system

Abstract

Provide a system. 【Solution means】 Means for a user to input a specific keyword, Means for generating a search query based on the keyword, Means for collecting relevant press release information from multiple information sources on the Internet using the generated search query, Means for filtering the collected information and extracting press release information that matches the keyword, Means for sorting the extracted information and categorizing it by company, local government, and release date, Means for exporting the sorted information in spreadsheet format, Means for generating graphs such as bar graphs, pie charts, and line graphs according to the user's request, A system including.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Currently, many companies and local governments spend a great deal of time and effort in collecting press release information and analyzing the trends of competing companies and local governments. In particular, since there is no established method for efficiently collecting and organizing information related to a specific theme (e.g., workcation), information is likely to be overlooked or duplicated. In addition, the work of organizing and visualizing the collected information and compiling it into analysis materials also relies heavily on manual work, which hinders the efficiency of proposal writing and proposal activities. As a result, there is a need for a system that can achieve rapid information collection and organization.

Means for Solving the Problems

[0005] The present invention provides a system that includes means for a user to input specific keywords, means for generating a search query based on the keywords, means for collecting relevant press release information from multiple sources on the internet using the generated search query, means for filtering the collected information and extracting press release information that matches the keywords, means for organizing the extracted information and categorizing it by company, local government, and announcement date, means for exporting the organized information in spreadsheet format, and means for generating graphs such as bar graphs, pie charts, and line graphs according to the user's request. This system automates information collection and organization and provides data that is easy to analyze visually, thereby supporting efficient proposal creation and presentation activities.

[0006] A "user" is an individual or group that operates the system.

[0007] A "keyword" is a word or phrase that a user enters to search for specific information.

[0008] A "search query" is a string of characters used to search for information on the internet, and is a search instruction generated based on keywords.

[0009] "Information sources" refer to websites and databases that provide press release information, including news sites, company websites, and local government websites.

[0010] "Press release information" refers to news, events, and project information officially announced by companies or local governments.

[0011] "Web scraping" is a technique for automatically extracting specific information from websites.

[0012] "Filtering" is the process of extracting only the necessary information from collected data and removing unnecessary information.

[0013] "Categorization" refers to classifying extracted information based on specific criteria, such as by company, by local government, or by publication date.

[0014] A "spreadsheet format" is a file format that saves organized data in a table format, and includes formats such as .csv and .xlsx.

[0015] A "graph" is a diagram used to visually represent data, and includes bar graphs, pie charts, line graphs, and other types of graphs.

[0016] "Visualization" is the process of displaying data in a visually understandable way.

[0017] A "project proposal" is a document that summarizes a specific project or proposal.

[0018] "Proposal activities" refer to the work of presenting plans or ideas in order to achieve a specific objective. [Brief explanation of the drawing]

[0019] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0020] 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.

[0021] First, the terms used in the following description will be described.

[0022] In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0023] 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.

[0024] 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.

[0025] 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).

[0026] 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."

[0027] [First Embodiment]

[0028] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0029] 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.

[0030] 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).

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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".

[0040] The system of the present invention allows a user to input specific keywords, generates a search query based on those keywords, and collects, organizes, and visualizes relevant press release information from multiple sources on the internet.

[0041] Program Overview

[0042] User actions

[0043] The user accesses the system using a terminal and enters specific keywords (e.g., "press release," "workation," "local government").

[0044] Generating search queries

[0045] The terminal generates a search query based on the entered keywords. This search query consists of AND searches and specified formats. For example, it might be generated as "Press release AND Workation AND Local government".

[0046] Data collection

[0047] The server uses the generated search query to scrape relevant press release information from multiple specified sources (news sites, company websites, local government websites, etc.). During scraping, it analyzes the HTML structure of each website and extracts the necessary data (title, publication date, body text, etc.).

[0048] Data filtering

[0049] The server filters the collected information and extracts press releases that match the user's keywords. This filtering includes evaluating keyword relevance and eliminating duplicate information.

[0050] Data organization

[0051] The server organizes the filtered data. This organization process categorizes the information by company, local government, and publication date. For example, press releases from a particular local government on a specific date might be grouped into a single category.

[0052] Data output and visualization

[0053] The terminal exports the organized data received from the server in spreadsheet format (.csv or .xlsx). It also generates various graphs (bar graphs, pie charts, line graphs, etc.) upon user request, visually displaying the data.

[0054] Specific example

[0055] User actions

[0056] The user enters the keywords "press release workation local government" into the system.

[0057] Generating search queries

[0058] The device generates a search query: "Press release AND workation AND local government".

[0059] Data collection

[0060] The server uses this search query to collect press release information from news sites and official websites. For example, the server retrieves the following information:

[0061] Local government: Tokyo Metropolitan Government

[0062] Title: Announcement of Workation Promotion

[0063] Announcement date: April 1, 2023

[0064] Data filtering

[0065] The server extracts only the information containing all of the following: "press release," "workation," and "local government." Duplicate information is also removed.

[0066] Data organization

[0067] The server organizes the filtered data by prefecture and classifies it into categories such as "Tokyo," "April 1, 2023," and "Announcement of Workation Promotion."

[0068] Data output and visualization

[0069] The device exports the organized data in spreadsheet format. It also displays the number of workation promotion projects for each municipality as a bar graph.

[0070] Thus, the system of the present invention automates the entire process from information gathering to organization and visualization, supporting users in efficiently creating project proposals and presentation materials.

[0071] The following describes the processing flow.

[0072] Step 1:

[0073] The user enters specific keywords using their device. For example, they might enter "press release workation local government".

[0074] Step 2:

[0075] The terminal generates a search query based on the entered keywords. It is structured in the form of "Press release AND Workation AND Local government".

[0076] Step 3:

[0077] The server uses a generated search query to scrape relevant press release information from multiple specified sources. Information is retrieved from news sites, company websites, and local government websites.

[0078] Step 4:

[0079] The server analyzes the information collected via scraping, extracting the title, publication date, and text from the document. It also analyzes the HTML structure to extract the necessary data.

[0080] Step 5:

[0081] The server filters the collected information. It extracts only information that includes all of the following: "press releases," "workation," and "local government," eliminating unnecessary information and spam.

[0082] Step 6:

[0083] The server organizes the filtered information. The information is categorized by company, local government, and publication date. For example, press releases from Tokyo on April 1, 2023, are grouped into a single category.

[0084] Step 7:

[0085] The server eliminates duplicate press release information. If the same press release is collected multiple times, it combines them into one and removes the duplicates.

[0086] Step 8:

[0087] The terminal exports the organized data received from the server in spreadsheet format (.csv or .xlsx). This allows the user to download and use it.

[0088] Step 9:

[0089] The device generates various graphs (bar graphs, pie charts, line graphs, etc.) in response to user requests, visually displaying data. For example, it can display the number of announced workation projects per month as a bar graph.

[0090] Step 10:

[0091] Users create project proposals and presentation materials based on exported data and generated graphs. They utilize the data to analyze the trends of competitors and local governments and make effective proposals.

[0092] (Example 1)

[0093] 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."

[0094] Traditional information gathering systems struggled to efficiently collect, organize, and visualize information related to specific keywords from multiple sources on the internet, requiring users to expend considerable time and effort. Furthermore, the elimination of duplicate information and data visualization were not automated, necessitating manual processing.

[0095] 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.

[0096] In this invention, the server includes means for a user to input a specific keyword, means for generating a search query based on the keyword, means for collecting relevant information from multiple information sources on the internet using the generated search query, means for filtering the collected information and extracting information that matches the keyword, means for organizing the extracted information and categorizing it by organization, administrative division, and date and time, means for exporting the organized information in spreadsheet software format, and means for generating charts and graphs according to the user's request. This automates a series of tasks from information collection to organization and visualization, enabling the user to efficiently obtain the necessary information.

[0097] "User" refers to a person who uses this system.

[0098] A "keyword" refers to a specific word or phrase that a user enters to search for information.

[0099] A "search query" refers to a string of characters that represents a specific command to search for information from internet sources, generated based on keywords.

[0100] "Information source" refers to a place where information exists, such as websites or databases on the internet.

[0101] "Filtering" refers to the process of selecting information that matches specific criteria from collected data.

[0102] "Categorization" refers to classifying collected and filtered information based on specific criteria (e.g., organization, administrative division, date and time).

[0103] "Spreadsheet format" refers to a format for electronically managing and analyzing information (e.g., .csv or .xlsx).

[0104] "Charts and graphs" refer to graphs and charts (e.g., bar graphs, pie charts, line graphs) used to visually represent data.

[0105] The system of the present invention enables efficient information collection, organization, and visualization through a complex configuration including users, terminals, and servers.

[0106] System Configuration

[0107] User actions

[0108] The user accesses the system using a device (e.g., a PC or smartphone) and enters specific keywords (e.g., "press release," "workation," "local government"). The device uses an input device such as a keyboard or touchscreen.

[0109] Generating search queries

[0110] The device retrieves the keywords entered by the user and converts them into an AND search query. This query is generated in the format of "press release AND workation AND local government".

[0111] Start of data collection

[0112] The server receives the generated search query and initiates access to the specified information sources (such as news sites, company websites, and local government websites). In this process, the server refers to a list of URLs for each information source and uses the search query to extract relevant information.

[0113] scraping

[0114] The server uses the Python BeautifulSoup library to parse the HTML of each information source and extract necessary data such as "title," "publication date," and "body text."

[0115] Specifically, the following information will be obtained:

[0116] Local government: Tokyo Metropolitan Government

[0117] Title: Announcement of Workation Promotion

[0118] Announcement date: April 1, 2023

[0119] Data filtering

[0120] The server filters the retrieved data. Here, it extracts only the information that exactly matches the search query and eliminates duplicate data.

[0121] Data organization

[0122] The server organizes the filtered data. The organized data is then categorized by organization, administrative division, and date. For example, the server creates categories such as "Tokyo Metropolitan Government," "April 1, 2023," and "Announcement of Workation Promotion," and groups related data together.

[0123] Data Output

[0124] The server sends the organized data to the terminal, and the terminal provides a function to export it in spreadsheet format (.csv or .xlsx).

[0125] Visualization

[0126] The device visualizes organized data according to user requests. It generates and displays bar graphs, pie charts, line graphs, and other visual representations. For example, it can display the number of workation promotion projects for each municipality as a bar graph.

[0127] Example of a prompt

[0128] "Design a system that collects, organizes, and visualizes press release information from multiple online sources based on a specific keyword input. Explain the entire process, from generating search queries based on the user's keywords, to collecting and filtering data from the sources, and finally organizing and visualizing the data."

[0129] Thus, the system of the present invention automatically collects, organizes, and visualizes relevant information simply by the user entering specific keywords, enabling the user to efficiently acquire and utilize the necessary information.

[0130] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0131] Step 1:

[0132] The user accesses the system using a terminal and enters a specific keyword.

[0133] Input: Specific keywords (e.g., "press release", "workation", "local government")

[0134] Output: Set of entered keywords

[0135] Specific action: The user enters a keyword into the text box and presses the "Search" button.

[0136] Step 2:

[0137] The terminal retrieves the entered keyword and generates a search query based on it.

[0138] Input: A set of keywords entered by the user.

[0139] Output: Search query (Example: "Press release AND workation AND local government")

[0140] Specific operation: The terminal converts the entered keyword into a string in AND search format.

[0141] Step 3:

[0142] The server receives the generated search query and initiates access to the specified information source.

[0143] Input: Generated search query, list of URLs for the source.

[0144] Output: HTML data to be collected

[0145] Specific operation: The server visits the URLs of each information source and retrieves the HTML data of the pages that match the search query.

[0146] Step 4:

[0147] The server performs scraping by analyzing the HTML of each information source and extracting the necessary data.

[0148] Input: HTML data to be collected

[0149] Output: Extracted information (e.g., "Title", "Publication Date", "Text")

[0150] Specific operation: The server uses the Python BeautifulSoup library to extract the title, publication date, and body text from the HTML.

[0151] Step 5:

[0152] The server filters the retrieved data, extracting only the information that exactly matches the search query.

[0153] Input: Set of extracted information

[0154] Output: Set of filtered information

[0155] Specific operation: The server evaluates the degree of matching with the search query and eliminates mismatched or duplicate information.

[0156] Step 6:

[0157] The server organizes the filtered data and classifies it by organization, administrative division, and date / time.

[0158] Input: A set of filtered information

[0159] Output: Set of classified information

[0160] Specific operation: The server categorizes data based on specific criteria and registers it in the database.

[0161] Step 7:

[0162] The server sends the organized data to the terminal, which then exports it in spreadsheet format.

[0163] Input: Set of classified information

[0164] Output: Spreadsheet file format (.csv or .xlsx)

[0165] Specific operation: The server sends the classified data to the terminal in JSON format, and the terminal converts and exports it in CSV or XLSX format.

[0166] Step 8:

[0167] The device visualizes organized data in response to user requests.

[0168] Input: Set of classified information

[0169] Output: Visualized data (e.g., bar graph, pie chart, line graph)

[0170] Specific operation: If the user requests data visualization, the device uses a visualization library to generate a graph and display it on the screen.

[0171] (Application Example 1)

[0172] 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."

[0173] Traditional information gathering systems required users to manually search for specific information and verify related information one by one from numerous sources, which presented significant challenges in terms of effort and time. Furthermore, organizing and visualizing the collected information was also done manually, resulting in problems such as data duplication and redundancy. In advertising operations in particular, timely information gathering and analysis are crucial, and an efficient system for this purpose was needed.

[0174] 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.

[0175] In this invention, the server includes means for a user to input a specific keyword, means for generating a search query based on the keyword, means for collecting relevant information from multiple information sources on the internet using the generated search query, means for filtering the collected information and extracting information that matches the keyword, means for organizing the extracted information and categorizing it by organization and presentation time, means for exporting the organized information in a calculation processing table format, means for generating data visualizations such as bar graphs, pie charts, and line graphs in response to the user's request, and means for inputting the generated graph information as prompt text into a generation AI model for further detailed analysis. This enables users to efficiently collect, organize, and visualize information, particularly enabling timely information analysis and strategic planning in advertising operations.

[0176] A "user" is an individual or group that uses the system to search for and analyze specific information.

[0177] A "keyword" is a word or phrase that a user enters when searching for specific information.

[0178] A "search query" is a search command generated based on keywords to retrieve specific information.

[0179] "Information sources" refer to websites and databases where information is publicly available, such as news portals, official organizations' websites, and public databases.

[0180] "Filtering" is the process of removing duplicate information from collected data and extracting information that matches keywords.

[0181] "Categorization" is the process of classifying extracted information based on specific criteria (for example, by organization, by presentation time).

[0182] A "calculation processing table" is a tabular document, such as Excel or CSV, used to organize and visually display data.

[0183] "Data visualization" is the process of visually displaying collected data in formats such as bar graphs, pie charts, and line graphs.

[0184] A "prompt statement" is a set of instructions given to a generating AI model for analysis and processing.

[0185] A "generative AI model" is a computer program that uses artificial intelligence technology to perform advanced analysis and processing based on input prompt sentences.

[0186]

[0187] The present invention is implemented as an information gathering and analysis system. This system has the function of allowing a user to input specific keywords, generating search queries based on those keywords, and collecting, organizing, and visualizing relevant information from multiple sources on the internet.

[0188] First, the user accesses the system using a terminal and enters specific keywords (e.g., "new product announcement," "campaign," "social media"). The terminal generates a search query based on the entered keywords. This search query consists of AND searches and a specified format. For example, it might be generated as "new product announcement AND campaign AND social media."

[0189] Next, the server uses the generated search query to collect information from multiple sources on the internet (news portals, official organization websites, public databases, etc.). During collection, the server analyzes the HTML structure of each website and extracts the necessary data (title, publication date, content, etc.).

[0190] The extracted information is filtered to extract only the information that matches the keywords and eliminate duplicate information. Then, the filtered data is organized and categorized by organization and presentation time.

[0191] The organized information can be exported as a calculation processing table (.csv or .xlsx format) upon user request. The data can also be visualized using bar graphs, pie charts, line graphs, and other methods. Furthermore, the generated graph information is input into the AI ​​model as prompt text for more detailed analysis.

[0192] The hardware used includes common PCs and smartphones, and the software used includes Python 3.x, BeautifulSoup, requests, Pandas, and Matplotlib. Python 3.x is used as the overall program framework, BeautifulSoup is used for HTML parsing, requests for web requests, Pandas for data frame manipulation, and Matplotlib for data visualization.

[0193] As a concrete example, consider a case where an advertising agency representative enters the keywords "new product launch campaign social media" into the app. In this case, the server collects relevant campaign information from news portals and the organization's official website, and then organizes and filters it. As a result, data containing information such as "a certain organization new product launch campaign (October 1, 2023)" is organized and output as a report in PDF or CSV format.

[0194] As an example of a prompt, the following can be entered into the generative AI model:

[0195] "Users enter keywords such as 'new product launch campaign social media,' and the system collects, filters, organizes, and visualizes relevant information, displaying it in spreadsheet and graph formats."

[0196] Thus, the system of the present invention enables users to efficiently collect, organize, and visualize information, and in particular, enables timely information analysis and strategic planning in advertising operations.

[0197] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0198] Step 1:

[0199] A user accesses the system using a terminal and enters specific keywords. These keywords may include multiple words or phrases, such as "new product announcement," "campaign," or "social media." The input data consists of these keywords, which are then passed to the search query generation phase as output.

[0200] Step 2:

[0201] The terminal generates a search query based on the entered keywords. This search query is composed of AND searches or specified formats, such as "New product announcement AND campaign AND social media". The input data is the keywords, and the output data is the generated search query.

[0202] Step 3:

[0203] The server uses the generated search query to collect information from multiple sources on the internet. Specifically, it retrieves HTML data from news portals, official organizational websites, public databases, etc., and parses the HTML structure using BeautifulSoup. The input data is the search query, and the output data is the collected HTML data.

[0204] Step 4:

[0205] The server filters the collected information. Specifically, it organizes it as a data frame using Pandas, extracts only the information that matches the keywords, and eliminates duplicate information. The input data is HTML data, and the output data is the filtered information.

[0206] Step 5:

[0207] The server organizes the filtered information and categorizes it by organization and presentation time. This makes it easier for users to view information according to specific criteria. The input data is filtered information, and the output data is categorized information.

[0208] Step 6:

[0209] The terminal exports the organized information as a calculation spreadsheet (.csv or .xlsx format) upon user request. The input data is categorized information, and the output data is a spreadsheet file.

[0210] Step 7:

[0211] The terminal also generates data visualizations such as bar graphs, pie charts, and line graphs in response to user requests. It uses Matplotlib to visually display the data. The input data is categorized information, and the output data is visualized data in graph format.

[0212] Step 8:

[0213] The terminal inputs the generated graph information as a prompt into the generating AI model for further detailed analysis. The input data is graph information, and the output data is the AI ​​analysis result. For example, the prompt "The user enters the keywords 'new product announcement campaign social media', and the AI ​​model should collect, filter, organize, and visualize the relevant information and display it in spreadsheet and graph format." is input into the generating AI model.

[0214] 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.

[0215] The present invention is a system that allows a user to input specific keywords, generates search queries based on those keywords, and collects, organizes, and visualizes relevant press release information from multiple sources on the internet. Furthermore, it includes a function to recognize the user's emotions and perform actions based on those emotions.

[0216] Program Overview

[0217] User actions

[0218] The user accesses the system using a terminal and enters specific keywords (e.g., "press release," "workation," "local government").

[0219] Generating search queries

[0220] The terminal generates a search query based on the entered keywords. This search query consists of AND searches and specified formats. For example, it might be generated as "Press release AND Workation AND Local government".

[0221] Data collection

[0222] The server uses the generated search query to scrape relevant press release information from multiple specified sources (news sites, company websites, local government websites, etc.). During scraping, it analyzes the HTML structure of each website and extracts the necessary data (title, publication date, body text, etc.).

[0223] Data filtering

[0224] The server filters the collected information and extracts press releases that match the user's keywords. This filtering includes evaluating keyword relevance and eliminating duplicate information.

[0225] Data organization

[0226] The server organizes the filtered data. This organization process categorizes the information by company, local government, and publication date. For example, press releases from a particular local government on a specific date might be grouped into a single category.

[0227] Data output and visualization

[0228] The terminal exports the organized data received from the server in spreadsheet format (.csv or .xlsx). It also generates various graphs (bar graphs, pie charts, line graphs, etc.) upon user request, visually displaying the data.

[0229] Embedding an emotion engine

[0230] emotion recognition

[0231] The emotion engine analyzes the user's emotions based on keywords entered, operation history, language used, and operation speed. Using emotion analysis technology, it recognizes whether the user is excited, calm, or stressed.

[0232] Prioritizing search results based on emotions

[0233] The server dynamically adjusts the priority of search results based on the perceived emotions of the user. For example, if the user is feeling stressed, it prioritizes displaying simpler and more intuitive search results.

[0234] Recommendations for proposal materials based on emotions

[0235] The emotion engine recommends the structure of proposals and project plans based on the user's emotions. For example, if the user is excited, it will recommend more detailed and specific materials, while if the user is calm, it will recommend concise and to the point.

[0236] Specific example

[0237] User actions

[0238] The user enters the keywords "press release workation local government" into the system.

[0239] Generating search queries

[0240] The device generates a search query: "Press release AND workation AND local government".

[0241] Data collection

[0242] The server uses this search query to collect press release information from news sites and official websites. For example, the server retrieves the following information:

[0243] Local government: Tokyo Metropolitan Government

[0244] Title: Announcement of Workation Promotion

[0245] Announcement date: April 1, 2023

[0246] Data filtering

[0247] The server extracts only the information containing all of the following: "press release," "workation," and "local government." Duplicate information is also removed.

[0248] Data organization

[0249] The server organizes the filtered data by prefecture and classifies it into categories such as "Tokyo," "April 1, 2023," and "Announcement of Workation Promotion."

[0250] Data output and visualization

[0251] The device exports the organized data in spreadsheet format. It also displays the number of workation promotion projects for each municipality as a bar graph.

[0252] Emotion Recognition and Application

[0253] While the user is interacting with the system, the emotion engine recognizes the user's emotions based on their interaction speed and input. For example, if the system detects that the user is excited, the server prioritizes displaying more detailed search results. Furthermore, the emotion engine recommends an appropriate structure for the proposal materials based on the user's emotions.

[0254] Thus, the system of the present invention automates the entire process from information gathering and organization to visualization and adjustment of operations based on user emotions, supporting users in efficiently creating project proposals and presentation materials.

[0255] The following describes the processing flow.

[0256] Step 1:

[0257] The user accesses the system using a device and enters specific keywords (e.g., "press release workation local government").

[0258] Step 2:

[0259] The device generates a search query based on keywords entered by the user. This search query is constructed in a format such as "press release AND workation AND local government".

[0260] Step 3:

[0261] The server uses generated search queries to scrape relevant press release information from multiple sources, including news sites, company websites, and local government websites. Specifically, it analyzes the HTML structure of each website and extracts the necessary data (title, publication date, body text, etc.).

[0262] Step 4:

[0263] The server analyzes the data collected via scraping and filters out press release information that matches the aforementioned keywords. Here, the degree of keyword matching is evaluated, and duplicate information is eliminated.

[0264] Step 5:

[0265] The server categorizes filtered data by company, local government, and announcement date. For example, press releases from Tokyo on April 1, 2023, are grouped together under a single category.

[0266] Step 6:

[0267] The server sends the organized data to the terminal, and the terminal then presents the user with the option to export it in spreadsheet format (.csv or .xlsx).

[0268] Step 7:

[0269] The device generates various graphs (bar graphs, pie charts, line graphs, etc.) in response to user requests, visually displaying data. For example, it can display the number of announced workation projects per month as a bar graph.

[0270] Step 8:

[0271] The emotion engine recognizes the user's emotions from the keywords and operation history they input. For example, it analyzes the user's emotions from the speed and intensity of their input, as well as their choice of words.

[0272] Step 9:

[0273] Emotion recognition allows the server to dynamically adjust the priority of search results based on the user's emotions. For example, if a user is feeling stressed, concise and summarized information will be prioritized.

[0274] Step 10:

[0275] The emotion engine provides a feature that recommends the structure of proposal materials based on the user's emotions. For example, if the user indicates an optimistic mood, it will recommend proposal materials that include detailed and positive content.

[0276] Step 11:

[0277] Users create project proposals and presentations based on exported data, generated graphs, and recommendations from the provided materials. This allows users to efficiently analyze the trends of competitors and local governments and make effective proposals.

[0278] (Example 2)

[0279] 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".

[0280] In modern society, a vast amount of information circulates on the internet, making it a challenge for users to quickly and accurately obtain the information they need. Especially with formalized information such as press releases, it is necessary to efficiently collect related information, avoid duplication, and organize it visually. Furthermore, appropriately adjusting results in response to changes in the user's emotions during the process to reduce user burden is also a crucial challenge.

[0281] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in Example 2 is realized by the following means. In this invention, the server includes means for a user to input a specific keyword, means for generating a search query based on the keyword, means for collecting relevant information from a plurality of information sources on the Internet using the generated search query, means for filtering the collected information and extracting information that matches the keyword, means for sorting the extracted information and categorizing it by organization and publication date, means for exporting the sorted information in spreadsheet format, means for generating various graphs according to the user's request, means for recognizing emotions from the user's operation history and operation speed, and means for adjusting the priority order of search results based on the recognized emotions. As a result, the user can quickly and accurately obtain the necessary information from a large amount of information, can sort and visualize it, and can provide appropriate information according to the emotions.

[0282] A "user" is a person or agent who accesses the system, inputs a specific keyword, and searches for and uses information.

[0283] A "keyword" is a word or phrase input by a user to search for specific information.

[0284] A "search query" is a character string constructed based on the input keyword and used to search information sources on the Internet.

[0285] An "information source" is a plurality of resources on the Internet such as websites and databases that are targets for collecting information.

[0286] "Filtering" is a process of selecting information that matches the user's keyword from the collected data and eliminating duplicate and unnecessary data.

[0287] "Categorization" is an act of classifying the sorted information based on specific criteria (e.g., by organization, by publication date).

[0288] "Spreadsheet format" refers to a file format for displaying and saving data in a table format, and generally refers to .csv or .xlsx files.

[0289] A "graph" is a visual representation of data and comes in various forms, such as bar graphs, pie charts, and line graphs.

[0290] "Emotion recognition" is the process of analyzing data such as the user's operation history and operation speed to determine the user's emotional state (e.g., excitement, calmness, stress).

[0291] "Search result prioritization" refers to the act of dynamically changing the order in which search results are displayed based on the perceived emotions of the user.

[0292] This invention is a system that allows a user to input specific keywords, generates search queries based on those keywords, and collects, organizes, and visualizes relevant information from multiple sources on the internet. It also includes a function to recognize the user's emotions and adjust the priority of search results based on those emotions.

[0293] The specific embodiment of this system is configured as follows:

[0294] 1. Enter keywords

[0295] The user accesses the system using a device and enters the keywords they want to search for. Examples of keywords include "press release," "workation," and "local government."

[0296] 2. Generating search queries

[0297] The terminal generates an appropriate search query based on the keywords entered by the user. This search query is in the form of keywords concatenated with the AND operator (e.g., "press release AND workation AND local government").

[0298] 3. Data collection

[0299] The server uses the generated search query to collect relevant information from a specified plurality of information sources (news sites, corporate official sites, local government official sites, etc.). Specifically, the server analyzes the HTML structure of each website and scrapes the necessary data.

[0300] 4. Data filtering

[0301] The server filters the collected information and extracts the information that matches the user's keyword. In this filtering process, the evaluation of the keyword matching degree and the elimination of duplicate information are performed.

[0302] 5. Data arrangement

[0303] The server arranges the filtered information and categorizes it by organization or release date. For example, the press release information published by a certain local government on a specific date is grouped into one category.

[0304] 6. Data output and visualization

[0305] The terminal exports the arranged data received from the server in the form of a spreadsheet (.csv or.xlsx), and also generates various graphs (bar graphs, pie charts, line graphs, etc.) according to the user's request and displays them visually.

[0306] 7. Sentiment recognition

[0307] The sentiment engine analyzes the user's input content, operation history, operation speed, etc., and judges the user's sentiment (excitement, calmness, stress, etc.).

[0308] 8. Adjustment of search result priority

[0309] The server dynamically adjusts the priority of search results based on the perceived emotions of the user. For example, if the user is feeling stressed, it prioritizes displaying simpler and more intuitive search results.

[0310] 9. Specific Examples

[0311] When a user enters the keywords "press release workation local government," the device generates a search query "press release AND workation AND local government." The server uses this search query to collect the following information from news sites and official websites:

[0312] Local government: Tokyo Metropolitan Government

[0313] Title: Announcement of Workation Promotion

[0314] Announcement date: April 1, 2023

[0315] The server filters this information, removes duplicates, and organizes it by prefecture and announcement date. The terminal provides this organized information to the user in spreadsheet and graph format. Furthermore, the emotion engine recognizes the user's emotions while they are using the device, and if it determines that the user is excited, it prioritizes displaying detailed information at a faster pace.

[0316] Example of a prompt:

[0317] "Enter specific keywords (e.g., 'press release,' 'workation,' 'local government') to collect and visualize relevant information. Export the collected information in spreadsheet format and display the data for each organization as a bar graph. Also, adjust the search results based on user sentiment."

[0318] Thus, by using the system of the present invention, users can quickly and accurately obtain the necessary data from a vast amount of information, and further organize and analyze it visually. In addition, it becomes possible to provide information flexibly in accordance with the user's emotions, thereby improving usability.

[0319] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0320] Step 1:

[0321] The user enters specific keywords. The user accesses the system using a terminal and enters the keywords they want to search for (e.g., "press release," "workation," "local government"). The input data is a list of keywords in text format.

[0322] Step 2:

[0323] The terminal generates a search query. Based on the entered keywords, the terminal generates a search query using the AND operator. For example, "press release AND workation AND local government". This query is used to search for information sources on the internet. The input is a list of keywords from the user, and the output is the generated search query.

[0324] Step 3:

[0325] The server collects relevant information. Using the generated search query, the server collects information from multiple sources, such as news sites, company websites, and local government websites. The server analyzes the HTML structure of each website and scrapes necessary data such as title, publication date, and body text. The input is the generated search query, and the output is the collected raw data.

[0326] Step 4:

[0327] The server filters the data. The server filters the collected raw data and extracts information that matches the user's keywords. During filtering, keyword matching is evaluated and duplicate information is removed. For example, only information containing all of the keywords "press release," "workation," and "local government" is retained. The input is the collected raw data, and the output is the filtered data.

[0328] Step 5:

[0329] The server organizes the data. The server categorizes the filtered data by organization and by publication date. For example, information released by the Tokyo Metropolitan Government on April 1, 2023, regarding the promotion of workation would be classified in the format "Tokyo Metropolitan Government / April 1, 2023 / Workation Promotion Announcement". The input is filtered data, and the output is organized data.

[0330] Step 6:

[0331] The terminal visualizes and exports data. The terminal exports the organized data in spreadsheet format (.csv or .xlsx) and generates and displays various graphs (bar graphs, pie charts, line graphs, etc.) according to user requests. For example, it can display the number of workation promotion projects for each municipality as a bar graph. The input is organized data, and the output is visualized information and an exported spreadsheet.

[0332] Step 7:

[0333] The emotion engine recognizes the user's emotions. The emotion engine analyzes the user's input, operation history, and operation speed to determine whether the user is excited, calm, or stressed. The input is the user's operation data, and the output is the recognized emotional state.

[0334] Step 8:

[0335] The server adjusts the priority of search results based on emotions. Based on the recognized emotions, the server makes adjustments, for example, prioritizing simple and intuitive search results if the user is stressed. The input is the recognized emotional state, and the output is the adjusted search results.

[0336] Thus, the user begins by entering specific keywords, and the system efficiently delivers information through data collection, filtering, organization, visualization, and sentiment recognition and its application.

[0337] (Application Example 2)

[0338] 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".

[0339] This invention aims to improve the efficiency of information gathering and processing, and particularly in work environments such as logistics centers, there is a need to quickly and efficiently collect and visually display the information that workers need. Furthermore, there is a lack of means to appropriately change the displayed content according to the emotions and state of the workers in order to improve work efficiency. In addition, it is necessary not only to collect information, but also to visualize it in an intuitively understandable format.

[0340] 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 the user to input a specific keyword, means for generating a search query based on the keyword, means for collecting relevant information from multiple information sources on the Internet using the generated search query, means for filtering the collected information and extracting information that matches the keyword, means for organizing the extracted information and categorizing it by category and publication date, means for exporting the organized information in spreadsheet format, means for generating a graph according to the user's request, means for recognizing the user's voice input and generating a search query, means for analyzing the user's emotions from their voice tone and operation speed and changing the search query and display content, and means for displaying the user's operation results on a head-mounted display. This enables rapid collection, organization, and visualization of information. Furthermore, work efficiency is improved by adapting the display content according to the worker's emotions and state.

[0341] A "user" is an entity that uses a system to input keywords and perform operations such as generating search queries and gathering information.

[0342] A "keyword" is a specific word or phrase entered by the user, and it forms the basis for generating a search query.

[0343] A "search query" is a search command constructed based on entered keywords, and is used to collect relevant information from internet sources.

[0344] "Information sources" refer to various websites and databases on the internet from which information is collected using search queries.

[0345] "Filtering" is the process of evaluating whether collected information matches keywords and eliminating unnecessary or duplicate information.

[0346] A "category" is a framework for classifying filtered information, used to organize it based on specific attributes or criteria.

[0347] "Spreadsheet format" refers to a format for exporting organized information as a tab-formatted file (e.g., .csv or .xlsx).

[0348] A "graph" is a tool for visually representing data, and includes various formats such as bar graphs, pie charts, and line graphs.

[0349] "Speech recognition" is a technology that converts speech input by a user into text data and generates search queries based on that data.

[0350] "Sentiment analysis" is a technology that recognizes a user's emotional state based on information such as the user's voice tone and operation speed.

[0351] "Displayed content" refers to organized information and graphs that are visually presented to the user.

[0352] A "head-mounted display" is a device worn on the user's head to display visual information, providing information within the work environment.

[0353] This invention provides a system for improving operational efficiency in logistics centers. The specific program processing of the system, as well as the hardware and software used, are described below.

[0354] System Configuration

[0355] hardware

[0356] A head-mounted display (HMD) is a device worn on the head by workers to display visual information. A specific example is Microsoft HoloLens®.

[0357] Microphone: A device for acquiring voice input and recognizing voice instructions from workers.

[0358] software

[0359] Speech recognition library: Use the speech_recognition library to convert the worker's voice instructions into text data.

[0360] HTTP Request Library: Use the requests library to collect data from multiple sources on the internet.

[0361] Data processing library: Use the pandas library to organize the collected data.

[0362] Data visualization library: Use the matplotlib library to visually display data.

[0363] Sentiment Analysis Model: A model is used to analyze emotions from voice tone and operation speed.

[0364] Program Processing Description

[0365] 1. Voice recognition and keyword input

[0366] The user wears a head-mounted display and uses a microphone to input necessary information and instructions via voice. This voice is then converted into text data through a speech recognition library.

[0367] 2. Generating search queries

[0368] A search query is generated based on keywords obtained as text data. This query is structured in a specified format and forms the basis for information gathering.

[0369] 3. Data Collection

[0370] The server uses the generated search query to collect relevant information from multiple sources on the internet (news sites, official websites, databases, etc.). It uses an HTTP request library to retrieve the information and extracts the necessary data (title, publication date, body text, etc.).

[0371] 4. Filtering and organizing data

[0372] The collected information is filtered based on specified keywords to eliminate unnecessary and duplicate information. Furthermore, a data processing library is used to classify and organize the information by category and publication date.

[0373] 5. Data Visualization

[0374] The organized information is displayed as graphs (bar graphs, pie charts, line graphs, etc.) using a data visualization library. This makes it easier for users to visually grasp the information.

[0375] 6. Sentiment analysis and adjustment of displayed content

[0376] An emotion analysis model analyzes the user's emotional state based on their voice tone and operation speed. If the user is tired, the display content is adjusted accordingly, such as showing only essential information concisely.

[0377] Specific example

[0378] When a user voice-inputs keywords such as "inventory information" or "product receiving and shipping status," the system generates a search query based on these keywords and collects relevant information. At the same time, if the sentiment analysis model detects fatigue from the user's voice tone, it reduces the workload by displaying only essential information.

[0379] Examples of prompts for generative AI models

[0380] Please describe the design of a system that can collect, organize, and visualize "inventory management and receiving / shipping information for a logistics center" in a specified format. Furthermore, please provide a concrete example of an application that includes a function to change the operation method based on the user's emotions.

[0381] As described above, the present invention provides a system that improves work efficiency and optimizes the operation method according to the user's condition.

[0382] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0383] Step 1:

[0384] The user wears a head-mounted display and inputs keywords by voice using a microphone. This voice data is acquired and converted into text data using a speech recognition library. The input is voice data, and the output is text data.

[0385] Specific operation: The user says "inventory information," and the voice is recognized through the microphone. This is then converted into text data, "inventory information," and passed to the system.

[0386] Step 2:

[0387] The terminal generates a search query based on keywords obtained as text data. Specifically, it constructs the keywords in a specified format (e.g., AND search). The input is text data, and the output is a search query.

[0388] Specific operation: Text data "Inventory Information" is entered, and a search query "Inventory Information AND Status" is generated.

[0389] Step 3:

[0390] The server uses the generated search query to collect relevant information from multiple sources. It uses an HTTP request library to retrieve data from news sites, official websites, databases, and other sources on the internet. The input is the search query, and the output is the collected information.

[0391] Specific operation: The search query "Inventory Information AND Status" is executed, and data regarding inventory information and status (e.g., title, publication date, body text) is retrieved from relevant websites.

[0392] Step 4:

[0393] The server filters the collected information and extracts information that matches the keywords. It uses a data processing library to remove unnecessary and duplicate information. The input is the collected information, and the output is the filtered information.

[0394] Specific operation: Information that does not match the criteria or duplicate information is removed from the acquired data.

[0395] Step 5:

[0396] The server organizes the filtered information by category and publication date. It uses a data processing library to classify the information and export it in spreadsheet format. The input is filtered information, and the output is organized data in spreadsheet format.

[0397] Specific operation: Filtered data is categorized by company and publication date, and exported as a .csv file.

[0398] Step 6:

[0399] The terminal generates graphs based on organized information. It uses a data visualization library to create visual graphs (bar graphs, pie charts, line graphs, etc.). Input is data in spreadsheet format, and output is graphs.

[0400] Specific operation: A bar graph showing inventory status is generated from spreadsheet-formatted data and displayed on the HMD screen.

[0401] Step 7:

[0402] The server analyzes the user's emotional state based on their voice tone and operation speed. Using an emotional analysis model, it determines whether the user is tired, etc. The input is voice tone and operation speed, and the output is the emotional state.

[0403] Specific behavior: If the user's voice tone is low and their operation speed is slow, the system analyzes that the user is fatigued.

[0404] Step 8:

[0405] The server adjusts the displayed content based on the analyzed emotional state. If fatigue is detected, the system displays only essential information concisely. The input is the emotional state, and the output is the adjusted display content.

[0406] Specific action: When the user is fatigued, only the essential inventory information is highlighted on the screen.

[0407] The above outlines the specific processing steps of the system program that implements the application example.

[0408] 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.

[0409] 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.

[0410] 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.

[0411] [Second Embodiment]

[0412] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0413] 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.

[0414] 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).

[0415] 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.

[0416] 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.

[0417] 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).

[0418] 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.

[0419] 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.

[0420] 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.

[0421] 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.

[0422] 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.

[0423] 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".

[0424] The system of the present invention allows a user to input specific keywords, generates a search query based on those keywords, and collects, organizes, and visualizes relevant press release information from multiple sources on the internet.

[0425] Program Overview

[0426] User actions

[0427] The user accesses the system using a terminal and enters specific keywords (e.g., "press release," "workation," "local government").

[0428] Generating search queries

[0429] The terminal generates a search query based on the entered keywords. This search query consists of AND searches and specified formats. For example, it might be generated as "Press release AND Workation AND Local government".

[0430] Data collection

[0431] The server uses the generated search query to scrape relevant press release information from multiple specified sources (news sites, company websites, local government websites, etc.). During scraping, it analyzes the HTML structure of each website and extracts the necessary data (title, publication date, body text, etc.).

[0432] Data filtering

[0433] The server filters the collected information and extracts press releases that match the user's keywords. This filtering includes evaluating keyword relevance and eliminating duplicate information.

[0434] Data organization

[0435] The server organizes the filtered data. This organization process categorizes the information by company, local government, and publication date. For example, press releases from a particular local government on a specific date might be grouped into a single category.

[0436] Data output and visualization

[0437] The terminal exports the organized data received from the server in spreadsheet format (.csv or .xlsx). It also generates various graphs (bar graphs, pie charts, line graphs, etc.) upon user request, visually displaying the data.

[0438] Specific example

[0439] User actions

[0440] The user enters the keywords "press release workation local government" into the system.

[0441] Generating search queries

[0442] The device generates a search query: "Press release AND workation AND local government".

[0443] Data collection

[0444] The server uses this search query to collect press release information from news sites and official websites. For example, the server retrieves the following information:

[0445] Local government: Tokyo Metropolitan Government

[0446] Title: Announcement of Workation Promotion

[0447] Announcement date: April 1, 2023

[0448] Data filtering

[0449] The server extracts only the information containing all of the following: "press release," "workation," and "local government." Duplicate information is also removed.

[0450] Data organization

[0451] The server organizes the filtered data by prefecture and classifies it into categories such as "Tokyo," "April 1, 2023," and "Announcement of Workation Promotion."

[0452] Data output and visualization

[0453] The device exports the organized data in spreadsheet format. It also displays the number of workation promotion projects for each municipality as a bar graph.

[0454] Thus, the system of the present invention automates the entire process from information gathering to organization and visualization, supporting users in efficiently creating project proposals and presentation materials.

[0455] The following describes the processing flow.

[0456] Step 1:

[0457] The user enters specific keywords using their device. For example, they might enter "press release workation local government".

[0458] Step 2:

[0459] The terminal generates a search query based on the entered keywords. It is structured in the form of "Press release AND Workation AND Local government".

[0460] Step 3:

[0461] The server uses a generated search query to scrape relevant press release information from multiple specified sources. Information is retrieved from news sites, company websites, and local government websites.

[0462] Step 4:

[0463] The server analyzes the information collected via scraping, extracting the title, publication date, and text from the document. It also analyzes the HTML structure to extract the necessary data.

[0464] Step 5:

[0465] The server filters the collected information. It extracts only information that includes all of the following: "press releases," "workation," and "local government," eliminating unnecessary information and spam.

[0466] Step 6:

[0467] The server organizes the filtered information. The information is categorized by company, local government, and publication date. For example, press releases from Tokyo on April 1, 2023, are grouped into a single category.

[0468] Step 7:

[0469] The server eliminates duplicate press release information. If the same press release is collected multiple times, it combines them into one and removes the duplicates.

[0470] Step 8:

[0471] The terminal exports the organized data received from the server in spreadsheet format (.csv or .xlsx). This allows the user to download and use it.

[0472] Step 9:

[0473] The device generates various graphs (bar graphs, pie charts, line graphs, etc.) in response to user requests, visually displaying data. For example, it can display the number of announced workation projects per month as a bar graph.

[0474] Step 10:

[0475] Users create project proposals and presentation materials based on exported data and generated graphs. They utilize the data to analyze the trends of competitors and local governments and make effective proposals.

[0476] (Example 1)

[0477] 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."

[0478] Traditional information gathering systems struggled to efficiently collect, organize, and visualize information related to specific keywords from multiple sources on the internet, requiring users to expend considerable time and effort. Furthermore, the elimination of duplicate information and data visualization were not automated, necessitating manual processing.

[0479] 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.

[0480] In this invention, the server includes means for a user to input a specific keyword, means for generating a search query based on the keyword, means for collecting relevant information from multiple information sources on the internet using the generated search query, means for filtering the collected information and extracting information that matches the keyword, means for organizing the extracted information and categorizing it by organization, administrative division, and date and time, means for exporting the organized information in spreadsheet software format, and means for generating charts and graphs according to the user's request. This automates a series of tasks from information collection to organization and visualization, enabling the user to efficiently obtain the necessary information.

[0481] "User" refers to a person who uses this system.

[0482] A "keyword" refers to a specific word or phrase that a user enters to search for information.

[0483] A "search query" refers to a string of characters that represents a specific command to search for information from internet sources, generated based on keywords.

[0484] "Information source" refers to a place where information exists, such as websites or databases on the internet.

[0485] "Filtering" refers to the process of selecting information that matches specific criteria from collected data.

[0486] "Categorization" refers to classifying collected and filtered information based on specific criteria (e.g., organization, administrative division, date and time).

[0487] "Spreadsheet format" refers to a format for electronically managing and analyzing information (e.g., .csv or .xlsx).

[0488] "Charts and graphs" refer to graphs and charts (e.g., bar graphs, pie charts, line graphs) used to visually represent data.

[0489] The system of the present invention enables efficient information collection, organization, and visualization through a complex configuration including users, terminals, and servers.

[0490] System Configuration

[0491] User actions

[0492] The user accesses the system using a device (e.g., a PC or smartphone) and enters specific keywords (e.g., "press release," "workation," "local government"). The device uses an input device such as a keyboard or touchscreen.

[0493] Generating search queries

[0494] The device retrieves the keywords entered by the user and converts them into an AND search query. This query is generated in the format of "press release AND workation AND local government".

[0495] Start of data collection

[0496] The server receives the generated search query and initiates access to the specified information sources (such as news sites, company websites, and local government websites). In this process, the server refers to a list of URLs for each information source and uses the search query to extract relevant information.

[0497] scraping

[0498] The server uses the Python BeautifulSoup library to parse the HTML of each information source and extract necessary data such as "title," "publication date," and "body text."

[0499] Specifically, the following information will be obtained:

[0500] Local government: Tokyo Metropolitan Government

[0501] Title: Announcement of Workation Promotion

[0502] Announcement date: April 1, 2023

[0503] Data filtering

[0504] The server filters the retrieved data. Here, it extracts only the information that exactly matches the search query and eliminates duplicate data.

[0505] Data organization

[0506] The server organizes the filtered data. The organized data is then categorized by organization, administrative division, and date. For example, the server creates categories such as "Tokyo Metropolitan Government," "April 1, 2023," and "Announcement of Workation Promotion," and groups related data together.

[0507] Data Output

[0508] The server sends the organized data to the terminal, and the terminal provides a function to export it in spreadsheet format (.csv or .xlsx).

[0509] Visualization

[0510] The device visualizes organized data according to user requests. It generates and displays bar graphs, pie charts, line graphs, and other visual representations. For example, it can display the number of workation promotion projects for each municipality as a bar graph.

[0511] Example of a prompt

[0512] "Design a system that collects, organizes, and visualizes press release information from multiple online sources based on a specific keyword input. Explain the entire process, from generating search queries based on the user's keywords, to collecting and filtering data from the sources, and finally organizing and visualizing the data."

[0513] Thus, the system of the present invention automatically collects, organizes, and visualizes relevant information simply by the user entering specific keywords, enabling the user to efficiently acquire and utilize the necessary information.

[0514] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0515] Step 1:

[0516] The user accesses the system using a terminal and enters a specific keyword.

[0517] Input: Specific keywords (e.g., "press release", "workation", "local government")

[0518] Output: Set of entered keywords

[0519] Specific action: The user enters a keyword into the text box and presses the "Search" button.

[0520] Step 2:

[0521] The terminal retrieves the entered keyword and generates a search query based on it.

[0522] Input: A set of keywords entered by the user.

[0523] Output: Search query (Example: "Press release AND workation AND local government")

[0524] Specific operation: The terminal converts the entered keyword into a string in AND search format.

[0525] Step 3:

[0526] The server receives the generated search query and initiates access to the specified information source.

[0527] Input: Generated search query, list of URLs for the source.

[0528] Output: HTML data to be collected

[0529] Specific operation: The server visits the URLs of each information source and retrieves the HTML data of the pages that match the search query.

[0530] Step 4:

[0531] The server performs scraping by analyzing the HTML of each information source and extracting the necessary data.

[0532] Input: HTML data to be collected

[0533] Output: Extracted information (e.g., "Title", "Publication Date", "Text")

[0534] Specific operation: The server uses the Python BeautifulSoup library to extract the title, publication date, and body text from the HTML.

[0535] Step 5:

[0536] The server filters the retrieved data, extracting only the information that exactly matches the search query.

[0537] Input: Set of extracted information

[0538] Output: Set of filtered information

[0539] Specific operation: The server evaluates the degree of matching with the search query and eliminates mismatched or duplicate information.

[0540] Step 6:

[0541] The server organizes the filtered data and classifies it by organization, administrative division, and date / time.

[0542] Input: A set of filtered information

[0543] Output: Set of classified information

[0544] Specific operation: The server categorizes data based on specific criteria and registers it in the database.

[0545] Step 7:

[0546] The server sends the organized data to the terminal, which then exports it in spreadsheet format.

[0547] Input: Set of classified information

[0548] Output: Spreadsheet file format (.csv or .xlsx)

[0549] Specific operation: The server sends the classified data to the terminal in JSON format, and the terminal converts and exports it in CSV or XLSX format.

[0550] Step 8:

[0551] The device visualizes organized data in response to user requests.

[0552] Input: Set of classified information

[0553] Output: Visualized data (e.g., bar graph, pie chart, line graph)

[0554] Specific operation: If the user requests data visualization, the device uses a visualization library to generate a graph and display it on the screen.

[0555] (Application Example 1)

[0556] 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."

[0557] Traditional information gathering systems required users to manually search for specific information and verify related information one by one from numerous sources, which presented significant challenges in terms of effort and time. Furthermore, organizing and visualizing the collected information was also done manually, resulting in problems such as data duplication and redundancy. In advertising operations in particular, timely information gathering and analysis are crucial, and an efficient system for this purpose was needed.

[0558] 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.

[0559] In this invention, the server includes means for a user to input a specific keyword, means for generating a search query based on the keyword, means for collecting relevant information from multiple information sources on the internet using the generated search query, means for filtering the collected information and extracting information that matches the keyword, means for organizing the extracted information and categorizing it by organization and presentation time, means for exporting the organized information in a calculation processing table format, means for generating data visualizations such as bar graphs, pie charts, and line graphs in response to the user's request, and means for inputting the generated graph information as prompt text into a generation AI model for further detailed analysis. This enables users to efficiently collect, organize, and visualize information, particularly enabling timely information analysis and strategic planning in advertising operations.

[0560] A "user" is an individual or group that uses the system to search for and analyze specific information.

[0561] A "keyword" is a word or phrase that a user enters when searching for specific information.

[0562] A "search query" is a search command generated based on keywords to retrieve specific information.

[0563] "Information sources" refer to websites and databases where information is publicly available, such as news portals, official organizations' websites, and public databases.

[0564] "Filtering" is the process of removing duplicate information from collected data and extracting information that matches keywords.

[0565] "Categorization" is the process of classifying extracted information based on specific criteria (for example, by organization, by presentation time).

[0566] A "calculation processing table" is a tabular document, such as Excel or CSV, used to organize and visually display data.

[0567] "Data visualization" is the process of visually displaying collected data in formats such as bar graphs, pie charts, and line graphs.

[0568] A "prompt statement" is a set of instructions given to a generating AI model for analysis and processing.

[0569] A "generative AI model" is a computer program that uses artificial intelligence technology to perform advanced analysis and processing based on input prompt sentences.

[0570]

[0571] The present invention is implemented as an information gathering and analysis system. This system has the function of allowing a user to input specific keywords, generating search queries based on those keywords, and collecting, organizing, and visualizing relevant information from multiple sources on the internet.

[0572] First, the user accesses the system using a terminal and enters specific keywords (e.g., "new product announcement," "campaign," "social media"). The terminal generates a search query based on the entered keywords. This search query consists of AND searches and a specified format. For example, it might be generated as "new product announcement AND campaign AND social media."

[0573] Next, the server uses the generated search query to collect information from multiple sources on the internet (news portals, official organization websites, public databases, etc.). During collection, the server analyzes the HTML structure of each website and extracts the necessary data (title, publication date, content, etc.).

[0574] The extracted information is filtered to extract only the information that matches the keywords and eliminate duplicate information. Then, the filtered data is organized and categorized by organization and presentation time.

[0575] The organized information can be exported as a calculation processing table (.csv or .xlsx format) upon user request. The data can also be visualized using bar graphs, pie charts, line graphs, and other methods. Furthermore, the generated graph information is input into the AI ​​model as prompt text for more detailed analysis.

[0576] The hardware used includes common PCs and smartphones, and the software used includes Python 3.x, BeautifulSoup, requests, Pandas, and Matplotlib. Python 3.x is used as the overall program framework, BeautifulSoup is used for HTML parsing, requests for web requests, Pandas for data frame manipulation, and Matplotlib for data visualization.

[0577] As a concrete example, consider a case where an advertising agency representative enters the keywords "new product launch campaign social media" into the app. In this case, the server collects relevant campaign information from news portals and the organization's official website, and then organizes and filters it. As a result, data containing information such as "a certain organization new product launch campaign (October 1, 2023)" is organized and output as a report in PDF or CSV format.

[0578] As an example of a prompt, the following can be entered into the generative AI model:

[0579] "Users enter keywords such as 'new product launch campaign social media,' and the system collects, filters, organizes, and visualizes relevant information, displaying it in spreadsheet and graph formats."

[0580] Thus, the system of the present invention enables users to efficiently collect, organize, and visualize information, and in particular, enables timely information analysis and strategic planning in advertising operations.

[0581] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0582] Step 1:

[0583] A user accesses the system using a terminal and enters specific keywords. These keywords may include multiple words or phrases, such as "new product announcement," "campaign," or "social media." The input data consists of these keywords, which are then passed to the search query generation phase as output.

[0584] Step 2:

[0585] The terminal generates a search query based on the entered keywords. This search query is composed of AND searches or specified formats, such as "New product announcement AND campaign AND social media". The input data is the keywords, and the output data is the generated search query.

[0586] Step 3:

[0587] The server uses the generated search query to collect information from multiple sources on the internet. Specifically, it retrieves HTML data from news portals, official organizational websites, public databases, etc., and parses the HTML structure using BeautifulSoup. The input data is the search query, and the output data is the collected HTML data.

[0588] Step 4:

[0589] The server filters the collected information. Specifically, it organizes it as a data frame using Pandas, extracts only the information that matches the keywords, and eliminates duplicate information. The input data is HTML data, and the output data is the filtered information.

[0590] Step 5:

[0591] The server organizes the filtered information and categorizes it by organization and presentation time. This makes it easier for users to view information according to specific criteria. The input data is filtered information, and the output data is categorized information.

[0592] Step 6:

[0593] The terminal exports the organized information as a calculation spreadsheet (.csv or .xlsx format) upon user request. The input data is categorized information, and the output data is a spreadsheet file.

[0594] Step 7:

[0595] The terminal also generates data visualizations such as bar graphs, pie charts, and line graphs in response to user requests. It uses Matplotlib to visually display the data. The input data is categorized information, and the output data is visualized data in graph format.

[0596] Step 8:

[0597] The terminal inputs the generated graph information as a prompt into the generating AI model for further detailed analysis. The input data is graph information, and the output data is the AI ​​analysis result. For example, the prompt "The user enters the keywords 'new product announcement campaign social media', and the AI ​​model should collect, filter, organize, and visualize the relevant information and display it in spreadsheet and graph format." is input into the generating AI model.

[0598] 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.

[0599] The present invention is a system that allows a user to input specific keywords, generates search queries based on those keywords, and collects, organizes, and visualizes relevant press release information from multiple sources on the internet. Furthermore, it includes a function to recognize the user's emotions and perform actions based on those emotions.

[0600] Program Overview

[0601] User actions

[0602] The user accesses the system using a terminal and enters specific keywords (e.g., "press release," "workation," "local government").

[0603] Generating search queries

[0604] The terminal generates a search query based on the entered keywords. This search query consists of AND searches and specified formats. For example, it might be generated as "Press release AND Workation AND Local government".

[0605] Data collection

[0606] The server uses the generated search query to scrape relevant press release information from multiple specified sources (news sites, company websites, local government websites, etc.). During scraping, it analyzes the HTML structure of each website and extracts the necessary data (title, publication date, body text, etc.).

[0607] Data filtering

[0608] The server filters the collected information and extracts press releases that match the user's keywords. This filtering includes evaluating keyword relevance and eliminating duplicate information.

[0609] Data organization

[0610] The server organizes the filtered data. This organization process categorizes the information by company, local government, and publication date. For example, press releases from a particular local government on a specific date might be grouped into a single category.

[0611] Data output and visualization

[0612] The terminal exports the organized data received from the server in spreadsheet format (.csv or .xlsx). It also generates various graphs (bar graphs, pie charts, line graphs, etc.) upon user request, visually displaying the data.

[0613] Embedding an emotion engine

[0614] emotion recognition

[0615] The emotion engine analyzes the user's emotions based on keywords entered, operation history, language used, and operation speed. Using emotion analysis technology, it recognizes whether the user is excited, calm, or stressed.

[0616] Prioritizing search results based on emotions

[0617] The server dynamically adjusts the priority of search results based on the perceived emotions of the user. For example, if the user is feeling stressed, it prioritizes displaying simpler and more intuitive search results.

[0618] Recommendations for proposal materials based on emotions

[0619] The emotion engine recommends the structure of proposals and project plans based on the user's emotions. For example, if the user is excited, it will recommend more detailed and specific materials, while if the user is calm, it will recommend concise and to the point.

[0620] Specific example

[0621] User actions

[0622] The user enters the keywords "press release workation local government" into the system.

[0623] Generating search queries

[0624] The device generates a search query: "Press release AND workation AND local government".

[0625] Data collection

[0626] The server uses this search query to collect press release information from news sites and official websites. For example, the server retrieves the following information:

[0627] Local government: Tokyo Metropolitan Government

[0628] Title: Announcement of Workation Promotion

[0629] Announcement date: April 1, 2023

[0630] Data filtering

[0631] The server extracts only the information containing all of the following: "press release," "workation," and "local government." Duplicate information is also removed.

[0632] Data organization

[0633] The server organizes the filtered data by prefecture and classifies it into categories such as "Tokyo," "April 1, 2023," and "Announcement of Workation Promotion."

[0634] Data output and visualization

[0635] The device exports the organized data in spreadsheet format. It also displays the number of workation promotion projects for each municipality as a bar graph.

[0636] Emotion Recognition and Application

[0637] While the user is interacting with the system, the emotion engine recognizes the user's emotions based on their interaction speed and input. For example, if the system detects that the user is excited, the server prioritizes displaying more detailed search results. Furthermore, the emotion engine recommends an appropriate structure for the proposal materials based on the user's emotions.

[0638] Thus, the system of the present invention automates the entire process from information gathering and organization to visualization and adjustment of operations based on user emotions, supporting users in efficiently creating project proposals and presentation materials.

[0639] The following describes the processing flow.

[0640] Step 1:

[0641] The user accesses the system using a device and enters specific keywords (e.g., "press release workation local government").

[0642] Step 2:

[0643] The device generates a search query based on keywords entered by the user. This search query is constructed in a format such as "press release AND workation AND local government".

[0644] Step 3:

[0645] The server uses generated search queries to scrape relevant press release information from multiple sources, including news sites, company websites, and local government websites. Specifically, it analyzes the HTML structure of each website and extracts the necessary data (title, publication date, body text, etc.).

[0646] Step 4:

[0647] The server analyzes the data collected via scraping and filters out press release information that matches the aforementioned keywords. Here, the degree of keyword matching is evaluated, and duplicate information is eliminated.

[0648] Step 5:

[0649] The server categorizes filtered data by company, local government, and announcement date. For example, press releases from Tokyo on April 1, 2023, are grouped together under a single category.

[0650] Step 6:

[0651] The server sends the organized data to the terminal, and the terminal then presents the user with the option to export it in spreadsheet format (.csv or .xlsx).

[0652] Step 7:

[0653] The device generates various graphs (bar graphs, pie charts, line graphs, etc.) in response to user requests, visually displaying data. For example, it can display the number of announced workation projects per month as a bar graph.

[0654] Step 8:

[0655] The emotion engine recognizes the user's emotions from the keywords and operation history they input. For example, it analyzes the user's emotions from the speed and intensity of their input, as well as their choice of words.

[0656] Step 9:

[0657] Emotion recognition allows the server to dynamically adjust the priority of search results based on the user's emotions. For example, if a user is feeling stressed, concise and summarized information will be prioritized.

[0658] Step 10:

[0659] The emotion engine provides a feature that recommends the structure of proposal materials based on the user's emotions. For example, if the user indicates an optimistic mood, it will recommend proposal materials that include detailed and positive content.

[0660] Step 11:

[0661] Users create project proposals and presentations based on exported data, generated graphs, and recommendations from the provided materials. This allows users to efficiently analyze the trends of competitors and local governments and make effective proposals.

[0662] (Example 2)

[0663] 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".

[0664] In modern society, a vast amount of information circulates on the internet, making it a challenge for users to quickly and accurately obtain the information they need. Especially with formalized information such as press releases, it is necessary to efficiently collect related information, avoid duplication, and organize it visually. Furthermore, appropriately adjusting results in response to changes in the user's emotions during the process to reduce user burden is also a crucial challenge.

[0665] The specific processing performed by the specific 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 the user to input specific keywords, means for generating a search query based on the keywords, means for collecting relevant information from multiple information sources on the Internet using the generated search query, means for filtering the collected information and extracting information that matches the keywords, means for organizing the extracted information and categorizing it by organization and publication date, means for exporting the organized information in spreadsheet format, means for generating various graphs according to the user's request, means for recognizing emotions from the user's operation history and operation speed, and means for adjusting the priority of search results based on the recognized emotions. As a result, the user can quickly and accurately obtain what they need from a large amount of information, organize and visualize it, and be provided with appropriate information according to their emotions.

[0666] A "user" is a person or agent who accesses the system and searches for and uses information by entering specific keywords.

[0667] A "keyword" is a word or phrase that a user enters to search for specific information.

[0668] A "search query" is a string of characters constructed based on entered keywords, used to search for information sources on the internet.

[0669] "Information sources" refer to multiple resources on the internet, such as websites and databases, from which information is collected.

[0670] "Filtering" is the process of selecting information that matches the user's keywords from collected data and eliminating duplicate or unnecessary data.

[0671] "Categorization" is the act of classifying organized information based on specific criteria (e.g., by organization, by publication date).

[0672] "Spreadsheet format" refers to a file format for displaying and saving data in a table format, and generally refers to .csv or .xlsx files.

[0673] A "graph" is a visual representation of data and comes in various forms, such as bar graphs, pie charts, and line graphs.

[0674] "Emotion recognition" is the process of analyzing data such as the user's operation history and operation speed to determine the user's emotional state (e.g., excitement, calmness, stress).

[0675] "Search result prioritization" refers to the act of dynamically changing the order in which search results are displayed based on the perceived emotions of the user.

[0676] This invention is a system that allows a user to input specific keywords, generates search queries based on those keywords, and collects, organizes, and visualizes relevant information from multiple sources on the internet. It also includes a function to recognize the user's emotions and adjust the priority of search results based on those emotions.

[0677] The specific embodiment of this system is configured as follows:

[0678] 1. Enter keywords

[0679] The user accesses the system using a device and enters the keywords they want to search for. Examples of keywords include "press release," "workation," and "local government."

[0680] 2. Generating search queries

[0681] The terminal generates an appropriate search query based on the keywords entered by the user. This search query is in the form of keywords concatenated with the AND operator (e.g., "press release AND workation AND local government").

[0682] 3. Data Collection

[0683] The server uses the generated search query to collect relevant information from multiple specified information sources (such as news sites, company websites, and local government websites). Specifically, the server analyzes the HTML structure of each website and scrapes the necessary data.

[0684] 4. Data filtering

[0685] The server filters the collected information and extracts information that matches the user's keywords. This filtering process includes evaluating the degree of keyword relevance and eliminating duplicate information.

[0686] 5. Data organization

[0687] The server organizes the filtered information and categorizes it by organization or publication date. For example, it might group press releases issued by a local government on a specific date into a single category.

[0688] 6. Data Output and Visualization

[0689] The terminal exports the organized data received from the server in spreadsheet format (.csv or .xlsx), and also generates and displays various graphs (bar graphs, pie charts, line graphs, etc.) according to the user's request.

[0690] 7. Emotion recognition

[0691] The emotion engine analyzes the user's input, operation history, and operation speed to determine the user's emotions (excitement, calmness, stress, etc.).

[0692] 8. Prioritizing search results

[0693] The server dynamically adjusts the priority of search results based on the perceived emotions of the user. For example, if the user is feeling stressed, it prioritizes displaying simpler and more intuitive search results.

[0694] 9. Specific Examples

[0695] When a user enters the keywords "press release workation local government," the device generates a search query "press release AND workation AND local government." The server uses this search query to collect the following information from news sites and official websites:

[0696] Local government: Tokyo Metropolitan Government

[0697] Title: Announcement of Workation Promotion

[0698] Announcement date: April 1, 2023

[0699] The server filters this information, removes duplicates, and organizes it by prefecture and announcement date. The terminal provides this organized information to the user in spreadsheet and graph format. Furthermore, the emotion engine recognizes the user's emotions while they are using the device, and if it determines that the user is excited, it prioritizes displaying detailed information at a faster pace.

[0700] Example of a prompt:

[0701] "Enter specific keywords (e.g., 'press release,' 'workation,' 'local government') to collect and visualize relevant information. Export the collected information in spreadsheet format and display the data for each organization as a bar graph. Also, adjust the search results based on user sentiment."

[0702] Thus, by using the system of the present invention, users can quickly and accurately obtain the necessary data from a vast amount of information, and further organize and analyze it visually. In addition, it becomes possible to provide information flexibly in accordance with the user's emotions, thereby improving usability.

[0703] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0704] Step 1:

[0705] The user enters specific keywords. The user accesses the system using a terminal and enters the keywords they want to search for (e.g., "press release," "workation," "local government"). The input data is a list of keywords in text format.

[0706] Step 2:

[0707] The terminal generates a search query. Based on the entered keywords, the terminal generates a search query using the AND operator. For example, "press release AND workation AND local government". This query is used to search for information sources on the internet. The input is a list of keywords from the user, and the output is the generated search query.

[0708] Step 3:

[0709] The server collects relevant information. Using the generated search query, the server collects information from multiple sources, such as news sites, company websites, and local government websites. The server analyzes the HTML structure of each website and scrapes necessary data such as title, publication date, and body text. The input is the generated search query, and the output is the collected raw data.

[0710] Step 4:

[0711] The server filters the data. The server filters the collected raw data and extracts information that matches the user's keywords. During filtering, keyword matching is evaluated and duplicate information is removed. For example, only information containing all of the keywords "press release," "workation," and "local government" is retained. The input is the collected raw data, and the output is the filtered data.

[0712] Step 5:

[0713] The server organizes the data. The server categorizes the filtered data by organization and by publication date. For example, information released by the Tokyo Metropolitan Government on April 1, 2023, regarding the promotion of workation would be classified in the format "Tokyo Metropolitan Government / April 1, 2023 / Workation Promotion Announcement". The input is filtered data, and the output is organized data.

[0714] Step 6:

[0715] The terminal visualizes and exports data. The terminal exports the organized data in spreadsheet format (.csv or .xlsx) and generates and displays various graphs (bar graphs, pie charts, line graphs, etc.) according to user requests. For example, it can display the number of workation promotion projects for each municipality as a bar graph. The input is organized data, and the output is visualized information and an exported spreadsheet.

[0716] Step 7:

[0717] The emotion engine recognizes the user's emotions. The emotion engine analyzes the user's input, operation history, and operation speed to determine whether the user is excited, calm, or stressed. The input is the user's operation data, and the output is the recognized emotional state.

[0718] Step 8:

[0719] The server adjusts the priority of search results based on emotions. Based on the recognized emotions, the server makes adjustments, for example, prioritizing simple and intuitive search results if the user is stressed. The input is the recognized emotional state, and the output is the adjusted search results.

[0720] Thus, the user begins by entering specific keywords, and the system efficiently delivers information through data collection, filtering, organization, visualization, and sentiment recognition and its application.

[0721] (Application Example 2)

[0722] 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."

[0723] This invention aims to improve the efficiency of information gathering and processing, and particularly in work environments such as logistics centers, there is a need to quickly and efficiently collect and visually display the information that workers need. Furthermore, there is a lack of means to appropriately change the displayed content according to the emotions and state of the workers in order to improve work efficiency. In addition, it is necessary not only to collect information, but also to visualize it in an intuitively understandable format.

[0724] 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 the user to input a specific keyword, means for generating a search query based on the keyword, means for collecting relevant information from multiple information sources on the Internet using the generated search query, means for filtering the collected information and extracting information that matches the keyword, means for organizing the extracted information and categorizing it by category and publication date, means for exporting the organized information in spreadsheet format, means for generating a graph according to the user's request, means for recognizing the user's voice input and generating a search query, means for analyzing the user's emotions from their voice tone and operation speed and changing the search query and display content, and means for displaying the user's operation results on a head-mounted display. This enables rapid collection, organization, and visualization of information. Furthermore, work efficiency is improved by adapting the display content according to the worker's emotions and state.

[0725] A "user" is an entity that uses a system to input keywords and perform operations such as generating search queries and gathering information.

[0726] A "keyword" is a specific word or phrase entered by the user, and it forms the basis for generating a search query.

[0727] A "search query" is a search command constructed based on entered keywords, and is used to collect relevant information from internet sources.

[0728] "Information sources" refer to various websites and databases on the internet from which information is collected using search queries.

[0729] "Filtering" is the process of evaluating whether collected information matches keywords and eliminating unnecessary or duplicate information.

[0730] A "category" is a framework for classifying filtered information, used to organize it based on specific attributes or criteria.

[0731] "Spreadsheet format" refers to a format for exporting organized information as a tab-formatted file (e.g., .csv or .xlsx).

[0732] A "graph" is a tool for visually representing data, and includes various formats such as bar graphs, pie charts, and line graphs.

[0733] "Speech recognition" is a technology that converts speech input by a user into text data and generates search queries based on that data.

[0734] "Sentiment analysis" is a technology that recognizes a user's emotional state based on information such as the user's voice tone and operation speed.

[0735] "Displayed content" refers to organized information and graphs that are visually presented to the user.

[0736] A "head-mounted display" is a device worn on the user's head to display visual information, providing information within the work environment.

[0737] This invention provides a system for improving operational efficiency in logistics centers. The specific program processing of the system, as well as the hardware and software used, are described below.

[0738] System Configuration

[0739] hardware

[0740] A head-mounted display (HMD) is a device worn on the head by workers to display visual information. A specific example is the Microsoft HoloLens.

[0741] Microphone: A device for acquiring voice input and recognizing voice instructions from workers.

[0742] software

[0743] Speech recognition library: Use the speech_recognition library to convert the worker's voice instructions into text data.

[0744] HTTP Request Library: Use the requests library to collect data from multiple sources on the internet.

[0745] Data processing library: Use the pandas library to organize the collected data.

[0746] Data visualization library: Use the matplotlib library to visually display data.

[0747] Sentiment Analysis Model: A model is used to analyze emotions from voice tone and operation speed.

[0748] Program Processing Description

[0749] 1. Voice recognition and keyword input

[0750] The user wears a head-mounted display and uses a microphone to input necessary information and instructions via voice. This voice is then converted into text data through a speech recognition library.

[0751] 2. Generating search queries

[0752] A search query is generated based on keywords obtained as text data. This query is structured in a specified format and forms the basis for information gathering.

[0753] 3. Data Collection

[0754] The server uses the generated search query to collect relevant information from multiple sources on the internet (news sites, official websites, databases, etc.). It uses an HTTP request library to retrieve the information and extracts the necessary data (title, publication date, body text, etc.).

[0755] 4. Filtering and organizing data

[0756] The collected information is filtered based on specified keywords to eliminate unnecessary and duplicate information. Furthermore, a data processing library is used to classify and organize the information by category and publication date.

[0757] 5. Data Visualization

[0758] The organized information is displayed as graphs (bar graphs, pie charts, line graphs, etc.) using a data visualization library. This makes it easier for users to visually grasp the information.

[0759] 6. Sentiment analysis and adjustment of displayed content

[0760] An emotion analysis model analyzes the user's emotional state based on their voice tone and operation speed. If the user is tired, the display content is adjusted accordingly, such as showing only essential information concisely.

[0761] Specific example

[0762] When a user voice-inputs keywords such as "inventory information" or "product receiving and shipping status," the system generates a search query based on these keywords and collects relevant information. At the same time, if the sentiment analysis model detects fatigue from the user's voice tone, it reduces the workload by displaying only essential information.

[0763] Examples of prompts for generative AI models

[0764] Please describe the design of a system that can collect, organize, and visualize "inventory management and receiving / shipping information for a logistics center" in a specified format. Furthermore, please provide a concrete example of an application that includes a function to change the operation method based on the user's emotions.

[0765] As described above, the present invention provides a system that improves work efficiency and optimizes the operation method according to the user's condition.

[0766] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0767] Step 1:

[0768] The user wears a head-mounted display and inputs keywords by voice using a microphone. This voice data is acquired and converted into text data using a speech recognition library. The input is voice data, and the output is text data.

[0769] Specific operation: The user says "inventory information," and the voice is recognized through the microphone. This is then converted into text data, "inventory information," and passed to the system.

[0770] Step 2:

[0771] The terminal generates a search query based on keywords obtained as text data. Specifically, it constructs the keywords in a specified format (e.g., AND search). The input is text data, and the output is a search query.

[0772] Specific operation: Text data "Inventory Information" is entered, and a search query "Inventory Information AND Status" is generated.

[0773] Step 3:

[0774] The server uses the generated search query to collect relevant information from multiple sources. It uses an HTTP request library to retrieve data from news sites, official websites, databases, and other sources on the internet. The input is the search query, and the output is the collected information.

[0775] Specific operation: The search query "Inventory Information AND Status" is executed, and data regarding inventory information and status (e.g., title, publication date, body text) is retrieved from relevant websites.

[0776] Step 4:

[0777] The server filters the collected information and extracts information that matches the keywords. It uses a data processing library to remove unnecessary and duplicate information. The input is the collected information, and the output is the filtered information.

[0778] Specific operation: Information that does not match the criteria or duplicate information is removed from the acquired data.

[0779] Step 5:

[0780] The server organizes the filtered information by category and publication date. It uses a data processing library to classify the information and export it in spreadsheet format. The input is filtered information, and the output is organized data in spreadsheet format.

[0781] Specific operation: Filtered data is categorized by company and publication date, and exported as a .csv file.

[0782] Step 6:

[0783] The terminal generates graphs based on organized information. It uses a data visualization library to create visual graphs (bar graphs, pie charts, line graphs, etc.). Input is data in spreadsheet format, and output is graphs.

[0784] Specific operation: A bar graph showing inventory status is generated from spreadsheet-formatted data and displayed on the HMD screen.

[0785] Step 7:

[0786] The server analyzes the user's emotional state based on their voice tone and operation speed. Using an emotional analysis model, it determines whether the user is tired, etc. The input is voice tone and operation speed, and the output is the emotional state.

[0787] Specific behavior: If the user's voice tone is low and their operation speed is slow, the system analyzes that the user is fatigued.

[0788] Step 8:

[0789] The server adjusts the displayed content based on the analyzed emotional state. If fatigue is detected, the system displays only essential information concisely. The input is the emotional state, and the output is the adjusted display content.

[0790] Specific action: When the user is fatigued, only the essential inventory information is highlighted on the screen.

[0791] The above outlines the specific processing steps of the system program that implements the application example.

[0792] 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.

[0793] 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.

[0794] 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.

[0795] [Third Embodiment]

[0796] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0797] 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.

[0798] 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).

[0799] 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.

[0800] 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.

[0801] 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).

[0802] 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.

[0803] 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.

[0804] 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.

[0805] 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.

[0806] 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.

[0807] 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".

[0808] The system of the present invention allows a user to input specific keywords, generates a search query based on those keywords, and collects, organizes, and visualizes relevant press release information from multiple sources on the internet.

[0809] Program Overview

[0810] User actions

[0811] The user accesses the system using a terminal and enters specific keywords (e.g., "press release," "workation," "local government").

[0812] Generating search queries

[0813] The terminal generates a search query based on the entered keywords. This search query consists of AND searches and specified formats. For example, it might be generated as "Press release AND Workation AND Local government".

[0814] Data collection

[0815] The server uses the generated search query to scrape relevant press release information from multiple specified sources (news sites, company websites, local government websites, etc.). During scraping, it analyzes the HTML structure of each website and extracts the necessary data (title, publication date, body text, etc.).

[0816] Data filtering

[0817] The server filters the collected information and extracts press releases that match the user's keywords. This filtering includes evaluating keyword relevance and eliminating duplicate information.

[0818] Data organization

[0819] The server organizes the filtered data. This organization process categorizes the information by company, local government, and publication date. For example, press releases from a particular local government on a specific date might be grouped into a single category.

[0820] Data output and visualization

[0821] The terminal exports the organized data received from the server in spreadsheet format (.csv or .xlsx). It also generates various graphs (bar graphs, pie charts, line graphs, etc.) upon user request, visually displaying the data.

[0822] Specific example

[0823] User actions

[0824] The user enters the keywords "press release workation local government" into the system.

[0825] Generating search queries

[0826] The device generates a search query: "Press release AND workation AND local government".

[0827] Data collection

[0828] The server uses this search query to collect press release information from news sites and official websites. For example, the server retrieves the following information:

[0829] Local government: Tokyo Metropolitan Government

[0830] Title: Announcement of Workation Promotion

[0831] Announcement date: April 1, 2023

[0832] Data filtering

[0833] The server extracts only the information containing all of the following: "press release," "workation," and "local government." Duplicate information is also removed.

[0834] Data organization

[0835] The server organizes the filtered data by prefecture and classifies it into categories such as "Tokyo," "April 1, 2023," and "Announcement of Workation Promotion."

[0836] Data output and visualization

[0837] The device exports the organized data in spreadsheet format. It also displays the number of workation promotion projects for each municipality as a bar graph.

[0838] Thus, the system of the present invention automates the entire process from information gathering to organization and visualization, supporting users in efficiently creating project proposals and presentation materials.

[0839] The following describes the processing flow.

[0840] Step 1:

[0841] The user enters specific keywords using their device. For example, they might enter "press release workation local government".

[0842] Step 2:

[0843] The terminal generates a search query based on the entered keywords. It is structured in the form of "Press release AND Workation AND Local government".

[0844] Step 3:

[0845] The server uses a generated search query to scrape relevant press release information from multiple specified sources. Information is retrieved from news sites, company websites, and local government websites.

[0846] Step 4:

[0847] The server analyzes the information collected via scraping, extracting the title, publication date, and text from the document. It also analyzes the HTML structure to extract the necessary data.

[0848] Step 5:

[0849] The server filters the collected information. It extracts only information that includes all of the following: "press releases," "workation," and "local government," eliminating unnecessary information and spam.

[0850] Step 6:

[0851] The server organizes the filtered information. The information is categorized by company, local government, and publication date. For example, press releases from Tokyo on April 1, 2023, are grouped into a single category.

[0852] Step 7:

[0853] The server eliminates duplicate press release information. If the same press release is collected multiple times, it combines them into one and removes the duplicates.

[0854] Step 8:

[0855] The terminal exports the organized data received from the server in spreadsheet format (.csv or .xlsx). This allows the user to download and use it.

[0856] Step 9:

[0857] The device generates various graphs (bar graphs, pie charts, line graphs, etc.) in response to user requests, visually displaying data. For example, it can display the number of announced workation projects per month as a bar graph.

[0858] Step 10:

[0859] Users create project proposals and presentation materials based on exported data and generated graphs. They utilize the data to analyze the trends of competitors and local governments and make effective proposals.

[0860] (Example 1)

[0861] 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."

[0862] Traditional information gathering systems struggled to efficiently collect, organize, and visualize information related to specific keywords from multiple sources on the internet, requiring users to expend considerable time and effort. Furthermore, the elimination of duplicate information and data visualization were not automated, necessitating manual processing.

[0863] 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.

[0864] In this invention, the server includes means for a user to input a specific keyword, means for generating a search query based on the keyword, means for collecting relevant information from multiple information sources on the internet using the generated search query, means for filtering the collected information and extracting information that matches the keyword, means for organizing the extracted information and categorizing it by organization, administrative division, and date and time, means for exporting the organized information in spreadsheet software format, and means for generating charts and graphs according to the user's request. This automates a series of tasks from information collection to organization and visualization, enabling the user to efficiently obtain the necessary information.

[0865] "User" refers to a person who uses this system.

[0866] A "keyword" refers to a specific word or phrase that a user enters to search for information.

[0867] A "search query" refers to a string of characters that represents a specific command to search for information from internet sources, generated based on keywords.

[0868] "Information source" refers to a place where information exists, such as websites or databases on the internet.

[0869] "Filtering" refers to the process of selecting information that matches specific criteria from collected data.

[0870] "Categorization" refers to classifying collected and filtered information based on specific criteria (e.g., organization, administrative division, date and time).

[0871] "Spreadsheet format" refers to a format for electronically managing and analyzing information (e.g., .csv or .xlsx).

[0872] "Charts and graphs" refer to graphs and charts (e.g., bar graphs, pie charts, line graphs) used to visually represent data.

[0873] The system of the present invention enables efficient information collection, organization, and visualization through a complex configuration including users, terminals, and servers.

[0874] System Configuration

[0875] User actions

[0876] The user accesses the system using a device (e.g., a PC or smartphone) and enters specific keywords (e.g., "press release," "workation," "local government"). The device uses an input device such as a keyboard or touchscreen.

[0877] Generating search queries

[0878] The device retrieves the keywords entered by the user and converts them into an AND search query. This query is generated in the format of "press release AND workation AND local government".

[0879] Start of data collection

[0880] The server receives the generated search query and initiates access to the specified information sources (such as news sites, company websites, and local government websites). In this process, the server refers to a list of URLs for each information source and uses the search query to extract relevant information.

[0881] scraping

[0882] The server uses the Python BeautifulSoup library to parse the HTML of each information source and extract necessary data such as "title," "publication date," and "body text."

[0883] Specifically, the following information will be obtained:

[0884] Local government: Tokyo Metropolitan Government

[0885] Title: Announcement of Workation Promotion

[0886] Announcement date: April 1, 2023

[0887] Data filtering

[0888] The server filters the retrieved data. Here, it extracts only the information that exactly matches the search query and eliminates duplicate data.

[0889] Data organization

[0890] The server organizes the filtered data. The organized data is then categorized by organization, administrative division, and date. For example, the server creates categories such as "Tokyo Metropolitan Government," "April 1, 2023," and "Announcement of Workation Promotion," and groups related data together.

[0891] Data Output

[0892] The server sends the organized data to the terminal, and the terminal provides a function to export it in spreadsheet format (.csv or .xlsx).

[0893] Visualization

[0894] The device visualizes organized data according to user requests. It generates and displays bar graphs, pie charts, line graphs, and other visual representations. For example, it can display the number of workation promotion projects for each municipality as a bar graph.

[0895] Example of a prompt

[0896] "Design a system that collects, organizes, and visualizes press release information from multiple online sources based on a specific keyword input. Explain the entire process, from generating search queries based on the user's keywords, to collecting and filtering data from the sources, and finally organizing and visualizing the data."

[0897] Thus, the system of the present invention automatically collects, organizes, and visualizes relevant information simply by the user entering specific keywords, enabling the user to efficiently acquire and utilize the necessary information.

[0898] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0899] Step 1:

[0900] The user accesses the system using a terminal and enters a specific keyword.

[0901] Input: Specific keywords (e.g., "press release", "workation", "local government")

[0902] Output: Set of entered keywords

[0903] Specific action: The user enters a keyword into the text box and presses the "Search" button.

[0904] Step 2:

[0905] The terminal retrieves the entered keyword and generates a search query based on it.

[0906] Input: A set of keywords entered by the user.

[0907] Output: Search query (Example: "Press release AND workation AND local government")

[0908] Specific operation: The terminal converts the entered keyword into a string in AND search format.

[0909] Step 3:

[0910] The server receives the generated search query and initiates access to the specified information source.

[0911] Input: Generated search query, list of URLs for the source.

[0912] Output: HTML data to be collected

[0913] Specific operation: The server visits the URLs of each information source and retrieves the HTML data of the pages that match the search query.

[0914] Step 4:

[0915] The server performs scraping by analyzing the HTML of each information source and extracting the necessary data.

[0916] Input: HTML data to be collected

[0917] Output: Extracted information (e.g., "Title", "Publication Date", "Text")

[0918] Specific operation: The server uses the Python BeautifulSoup library to extract the title, publication date, and body text from the HTML.

[0919] Step 5:

[0920] The server filters the retrieved data, extracting only the information that exactly matches the search query.

[0921] Input: Set of extracted information

[0922] Output: Set of filtered information

[0923] Specific operation: The server evaluates the degree of matching with the search query and eliminates mismatched or duplicate information.

[0924] Step 6:

[0925] The server organizes the filtered data and classifies it by organization, administrative division, and date / time.

[0926] Input: A set of filtered information

[0927] Output: Set of classified information

[0928] Specific operation: The server categorizes data based on specific criteria and registers it in the database.

[0929] Step 7:

[0930] The server sends the organized data to the terminal, which then exports it in spreadsheet format.

[0931] Input: Set of classified information

[0932] Output: Spreadsheet file format (.csv or .xlsx)

[0933] Specific operation: The server sends the classified data to the terminal in JSON format, and the terminal converts and exports it in CSV or XLSX format.

[0934] Step 8:

[0935] The device visualizes organized data in response to user requests.

[0936] Input: Set of classified information

[0937] Output: Visualized data (e.g., bar graph, pie chart, line graph)

[0938] Specific operation: If the user requests data visualization, the device uses a visualization library to generate a graph and display it on the screen.

[0939] (Application Example 1)

[0940] 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."

[0941] Traditional information gathering systems required users to manually search for specific information and verify related information one by one from numerous sources, which presented significant challenges in terms of effort and time. Furthermore, organizing and visualizing the collected information was also done manually, resulting in problems such as data duplication and redundancy. In advertising operations in particular, timely information gathering and analysis are crucial, and an efficient system for this purpose was needed.

[0942] 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.

[0943] In this invention, the server includes means for a user to input a specific keyword, means for generating a search query based on the keyword, means for collecting relevant information from multiple information sources on the internet using the generated search query, means for filtering the collected information and extracting information that matches the keyword, means for organizing the extracted information and categorizing it by organization and presentation time, means for exporting the organized information in a calculation processing table format, means for generating data visualizations such as bar graphs, pie charts, and line graphs in response to the user's request, and means for inputting the generated graph information as prompt text into a generation AI model for further detailed analysis. This enables users to efficiently collect, organize, and visualize information, particularly enabling timely information analysis and strategic planning in advertising operations.

[0944] A "user" is an individual or group that uses the system to search for and analyze specific information.

[0945] A "keyword" is a word or phrase that a user enters when searching for specific information.

[0946] A "search query" is a search command generated based on keywords to retrieve specific information.

[0947] "Information sources" refer to websites and databases where information is publicly available, such as news portals, official organizations' websites, and public databases.

[0948] "Filtering" is the process of removing duplicate information from collected data and extracting information that matches keywords.

[0949] "Categorization" is the process of classifying extracted information based on specific criteria (for example, by organization, by presentation time).

[0950] A "calculation processing table" is a tabular document, such as Excel or CSV, used to organize and visually display data.

[0951] "Data visualization" is the process of visually displaying collected data in formats such as bar graphs, pie charts, and line graphs.

[0952] A "prompt statement" is a set of instructions given to a generating AI model for analysis and processing.

[0953] A "generative AI model" is a computer program that uses artificial intelligence technology to perform advanced analysis and processing based on input prompt sentences.

[0954]

[0955] The present invention is implemented as an information gathering and analysis system. This system has the function of allowing a user to input specific keywords, generating search queries based on those keywords, and collecting, organizing, and visualizing relevant information from multiple sources on the internet.

[0956] First, the user accesses the system using a terminal and enters specific keywords (e.g., "new product announcement," "campaign," "social media"). The terminal generates a search query based on the entered keywords. This search query consists of AND searches and a specified format. For example, it might be generated as "new product announcement AND campaign AND social media."

[0957] Next, the server uses the generated search query to collect information from multiple sources on the internet (news portals, official organization websites, public databases, etc.). During collection, the server analyzes the HTML structure of each website and extracts the necessary data (title, publication date, content, etc.).

[0958] The extracted information is filtered to extract only the information that matches the keywords and eliminate duplicate information. Then, the filtered data is organized and categorized by organization and presentation time.

[0959] The organized information can be exported as a calculation processing table (.csv or .xlsx format) upon user request. The data can also be visualized using bar graphs, pie charts, line graphs, and other methods. Furthermore, the generated graph information is input into the AI ​​model as prompt text for more detailed analysis.

[0960] The hardware used includes common PCs and smartphones, and the software used includes Python 3.x, BeautifulSoup, requests, Pandas, and Matplotlib. Python 3.x is used as the overall program framework, BeautifulSoup is used for HTML parsing, requests for web requests, Pandas for data frame manipulation, and Matplotlib for data visualization.

[0961] As a concrete example, consider a case where an advertising agency representative enters the keywords "new product launch campaign social media" into the app. In this case, the server collects relevant campaign information from news portals and the organization's official website, and then organizes and filters it. As a result, data containing information such as "a certain organization new product launch campaign (October 1, 2023)" is organized and output as a report in PDF or CSV format.

[0962] As an example of a prompt, the following can be entered into the generative AI model:

[0963] "Users enter keywords such as 'new product launch campaign social media,' and the system collects, filters, organizes, and visualizes relevant information, displaying it in spreadsheet and graph formats."

[0964] Thus, the system of the present invention enables users to efficiently collect, organize, and visualize information, and in particular, enables timely information analysis and strategic planning in advertising operations.

[0965] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0966] Step 1:

[0967] A user accesses the system using a terminal and enters specific keywords. These keywords may include multiple words or phrases, such as "new product announcement," "campaign," or "social media." The input data consists of these keywords, which are then passed to the search query generation phase as output.

[0968] Step 2:

[0969] The terminal generates a search query based on the entered keywords. This search query is composed of AND searches or specified formats, such as "New product announcement AND campaign AND social media". The input data is the keywords, and the output data is the generated search query.

[0970] Step 3:

[0971] The server uses the generated search query to collect information from multiple sources on the internet. Specifically, it retrieves HTML data from news portals, official organizational websites, public databases, etc., and parses the HTML structure using BeautifulSoup. The input data is the search query, and the output data is the collected HTML data.

[0972] Step 4:

[0973] The server filters the collected information. Specifically, it organizes it as a data frame using Pandas, extracts only the information that matches the keywords, and eliminates duplicate information. The input data is HTML data, and the output data is the filtered information.

[0974] Step 5:

[0975] The server organizes the filtered information and categorizes it by organization and presentation time. This makes it easier for users to view information according to specific criteria. The input data is filtered information, and the output data is categorized information.

[0976] Step 6:

[0977] The terminal exports the organized information as a calculation spreadsheet (.csv or .xlsx format) upon user request. The input data is categorized information, and the output data is a spreadsheet file.

[0978] Step 7:

[0979] The terminal also generates data visualizations such as bar graphs, pie charts, and line graphs in response to user requests. It uses Matplotlib to visually display the data. The input data is categorized information, and the output data is visualized data in graph format.

[0980] Step 8:

[0981] The terminal inputs the generated graph information as a prompt into the generating AI model for further detailed analysis. The input data is graph information, and the output data is the AI ​​analysis result. For example, the prompt "The user enters the keywords 'new product announcement campaign social media', and the AI ​​model should collect, filter, organize, and visualize the relevant information and display it in spreadsheet and graph format." is input into the generating AI model.

[0982] 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.

[0983] The present invention is a system that allows a user to input specific keywords, generates search queries based on those keywords, and collects, organizes, and visualizes relevant press release information from multiple sources on the internet. Furthermore, it includes a function to recognize the user's emotions and perform actions based on those emotions.

[0984] Program Overview

[0985] User actions

[0986] The user accesses the system using a terminal and enters specific keywords (e.g., "press release," "workation," "local government").

[0987] Generating search queries

[0988] The terminal generates a search query based on the entered keywords. This search query consists of AND searches and specified formats. For example, it might be generated as "Press release AND Workation AND Local government".

[0989] Data collection

[0990] The server uses the generated search query to scrape relevant press release information from multiple specified sources (news sites, company websites, local government websites, etc.). During scraping, it analyzes the HTML structure of each website and extracts the necessary data (title, publication date, body text, etc.).

[0991] Data filtering

[0992] The server filters the collected information and extracts press releases that match the user's keywords. This filtering includes evaluating keyword relevance and eliminating duplicate information.

[0993] Data organization

[0994] The server organizes the filtered data. This organization process categorizes the information by company, local government, and publication date. For example, press releases from a particular local government on a specific date might be grouped into a single category.

[0995] Data output and visualization

[0996] The terminal exports the organized data received from the server in spreadsheet format (.csv or .xlsx). It also generates various graphs (bar graphs, pie charts, line graphs, etc.) upon user request, visually displaying the data.

[0997] Embedding an emotion engine

[0998] emotion recognition

[0999] The emotion engine analyzes the user's emotions based on keywords entered, operation history, language used, and operation speed. Using emotion analysis technology, it recognizes whether the user is excited, calm, or stressed.

[1000] Prioritizing search results based on emotions

[1001] The server dynamically adjusts the priority of search results based on the perceived emotions of the user. For example, if the user is feeling stressed, it prioritizes displaying simpler and more intuitive search results.

[1002] Recommendations for proposal materials based on emotions

[1003] The emotion engine recommends the structure of proposals and project plans based on the user's emotions. For example, if the user is excited, it will recommend more detailed and specific materials, while if the user is calm, it will recommend concise and to the point.

[1004] Specific example

[1005] User actions

[1006] The user enters the keywords "press release workation local government" into the system.

[1007] Generating search queries

[1008] The device generates a search query: "Press release AND workation AND local government".

[1009] Data collection

[1010] The server uses this search query to collect press release information from news sites and official websites. For example, the server retrieves the following information:

[1011] Local government: Tokyo Metropolitan Government

[1012] Title: Announcement of Workation Promotion

[1013] Announcement date: April 1, 2023

[1014] Data filtering

[1015] The server extracts only the information containing all of the following: "press release," "workation," and "local government." Duplicate information is also removed.

[1016] Data organization

[1017] The server organizes the filtered data by prefecture and classifies it into categories such as "Tokyo," "April 1, 2023," and "Announcement of Workation Promotion."

[1018] Data output and visualization

[1019] The device exports the organized data in spreadsheet format. It also displays the number of workation promotion projects for each municipality as a bar graph.

[1020] Emotion Recognition and Application

[1021] While the user is interacting with the system, the emotion engine recognizes the user's emotions based on their interaction speed and input. For example, if the system detects that the user is excited, the server prioritizes displaying more detailed search results. Furthermore, the emotion engine recommends an appropriate structure for the proposal materials based on the user's emotions.

[1022] Thus, the system of the present invention automates the entire process from information gathering and organization to visualization and adjustment of operations based on user emotions, supporting users in efficiently creating project proposals and presentation materials.

[1023] The following describes the processing flow.

[1024] Step 1:

[1025] The user accesses the system using a device and enters specific keywords (e.g., "press release workation local government").

[1026] Step 2:

[1027] The device generates a search query based on keywords entered by the user. This search query is constructed in a format such as "press release AND workation AND local government".

[1028] Step 3:

[1029] The server uses generated search queries to scrape relevant press release information from multiple sources, including news sites, company websites, and local government websites. Specifically, it analyzes the HTML structure of each website and extracts the necessary data (title, publication date, body text, etc.).

[1030] Step 4:

[1031] The server analyzes the data collected via scraping and filters out press release information that matches the aforementioned keywords. Here, the degree of keyword matching is evaluated, and duplicate information is eliminated.

[1032] Step 5:

[1033] The server categorizes filtered data by company, local government, and announcement date. For example, press releases from Tokyo on April 1, 2023, are grouped together under a single category.

[1034] Step 6:

[1035] The server sends the organized data to the terminal, and the terminal then presents the user with the option to export it in spreadsheet format (.csv or .xlsx).

[1036] Step 7:

[1037] The device generates various graphs (bar graphs, pie charts, line graphs, etc.) in response to user requests, visually displaying data. For example, it can display the number of announced workation projects per month as a bar graph.

[1038] Step 8:

[1039] The emotion engine recognizes the user's emotions from the keywords and operation history they input. For example, it analyzes the user's emotions from the speed and intensity of their input, as well as their choice of words.

[1040] Step 9:

[1041] Emotion recognition allows the server to dynamically adjust the priority of search results based on the user's emotions. For example, if a user is feeling stressed, concise and summarized information will be prioritized.

[1042] Step 10:

[1043] The emotion engine provides a feature that recommends the structure of proposal materials based on the user's emotions. For example, if the user indicates an optimistic mood, it will recommend proposal materials that include detailed and positive content.

[1044] Step 11:

[1045] Users create project proposals and presentations based on exported data, generated graphs, and recommendations from the provided materials. This allows users to efficiently analyze the trends of competitors and local governments and make effective proposals.

[1046] (Example 2)

[1047] 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."

[1048] In modern society, a vast amount of information circulates on the internet, making it a challenge for users to quickly and accurately obtain the information they need. Especially with formalized information such as press releases, it is necessary to efficiently collect related information, avoid duplication, and organize it visually. Furthermore, appropriately adjusting results in response to changes in the user's emotions during the process to reduce user burden is also a crucial challenge.

[1049] The specific processing performed by the specific 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 the user to input specific keywords, means for generating a search query based on the keywords, means for collecting relevant information from multiple information sources on the Internet using the generated search query, means for filtering the collected information and extracting information that matches the keywords, means for organizing the extracted information and categorizing it by organization and publication date, means for exporting the organized information in spreadsheet format, means for generating various graphs according to the user's request, means for recognizing emotions from the user's operation history and operation speed, and means for adjusting the priority of search results based on the recognized emotions. As a result, the user can quickly and accurately obtain what they need from a large amount of information, organize and visualize it, and be provided with appropriate information according to their emotions.

[1050] A "user" is a person or agent who accesses the system and searches for and uses information by entering specific keywords.

[1051] A "keyword" is a word or phrase that a user enters to search for specific information.

[1052] A "search query" is a string of characters constructed based on entered keywords, used to search for information sources on the internet.

[1053] "Information sources" refer to multiple resources on the internet, such as websites and databases, from which information is collected.

[1054] "Filtering" is the process of selecting information that matches the user's keywords from collected data and eliminating duplicate or unnecessary data.

[1055] "Categorization" is the act of classifying organized information based on specific criteria (e.g., by organization, by publication date).

[1056] "Spreadsheet format" refers to a file format for displaying and saving data in a table format, and generally refers to .csv or .xlsx files.

[1057] A "graph" is a visual representation of data and comes in various forms, such as bar graphs, pie charts, and line graphs.

[1058] "Emotion recognition" is the process of analyzing data such as the user's operation history and operation speed to determine the user's emotional state (e.g., excitement, calmness, stress).

[1059] "Search result prioritization" refers to the act of dynamically changing the order in which search results are displayed based on the perceived emotions of the user.

[1060] This invention is a system that allows a user to input specific keywords, generates search queries based on those keywords, and collects, organizes, and visualizes relevant information from multiple sources on the internet. It also includes a function to recognize the user's emotions and adjust the priority of search results based on those emotions.

[1061] The specific embodiment of this system is configured as follows:

[1062] 1. Enter keywords

[1063] The user accesses the system using a device and enters the keywords they want to search for. Examples of keywords include "press release," "workation," and "local government."

[1064] 2. Generating search queries

[1065] The terminal generates an appropriate search query based on the keywords entered by the user. This search query is in the form of keywords concatenated with the AND operator (e.g., "press release AND workation AND local government").

[1066] 3. Data Collection

[1067] The server uses the generated search query to collect relevant information from multiple specified information sources (such as news sites, company websites, and local government websites). Specifically, the server analyzes the HTML structure of each website and scrapes the necessary data.

[1068] 4. Data filtering

[1069] The server filters the collected information and extracts information that matches the user's keywords. This filtering process includes evaluating the degree of keyword relevance and eliminating duplicate information.

[1070] 5. Data organization

[1071] The server organizes the filtered information and categorizes it by organization or publication date. For example, it might group press releases issued by a local government on a specific date into a single category.

[1072] 6. Data Output and Visualization

[1073] The terminal exports the organized data received from the server in spreadsheet format (.csv or .xlsx), and also generates and displays various graphs (bar graphs, pie charts, line graphs, etc.) according to the user's request.

[1074] 7. Emotion recognition

[1075] The emotion engine analyzes the user's input, operation history, and operation speed to determine the user's emotions (excitement, calmness, stress, etc.).

[1076] 8. Prioritizing search results

[1077] The server dynamically adjusts the priority of search results based on the perceived emotions of the user. For example, if the user is feeling stressed, it prioritizes displaying simpler and more intuitive search results.

[1078] 9. Specific Examples

[1079] When a user enters the keywords "press release workation local government," the device generates a search query "press release AND workation AND local government." The server uses this search query to collect the following information from news sites and official websites:

[1080] Local government: Tokyo Metropolitan Government

[1081] Title: Announcement of Workation Promotion

[1082] Announcement date: April 1, 2023

[1083] The server filters this information, removes duplicates, and organizes it by prefecture and announcement date. The terminal provides this organized information to the user in spreadsheet and graph format. Furthermore, the emotion engine recognizes the user's emotions while they are using the device, and if it determines that the user is excited, it prioritizes displaying detailed information at a faster pace.

[1084] Example of a prompt:

[1085] "Enter specific keywords (e.g., 'press release,' 'workation,' 'local government') to collect and visualize relevant information. Export the collected information in spreadsheet format and display the data for each organization as a bar graph. Also, adjust the search results based on user sentiment."

[1086] Thus, by using the system of the present invention, users can quickly and accurately obtain the necessary data from a vast amount of information, and further organize and analyze it visually. In addition, it becomes possible to provide information flexibly in accordance with the user's emotions, thereby improving usability.

[1087] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1088] Step 1:

[1089] The user enters specific keywords. The user accesses the system using a terminal and enters the keywords they want to search for (e.g., "press release," "workation," "local government"). The input data is a list of keywords in text format.

[1090] Step 2:

[1091] The terminal generates a search query. Based on the entered keywords, the terminal generates a search query using the AND operator. For example, "press release AND workation AND local government". This query is used to search for information sources on the internet. The input is a list of keywords from the user, and the output is the generated search query.

[1092] Step 3:

[1093] The server collects relevant information. Using the generated search query, the server collects information from multiple sources, such as news sites, company websites, and local government websites. The server analyzes the HTML structure of each website and scrapes necessary data such as title, publication date, and body text. The input is the generated search query, and the output is the collected raw data.

[1094] Step 4:

[1095] The server filters the data. The server filters the collected raw data and extracts information that matches the user's keywords. During filtering, keyword matching is evaluated and duplicate information is removed. For example, only information containing all of the keywords "press release," "workation," and "local government" is retained. The input is the collected raw data, and the output is the filtered data.

[1096] Step 5:

[1097] The server organizes the data. The server categorizes the filtered data by organization and by publication date. For example, information released by the Tokyo Metropolitan Government on April 1, 2023, regarding the promotion of workation would be classified in the format "Tokyo Metropolitan Government / April 1, 2023 / Workation Promotion Announcement". The input is filtered data, and the output is organized data.

[1098] Step 6:

[1099] The terminal visualizes and exports data. The terminal exports the organized data in spreadsheet format (.csv or .xlsx) and generates and displays various graphs (bar graphs, pie charts, line graphs, etc.) according to user requests. For example, it can display the number of workation promotion projects for each municipality as a bar graph. The input is organized data, and the output is visualized information and an exported spreadsheet.

[1100] Step 7:

[1101] The emotion engine recognizes the user's emotions. The emotion engine analyzes the user's input, operation history, and operation speed to determine whether the user is excited, calm, or stressed. The input is the user's operation data, and the output is the recognized emotional state.

[1102] Step 8:

[1103] The server adjusts the priority of search results based on emotions. Based on the recognized emotions, the server makes adjustments, for example, prioritizing simple and intuitive search results if the user is stressed. The input is the recognized emotional state, and the output is the adjusted search results.

[1104] Thus, the user begins by entering specific keywords, and the system efficiently delivers information through data collection, filtering, organization, visualization, and sentiment recognition and its application.

[1105] (Application Example 2)

[1106] 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."

[1107] This invention aims to improve the efficiency of information gathering and processing, and particularly in work environments such as logistics centers, there is a need to quickly and efficiently collect and visually display the information that workers need. Furthermore, there is a lack of means to appropriately change the displayed content according to the emotions and state of the workers in order to improve work efficiency. In addition, it is necessary not only to collect information, but also to visualize it in an intuitively understandable format.

[1108] 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 the user to input a specific keyword, means for generating a search query based on the keyword, means for collecting relevant information from multiple information sources on the Internet using the generated search query, means for filtering the collected information and extracting information that matches the keyword, means for organizing the extracted information and categorizing it by category and publication date, means for exporting the organized information in spreadsheet format, means for generating a graph according to the user's request, means for recognizing the user's voice input and generating a search query, means for analyzing the user's emotions from their voice tone and operation speed and changing the search query and display content, and means for displaying the user's operation results on a head-mounted display. This enables rapid collection, organization, and visualization of information. Furthermore, work efficiency is improved by adapting the display content according to the worker's emotions and state.

[1109] A "user" is an entity that uses a system to input keywords and perform operations such as generating search queries and gathering information.

[1110] A "keyword" is a specific word or phrase entered by the user, and it forms the basis for generating a search query.

[1111] A "search query" is a search command constructed based on entered keywords, and is used to collect relevant information from internet sources.

[1112] "Information sources" refer to various websites and databases on the internet from which information is collected using search queries.

[1113] "Filtering" is the process of evaluating whether collected information matches keywords and eliminating unnecessary or duplicate information.

[1114] A "category" is a framework for classifying filtered information, used to organize it based on specific attributes or criteria.

[1115] "Spreadsheet format" refers to a format for exporting organized information as a tab-formatted file (e.g., .csv or .xlsx).

[1116] A "graph" is a tool for visually representing data, and includes various formats such as bar graphs, pie charts, and line graphs.

[1117] "Speech recognition" is a technology that converts speech input by a user into text data and generates search queries based on that data.

[1118] "Sentiment analysis" is a technology that recognizes a user's emotional state based on information such as the user's voice tone and operation speed.

[1119] "Displayed content" refers to organized information and graphs that are visually presented to the user.

[1120] A "head-mounted display" is a device worn on the user's head to display visual information, providing information within the work environment.

[1121] This invention provides a system for improving operational efficiency in logistics centers. The specific program processing of the system, as well as the hardware and software used, are described below.

[1122] System Configuration

[1123] hardware

[1124] A head-mounted display (HMD) is a device worn on the head by workers to display visual information. A specific example is the Microsoft HoloLens.

[1125] Microphone: A device for acquiring voice input and recognizing voice instructions from workers.

[1126] software

[1127] Speech recognition library: Use the speech_recognition library to convert the worker's voice instructions into text data.

[1128] HTTP Request Library: Use the requests library to collect data from multiple sources on the internet.

[1129] Data processing library: Use the pandas library to organize the collected data.

[1130] Data visualization library: Use the matplotlib library to visually display data.

[1131] Sentiment Analysis Model: A model is used to analyze emotions from voice tone and operation speed.

[1132] Program Processing Description

[1133] 1. Voice recognition and keyword input

[1134] The user wears a head-mounted display and uses a microphone to input necessary information and instructions via voice. This voice is then converted into text data through a speech recognition library.

[1135] 2. Generating search queries

[1136] A search query is generated based on keywords obtained as text data. This query is structured in a specified format and forms the basis for information gathering.

[1137] 3. Data Collection

[1138] The server uses the generated search query to collect relevant information from multiple sources on the internet (news sites, official websites, databases, etc.). It uses an HTTP request library to retrieve the information and extracts the necessary data (title, publication date, body text, etc.).

[1139] 4. Filtering and organizing data

[1140] The collected information is filtered based on specified keywords to eliminate unnecessary and duplicate information. Furthermore, a data processing library is used to classify and organize the information by category and publication date.

[1141] 5. Data Visualization

[1142] The organized information is displayed as graphs (bar graphs, pie charts, line graphs, etc.) using a data visualization library. This makes it easier for users to visually grasp the information.

[1143] 6. Sentiment analysis and adjustment of displayed content

[1144] An emotion analysis model analyzes the user's emotional state based on their voice tone and operation speed. If the user is tired, the display content is adjusted accordingly, such as showing only essential information concisely.

[1145] Specific example

[1146] When a user voice-inputs keywords such as "inventory information" or "product receiving and shipping status," the system generates a search query based on these keywords and collects relevant information. At the same time, if the sentiment analysis model detects fatigue from the user's voice tone, it reduces the workload by displaying only essential information.

[1147] Examples of prompts for generative AI models

[1148] Please describe the design of a system that can collect, organize, and visualize "inventory management and receiving / shipping information for a logistics center" in a specified format. Furthermore, please provide a concrete example of an application that includes a function to change the operation method based on the user's emotions.

[1149] As described above, the present invention provides a system that improves work efficiency and optimizes the operation method according to the user's condition.

[1150] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1151] Step 1:

[1152] The user wears a head-mounted display and inputs keywords by voice using a microphone. This voice data is acquired and converted into text data using a speech recognition library. The input is voice data, and the output is text data.

[1153] Specific operation: The user says "inventory information," and the voice is recognized through the microphone. This is then converted into text data, "inventory information," and passed to the system.

[1154] Step 2:

[1155] The terminal generates a search query based on keywords obtained as text data. Specifically, it constructs the keywords in a specified format (e.g., AND search). The input is text data, and the output is a search query.

[1156] Specific operation: Text data "Inventory Information" is entered, and a search query "Inventory Information AND Status" is generated.

[1157] Step 3:

[1158] The server uses the generated search query to collect relevant information from multiple sources. It uses an HTTP request library to retrieve data from news sites, official websites, databases, and other sources on the internet. The input is the search query, and the output is the collected information.

[1159] Specific operation: The search query "Inventory Information AND Status" is executed, and data regarding inventory information and status (e.g., title, publication date, body text) is retrieved from relevant websites.

[1160] Step 4:

[1161] The server filters the collected information and extracts information that matches the keywords. It uses a data processing library to remove unnecessary and duplicate information. The input is the collected information, and the output is the filtered information.

[1162] Specific operation: Information that does not match the criteria or duplicate information is removed from the acquired data.

[1163] Step 5:

[1164] The server organizes the filtered information by category and publication date. It uses a data processing library to classify the information and export it in spreadsheet format. The input is filtered information, and the output is organized data in spreadsheet format.

[1165] Specific operation: Filtered data is categorized by company and publication date, and exported as a .csv file.

[1166] Step 6:

[1167] The terminal generates graphs based on organized information. It uses a data visualization library to create visual graphs (bar graphs, pie charts, line graphs, etc.). Input is data in spreadsheet format, and output is graphs.

[1168] Specific operation: A bar graph showing inventory status is generated from spreadsheet-formatted data and displayed on the HMD screen.

[1169] Step 7:

[1170] The server analyzes the user's emotional state based on their voice tone and operation speed. Using an emotional analysis model, it determines whether the user is tired, etc. The input is voice tone and operation speed, and the output is the emotional state.

[1171] Specific behavior: If the user's voice tone is low and their operation speed is slow, the system analyzes that the user is fatigued.

[1172] Step 8:

[1173] The server adjusts the displayed content based on the analyzed emotional state. If fatigue is detected, the system displays only essential information concisely. The input is the emotional state, and the output is the adjusted display content.

[1174] Specific action: When the user is fatigued, only the essential inventory information is highlighted on the screen.

[1175] The above outlines the specific processing steps of the system program that implements the application example.

[1176] 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.

[1177] 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.

[1178] 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.

[1179] [Fourth Embodiment]

[1180] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1181] 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.

[1182] 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).

[1183] 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.

[1184] 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.

[1185] 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).

[1186] 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.

[1187] 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.

[1188] 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.

[1189] 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.

[1190] 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.

[1191] 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.

[1192] 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".

[1193] The system of the present invention allows a user to input specific keywords, generates a search query based on those keywords, and collects, organizes, and visualizes relevant press release information from multiple sources on the internet.

[1194] Program Overview

[1195] User actions

[1196] The user accesses the system using a terminal and enters specific keywords (e.g., "press release," "workation," "local government").

[1197] Generating search queries

[1198] The terminal generates a search query based on the entered keywords. This search query consists of AND searches and specified formats. For example, it might be generated as "Press release AND Workation AND Local government".

[1199] Data collection

[1200] The server uses the generated search query to scrape relevant press release information from multiple specified sources (news sites, company websites, local government websites, etc.). During scraping, it analyzes the HTML structure of each website and extracts the necessary data (title, publication date, body text, etc.).

[1201] Data filtering

[1202] The server filters the collected information and extracts press releases that match the user's keywords. This filtering includes evaluating keyword relevance and eliminating duplicate information.

[1203] Data organization

[1204] The server organizes the filtered data. This organization process categorizes the information by company, local government, and publication date. For example, press releases from a particular local government on a specific date might be grouped into a single category.

[1205] Data output and visualization

[1206] The terminal exports the organized data received from the server in spreadsheet format (.csv or .xlsx). It also generates various graphs (bar graphs, pie charts, line graphs, etc.) upon user request, visually displaying the data.

[1207] Specific example

[1208] User actions

[1209] The user enters the keywords "press release workation local government" into the system.

[1210] Generating search queries

[1211] The device generates a search query: "Press release AND workation AND local government".

[1212] Data collection

[1213] The server uses this search query to collect press release information from news sites and official websites. For example, the server retrieves the following information:

[1214] Local government: Tokyo Metropolitan Government

[1215] Title: Announcement of Workation Promotion

[1216] Announcement date: April 1, 2023

[1217] Data filtering

[1218] The server extracts only the information containing all of the following: "press release," "workation," and "local government." Duplicate information is also removed.

[1219] Data organization

[1220] The server organizes the filtered data by prefecture and classifies it into categories such as "Tokyo," "April 1, 2023," and "Announcement of Workation Promotion."

[1221] Data output and visualization

[1222] The device exports the organized data in spreadsheet format. It also displays the number of workation promotion projects for each municipality as a bar graph.

[1223] Thus, the system of the present invention automates the entire process from information gathering to organization and visualization, supporting users in efficiently creating project proposals and presentation materials.

[1224] The following describes the processing flow.

[1225] Step 1:

[1226] The user enters specific keywords using their device. For example, they might enter "press release workation local government".

[1227] Step 2:

[1228] The terminal generates a search query based on the entered keywords. It is structured in the form of "Press release AND Workation AND Local government".

[1229] Step 3:

[1230] The server uses a generated search query to scrape relevant press release information from multiple specified sources. Information is retrieved from news sites, company websites, and local government websites.

[1231] Step 4:

[1232] The server analyzes the information collected via scraping, extracting the title, publication date, and text from the document. It also analyzes the HTML structure to extract the necessary data.

[1233] Step 5:

[1234] The server filters the collected information. It extracts only information that includes all of the following: "press releases," "workation," and "local government," eliminating unnecessary information and spam.

[1235] Step 6:

[1236] The server organizes the filtered information. The information is categorized by company, local government, and publication date. For example, press releases from Tokyo on April 1, 2023, are grouped into a single category.

[1237] Step 7:

[1238] The server eliminates duplicate press release information. If the same press release is collected multiple times, it combines them into one and removes the duplicates.

[1239] Step 8:

[1240] The terminal exports the organized data received from the server in spreadsheet format (.csv or .xlsx). This allows the user to download and use it.

[1241] Step 9:

[1242] The device generates various graphs (bar graphs, pie charts, line graphs, etc.) in response to user requests, visually displaying data. For example, it can display the number of announced workation projects per month as a bar graph.

[1243] Step 10:

[1244] Users create project proposals and presentation materials based on exported data and generated graphs. They utilize the data to analyze the trends of competitors and local governments and make effective proposals.

[1245] (Example 1)

[1246] 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".

[1247] Traditional information gathering systems struggled to efficiently collect, organize, and visualize information related to specific keywords from multiple sources on the internet, requiring users to expend considerable time and effort. Furthermore, the elimination of duplicate information and data visualization were not automated, necessitating manual processing.

[1248] 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.

[1249] In this invention, the server includes means for a user to input a specific keyword, means for generating a search query based on the keyword, means for collecting relevant information from multiple information sources on the internet using the generated search query, means for filtering the collected information and extracting information that matches the keyword, means for organizing the extracted information and categorizing it by organization, administrative division, and date and time, means for exporting the organized information in spreadsheet software format, and means for generating charts and graphs according to the user's request. This automates a series of tasks from information collection to organization and visualization, enabling the user to efficiently obtain the necessary information.

[1250] "User" refers to a person who uses this system.

[1251] A "keyword" refers to a specific word or phrase that a user enters to search for information.

[1252] A "search query" refers to a string of characters that represents a specific command to search for information from internet sources, generated based on keywords.

[1253] "Information source" refers to a place where information exists, such as websites or databases on the internet.

[1254] "Filtering" refers to the process of selecting information that matches specific criteria from collected data.

[1255] "Categorization" refers to classifying collected and filtered information based on specific criteria (e.g., organization, administrative division, date and time).

[1256] "Spreadsheet format" refers to a format for electronically managing and analyzing information (e.g., .csv or .xlsx).

[1257] "Charts and graphs" refer to graphs and charts (e.g., bar graphs, pie charts, line graphs) used to visually represent data.

[1258] The system of the present invention enables efficient information collection, organization, and visualization through a complex configuration including users, terminals, and servers.

[1259] System Configuration

[1260] User actions

[1261] The user accesses the system using a device (e.g., a PC or smartphone) and enters specific keywords (e.g., "press release," "workation," "local government"). The device uses an input device such as a keyboard or touchscreen.

[1262] Generating search queries

[1263] The device retrieves the keywords entered by the user and converts them into an AND search query. This query is generated in the format of "press release AND workation AND local government".

[1264] Start of data collection

[1265] The server receives the generated search query and initiates access to the specified information sources (such as news sites, company websites, and local government websites). In this process, the server refers to a list of URLs for each information source and uses the search query to extract relevant information.

[1266] scraping

[1267] The server uses the Python BeautifulSoup library to parse the HTML of each information source and extract necessary data such as "title," "publication date," and "body text."

[1268] Specifically, the following information will be obtained:

[1269] Local government: Tokyo Metropolitan Government

[1270] Title: Announcement of Workation Promotion

[1271] Announcement date: April 1, 2023

[1272] Data filtering

[1273] The server filters the retrieved data. Here, it extracts only the information that exactly matches the search query and eliminates duplicate data.

[1274] Data organization

[1275] The server organizes the filtered data. The organized data is then categorized by organization, administrative division, and date. For example, the server creates categories such as "Tokyo Metropolitan Government," "April 1, 2023," and "Announcement of Workation Promotion," and groups related data together.

[1276] Data Output

[1277] The server sends the organized data to the terminal, and the terminal provides a function to export it in spreadsheet format (.csv or .xlsx).

[1278] Visualization

[1279] The device visualizes organized data according to user requests. It generates and displays bar graphs, pie charts, line graphs, and other visual representations. For example, it can display the number of workation promotion projects for each municipality as a bar graph.

[1280] Example of a prompt

[1281] "Design a system that collects, organizes, and visualizes press release information from multiple online sources based on a specific keyword input. Explain the entire process, from generating search queries based on the user's keywords, to collecting and filtering data from the sources, and finally organizing and visualizing the data."

[1282] Thus, the system of the present invention automatically collects, organizes, and visualizes relevant information simply by the user entering specific keywords, enabling the user to efficiently acquire and utilize the necessary information.

[1283] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1284] Step 1:

[1285] The user accesses the system using a terminal and enters a specific keyword.

[1286] Input: Specific keywords (e.g., "press release", "workation", "local government")

[1287] Output: Set of entered keywords

[1288] Specific action: The user enters a keyword into the text box and presses the "Search" button.

[1289] Step 2:

[1290] The terminal retrieves the entered keyword and generates a search query based on it.

[1291] Input: A set of keywords entered by the user.

[1292] Output: Search query (Example: "Press release AND workation AND local government")

[1293] Specific operation: The terminal converts the entered keyword into a string in AND search format.

[1294] Step 3:

[1295] The server receives the generated search query and initiates access to the specified information source.

[1296] Input: Generated search query, list of URLs for the source.

[1297] Output: HTML data to be collected

[1298] Specific operation: The server visits the URLs of each information source and retrieves the HTML data of the pages that match the search query.

[1299] Step 4:

[1300] The server performs scraping by analyzing the HTML of each information source and extracting the necessary data.

[1301] Input: HTML data to be collected

[1302] Output: Extracted information (e.g., "Title", "Publication Date", "Text")

[1303] Specific operation: The server uses the Python BeautifulSoup library to extract the title, publication date, and body text from the HTML.

[1304] Step 5:

[1305] The server filters the retrieved data, extracting only the information that exactly matches the search query.

[1306] Input: Set of extracted information

[1307] Output: Set of filtered information

[1308] Specific operation: The server evaluates the degree of matching with the search query and eliminates mismatched or duplicate information.

[1309] Step 6:

[1310] The server organizes the filtered data and classifies it by organization, administrative division, and date / time.

[1311] Input: A set of filtered information

[1312] Output: Set of classified information

[1313] Specific operation: The server categorizes data based on specific criteria and registers it in the database.

[1314] Step 7:

[1315] The server sends the organized data to the terminal, which then exports it in spreadsheet format.

[1316] Input: Set of classified information

[1317] Output: Spreadsheet file format (.csv or .xlsx)

[1318] Specific operation: The server sends the classified data to the terminal in JSON format, and the terminal converts and exports it in CSV or XLSX format.

[1319] Step 8:

[1320] The device visualizes organized data in response to user requests.

[1321] Input: Set of classified information

[1322] Output: Visualized data (e.g., bar graph, pie chart, line graph)

[1323] Specific operation: If the user requests data visualization, the device uses a visualization library to generate a graph and display it on the screen.

[1324] (Application Example 1)

[1325] 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".

[1326] Traditional information gathering systems required users to manually search for specific information and verify related information one by one from numerous sources, which presented significant challenges in terms of effort and time. Furthermore, organizing and visualizing the collected information was also done manually, resulting in problems such as data duplication and redundancy. In advertising operations in particular, timely information gathering and analysis are crucial, and an efficient system for this purpose was needed.

[1327] 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.

[1328] In this invention, the server includes means for a user to input a specific keyword, means for generating a search query based on the keyword, means for collecting relevant information from multiple information sources on the internet using the generated search query, means for filtering the collected information and extracting information that matches the keyword, means for organizing the extracted information and categorizing it by organization and presentation time, means for exporting the organized information in a calculation processing table format, means for generating data visualizations such as bar graphs, pie charts, and line graphs in response to the user's request, and means for inputting the generated graph information as prompt text into a generation AI model for further detailed analysis. This enables users to efficiently collect, organize, and visualize information, particularly enabling timely information analysis and strategic planning in advertising operations.

[1329] A "user" is an individual or group that uses the system to search for and analyze specific information.

[1330] A "keyword" is a word or phrase that a user enters when searching for specific information.

[1331] A "search query" is a search command generated based on keywords to retrieve specific information.

[1332] "Information sources" refer to websites and databases where information is publicly available, such as news portals, official organizations' websites, and public databases.

[1333] "Filtering" is the process of removing duplicate information from collected data and extracting information that matches keywords.

[1334] "Categorization" is the process of classifying extracted information based on specific criteria (for example, by organization, by presentation time).

[1335] A "calculation processing table" is a tabular document, such as Excel or CSV, used to organize and visually display data.

[1336] "Data visualization" is the process of visually displaying collected data in formats such as bar graphs, pie charts, and line graphs.

[1337] A "prompt statement" is a set of instructions given to a generating AI model for analysis and processing.

[1338] A "generative AI model" is a computer program that uses artificial intelligence technology to perform advanced analysis and processing based on input prompt sentences.

[1339]

[1340] The present invention is implemented as an information gathering and analysis system. This system has the function of allowing a user to input specific keywords, generating search queries based on those keywords, and collecting, organizing, and visualizing relevant information from multiple sources on the internet.

[1341] First, the user accesses the system using a terminal and enters specific keywords (e.g., "new product announcement," "campaign," "social media"). The terminal generates a search query based on the entered keywords. This search query consists of AND searches and a specified format. For example, it might be generated as "new product announcement AND campaign AND social media."

[1342] Next, the server uses the generated search query to collect information from multiple sources on the internet (news portals, official organization websites, public databases, etc.). During collection, the server analyzes the HTML structure of each website and extracts the necessary data (title, publication date, content, etc.).

[1343] The extracted information is filtered to extract only the information that matches the keywords and eliminate duplicate information. Then, the filtered data is organized and categorized by organization and presentation time.

[1344] The organized information can be exported as a calculation processing table (.csv or .xlsx format) upon user request. The data can also be visualized using bar graphs, pie charts, line graphs, and other methods. Furthermore, the generated graph information is input into the AI ​​model as prompt text for more detailed analysis.

[1345] The hardware used includes common PCs and smartphones, and the software used includes Python 3.x, BeautifulSoup, requests, Pandas, and Matplotlib. Python 3.x is used as the overall program framework, BeautifulSoup is used for HTML parsing, requests for web requests, Pandas for data frame manipulation, and Matplotlib for data visualization.

[1346] As a concrete example, consider a case where an advertising agency representative enters the keywords "new product launch campaign social media" into the app. In this case, the server collects relevant campaign information from news portals and the organization's official website, and then organizes and filters it. As a result, data containing information such as "a certain organization new product launch campaign (October 1, 2023)" is organized and output as a report in PDF or CSV format.

[1347] As an example of a prompt, the following can be entered into the generative AI model:

[1348] "Users enter keywords such as 'new product launch campaign social media,' and the system collects, filters, organizes, and visualizes relevant information, displaying it in spreadsheet and graph formats."

[1349] Thus, the system of the present invention enables users to efficiently collect, organize, and visualize information, and in particular, enables timely information analysis and strategic planning in advertising operations.

[1350] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1351] Step 1:

[1352] A user accesses the system using a terminal and enters specific keywords. These keywords may include multiple words or phrases, such as "new product announcement," "campaign," or "social media." The input data consists of these keywords, which are then passed to the search query generation phase as output.

[1353] Step 2:

[1354] The terminal generates a search query based on the entered keywords. This search query is composed of AND searches or specified formats, such as "New product announcement AND campaign AND social media". The input data is the keywords, and the output data is the generated search query.

[1355] Step 3:

[1356] The server uses the generated search query to collect information from multiple sources on the internet. Specifically, it retrieves HTML data from news portals, official organizational websites, public databases, etc., and parses the HTML structure using BeautifulSoup. The input data is the search query, and the output data is the collected HTML data.

[1357] Step 4:

[1358] The server filters the collected information. Specifically, it organizes it as a data frame using Pandas, extracts only the information that matches the keywords, and eliminates duplicate information. The input data is HTML data, and the output data is the filtered information.

[1359] Step 5:

[1360] The server organizes the filtered information and categorizes it by organization and presentation time. This makes it easier for users to view information according to specific criteria. The input data is filtered information, and the output data is categorized information.

[1361] Step 6:

[1362] The terminal exports the organized information as a calculation spreadsheet (.csv or .xlsx format) upon user request. The input data is categorized information, and the output data is a spreadsheet file.

[1363] Step 7:

[1364] The terminal also generates data visualizations such as bar graphs, pie charts, and line graphs in response to user requests. It uses Matplotlib to visually display the data. The input data is categorized information, and the output data is visualized data in graph format.

[1365] Step 8:

[1366] The terminal inputs the generated graph information as a prompt into the generating AI model for further detailed analysis. The input data is graph information, and the output data is the AI ​​analysis result. For example, the prompt "The user enters the keywords 'new product announcement campaign social media', and the AI ​​model should collect, filter, organize, and visualize the relevant information and display it in spreadsheet and graph format." is input into the generating AI model.

[1367] 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.

[1368] The present invention is a system that allows a user to input specific keywords, generates search queries based on those keywords, and collects, organizes, and visualizes relevant press release information from multiple sources on the internet. Furthermore, it includes a function to recognize the user's emotions and perform actions based on those emotions.

[1369] Program Overview

[1370] User actions

[1371] The user accesses the system using a terminal and enters specific keywords (e.g., "press release," "workation," "local government").

[1372] Generating search queries

[1373] The terminal generates a search query based on the entered keywords. This search query consists of AND searches and specified formats. For example, it might be generated as "Press release AND Workation AND Local government".

[1374] Data collection

[1375] The server uses the generated search query to scrape relevant press release information from multiple specified sources (news sites, company websites, local government websites, etc.). During scraping, it analyzes the HTML structure of each website and extracts the necessary data (title, publication date, body text, etc.).

[1376] Data filtering

[1377] The server filters the collected information and extracts press releases that match the user's keywords. This filtering includes evaluating keyword relevance and eliminating duplicate information.

[1378] Data organization

[1379] The server organizes the filtered data. This organization process categorizes the information by company, local government, and publication date. For example, press releases from a particular local government on a specific date might be grouped into a single category.

[1380] Data output and visualization

[1381] The terminal exports the organized data received from the server in spreadsheet format (.csv or .xlsx). It also generates various graphs (bar graphs, pie charts, line graphs, etc.) upon user request, visually displaying the data.

[1382] Embedding an emotion engine

[1383] emotion recognition

[1384] The emotion engine analyzes the user's emotions based on keywords entered, operation history, language used, and operation speed. Using emotion analysis technology, it recognizes whether the user is excited, calm, or stressed.

[1385] Prioritizing search results based on emotions

[1386] The server dynamically adjusts the priority of search results based on the perceived emotions of the user. For example, if the user is feeling stressed, it prioritizes displaying simpler and more intuitive search results.

[1387] Recommendations for proposal materials based on emotions

[1388] The emotion engine recommends the structure of proposals and project plans based on the user's emotions. For example, if the user is excited, it will recommend more detailed and specific materials, while if the user is calm, it will recommend concise and to the point.

[1389] Specific example

[1390] User actions

[1391] The user enters the keywords "press release workation local government" into the system.

[1392] Generating search queries

[1393] The device generates a search query: "Press release AND workation AND local government".

[1394] Data collection

[1395] The server uses this search query to collect press release information from news sites and official websites. For example, the server retrieves the following information:

[1396] Local government: Tokyo Metropolitan Government

[1397] Title: Announcement of Workation Promotion

[1398] Announcement date: April 1, 2023

[1399] Data filtering

[1400] The server extracts only the information containing all of the following: "press release," "workation," and "local government." Duplicate information is also removed.

[1401] Data organization

[1402] The server organizes the filtered data by prefecture and classifies it into categories such as "Tokyo," "April 1, 2023," and "Announcement of Workation Promotion."

[1403] Data output and visualization

[1404] The device exports the organized data in spreadsheet format. It also displays the number of workation promotion projects for each municipality as a bar graph.

[1405] Emotion Recognition and Application

[1406] While the user is interacting with the system, the emotion engine recognizes the user's emotions based on their interaction speed and input. For example, if the system detects that the user is excited, the server prioritizes displaying more detailed search results. Furthermore, the emotion engine recommends an appropriate structure for the proposal materials based on the user's emotions.

[1407] Thus, the system of the present invention automates the entire process from information gathering and organization to visualization and adjustment of operations based on user emotions, supporting users in efficiently creating project proposals and presentation materials.

[1408] The following describes the processing flow.

[1409] Step 1:

[1410] The user accesses the system using a device and enters specific keywords (e.g., "press release workation local government").

[1411] Step 2:

[1412] The device generates a search query based on keywords entered by the user. This search query is constructed in a format such as "press release AND workation AND local government".

[1413] Step 3:

[1414] The server uses generated search queries to scrape relevant press release information from multiple sources, including news sites, company websites, and local government websites. Specifically, it analyzes the HTML structure of each website and extracts the necessary data (title, publication date, body text, etc.).

[1415] Step 4:

[1416] The server analyzes the data collected via scraping and filters out press release information that matches the aforementioned keywords. Here, the degree of keyword matching is evaluated, and duplicate information is eliminated.

[1417] Step 5:

[1418] The server categorizes filtered data by company, local government, and announcement date. For example, press releases from Tokyo on April 1, 2023, are grouped together under a single category.

[1419] Step 6:

[1420] The server sends the organized data to the terminal, and the terminal then presents the user with the option to export it in spreadsheet format (.csv or .xlsx).

[1421] Step 7:

[1422] The device generates various graphs (bar graphs, pie charts, line graphs, etc.) in response to user requests, visually displaying data. For example, it can display the number of announced workation projects per month as a bar graph.

[1423] Step 8:

[1424] The emotion engine recognizes the user's emotions from the keywords and operation history they input. For example, it analyzes the user's emotions from the speed and intensity of their input, as well as their choice of words.

[1425] Step 9:

[1426] Emotion recognition allows the server to dynamically adjust the priority of search results based on the user's emotions. For example, if a user is feeling stressed, concise and summarized information will be prioritized.

[1427] Step 10:

[1428] The emotion engine provides a feature that recommends the structure of proposal materials based on the user's emotions. For example, if the user indicates an optimistic mood, it will recommend proposal materials that include detailed and positive content.

[1429] Step 11:

[1430] Users create project proposals and presentations based on exported data, generated graphs, and recommendations from the provided materials. This allows users to efficiently analyze the trends of competitors and local governments and make effective proposals.

[1431] (Example 2)

[1432] 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".

[1433] In modern society, a vast amount of information circulates on the internet, making it a challenge for users to quickly and accurately obtain the information they need. Especially with formalized information such as press releases, it is necessary to efficiently collect related information, avoid duplication, and organize it visually. Furthermore, appropriately adjusting results in response to changes in the user's emotions during the process to reduce user burden is also a crucial challenge.

[1434] The specific processing performed by the specific 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 the user to input specific keywords, means for generating a search query based on the keywords, means for collecting relevant information from multiple information sources on the Internet using the generated search query, means for filtering the collected information and extracting information that matches the keywords, means for organizing the extracted information and categorizing it by organization and publication date, means for exporting the organized information in spreadsheet format, means for generating various graphs according to the user's request, means for recognizing emotions from the user's operation history and operation speed, and means for adjusting the priority of search results based on the recognized emotions. As a result, the user can quickly and accurately obtain what they need from a large amount of information, organize and visualize it, and be provided with appropriate information according to their emotions.

[1435] A "user" is a person or agent who accesses the system and searches for and uses information by entering specific keywords.

[1436] A "keyword" is a word or phrase that a user enters to search for specific information.

[1437] A "search query" is a string of characters constructed based on entered keywords, used to search for information sources on the internet.

[1438] "Information sources" refer to multiple resources on the internet, such as websites and databases, from which information is collected.

[1439] "Filtering" is the process of selecting information that matches the user's keywords from collected data and eliminating duplicate or unnecessary data.

[1440] "Categorization" is the act of classifying organized information based on specific criteria (e.g., by organization, by publication date).

[1441] "Spreadsheet format" refers to a file format for displaying and saving data in a table format, and generally refers to .csv or .xlsx files.

[1442] A "graph" is a visual representation of data and comes in various forms, such as bar graphs, pie charts, and line graphs.

[1443] "Emotion recognition" is the process of analyzing data such as the user's operation history and operation speed to determine the user's emotional state (e.g., excitement, calmness, stress).

[1444] "Search result prioritization" refers to the act of dynamically changing the order in which search results are displayed based on the perceived emotions of the user.

[1445] This invention is a system that allows a user to input specific keywords, generates search queries based on those keywords, and collects, organizes, and visualizes relevant information from multiple sources on the internet. It also includes a function to recognize the user's emotions and adjust the priority of search results based on those emotions.

[1446] The specific embodiment of this system is configured as follows:

[1447] 1. Enter keywords

[1448] The user accesses the system using a device and enters the keywords they want to search for. Examples of keywords include "press release," "workation," and "local government."

[1449] 2. Generating search queries

[1450] The terminal generates an appropriate search query based on the keywords entered by the user. This search query is in the form of keywords concatenated with the AND operator (e.g., "press release AND workation AND local government").

[1451] 3. Data Collection

[1452] The server uses the generated search query to collect relevant information from multiple specified information sources (such as news sites, company websites, and local government websites). Specifically, the server analyzes the HTML structure of each website and scrapes the necessary data.

[1453] 4. Data filtering

[1454] The server filters the collected information and extracts information that matches the user's keywords. This filtering process includes evaluating the degree of keyword relevance and eliminating duplicate information.

[1455] 5. Data organization

[1456] The server organizes the filtered information and categorizes it by organization or publication date. For example, it might group press releases issued by a local government on a specific date into a single category.

[1457] 6. Data Output and Visualization

[1458] The terminal exports the organized data received from the server in spreadsheet format (.csv or .xlsx), and also generates and displays various graphs (bar graphs, pie charts, line graphs, etc.) according to the user's request.

[1459] 7. Emotion recognition

[1460] The emotion engine analyzes the user's input, operation history, and operation speed to determine the user's emotions (excitement, calmness, stress, etc.).

[1461] 8. Prioritizing search results

[1462] The server dynamically adjusts the priority of search results based on the perceived emotions of the user. For example, if the user is feeling stressed, it prioritizes displaying simpler and more intuitive search results.

[1463] 9. Specific Examples

[1464] When a user enters the keywords "press release workation local government," the device generates a search query "press release AND workation AND local government." The server uses this search query to collect the following information from news sites and official websites:

[1465] Local government: Tokyo Metropolitan Government

[1466] Title: Announcement of Workation Promotion

[1467] Announcement date: April 1, 2023

[1468] The server filters this information, removes duplicates, and organizes it by prefecture and announcement date. The terminal provides this organized information to the user in spreadsheet and graph format. Furthermore, the emotion engine recognizes the user's emotions while they are using the device, and if it determines that the user is excited, it prioritizes displaying detailed information at a faster pace.

[1469] Example of a prompt:

[1470] "Enter specific keywords (e.g., 'press release,' 'workation,' 'local government') to collect and visualize relevant information. Export the collected information in spreadsheet format and display the data for each organization as a bar graph. Also, adjust the search results based on user sentiment."

[1471] Thus, by using the system of the present invention, users can quickly and accurately obtain the necessary data from a vast amount of information, and further organize and analyze it visually. In addition, it becomes possible to provide information flexibly in accordance with the user's emotions, thereby improving usability.

[1472] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1473] Step 1:

[1474] The user enters specific keywords. The user accesses the system using a terminal and enters the keywords they want to search for (e.g., "press release," "workation," "local government"). The input data is a list of keywords in text format.

[1475] Step 2:

[1476] The terminal generates a search query. Based on the entered keywords, the terminal generates a search query using the AND operator. For example, "press release AND workation AND local government". This query is used to search for information sources on the internet. The input is a list of keywords from the user, and the output is the generated search query.

[1477] Step 3:

[1478] The server collects relevant information. Using the generated search query, the server collects information from multiple sources, such as news sites, company websites, and local government websites. The server analyzes the HTML structure of each website and scrapes necessary data such as title, publication date, and body text. The input is the generated search query, and the output is the collected raw data.

[1479] Step 4:

[1480] The server filters the data. The server filters the collected raw data and extracts information that matches the user's keywords. During filtering, keyword matching is evaluated and duplicate information is removed. For example, only information containing all of the keywords "press release," "workation," and "local government" is retained. The input is the collected raw data, and the output is the filtered data.

[1481] Step 5:

[1482] The server organizes the data. The server categorizes the filtered data by organization and by publication date. For example, information released by the Tokyo Metropolitan Government on April 1, 2023, regarding the promotion of workation would be classified in the format "Tokyo Metropolitan Government / April 1, 2023 / Workation Promotion Announcement". The input is filtered data, and the output is organized data.

[1483] Step 6:

[1484] The terminal visualizes and exports data. The terminal exports the organized data in spreadsheet format (.csv or .xlsx) and generates and displays various graphs (bar graphs, pie charts, line graphs, etc.) according to user requests. For example, it can display the number of workation promotion projects for each municipality as a bar graph. The input is organized data, and the output is visualized information and an exported spreadsheet.

[1485] Step 7:

[1486] The emotion engine recognizes the user's emotions. The emotion engine analyzes the user's input, operation history, and operation speed to determine whether the user is excited, calm, or stressed. The input is the user's operation data, and the output is the recognized emotional state.

[1487] Step 8:

[1488] The server adjusts the priority of search results based on emotions. Based on the recognized emotions, the server makes adjustments, for example, prioritizing simple and intuitive search results if the user is stressed. The input is the recognized emotional state, and the output is the adjusted search results.

[1489] Thus, the user begins by entering specific keywords, and the system efficiently delivers information through data collection, filtering, organization, visualization, and sentiment recognition and its application.

[1490] (Application Example 2)

[1491] 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".

[1492] This invention aims to improve the efficiency of information gathering and processing, and particularly in work environments such as logistics centers, there is a need to quickly and efficiently collect and visually display the information that workers need. Furthermore, there is a lack of means to appropriately change the displayed content according to the emotions and state of the workers in order to improve work efficiency. In addition, it is necessary not only to collect information, but also to visualize it in an intuitively understandable format.

[1493] 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 the user to input a specific keyword, means for generating a search query based on the keyword, means for collecting relevant information from multiple information sources on the Internet using the generated search query, means for filtering the collected information and extracting information that matches the keyword, means for organizing the extracted information and categorizing it by category and publication date, means for exporting the organized information in spreadsheet format, means for generating a graph according to the user's request, means for recognizing the user's voice input and generating a search query, means for analyzing the user's emotions from their voice tone and operation speed and changing the search query and display content, and means for displaying the user's operation results on a head-mounted display. This enables rapid collection, organization, and visualization of information. Furthermore, work efficiency is improved by adapting the display content according to the worker's emotions and state.

[1494] A "user" is an entity that uses a system to input keywords and perform operations such as generating search queries and gathering information.

[1495] A "keyword" is a specific word or phrase entered by the user, and it forms the basis for generating a search query.

[1496] A "search query" is a search command constructed based on entered keywords, and is used to collect relevant information from internet sources.

[1497] "Information sources" refer to various websites and databases on the internet from which information is collected using search queries.

[1498] "Filtering" is the process of evaluating whether collected information matches keywords and eliminating unnecessary or duplicate information.

[1499] A "category" is a framework for classifying filtered information, used to organize it based on specific attributes or criteria.

[1500] "Spreadsheet format" refers to a format for exporting organized information as a tab-formatted file (e.g., .csv or .xlsx).

[1501] A "graph" is a tool for visually representing data, and includes various formats such as bar graphs, pie charts, and line graphs.

[1502] "Speech recognition" is a technology that converts speech input by a user into text data and generates search queries based on that data.

[1503] "Sentiment analysis" is a technology that recognizes a user's emotional state based on information such as the user's voice tone and operation speed.

[1504] "Displayed content" refers to organized information and graphs that are visually presented to the user.

[1505] A "head-mounted display" is a device worn on the user's head to display visual information, providing information within the work environment.

[1506] This invention provides a system for improving operational efficiency in logistics centers. The specific program processing of the system, as well as the hardware and software used, are described below.

[1507] System Configuration

[1508] hardware

[1509] A head-mounted display (HMD) is a device worn on the head by workers to display visual information. A specific example is the Microsoft HoloLens.

[1510] Microphone: A device for acquiring voice input and recognizing voice instructions from workers.

[1511] software

[1512] Speech recognition library: Use the speech_recognition library to convert the worker's voice instructions into text data.

[1513] HTTP Request Library: Use the requests library to collect data from multiple sources on the internet.

[1514] Data processing library: Use the pandas library to organize the collected data.

[1515] Data visualization library: Use the matplotlib library to visually display data.

[1516] Sentiment Analysis Model: A model is used to analyze emotions from voice tone and operation speed.

[1517] Program Processing Description

[1518] 1. Voice recognition and keyword input

[1519] The user wears a head-mounted display and uses a microphone to input necessary information and instructions via voice. This voice is then converted into text data through a speech recognition library.

[1520] 2. Generating search queries

[1521] A search query is generated based on keywords obtained as text data. This query is structured in a specified format and forms the basis for information gathering.

[1522] 3. Data Collection

[1523] The server uses the generated search query to collect relevant information from multiple sources on the internet (news sites, official websites, databases, etc.). It uses an HTTP request library to retrieve the information and extracts the necessary data (title, publication date, body text, etc.).

[1524] 4. Filtering and organizing data

[1525] The collected information is filtered based on specified keywords to eliminate unnecessary and duplicate information. Furthermore, a data processing library is used to classify and organize the information by category and publication date.

[1526] 5. Data Visualization

[1527] The organized information is displayed as graphs (bar graphs, pie charts, line graphs, etc.) using a data visualization library. This makes it easier for users to visually grasp the information.

[1528] 6. Sentiment analysis and adjustment of displayed content

[1529] An emotion analysis model analyzes the user's emotional state based on their voice tone and operation speed. If the user is tired, the display content is adjusted accordingly, such as showing only essential information concisely.

[1530] Specific example

[1531] When a user voice-inputs keywords such as "inventory information" or "product receiving and shipping status," the system generates a search query based on these keywords and collects relevant information. At the same time, if the sentiment analysis model detects fatigue from the user's voice tone, it reduces the workload by displaying only essential information.

[1532] Examples of prompts for generative AI models

[1533] Please describe the design of a system that can collect, organize, and visualize "inventory management and receiving / shipping information for a logistics center" in a specified format. Furthermore, please provide a concrete example of an application that includes a function to change the operation method based on the user's emotions.

[1534] As described above, the present invention provides a system that improves work efficiency and optimizes the operation method according to the user's condition.

[1535] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1536] Step 1:

[1537] The user wears a head-mounted display and inputs keywords by voice using a microphone. This voice data is acquired and converted into text data using a speech recognition library. The input is voice data, and the output is text data.

[1538] Specific operation: The user says "inventory information," and the voice is recognized through the microphone. This is then converted into text data, "inventory information," and passed to the system.

[1539] Step 2:

[1540] The terminal generates a search query based on keywords obtained as text data. Specifically, it constructs the keywords in a specified format (e.g., AND search). The input is text data, and the output is a search query.

[1541] Specific operation: Text data "Inventory Information" is entered, and a search query "Inventory Information AND Status" is generated.

[1542] Step 3:

[1543] The server uses the generated search query to collect relevant information from multiple sources. It uses an HTTP request library to retrieve data from news sites, official websites, databases, and other sources on the internet. The input is the search query, and the output is the collected information.

[1544] Specific operation: The search query "Inventory Information AND Status" is executed, and data regarding inventory information and status (e.g., title, publication date, body text) is retrieved from relevant websites.

[1545] Step 4:

[1546] The server filters the collected information and extracts information that matches the keywords. It uses a data processing library to remove unnecessary and duplicate information. The input is the collected information, and the output is the filtered information.

[1547] Specific operation: Information that does not match the criteria or duplicate information is removed from the acquired data.

[1548] Step 5:

[1549] The server organizes the filtered information by category and publication date. It uses a data processing library to classify the information and export it in spreadsheet format. The input is filtered information, and the output is organized data in spreadsheet format.

[1550] Specific operation: Filtered data is categorized by company and publication date, and exported as a .csv file.

[1551] Step 6:

[1552] The terminal generates graphs based on organized information. It uses a data visualization library to create visual graphs (bar graphs, pie charts, line graphs, etc.). Input is data in spreadsheet format, and output is graphs.

[1553] Specific operation: A bar graph showing inventory status is generated from spreadsheet-formatted data and displayed on the HMD screen.

[1554] Step 7:

[1555] The server analyzes the user's emotional state based on their voice tone and operation speed. Using an emotional analysis model, it determines whether the user is tired, etc. The input is voice tone and operation speed, and the output is the emotional state.

[1556] Specific behavior: If the user's voice tone is low and their operation speed is slow, the system analyzes that the user is fatigued.

[1557] Step 8:

[1558] The server adjusts the displayed content based on the analyzed emotional state. If fatigue is detected, the system displays only essential information concisely. The input is the emotional state, and the output is the adjusted display content.

[1559] Specific action: When the user is fatigued, only the essential inventory information is highlighted on the screen.

[1560] The above outlines the specific processing steps of the system program that implements the application example.

[1561] 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.

[1562] 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.

[1563] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1564] 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.

[1565] 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.

[1566] 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.

[1567] 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.

[1568] 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.

[1569] 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."

[1570] 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.

[1571] 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.

[1572] 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.

[1573] 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.

[1574] 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.

[1575] 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.

[1576] 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.

[1577] 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.

[1578] 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.

[1579] 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.

[1580] 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.

[1581] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[1582] The following is further disclosed regarding the embodiments described above.

[1583] (Claim 1)

[1584] A means for the user to enter a specific keyword,

[1585] A means for generating a search query based on the aforementioned keywords,

[1586] A means for collecting relevant press release information from multiple sources on the internet using the generated search query,

[1587] A means for filtering the collected information and extracting press release information that matches the keywords,

[1588] A method for organizing the extracted information and categorizing it by company, local government, and publication date,

[1589] A means for exporting the organized information in spreadsheet format,

[1590] A means for generating graphs such as bar graphs, pie charts, and line graphs in response to the user's request,

[1591] A system that includes this.

[1592] (Claim 2)

[1593] The system according to claim 1, wherein the information source is a news site, a company's official website, or a local government's official website.

[1594] (Claim 3)

[1595] The system according to claim 1, wherein the filtering means has a function to eliminate duplicate press release information.

[1596] "Example 1"

[1597] (Claim 1)

[1598] A means for the user to enter a specific keyword,

[1599] A means for generating a search query based on the aforementioned keywords,

[1600] A means for collecting relevant information from multiple information sources on the internet using the generated search query,

[1601] A means for filtering the collected information and extracting information that matches the keyword,

[1602] A means of organizing the extracted information and categorizing it by organization, administrative division, and date,

[1603] A means for exporting the organized information in spreadsheet software format,

[1604] A means for generating charts and graphs in response to the user's request,

[1605] A system that includes this.

[1606] (Claim 2)

[1607] The system according to claim 1, wherein the information source is a news site or an official website.

[1608] (Claim 3)

[1609] The system according to claim 1, wherein the filtering means has a function to eliminate duplicate information.

[1610] "Application Example 1"

[1611] (Claim 1)

[1612] A means for the user to enter a specific keyword,

[1613] A means for generating a search query based on the aforementioned keywords,

[1614] A means for collecting relevant information from multiple information sources on the internet using the generated search query,

[1615] A means for filtering the collected information and extracting information that matches the keyword,

[1616] A means of organizing the extracted information and categorizing it by organization and presentation time,

[1617] A means for exporting the aforementioned organized information in a calculation processing table format,

[1618] A means for generating data visualizations such as bar graphs, pie charts, and line graphs in response to the user's request,

[1619] The generated graph information is input as a prompt message to the generating AI model, and a means is provided to perform further detailed analysis.

[1620] A system that includes this.

[1621] (Claim 2)

[1622] The system according to claim 1, wherein the information source is a news portal, an organization's official website, or a public database.

[1623] (Claim 3)

[1624] The system according to claim 1, wherein the filtering means has a function to eliminate duplicate information.

[1625] "Example 2 of combining an emotion engine"

[1626] (Claim 1)

[1627] A means for the user to enter a specific keyword,

[1628] A means for generating a search query based on the aforementioned keywords,

[1629] A means for collecting relevant information from multiple information sources on the internet using the generated search query,

[1630] A means for filtering the collected information and extracting information that matches the keyword,

[1631] A means of organizing the extracted information and categorizing it by organization and publication date,

[1632] A means for exporting the organized information in spreadsheet format,

[1633] A means for generating various graphs in response to the user's request,

[1634] A means of recognizing emotions from the user's operation history and operation speed,

[1635] Means for adjusting the priority of search results based on the recognized emotions,

[1636] A system that includes this.

[1637] (Claim 2)

[1638] The system according to claim 1, wherein the information source is a news site or an official website.

[1639] (Claim 3)

[1640] The system according to claim 1, wherein the filtering means has a function to eliminate duplicate information.

[1641] "Application example 2 when combining with an emotional engine"

[1642] (Claim 1)

[1643] A means for the user to enter a specific keyword,

[1644] A means for generating a search query based on the aforementioned keywords,

[1645] A means for collecting relevant information from multiple information sources on the internet using the generated search query,

[1646] A means for filtering the collected information and extracting information that matches the keyword,

[1647] A means for organizing the extracted information and categorizing it by category and by publication date,

[1648] A means for exporting the organized information in spreadsheet format,

[1649] A means for generating a graph in response to the user's request,

[1650] A means for recognizing user voice input and generating search queries,

[1651] A method to analyze user emotions from their voice tone and operation speed, and change search queries and displayed content accordingly.

[1652] Means for displaying the user's operation results on a head-mounted display,

[1653] A system that includes this.

[1654] (Claim 2)

[1655] The system according to claim 1, wherein the information source is a news site, an official website, or a database.

[1656] (Claim 3)

[1657] The system according to claim 1, wherein the filtering means has a function to eliminate duplicate information. [Explanation of Symbols]

[1658] 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 for the user to enter a specific keyword, A means for generating a search query based on the aforementioned keywords, A means for collecting relevant press release information from multiple sources on the internet using the generated search query, A means for filtering the collected information and extracting press release information that matches the keywords, A method for organizing the extracted information and categorizing it by company, local government, and publication date, A means for exporting the organized information in spreadsheet format, A means for generating graphs such as bar graphs, pie charts, and line graphs in response to the user's request, A system that includes this.

2. The system according to claim 1, wherein the information source is a news site, a company's official website, or a local government's official website.

3. The system according to claim 1, wherein the filtering means has a function to eliminate duplicate press release information.

Images