processing technology, means for creating the generated document format using a cloud service, and means for using email or push notifications as a notification method. This enables automatic collection, analysis, standardization, storage, automatic document generation, and rapid notification to users of product update information.

[0434] An "information network" refers to communication infrastructure used for sending and receiving data, such as the internet and local area networks.

[0435] "Change information" refers to data related to updates to merchandise or products, specifically including information such as the addition of new features, bug fixes, and performance improvements.

[0436] "Collection means" refers to functions and technologies for obtaining change information from data sources via an information network.

[0437] "Analysis means" refers to functions and technologies for processing collected change information and extracting necessary information. This includes natural language processing technologies, among others.

[0438] A "standardized data format" is a data structure that converts analyzed information into a specific format and stores it in a unified format.

[0439] A "storage device" is a physical or virtual storage device used to store data for extended periods.

[0440] "Document format" refers to the format used to present analyzed and standardized data, and includes presentation materials (slides) and calculation tables (spreadsheets).

[0441] "Generation means" refers to technologies and functions for automatically creating document formats based on stored data.

[0442] "Notification methods" refer to methods used to inform users when new changes are added, and include email and push notifications.

[0443] A "scheduling tool" is a function or technology that allows you to create a plan for performing tasks at regular, fixed times.

[0444] "Natural language processing technology" is a technique for analyzing collected text data and understanding its meaning and intent.

[0445] "Cloud services" refer to services such as software and storage that are provided on remote servers via the internet.

[0446] This invention is a system that automatically collects, analyzes, standardizes, and stores change information, generates documents based on that information, and notifies users. A specific embodiment of this system will be described below.

[0447] The server periodically collects change information from multiple data sources on the information network. These data sources include product API endpoints and various websites. For example, the server can send an HTTP request and receive data in JSON format as a response.

[0448] The server analyzes the collected JSON data and extracts the necessary information. Natural language processing (NLP) techniques are used as the specific analysis method. These NLP techniques include libraries such as spaCy and NLTK. This analysis yields information such as version numbers, types of changes (bug fixes, new features, etc.), and detailed descriptions, which are then converted into a standardized data format.

[0449] Standardized data is stored in storage by the server. A database is used as the storage device. Because the database is structured, the information can be retrieved and used quickly and efficiently later.

[0450] Next, the server automatically generates document formats (slides or spreadsheets) based on the stored data. Cloud services are used for document generation. Specifically, the Google Slides API and Google Sheets API are used. This automatically generates updated information in presentation or spreadsheet format.

[0451] When new changes are added, the server sends a notification to the user. Notifications are sent via email or push notifications, allowing users to quickly access the latest information.

[0452] For example, when the latest version 2.0.1 of product A is released, its release notes include information such as "Login problem fixed" and "Dark mode added." The server collects this information via an API, analyzes it, and converts it into a standardized data format. This information is then stored in a database, and new information is automatically reflected with each update. Next, a presentation using Google Slides is automatically generated based on the output format selected by the user. The generated slides may include content such as the following:

[0453] 1. Title Slide: "Product A Version 2.0.1 Update"

[0454] 2. Content slides: "1. Fixed login issues" "2. Added dark mode"

[0455] Furthermore, the server notifies users via email when new update information is added. The email body includes a brief summary and a link to further details. In this way, users can quickly and efficiently grasp new update information.

[0456] The following are specific examples of prompt statements to be input to a generative AI model:

[0457] "Product A has released its latest version, 2.0.1. Please describe a system that automatically collects, analyzes, and stores update information in a standardized data format, and then notifies users of this update. The information to be collected will include details of bug fixes and new features."

[0458] In this way, technical automation is achieved, and a system is built that allows users to efficiently obtain the latest change information.

[0459] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0460] Step 1:

[0461] The server sets a regular schedule. Based on this schedule, a task to collect product update information is automatically executed. The server uses crontab or Task Scheduler to set this schedule. The input is time information for scheduling, and the output is the set schedule information.

[0462] Specific actions:

[0463] The server sets a schedule in the format "0 1 / path / to / script.sh". This causes the script to run automatically every day at 1 AM.

[0464] Step 2:

[0465] The server collects change information from data sources on the information network based on a configured schedule. The server sends an HTTP request to the API endpoint and receives JSON data as a response. The input is the URL of the API endpoint, and the output is the retrieved JSON data.

[0466] Specific actions:

[0467] The server sends a GET request to the API endpoint and receives a response from "https: / / api.example.com / productA / version". This response contains the latest version information for product A.

[0468] Step 3:

[0469] The server parses the collected JSON data, extracting and standardizing the necessary information. The server uses natural language processing techniques to extract information such as version numbers and change types from the text data. The input is the acquired JSON data, and the output is in a standardized data format.

[0470] Specific actions:

[0471] The server uses a natural language processing library (e.g., spaCy) to identify version numbers and changes from JSON data and convert them into a standardized data structure. For example, it might extract "bug fixes" and "new features added" as changes for version 2.0.1.

[0472] Step 4:

[0473] The server analyzes and standardizes the data and stores it in storage. A structured database is used as the database. The input is standardized data, and the output is the information stored in the database.

[0474] Specific actions:

[0475] The server uses the SQLAlchemy library to analyze and standardize the data, then inserts it into the database. The database stores information such as "Product A," "Version 2.0.1," "Bug fixes," and "New features added."

[0476] Step 5:

[0477] The server automatically generates document formats (slides or spreadsheets) based on stored data. The server uses the Google Slides API and Google Sheets API to generate documents on cloud services. The input is information stored in a database, and the output is the generated document file.

[0478] Specific actions:

[0479] The server uses the Google Slides API to create a new presentation and insert update information into the slides. The generated slides include a title slide titled "Product A Version 2.0.1 Update" and detailed slides describing the changes.

[0480] Step 6:

[0481] The server sends a notification to users when new change information is added. Notification methods include email and push notifications. The input is the new change information, and the output is the notification sent to the user.

[0482] Specific actions:

[0483] The server uses an SMTP server to send an email to the user containing information about the new version update. The email includes a summary of "Product A Version 2.0.1 Update" and a link to the details.

[0484] (Application Example 1)

[0485] 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."

[0486] In modern brick-and-mortar stores, there is a need to quickly and accurately grasp updates on a wide variety of products and efficiently provide that information to staff and managers. However, manually collecting, analyzing, and notifying relevant parties of updates for numerous products is extremely time-consuming and prone to delays and errors. This challenge is particularly pronounced in brick-and-mortar stores that handle a large volume of products, and inefficient management of product update information can negatively impact the overall efficiency of operations and the quality of service.

[0487] 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.

[0488] In this invention, the server includes means for periodically collecting update information from multiple data sources on the internet, means for analyzing the collected update information and converting it into a standardized data format, means for storing the converted data in a database, means for automatically generating a document format (including slides or spreadsheets) based on the stored data, means for notifying the user when new update information is added, means for analyzing product update information and generating information to be displayed on a smart device, means for providing information to staff based on product update information, and means for generating and displaying cloud-based presentations or spreadsheets. This makes it possible to quickly and accurately grasp update information for a wide variety of products in physical stores and efficiently provide it to managers and staff.

[0489] A "data source" refers to multiple sources of information that provide update information on the internet.

[0490] "Update information" refers to detailed information about changes made to a product, such as the latest version, major fixes, and the addition of new features.

[0491] "Analysis" refers to the process of extracting useful information from collected data and converting it into a standardized format.

[0492] A "standardized data format" is a unified format that allows analyzed data to be stored and used consistently.

[0493] A "database" is a structured collection of data used to efficiently store, manage, and retrieve data.

[0494] "Document format" refers to the visual display format of information, including slides or spreadsheets.

[0495] A "cloud-based presentation" refers to a presentation document that can be accessed and edited via the internet.

[0496] A "spreadsheet service" refers to spreadsheet software that can be used online.

[0497] "Notification" refers to informing relevant parties when new update information becomes available.

[0498] A "smart device" refers to an internet-connected device with advanced features, such as a smartphone, tablet, or smart glasses.

[0499] This invention relates to a system for automatically collecting, analyzing, and notifying updates on merchandise in physical stores. The following describes how this system is specifically implemented.

[0500] Hardware and software to be used

[0501] The entire system uses the following hardware and software.

[0502] Server: Performs data collection, analysis, database management, document generation, and notification sending.

[0503] Main software used: Python, Requests library, sqlite3, Google API client library, smtplib, etc.

[0504] Smart devices: Smartphones, tablets, smart glasses, etc. Used for display and notification reception.

[0505] Data collection

[0506] The server periodically collects product update information from multiple data sources on the internet. This collection uses API requests and web scraping. For example, it obtains update information for product A in JSON format from an API endpoint.

[0507] Information analysis and transformation

[0508] The collected update information is analyzed using natural language processing (NLP) and converted into a standardized data format. This analysis extracts the version number, type of change (bug fixes, new features, etc.), and detailed descriptions. The converted data is then unified into a consistent format for post-processing.

[0509] Save to database

[0510] The analyzed data is stored in the server's database. This database is structured, allowing for fast and efficient retrieval of the stored information.

[0511] Automatic document generation

[0512] The server automatically generates documents based on the stored data. These documents are generated in cloud-based presentation or spreadsheet formats. For example, using the Google Slides API, slides that make up a presentation containing update information are automatically created.

[0513] notification

[0514] When new update information is added, the server sends a notification to smart devices. Email and push notifications are used to ensure users are quickly informed of the updates.

[0515] Information provision via smart devices

[0516] The analyzed update information is displayed on smart devices. Users can instantly check the latest information on products and take necessary actions quickly.

[0517] Specific example

[0518] For example, if the latest version 2.1.0 of product A is released, the information will be processed as follows.

[0519] 1. Collect update information for version 2.1.0 from the API endpoint.

[0520] 2. Analyze information such as "improved product page loading speed" and "added new recommendation features," and convert it into a standardized data format.

[0521] 3. Save to an SQLite database.

[0522] 4. Based on the collected information, the next slide will be automatically generated using the Google Slides API.

[0523] Title slide: "Product A Version 2.1.0 Update"

[0524] Presentation slides: "1. Improved product page loading speed" "2. Added a new recommendation feature"

[0525] 5. Notify users of new update information.

[0526] Examples of input prompts for a generative AI model

[0527] "Please analyze and process the update information for version 2.1.0 of product A, and generate a presentation. Also, please send an email to administrators and staff notifying them of the new update information."

[0528] In this way, by combining servers, smart devices, and cloud-based presentation and spreadsheet services, it is possible to achieve efficient product update management in physical stores.

[0529] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0530] Step 1:

[0531] The server periodically collects update information from multiple data sources on the internet. Specifically, it uses API requests to obtain product update information. The input is the URL of the API endpoint, and the output is update information data in JSON format. This data includes the version number and changes of the updated product.

[0532] Step 2:

[0533] The server parses the collected JSON-formatted update information and converts it into a standardized data format. Natural language processing (NLP) is used for this parsing. The input is JSON data, and the output is a standardized data format containing version number, type of change (bug fix, new feature added), and detailed description. Specifically, it extracts predetermined key information from the JSON data and converts it into a unified format.

[0534] Step 3:

[0535] The server saves the converted data to a local SQLite database. Standardized data is used as input, and the output is the addition of new records to the database. This saving process allows for fast and efficient retrieval and use of the information later. Specifically, data is added using SQL INSERT statements.

[0536] Step 4:

[0537] The server automatically generates a document format (slides or spreadsheets) based on the stored data. This primarily uses the Google Slides API. The input is updated information retrieved from the database, and the output is a new presentation generated on Google Slides. Specifically, the Google Slides API is called, and information is inserted into the slides according to the template.

[0538] Step 5:

[0539] The server sends notifications to users when new update information is added. Email and push notifications are used as notification methods. The input consists of the update information and a list of users who should receive notifications, and the output is a notification message. Specifically, this involves sending emails using an SMTP server or calling a push notification API.

[0540] Step 6:

[0541] The terminal (smart device) displays the analyzed update information. Users can immediately check the latest product information on their smartphones or tablets. The input is update information sent from the server, and the output is the latest information displayed on the device. Specifically, the device's notification function or application receives the new information and displays it on the screen.

[0542] Step 7:

[0543] The server uses updated product information to provide training and response instructions to staff. This method allows staff to quickly grasp new information and use it to assist customers. The input is the latest product information, and the output is instructions and training materials for staff. Specifically, it generates training materials based on new information and sends notifications.

[0544] 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.

[0545] This invention relates to a system that automatically collects and analyzes product update information, generates related documents, and further recognizes user emotions to adjust notification content. Specifically, it periodically collects update information, converts it into a standardized data format, stores it in a database, generates output in cloud-based presentation or spreadsheet format, and provides customized notifications based on user emotions using an emotion engine.

[0546] Program Processing Overview

[0547] 1. Data Collection

[0548] The server collects product update information from multiple data sources using API endpoints and web scraping, based on a schedule. For example, it sends an HTTP request to the API endpoint for product A, https: / / api.example.com / productA / updates, and receives JSON data as a response.

[0549] 2. Information Analysis and Transformation

[0550] The server parses the received JSON data and uses natural language processing (NLP) to extract important information (version number, changes, etc.). The extracted information is converted into a standardized data format and stored in the database as a unified format. For example, information such as "new version 2.0.1", "login problem fixed", and "dark mode added" can be obtained.

[0551] 3. Storing in a database

[0552] The server stores the analyzed and transformed data in the database. It compares it with the already stored data and updates or adds any new information.

[0553] 4. Automatic output generation

[0554] The server generates cloud-based presentations (such as Google Slides) or spreadsheets based on information in the database. For example, it can use the Google Slides API to generate a new presentation and insert update information into it. The generated slides will have the title "Product A Version 2.0.1 Update" and each slide will contain information such as "1. Fixed login issue" and "2. Added dark mode".

[0555] 5. Analysis using an emotion engine

[0556] The server analyzes user feedback and usage history using an emotion engine. The emotion engine estimates emotions from the user's facial expressions, voice, and text data, and stores the results.

[0557] 6. Customize update notifications

[0558] The server generates customized notifications based on the analysis results from the emotion engine, tailored to the user's emotions. For example, if the user is stressed, the notification will be concise and use positive language. Conversely, if the user is relaxed, the notification will also include detailed changes and recommended actions.

[0559] 7. Send update notifications

[0560] When the server detects new update information, it sends a notification to the user. Customized notifications, reflecting the results of the sentiment engine, are sent via email or push notification. For example, if the user is feeling stressed, a concise message such as "New version 2.0.1 has been released. Login issues have been fixed and dark mode has been added." might be sent.

[0561] Specific example

[0562] For example, if the latest version 2.0.1 of product A is released, its release notes will include information such as "Login problem fixed" and "Dark mode added." The server collects this information via an API, analyzes it, and converts it into a standardized data format as follows:

[0563] json

[0564] {

[0565] "product": "A",

[0566] "version": "2.0.1",

[0567] "updates": [

[0568] {"type": "bugfix", "description": "Fixed login issue"},

[0569] {"type": "feature", "description": "Added dark mode"}

[0570] ]

[0571] }

[0572] This information is stored in a database and automatically updated whenever it is updated. Then, the presentation automatically generated using Google Slides will have the aforementioned information placed on the slides.

[0573] Furthermore, based on user emotion assessment information, users experiencing stress receive the concise notification mentioned above, while users with ample free time receive a more detailed notification with a link stating, "A new version 2.0.1 has been released. Please see the detailed release notes here." In this way, the user experience can be improved.

[0574] The following describes the processing flow.

[0575] Step 1:

[0576] The server collects product update information from multiple data sources using API endpoints on the internet and web scraping, based on a schedule. Specifically, it sends an HTTP request GET https: / / api.example.com / productA / updates to the API endpoint for product A and receives JSON data as a response.

[0577] Step 2:

[0578] The server parses the response data received from the API. For example, if the JSON data received as a response is in the following format:

[0579] json

[0580] {

[0581] "version": "2.0.1",

[0582] "changes": [

[0583] {

[0584] "type": "bugfix",

[0585] "description": "Fixed login issue"

[0586] },

[0587] {

[0588] "type": "feature",

[0589] "description": "Added dark mode"

[0590] }

[0591] ]

[0592] }

[0593] The server will analyze this data.

[0594] Step 3:

[0595] The server uses natural language processing (NLP) tools to extract important information from the parsed data. Specifically, it identifies and extracts the "version number," "type of change," and "details of the change."

[0596] Step 4:

[0597] The server converts the extracted information into a standardized data format. For example, it converts it to a unified format such as the following:

[0598] json

[0599] {

[0600] "product": "A",

[0601] "version": "2.0.1",

[0602] "updates": [

[0603] {"type": "bugfix", "description": "Fixed login issue"},

[0604] {"type": "feature", "description": "Added dark mode"}

[0605] ]

[0606] }

[0607] Step 5:

[0608] The server saves the converted standardized data to the database. It checks for duplicates with existing data and adds or updates new information.

[0609] Step 6:

[0610] The server automatically generates output in response to user requests. For example, it creates a new presentation using the Google Slides API. Specifically, it adds "Product A Version 2.0.1 Update" as the slide title and enters the following information into each slide:

[0611] 1. Content of Slide 1: "Login problem fixed"

[0612] 2. Content of Slide 2: "Add Dark Mode"

[0613] Step 7:

[0614] The server uses an emotion engine to analyze the user's emotional data. The emotion engine processes data such as user feedback, facial expressions, voice, and text to determine the user's current emotional state (stress, relaxation, excitement, etc.).

[0615] Step 8:

[0616] The server generates customized notification content based on the analysis results of the emotion engine. For example, if the user is stressed, it creates a concise and positive notification; if they are relaxed, it creates a notification that includes detailed release notes and recommended actions.

[0617] Step 9:

[0618] When the server detects new update information, it sends a notification to the user. Customized notifications, reflecting the results of the sentiment engine, are sent via email or push notification. For example, an email like the following might be sent:

[0619] For users experiencing high stress levels: "A new version, 2.0.1, has been released. Login issues have been fixed, and dark mode has been added."

[0620] For relaxed users: An email with a link saying, "A new version 2.0.1 has been released. Click here for detailed release notes."

[0621] As described above, the system automatically collects, analyzes, and stores product update information, and uses an emotion engine to notify users in the most optimal way. This improves the user experience.

[0622] (Example 2)

[0623] 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".

[0624] Traditional systems had problems with effectively managing and notifying users of product updates, requiring a lot of effort, and failing to provide appropriate notifications based on user sentiment. The difficulty in providing customized notifications tailored to user needs and circumstances resulted in a degraded user experience.

[0625] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for periodically collecting update information from multiple data sources on the internet, means for analyzing the collected update information and converting it into a standardized data format, means for storing the converted data in a database, means for analyzing the user's emotions using an emotion engine and customizing notification content based on the analysis results, and means for notifying the user when new update information is added. This enables automatic management of product update information and customized notifications based on emotions.

[0626] A "data source" is an information source that provides updated information about products on the internet.

[0627] "Update information" refers to information that indicates changes to a product, such as version upgrades, feature additions, and bug fixes.

[0628] "Analysis" refers to the process of breaking down collected update information, extracting important elements, and understanding them.

[0629] A "standardized data format" is a format that enhances data consistency and compatibility by converting analyzed information into a consistent format.

[0630] A "database" is a place to store and manage analyzed data for the long term.

[0631] A "document format" refers to the format of visual materials (such as presentation slides or spreadsheets) used to visually organize information and make it easier to understand.

[0632] An "emotion engine" is an algorithm or system that analyzes user feedback and usage history to estimate their emotional state.

[0633] "Customizing notification content" means adjusting and optimizing the content of update notifications according to the user's emotional state.

[0634] This invention relates to a system that automatically collects and analyzes product update information, generates related documents, and further recognizes user emotions to adjust notification content. Specifically, it periodically collects update information, converts it into a standardized data format, stores it in a database, and generates output in cloud-based presentation or spreadsheet format. It also uses an emotion engine to provide customized notifications based on user emotions.

[0635] First, the server collects product update information from multiple data sources based on a schedule, using API endpoints and web scraping. For example, it sends an HTTP request to the API endpoint for product A, https: / / api.example.com / productA / updates, and receives JSON data as a response. HTTP GET requests and scraping tools are used as collection methods.

[0636] The collected data is parsed by the server, and important information is extracted using natural language processing (NLP) algorithms. For example, information such as the version number "2.0.1" and changes such as "fixed login issue" and "added dark mode" is extracted. This information is converted into a standardized data format (e.g., JSON format) and stored in the database as a unified format.

[0637] Based on the information stored in the database, the server generates cloud-based presentations (such as Google Slides) or spreadsheets. Using the Google Slides API, a new presentation is generated and the update details are inserted into it. The generated slides will have the title "Product A Version 2.0.1 Update" and each slide will contain information such as "1. Fixed login issue" and "2. Added dark mode".

[0638] Next, user feedback and usage history are analyzed by the emotion engine. The emotion engine estimates the user's emotions from facial expressions, voice, and text data, and stores the results. This allows the system to determine whether the user is stressed or relaxed.

[0639] Based on the analysis results, the server generates customized notifications tailored to the user's emotions. For example, if the user is stressed, the notification will be concise and use positive language. Conversely, if the user is relaxed, the notification will also include detailed changes and recommended actions. This process improves the user experience and ensures that necessary information is effectively communicated.

[0640] Finally, when new update information is detected, the server sends a customized notification to the user that reflects the results of the sentiment engine. The notification can be sent via email or push notification, and a specific example would be a concise message such as, "New version 2.0.1 has been released. Login issues have been fixed and dark mode has been added."

[0641] An example of a prompt message is input to the generating AI model in the following format:

[0642] "A new version 2.0.1 of Product A has been released. This version includes 'Login issue fix' and 'Dark Mode added.' Please generate sentiment-based notifications for users regarding these changes."

[0643] This invention automates the management of product update information and notifications to users, and further enhances the user experience by providing optimal notifications tailored to the user's emotions.

[0644] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0645] Step 1:

[0646] The server periodically collects update information from multiple data sources on the internet. Inputs include a schedule and the URLs of the data sources (e.g., https: / / api.example.com / productA / updates). Based on this, the server sends an HTTP GET request and receives update information in JSON format as a response. Specifically, it sends a request to the URL of product A and retrieves JSON data containing the version number and changes.

[0647] Step 2:

[0648] The server parses and analyzes the collected JSON data. The input is the acquired JSON data. The server uses natural language processing (NLP) algorithms to analyze the data and extract important information (e.g., version number, changes). Specifically, it extracts the keys "version" and "changes" from the JSON and retrieves their respective values. This data is then converted into a unified format.

[0649] Step 3:

[0650] The server stores the parsed and transformed data in a database. The input is a standardized data format (e.g., transformed JSON data). The server compares it with existing data and updates or adds new information if necessary. Specifically, it checks the entry for product A in the database and updates it if the version information and changes are new.

[0651] Step 4:

[0652] The server generates cloud-based presentations and spreadsheets based on information in the database. The input includes information stored in the database (e.g., version numbers and changes). The server uses the Google Slides API to generate a new presentation and insert the update details into it. Specifically, it creates a title slide such as "Product A Version 2.0.1 Update" and places the changes on each slide.

[0653] Step 5:

[0654] The server analyzes user feedback and usage history using an emotion engine. Input includes user feedback data and usage history data. The server uses the emotion engine to analyze this data and estimate the user's emotional state (e.g., stress, relaxation). Specifically, it identifies emotions from voice and text data and stores the results.

[0655] Step 6:

[0656] The server generates customized notifications based on the user's emotions, using the results of the emotion engine's analysis. Inputs include the emotion analysis results and update information from the database. The server adjusts the notification content according to each user's emotional state. Specifically, it creates concise notifications for stressed users and detailed notifications for relaxed users.

[0657] Step 7:

[0658] When the server detects new update information, it sends a notification to the user. The input is a customized notification message. The server sends the notification to the user using methods such as email or push notifications. Specifically, the notification might be in the format of, "New version 2.0.1 has been released. Login issues have been fixed and dark mode has been added."

[0659] In this way, the automatic collection, analysis, database management, document generation, and user notification of product update information are all realized in a single, streamlined process.

[0660] (Application Example 2)

[0661] 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."

[0662] Traditional update notification systems often simply relay collected information to users without considering their current emotional state or feedback, resulting in a lack of improved user experience. Furthermore, this could lead to users receiving unnecessary information, potentially causing stress. Additionally, important changes might be overlooked, leading to a lack of understanding of the update content.

[0663] 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 periodically collecting update information from multiple data sources on the internet, means for analyzing the collected update information and converting it into a standardized data format, means for storing the converted data in a database, means for automatically generating a document format (including slides or spreadsheets) based on the stored data, means for analyzing the user's emotions based on user feedback and usage history, means for customizing update notifications according to the user's emotions, and means for sending customized notifications to the user when new update information is added. This makes it possible to appropriately provide information according to the user's emotional state and to appropriately notify them without missing important information.

[0664] "Means of collecting update information from multiple data sources on the internet on a regular basis" refers to a function that automatically retrieves software and service update information from multiple websites and APIs based on a schedule set via the internet.

[0665] "Means for analyzing collected update information and converting it into a standardized data format" refers to a function that analyzes acquired update information using natural language processing and data analysis techniques and formats it into a unified format.

[0666] "Means of storing converted data in a database" refers to a function that stores analyzed and standardized data in a database so that it can be searched and referenced later.

[0667] "Means for automatically generating document formats (including slides or spreadsheets) based on saved data" refers to a function that automatically creates visual documents such as presentation slides and spreadsheets using information stored in a database.

[0668] "Means of analyzing user emotions based on user feedback and usage history" refers to a function that collects user input and operation history and uses an emotion analysis algorithm to estimate the user's current emotional state based on this data.

[0669] "Means of customizing update notifications according to user emotions" refers to a function that takes into account the analyzed emotional state of the user and modifies the notification content or presents it in a specific way to provide information in the most optimal format for the user.

[0670] "Means of sending customized notifications to users when new update information is added" refers to a function that sends a pre-customized notification message to users via email or push notification when new update information is added to the system.

[0671] This invention can be implemented by coordinating several system components and programs. The specific method is described below.

[0672] The server periodically collects update information from multiple data sources on the internet. This can be done using techniques such as Web APIs and Web scraping. For example, to collect the latest update information for product A, an HTTP request is sent to a specified API endpoint, and JSON data is received as a response. Since this collected data is difficult to use directly, it is analyzed using natural language processing (NLP) techniques and converted into a standardized data format. The analyzed data is then formatted into a unified format and stored in a database. Cloud services such as Amazon RDS and Google Cloud Firestore can be used for the database.

[0673] Next, a document format (slides or spreadsheet) is automatically generated based on this saved data. This can be achieved using cloud-based presentation tools such as the "Google Slides API" or "Google Sheets API". For example, based on the update information for the new version 2.0.1, a presentation titled "Product A Version 2.0.1 Update" is created in Google Slides, and information such as "Login problem fixed" and "Dark mode added" is inserted into its content.

[0674] Furthermore, user feedback and usage history are analyzed using an emotion engine. In this case, emotion analysis engines such as "Amazon Rekognition," "Google Cloud Vision," and "Microsoft Azure Face API" can be used to analyze the user's facial expressions, voice, and text data to estimate their emotional state. For example, if a user writes "It's become easier to use" in their feedback, the feedback text is analyzed using NLP technology to determine that the emotion is "positive."

[0675] Update notifications are customized based on the user's sentiment. If the sentiment is positive, a detailed notification is applied, such as "A new version 2.0.1 has been released. See the detailed release notes here." Conversely, if the sentiment is negative, a concise notification is sent, such as "A new version 2.0.1 has been released. Login issues have been fixed and dark mode has been added." This customized notification is sent to the user via email or push notification. Email services such as "Amazon SES" and "SendGrid" or "Firebase Cloud Messaging (FCM)" can be used.

[0676] For example, suppose user A is using the "EmotionPay" app and receives a notification about the latest update. The system first analyzes the user's feedback with its emotion engine and detects positive emotions. As a result, the system chooses to send a detailed notification, and user A receives a notification stating, "A new version 2.0.1 has been released. Click here for detailed release notes."

[0677] An example of a prompt statement is as follows:

[0678] "As an EmotionPay user, you will receive a notification when the latest version 2.0.1 is released. Based on your feedback and sentiment analysis, the notification will be customized and will determine whether or not it includes detailed release notes. Please write 'Positive' or 'Negative' in your feedback."

[0679] In this way, this invention can provide appropriate information according to the user's emotional state and improve the user experience.

[0680] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0681] Step 1:

[0682] The server periodically collects update information from multiple data sources on the internet. This is done by sending HTTP requests to API endpoints and websites according to a pre-configured schedule. As a result, data in JSON format is returned as a response. The input is the URL of the API endpoint or website, and the output is the collected update information in JSON format.

[0683] Step 2:

[0684] The server analyzes the collected update information and converts it into a standardized data format. This is done by parsing the acquired JSON data, using natural language processing (NLP) techniques to extract important information (e.g., version number and changes), and converting it into a unified format. The input is the collected JSON data, and the output is a standardized data format. Specifically, the system uses Python's json module to import data and then analyzes it using NLP libraries such as spaCy or NLTK.

[0685] Step 3:

[0686] The server stores the transformed data in a database. This is a process that uses a database connection module to parse and standardize the data, store it in the database, and update or add any new information by comparing it with existing data. The input is a standardized data format, and the output is the data stored in the database. Specifically, SQL queries are used to insert and update data in the database.

[0687] Step 4:

[0688] The server automatically generates document formats (slides or spreadsheets) based on the stored data. This is a process of creating automatically generated documents using cloud-based presentation tools such as the Google Slides API and the Google Sheets API. The input is update information stored in the database, and the output is the generated presentation or spreadsheet. Specifically, a new document is generated using the Google API client, and the update information is inserted.

[0689] Step 5:

[0690] The server analyzes user sentiment based on user feedback and usage history. This process involves processing user feedback text and usage history data using a sentiment analysis engine (e.g., Amazon Rekognition, Google Cloud Vision, Microsoft Azure Face API) to estimate the user's sentiment. The input is user feedback and usage history data, and the output is the analyzed sentiment data. Specifically, the server calls the sentiment analysis API and saves the results to a database.

[0691] Step 6:

[0692] The server customizes update notifications based on the user's emotions. This is a process that modifies the notification content based on the emotion analysis results. For example, if the emotion is "positive," a detailed notification is created, and if the emotion is "negative," a concise notification is created. The input is the emotion analysis result, and the output is the customized notification message. Specifically, multiple notification templates are prepared, and the appropriate template is selected according to the emotion analysis result.

[0693] Step 7:

[0694] The server sends customized notifications to users when new update information is added. This is done, for example, via email or push notifications. The input is the customized notification message, and the output is the notification sent to the user. Specifically, the server calls a notification service (e.g., Amazon SES, SendGrid, Firebase Cloud Messaging (FCM)) to send the notification message.

[0695] 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.

[0696] 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.

[0697] 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.

[0698] [Third Embodiment]

[0699] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0700] 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.

[0701] 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).

[0702] 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.

[0703] 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.

[0704] 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).

[0705] 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.

[0706] 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.

[0707] 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.

[0708] 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.

[0709] 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.

[0710] 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".

[0711] This invention relates to a system that automatically collects and analyzes product update information, generates related documents, and notifies users. In particular, it periodically collects update information, converts it into a standardized data format, stores it in a database, and further generates output in cloud-based presentation or spreadsheet format.

[0712] Program Processing Overview

[0713] 1. Data Collection

[0714] The server collects product update information from multiple data sources based on a regular schedule. For example, the server sends an HTTP request to the API endpoint of product A and receives JSON data as a response. The data obtained in this way includes the latest version information and corrections for that product.

[0715] 2. Information Analysis and Transformation

[0716] The server uses natural language processing (NLP) to analyze the collected JSON data and extract the necessary information. This analysis yields specific version numbers, types of changes (bug fixes, new features, etc.), and detailed descriptions. The analyzed information is then converted into a predefined standardized format.

[0717] 3. Storing in a database

[0718] The extracted and standardized data is stored in a database. Because the database is structured, the information can be retrieved and used quickly and efficiently later.

[0719] 4. Automatic output generation

[0720] The server automatically generates document formats (slides or spreadsheets) based on information stored in the database. For example, it can use the Google Slides API to generate a new presentation and insert update information into the slides. Similarly, when outputting as a spreadsheet, the API is used to input the data.

[0721] 5. Update notification

[0722] When the server detects new update information, it sends a notification to the user. By using methods such as email and push notifications, users can quickly receive the latest information.

[0723] Specific example

[0724] For example, if the latest version 2.0.1 of product A is released, its release notes will include information such as "Login problem fixed" and "Dark mode added." The server collects this information via an API, analyzes it, and converts it into a standardized data format as follows.

[0725] json

[0726] {

[0727] "product": "A",

[0728] "version": "2.0.1",

[0729] "updates": [

[0730] {"type": "bugfix", "description": "Fixed login issue"},

[0731] {"type": "feature", "description": "Added dark mode"}

[0732] ]

[0733] }

[0734] This information is stored in a database and automatically updated whenever it is updated. Next, based on the output format selected by the user, a presentation is automatically generated, for example, using Google Slides. The generated slides include:

[0735] 1. Title Slide: "Product A Version 2.0.1 Update"

[0736] 2. Content slides: "1. Fixed login issues" "2. Added dark mode"

[0737] The data is entered in this format.

[0738] Finally, users are notified by email when new update information is added. The email body includes a brief summary and a link to further details. In this way, users can quickly and efficiently grasp new update information.

[0739] The following describes the processing flow.

[0740] Step 1:

[0741] The server sends an HTTP request to an API endpoint on the internet based on a schedule. This request is to retrieve the latest update information for a product; for example, it sends a request GET https: / / api.example.com / productA / updates to retrieve update information for product A.

[0742] Step 2:

[0743] The server receives JSON data as a response from the API. This response contains information such as new version information, changes, and bug fixes for the product, and is ready to be analyzed in the next step.

[0744] Step 3:

[0745] The server parses the received JSON data and uses natural language processing (NLP) tools to extract important information (version number, changes, etc.). For example, it might obtain information such as version "2.0.1", "login issue fixed", and "dark mode added".

[0746] Step 4:

[0747] The server converts the parsed information into a standardized data format. This standardized format is a unified format defined for use in the system, and may look like this:

[0748] json

[0749] {

[0750] "product": "A",

[0751] "version": "2.0.1",

[0752] "updates": [

[0753] {"type": "bugfix", "description": "Fixed login issue"},

[0754] {"type": "feature", "description": "Added dark mode"}

[0755] ]

[0756] }

[0757] Step 5:

[0758] The server saves the converted data to the database. It compares it with the already saved data and updates or adds any new information.

[0759] Step 6:

[0760] The server automatically generates output based on collected and analyzed information in response to user requests. For example, it can create a new presentation using the Google Slides API and insert update information into it. Specifically, it can add "Product A Version 2.0.1 Update" as the slide title and enter content such as "1. Fixed login issue" and "2. Added dark mode" on each slide.

[0761] Step 7:

[0762] The server saves the generated documents to designated cloud storage and generates a link that the user can access. Using this link, the user can access the latest update information from anywhere.

[0763] Step 8:

[0764] When the server detects new update information, it uses a means to notify users, such as sending emails or push notifications. For example, it might use an SMTP server to send an email to users stating, "New version 2.0.1 has been released." The email would include detailed release notes and links.

[0765] (Example 1)

[0766] 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."

[0767] Traditional methods of managing product update information were often manual, resulting in low efficiency and time-consuming updates. Furthermore, the analysis and standardization of information was labor-intensive, placing a heavy burden on workers. Additionally, it was sometimes difficult to notify users of updates in a timely manner, making it challenging for users to access the latest information.

[0768] 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.

[0769] In this invention, the server includes means for periodically collecting change information from multiple data sources on an information network, means for analyzing the collected change information and converting it into a standardized data format, means for storing the converted data in a storage device, means for automatically generating a document format (including display materials or calculation tables) based on the stored data, means for notifying the user when new change information is added, means for setting a periodic schedule, means for analyzing the collected data using natural language processing technology, means for creating the generated document format using a cloud service, and means for using email or push notifications as a notification method. This enables automatic collection, analysis, standardization, storage, automatic document generation, and rapid notification to users of product update information.

[0770] An "information network" refers to communication infrastructure used for sending and receiving data, such as the internet and local area networks.

[0771] "Change information" refers to data related to updates to merchandise or products, specifically including information such as the addition of new features, bug fixes, and performance improvements.

[0772] "Collection means" refers to functions and technologies for obtaining change information from data sources via an information network.

[0773] "Analysis means" refers to functions and technologies for processing collected change information and extracting necessary information. This includes natural language processing technologies, among others.

[0774] A "standardized data format" is a data structure that converts analyzed information into a specific format and stores it in a unified format.

[0775] A "storage device" is a physical or virtual storage device used to store data for extended periods.

[0776] "Document format" refers to the format used to present analyzed and standardized data, and includes presentation materials (slides) and calculation tables (spreadsheets).

[0777] "Generation means" refers to technologies and functions for automatically creating document formats based on stored data.

[0778] "Notification methods" refer to methods used to inform users when new changes are added, and include email and push notifications.

[0779] A "scheduling tool" is a function or technology that allows you to create a plan for performing tasks at regular, fixed times.

[0780] "Natural language processing technology" is a technique for analyzing collected text data and understanding its meaning and intent.

[0781] "Cloud services" refer to services such as software and storage that are provided on remote servers via the internet.

[0782] This invention is a system that automatically collects, analyzes, standardizes, and stores change information, generates documents based on that information, and notifies users. A specific embodiment of this system will be described below.

[0783] The server periodically collects change information from multiple data sources on the information network. These data sources include product API endpoints and various websites. For example, the server can send an HTTP request and receive data in JSON format as a response.

[0784] The server analyzes the collected JSON data and extracts the necessary information. Natural language processing (NLP) techniques are used as the specific analysis method. These NLP techniques include libraries such as spaCy and NLTK. This analysis yields information such as version numbers, types of changes (bug fixes, new features, etc.), and detailed descriptions, which are then converted into a standardized data format.

[0785] Standardized data is stored in storage by the server. A database is used as the storage device. Because the database is structured, the information can be retrieved and used quickly and efficiently later.

[0786] Next, the server automatically generates document formats (slides or spreadsheets) based on the stored data. Cloud services are used for document generation. Specifically, the Google Slides API and Google Sheets API are used. This automatically generates updated information in presentation or spreadsheet format.

[0787] When new changes are added, the server sends a notification to the user. Notifications are sent via email or push notifications, allowing users to quickly access the latest information.

[0788] For example, when the latest version 2.0.1 of product A is released, its release notes include information such as "Login problem fixed" and "Dark mode added." The server collects this information via an API, analyzes it, and converts it into a standardized data format. This information is then stored in a database, and new information is automatically reflected with each update. Next, a presentation using Google Slides is automatically generated based on the output format selected by the user. The generated slides may include content such as the following:

[0789] 1. Title Slide: "Product A Version 2.0.1 Update"

[0790] 2. Content slides: "1. Fixed login issues" "2. Added dark mode"

[0791] Furthermore, the server notifies users via email when new update information is added. The email body includes a brief summary and a link to further details. In this way, users can quickly and efficiently grasp new update information.

[0792] The following are specific examples of prompt statements to be input to a generative AI model:

[0793] "Product A has released its latest version, 2.0.1. Please describe a system that automatically collects, analyzes, and stores update information in a standardized data format, and then notifies users of this update. The information to be collected will include details of bug fixes and new features."

[0794] In this way, technical automation is achieved, and a system is built that allows users to efficiently obtain the latest change information.

[0795] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0796] Step 1:

[0797] The server sets a regular schedule. Based on this schedule, a task to collect product update information is automatically executed. The server uses crontab or Task Scheduler to set this schedule. The input is time information for scheduling, and the output is the set schedule information.

[0798] Specific actions:

[0799] The server sets a schedule in the format "0 1 / path / to / script.sh". This causes the script to run automatically every day at 1 AM.

[0800] Step 2:

[0801] The server collects change information from data sources on the information network based on a configured schedule. The server sends an HTTP request to the API endpoint and receives JSON data as a response. The input is the URL of the API endpoint, and the output is the retrieved JSON data.

[0802] Specific actions:

[0803] The server sends a GET request to the API endpoint and receives a response from "https: / / api.example.com / productA / version". This response contains the latest version information for product A.

[0804] Step 3:

[0805] The server parses the collected JSON data, extracting and standardizing the necessary information. The server uses natural language processing techniques to extract information such as version numbers and change types from the text data. The input is the acquired JSON data, and the output is in a standardized data format.

[0806] Specific actions:

[0807] The server uses a natural language processing library (e.g., spaCy) to identify version numbers and changes from JSON data and convert them into a standardized data structure. For example, it might extract "bug fixes" and "new features added" as changes for version 2.0.1.

[0808] Step 4:

[0809] The server analyzes and standardizes the data and stores it in storage. A structured database is used as the database. The input is standardized data, and the output is the information stored in the database.

[0810] Specific actions:

[0811] The server uses the SQLAlchemy library to analyze and standardize the data, then inserts it into the database. The database stores information such as "Product A," "Version 2.0.1," "Bug fixes," and "New features added."

[0812] Step 5:

[0813] The server automatically generates document formats (slides or spreadsheets) based on stored data. The server uses the Google Slides API and Google Sheets API to generate documents on cloud services. The input is information stored in a database, and the output is the generated document file.

[0814] Specific actions:

[0815] The server uses the Google Slides API to create a new presentation and insert update information into the slides. The generated slides include a title slide titled "Product A Version 2.0.1 Update" and detailed slides describing the changes.

[0816] Step 6:

[0817] The server sends a notification to users when new change information is added. Notification methods include email and push notifications. The input is the new change information, and the output is the notification sent to the user.

[0818] Specific actions:

[0819] The server uses an SMTP server to send an email to the user containing information about the new version update. The email includes a summary of "Product A Version 2.0.1 Update" and a link to the details.

[0820] (Application Example 1)

[0821] 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."

[0822] In modern brick-and-mortar stores, there is a need to quickly and accurately grasp updates on a wide variety of products and efficiently provide that information to staff and managers. However, manually collecting, analyzing, and notifying relevant parties of updates for numerous products is extremely time-consuming and prone to delays and errors. This challenge is particularly pronounced in brick-and-mortar stores that handle a large volume of products, and inefficient management of product update information can negatively impact the overall efficiency of operations and the quality of service.

[0823] 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.

[0824] In this invention, the server includes means for periodically collecting update information from multiple data sources on the internet, means for analyzing the collected update information and converting it into a standardized data format, means for storing the converted data in a database, means for automatically generating a document format (including slides or spreadsheets) based on the stored data, means for notifying the user when new update information is added, means for analyzing product update information and generating information to be displayed on a smart device, means for providing information to staff based on product update information, and means for generating and displaying cloud-based presentations or spreadsheets. This makes it possible to quickly and accurately grasp update information for a wide variety of products in physical stores and efficiently provide it to managers and staff.

[0825] A "data source" refers to multiple sources of information that provide update information on the internet.

[0826] "Update information" refers to detailed information about changes made to a product, such as the latest version, major fixes, and the addition of new features.

[0827] "Analysis" refers to the process of extracting useful information from collected data and converting it into a standardized format.

[0828] A "standardized data format" is a unified format that allows analyzed data to be stored and used consistently.

[0829] A "database" is a structured collection of data used to efficiently store, manage, and retrieve data.

[0830] "Document format" refers to the visual display format of information, including slides or spreadsheets.

[0831] A "cloud-based presentation" refers to a presentation document that can be accessed and edited via the internet.

[0832] A "spreadsheet service" refers to spreadsheet software that can be used online.

[0833] "Notification" refers to informing relevant parties when new update information becomes available.

[0834] A "smart device" refers to an internet-connected device with advanced features, such as a smartphone, tablet, or smart glasses.

[0835] This invention relates to a system for automatically collecting, analyzing, and notifying updates on merchandise in physical stores. The following describes how this system is specifically implemented.

[0836] Hardware and software to be used

[0837] The entire system uses the following hardware and software.

[0838] Server: Performs data collection, analysis, database management, document generation, and notification sending.

[0839] Main software used: Python, Requests library, sqlite3, Google API client library, smtplib, etc.

[0840] Smart devices: Smartphones, tablets, smart glasses, etc. Used for display and notification reception.

[0841] Data collection

[0842] The server periodically collects product update information from multiple data sources on the internet. This collection uses API requests and web scraping. For example, it obtains update information for product A in JSON format from an API endpoint.

[0843] Information analysis and transformation

[0844] The collected update information is analyzed using natural language processing (NLP) and converted into a standardized data format. This analysis extracts the version number, type of change (bug fixes, new features, etc.), and detailed descriptions. The converted data is then unified into a consistent format for post-processing.

[0845] Save to database

[0846] The analyzed data is stored in the server's database. This database is structured, allowing for fast and efficient retrieval of the stored information.

[0847] Automatic document generation

[0848] The server automatically generates documents based on the stored data. These documents are generated in cloud-based presentation or spreadsheet formats. For example, using the Google Slides API, slides that make up a presentation containing update information are automatically created.

[0849] notification

[0850] When new update information is added, the server sends a notification to smart devices. Email and push notifications are used to ensure users are quickly informed of the updates.

[0851] Information provision via smart devices

[0852] The analyzed update information is displayed on smart devices. Users can instantly check the latest information on products and take necessary actions quickly.

[0853] Specific example

[0854] For example, if the latest version 2.1.0 of product A is released, the information will be processed as follows.

[0855] 1. Collect update information for version 2.1.0 from the API endpoint.

[0856] 2. Analyze information such as "improved product page loading speed" and "added new recommendation features," and convert it into a standardized data format.

[0857] 3. Save to an SQLite database.

[0858] 4. Based on the collected information, the next slide will be automatically generated using the Google Slides API.

[0859] Title slide: "Product A Version 2.1.0 Update"

[0860] Presentation slides: "1. Improved product page loading speed" "2. Added a new recommendation feature"

[0861] 5. Notify users of new update information.

[0862] Examples of input prompts for a generative AI model

[0863] "Please analyze and process the update information for version 2.1.0 of product A, and generate a presentation. Also, please send an email to administrators and staff notifying them of the new update information."

[0864] In this way, by combining servers, smart devices, and cloud-based presentation and spreadsheet services, it is possible to achieve efficient product update management in physical stores.

[0865] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0866] Step 1:

[0867] The server periodically collects update information from multiple data sources on the internet. Specifically, it uses API requests to obtain product update information. The input is the URL of the API endpoint, and the output is update information data in JSON format. This data includes the version number and changes of the updated product.

[0868] Step 2:

[0869] The server parses the collected JSON-formatted update information and converts it into a standardized data format. Natural language processing (NLP) is used for this parsing. The input is JSON data, and the output is a standardized data format containing version number, type of change (bug fix, new feature added), and detailed description. Specifically, it extracts predetermined key information from the JSON data and converts it into a unified format.

[0870] Step 3:

[0871] The server saves the converted data to a local SQLite database. Standardized data is used as input, and the output is the addition of new records to the database. This saving process allows for fast and efficient retrieval and use of the information later. Specifically, data is added using SQL INSERT statements.

[0872] Step 4:

[0873] The server automatically generates a document format (slides or spreadsheets) based on the stored data. This primarily uses the Google Slides API. The input is updated information retrieved from the database, and the output is a new presentation generated on Google Slides. Specifically, the Google Slides API is called, and information is inserted into the slides according to the template.

[0874] Step 5:

[0875] The server sends notifications to users when new update information is added. Email and push notifications are used as notification methods. The input consists of the update information and a list of users who should receive notifications, and the output is a notification message. Specifically, this involves sending emails using an SMTP server or calling a push notification API.

[0876] Step 6:

[0877] The terminal (smart device) displays the analyzed update information. Users can immediately check the latest product information on their smartphones or tablets. The input is update information sent from the server, and the output is the latest information displayed on the device. Specifically, the device's notification function or application receives the new information and displays it on the screen.

[0878] Step 7:

[0879] The server uses updated product information to provide training and response instructions to staff. This method allows staff to quickly grasp new information and use it to assist customers. The input is the latest product information, and the output is instructions and training materials for staff. Specifically, it generates training materials based on new information and sends notifications.

[0880] 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.

[0881] This invention relates to a system that automatically collects and analyzes product update information, generates related documents, and further recognizes user emotions to adjust notification content. Specifically, it periodically collects update information, converts it into a standardized data format, stores it in a database, generates output in cloud-based presentation or spreadsheet format, and provides customized notifications based on user emotions using an emotion engine.

[0882] Program Processing Overview

[0883] 1. Data Collection

[0884] The server collects product update information from multiple data sources using API endpoints and web scraping, based on a schedule. For example, it sends an HTTP request to the API endpoint for product A, https: / / api.example.com / productA / updates, and receives JSON data as a response.

[0885] 2. Information Analysis and Transformation

[0886] The server parses the received JSON data and uses natural language processing (NLP) to extract important information (version number, changes, etc.). The extracted information is converted into a standardized data format and stored in the database as a unified format. For example, information such as "new version 2.0.1", "login problem fixed", and "dark mode added" can be obtained.

[0887] 3. Storing in a database

[0888] The server stores the analyzed and transformed data in the database. It compares it with the already stored data and updates or adds any new information.

[0889] 4. Automatic output generation

[0890] The server generates cloud-based presentations (such as Google Slides) or spreadsheets based on information in the database. For example, it can use the Google Slides API to generate a new presentation and insert update information into it. The generated slides will have the title "Product A Version 2.0.1 Update" and each slide will contain information such as "1. Fixed login issue" and "2. Added dark mode".

[0891] 5. Analysis using an emotion engine

[0892] The server analyzes user feedback and usage history using an emotion engine. The emotion engine estimates emotions from the user's facial expressions, voice, and text data, and stores the results.

[0893] 6. Customize update notifications

[0894] The server generates customized notifications based on the analysis results from the emotion engine, tailored to the user's emotions. For example, if the user is stressed, the notification will be concise and use positive language. Conversely, if the user is relaxed, the notification will also include detailed changes and recommended actions.

[0895] 7. Send update notifications

[0896] When the server detects new update information, it sends a notification to the user. Customized notifications, reflecting the results of the sentiment engine, are sent via email or push notification. For example, if the user is feeling stressed, a concise message such as "New version 2.0.1 has been released. Login issues have been fixed and dark mode has been added." might be sent.

[0897] Specific example

[0898] For example, if the latest version 2.0.1 of product A is released, its release notes will include information such as "Login problem fixed" and "Dark mode added." The server collects this information via an API, analyzes it, and converts it into a standardized data format as follows:

[0899] json

[0900] {

[0901] "product": "A",

[0902] "version": "2.0.1",

[0903] "updates": [

[0904] {"type": "bugfix", "description": "Fixed login issue"},

[0905] {"type": "feature", "description": "Added dark mode"}

[0906] ]

[0907] }

[0908] This information is stored in a database and automatically updated whenever it is updated. Then, the presentation automatically generated using Google Slides will have the aforementioned information placed on the slides.

[0909] Furthermore, based on user emotion assessment information, users experiencing stress receive the concise notification mentioned above, while users with ample free time receive a more detailed notification with a link stating, "A new version 2.0.1 has been released. Please see the detailed release notes here." In this way, the user experience can be improved.

[0910] The following describes the processing flow.

[0911] Step 1:

[0912] The server collects product update information from multiple data sources using API endpoints on the internet and web scraping, based on a schedule. Specifically, it sends an HTTP request GET https: / / api.example.com / productA / updates to the API endpoint for product A and receives JSON data as a response.

[0913] Step 2:

[0914] The server parses the response data received from the API. For example, if the JSON data received as a response is in the following format:

[0915] json

[0916] {

[0917] "version": "2.0.1",

[0918] "changes": [

[0919] {

[0920] "type": "bugfix",

[0921] "description": "Fixed login issue"

[0922] },

[0923] {

[0924] "type": "feature",

[0925] "description": "Added dark mode"

[0926] }

[0927] ]

[0928] }

[0929] The server will analyze this data.

[0930] Step 3:

[0931] The server uses natural language processing (NLP) tools to extract important information from the parsed data. Specifically, it identifies and extracts the "version number," "type of change," and "details of the change."

[0932] Step 4:

[0933] The server converts the extracted information into a standardized data format. For example, it converts it to a unified format such as the following:

[0934] json

[0935] {

[0936] "product": "A",

[0937] "version": "2.0.1",

[0938] "updates": [

[0939] {"type": "bugfix", "description": "Fixed login issue"},

[0940] {"type": "feature", "description": "Added dark mode"}

[0941] ]

[0942] }

[0943] Step 5:

[0944] The server saves the converted standardized data to the database. It checks for duplicates with existing data and adds or updates new information.

[0945] Step 6:

[0946] The server automatically generates output in response to user requests. For example, it creates a new presentation using the Google Slides API. Specifically, it adds "Product A Version 2.0.1 Update" as the slide title and enters the following information into each slide:

[0947] 1. Content of Slide 1: "Login problem fixed"

[0948] 2. Content of Slide 2: "Add Dark Mode"

[0949] Step 7:

[0950] The server uses an emotion engine to analyze the user's emotional data. The emotion engine processes data such as user feedback, facial expressions, voice, and text to determine the user's current emotional state (stress, relaxation, excitement, etc.).

[0951] Step 8:

[0952] The server generates customized notification content based on the analysis results of the emotion engine. For example, if the user is stressed, it creates a concise and positive notification; if they are relaxed, it creates a notification that includes detailed release notes and recommended actions.

[0953] Step 9:

[0954] When the server detects new update information, it sends a notification to the user. Customized notifications, reflecting the results of the sentiment engine, are sent via email or push notification. For example, an email like the following might be sent:

[0955] For users experiencing high stress levels: "A new version, 2.0.1, has been released. Login issues have been fixed, and dark mode has been added."

[0956] For relaxed users: An email with a link saying, "A new version 2.0.1 has been released. Click here for detailed release notes."

[0957] As described above, the system automatically collects, analyzes, and stores product update information, and uses an emotion engine to notify users in the most optimal way. This improves the user experience.

[0958] (Example 2)

[0959] 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."

[0960] Traditional systems had problems with effectively managing and notifying users of product updates, requiring a lot of effort, and failing to provide appropriate notifications based on user sentiment. The difficulty in providing customized notifications tailored to user needs and circumstances resulted in a degraded user experience.

[0961] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for periodically collecting update information from multiple data sources on the internet, means for analyzing the collected update information and converting it into a standardized data format, means for storing the converted data in a database, means for analyzing the user's emotions using an emotion engine and customizing notification content based on the analysis results, and means for notifying the user when new update information is added. This enables automatic management of product update information and customized notifications based on emotions.

[0962] A "data source" is an information source that provides updated information about products on the internet.

[0963] "Update information" refers to information that indicates changes to a product, such as version upgrades, feature additions, and bug fixes.

[0964] "Analysis" refers to the process of breaking down collected update information, extracting important elements, and understanding them.

[0965] A "standardized data format" is a format that enhances data consistency and compatibility by converting analyzed information into a consistent format.

[0966] A "database" is a place to store and manage analyzed data for the long term.

[0967] A "document format" refers to the format of visual materials (such as presentation slides or spreadsheets) used to visually organize information and make it easier to understand.

[0968] An "emotion engine" is an algorithm or system that analyzes user feedback and usage history to estimate their emotional state.

[0969] "Customizing notification content" means adjusting and optimizing the content of update notifications according to the user's emotional state.

[0970] This invention relates to a system that automatically collects and analyzes product update information, generates related documents, and further recognizes user emotions to adjust notification content. Specifically, it periodically collects update information, converts it into a standardized data format, stores it in a database, and generates output in cloud-based presentation or spreadsheet format. It also uses an emotion engine to provide customized notifications based on user emotions.

[0971] First, the server collects product update information from multiple data sources based on a schedule, using API endpoints and web scraping. For example, it sends an HTTP request to the API endpoint for product A, https: / / api.example.com / productA / updates, and receives JSON data as a response. HTTP GET requests and scraping tools are used as collection methods.

[0972] The collected data is parsed by the server, and important information is extracted using natural language processing (NLP) algorithms. For example, information such as the version number "2.0.1" and changes such as "fixed login issue" and "added dark mode" is extracted. This information is converted into a standardized data format (e.g., JSON format) and stored in the database as a unified format.

[0973] Based on the information stored in the database, the server generates cloud-based presentations (such as Google Slides) or spreadsheets. Using the Google Slides API, a new presentation is generated and the update details are inserted into it. The generated slides will have the title "Product A Version 2.0.1 Update" and each slide will contain information such as "1. Fixed login issue" and "2. Added dark mode".

[0974] Next, user feedback and usage history are analyzed by the emotion engine. The emotion engine estimates the user's emotions from facial expressions, voice, and text data, and stores the results. This allows the system to determine whether the user is stressed or relaxed.

[0975] Based on the analysis results, the server generates customized notifications tailored to the user's emotions. For example, if the user is stressed, the notification will be concise and use positive language. Conversely, if the user is relaxed, the notification will also include detailed changes and recommended actions. This process improves the user experience and ensures that necessary information is effectively communicated.

[0976] Finally, when new update information is detected, the server sends a customized notification to the user that reflects the results of the sentiment engine. The notification can be sent via email or push notification, and a specific example would be a concise message such as, "New version 2.0.1 has been released. Login issues have been fixed and dark mode has been added."

[0977] An example of a prompt message is input to the generating AI model in the following format:

[0978] "A new version 2.0.1 of Product A has been released. This version includes 'Login issue fix' and 'Dark Mode added.' Please generate sentiment-based notifications for users regarding these changes."

[0979] This invention automates the management of product update information and notifications to users, and further enhances the user experience by providing optimal notifications tailored to the user's emotions.

[0980] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0981] Step 1:

[0982] The server periodically collects update information from multiple data sources on the internet. Inputs include a schedule and the URLs of the data sources (e.g., https: / / api.example.com / productA / updates). Based on this, the server sends an HTTP GET request and receives update information in JSON format as a response. Specifically, it sends a request to the URL of product A and retrieves JSON data containing the version number and changes.

[0983] Step 2:

[0984] The server parses and analyzes the collected JSON data. The input is the acquired JSON data. The server uses natural language processing (NLP) algorithms to analyze the data and extract important information (e.g., version number, changes). Specifically, it extracts the keys "version" and "changes" from the JSON and retrieves their respective values. This data is then converted into a unified format.

[0985] Step 3:

[0986] The server stores the parsed and transformed data in a database. The input is a standardized data format (e.g., transformed JSON data). The server compares it with existing data and updates or adds new information if necessary. Specifically, it checks the entry for product A in the database and updates it if the version information and changes are new.

[0987] Step 4:

[0988] The server generates cloud-based presentations and spreadsheets based on information in the database. The input includes information stored in the database (e.g., version numbers and changes). The server uses the Google Slides API to generate a new presentation and insert the update details into it. Specifically, it creates a title slide such as "Product A Version 2.0.1 Update" and places the changes on each slide.

[0989] Step 5:

[0990] The server analyzes user feedback and usage history using an emotion engine. Input includes user feedback data and usage history data. The server uses the emotion engine to analyze this data and estimate the user's emotional state (e.g., stress, relaxation). Specifically, it identifies emotions from voice and text data and stores the results.

[0991] Step 6:

[0992] The server generates customized notifications based on the user's emotions, using the results of the emotion engine's analysis. Inputs include the emotion analysis results and update information from the database. The server adjusts the notification content according to each user's emotional state. Specifically, it creates concise notifications for stressed users and detailed notifications for relaxed users.

[0993] Step 7:

[0994] When the server detects new update information, it sends a notification to the user. The input is a customized notification message. The server sends the notification to the user using methods such as email or push notifications. Specifically, the notification might be in the format of, "New version 2.0.1 has been released. Login issues have been fixed and dark mode has been added."

[0995] In this way, the automatic collection, analysis, database management, document generation, and user notification of product update information are all realized in a single, streamlined process.

[0996] (Application Example 2)

[0997] 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."

[0998] Traditional update notification systems often simply relay collected information to users without considering their current emotional state or feedback, resulting in a lack of improved user experience. Furthermore, this could lead to users receiving unnecessary information, potentially causing stress. Additionally, important changes might be overlooked, leading to a lack of understanding of the update content.

[0999] 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 periodically collecting update information from multiple data sources on the internet, means for analyzing the collected update information and converting it into a standardized data format, means for storing the converted data in a database, means for automatically generating a document format (including slides or spreadsheets) based on the stored data, means for analyzing the user's emotions based on user feedback and usage history, means for customizing update notifications according to the user's emotions, and means for sending customized notifications to the user when new update information is added. This makes it possible to appropriately provide information according to the user's emotional state and to appropriately notify them without missing important information.

[1000] "Means of collecting update information from multiple data sources on the internet on a regular basis" refers to a function that automatically retrieves software and service update information from multiple websites and APIs based on a schedule set via the internet.

[1001] "Means for analyzing collected update information and converting it into a standardized data format" refers to a function that analyzes acquired update information using natural language processing and data analysis techniques and formats it into a unified format.

[1002] "Means of storing converted data in a database" refers to a function that stores analyzed and standardized data in a database so that it can be searched and referenced later.

[1003] "Means for automatically generating document formats (including slides or spreadsheets) based on saved data" refers to a function that automatically creates visual documents such as presentation slides and spreadsheets using information stored in a database.

[1004] "Means of analyzing user emotions based on user feedback and usage history" refers to a function that collects user input and operation history and uses an emotion analysis algorithm to estimate the user's current emotional state based on this data.

[1005] "Means of customizing update notifications according to user emotions" refers to a function that takes into account the analyzed emotional state of the user and modifies the notification content or presents it in a specific way to provide information in the most optimal format for the user.

[1006] "Means of sending customized notifications to users when new update information is added" refers to a function that sends a pre-customized notification message to users via email or push notification when new update information is added to the system.

[1007] This invention can be implemented by coordinating several system components and programs. The specific method is described below.

[1008] The server periodically collects update information from multiple data sources on the internet. This can be done using techniques such as Web APIs and Web scraping. For example, to collect the latest update information for product A, an HTTP request is sent to a specified API endpoint, and JSON data is received as a response. Since this collected data is difficult to use directly, it is analyzed using natural language processing (NLP) techniques and converted into a standardized data format. The analyzed data is then formatted into a unified format and stored in a database. Cloud services such as Amazon RDS and Google Cloud Firestore can be used for the database.

[1009] Next, a document format (slides or spreadsheet) is automatically generated based on this saved data. This can be achieved using cloud-based presentation tools such as the "Google Slides API" or "Google Sheets API". For example, based on the update information for the new version 2.0.1, a presentation titled "Product A Version 2.0.1 Update" is created in Google Slides, and information such as "Login problem fixed" and "Dark mode added" is inserted into its content.

[1010] Furthermore, user feedback and usage history are analyzed using an emotion engine. In this case, emotion analysis engines such as "Amazon Rekognition," "Google Cloud Vision," and "Microsoft Azure Face API" can be used to analyze the user's facial expressions, voice, and text data to estimate their emotional state. For example, if a user writes "It's become easier to use" in their feedback, the feedback text is analyzed using NLP technology to determine that the emotion is "positive."

[1011] Update notifications are customized based on the user's sentiment. If the sentiment is positive, a detailed notification is applied, such as "A new version 2.0.1 has been released. See the detailed release notes here." Conversely, if the sentiment is negative, a concise notification is sent, such as "A new version 2.0.1 has been released. Login issues have been fixed and dark mode has been added." This customized notification is sent to the user via email or push notification. Email services such as "Amazon SES" and "SendGrid" or "Firebase Cloud Messaging (FCM)" can be used.

[1012] For example, suppose user A is using the "EmotionPay" app and receives a notification about the latest update. The system first analyzes the user's feedback with its emotion engine and detects positive emotions. As a result, the system chooses to send a detailed notification, and user A receives a notification stating, "A new version 2.0.1 has been released. Click here for detailed release notes."

[1013] An example of a prompt statement is as follows:

[1014] "As an EmotionPay user, you will receive a notification when the latest version 2.0.1 is released. Based on your feedback and sentiment analysis, the notification will be customized and will determine whether or not it includes detailed release notes. Please write 'Positive' or 'Negative' in your feedback."

[1015] In this way, this invention can provide appropriate information according to the user's emotional state and improve the user experience.

[1016] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1017] Step 1:

[1018] The server periodically collects update information from multiple data sources on the internet. This is done by sending HTTP requests to API endpoints and websites according to a pre-configured schedule. As a result, data in JSON format is returned as a response. The input is the URL of the API endpoint or website, and the output is the collected update information in JSON format.

[1019] Step 2:

[1020] The server analyzes the collected update information and converts it into a standardized data format. This is done by parsing the acquired JSON data, using natural language processing (NLP) techniques to extract important information (e.g., version number and changes), and converting it into a unified format. The input is the collected JSON data, and the output is a standardized data format. Specifically, the system uses Python's json module to import data and then analyzes it using NLP libraries such as spaCy or NLTK.

[1021] Step 3:

[1022] The server stores the transformed data in a database. This is a process that uses a database connection module to parse and standardize the data, store it in the database, and update or add any new information by comparing it with existing data. The input is a standardized data format, and the output is the data stored in the database. Specifically, SQL queries are used to insert and update data in the database.

[1023] Step 4:

[1024] The server automatically generates document formats (slides or spreadsheets) based on the stored data. This is a process of creating automatically generated documents using cloud-based presentation tools such as the Google Slides API and the Google Sheets API. The input is update information stored in the database, and the output is the generated presentation or spreadsheet. Specifically, a new document is generated using the Google API client, and the update information is inserted.

[1025] Step 5:

[1026] The server analyzes user sentiment based on user feedback and usage history. This process involves processing user feedback text and usage history data using a sentiment analysis engine (e.g., Amazon Rekognition, Google Cloud Vision, Microsoft Azure Face API) to estimate the user's sentiment. The input is user feedback and usage history data, and the output is the analyzed sentiment data. Specifically, the server calls the sentiment analysis API and saves the results to a database.

[1027] Step 6:

[1028] The server customizes update notifications based on the user's emotions. This is a process that modifies the notification content based on the emotion analysis results. For example, if the emotion is "positive," a detailed notification is created, and if the emotion is "negative," a concise notification is created. The input is the emotion analysis result, and the output is the customized notification message. Specifically, multiple notification templates are prepared, and the appropriate template is selected according to the emotion analysis result.

[1029] Step 7:

[1030] The server sends customized notifications to users when new update information is added. This is done, for example, via email or push notifications. The input is the customized notification message, and the output is the notification sent to the user. Specifically, the server calls a notification service (e.g., Amazon SES, SendGrid, Firebase Cloud Messaging (FCM)) to send the notification message.

[1031] 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.

[1032] 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.

[1033] 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.

[1034] [Fourth Embodiment]

[1035] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1036] 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.

[1037] 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).

[1038] 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.

[1039] 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.

[1040] 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).

[1041] 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.

[1042] 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.

[1043] 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.

[1044] 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.

[1045] 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.

[1046] 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.

[1047] 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".

[1048] This invention relates to a system that automatically collects and analyzes product update information, generates related documents, and notifies users. In particular, it periodically collects update information, converts it into a standardized data format, stores it in a database, and further generates output in cloud-based presentation or spreadsheet format.

[1049] Program Processing Overview

[1050] 1. Data Collection

[1051] The server collects product update information from multiple data sources based on a regular schedule. For example, the server sends an HTTP request to the API endpoint of product A and receives JSON data as a response. The data obtained in this way includes the latest version information and corrections for that product.

[1052] 2. Information Analysis and Transformation

[1053] The server uses natural language processing (NLP) to analyze the collected JSON data and extract the necessary information. This analysis yields specific version numbers, types of changes (bug fixes, new features, etc.), and detailed descriptions. The analyzed information is then converted into a predefined standardized format.

[1054] 3. Storing in a database

[1055] The extracted and standardized data is stored in a database. Because the database is structured, the information can be retrieved and used quickly and efficiently later.

[1056] 4. Automatic output generation

[1057] The server automatically generates document formats (slides or spreadsheets) based on information stored in the database. For example, it can use the Google Slides API to generate a new presentation and insert update information into the slides. Similarly, when outputting as a spreadsheet, the API is used to input the data.

[1058] 5. Update notification

[1059] When the server detects new update information, it sends a notification to the user. By using methods such as email and push notifications, users can quickly receive the latest information.

[1060] Specific example

[1061] For example, if the latest version 2.0.1 of product A is released, its release notes will include information such as "Login problem fixed" and "Dark mode added." The server collects this information via an API, analyzes it, and converts it into a standardized data format as follows.

[1062] json

[1063] {

[1064] "product": "A",

[1065] "version": "2.0.1",

[1066] "updates": [

[1067] {"type": "bugfix", "description": "Fixed login issue"},

[1068] {"type": "feature", "description": "Added dark mode"}

[1069] ]

[1070] }

[1071] This information is stored in a database and automatically updated whenever it is updated. Next, based on the output format selected by the user, a presentation is automatically generated, for example, using Google Slides. The generated slides include:

[1072] 1. Title Slide: "Product A Version 2.0.1 Update"

[1073] 2. Content slides: "1. Fixed login issues" "2. Added dark mode"

[1074] The data is entered in this format.

[1075] Finally, users are notified by email when new update information is added. The email body includes a brief summary and a link to further details. In this way, users can quickly and efficiently grasp new update information.

[1076] The following describes the processing flow.

[1077] Step 1:

[1078] The server sends an HTTP request to an API endpoint on the internet based on a schedule. This request is to retrieve the latest update information for a product; for example, it sends a request GET https: / / api.example.com / productA / updates to retrieve update information for product A.

[1079] Step 2:

[1080] The server receives JSON data as a response from the API. This response contains information such as new version information, changes, and bug fixes for the product, and is ready to be analyzed in the next step.

[1081] Step 3:

[1082] The server parses the received JSON data and uses natural language processing (NLP) tools to extract important information (version number, changes, etc.). For example, it might obtain information such as version "2.0.1", "login issue fixed", and "dark mode added".

[1083] Step 4:

[1084] The server converts the parsed information into a standardized data format. This standardized format is a unified format defined for use in the system, and may look like this:

[1085] json

[1086] {

[1087] "product": "A",

[1088] "version": "2.0.1",

[1089] "updates": [

[1090] {"type": "bugfix", "description": "Fixed login issue"},

[1091] {"type": "feature", "description": "Added dark mode"}

[1092] ]

[1093] }

[1094] Step 5:

[1095] The server saves the converted data to the database. It compares it with the already saved data and updates or adds any new information.

[1096] Step 6:

[1097] The server automatically generates output based on collected and analyzed information in response to user requests. For example, it can create a new presentation using the Google Slides API and insert update information into it. Specifically, it can add "Product A Version 2.0.1 Update" as the slide title and enter content such as "1. Fixed login issue" and "2. Added dark mode" on each slide.

[1098] Step 7:

[1099] The server saves the generated documents to designated cloud storage and generates a link that users can access. Using this link, users can access the latest update information from anywhere.

[1100] Step 8:

[1101] When the server detects new update information, it uses a means to notify users, such as sending emails or push notifications. For example, it might use an SMTP server to send an email to users stating, "New version 2.0.1 has been released." The email would include detailed release notes and links.

[1102] (Example 1)

[1103] 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".

[1104] Traditional methods of managing product update information were often manual, resulting in low efficiency and time-consuming updates. Furthermore, the analysis and standardization of information was labor-intensive, placing a heavy burden on workers. Additionally, it was sometimes difficult to notify users of updates in a timely manner, making it challenging for users to access the latest information.

[1105] 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.

[1106] In this invention, the server includes means for periodically collecting change information from multiple data sources on an information network, means for analyzing the collected change information and converting it into a standardized data format, means for storing the converted data in a storage device, means for automatically generating a document format (including display materials or calculation tables) based on the stored data, means for notifying the user when new change information is added, means for setting a periodic schedule, means for analyzing the collected data using natural language processing technology, means for creating the generated document format using a cloud service, and means for using email or push notifications as a notification method. This enables automatic collection, analysis, standardization, storage, automatic document generation, and rapid notification to users of product update information.

[1107] An "information network" refers to communication infrastructure used for sending and receiving data, such as the internet and local area networks.

[1108] "Change information" refers to data related to updates to merchandise or products, specifically including information such as the addition of new features, bug fixes, and performance improvements.

[1109] "Collection means" refers to functions and technologies for obtaining change information from data sources via an information network.

[1110] "Analysis means" refers to functions and technologies for processing collected change information and extracting necessary information. This includes natural language processing technologies, among others.

[1111] A "standardized data format" is a data structure that converts analyzed information into a specific format and stores it in a unified format.

[1112] A "storage device" is a physical or virtual storage device used to store data for extended periods.

[1113] "Document format" refers to the format used to present analyzed and standardized data, and includes presentation materials (slides) and calculation tables (spreadsheets).

[1114] "Generation means" refers to technologies and functions for automatically creating document formats based on stored data.

[1115] "Notification methods" refer to methods used to inform users when new changes are added, and include email and push notifications.

[1116] A "scheduling tool" is a function or technology that allows you to create a plan for performing tasks at regular, fixed times.

[1117] "Natural language processing technology" is a technique for analyzing collected text data and understanding its meaning and intent.

[1118] "Cloud services" refer to services such as software and storage that are provided on remote servers via the internet.

[1119] This invention is a system that automatically collects, analyzes, standardizes, and stores change information, generates documents based on that information, and notifies users. A specific embodiment of this system will be described below.

[1120] The server periodically collects change information from multiple data sources on the information network. These data sources include product API endpoints and various websites. For example, the server can send an HTTP request and receive data in JSON format as a response.

[1121] The server analyzes the collected JSON data and extracts the necessary information. Natural language processing (NLP) techniques are used as the specific analysis method. These NLP techniques include libraries such as spaCy and NLTK. This analysis yields information such as version numbers, types of changes (bug fixes, new features, etc.), and detailed descriptions, which are then converted into a standardized data format.

[1122] Standardized data is stored in storage by the server. A database is used as the storage device. Because the database is structured, the information can be retrieved and used quickly and efficiently later.

[1123] Next, the server automatically generates document formats (slides or spreadsheets) based on the stored data. Cloud services are used for document generation. Specifically, the Google Slides API and Google Sheets API are used. This automatically generates updated information in presentation or spreadsheet format.

[1124] When new changes are added, the server sends a notification to the user. Notifications are sent via email or push notifications, allowing users to quickly access the latest information.

[1125] For example, when the latest version 2.0.1 of product A is released, its release notes include information such as "Login problem fixed" and "Dark mode added." The server collects this information via an API, analyzes it, and converts it into a standardized data format. This information is then stored in a database, and new information is automatically reflected with each update. Next, a presentation using Google Slides is automatically generated based on the output format selected by the user. The generated slides may include content such as the following:

[1126] 1. Title Slide: "Product A Version 2.0.1 Update"

[1127] 2. Content slides: "1. Fixed login issues" "2. Added dark mode"

[1128] Furthermore, the server notifies users via email when new update information is added. The email body includes a brief summary and a link to further details. In this way, users can quickly and efficiently grasp new update information.

[1129] The following are specific examples of prompt statements to be input to a generative AI model:

[1130] "Product A has released its latest version, 2.0.1. Please describe a system that automatically collects, analyzes, and stores update information in a standardized data format, and then notifies users of this update. The information to be collected will include details of bug fixes and new features."

[1131] In this way, technical automation is achieved, and a system is built that allows users to efficiently obtain the latest change information.

[1132] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1133] Step 1:

[1134] The server sets a regular schedule. Based on this schedule, a task to collect product update information is automatically executed. The server uses crontab or Task Scheduler to set this schedule. The input is time information for scheduling, and the output is the set schedule information.

[1135] Specific actions:

[1136] The server sets a schedule in the format "0 1 / path / to / script.sh". This causes the script to run automatically every day at 1 AM.

[1137] Step 2:

[1138] The server collects change information from data sources on the information network based on a configured schedule. The server sends an HTTP request to the API endpoint and receives JSON data as a response. The input is the URL of the API endpoint, and the output is the retrieved JSON data.

[1139] Specific actions:

[1140] The server sends a GET request to the API endpoint and receives a response from "https: / / api.example.com / productA / version". This response contains the latest version information for product A.

[1141] Step 3:

[1142] The server parses the collected JSON data, extracting and standardizing the necessary information. The server uses natural language processing techniques to extract information such as version numbers and change types from the text data. The input is the acquired JSON data, and the output is in a standardized data format.

[1143] Specific actions:

[1144] The server uses a natural language processing library (e.g., spaCy) to identify version numbers and changes from JSON data and convert them into a standardized data structure. For example, it might extract "bug fixes" and "new features added" as changes for version 2.0.1.

[1145] Step 4:

[1146] The server analyzes and standardizes the data and stores it in storage. A structured database is used as the database. The input is standardized data, and the output is the information stored in the database.

[1147] Specific actions:

[1148] The server uses the SQLAlchemy library to analyze and standardize the data, then inserts it into the database. The database stores information such as "Product A," "Version 2.0.1," "Bug fixes," and "New features added."

[1149] Step 5:

[1150] The server automatically generates document formats (slides or spreadsheets) based on stored data. The server uses the Google Slides API and Google Sheets API to generate documents on cloud services. The input is information stored in a database, and the output is the generated document file.

[1151] Specific actions:

[1152] The server uses the Google Slides API to create a new presentation and insert update information into the slides. The generated slides include a title slide titled "Product A Version 2.0.1 Update" and detailed slides describing the changes.

[1153] Step 6:

[1154] The server sends a notification to users when new change information is added. Notification methods include email and push notifications. The input is the new change information, and the output is the notification sent to the user.

[1155] Specific actions:

[1156] The server uses an SMTP server to send an email to the user containing information about the new version update. The email includes a summary of "Product A Version 2.0.1 Update" and a link to the details.

[1157] (Application Example 1)

[1158] 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".

[1159] In modern brick-and-mortar stores, there is a need to quickly and accurately grasp updates on a wide variety of products and efficiently provide that information to staff and managers. However, manually collecting, analyzing, and notifying relevant parties of updates for numerous products is extremely time-consuming and prone to delays and errors. This challenge is particularly pronounced in brick-and-mortar stores that handle a large volume of products, and inefficient management of product update information can negatively impact the overall efficiency of operations and the quality of service.

[1160] 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.

[1161] In this invention, the server includes means for periodically collecting update information from multiple data sources on the internet, means for analyzing the collected update information and converting it into a standardized data format, means for storing the converted data in a database, means for automatically generating a document format (including slides or spreadsheets) based on the stored data, means for notifying the user when new update information is added, means for analyzing product update information and generating information to be displayed on a smart device, means for providing information to staff based on product update information, and means for generating and displaying cloud-based presentations or spreadsheets. This makes it possible to quickly and accurately grasp update information for a wide variety of products in physical stores and efficiently provide it to managers and staff.

[1162] A "data source" refers to multiple sources of information that provide update information on the internet.

[1163] "Update information" refers to detailed information about changes made to a product, such as the latest version, major fixes, and the addition of new features.

[1164] "Analysis" refers to the process of extracting useful information from collected data and converting it into a standardized format.

[1165] A "standardized data format" is a unified format that allows analyzed data to be stored and used consistently.

[1166] A "database" is a structured collection of data used to efficiently store, manage, and retrieve data.

[1167] "Document format" refers to the visual display format of information, including slides or spreadsheets.

[1168] A "cloud-based presentation" refers to a presentation document that can be accessed and edited via the internet.

[1169] A "spreadsheet service" refers to spreadsheet software that can be used online.

[1170] "Notification" refers to informing relevant parties when new update information becomes available.

[1171] A "smart device" refers to an internet-connected device with advanced features, such as a smartphone, tablet, or smart glasses.

[1172] This invention relates to a system for automatically collecting, analyzing, and notifying updates on merchandise in physical stores. The following describes how this system is specifically implemented.

[1173] Hardware and software to be used

[1174] The entire system uses the following hardware and software.

[1175] Server: Performs data collection, analysis, database management, document generation, and notification sending.

[1176] Main software used: Python, Requests library, sqlite3, Google API client library, smtplib, etc.

[1177] Smart devices: Smartphones, tablets, smart glasses, etc. Used for display and notification reception.

[1178] Data collection

[1179] The server periodically collects product update information from multiple data sources on the internet. This collection uses API requests and web scraping. For example, it obtains update information for product A in JSON format from an API endpoint.

[1180] Information analysis and transformation

[1181] The collected update information is analyzed using natural language processing (NLP) and converted into a standardized data format. This analysis extracts the version number, type of change (bug fixes, new features, etc.), and detailed descriptions. The converted data is then unified into a consistent format for post-processing.

[1182] Save to database

[1183] The analyzed data is stored in the server's database. This database is structured, allowing for fast and efficient retrieval of the stored information.

[1184] Automatic document generation

[1185] The server automatically generates documents based on the stored data. These documents are generated in cloud-based presentation or spreadsheet formats. For example, using the Google Slides API, slides that make up a presentation containing update information are automatically created.

[1186] notification

[1187] When new update information is added, the server sends a notification to smart devices. Email and push notifications are used to ensure users are quickly informed of the updates.

[1188] Information provision via smart devices

[1189] The analyzed update information is displayed on smart devices. Users can instantly check the latest information on products and take necessary actions quickly.

[1190] Specific example

[1191] For example, if the latest version 2.1.0 of product A is released, the information will be processed as follows.

[1192] 1. Collect update information for version 2.1.0 from the API endpoint.

[1193] 2. Analyze information such as "improved product page loading speed" and "added new recommendation features," and convert it into a standardized data format.

[1194] 3. Save to an SQLite database.

[1195] 4. Based on the collected information, the next slide will be automatically generated using the Google Slides API.

[1196] Title slide: "Product A Version 2.1.0 Update"

[1197] Presentation slides: "1. Improved product page loading speed" "2. Added a new recommendation feature"

[1198] 5. Notify users of new update information.

[1199] Examples of input prompts for a generative AI model

[1200] "Please analyze and process the update information for version 2.1.0 of product A, and generate a presentation. Also, please send an email to administrators and staff notifying them of the new update information."

[1201] In this way, by combining servers, smart devices, and cloud-based presentation and spreadsheet services, it is possible to achieve efficient product update management in physical stores.

[1202] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1203] Step 1:

[1204] The server periodically collects update information from multiple data sources on the internet. Specifically, it uses API requests to obtain product update information. The input is the URL of the API endpoint, and the output is update information data in JSON format. This data includes the version number and changes of the updated product.

[1205] Step 2:

[1206] The server parses the collected JSON-formatted update information and converts it into a standardized data format. Natural language processing (NLP) is used for this parsing. The input is JSON data, and the output is a standardized data format containing version number, type of change (bug fix, new feature added), and detailed description. Specifically, it extracts predetermined key information from the JSON data and converts it into a unified format.

[1207] Step 3:

[1208] The server saves the converted data to a local SQLite database. Standardized data is used as input, and the output is the addition of new records to the database. This saving process allows for fast and efficient retrieval and use of the information later. Specifically, data is added using SQL INSERT statements.

[1209] Step 4:

[1210] The server automatically generates a document format (slides or spreadsheets) based on the stored data. This primarily uses the Google Slides API. The input is updated information retrieved from the database, and the output is a new presentation generated on Google Slides. Specifically, the Google Slides API is called, and information is inserted into the slides according to the template.

[1211] Step 5:

[1212] The server sends notifications to users when new update information is added. Email and push notifications are used as notification methods. The input consists of the update information and a list of users who should receive notifications, and the output is a notification message. Specifically, this involves sending emails using an SMTP server or calling a push notification API.

[1213] Step 6:

[1214] The terminal (smart device) displays the analyzed update information. Users can immediately check the latest product information on their smartphones or tablets. The input is update information sent from the server, and the output is the latest information displayed on the device. Specifically, the device's notification function or application receives the new information and displays it on the screen.

[1215] Step 7:

[1216] The server uses updated product information to provide training and response instructions to staff. This method allows staff to quickly grasp new information and use it to assist customers. The input is the latest product information, and the output is instructions and training materials for staff. Specifically, it generates training materials based on new information and sends notifications.

[1217] 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.

[1218] This invention relates to a system that automatically collects and analyzes product update information, generates related documents, and further recognizes user emotions to adjust notification content. Specifically, it periodically collects update information, converts it into a standardized data format, stores it in a database, generates output in cloud-based presentation or spreadsheet format, and provides customized notifications based on user emotions using an emotion engine.

[1219] Program Processing Overview

[1220] 1. Data Collection

[1221] The server collects product update information from multiple data sources using API endpoints and web scraping, based on a schedule. For example, it sends an HTTP request to the API endpoint for product A, https: / / api.example.com / productA / updates, and receives JSON data as a response.

[1222] 2. Information Analysis and Transformation

[1223] The server parses the received JSON data and uses natural language processing (NLP) to extract important information (version number, changes, etc.). The extracted information is converted into a standardized data format and stored in the database as a unified format. For example, information such as "new version 2.0.1", "login problem fixed", and "dark mode added" can be obtained.

[1224] 3. Storing in a database

[1225] The server stores the analyzed and transformed data in the database. It compares it with the already stored data and updates or adds any new information.

[1226] 4. Automatic output generation

[1227] The server generates cloud-based presentations (such as Google Slides) or spreadsheets based on information in the database. For example, it can use the Google Slides API to generate a new presentation and insert update information into it. The generated slides will have the title "Product A Version 2.0.1 Update" and each slide will contain information such as "1. Fixed login issue" and "2. Added dark mode".

[1228] 5. Analysis using an emotion engine

[1229] The server analyzes user feedback and usage history using an emotion engine. The emotion engine estimates emotions from the user's facial expressions, voice, and text data, and stores the results.

[1230] 6. Customize update notifications

[1231] The server generates customized notifications based on the analysis results from the emotion engine, tailored to the user's emotions. For example, if the user is stressed, the notification will be concise and use positive language. Conversely, if the user is relaxed, the notification will also include detailed changes and recommended actions.

[1232] 7. Send update notifications

[1233] When the server detects new update information, it sends a notification to the user. Customized notifications, reflecting the results of the sentiment engine, are sent via email or push notification. For example, if the user is feeling stressed, a concise message such as "New version 2.0.1 has been released. Login issues have been fixed and dark mode has been added." might be sent.

[1234] Specific example

[1235] For example, if the latest version 2.0.1 of product A is released, its release notes will include information such as "Login problem fixed" and "Dark mode added." The server collects this information via an API, analyzes it, and converts it into a standardized data format as follows:

[1236] json

[1237] {

[1238] "product": "A",

[1239] "version": "2.0.1",

[1240] "updates": [

[1241] {"type": "bugfix", "description": "Fixed login issue"},

[1242] {"type": "feature", "description": "Added dark mode"}

[1243] ]

[1244] }

[1245] This information is stored in a database and automatically updated whenever it is updated. Then, the presentation automatically generated using Google Slides will have the aforementioned information placed on the slides.

[1246] Furthermore, based on user emotion assessment information, users experiencing stress receive the concise notification mentioned above, while users with ample free time receive a more detailed notification with a link stating, "A new version 2.0.1 has been released. Please see the detailed release notes here." In this way, the user experience can be improved.

[1247] The following describes the processing flow.

[1248] Step 1:

[1249] The server collects product update information from multiple data sources using API endpoints on the internet and web scraping, based on a schedule. Specifically, it sends an HTTP request GET https: / / api.example.com / productA / updates to the API endpoint for product A and receives JSON data as a response.

[1250] Step 2:

[1251] The server parses the response data received from the API. For example, if the JSON data received as a response is in the following format:

[1252] json

[1253] {

[1254] "version": "2.0.1",

[1255] "changes": [

[1256] {

[1257] "type": "bugfix",

[1258] "description": "Fixed login issue"

[1259] },

[1260] {

[1261] "type": "feature",

[1262] "description": "Added dark mode"

[1263] }

[1264] ]

[1265] }

[1266] The server will analyze this data.

[1267] Step 3:

[1268] The server uses natural language processing (NLP) tools to extract important information from the parsed data. Specifically, it identifies and extracts the "version number," "type of change," and "details of the change."

[1269] Step 4:

[1270] The server converts the extracted information into a standardized data format. For example, it converts it to a unified format such as the following:

[1271] json

[1272] {

[1273] "product": "A",

[1274] "version": "2.0.1",

[1275] "updates": [

[1276] {"type": "bugfix", "description": "Fixed login issue"},

[1277] {"type": "feature", "description": "Added dark mode"}

[1278] ]

[1279] }

[1280] Step 5:

[1281] The server saves the converted standardized data to the database. It checks for duplicates with existing data and adds or updates new information.

[1282] Step 6:

[1283] The server automatically generates output in response to user requests. For example, it creates a new presentation using the Google Slides API. Specifically, it adds "Product A Version 2.0.1 Update" as the slide title and enters the following information into each slide:

[1284] 1. Content of Slide 1: "Login problem fixed"

[1285] 2. Content of Slide 2: "Add Dark Mode"

[1286] Step 7:

[1287] The server uses an emotion engine to analyze the user's emotional data. The emotion engine processes data such as user feedback, facial expressions, voice, and text to determine the user's current emotional state (stress, relaxation, excitement, etc.).

[1288] Step 8:

[1289] The server generates customized notification content based on the analysis results of the emotion engine. For example, if the user is stressed, it creates a concise and positive notification; if they are relaxed, it creates a notification that includes detailed release notes and recommended actions.

[1290] Step 9:

[1291] When the server detects new update information, it sends a notification to the user. Customized notifications, reflecting the results of the sentiment engine, are sent via email or push notification. For example, an email like the following might be sent:

[1292] For users experiencing high stress levels: "A new version, 2.0.1, has been released. Login issues have been fixed, and dark mode has been added."

[1293] For relaxed users: An email with a link saying, "A new version 2.0.1 has been released. Click here for detailed release notes."

[1294] As described above, the system automatically collects, analyzes, and stores product update information, and uses an emotion engine to notify users in the most optimal way. This improves the user experience.

[1295] (Example 2)

[1296] 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".

[1297] Traditional systems had problems with effectively managing and notifying users of product updates, requiring a lot of effort, and failing to provide appropriate notifications based on user sentiment. The difficulty in providing customized notifications tailored to user needs and circumstances resulted in a degraded user experience.

[1298] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for periodically collecting update information from multiple data sources on the internet, means for analyzing the collected update information and converting it into a standardized data format, means for storing the converted data in a database, means for analyzing the user's emotions using an emotion engine and customizing notification content based on the analysis results, and means for notifying the user when new update information is added. This enables automatic management of product update information and customized notifications based on emotions.

[1299] A "data source" is an information source that provides updated information about products on the internet.

[1300] "Update information" refers to information that indicates changes to a product, such as version upgrades, feature additions, and bug fixes.

[1301] "Analysis" refers to the process of breaking down collected update information, extracting important elements, and understanding them.

[1302] A "standardized data format" is a format that enhances data consistency and compatibility by converting analyzed information into a consistent format.

[1303] A "database" is a place to store and manage analyzed data for the long term.

[1304] A "document format" refers to the format of visual materials (such as presentation slides or spreadsheets) used to visually organize information and make it easier to understand.

[1305] An "emotion engine" is an algorithm or system that analyzes user feedback and usage history to estimate their emotional state.

[1306] "Customizing notification content" means adjusting and optimizing the content of update notifications according to the user's emotional state.

[1307] This invention relates to a system that automatically collects and analyzes product update information, generates related documents, and further recognizes user emotions to adjust notification content. Specifically, it periodically collects update information, converts it into a standardized data format, stores it in a database, and generates output in cloud-based presentation or spreadsheet format. It also uses an emotion engine to provide customized notifications based on user emotions.

[1308] First, the server collects product update information from multiple data sources based on a schedule, using API endpoints and web scraping. For example, it sends an HTTP request to the API endpoint for product A, https: / / api.example.com / productA / updates, and receives JSON data as a response. HTTP GET requests and scraping tools are used as collection methods.

[1309] The collected data is parsed by the server, and important information is extracted using natural language processing (NLP) algorithms. For example, information such as the version number "2.0.1" and changes such as "fixed login issue" and "added dark mode" is extracted. This information is converted into a standardized data format (e.g., JSON format) and stored in the database as a unified format.

[1310] Based on the information stored in the database, the server generates cloud-based presentations (such as Google Slides) or spreadsheets. Using the Google Slides API, a new presentation is generated and the update details are inserted into it. The generated slides will have the title "Product A Version 2.0.1 Update" and each slide will contain information such as "1. Fixed login issue" and "2. Added dark mode".

[1311] Next, user feedback and usage history are analyzed by the emotion engine. The emotion engine estimates the user's emotions from facial expressions, voice, and text data, and stores the results. This allows the system to determine whether the user is stressed or relaxed.

[1312] Based on the analysis results, the server generates customized notifications tailored to the user's emotions. For example, if the user is stressed, the notification will be concise and use positive language. Conversely, if the user is relaxed, the notification will also include detailed changes and recommended actions. This process improves the user experience and ensures that necessary information is effectively communicated.

[1313] Finally, when new update information is detected, the server sends a customized notification to the user that reflects the results of the sentiment engine. The notification can be sent via email or push notification, and a specific example would be a concise message such as, "New version 2.0.1 has been released. Login issues have been fixed and dark mode has been added."

[1314] An example of a prompt message is input to the generating AI model in the following format:

[1315] "A new version 2.0.1 of Product A has been released. This version includes 'Login issue fix' and 'Dark Mode added.' Please generate sentiment-based notifications for users regarding these changes."

[1316] This invention automates the management of product update information and notifications to users, and further enhances the user experience by providing optimal notifications tailored to the user's emotions.

[1317] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1318] Step 1:

[1319] The server periodically collects update information from multiple data sources on the internet. Inputs include a schedule and the URLs of the data sources (e.g., https: / / api.example.com / productA / updates). Based on this, the server sends an HTTP GET request and receives update information in JSON format as a response. Specifically, it sends a request to the URL of product A and retrieves JSON data containing the version number and changes.

[1320] Step 2:

[1321] The server parses and analyzes the collected JSON data. The input is the acquired JSON data. The server uses natural language processing (NLP) algorithms to analyze the data and extract important information (e.g., version number, changes). Specifically, it extracts the keys "version" and "changes" from the JSON and retrieves their respective values. This data is then converted into a unified format.

[1322] Step 3:

[1323] The server stores the parsed and transformed data in a database. The input is a standardized data format (e.g., transformed JSON data). The server compares it with existing data and updates or adds new information if necessary. Specifically, it checks the entry for product A in the database and updates it if the version information and changes are new.

[1324] Step 4:

[1325] The server generates cloud-based presentations and spreadsheets based on information in the database. The input includes information stored in the database (e.g., version numbers and changes). The server uses the Google Slides API to generate a new presentation and insert the update details into it. Specifically, it creates a title slide such as "Product A Version 2.0.1 Update" and places the changes on each slide.

[1326] Step 5:

[1327] The server analyzes user feedback and usage history using an emotion engine. Input includes user feedback data and usage history data. The server uses the emotion engine to analyze this data and estimate the user's emotional state (e.g., stress, relaxation). Specifically, it identifies emotions from voice and text data and stores the results.

[1328] Step 6:

[1329] The server generates customized notifications based on the user's emotions, using the results of the emotion engine's analysis. Inputs include the emotion analysis results and update information from the database. The server adjusts the notification content according to each user's emotional state. Specifically, it creates concise notifications for stressed users and detailed notifications for relaxed users.

[1330] Step 7:

[1331] When the server detects new update information, it sends a notification to the user. The input is a customized notification message. The server sends the notification to the user using methods such as email or push notifications. Specifically, the notification might be in the format of, "New version 2.0.1 has been released. Login issues have been fixed and dark mode has been added."

[1332] In this way, the automatic collection, analysis, database management, document generation, and user notification of product update information are all realized in a single, streamlined process.

[1333] (Application Example 2)

[1334] 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".

[1335] Traditional update notification systems often simply relay collected information to users without considering their current emotional state or feedback, resulting in a lack of improved user experience. Furthermore, this could lead to users receiving unnecessary information, potentially causing stress. Additionally, important changes might be overlooked, leading to a lack of understanding of the update content.

[1336] 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 periodically collecting update information from multiple data sources on the internet, means for analyzing the collected update information and converting it into a standardized data format, means for storing the converted data in a database, means for automatically generating a document format (including slides or spreadsheets) based on the stored data, means for analyzing the user's emotions based on user feedback and usage history, means for customizing update notifications according to the user's emotions, and means for sending customized notifications to the user when new update information is added. This makes it possible to appropriately provide information according to the user's emotional state and to appropriately notify them without missing important information.

[1337] "Means of collecting update information from multiple data sources on the internet on a regular basis" refers to a function that automatically retrieves software and service update information from multiple websites and APIs based on a schedule set via the internet.

[1338] "Means for analyzing collected update information and converting it into a standardized data format" refers to a function that analyzes acquired update information using natural language processing and data analysis techniques and formats it into a unified format.

[1339] "Means of storing converted data in a database" refers to a function that stores analyzed and standardized data in a database so that it can be searched and referenced later.

[1340] "Means for automatically generating document formats (including slides or spreadsheets) based on saved data" refers to a function that automatically creates visual documents such as presentation slides and spreadsheets using information stored in a database.

[1341] "Means of analyzing user emotions based on user feedback and usage history" refers to a function that collects user input and operation history and uses an emotion analysis algorithm to estimate the user's current emotional state based on this data.

[1342] "Means of customizing update notifications according to user emotions" refers to a function that takes into account the analyzed emotional state of the user and modifies the notification content or presents it in a specific way to provide information in the most optimal format for the user.

[1343] "Means of sending customized notifications to users when new update information is added" refers to a function that sends a pre-customized notification message to users via email or push notification when new update information is added to the system.

[1344] This invention can be implemented by coordinating several system components and programs. The specific method is described below.

[1345] The server periodically collects update information from multiple data sources on the internet. This can be done using techniques such as Web APIs and Web scraping. For example, to collect the latest update information for product A, an HTTP request is sent to a specified API endpoint, and JSON data is received as a response. Since this collected data is difficult to use directly, it is analyzed using natural language processing (NLP) techniques and converted into a standardized data format. The analyzed data is then formatted into a unified format and stored in a database. Cloud services such as Amazon RDS and Google Cloud Firestore can be used for the database.

[1346] Next, a document format (slides or spreadsheet) is automatically generated based on this saved data. This can be achieved using cloud-based presentation tools such as the "Google Slides API" or "Google Sheets API". For example, based on the update information for the new version 2.0.1, a presentation titled "Product A Version 2.0.1 Update" is created in Google Slides, and information such as "Login problem fixed" and "Dark mode added" is inserted into its content.

[1347] Furthermore, user feedback and usage history are analyzed using an emotion engine. In this case, emotion analysis engines such as "Amazon Rekognition," "Google Cloud Vision," and "Microsoft Azure Face API" can be used to analyze the user's facial expressions, voice, and text data to estimate their emotional state. For example, if a user writes "It's become easier to use" in their feedback, the feedback text is analyzed using NLP technology to determine that the emotion is "positive."

[1348] Update notifications are customized based on the user's sentiment. If the sentiment is positive, a detailed notification is applied, such as "A new version 2.0.1 has been released. See the detailed release notes here." Conversely, if the sentiment is negative, a concise notification is sent, such as "A new version 2.0.1 has been released. Login issues have been fixed and dark mode has been added." This customized notification is sent to the user via email or push notification. Email services such as "Amazon SES" and "SendGrid" or "Firebase Cloud Messaging (FCM)" can be used.

[1349] For example, suppose user A is using the "EmotionPay" app and receives a notification about the latest update. The system first analyzes the user's feedback with its emotion engine and detects positive emotions. As a result, the system chooses to send a detailed notification, and user A receives a notification stating, "A new version 2.0.1 has been released. Click here for detailed release notes."

[1350] An example of a prompt statement is as follows:

[1351] "As an EmotionPay user, you will receive a notification when the latest version 2.0.1 is released. Based on your feedback and sentiment analysis, the notification will be customized and will determine whether or not it includes detailed release notes. Please write 'Positive' or 'Negative' in your feedback."

[1352] In this way, this invention can provide appropriate information according to the user's emotional state and improve the user experience.

[1353] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1354] Step 1:

[1355] The server periodically collects update information from multiple data sources on the internet. This is done by sending HTTP requests to API endpoints and websites according to a pre-configured schedule. As a result, data in JSON format is returned as a response. The input is the URL of the API endpoint or website, and the output is the collected update information in JSON format.

[1356] Step 2:

[1357] The server analyzes the collected update information and converts it into a standardized data format. This is done by parsing the acquired JSON data, using natural language processing (NLP) techniques to extract important information (e.g., version number and changes), and converting it into a unified format. The input is the collected JSON data, and the output is a standardized data format. Specifically, the system uses Python's json module to import data and then analyzes it using NLP libraries such as spaCy or NLTK.

[1358] Step 3:

[1359] The server stores the transformed data in a database. This is a process that uses a database connection module to parse and standardize the data, store it in the database, and update or add any new information by comparing it with existing data. The input is a standardized data format, and the output is the data stored in the database. Specifically, SQL queries are used to insert and update data in the database.

[1360] Step 4:

[1361] The server automatically generates document formats (slides or spreadsheets) based on the stored data. This is a process of creating automatically generated documents using cloud-based presentation tools such as the Google Slides API and the Google Sheets API. The input is update information stored in the database, and the output is the generated presentation or spreadsheet. Specifically, a new document is generated using the Google API client, and the update information is inserted.

[1362] Step 5:

[1363] The server analyzes user sentiment based on user feedback and usage history. This process involves processing user feedback text and usage history data using a sentiment analysis engine (e.g., Amazon Rekognition, Google Cloud Vision, Microsoft Azure Face API) to estimate the user's sentiment. The input is user feedback and usage history data, and the output is the analyzed sentiment data. Specifically, the server calls the sentiment analysis API and saves the results to a database.

[1364] Step 6:

[1365] The server customizes update notifications based on the user's emotions. This is a process that modifies the notification content based on the emotion analysis results. For example, if the emotion is "positive," a detailed notification is created, and if the emotion is "negative," a concise notification is created. The input is the emotion analysis result, and the output is the customized notification message. Specifically, multiple notification templates are prepared, and the appropriate template is selected according to the emotion analysis result.

[1366] Step 7:

[1367] The server sends customized notifications to users when new update information is added. This is done, for example, via email or push notifications. The input is the customized notification message, and the output is the notification sent to the user. Specifically, the server calls a notification service (e.g., Amazon SES, SendGrid, Firebase Cloud Messaging (FCM)) to send the notification message.

[1368] 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.

[1369] 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.

[1370] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1371] 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.

[1372] 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.

[1373] 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.

[1374] 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.

[1375] 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.

[1376] 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."

[1377] 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.

[1378] 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.

[1379] 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.

[1380] 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.

[1381] 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.

[1382] 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.

[1383] 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.

[1384] 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.

[1385] 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.

[1386] 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.

[1387] 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.

[1388] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[1389] The following is further disclosed regarding the embodiments described above.

[1390] (Claim 1)

[1391] A means of regularly collecting update information from multiple data sources on the internet,

[1392] A means of analyzing the collected update information and converting it into a standardized data format,

[1393] A means of saving the converted data to a database,

[1394] A means for automatically generating a document format (including slides or spreadsheets) based on saved data,

[1395] A system that includes a means of notifying users when new update information is added.

[1396] (Claim 2)

[1397] The system according to claim 1, wherein the aforementioned document format is generated using cloud-based presentation and spreadsheet services.

[1398] (Claim 3)

[1399] The system according to claim 1, wherein the collection means uses API requests or web scraping.

[1400] "Example 1"

[1401] (Claim 1)

[1402] A means of periodically collecting change information from multiple data sources on an information network,

[1403] A means for analyzing the collected change information and converting it into a standardized data format,

[1404] A means for storing the converted data in a storage device,

[1405] A means for automatically generating a document format (including display materials or calculation tables) based on saved data,

[1406] A means of notifying users when new changes are added,

[1407] Means for setting up a regular schedule,

[1408] A means of analyzing the collected data using natural language processing technology,

[1409] A method for creating the generated document format using a cloud service,

[1410] A system that includes methods of notification such as email and push notifications.

[1411] (Claim 2)

[1412] The system according to claim 1, wherein the aforementioned document format is generated using cloud-based presentation and spreadsheet services.

[1413] (Claim 3)

[1414] The system according to claim 1, wherein the collection means uses a response request or site information extraction technique.

[1415] "Application Example 1"

[1416] (Claim 1)

[1417] A means of regularly collecting update information from multiple data sources on the internet,

[1418] A means of analyzing the collected update information and converting it into a standardized data format,

[1419] A means of saving the converted data to a database,

[1420] A means for automatically generating a document format (including slides or spreadsheets) based on saved data,

[1421] A means of notifying users when new update information is added,

[1422] A means for analyzing product update information and generating information to be displayed on a smart device,

[1423] A means of providing information to staff based on updates to the products,

[1424] A system including means for generating and displaying cloud-based presentations or spreadsheet formations.

[1425] (Claim 2)

[1426] The system according to claim 1, generated using cloud-based presentation and spreadsheet services.

[1427] (Claim 3)

[1428] The system according to claim 1, wherein the means of collection is an API request or web scraping.

[1429] "Example 2 of combining an emotion engine"

[1430] (Claim 1)

[1431] A means of regularly collecting update information from multiple data sources on the internet,

[1432] A means of analyzing the collected update information and converting it into a standardized data format,

[1433] A means of saving the converted data to a database,

[1434] A means for automatically generating a document format (including slides or spreadsheets) based on saved data,

[1435] A means of analyzing user emotions using an emotion engine and customizing notification content based on the analysis results,

[1436] A system that includes a means of notifying users when new update information is added.

[1437] (Claim 2)

[1438] The system according to claim 1, wherein the aforementioned document format is generated using cloud-based presentation and spreadsheet services.

[1439] (Claim 3)

[1440] The system according to claim 1, wherein the collection means uses API requests or web scraping.

[1441] "Application example 2 when combining with an emotional engine"

[1442] (Claim 1)

[1443] A means of regularly collecting update information from multiple data sources on the internet,

[1444] A means of analyzing the collected update information and converting it into a standardized data format,

[1445] A means of saving the converted data to a database,

[1446] A means for automatically generating a document format (including slides or spreadsheets) based on saved data,

[1447] A means of analyzing user sentiment based on user feedback and usage history,

[1448] A means to customize update notifications according to the user's emotions,

[1449] A system that includes means of sending customized notifications to users when new update information is added.

[1450] (Claim 2)

[1451] The system according to claim 1, wherein the aforementioned document format is generated using cloud-based presentation and spreadsheet services.

[1452] (Claim 3)

[1453] The system according to claim 1, wherein the collection means uses API requests or web scraping. [Explanation of symbols]

[1454] 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 regularly collecting update information from multiple data sources on the internet, A means of analyzing the collected update information and converting it into a standardized data format, A means of saving the converted data to a database, A means for automatically generating a document format (including slides or spreadsheets) based on saved data, A system that includes a means of notifying users when new update information is added.

2. The system according to claim 1, wherein the aforementioned document format is generated using cloud-based presentation and spreadsheet services.

3. The system according to claim 1, wherein the collection means uses API requests or web scraping.

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