system

Abstract

We provide the system. [Solution] A means for detecting when a file is uploaded from a user terminal, A means of analyzing the contents of an uploaded file and generating a summary, A means for extracting relevant tags from the generated summary, A system that includes means for classifying and moving files to appropriate shared folders based on extracted tags.

Description

Technical Field

[0005]

[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 the 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

Means for Solving the Problems

[0005] This invention relates to a system that includes means for detecting when a file is uploaded from a user terminal, means for analyzing the contents of the uploaded file and generating a summary, means for extracting relevant tags from the generated summary, and means for classifying and moving the file to an appropriate shared folder based on the extracted tags. This system enables automatic classification and storage based on file content simply by each individual uploading files to their own public folder, resulting in efficient file sharing and searching. Furthermore, by using generative artificial intelligence for file content analysis, more accurate tagging is achieved. This significantly improves file management in projects and business operations.

[0006] A "user terminal" is a computing device used to create and edit files and upload those files.

[0007] "Uploading" refers to the act of sending a file from a user's device to a server.

[0008] "Detection means" refers to a function that senses when a file is uploaded and notifies other systems of that information.

[0009] "Means for analyzing content" refers to a function that uses a program to read and analyze the contents of uploaded files.

[0010] The "means of generating a summary" refer to the part that concisely summarizes the contents of the analyzed file.

[0011] "A means of extracting tags" refers to a function that selects highly relevant keywords and phrases based on the summarized content and sets them as tags.

[0012] "Classification and relocation methods" refers to the function of sorting files into appropriate shared folders based on extracted tags and physically moving them.

[0013] "Generative artificial intelligence" is an AI technology that uses machine learning algorithms, including natural language processing, to understand the contents of files and perform tasks such as summarizing and tagging.

[0014] A "shared folder" is a file storage area used for projects or tasks that can be accessed by multiple users.

[0015] A "search system" refers to a function that finds related files within a shared folder based on specific keywords or tags. [Brief explanation of the drawing]

[0016] [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] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This 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 the 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 the emotion engine is combined.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, the labeled processor (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.

[0020] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] 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.

[0022] 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).

[0023] 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."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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".

[0037] Embodiments of this invention will now be described. This system aims to facilitate file searching by efficiently managing user-created files and appropriately classifying and storing them within a shared folder.

[0038] System Configuration

[0039] 1. User terminal

[0040] It is a computing device that allows users to create and edit files in their local environment and upload them to their public folder.

[0041] 2. Server

[0042] It plays a central role in receiving uploaded files and performing a series of processes including analysis, summary generation, tagging, classification, and movement.

[0043] Program operation

[0044] File Upload

[0045] A user creates a file and uploads it to their public folder. For example, a user uploads "Project A Progress Report.doc" to their public folder.

[0046] The device detects this upload and notifies the server of information such as the file name and metadata.

[0047] File analysis and summary generation

[0048] The server receives notification of the upload and identifies the file. Next, the server analyzes the file's contents. For example, in the case of a PDF file, it uses OCR technology to convert it into text data.

[0049] The server uses generative artificial intelligence to generate a summary of the content, using the converted text data as input. For example, it might concisely summarize the contents of a file titled "Project A Progress Report."

[0050] Tag extraction

[0051] Based on the generated summary, the server extracts relevant tags. For example, it automatically generates tags such as "Project A," "Progress," "Report," and "October 2023."

[0052] File classification and movement

[0053] For tagged files, the server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Project A" and "Progress," the file might be moved to the " / sharedfolder / Project A / Progress" folder.

[0054] File Search

[0055] Users use the search interface to find the files they need within a shared folder. For example, they might search using the keyword "Project A Progress Report October 2023".

[0056] The server parses the search query, matches it with appropriate tags to identify the file, and returns the search results. As a result, the user can easily access the desired file.

[0057] Specific example

[0058] For example, suppose a user creates a file named "Project B Budget Report.xlsx" and uploads it to a shared folder. The server detects this file, analyzes its contents, and generates tags such as "Budget," "Project B," and "Report." The server then automatically moves this file to the " / Shared Folder / Project B / Budget Report" folder. If a user searches for "Project B Budget Report," the search results will immediately return the desired file, "Project B Budget Report.xlsx."

[0059] This system simplifies file classification and management, enabling more efficient work.

[0060] The following describes the processing flow.

[0061] Step 1:

[0062] The user creates a file on their local device and uploads it to their public folder. For example, they might upload "Project A Progress Report.doc".

[0063] Step 2:

[0064] The device detects uploaded files and notifies the server of metadata such as file name, file path, and upload time.

[0065] Step 3:

[0066] The server receives the upload notification and confirms that the new file has been added to the public folder.

[0067] Step 4:

[0068] The server reads the file and converts its contents into text format. For example, in the case of a PDF, OCR technology is used to convert it into text data.

[0069] Step 5:

[0070] The server takes the converted text data as input and invokes a generative artificial intelligence to analyze its content. The generative AI then generates a summary from the analyzed text data.

[0071] Step 6:

[0072] The server generates relevant tags based on the summary results from the generative AI. For example, it might extract tags such as "Project A," "Progress," "Report," and "October 2023."

[0073] Step 7:

[0074] The server-generated tags are added as metadata to the file.

[0075] Step 8:

[0076] Based on the extracted tags, the server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Project A" and "Progress," it identifies the folder " / Shared Folder / Project A / Progress."

[0077] Step 9:

[0078] The server physically moves the files from the public folder to the appropriate shared folder.

[0079] Step 10:

[0080] Users use the search interface to find the files they need within the shared folder. For example, they might enter a keyword such as "Project A Progress Report October 2023".

[0081] Step 11:

[0082] The server analyzes the search query and finds highly relevant files within the shared folder.

[0083] Step 12:

[0084] The server returns relevant files to the user as search results, making it easy for the user to access the desired files.

[0085] ---

[0086] This processing flow automates each step, allowing users to efficiently manage and search for files.

[0087] (Example 1)

[0088] 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."

[0089] In modern information management, a major problem is the scattering of large numbers of files, making organization and searching difficult. As a result, users often have to spend a great deal of time and effort to access the information they need. Furthermore, systems with advanced features such as proper file classification and summarization within shared folders, and automatic extraction of related tags, are limited.

[0090] 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.

[0091] In this invention, the server includes means for detecting when a file is uploaded from a user terminal, means for notifying the server of the metadata of the uploaded file, means for analyzing the contents of the uploaded file and extracting text data, means for generating a summary using generative artificial intelligence with respect to the extracted text data, means for extracting relevant tags from the generated summary, means for classifying and moving files to appropriate shared folders based on the extracted tags, means for the user to perform a file search based on tags using a search interface, and means for the server to analyze the search query, identify the relevant files, and return the search results. This automates the organization and management of large numbers of files, enabling users to quickly and efficiently access the information they need.

[0092] A "user terminal" refers to a computing device used by a user, such as a computer, smartphone, or tablet.

[0093] A "server" is a computing system that receives uploaded files and performs analysis, summarization, tagging, classification / movement, and analysis of search queries.

[0094] "Uploading" refers to the act of transferring files from a user's device to a server.

[0095] "Metadata" refers to additional information about a file, such as file name, creation date and time, and file size.

[0096] "Analysis" is the process of deciphering the contents of uploaded files and extracting useful information such as text data.

[0097] "OCR technology" is an optical character recognition technology used to extract text data from image data.

[0098] A "text extraction library" is a software component used to extract text data from files such as DOC and XLSX.

[0099] "Generative artificial intelligence" refers to artificial intelligence technology that performs text summarization and generation based on input data.

[0100] A "summary" is a text that concisely summarizes the contents of a file.

[0101] A "tag" is a keyword or label that indicates the specific content or attributes of a file.

[0102] A "shared folder" is a data storage area that can be accessed by multiple users.

[0103] "Classification and relocation" is the process of sorting files into the appropriate folders based on the extracted tags.

[0104] A "search interface" is a user interface that allows users to search for necessary files by entering tags or keywords.

[0105] A "search query" is a search word or phrase that a user enters into the search interface.

[0106] "Search results" refer to a list of files that the server identifies and returns to the user based on the search query.

[0107] This invention relates to a system for users to create, efficiently manage, and properly classify and store files within a shared folder. It enables users to quickly and efficiently access the information they need.

[0108] Hardware to use

[0109] 1. User terminal: A computing device such as a computer, smartphone, or tablet used by the user to create files and upload them to a public folder.

[0110] 2. Servers: Cloud servers and on-premises servers are used to receive, analyze, summarize, tag, classify, and move files.

[0111] Software to use

[0112] 1. File analysis software:

[0113] OCR technology (e.g., Tesseract) is used to analyze PDF files.

[0114] Text extraction from DOC and XLSX files is performed using a text extraction library (e.g., Apache® POI).

[0115] 2. Generative Artificial Intelligence: Generative artificial intelligence (e.g., OpenAI® GPT-3®) will be used to generate summaries of file contents.

[0116] 3. File Management System: A proprietary management system for uploading, notifying, and storing files.

[0117] Explanation of natural language processing

[0118] File upload:

[0119] The user creates a file named "Project A Progress Report.doc" and uploads it to the public folder. The device detects this upload and notifies the server of information such as the file name and metadata.

[0120] File analysis:

[0121] The server receives the upload notification and identifies the file. Next, the server analyzes the file content. For PDF files, it uses OCR technology to convert them into text data. For DOC and XLSX files, it uses a text extraction library to extract the text data.

[0122] Summary generation:

[0123] Using the extracted text data, the server generates a summary of the content using generative artificial intelligence. For example, it might concisely summarize the contents of the "Project A Progress Report" file.

[0124] Tag extraction:

[0125] Based on the generated summary, the server extracts relevant tags. For example, tags such as "Project A," "Progress," "Report," and "October 2023" are automatically generated.

[0126] File classification and movement:

[0127] For tagged files, the server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Project A" and "Progress," the file might be moved to the " / Shared Folder / Project A / Progress" folder.

[0128] Search for files:

[0129] When a user searches for a file within a shared folder, they use the search interface. For example, they might search using the keyword "Project A Progress Report October 2023". The server parses the search query, matches it with appropriate tags to identify the file, and returns the search results. As a result, the user can easily access the desired file.

[0130] Specific example

[0131] For example, suppose a user creates a file named "Project B Budget Report.xlsx" and uploads it to a shared folder. The server analyzes its contents and generates tags such as "Budget," "Project B," and "Report." The server then automatically moves this file to the " / Shared Folder / Project B / Budget Report" folder. If a user searches for "Project B Budget Report," the desired file, "Project B Budget Report.xlsx," will be immediately returned as a search result. This system simplifies file classification and management, enabling more efficient work.

[0132] Example of a prompt

[0133] Example prompt message for when you upload "Project A progress report.doc":

[0134] A user uploaded "Project A Progress Report.doc" to the public folder. This file was converted to text using OCR technology, and then an automatic summary was generated. Relevant tags such as "Project A," "Progress," "Report," and "October 2023" were then added, and it was categorized into the appropriate folder. This allows users to quickly find the desired file by searching for "Project A Progress Report October 2023."

[0135] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0136] Processing flow of this system

[0137] Step 1: File Upload Detection

[0138] Users create files on their own devices and upload them to a public folder.

[0139] The device monitors changes to the public folder in real time and detects when new files are added.

[0140] Input: A file uploaded by the user to a public folder (e.g., "Project A Progress Report.doc")

[0141] Output: Notification that a file has been uploaded

[0142] Step 2: Metadata Notification

[0143] The terminal notifies the server of the file name and metadata (file path, creation date and time, etc.).

[0144] Input: Metadata of the uploaded file

[0145] Output: Metadata notification to the server

[0146] Step 3: Analyze the files

[0147] The server receives the upload notification and identifies the relevant file.

[0148] The server analyzes the file contents and extracts text data.

[0149] For PDF files, use OCR technology (e.g., Tesseract) to extract text from the image.

[0150] For DOC and XLSX files, use a text extraction library (e.g., Apache POI) to extract the text data.

[0151] Input: Uploaded file

[0152] Output: Extracted text data

[0153] Step 4: Summary Generation

[0154] The server inputs the extracted text data into a generative artificial intelligence (e.g., GPT-3) to generate a summary of its content.

[0155] The generated summary will include a report detailing the progress and future plans for Project A.

[0156] Input: Extracted text data

[0157] Output: Summary text

[0158] Step 5: Tag Extraction

[0159] The server extracts relevant tags based on the generated summary.

[0160] Using natural language processing technology (e.g., spaCy), tags such as "Project A," "Progress," and "Report" are automatically generated.

[0161] Input: Summary text

[0162] Output: Extracted tag list

[0163] Step 6: File classification and movement

[0164] The server identifies the appropriate folder based on the tags and moves the files to that folder.

[0165] Based on the tags, folders such as " / shared folder / project A / progress" are selected.

[0166] Input: Extracted tag list

[0167] Output: New path to the file

[0168] Step 7: Search for files

[0169] The user searches for files using the search interface.

[0170] Enter keywords such as "Project A Progress Report October 2023".

[0171] Input: User's search keywords

[0172] Output: Search query

[0173] Step 8: Parse the search query and return the results.

[0174] The server parses the search query, matches it with tags, identifies the relevant files, and returns the search results.

[0175] Input: Search query

[0176] Output: List of identified files

[0177] This system allows users to automatically organize and manage large amounts of files, enabling them to quickly access the information they need.

[0178] (Application Example 1)

[0179] 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."

[0180] Logistics centers generate a large volume of documents and data daily, making efficient management and retrieval a significant challenge. Manually classifying and storing paper-based documents and multiple digital files is time-consuming, labor-intensive, and prone to human error. Therefore, it is necessary to improve document management efficiency, reduce the workload on staff, and enable quick and accurate searching and access.

[0181] 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.

[0182] In this invention, the server includes means for detecting when a file is uploaded, means for analyzing the contents of the uploaded file and generating a summary, means for extracting relevant tags from the generated summary, means for classifying and moving files to appropriate shared folders based on the extracted tags, means for automatically creating and classifying folders based on the contents of the uploaded file, means for generating summaries and tags using generative artificial intelligence, and means for analyzing and storing data using a cloud server. This enables improved efficiency and accuracy in file management.

[0183] A "user terminal" is a computing device operated by a user, and is a device used for creating, editing, and uploading files.

[0184] A "file" is a form of electronic data, a recording medium that contains various types of information, such as documents, images, and spreadsheet data.

[0185] "Uploading" refers to the operation of sending data files from a local environment to a remote environment such as a server.

[0186] "Analysis" is the process of examining the contents of an uploaded file and understanding its structure and elements.

[0187] A "summary" is a concise, abbreviated version of the file's contents.

[0188] A "tag" is an identification label assigned to data to facilitate classification and searching.

[0189] A "shared folder" is a folder that can be accessed by multiple users and serves as a storage area for files.

[0190] A "cloud server" is a remote server accessible via the internet, used for data storage and analysis.

[0191] "Generative artificial intelligence" refers to artificial intelligence technology used to generate new information based on input data.

[0192] "Automatic creation" refers to a process where the system autonomously generates folders and other elements without user intervention.

[0193] "Classification" is the act of grouping files according to specific criteria.

[0194] "Moving" refers to the operation of physically or logically rearranging a file from one location to another.

[0195] This invention will now be described in terms of embodiments for carrying it out. This system is intended to efficiently manage documents and data files in a logistics center.

[0196] This system mainly consists of user terminals and cloud servers.

[0197] User terminal

[0198] User terminals are computing devices such as smartphones and tablets used by staff at the logistics center. Users can create and edit files from their own devices and upload them to the system.

[0199] server

[0200] Cloud servers are the core components that process uploaded files, handling a series of operations including analysis, summary generation, tagging, classification, and migration.

[0201] System operation procedure

[0202] 1. Upload files

[0203] When a user uploads a file from their smartphone, the device detects the upload and notifies the cloud server of the file's metadata, name, and other information.

[0204] 2. File analysis and summary generation

[0205] The cloud server receives the uploaded information and analyzes the contents of files such as Word documents and PDFs. It may also use OCR technology to extract text data from image files. Next, generative artificial intelligence is used based on the extracted text data to generate a summary of the content. For example, it might concisely summarize the contents of "Inventory List 2023.doc".

[0206] 3. Tag extraction

[0207] Based on the generated summary, the cloud server extracts relevant tags. For example, it automatically generates tags such as "inventory," "list," and "2023."

[0208] 4. File classification and movement

[0209] For tagged files, the cloud server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Inventory" and "List," it moves the files to the " / Logistics / Inventory" folder. Folders are automatically created as needed.

[0210] Hardware and software to use

[0211] Smartphone: Use it to upload and manage files.

[0212] Cloud server: Performs data analysis and storage.

[0213] Watchdog: A library for detecting file changes.

[0214] Transformers is a library that provides generative artificial intelligence models, performing summary generation and tagging.

[0215] Specific example

[0216] For example, if a staff member uploads "Inventory List 2023.pdf" from their smartphone, the cloud server receives the file and converts its contents into text using OCR technology. Next, it generates a summary using generative artificial intelligence and extracts tags such as "Inventory," "List," and "2023." Based on these tags, the cloud server then identifies the " / Logistics / Inventory" folder, automatically creates the folder if necessary, and moves the file there. When a user searches for "Inventory List 2023," they can immediately access the desired file.

[0217] Example of a prompt

[0218] Examples of prompts to input into a generative artificial intelligence are as follows:

[0219] "Please briefly summarize the contents of the 2023 inventory list."

[0220] In this way, this invention can achieve improved efficiency and accuracy in file management.

[0221] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0222] Step 1:

[0223] The user uploads a file from their smartphone.

[0224] Input: Created file

[0225] Operation: This involves a user at a logistics center saving new documents, reports, and other files to their smartphone and then uploading them to a cloud system.

[0226] Output: Upload event occurrence and file metadata

[0227] Step 2:

[0228] The device detects the file upload.

[0229] Input: Uploaded file

[0230] Operation: The user terminal detects the moment a file is uploaded to the system and retrieves the file's name and other metadata.

[0231] Output: File metadata and upload notification

[0232] Step 3:

[0233] The server receives the upload notification and analyzes the file contents.

[0234] Input: File metadata and actual file

[0235] Operation: The server retrieves the uploaded files and analyzes their contents. It uses OCR technology to convert image files into text data and reads the contents of document files as text.

[0236] Output: Analyzed text data

[0237] Step 4:

[0238] The server uses generative artificial intelligence to generate a summary from the analyzed text data.

[0239] Input: Parsed text data

[0240] Operation: The server supplies the analyzed text data as input to a generative artificial intelligence system, which then generates a summary. The prompt used is "Please summarize the content concisely."

[0241] Output: Generated summary

[0242] Step 5:

[0243] The server extracts relevant tags from the generated summary.

[0244] Input: Generated summary

[0245] Operation: The server analyzes the summary and uses generative artificial intelligence to extract relevant tags. For example, tags are determined based on keywords and important terms contained in the summary.

[0246] Output: Extracted tags

[0247] Step 6:

[0248] The server categorizes and moves files to the appropriate shared folder based on the extracted tags.

[0249] Input: Extracted tags

[0250] Operation: The server determines the file's storage location based on its tags. If the corresponding folder does not exist, it automatically creates a new folder as needed and moves the file into it. If the file is named "Inventory List 2023", it will be moved to the " / Logistics / Inventory" folder.

[0251] Output: Files moved to the appropriate folder

[0252] Step 7:

[0253] The user searches for files within the shared folder.

[0254] Input: Search keyword

[0255] Operation: Users use a search interface on their smartphones to search for necessary files. For example, they might search using the keyword "Inventory List 2023".

[0256] Output: List of related files

[0257] 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.

[0258] Embodiments of this invention will now be described. This system aims to facilitate file searching by efficiently managing user-created files and appropriately classifying and storing them within a shared folder. Furthermore, by incorporating an emotion engine that recognizes user emotions, more flexible and personalized file management becomes possible.

[0259] System Configuration

[0260] 1. User terminal

[0261] It is a computing device that allows users to create and edit files in their local environment and upload them to their public folder. It is equipped with an emotion engine that can detect the user's emotional state in real time.

[0262] 2. Server

[0263] It plays a central role in receiving uploaded files and performing a series of processes including analysis, summary generation, tagging, classification, and movement. It complements file management based on sentiment data obtained from the sentiment engine.

[0264] Program operation

[0265] File Upload

[0266] A user creates a file and uploads it to their public folder. For example, they might upload "Project A Progress Report.doc".

[0267] The device detects this upload and notifies the server of information such as the file name and metadata.

[0268] File analysis and summary generation

[0269] The server receives notification of the upload and identifies the file. Next, the server analyzes the file's contents. For example, in the case of a PDF file, it uses OCR technology to convert it into text data.

[0270] The server uses generative artificial intelligence to generate a summary of the content, using the converted text data as input. For example, it might concisely summarize the contents of a file titled "Project A Progress Report."

[0271] Tag extraction

[0272] Based on the generated summary, the server generates relevant tags. For example, it automatically generates tags such as "Project A," "Progress," "Report," and "October 2023."

[0273] Acquisition and reflection of emotional data

[0274] An emotion engine that recognizes user emotions detects the user's emotional state when creating or editing files and sends that data to the server. Emotion data includes states such as "stress," "concentration," and "excitement."

[0275] Based on this sentiment data, the server supplements and modifies the generated tags and summaries, and further reflects them in the file's metadata. For example, a file created by a user while highly focused will be tagged "focused" and judged to be of high importance.

[0276] File classification and movement

[0277] For tagged files, the server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Project A" and "Progress," the file might be moved to the " / sharedfolder / Project A / Progress" folder.

[0278] File Search

[0279] Users use the search interface to find the files they need within a shared folder. For example, they might search using the keyword "Project A Progress Report October 2023".

[0280] The server parses the search query, matches it with appropriate tags to identify the file, and returns the search results. As a result, the user can easily access the desired file.

[0281] Specific example

[0282] For example, suppose a user creates a file named "Project B Budget Report.xlsx" and uploads it to a shared folder. The server detects this file, analyzes its contents, and generates tags such as "Budget," "Project B," and "Report." The sentiment engine recognizes the user's "high stress" state and adds this information to the metadata as well. The server then automatically moves this file to the " / Shared Folder / Project B / Budget Report" folder. If a user searches for "Project B Budget Report," the search results will immediately return the desired file, "Project B Budget Report.xlsx."

[0283] This system simplifies file classification and management, enabling more efficient work. Furthermore, the introduction of an emotion engine allows for personalized file management that takes into account the user's emotional state.

[0284] The following describes the processing flow.

[0285] Step 1:

[0286] The user creates a file on the local terminal and uploads it to their public folder. For example, upload "Project A Progress Report.doc" to the public folder.

[0287] Step 2:

[0288] The terminal detects the uploaded file and notifies the server of metadata such as the file name, file path, and upload time.

[0289] Step 3:

[0290] The server receives the upload notification and confirms that a new file has been added to the public folder.

[0291] Step 4:

[0292] The server reads the file and converts the content into text format. For example, in the case of PDF, use OCR technology to convert it into text data.

[0293] Step 5:

[0294] Using the converted text data as input, the server calls a generative artificial intelligence to analyze the content. The generative AI generates a summary from the analyzed text data.

[0295] Step 6:

[0296] Based on the summary result of the generative AI, the server generates relevant tags. For example, extract tags such as "Project A", "Progress", "Report", "October 2023".

[0297] ]>Step 7:

[0298] Add the tags generated by the server as file metadata.

[0299] Step 8:

[0300] The emotion engine detects the user's emotional state in real time and sends the data to the server. The emotion data includes states such as "stress", "concentration", "excitement", etc.

[0301] Step 9:

[0302] The server receives the emotion data and complements and corrects the tags and summaries generated based on this data. For example, a "concentration" tag is assigned to a file created by the user in a high concentration state, and it is determined to have a high importance.

[0303] Step 10:

[0304] Based on the extracted tags, the server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Project A" and "Progress Status", the " / Shared Folder / Project A / Progress Status" folder is identified.

[0305] Step 11:

[0306] The server physically moves the file from the public folder to the appropriate shared folder.

[0307] Step 12:

[0308] The user uses the search interface to search for the required files within the shared folder. For example, enter the keyword "Project A Progress Report October 2023".

[0309] Step 13:

[0310] The server analyzes the search query and finds the relevant files from within the shared folder.

[0311] Step 14:

[0312] The server returns relevant files to the user as search results, making it easy for the user to access the desired files.

[0313] This processing flow automates each step, allowing users to efficiently manage and search for files. Furthermore, the introduction of an emotion engine enables personalized file management that takes into account the user's emotional state. For example, when a user creates "Project B Budget Report.xlsx" and uploads it to a shared folder, the system detects that the user is in a high-stress state and adds this information to the metadata. Based on this information, the server determines the file is important, assigns appropriate tags, and moves it to " / shared folder / Project B / Budget Report". If the user then searches for "Project B Budget Report," the desired file is immediately returned as a search result.

[0314] (Example 2)

[0315] 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".

[0316] Traditional file management systems often require manual file classification and searching, which is time-consuming and labor-intensive. Furthermore, they fail to consider user work efficiency and emotional state, making efficient and flexible file management difficult. As a result, file locator and work comfort are compromised, leading to increased user burden.

[0317] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for detecting when a file is uploaded from a user terminal, means for analyzing the contents of the uploaded file and generating a summary, means for extracting relevant tags from the generated summary, means for detecting the user's emotional state in real time, means for transmitting the detected emotional data to the server, means for supplementing and correcting the tags and summaries generated based on the emotional data, and means for classifying and moving files to appropriate shared folders based on the extracted tags. This enables efficient automatic classification and searching of files, and in addition, personalized file management according to the user's emotional state.

[0318] A "user terminal" is a computing device that a user uses to create, edit, and upload files.

[0319] A "server" is a central computer system that receives, analyzes, summarizes, tags, classifies, moves, and processes sentiment data for uploaded files.

[0320] "Methods for analyzing file contents" refers to technologies that analyze the text and image data of uploaded files to summarize their contents and extract tags.

[0321] "Methods for generating summaries" refers to techniques that shorten the contents of a file and concisely summarize important information.

[0322] "Methods for extracting tags" refers to technologies that perform a process of automatically extracting relevant keywords from the contents of a file or the generated summary.

[0323] "Methods for detecting emotional states in real time" refers to technologies that analyze and detect a user's emotional state in real time based on their facial expressions, voice, and other factors.

[0324] "Means for transmitting emotional data" refers to communication technology for sending data about a user's emotional state to a server.

[0325] "Methods for supplementing and correcting tags and summaries" refers to technologies that perform the process of correcting and supplementing tags and summaries generated based on detected sentiment data.

[0326] "Methods for classifying and moving files to shared folders" refers to technologies for classifying files into appropriate subfolders based on generated tags and then moving them to those folders.

[0327] Embodiments of this invention will now be described. This system aims to facilitate file searching by efficiently managing user-created files and appropriately classifying and storing them within a shared folder. Furthermore, by incorporating an emotion engine that recognizes user emotions, more flexible and personalized file management becomes possible.

[0328] System Configuration

[0329] 1. User terminal

[0330] A user terminal is a computing device used by a user to create and edit files in their local environment. Examples include personal computers and smartphones. Terminals are equipped with an emotion engine that can detect the user's emotional state in real time from their facial expressions and voice. Specifically, facial recognition software and voice recognition software are used for this purpose.

[0331] 2. Server

[0332] The server receives files uploaded from user terminals, analyzes their contents, and generates summaries. The software used includes OCR technology, natural language processing technology, and generative AI models (e.g., GPT-4®). It also receives sentiment data from the sentiment engine and uses it to complete and correct tags and summaries. Specifically, OCR engines such as Tesseract are used for file content analysis, and generative artificial intelligence (e.g., generative AI models) is used for summary generation.

[0333] Program operation

[0334] File Upload

[0335] A user creates a file and uploads it to their public folder. For example, they might upload "Project A Progress Report.doc". The device detects this upload and notifies the server of information such as the file name and metadata.

[0336] File analysis and summary generation

[0337] The server receives an upload notification and identifies the file. Next, the server analyzes the file's contents. For example, in the case of a PDF file, it uses OCR technology to convert it into text data. Using the converted text data as input, the server uses generative artificial intelligence to generate a summary of the content. For example, it might concisely summarize the contents of a file titled "Project A Progress Report."

[0338] Tag extraction

[0339] Based on the generated summary, the server generates relevant tags. For example, it automatically generates tags such as "Project A," "Progress," "Report," and "October 2023."

[0340] Acquisition and reflection of emotional data

[0341] An emotion engine that recognizes user emotions detects the user's emotional state when creating or editing files and sends that data to the server. This emotion data includes states such as "stress," "concentration," and "excitement." The server uses this emotion data to supplement and modify generated tags and summaries, and further reflects this in the file's metadata. For example, a file created by a user in a highly focused state will be tagged "concentration" and judged to be of high importance.

[0342] Specific example

[0343] For example, suppose a user creates a file named "Project B Budget Report.xlsx" and uploads it to a shared folder. The server detects this file, analyzes its contents, and generates tags such as "Budget," "Project B," and "Report." The sentiment engine recognizes the user's "high stress" state and adds this information to the metadata as well. The server then automatically moves this file to the " / Shared Folder / Project B / Budget Report" folder. If a user searches for "Project B Budget Report," the search results will immediately return the desired file, "Project B Budget Report.xlsx."

[0344] This system simplifies file classification and management, enabling more efficient work. Furthermore, the introduction of an emotion engine allows for personalized file management that takes into account the user's emotional state.

[0345] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0346] Program processing flow

[0347] Step 1: Create and upload files

[0348] The user creates a file, for example, "Project A Progress Report.doc". The input is a file created by the user on a device such as a PC or smartphone.

[0349] Users upload files they have created to their public folder. For example, they can drag and drop files into the public folder or click the upload button. The output is the file uploaded to the public folder.

[0350] Step 2: Upload detection and notification

[0351] The device detects when a new file has been uploaded to the public folder. Specifically, it uses a file system monitoring tool to periodically check for changes in the folder. The input is a list of files in the public folder.

[0352] The terminal notifies the server of information about the uploaded file (file name, size, metadata, etc.). The output is the file information sent to the server.

[0353] Step 3: File analysis and summary generation

[0354] The server receives the upload notification and retrieves the corresponding file. The input is the file information sent from the device.

[0355] The server analyzes the file's contents. For example, in the case of a PDF file, it uses OCR technology to convert it into text data. Specifically, it uses an OCR engine such as Tesseract. The output is the converted text data.

[0356] The server uses a generative artificial intelligence (e.g., GPT-4) as input to convert the text data and generates a summary of its contents. The output is a summary of the file's contents.

[0357] Step 4: Tag Extraction

[0358] The server generates relevant tags based on the generated summary. For example, it may use natural language processing techniques to extract keywords from the summary. The input is the generated summary.

[0359] The server generates relevant tags. For example, it extracts tags such as "Project A," "Progress," "Report," and "October 2023." The output is a list of the extracted tags.

[0360] Step 5: Acquisition and reflection of emotional data

[0361] The device uses an emotion engine to detect the user's emotional state in real time when creating or editing files. Specifically, it uses facial recognition software and speech recognition software. The input consists of the user's facial expressions and voice data.

[0362] The device sends detected emotional data to the server. This data may include states such as "stress," "concentration," and "excitement." The output is the emotional data sent to the server.

[0363] The server uses sentiment data to supplement and modify the generated tags and summaries. For example, it adds the "focused" tag to files deemed highly important. The output consists of the supplemented and modified tags and summary text.

[0364] Step 6: Classify and move files

[0365] The server identifies the appropriate subfolder within the shared folder based on the extracted tags. For example, based on the tags "Project A" and "Progress," it identifies the folder " / sharedfolder / Project A / Progress." The input is a list of tags.

[0366] The server moves the file to a specified subfolder. Specifically, it uses a file manipulation API to move the file. The output is the file moved to the appropriate subfolder.

[0367] Step 7: Search for files

[0368] When a user needs to find a file, they use the search interface. For example, they might enter the keyword "Project A Progress Report October 2023" into the search bar. The input is the search query entered by the user.

[0369] The server parses the search query and identifies files based on relevant tags. Specifically, it uses a full-text search engine to search for indexed tags and metadata. The output is a file list as search results.

[0370] The user accesses the desired file from the search results. For example, they click on "Project A Progress Report.doc" to open it.

[0371] (Application Example 2)

[0372] 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 device 14 will be referred to as the "terminal."

[0373] In today's digital society, file management and retrieval are critical challenges. Especially in environments where a large number of files are generated daily, proper classification and rapid searching are essential. Furthermore, file management that considers user emotions and context has the potential to further improve efficiency, but existing systems have lacked such functionality. Against this backdrop, there is a need for flexible file management methods that reflect user emotions.

[0374] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0375] In this invention, the server includes means for detecting when a file is uploaded from a user terminal, means for analyzing the contents of the uploaded file and generating a summary, means for extracting relevant tags from the generated summary, means for classifying and moving the file to an appropriate shared folder based on the extracted tags, means for processing the user's emotional data using an emotional recognition engine that recognizes the user's emotions, and means for supplementing and correcting the tags and summary generated based on the emotional data. This enables personalized file management that takes into account the user's emotional state.

[0376] A "user terminal" is a computing device used by a user to create, edit, and upload files.

[0377] "Means for detecting when a file is uploaded" refers to a function that recognizes when a file has been uploaded from a user's terminal to the server.

[0378] "Method for analyzing file contents and generating summaries" refers to a function that analyzes the contents of uploaded files, extracts important information, and summarizes it concisely.

[0379] "Method for extracting relevant tags" refers to a function that automatically extracts appropriate keywords and tags from the generated summary or file content.

[0380] "Method for classifying and moving files to appropriate shared folders" refers to a function that organizes and moves files to the most suitable folder based on extracted tags.

[0381] An "emotion recognition engine" is a technology for detecting and recognizing a user's emotional state in real time.

[0382] "Means for processing emotional data" refers to a function that processes the detected emotional state of a user as data.

[0383] "Means for supplementing and correcting generated tags and summaries" refers to functions that adjust and correct already generated tags and summaries based on information including sentiment data.

[0384] This invention is a file management system that primarily comprises a user terminal, a server, and an emotion recognition engine. Specific examples of each element are shown below.

[0385] System Configuration

[0386] User terminal

[0387] A user terminal is a computing device used by users to create, edit, and upload files. It is equipped with an emotion recognition engine that can detect the user's emotional state in real time. Emotional states can range from stress, concentration, and excitement.

[0388] server

[0389] The server receives files uploaded from user terminals, analyzes them, and generates summaries. It also extracts relevant tags from the generated summaries and, based on this information, classifies and moves the files to appropriate shared folders. Generative artificial intelligence is implemented on the server, which is used for file content analysis and summary generation.

[0390] Program operation

[0391] emotion recognition

[0392] The emotion recognition engine analyzes the user's video feed and detects emotions in real time. Emotional data reflects the user's mental state while creating or editing files. This data is used as a crucial element in the file management process.

[0393] File analysis and summary generation

[0394] When the server receives a file, it first analyzes its contents. For example, in the case of a PDF file, it uses OCR technology to convert it into text data. Then, it uses a generative artificial intelligence model to generate a summary of the content. This summary concisely summarizes the key points of the file.

[0395] Tag generation and classification movement

[0396] Based on the generated summary, the server automatically creates relevant tags. This process also takes sentiment data into consideration. For example, files created in a "focused" state will be tagged "important." Based on the tags, the files are then categorized and moved to the appropriate shared folder.

[0397] Specific example

[0398] For example, suppose a user creates a file named "Project B Budget Report.xlsx" and uploads it to a shared folder. At this point, the emotion recognition engine detects the user's "high stress" state. The file's contents are analyzed, and tags such as "Budget," "Project B," and "Report" are generated. Finally, the server automatically moves this file to the " / Shared Folder / Project B / Budget Report" folder. If the user searches for "Project B Budget Report," they can immediately access the desired file.

[0399] Example of a prompt

[0400] Please generate a summary of the files tagged "Project". The following is the content of the files:

[0401] ---

[0402] The Project A progress report details the progress up to October. The main challenges are...

[0403] ---

[0404] Emotional data: Concentration

[0405] In this way, file management that takes into account the user's emotional state becomes possible, resulting in a system that significantly improves the efficiency of file searching and management.

[0406] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0407] Step 1:

[0408] The user's device uploads files created or edited by the user to a public folder. At this time, the device detects emotions in real time via the user's video feed using an emotion recognition engine and collects the data. The input consists of the uploaded file and collected emotion data. The output consists of an upload notification and emotion data.

[0409] Step 2:

[0410] The device detects file uploads and sends upload notifications and sentiment data to the server. Specifically, it makes an API call to notify the server of the uploaded file path and sentiment data. The inputs are the upload notification and sentiment data, and the output is the notification sent to the server.

[0411] Step 3:

[0412] The server receives the upload notification and identifies the target file. Next, it analyzes the file's contents. For example, in the case of a PDF file, it uses OCR technology (e.g., the "ocrmypdf" library) to convert it into text data. The input is the uploaded file, and the output is text data.

[0413] Step 4:

[0414] The server uses a generative artificial intelligence model to generate a summary from text data. Specifically, it inputs prompt sentences into the generative AI model and generates a summary. The input is text data and prompt sentences, and the output is a summary sentence.

[0415] Step 5:

[0416] The server extracts relevant tags based on the generated summary. Specifically, it analyzes the summary to extract keywords and then completes the tags based on sentiment data. The input is the summary and sentiment data, and the output is the relevant tags.

[0417] Step 6:

[0418] The server categorizes and moves files to the appropriate shared folders based on the extracted tags. Specifically, it determines the folder path based on the tags and moves the files to that path. The input is the associated tags and files, and the output is the new save path for the files.

[0419] Step 7:

[0420] When a user searches for files within a shared folder, they enter a search query. The server parses the search query, matches it against relevant tags to identify the target files, and returns the search results. Specifically, it executes a database query to find files with the specified tags. The input is the search query, and the output is the search results.

[0421] In this way, personalized file management and searching that takes into account the user's emotional state are achieved.

[0422] 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.

[0423] 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.

[0424] 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.

[0425] [Second Embodiment]

[0426] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0427] 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.

[0428] 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).

[0429] 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.

[0430] 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.

[0431] 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).

[0432] 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.

[0433] 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.

[0434] 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.

[0435] 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.

[0436] 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.

[0437] 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".

[0438] Embodiments of this invention will now be described. This system aims to facilitate file searching by efficiently managing user-created files and appropriately classifying and storing them within a shared folder.

[0439] System Configuration

[0440] 1. User terminal

[0441] It is a computing device that allows users to create and edit files in their local environment and upload them to their public folder.

[0442] 2. Server

[0443] It plays a central role in receiving uploaded files and performing a series of processes including analysis, summary generation, tagging, classification, and movement.

[0444] Program operation

[0445] File Upload

[0446] A user creates a file and uploads it to their public folder. For example, a user uploads "Project A Progress Report.doc" to their public folder.

[0447] The device detects this upload and notifies the server of information such as the file name and metadata.

[0448] File analysis and summary generation

[0449] The server receives notification of the upload and identifies the file. Next, the server analyzes the file's contents. For example, in the case of a PDF file, it uses OCR technology to convert it into text data.

[0450] The server uses generative artificial intelligence to generate a summary of the content, using the converted text data as input. For example, it might concisely summarize the contents of a file titled "Project A Progress Report."

[0451] Tag extraction

[0452] Based on the generated summary, the server extracts relevant tags. For example, it automatically generates tags such as "Project A," "Progress," "Report," and "October 2023."

[0453] File classification and movement

[0454] For tagged files, the server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Project A" and "Progress," the file might be moved to the " / sharedfolder / Project A / Progress" folder.

[0455] File Search

[0456] Users use the search interface to find the files they need within a shared folder. For example, they might search using the keyword "Project A Progress Report October 2023".

[0457] The server parses the search query, matches it with appropriate tags to identify the file, and returns the search results. As a result, the user can easily access the desired file.

[0458] Specific example

[0459] For example, suppose a user creates a file named "Project B Budget Report.xlsx" and uploads it to a shared folder. The server detects this file, analyzes its contents, and generates tags such as "Budget," "Project B," and "Report." The server then automatically moves this file to the " / Shared Folder / Project B / Budget Report" folder. If a user searches for "Project B Budget Report," the search results will immediately return the desired file, "Project B Budget Report.xlsx."

[0460] This system simplifies file classification and management, enabling more efficient work.

[0461] The following describes the processing flow.

[0462] Step 1:

[0463] The user creates a file on their local device and uploads it to their public folder. For example, they might upload "Project A Progress Report.doc".

[0464] Step 2:

[0465] The device detects uploaded files and notifies the server of metadata such as file name, file path, and upload time.

[0466] Step 3:

[0467] The server receives the upload notification and confirms that the new file has been added to the public folder.

[0468] Step 4:

[0469] The server reads the file and converts its contents into text format. For example, in the case of a PDF, OCR technology is used to convert it into text data.

[0470] Step 5:

[0471] The server takes the converted text data as input and invokes a generative artificial intelligence to analyze its content. The generative AI then generates a summary from the analyzed text data.

[0472] Step 6:

[0473] The server generates relevant tags based on the summary results from the generative AI. For example, it might extract tags such as "Project A," "Progress," "Report," and "October 2023."

[0474] Step 7:

[0475] The server-generated tags are added as metadata to the file.

[0476] Step 8:

[0477] Based on the extracted tags, the server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Project A" and "Progress," it identifies the folder " / Shared Folder / Project A / Progress."

[0478] Step 9:

[0479] The server physically moves the files from the public folder to the appropriate shared folder.

[0480] Step 10:

[0481] Users use the search interface to find the files they need within the shared folder. For example, they might enter a keyword such as "Project A Progress Report October 2023".

[0482] Step 11:

[0483] The server analyzes the search query and finds highly relevant files within the shared folder.

[0484] Step 12:

[0485] The server returns relevant files to the user as search results, making it easy for the user to access the desired files.

[0486] ---

[0487] This processing flow automates each step, allowing users to efficiently manage and search for files.

[0488] (Example 1)

[0489] 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".

[0490] In modern information management, a major problem is the scattering of large numbers of files, making organization and searching difficult. As a result, users often have to spend a great deal of time and effort to access the information they need. Furthermore, systems with advanced features such as proper file classification and summarization within shared folders, and automatic extraction of related tags, are limited.

[0491] 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.

[0492] In this invention, the server includes means for detecting when a file is uploaded from a user terminal, means for notifying the server of the metadata of the uploaded file, means for analyzing the contents of the uploaded file and extracting text data, means for generating a summary using generative artificial intelligence with respect to the extracted text data, means for extracting relevant tags from the generated summary, means for classifying and moving files to appropriate shared folders based on the extracted tags, means for the user to perform a file search based on tags using a search interface, and means for the server to analyze the search query, identify the relevant files, and return the search results. This automates the organization and management of large numbers of files, enabling users to quickly and efficiently access the information they need.

[0493] A "user terminal" refers to a computing device used by a user, such as a computer, smartphone, or tablet.

[0494] A "server" is a computing system that receives uploaded files and performs analysis, summarization, tagging, classification / movement, and analysis of search queries.

[0495] "Uploading" refers to the act of transferring files from a user's device to a server.

[0496] "Metadata" refers to additional information about a file, such as file name, creation date and time, and file size.

[0497] "Analysis" is the process of deciphering the contents of uploaded files and extracting useful information such as text data.

[0498] "OCR technology" is an optical character recognition technology used to extract text data from image data.

[0499] A "text extraction library" is a software component used to extract text data from files such as DOC and XLSX.

[0500] "Generative artificial intelligence" refers to artificial intelligence technology that performs text summarization and generation based on input data.

[0501] A "summary" is a text that concisely summarizes the contents of a file.

[0502] A "tag" is a keyword or label that indicates the specific content or attributes of a file.

[0503] A "shared folder" is a data storage area that can be accessed by multiple users.

[0504] "Classification and relocation" is the process of sorting files into the appropriate folders based on the extracted tags.

[0505] A "search interface" is a user interface that allows users to search for necessary files by entering tags or keywords.

[0506] A "search query" is a search word or phrase that a user enters into the search interface.

[0507] "Search results" refer to a list of files that the server identifies and returns to the user based on the search query.

[0508] This invention relates to a system for users to create, efficiently manage, and properly classify and store files within a shared folder. It enables users to quickly and efficiently access the information they need.

[0509] Hardware to use

[0510] 1. User terminal: A computing device such as a computer, smartphone, or tablet used by the user to create files and upload them to a public folder.

[0511] 2. Servers: Cloud servers and on-premises servers are used to receive, analyze, summarize, tag, classify, and move files.

[0512] Software to use

[0513] 1. File analysis software:

[0514] OCR technology (e.g., Tesseract) is used to analyze PDF files.

[0515] Text extraction from DOC and XLSX files is performed using a text extraction library (e.g., Apache POI).

[0516] 2. Generative Artificial Intelligence: Generative artificial intelligence (e.g., OpenAI GPT-3) will be used to generate summaries of file contents.

[0517] 3. File Management System: A proprietary management system for uploading, notifying, and storing files.

[0518] Explanation of natural language processing

[0519] File upload:

[0520] The user creates a file named "Project A Progress Report.doc" and uploads it to the public folder. The device detects this upload and notifies the server of information such as the file name and metadata.

[0521] File analysis:

[0522] The server receives the upload notification and identifies the file. Next, the server analyzes the file content. For PDF files, it uses OCR technology to convert them into text data. For DOC and XLSX files, it uses a text extraction library to extract the text data.

[0523] Summary generation:

[0524] Using the extracted text data, the server generates a summary of the content using generative artificial intelligence. For example, it might concisely summarize the contents of the "Project A Progress Report" file.

[0525] Tag extraction:

[0526] Based on the generated summary, the server extracts relevant tags. For example, tags such as "Project A," "Progress," "Report," and "October 2023" are automatically generated.

[0527] File classification and movement:

[0528] For tagged files, the server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Project A" and "Progress," the file might be moved to the " / Shared Folder / Project A / Progress" folder.

[0529] Search for files:

[0530] When a user searches for a file within a shared folder, they use the search interface. For example, they might search using the keyword "Project A Progress Report October 2023". The server parses the search query, matches it with appropriate tags to identify the file, and returns the search results. As a result, the user can easily access the desired file.

[0531] Specific example

[0532] For example, suppose a user creates a file named "Project B Budget Report.xlsx" and uploads it to a shared folder. The server analyzes its contents and generates tags such as "Budget," "Project B," and "Report." The server then automatically moves this file to the " / Shared Folder / Project B / Budget Report" folder. If a user searches for "Project B Budget Report," the desired file, "Project B Budget Report.xlsx," will be immediately returned as a search result. This system simplifies file classification and management, enabling more efficient work.

[0533] Example of a prompt

[0534] Example prompt message for when you upload "Project A progress report.doc":

[0535] A user uploaded "Project A Progress Report.doc" to the public folder. This file was converted to text using OCR technology, and then an automatic summary was generated. Relevant tags such as "Project A," "Progress," "Report," and "October 2023" were then added, and it was categorized into the appropriate folder. This allows users to quickly find the desired file by searching for "Project A Progress Report October 2023."

[0536] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0537] Processing flow of this system

[0538] Step 1: File Upload Detection

[0539] Users create files on their own devices and upload them to a public folder.

[0540] The device monitors changes to the public folder in real time and detects when new files are added.

[0541] Input: A file uploaded by the user to a public folder (e.g., "Project A Progress Report.doc")

[0542] Output: Notification that a file has been uploaded

[0543] Step 2: Metadata Notification

[0544] The terminal notifies the server of the file name and metadata (file path, creation date and time, etc.).

[0545] Input: Metadata of the uploaded file

[0546] Output: Metadata notification to the server

[0547] Step 3: Analyze the files

[0548] The server receives the upload notification and identifies the relevant file.

[0549] The server analyzes the file contents and extracts text data.

[0550] For PDF files, use OCR technology (e.g., Tesseract) to extract text from the image.

[0551] For DOC and XLSX files, use a text extraction library (e.g., Apache POI) to extract the text data.

[0552] Input: Uploaded file

[0553] Output: Extracted text data

[0554] Step 4: Summary Generation

[0555] The server inputs the extracted text data into a generative artificial intelligence (e.g., GPT-3) to generate a summary of its content.

[0556] The generated summary will include a report detailing the progress and future plans for Project A.

[0557] Input: Extracted text data

[0558] Output: Summary text

[0559] Step 5: Tag Extraction

[0560] The server extracts relevant tags based on the generated summary.

[0561] Using natural language processing technology (e.g., spaCy), tags such as "Project A," "Progress," and "Report" are automatically generated.

[0562] Input: Summary text

[0563] Output: Extracted tag list

[0564] Step 6: File classification and movement

[0565] The server identifies the appropriate folder based on the tags and moves the files to that folder.

[0566] Based on the tags, folders such as " / shared folder / project A / progress" are selected.

[0567] Input: Extracted tag list

[0568] Output: New path to the file

[0569] Step 7: Search for files

[0570] The user searches for files using the search interface.

[0571] Enter keywords such as "Project A Progress Report October 2023".

[0572] Input: User's search keywords

[0573] Output: Search query

[0574] Step 8: Parse the search query and return the results.

[0575] The server parses the search query, matches it with tags, identifies the relevant files, and returns the search results.

[0576] Input: Search query

[0577] Output: List of identified files

[0578] This system allows users to automatically organize and manage large amounts of files, enabling them to quickly access the information they need.

[0579] (Application Example 1)

[0580] 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."

[0581] Logistics centers generate a large volume of documents and data daily, making efficient management and retrieval a significant challenge. Manually classifying and storing paper-based documents and multiple digital files is time-consuming, labor-intensive, and prone to human error. Therefore, it is necessary to improve document management efficiency, reduce the workload on staff, and enable quick and accurate searching and access.

[0582] 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.

[0583] In this invention, the server includes means for detecting when a file is uploaded, means for analyzing the contents of the uploaded file and generating a summary, means for extracting relevant tags from the generated summary, means for classifying and moving files to appropriate shared folders based on the extracted tags, means for automatically creating and classifying folders based on the contents of the uploaded file, means for generating summaries and tags using generative artificial intelligence, and means for analyzing and storing data using a cloud server. This enables improved efficiency and accuracy in file management.

[0584] A "user terminal" is a computing device operated by a user, and is a device used for creating, editing, and uploading files.

[0585] A "file" is a form of electronic data, a recording medium that contains various types of information, such as documents, images, and spreadsheet data.

[0586] "Uploading" refers to the operation of sending data files from a local environment to a remote environment such as a server.

[0587] "Analysis" is the process of examining the contents of an uploaded file and understanding its structure and elements.

[0588] A "summary" is a concise, abbreviated version of the file's contents.

[0589] A "tag" is an identification label assigned to data to facilitate classification and searching.

[0590] A "shared folder" is a folder that can be accessed by multiple users and serves as a storage area for files.

[0591] A "cloud server" is a remote server accessible via the internet, used for data storage and analysis.

[0592] "Generative artificial intelligence" refers to artificial intelligence technology used to generate new information based on input data.

[0593] "Automatic creation" refers to a process where the system autonomously generates folders and other elements without user intervention.

[0594] "Classification" is the act of grouping files according to specific criteria.

[0595] "Moving" refers to the operation of physically or logically rearranging a file from one location to another.

[0596] This invention will now be described in terms of embodiments for carrying it out. This system is intended to efficiently manage documents and data files in a logistics center.

[0597] This system mainly consists of user terminals and cloud servers.

[0598] User terminal

[0599] User terminals are computing devices such as smartphones and tablets used by staff at the logistics center. Users can create and edit files from their own devices and upload them to the system.

[0600] server

[0601] Cloud servers are the core components that process uploaded files, handling a series of operations including analysis, summary generation, tagging, classification, and migration.

[0602] System operation procedure

[0603] 1. Upload files

[0604] When a user uploads a file from their smartphone, the device detects the upload and notifies the cloud server of the file's metadata, name, and other information.

[0605] 2. File analysis and summary generation

[0606] The cloud server receives the uploaded information and analyzes the contents of files such as Word documents and PDFs. It may also use OCR technology to extract text data from image files. Next, generative artificial intelligence is used based on the extracted text data to generate a summary of the content. For example, it might concisely summarize the contents of "Inventory List 2023.doc".

[0607] 3. Tag extraction

[0608] Based on the generated summary, the cloud server extracts relevant tags. For example, it automatically generates tags such as "inventory," "list," and "2023."

[0609] 4. File classification and movement

[0610] For tagged files, the cloud server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Inventory" and "List," it moves the files to the " / Logistics / Inventory" folder. Folders are automatically created as needed.

[0611] Hardware and software to use

[0612] Smartphone: Use it to upload and manage files.

[0613] Cloud server: Performs data analysis and storage.

[0614] Watchdog: A library for detecting file changes.

[0615] Transformers is a library that provides generative artificial intelligence models, performing summary generation and tagging.

[0616] Specific example

[0617] For example, if a staff member uploads "Inventory List 2023.pdf" from their smartphone, the cloud server receives the file and converts its contents into text using OCR technology. Next, it generates a summary using generative artificial intelligence and extracts tags such as "Inventory," "List," and "2023." Based on these tags, the cloud server then identifies the " / Logistics / Inventory" folder, automatically creates the folder if necessary, and moves the file there. When a user searches for "Inventory List 2023," they can immediately access the desired file.

[0618] Example of a prompt

[0619] Examples of prompts to input into a generative artificial intelligence are as follows:

[0620] "Please briefly summarize the contents of the 2023 inventory list."

[0621] In this way, this invention can achieve improved efficiency and accuracy in file management.

[0622] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0623] Step 1:

[0624] The user uploads a file from their smartphone.

[0625] Input: Created file

[0626] Operation: This involves a user at a logistics center saving new documents, reports, and other files to their smartphone and then uploading them to a cloud system.

[0627] Output: Upload event occurrence and file metadata

[0628] Step 2:

[0629] The device detects the file upload.

[0630] Input: Uploaded file

[0631] Operation: The user terminal detects the moment a file is uploaded to the system and retrieves the file's name and other metadata.

[0632] Output: File metadata and upload notification

[0633] Step 3:

[0634] The server receives the upload notification and analyzes the file contents.

[0635] Input: File metadata and actual file

[0636] Operation: The server retrieves the uploaded files and analyzes their contents. It uses OCR technology to convert image files into text data and reads the contents of document files as text.

[0637] Output: Analyzed text data

[0638] Step 4:

[0639] The server uses generative artificial intelligence to generate a summary from the analyzed text data.

[0640] Input: Parsed text data

[0641] Operation: The server supplies the analyzed text data as input to a generative artificial intelligence system, which then generates a summary. The prompt used is "Please summarize the content concisely."

[0642] Output: Generated summary

[0643] Step 5:

[0644] The server extracts relevant tags from the generated summary.

[0645] Input: Generated summary

[0646] Operation: The server analyzes the summary and uses generative artificial intelligence to extract relevant tags. For example, tags are determined based on keywords and important terms contained in the summary.

[0647] Output: Extracted tags

[0648] Step 6:

[0649] The server categorizes and moves files to the appropriate shared folder based on the extracted tags.

[0650] Input: Extracted tags

[0651] Operation: The server determines the file's storage location based on its tags. If the corresponding folder does not exist, it automatically creates a new folder as needed and moves the file into it. If the file is named "Inventory List 2023", it will be moved to the " / Logistics / Inventory" folder.

[0652] Output: Files moved to the appropriate folder

[0653] Step 7:

[0654] The user searches for files within the shared folder.

[0655] Input: Search keyword

[0656] Operation: Users use a search interface on their smartphones to search for necessary files. For example, they might search using the keyword "Inventory List 2023".

[0657] Output: List of related files

[0658] 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.

[0659] Embodiments of this invention will now be described. This system aims to facilitate file searching by efficiently managing user-created files and appropriately classifying and storing them within a shared folder. Furthermore, by incorporating an emotion engine that recognizes user emotions, more flexible and personalized file management becomes possible.

[0660] System Configuration

[0661] 1. User terminal

[0662] It is a computing device that allows users to create and edit files in their local environment and upload them to their public folder. It is equipped with an emotion engine that can detect the user's emotional state in real time.

[0663] 2. Server

[0664] It plays a central role in receiving uploaded files and performing a series of processes including analysis, summary generation, tagging, classification, and movement. It complements file management based on sentiment data obtained from the sentiment engine.

[0665] Program operation

[0666] File Upload

[0667] A user creates a file and uploads it to their public folder. For example, they might upload "Project A Progress Report.doc".

[0668] The device detects this upload and notifies the server of information such as the file name and metadata.

[0669] File analysis and summary generation

[0670] The server receives notification of the upload and identifies the file. Next, the server analyzes the file's contents. For example, in the case of a PDF file, it uses OCR technology to convert it into text data.

[0671] The server uses generative artificial intelligence to generate a summary of the content, using the converted text data as input. For example, it might concisely summarize the contents of a file titled "Project A Progress Report."

[0672] Tag extraction

[0673] Based on the generated summary, the server generates relevant tags. For example, it automatically generates tags such as "Project A," "Progress," "Report," and "October 2023."

[0674] Acquisition and reflection of emotional data

[0675] An emotion engine that recognizes user emotions detects the user's emotional state when creating or editing files and sends that data to the server. Emotion data includes states such as "stress," "concentration," and "excitement."

[0676] Based on this sentiment data, the server supplements and modifies the generated tags and summaries, and further reflects them in the file's metadata. For example, a file created by a user while highly focused will be tagged "focused" and judged to be of high importance.

[0677] File classification and movement

[0678] For tagged files, the server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Project A" and "Progress," the file might be moved to the " / sharedfolder / Project A / Progress" folder.

[0679] File Search

[0680] Users use the search interface to find the files they need within a shared folder. For example, they might search using the keyword "Project A Progress Report October 2023".

[0681] The server parses the search query, matches it with appropriate tags to identify the file, and returns the search results. As a result, the user can easily access the desired file.

[0682] Specific example

[0683] For example, suppose a user creates a file named "Project B Budget Report.xlsx" and uploads it to a shared folder. The server detects this file, analyzes its contents, and generates tags such as "Budget," "Project B," and "Report." The sentiment engine recognizes the user's "high stress" state and adds this information to the metadata as well. The server then automatically moves this file to the " / Shared Folder / Project B / Budget Report" folder. If a user searches for "Project B Budget Report," the search results will immediately return the desired file, "Project B Budget Report.xlsx."

[0684] This system simplifies file classification and management, enabling more efficient work. Furthermore, the introduction of an emotion engine allows for personalized file management that takes into account the user's emotional state.

[0685] The following describes the processing flow.

[0686] Step 1:

[0687] The user creates a file on their local device and uploads it to their public folder. For example, they might upload "Project A Progress Report.doc" to their public folder.

[0688] Step 2:

[0689] The device detects uploaded files and notifies the server of metadata such as file name, file path, and upload time.

[0690] Step 3:

[0691] The server receives the upload notification and confirms that the new file has been added to the public folder.

[0692] Step 4:

[0693] The server reads the file and converts its contents into text format. For example, in the case of a PDF, OCR technology is used to convert it into text data.

[0694] Step 5:

[0695] The server takes the converted text data as input and invokes a generative artificial intelligence to analyze its content. The generative AI then generates a summary from the analyzed text data.

[0696] Step 6:

[0697] The server generates relevant tags based on the summary results from the generative AI. For example, it might extract tags such as "Project A," "Progress," "Report," and "October 2023."

[0698] Step 7:

[0699] The server-generated tags are added as metadata to the file.

[0700] Step 8:

[0701] The emotion engine detects the user's emotional state in real time and sends that data to the server. Emotional data includes states such as "stress," "concentration," and "excitement."

[0702] Step 9:

[0703] The server receives sentiment data and uses it to supplement and modify tags and summaries generated from that data. For example, a file created by a user while highly focused will be tagged "focused" and judged to be of high importance.

[0704] Step 10:

[0705] Based on the extracted tags, the server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Project A" and "Progress," it identifies the folder " / Shared Folder / Project A / Progress."

[0706] Step 11:

[0707] The server physically moves the files from the public folder to the appropriate shared folder.

[0708] Step 12:

[0709] Users use the search interface to find the files they need within the shared folder. For example, they might enter a keyword such as "Project A Progress Report October 2023".

[0710] Step 13:

[0711] The server analyzes the search query and finds highly relevant files within the shared folder.

[0712] Step 14:

[0713] The server returns relevant files to the user as search results, making it easy for the user to access the desired files.

[0714] This processing flow automates each step, allowing users to efficiently manage and search for files. Furthermore, the introduction of an emotion engine enables personalized file management that takes into account the user's emotional state. For example, when a user creates "Project B Budget Report.xlsx" and uploads it to a shared folder, the system detects that the user is in a high-stress state and adds this information to the metadata. Based on this information, the server determines the file is important, assigns appropriate tags, and moves it to " / shared folder / Project B / Budget Report". If the user then searches for "Project B Budget Report," the desired file is immediately returned as a search result.

[0715] (Example 2)

[0716] 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".

[0717] Traditional file management systems often require manual file classification and searching, which is time-consuming and labor-intensive. Furthermore, they fail to consider user work efficiency and emotional state, making efficient and flexible file management difficult. As a result, file locator and work comfort are compromised, leading to increased user burden.

[0718] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for detecting when a file is uploaded from a user terminal, means for analyzing the contents of the uploaded file and generating a summary, means for extracting relevant tags from the generated summary, means for detecting the user's emotional state in real time, means for transmitting the detected emotional data to the server, means for supplementing and correcting the tags and summaries generated based on the emotional data, and means for classifying and moving files to appropriate shared folders based on the extracted tags. This enables efficient automatic classification and searching of files, and in addition, personalized file management according to the user's emotional state.

[0719] A "user terminal" is a computing device that a user uses to create, edit, and upload files.

[0720] A "server" is a central computer system that receives, analyzes, summarizes, tags, classifies, moves, and processes sentiment data for uploaded files.

[0721] "Methods for analyzing file contents" refers to technologies that analyze the text and image data of uploaded files to summarize their contents and extract tags.

[0722] "Methods for generating summaries" refers to techniques that shorten the contents of a file and concisely summarize important information.

[0723] "Methods for extracting tags" refers to technologies that perform a process of automatically extracting relevant keywords from the contents of a file or the generated summary.

[0724] "Methods for detecting emotional states in real time" refers to technologies that analyze and detect a user's emotional state in real time based on their facial expressions, voice, and other factors.

[0725] "Means for transmitting emotional data" refers to communication technology for sending data about a user's emotional state to a server.

[0726] "Methods for supplementing and correcting tags and summaries" refers to technologies that perform the process of correcting and supplementing tags and summaries generated based on detected sentiment data.

[0727] "Methods for classifying and moving files to shared folders" refers to technologies for classifying files into appropriate subfolders based on generated tags and then moving them to those folders.

[0728] Embodiments of this invention will now be described. This system aims to facilitate file searching by efficiently managing user-created files and appropriately classifying and storing them within a shared folder. Furthermore, by incorporating an emotion engine that recognizes user emotions, more flexible and personalized file management becomes possible.

[0729] System Configuration

[0730] 1. User terminal

[0731] A user terminal is a computing device used by a user to create and edit files in their local environment. Examples include personal computers and smartphones. Terminals are equipped with an emotion engine that can detect the user's emotional state in real time from their facial expressions and voice. Specifically, facial recognition software and voice recognition software are used for this purpose.

[0732] 2. Server

[0733] The server receives files uploaded from user terminals, analyzes their content, and generates summaries. The software used includes OCR technology, natural language processing technology, and generative AI models (e.g., GPT-4). It also receives sentiment data from the sentiment engine and uses it to complete and modify tags and summaries. Specifically, OCR engines such as Tesseract are used for analyzing file content, and generative artificial intelligence (e.g., generative AI models) are used for summary generation.

[0734] Program operation

[0735] File Upload

[0736] A user creates a file and uploads it to their public folder. For example, they might upload "Project A Progress Report.doc". The device detects this upload and notifies the server of information such as the file name and metadata.

[0737] File analysis and summary generation

[0738] The server receives an upload notification and identifies the file. Next, the server analyzes the file's contents. For example, in the case of a PDF file, it uses OCR technology to convert it into text data. Using the converted text data as input, the server uses generative artificial intelligence to generate a summary of the content. For example, it might concisely summarize the contents of a file titled "Project A Progress Report."

[0739] Tag extraction

[0740] Based on the generated summary, the server generates relevant tags. For example, it automatically generates tags such as "Project A," "Progress," "Report," and "October 2023."

[0741] Acquisition and reflection of emotional data

[0742] An emotion engine that recognizes user emotions detects the user's emotional state when creating or editing files and sends that data to the server. This emotion data includes states such as "stress," "concentration," and "excitement." The server uses this emotion data to supplement and modify generated tags and summaries, and further reflects this in the file's metadata. For example, a file created by a user in a highly focused state will be tagged "concentration" and judged to be of high importance.

[0743] Specific example

[0744] For example, suppose a user creates a file named "Project B Budget Report.xlsx" and uploads it to a shared folder. The server detects this file, analyzes its contents, and generates tags such as "Budget," "Project B," and "Report." The sentiment engine recognizes the user's "high stress" state and adds this information to the metadata as well. The server then automatically moves this file to the " / Shared Folder / Project B / Budget Report" folder. If a user searches for "Project B Budget Report," the search results will immediately return the desired file, "Project B Budget Report.xlsx."

[0745] This system simplifies file classification and management, enabling more efficient work. Furthermore, the introduction of an emotion engine allows for personalized file management that takes into account the user's emotional state.

[0746] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0747] Program processing flow

[0748] Step 1: Create and upload files

[0749] The user creates a file, for example, "Project A Progress Report.doc". The input is a file created by the user on a device such as a PC or smartphone.

[0750] Users upload files they have created to their public folder. For example, they can drag and drop files into the public folder or click the upload button. The output is the file uploaded to the public folder.

[0751] Step 2: Upload detection and notification

[0752] The device detects when a new file has been uploaded to the public folder. Specifically, it uses a file system monitoring tool to periodically check for changes in the folder. The input is a list of files in the public folder.

[0753] The terminal notifies the server of information about the uploaded file (file name, size, metadata, etc.). The output is the file information sent to the server.

[0754] Step 3: File analysis and summary generation

[0755] The server receives the upload notification and retrieves the corresponding file. The input is the file information sent from the device.

[0756] The server analyzes the file's contents. For example, in the case of a PDF file, it uses OCR technology to convert it into text data. Specifically, it uses an OCR engine such as Tesseract. The output is the converted text data.

[0757] The server uses a generative artificial intelligence (e.g., GPT-4) as input to convert the text data and generates a summary of its contents. The output is a summary of the file's contents.

[0758] Step 4: Tag Extraction

[0759] The server generates relevant tags based on the generated summary. For example, it may use natural language processing techniques to extract keywords from the summary. The input is the generated summary.

[0760] The server generates relevant tags. For example, it extracts tags such as "Project A," "Progress," "Report," and "October 2023." The output is a list of the extracted tags.

[0761] Step 5: Acquisition and reflection of emotional data

[0762] The device uses an emotion engine to detect the user's emotional state in real time when creating or editing files. Specifically, it uses facial recognition software and speech recognition software. The input consists of the user's facial expressions and voice data.

[0763] The device sends detected emotional data to the server. This data may include states such as "stress," "concentration," and "excitement." The output is the emotional data sent to the server.

[0764] The server uses sentiment data to supplement and modify the generated tags and summaries. For example, it adds the "focused" tag to files deemed highly important. The output consists of the supplemented and modified tags and summary text.

[0765] Step 6: Classify and move files

[0766] The server identifies the appropriate subfolder within the shared folder based on the extracted tags. For example, based on the tags "Project A" and "Progress," it identifies the folder " / sharedfolder / Project A / Progress." The input is a list of tags.

[0767] The server moves the file to a specified subfolder. Specifically, it uses a file manipulation API to move the file. The output is the file moved to the appropriate subfolder.

[0768] Step 7: Search for files

[0769] When a user needs to find a file, they use the search interface. For example, they might enter the keyword "Project A Progress Report October 2023" into the search bar. The input is the search query entered by the user.

[0770] The server parses the search query and identifies files based on relevant tags. Specifically, it uses a full-text search engine to search for indexed tags and metadata. The output is a file list as search results.

[0771] The user accesses the desired file from the search results. For example, they click on "Project A Progress Report.doc" to open it.

[0772] (Application Example 2)

[0773] 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."

[0774] In today's digital society, file management and retrieval are critical challenges. Especially in environments where a large number of files are generated daily, proper classification and rapid searching are essential. Furthermore, file management that considers user emotions and context has the potential to further improve efficiency, but existing systems have lacked such functionality. Against this backdrop, there is a need for flexible file management methods that reflect user emotions.

[0775] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0776] In this invention, the server includes means for detecting when a file is uploaded from a user terminal, means for analyzing the contents of the uploaded file and generating a summary, means for extracting relevant tags from the generated summary, means for classifying and moving the file to an appropriate shared folder based on the extracted tags, means for processing the user's emotional data using an emotional recognition engine that recognizes the user's emotions, and means for supplementing and correcting the tags and summary generated based on the emotional data. This enables personalized file management that takes into account the user's emotional state.

[0777] A "user terminal" is a computing device used by a user to create, edit, and upload files.

[0778] "Means for detecting when a file is uploaded" refers to a function that recognizes when a file has been uploaded from a user's terminal to the server.

[0779] "Method for analyzing file contents and generating summaries" refers to a function that analyzes the contents of uploaded files, extracts important information, and summarizes it concisely.

[0780] "Method for extracting relevant tags" refers to a function that automatically extracts appropriate keywords and tags from the generated summary or file content.

[0781] "Method for classifying and moving files to appropriate shared folders" refers to a function that organizes and moves files to the most suitable folder based on extracted tags.

[0782] An "emotion recognition engine" is a technology for detecting and recognizing a user's emotional state in real time.

[0783] "Means for processing emotional data" refers to a function that processes the detected emotional state of a user as data.

[0784] "Means for supplementing and correcting generated tags and summaries" refers to functions that adjust and correct already generated tags and summaries based on information including sentiment data.

[0785] This invention is a file management system that primarily comprises a user terminal, a server, and an emotion recognition engine. Specific examples of each element are shown below.

[0786] System Configuration

[0787] User terminal

[0788] A user terminal is a computing device used by users to create, edit, and upload files. It is equipped with an emotion recognition engine that can detect the user's emotional state in real time. Emotional states can range from stress, concentration, and excitement.

[0789] server

[0790] The server receives files uploaded from user terminals, analyzes them, and generates summaries. It also extracts relevant tags from the generated summaries and, based on this information, classifies and moves the files to appropriate shared folders. Generative artificial intelligence is implemented on the server, which is used for file content analysis and summary generation.

[0791] Program operation

[0792] emotion recognition

[0793] The emotion recognition engine analyzes the user's video feed and detects emotions in real time. Emotional data reflects the user's mental state while creating or editing files. This data is used as a crucial element in the file management process.

[0794] File analysis and summary generation

[0795] When the server receives a file, it first analyzes its contents. For example, in the case of a PDF file, it uses OCR technology to convert it into text data. Then, it uses a generative artificial intelligence model to generate a summary of the content. This summary concisely summarizes the key points of the file.

[0796] Tag generation and classification movement

[0797] Based on the generated summary, the server automatically creates relevant tags. This process also takes sentiment data into consideration. For example, files created in a "focused" state will be tagged "important." Based on the tags, the files are then categorized and moved to the appropriate shared folder.

[0798] Specific example

[0799] For example, suppose a user creates a file named "Project B Budget Report.xlsx" and uploads it to a shared folder. At this point, the emotion recognition engine detects the user's "high stress" state. The file's contents are analyzed, and tags such as "Budget," "Project B," and "Report" are generated. Finally, the server automatically moves this file to the " / Shared Folder / Project B / Budget Report" folder. If the user searches for "Project B Budget Report," they can immediately access the desired file.

[0800] Example of a prompt

[0801] Please generate a summary of the files tagged "Project". The following is the content of the files:

[0802] ---

[0803] The Project A progress report details the progress up to October. The main challenges are...

[0804] ---

[0805] Emotional data: Concentration

[0806] In this way, file management that takes into account the user's emotional state becomes possible, resulting in a system that significantly improves the efficiency of file searching and management.

[0807] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0808] Step 1:

[0809] The user's device uploads files created or edited by the user to a public folder. At this time, the device detects emotions in real time via the user's video feed using an emotion recognition engine and collects the data. The input consists of the uploaded file and collected emotion data. The output consists of an upload notification and emotion data.

[0810] Step 2:

[0811] The device detects file uploads and sends upload notifications and sentiment data to the server. Specifically, it makes an API call to notify the server of the uploaded file path and sentiment data. The inputs are the upload notification and sentiment data, and the output is the notification sent to the server.

[0812] Step 3:

[0813] The server receives the upload notification and identifies the target file. Next, it analyzes the file's contents. For example, in the case of a PDF file, it uses OCR technology (e.g., the "ocrmypdf" library) to convert it into text data. The input is the uploaded file, and the output is text data.

[0814] Step 4:

[0815] The server uses a generative artificial intelligence model to generate a summary from text data. Specifically, it inputs prompt sentences into the generative AI model and generates a summary. The input is text data and prompt sentences, and the output is a summary sentence.

[0816] Step 5:

[0817] The server extracts relevant tags based on the generated summary. Specifically, it analyzes the summary to extract keywords and then completes the tags based on sentiment data. The input is the summary and sentiment data, and the output is the relevant tags.

[0818] Step 6:

[0819] The server categorizes and moves files to the appropriate shared folders based on the extracted tags. Specifically, it determines the folder path based on the tags and moves the files to that path. The input is the associated tags and files, and the output is the new save path for the files.

[0820] Step 7:

[0821] When a user searches for files within a shared folder, they enter a search query. The server parses the search query, matches it against relevant tags to identify the target files, and returns the search results. Specifically, it executes a database query to find files with the specified tags. The input is the search query, and the output is the search results.

[0822] In this way, personalized file management and searching that takes into account the user's emotional state are achieved.

[0823] 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.

[0824] 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.

[0825] 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.

[0826] [Third Embodiment]

[0827] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0828] 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.

[0829] 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).

[0830] 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.

[0831] 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.

[0832] 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).

[0833] 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.

[0834] 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.

[0835] 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.

[0836] 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.

[0837] 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.

[0838] 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".

[0839] Embodiments of this invention will now be described. This system aims to facilitate file searching by efficiently managing user-created files and appropriately classifying and storing them within a shared folder.

[0840] System Configuration

[0841] 1. User terminal

[0842] It is a computing device that allows users to create and edit files in their local environment and upload them to their public folder.

[0843] 2. Server

[0844] It plays a central role in receiving uploaded files and performing a series of processes including analysis, summary generation, tagging, classification, and movement.

[0845] Program operation

[0846] File Upload

[0847] A user creates a file and uploads it to their public folder. For example, a user uploads "Project A Progress Report.doc" to their public folder.

[0848] The device detects this upload and notifies the server of information such as the file name and metadata.

[0849] File analysis and summary generation

[0850] The server receives notification of the upload and identifies the file. Next, the server analyzes the file's contents. For example, in the case of a PDF file, it uses OCR technology to convert it into text data.

[0851] The server uses generative artificial intelligence to generate a summary of the content, using the converted text data as input. For example, it might concisely summarize the contents of a file titled "Project A Progress Report."

[0852] Tag extraction

[0853] Based on the generated summary, the server extracts relevant tags. For example, it automatically generates tags such as "Project A," "Progress," "Report," and "October 2023."

[0854] File classification and movement

[0855] For tagged files, the server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Project A" and "Progress," the file might be moved to the " / sharedfolder / Project A / Progress" folder.

[0856] File Search

[0857] Users use the search interface to find the files they need within a shared folder. For example, they might search using the keyword "Project A Progress Report October 2023".

[0858] The server parses the search query, matches it with appropriate tags to identify the file, and returns the search results. As a result, the user can easily access the desired file.

[0859] Specific example

[0860] For example, suppose a user creates a file named "Project B Budget Report.xlsx" and uploads it to a shared folder. The server detects this file, analyzes its contents, and generates tags such as "Budget," "Project B," and "Report." The server then automatically moves this file to the " / Shared Folder / Project B / Budget Report" folder. If a user searches for "Project B Budget Report," the search results will immediately return the desired file, "Project B Budget Report.xlsx."

[0861] This system simplifies file classification and management, enabling more efficient work.

[0862] The following describes the processing flow.

[0863] Step 1:

[0864] The user creates a file on their local device and uploads it to their public folder. For example, they might upload "Project A Progress Report.doc".

[0865] Step 2:

[0866] The device detects uploaded files and notifies the server of metadata such as file name, file path, and upload time.

[0867] Step 3:

[0868] The server receives the upload notification and confirms that the new file has been added to the public folder.

[0869] Step 4:

[0870] The server reads the file and converts its contents into text format. For example, in the case of a PDF, OCR technology is used to convert it into text data.

[0871] Step 5:

[0872] The server takes the converted text data as input and invokes a generative artificial intelligence to analyze its content. The generative AI then generates a summary from the analyzed text data.

[0873] Step 6:

[0874] The server generates relevant tags based on the summary results from the generative AI. For example, it might extract tags such as "Project A," "Progress," "Report," and "October 2023."

[0875] Step 7:

[0876] The server-generated tags are added as metadata to the file.

[0877] Step 8:

[0878] Based on the extracted tags, the server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Project A" and "Progress," it identifies the folder " / Shared Folder / Project A / Progress."

[0879] Step 9:

[0880] The server physically moves the files from the public folder to the appropriate shared folder.

[0881] Step 10:

[0882] Users use the search interface to find the files they need within the shared folder. For example, they might enter a keyword such as "Project A Progress Report October 2023".

[0883] Step 11:

[0884] The server analyzes the search query and finds highly relevant files within the shared folder.

[0885] Step 12:

[0886] The server returns relevant files to the user as search results, making it easy for the user to access the desired files.

[0887] ---

[0888] This processing flow automates each step, allowing users to efficiently manage and search for files.

[0889] (Example 1)

[0890] 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."

[0891] In modern information management, a major problem is the scattering of large numbers of files, making organization and searching difficult. As a result, users often have to spend a great deal of time and effort to access the information they need. Furthermore, systems with advanced features such as proper file classification and summarization within shared folders, and automatic extraction of related tags, are limited.

[0892] 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.

[0893] In this invention, the server includes means for detecting when a file is uploaded from a user terminal, means for notifying the server of the metadata of the uploaded file, means for analyzing the contents of the uploaded file and extracting text data, means for generating a summary using generative artificial intelligence with respect to the extracted text data, means for extracting relevant tags from the generated summary, means for classifying and moving files to appropriate shared folders based on the extracted tags, means for the user to perform a file search based on tags using a search interface, and means for the server to analyze the search query, identify the relevant files, and return the search results. This automates the organization and management of large numbers of files, enabling users to quickly and efficiently access the information they need.

[0894] A "user terminal" refers to a computing device used by a user, such as a computer, smartphone, or tablet.

[0895] A "server" is a computing system that receives uploaded files and performs analysis, summarization, tagging, classification / movement, and analysis of search queries.

[0896] "Uploading" refers to the act of transferring files from a user's device to a server.

[0897] "Metadata" refers to additional information about a file, such as file name, creation date and time, and file size.

[0898] "Analysis" is the process of deciphering the contents of uploaded files and extracting useful information such as text data.

[0899] "OCR technology" is an optical character recognition technology used to extract text data from image data.

[0900] A "text extraction library" is a software component used to extract text data from files such as DOC and XLSX.

[0901] "Generative artificial intelligence" refers to artificial intelligence technology that performs text summarization and generation based on input data.

[0902] A "summary" is a text that concisely summarizes the contents of a file.

[0903] A "tag" is a keyword or label that indicates the specific content or attributes of a file.

[0904] A "shared folder" is a data storage area that can be accessed by multiple users.

[0905] "Classification and relocation" is the process of sorting files into the appropriate folders based on the extracted tags.

[0906] A "search interface" is a user interface that allows users to search for necessary files by entering tags or keywords.

[0907] A "search query" is a search word or phrase that a user enters into the search interface.

[0908] "Search results" refer to a list of files that the server identifies and returns to the user based on the search query.

[0909] This invention relates to a system for users to create, efficiently manage, and properly classify and store files within a shared folder. It enables users to quickly and efficiently access the information they need.

[0910] Hardware to use

[0911] 1. User terminal: A computing device such as a computer, smartphone, or tablet used by the user to create files and upload them to a public folder.

[0912] 2. Servers: Cloud servers and on-premises servers are used to receive, analyze, summarize, tag, classify, and move files.

[0913] Software to use

[0914] 1. File analysis software:

[0915] OCR technology (e.g., Tesseract) is used to analyze PDF files.

[0916] Text extraction from DOC and XLSX files is performed using a text extraction library (e.g., Apache POI).

[0917] 2. Generative Artificial Intelligence: Generative artificial intelligence (e.g., OpenAI GPT-3) will be used to generate summaries of file contents.

[0918] 3. File Management System: A proprietary management system for uploading, notifying, and storing files.

[0919] Explanation of natural language processing

[0920] File upload:

[0921] The user creates a file named "Project A Progress Report.doc" and uploads it to the public folder. The device detects this upload and notifies the server of information such as the file name and metadata.

[0922] File analysis:

[0923] The server receives the upload notification and identifies the file. Next, the server analyzes the file content. For PDF files, it uses OCR technology to convert them into text data. For DOC and XLSX files, it uses a text extraction library to extract the text data.

[0924] Summary generation:

[0925] Using the extracted text data, the server generates a summary of the content using generative artificial intelligence. For example, it might concisely summarize the contents of the "Project A Progress Report" file.

[0926] Tag extraction:

[0927] Based on the generated summary, the server extracts relevant tags. For example, tags such as "Project A," "Progress," "Report," and "October 2023" are automatically generated.

[0928] File classification and movement:

[0929] For tagged files, the server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Project A" and "Progress," the file might be moved to the " / Shared Folder / Project A / Progress" folder.

[0930] Search for files:

[0931] When a user searches for a file within a shared folder, they use the search interface. For example, they might search using the keyword "Project A Progress Report October 2023". The server parses the search query, matches it with appropriate tags to identify the file, and returns the search results. As a result, the user can easily access the desired file.

[0932] Specific example

[0933] For example, suppose a user creates a file named "Project B Budget Report.xlsx" and uploads it to a shared folder. The server analyzes its contents and generates tags such as "Budget," "Project B," and "Report." The server then automatically moves this file to the " / Shared Folder / Project B / Budget Report" folder. If a user searches for "Project B Budget Report," the desired file, "Project B Budget Report.xlsx," will be immediately returned as a search result. This system simplifies file classification and management, enabling more efficient work.

[0934] Example of a prompt

[0935] Example prompt message for when you upload "Project A progress report.doc":

[0936] A user uploaded "Project A Progress Report.doc" to the public folder. This file was converted to text using OCR technology, and then an automatic summary was generated. Relevant tags such as "Project A," "Progress," "Report," and "October 2023" were then added, and it was categorized into the appropriate folder. This allows users to quickly find the desired file by searching for "Project A Progress Report October 2023."

[0937] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0938] Processing flow of this system

[0939] Step 1: File Upload Detection

[0940] Users create files on their own devices and upload them to a public folder.

[0941] The device monitors changes to the public folder in real time and detects when new files are added.

[0942] Input: A file uploaded by the user to a public folder (e.g., "Project A Progress Report.doc")

[0943] Output: Notification that a file has been uploaded

[0944] Step 2: Metadata Notification

[0945] The terminal notifies the server of the file name and metadata (file path, creation date and time, etc.).

[0946] Input: Metadata of the uploaded file

[0947] Output: Metadata notification to the server

[0948] Step 3: Analyze the files

[0949] The server receives the upload notification and identifies the relevant file.

[0950] The server analyzes the file contents and extracts text data.

[0951] For PDF files, use OCR technology (e.g., Tesseract) to extract text from the image.

[0952] For DOC and XLSX files, use a text extraction library (e.g., Apache POI) to extract the text data.

[0953] Input: Uploaded file

[0954] Output: Extracted text data

[0955] Step 4: Summary Generation

[0956] The server inputs the extracted text data into a generative artificial intelligence (e.g., GPT-3) to generate a summary of its content.

[0957] The generated summary will include a report detailing the progress and future plans for Project A.

[0958] Input: Extracted text data

[0959] Output: Summary text

[0960] Step 5: Tag Extraction

[0961] The server extracts relevant tags based on the generated summary.

[0962] Using natural language processing technology (e.g., spaCy), tags such as "Project A," "Progress," and "Report" are automatically generated.

[0963] Input: Summary text

[0964] Output: Extracted tag list

[0965] Step 6: File classification and movement

[0966] The server identifies the appropriate folder based on the tags and moves the files to that folder.

[0967] Based on the tags, folders such as " / shared folder / project A / progress" are selected.

[0968] Input: Extracted tag list

[0969] Output: New path to the file

[0970] Step 7: Search for files

[0971] The user searches for files using the search interface.

[0972] Enter keywords such as "Project A Progress Report October 2023".

[0973] Input: User's search keywords

[0974] Output: Search query

[0975] Step 8: Parse the search query and return the results.

[0976] The server parses the search query, matches it with tags, identifies the relevant files, and returns the search results.

[0977] Input: Search query

[0978] Output: List of identified files

[0979] This system allows users to automatically organize and manage large amounts of files, enabling them to quickly access the information they need.

[0980] (Application Example 1)

[0981] 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."

[0982] Logistics centers generate a large volume of documents and data daily, making efficient management and retrieval a significant challenge. Manually classifying and storing paper-based documents and multiple digital files is time-consuming, labor-intensive, and prone to human error. Therefore, it is necessary to improve document management efficiency, reduce the workload on staff, and enable quick and accurate searching and access.

[0983] 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.

[0984] In this invention, the server includes means for detecting when a file is uploaded, means for analyzing the contents of the uploaded file and generating a summary, means for extracting relevant tags from the generated summary, means for classifying and moving files to appropriate shared folders based on the extracted tags, means for automatically creating and classifying folders based on the contents of the uploaded file, means for generating summaries and tags using generative artificial intelligence, and means for analyzing and storing data using a cloud server. This enables improved efficiency and accuracy in file management.

[0985] A "user terminal" is a computing device operated by a user, and is a device used for creating, editing, and uploading files.

[0986] A "file" is a form of electronic data, a recording medium that contains various types of information, such as documents, images, and spreadsheet data.

[0987] "Uploading" refers to the operation of sending data files from a local environment to a remote environment such as a server.

[0988] "Analysis" is the process of examining the contents of an uploaded file and understanding its structure and elements.

[0989] A "summary" is a concise, abbreviated version of the file's contents.

[0990] A "tag" is an identification label assigned to data to facilitate classification and searching.

[0991] A "shared folder" is a folder that can be accessed by multiple users and serves as a storage area for files.

[0992] A "cloud server" is a remote server accessible via the internet, used for data storage and analysis.

[0993] "Generative artificial intelligence" refers to artificial intelligence technology used to generate new information based on input data.

[0994] "Automatic creation" refers to a process where the system autonomously generates folders and other elements without user intervention.

[0995] "Classification" is the act of grouping files according to specific criteria.

[0996] "Moving" refers to the operation of physically or logically rearranging a file from one location to another.

[0997] This invention will now be described in terms of embodiments for carrying it out. This system is intended to efficiently manage documents and data files in a logistics center.

[0998] This system mainly consists of user terminals and cloud servers.

[0999] User terminal

[1000] User terminals are computing devices such as smartphones and tablets used by staff at the logistics center. Users can create and edit files from their own devices and upload them to the system.

[1001] server

[1002] Cloud servers are the core components that process uploaded files, handling a series of operations including analysis, summary generation, tagging, classification, and migration.

[1003] System operation procedure

[1004] 1. Upload files

[1005] When a user uploads a file from their smartphone, the device detects the upload and notifies the cloud server of the file's metadata, name, and other information.

[1006] 2. File analysis and summary generation

[1007] The cloud server receives the uploaded information and analyzes the contents of files such as Word documents and PDFs. It may also use OCR technology to extract text data from image files. Next, generative artificial intelligence is used based on the extracted text data to generate a summary of the content. For example, it might concisely summarize the contents of "Inventory List 2023.doc".

[1008] 3. Tag extraction

[1009] Based on the generated summary, the cloud server extracts relevant tags. For example, it automatically generates tags such as "inventory," "list," and "2023."

[1010] 4. File classification and movement

[1011] For tagged files, the cloud server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Inventory" and "List," it moves the files to the " / Logistics / Inventory" folder. Folders are automatically created as needed.

[1012] Hardware and software to use

[1013] Smartphone: Use it to upload and manage files.

[1014] Cloud server: Performs data analysis and storage.

[1015] Watchdog: A library for detecting file changes.

[1016] Transformers is a library that provides generative artificial intelligence models, performing summary generation and tagging.

[1017] Specific example

[1018] For example, if a staff member uploads "Inventory List 2023.pdf" from their smartphone, the cloud server receives the file and converts its contents into text using OCR technology. Next, it generates a summary using generative artificial intelligence and extracts tags such as "Inventory," "List," and "2023." Based on these tags, the cloud server then identifies the " / Logistics / Inventory" folder, automatically creates the folder if necessary, and moves the file there. When a user searches for "Inventory List 2023," they can immediately access the desired file.

[1019] Example of a prompt

[1020] Examples of prompts to input into a generative artificial intelligence are as follows:

[1021] "Please briefly summarize the contents of the 2023 inventory list."

[1022] In this way, this invention can achieve improved efficiency and accuracy in file management.

[1023] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1024] Step 1:

[1025] The user uploads a file from their smartphone.

[1026] Input: Created file

[1027] Operation: This involves a user at a logistics center saving new documents, reports, and other files to their smartphone and then uploading them to a cloud system.

[1028] Output: Upload event occurrence and file metadata

[1029] Step 2:

[1030] The device detects the file upload.

[1031] Input: Uploaded file

[1032] Operation: The user terminal detects the moment a file is uploaded to the system and retrieves the file's name and other metadata.

[1033] Output: File metadata and upload notification

[1034] Step 3:

[1035] The server receives the upload notification and analyzes the file contents.

[1036] Input: File metadata and actual file

[1037] Operation: The server retrieves the uploaded files and analyzes their contents. It uses OCR technology to convert image files into text data and reads the contents of document files as text.

[1038] Output: Analyzed text data

[1039] Step 4:

[1040] The server uses generative artificial intelligence to generate a summary from the analyzed text data.

[1041] Input: Parsed text data

[1042] Operation: The server supplies the analyzed text data as input to a generative artificial intelligence system, which then generates a summary. The prompt used is "Please summarize the content concisely."

[1043] Output: Generated summary

[1044] Step 5:

[1045] The server extracts relevant tags from the generated summary.

[1046] Input: Generated summary

[1047] Operation: The server analyzes the summary and uses generative artificial intelligence to extract relevant tags. For example, tags are determined based on keywords and important terms contained in the summary.

[1048] Output: Extracted tags

[1049] Step 6:

[1050] The server categorizes and moves files to the appropriate shared folder based on the extracted tags.

[1051] Input: Extracted tags

[1052] Operation: The server determines the file's storage location based on its tags. If the corresponding folder does not exist, it automatically creates a new folder as needed and moves the file into it. If the file is named "Inventory List 2023", it will be moved to the " / Logistics / Inventory" folder.

[1053] Output: Files moved to the appropriate folder

[1054] Step 7:

[1055] The user searches for files within the shared folder.

[1056] Input: Search keyword

[1057] Operation: Users use a search interface on their smartphones to search for necessary files. For example, they might search using the keyword "Inventory List 2023".

[1058] Output: List of related files

[1059] 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.

[1060] Embodiments of this invention will now be described. This system aims to facilitate file searching by efficiently managing user-created files and appropriately classifying and storing them within a shared folder. Furthermore, by incorporating an emotion engine that recognizes user emotions, more flexible and personalized file management becomes possible.

[1061] System Configuration

[1062] 1. User terminal

[1063] It is a computing device that allows users to create and edit files in their local environment and upload them to their public folder. It is equipped with an emotion engine that can detect the user's emotional state in real time.

[1064] 2. Server

[1065] It plays a central role in receiving uploaded files and performing a series of processes including analysis, summary generation, tagging, classification, and movement. It complements file management based on sentiment data obtained from the sentiment engine.

[1066] Program operation

[1067] File Upload

[1068] A user creates a file and uploads it to their public folder. For example, they might upload "Project A Progress Report.doc".

[1069] The device detects this upload and notifies the server of information such as the file name and metadata.

[1070] File analysis and summary generation

[1071] The server receives notification of the upload and identifies the file. Next, the server analyzes the file's contents. For example, in the case of a PDF file, it uses OCR technology to convert it into text data.

[1072] The server uses generative artificial intelligence to generate a summary of the content, using the converted text data as input. For example, it might concisely summarize the contents of a file titled "Project A Progress Report."

[1073] Tag extraction

[1074] Based on the generated summary, the server generates relevant tags. For example, it automatically generates tags such as "Project A," "Progress," "Report," and "October 2023."

[1075] Acquisition and reflection of emotional data

[1076] An emotion engine that recognizes user emotions detects the user's emotional state when creating or editing files and sends that data to the server. Emotion data includes states such as "stress," "concentration," and "excitement."

[1077] Based on this sentiment data, the server supplements and modifies the generated tags and summaries, and further reflects them in the file's metadata. For example, a file created by a user while highly focused will be tagged "focused" and judged to be of high importance.

[1078] File classification and movement

[1079] For tagged files, the server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Project A" and "Progress," the file might be moved to the " / sharedfolder / Project A / Progress" folder.

[1080] File Search

[1081] Users use the search interface to find the files they need within a shared folder. For example, they might search using the keyword "Project A Progress Report October 2023".

[1082] The server parses the search query, matches it with appropriate tags to identify the file, and returns the search results. As a result, the user can easily access the desired file.

[1083] Specific example

[1084] For example, suppose a user creates a file named "Project B Budget Report.xlsx" and uploads it to a shared folder. The server detects this file, analyzes its contents, and generates tags such as "Budget," "Project B," and "Report." The sentiment engine recognizes the user's "high stress" state and adds this information to the metadata as well. The server then automatically moves this file to the " / Shared Folder / Project B / Budget Report" folder. If a user searches for "Project B Budget Report," the search results will immediately return the desired file, "Project B Budget Report.xlsx."

[1085] This system simplifies file classification and management, enabling more efficient work. Furthermore, the introduction of an emotion engine allows for personalized file management that takes into account the user's emotional state.

[1086] The following describes the processing flow.

[1087] Step 1:

[1088] The user creates a file on their local device and uploads it to their public folder. For example, they might upload "Project A Progress Report.doc" to their public folder.

[1089] Step 2:

[1090] The device detects uploaded files and notifies the server of metadata such as file name, file path, and upload time.

[1091] Step 3:

[1092] The server receives the upload notification and confirms that the new file has been added to the public folder.

[1093] Step 4:

[1094] The server reads the file and converts its contents into text format. For example, in the case of a PDF, OCR technology is used to convert it into text data.

[1095] Step 5:

[1096] The server takes the converted text data as input and invokes a generative artificial intelligence to analyze its content. The generative AI then generates a summary from the analyzed text data.

[1097] Step 6:

[1098] The server generates relevant tags based on the summary results from the generative AI. For example, it might extract tags such as "Project A," "Progress," "Report," and "October 2023."

[1099] Step 7:

[1100] The server-generated tags are added as metadata to the file.

[1101] Step 8:

[1102] The emotion engine detects the user's emotional state in real time and sends that data to the server. Emotional data includes states such as "stress," "concentration," and "excitement."

[1103] Step 9:

[1104] The server receives sentiment data and uses it to supplement and modify tags and summaries generated from that data. For example, a file created by a user while highly focused will be tagged "focused" and judged to be of high importance.

[1105] Step 10:

[1106] Based on the extracted tags, the server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Project A" and "Progress," it identifies the folder " / Shared Folder / Project A / Progress."

[1107] Step 11:

[1108] The server physically moves the files from the public folder to the appropriate shared folder.

[1109] Step 12:

[1110] Users use the search interface to find the files they need within the shared folder. For example, they might enter a keyword such as "Project A Progress Report October 2023".

[1111] Step 13:

[1112] The server analyzes the search query and finds highly relevant files within the shared folder.

[1113] Step 14:

[1114] The server returns relevant files to the user as search results, making it easy for the user to access the desired files.

[1115] This processing flow automates each step, allowing users to efficiently manage and search for files. Furthermore, the introduction of an emotion engine enables personalized file management that takes into account the user's emotional state. For example, when a user creates "Project B Budget Report.xlsx" and uploads it to a shared folder, the system detects that the user is in a high-stress state and adds this information to the metadata. Based on this information, the server determines the file is important, assigns appropriate tags, and moves it to " / shared folder / Project B / Budget Report". If the user then searches for "Project B Budget Report," the desired file is immediately returned as a search result.

[1116] (Example 2)

[1117] 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."

[1118] Traditional file management systems often require manual file classification and searching, which is time-consuming and labor-intensive. Furthermore, they fail to consider user work efficiency and emotional state, making efficient and flexible file management difficult. As a result, file locator and work comfort are compromised, leading to increased user burden.

[1119] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for detecting when a file is uploaded from a user terminal, means for analyzing the contents of the uploaded file and generating a summary, means for extracting relevant tags from the generated summary, means for detecting the user's emotional state in real time, means for transmitting the detected emotional data to the server, means for supplementing and correcting the tags and summaries generated based on the emotional data, and means for classifying and moving files to appropriate shared folders based on the extracted tags. This enables efficient automatic classification and searching of files, and in addition, personalized file management according to the user's emotional state.

[1120] A "user terminal" is a computing device that a user uses to create, edit, and upload files.

[1121] A "server" is a central computer system that receives, analyzes, summarizes, tags, classifies, moves, and processes sentiment data for uploaded files.

[1122] "Methods for analyzing file contents" refers to technologies that analyze the text and image data of uploaded files to summarize their contents and extract tags.

[1123] "Methods for generating summaries" refers to techniques that shorten the contents of a file and concisely summarize important information.

[1124] "Methods for extracting tags" refers to technologies that perform a process of automatically extracting relevant keywords from the contents of a file or the generated summary.

[1125] "Methods for detecting emotional states in real time" refers to technologies that analyze and detect a user's emotional state in real time based on their facial expressions, voice, and other factors.

[1126] "Means for transmitting emotional data" refers to communication technology for sending data about a user's emotional state to a server.

[1127] "Methods for supplementing and correcting tags and summaries" refers to technologies that perform the process of correcting and supplementing tags and summaries generated based on detected sentiment data.

[1128] "Methods for classifying and moving files to shared folders" refers to technologies for classifying files into appropriate subfolders based on generated tags and then moving them to those folders.

[1129] Embodiments of this invention will now be described. This system aims to facilitate file searching by efficiently managing user-created files and appropriately classifying and storing them within a shared folder. Furthermore, by incorporating an emotion engine that recognizes user emotions, more flexible and personalized file management becomes possible.

[1130] System Configuration

[1131] 1. User terminal

[1132] A user terminal is a computing device used by a user to create and edit files in their local environment. Examples include personal computers and smartphones. Terminals are equipped with an emotion engine that can detect the user's emotional state in real time from their facial expressions and voice. Specifically, facial recognition software and voice recognition software are used for this purpose.

[1133] 2. Server

[1134] The server receives files uploaded from user terminals, analyzes their content, and generates summaries. The software used includes OCR technology, natural language processing technology, and generative AI models (e.g., GPT-4). It also receives sentiment data from the sentiment engine and uses it to complete and modify tags and summaries. Specifically, OCR engines such as Tesseract are used for analyzing file content, and generative artificial intelligence (e.g., generative AI models) are used for summary generation.

[1135] Program operation

[1136] File Upload

[1137] A user creates a file and uploads it to their public folder. For example, they might upload "Project A Progress Report.doc". The device detects this upload and notifies the server of information such as the file name and metadata.

[1138] File analysis and summary generation

[1139] The server receives an upload notification and identifies the file. Next, the server analyzes the file's contents. For example, in the case of a PDF file, it uses OCR technology to convert it into text data. Using the converted text data as input, the server uses generative artificial intelligence to generate a summary of the content. For example, it might concisely summarize the contents of a file titled "Project A Progress Report."

[1140] Tag extraction

[1141] Based on the generated summary, the server generates relevant tags. For example, it automatically generates tags such as "Project A," "Progress," "Report," and "October 2023."

[1142] Acquisition and reflection of emotional data

[1143] An emotion engine that recognizes user emotions detects the user's emotional state when creating or editing files and sends that data to the server. This emotion data includes states such as "stress," "concentration," and "excitement." The server uses this emotion data to supplement and modify generated tags and summaries, and further reflects this in the file's metadata. For example, a file created by a user in a highly focused state will be tagged "concentration" and judged to be of high importance.

[1144] Specific example

[1145] For example, suppose a user creates a file named "Project B Budget Report.xlsx" and uploads it to a shared folder. The server detects this file, analyzes its contents, and generates tags such as "Budget," "Project B," and "Report." The sentiment engine recognizes the user's "high stress" state and adds this information to the metadata as well. The server then automatically moves this file to the " / Shared Folder / Project B / Budget Report" folder. If a user searches for "Project B Budget Report," the search results will immediately return the desired file, "Project B Budget Report.xlsx."

[1146] This system simplifies file classification and management, enabling more efficient work. Furthermore, the introduction of an emotion engine allows for personalized file management that takes into account the user's emotional state.

[1147] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1148] Program processing flow

[1149] Step 1: Create and upload files

[1150] The user creates a file, for example, "Project A Progress Report.doc". The input is a file created by the user on a device such as a PC or smartphone.

[1151] Users upload files they have created to their public folder. For example, they can drag and drop files into the public folder or click the upload button. The output is the file uploaded to the public folder.

[1152] Step 2: Upload detection and notification

[1153] The device detects when a new file has been uploaded to the public folder. Specifically, it uses a file system monitoring tool to periodically check for changes in the folder. The input is a list of files in the public folder.

[1154] The terminal notifies the server of information about the uploaded file (file name, size, metadata, etc.). The output is the file information sent to the server.

[1155] Step 3: File analysis and summary generation

[1156] The server receives the upload notification and retrieves the corresponding file. The input is the file information sent from the device.

[1157] The server analyzes the file's contents. For example, in the case of a PDF file, it uses OCR technology to convert it into text data. Specifically, it uses an OCR engine such as Tesseract. The output is the converted text data.

[1158] The server uses a generative artificial intelligence (e.g., GPT-4) as input to convert the text data and generates a summary of its contents. The output is a summary of the file's contents.

[1159] Step 4: Tag Extraction

[1160] The server generates relevant tags based on the generated summary. For example, it may use natural language processing techniques to extract keywords from the summary. The input is the generated summary.

[1161] The server generates relevant tags. For example, it extracts tags such as "Project A," "Progress," "Report," and "October 2023." The output is a list of the extracted tags.

[1162] Step 5: Acquisition and reflection of emotional data

[1163] The device uses an emotion engine to detect the user's emotional state in real time when creating or editing files. Specifically, it uses facial recognition software and speech recognition software. The input consists of the user's facial expressions and voice data.

[1164] The device sends detected emotional data to the server. This data may include states such as "stress," "concentration," and "excitement." The output is the emotional data sent to the server.

[1165] The server uses sentiment data to supplement and modify the generated tags and summaries. For example, it adds the "focused" tag to files deemed highly important. The output consists of the supplemented and modified tags and summary text.

[1166] Step 6: Classify and move files

[1167] The server identifies the appropriate subfolder within the shared folder based on the extracted tags. For example, based on the tags "Project A" and "Progress," it identifies the folder " / sharedfolder / Project A / Progress." The input is a list of tags.

[1168] The server moves the file to a specified subfolder. Specifically, it uses a file manipulation API to move the file. The output is the file moved to the appropriate subfolder.

[1169] Step 7: Search for files

[1170] When a user needs to find a file, they use the search interface. For example, they might enter the keyword "Project A Progress Report October 2023" into the search bar. The input is the search query entered by the user.

[1171] The server parses the search query and identifies files based on relevant tags. Specifically, it uses a full-text search engine to search for indexed tags and metadata. The output is a file list as search results.

[1172] The user accesses the desired file from the search results. For example, they click on "Project A Progress Report.doc" to open it.

[1173] (Application Example 2)

[1174] 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."

[1175] In today's digital society, file management and retrieval are critical challenges. Especially in environments where a large number of files are generated daily, proper classification and rapid searching are essential. Furthermore, file management that considers user emotions and context has the potential to further improve efficiency, but existing systems have lacked such functionality. Against this backdrop, there is a need for flexible file management methods that reflect user emotions.

[1176] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1177] In this invention, the server includes means for detecting when a file is uploaded from a user terminal, means for analyzing the contents of the uploaded file and generating a summary, means for extracting relevant tags from the generated summary, means for classifying and moving the file to an appropriate shared folder based on the extracted tags, means for processing the user's emotional data using an emotional recognition engine that recognizes the user's emotions, and means for supplementing and correcting the tags and summary generated based on the emotional data. This enables personalized file management that takes into account the user's emotional state.

[1178] A "user terminal" is a computing device used by a user to create, edit, and upload files.

[1179] "Means for detecting when a file is uploaded" refers to a function that recognizes when a file has been uploaded from a user's terminal to the server.

[1180] "Method for analyzing file contents and generating summaries" refers to a function that analyzes the contents of uploaded files, extracts important information, and summarizes it concisely.

[1181] "Method for extracting relevant tags" refers to a function that automatically extracts appropriate keywords and tags from the generated summary or file content.

[1182] "Method for classifying and moving files to appropriate shared folders" refers to a function that organizes and moves files to the most suitable folder based on extracted tags.

[1183] An "emotion recognition engine" is a technology for detecting and recognizing a user's emotional state in real time.

[1184] "Means for processing emotional data" refers to a function that processes the detected emotional state of a user as data.

[1185] "Means for supplementing and correcting generated tags and summaries" refers to functions that adjust and correct already generated tags and summaries based on information including sentiment data.

[1186] This invention is a file management system that primarily comprises a user terminal, a server, and an emotion recognition engine. Specific examples of each element are shown below.

[1187] System Configuration

[1188] User terminal

[1189] A user terminal is a computing device used by users to create, edit, and upload files. It is equipped with an emotion recognition engine that can detect the user's emotional state in real time. Emotional states can range from stress, concentration, and excitement.

[1190] server

[1191] The server receives files uploaded from user terminals, analyzes them, and generates summaries. It also extracts relevant tags from the generated summaries and, based on this information, classifies and moves the files to appropriate shared folders. Generative artificial intelligence is implemented on the server, which is used for file content analysis and summary generation.

[1192] Program operation

[1193] emotion recognition

[1194] The emotion recognition engine analyzes the user's video feed and detects emotions in real time. Emotional data reflects the user's mental state while creating or editing files. This data is used as a crucial element in the file management process.

[1195] File analysis and summary generation

[1196] When the server receives a file, it first analyzes its contents. For example, in the case of a PDF file, it uses OCR technology to convert it into text data. Then, it uses a generative artificial intelligence model to generate a summary of the content. This summary concisely summarizes the key points of the file.

[1197] Tag generation and classification movement

[1198] Based on the generated summary, the server automatically creates relevant tags. This process also takes sentiment data into consideration. For example, files created in a "focused" state will be tagged "important." Based on the tags, the files are then categorized and moved to the appropriate shared folder.

[1199] Specific example

[1200] For example, suppose a user creates a file named "Project B Budget Report.xlsx" and uploads it to a shared folder. At this point, the emotion recognition engine detects the user's "high stress" state. The file's contents are analyzed, and tags such as "Budget," "Project B," and "Report" are generated. Finally, the server automatically moves this file to the " / Shared Folder / Project B / Budget Report" folder. If the user searches for "Project B Budget Report," they can immediately access the desired file.

[1201] Example of a prompt

[1202] Please generate a summary of the files tagged "Project". The following is the content of the files:

[1203] ---

[1204] The Project A progress report details the progress up to October. The main challenges are...

[1205] ---

[1206] Emotional data: Concentration

[1207] In this way, file management that takes into account the user's emotional state becomes possible, resulting in a system that significantly improves the efficiency of file searching and management.

[1208] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1209] Step 1:

[1210] The user's device uploads files created or edited by the user to a public folder. At this time, the device detects emotions in real time via the user's video feed using an emotion recognition engine and collects the data. The input consists of the uploaded file and collected emotion data. The output consists of an upload notification and emotion data.

[1211] Step 2:

[1212] The device detects file uploads and sends upload notifications and sentiment data to the server. Specifically, it makes an API call to notify the server of the uploaded file path and sentiment data. The inputs are the upload notification and sentiment data, and the output is the notification sent to the server.

[1213] Step 3:

[1214] The server receives the upload notification and identifies the target file. Next, it analyzes the file's contents. For example, in the case of a PDF file, it uses OCR technology (e.g., the "ocrmypdf" library) to convert it into text data. The input is the uploaded file, and the output is text data.

[1215] Step 4:

[1216] The server uses a generative artificial intelligence model to generate a summary from text data. Specifically, it inputs prompt sentences into the generative AI model and generates a summary. The input is text data and prompt sentences, and the output is a summary sentence.

[1217] Step 5:

[1218] The server extracts relevant tags based on the generated summary. Specifically, it analyzes the summary to extract keywords and then completes the tags based on sentiment data. The input is the summary and sentiment data, and the output is the relevant tags.

[1219] Step 6:

[1220] The server categorizes and moves files to the appropriate shared folders based on the extracted tags. Specifically, it determines the folder path based on the tags and moves the files to that path. The input is the associated tags and files, and the output is the new save path for the files.

[1221] Step 7:

[1222] When a user searches for files within a shared folder, they enter a search query. The server parses the search query, matches it against relevant tags to identify the target files, and returns the search results. Specifically, it executes a database query to find files with the specified tags. The input is the search query, and the output is the search results.

[1223] In this way, personalized file management and searching that takes into account the user's emotional state are achieved.

[1224] 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.

[1225] 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.

[1226] 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.

[1227] [Fourth Embodiment]

[1228] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1229] 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.

[1230] 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).

[1231] 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.

[1232] 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.

[1233] 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).

[1234] 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.

[1235] 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.

[1236] 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.

[1237] 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.

[1238] 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.

[1239] 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.

[1240] 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".

[1241] Embodiments of this invention will now be described. This system aims to facilitate file searching by efficiently managing user-created files and appropriately classifying and storing them within a shared folder.

[1242] System Configuration

[1243] 1. User terminal

[1244] It is a computing device that allows users to create and edit files in their local environment and upload them to their public folder.

[1245] 2. Server

[1246] It plays a central role in receiving uploaded files and performing a series of processes including analysis, summary generation, tagging, classification, and movement.

[1247] Program operation

[1248] File Upload

[1249] A user creates a file and uploads it to their public folder. For example, a user uploads "Project A Progress Report.doc" to their public folder.

[1250] The device detects this upload and notifies the server of information such as the file name and metadata.

[1251] File analysis and summary generation

[1252] The server receives notification of the upload and identifies the file. Next, the server analyzes the file's contents. For example, in the case of a PDF file, it uses OCR technology to convert it into text data.

[1253] The server uses generative artificial intelligence to generate a summary of the content, using the converted text data as input. For example, it might concisely summarize the contents of a file titled "Project A Progress Report."

[1254] Tag extraction

[1255] Based on the generated summary, the server extracts relevant tags. For example, it automatically generates tags such as "Project A," "Progress," "Report," and "October 2023."

[1256] File classification and movement

[1257] For tagged files, the server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Project A" and "Progress," the file might be moved to the " / sharedfolder / Project A / Progress" folder.

[1258] File Search

[1259] Users use the search interface to find the files they need within a shared folder. For example, they might search using the keyword "Project A Progress Report October 2023".

[1260] The server parses the search query, matches it with appropriate tags to identify the file, and returns the search results. As a result, the user can easily access the desired file.

[1261] Specific example

[1262] For example, suppose a user creates a file named "Project B Budget Report.xlsx" and uploads it to a shared folder. The server detects this file, analyzes its contents, and generates tags such as "Budget," "Project B," and "Report." The server then automatically moves this file to the " / Shared Folder / Project B / Budget Report" folder. If a user searches for "Project B Budget Report," the search results will immediately return the desired file, "Project B Budget Report.xlsx."

[1263] This system simplifies file classification and management, enabling more efficient work.

[1264] The following describes the processing flow.

[1265] Step 1:

[1266] The user creates a file on their local device and uploads it to their public folder. For example, they might upload "Project A Progress Report.doc".

[1267] Step 2:

[1268] The device detects uploaded files and notifies the server of metadata such as file name, file path, and upload time.

[1269] Step 3:

[1270] The server receives the upload notification and confirms that the new file has been added to the public folder.

[1271] Step 4:

[1272] The server reads the file and converts its contents into text format. For example, in the case of a PDF, OCR technology is used to convert it into text data.

[1273] Step 5:

[1274] The server takes the converted text data as input and invokes a generative artificial intelligence to analyze its content. The generative AI then generates a summary from the analyzed text data.

[1275] Step 6:

[1276] The server generates relevant tags based on the summary results from the generative AI. For example, it might extract tags such as "Project A," "Progress," "Report," and "October 2023."

[1277] Step 7:

[1278] The server-generated tags are added as metadata to the file.

[1279] Step 8:

[1280] Based on the extracted tags, the server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Project A" and "Progress," it identifies the folder " / Shared Folder / Project A / Progress."

[1281] Step 9:

[1282] The server physically moves the files from the public folder to the appropriate shared folder.

[1283] Step 10:

[1284] Users use the search interface to find the files they need within the shared folder. For example, they might enter a keyword such as "Project A Progress Report October 2023".

[1285] Step 11:

[1286] The server analyzes the search query and finds highly relevant files within the shared folder.

[1287] Step 12:

[1288] The server returns relevant files to the user as search results, making it easy for the user to access the desired files.

[1289] ---

[1290] This processing flow automates each step, allowing users to efficiently manage and search for files.

[1291] (Example 1)

[1292] 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".

[1293] In modern information management, a major problem is the scattering of large numbers of files, making organization and searching difficult. As a result, users often have to spend a great deal of time and effort to access the information they need. Furthermore, systems with advanced features such as proper file classification and summarization within shared folders, and automatic extraction of related tags, are limited.

[1294] 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.

[1295] In this invention, the server includes means for detecting when a file is uploaded from a user terminal, means for notifying the server of the metadata of the uploaded file, means for analyzing the contents of the uploaded file and extracting text data, means for generating a summary using generative artificial intelligence with respect to the extracted text data, means for extracting relevant tags from the generated summary, means for classifying and moving files to appropriate shared folders based on the extracted tags, means for the user to perform a file search based on tags using a search interface, and means for the server to analyze the search query, identify the relevant files, and return the search results. This automates the organization and management of large numbers of files, enabling users to quickly and efficiently access the information they need.

[1296] A "user terminal" refers to a computing device used by a user, such as a computer, smartphone, or tablet.

[1297] A "server" is a computing system that receives uploaded files and performs analysis, summarization, tagging, classification / movement, and analysis of search queries.

[1298] "Uploading" refers to the act of transferring files from a user's device to a server.

[1299] "Metadata" refers to additional information about a file, such as file name, creation date and time, and file size.

[1300] "Analysis" is the process of deciphering the contents of uploaded files and extracting useful information such as text data.

[1301] "OCR technology" is an optical character recognition technology used to extract text data from image data.

[1302] A "text extraction library" is a software component used to extract text data from files such as DOC and XLSX.

[1303] "Generative artificial intelligence" refers to artificial intelligence technology that performs text summarization and generation based on input data.

[1304] A "summary" is a text that concisely summarizes the contents of a file.

[1305] A "tag" is a keyword or label that indicates the specific content or attributes of a file.

[1306] A "shared folder" is a data storage area that can be accessed by multiple users.

[1307] "Classification and relocation" is the process of sorting files into the appropriate folders based on the extracted tags.

[1308] A "search interface" is a user interface that allows users to search for necessary files by entering tags or keywords.

[1309] A "search query" is a search word or phrase that a user enters into the search interface.

[1310] "Search results" refer to a list of files that the server identifies and returns to the user based on the search query.

[1311] This invention relates to a system for users to create, efficiently manage, and properly classify and store files within a shared folder. It enables users to quickly and efficiently access the information they need.

[1312] Hardware to use

[1313] 1. User terminal: A computing device such as a computer, smartphone, or tablet used by the user to create files and upload them to a public folder.

[1314] 2. Servers: Cloud servers and on-premises servers are used to receive, analyze, summarize, tag, classify, and move files.

[1315] Software to use

[1316] 1. File analysis software:

[1317] OCR technology (e.g., Tesseract) is used to analyze PDF files.

[1318] Text extraction from DOC and XLSX files is performed using a text extraction library (e.g., Apache POI).

[1319] 2. Generative Artificial Intelligence: Generative artificial intelligence (e.g., OpenAI GPT-3) will be used to generate summaries of file contents.

[1320] 3. File Management System: A proprietary management system for uploading, notifying, and storing files.

[1321] Explanation of natural language processing

[1322] File upload:

[1323] The user creates a file named "Project A Progress Report.doc" and uploads it to the public folder. The device detects this upload and notifies the server of information such as the file name and metadata.

[1324] File analysis:

[1325] The server receives the upload notification and identifies the file. Next, the server analyzes the file content. For PDF files, it uses OCR technology to convert them into text data. For DOC and XLSX files, it uses a text extraction library to extract the text data.

[1326] Summary generation:

[1327] Using the extracted text data, the server generates a summary of the content using generative artificial intelligence. For example, it might concisely summarize the contents of the "Project A Progress Report" file.

[1328] Tag extraction:

[1329] Based on the generated summary, the server extracts relevant tags. For example, tags such as "Project A," "Progress," "Report," and "October 2023" are automatically generated.

[1330] File classification and movement:

[1331] For tagged files, the server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Project A" and "Progress," the file might be moved to the " / Shared Folder / Project A / Progress" folder.

[1332] Search for files:

[1333] When a user searches for a file within a shared folder, they use the search interface. For example, they might search using the keyword "Project A Progress Report October 2023". The server parses the search query, matches it with appropriate tags to identify the file, and returns the search results. As a result, the user can easily access the desired file.

[1334] Specific example

[1335] For example, suppose a user creates a file named "Project B Budget Report.xlsx" and uploads it to a shared folder. The server analyzes its contents and generates tags such as "Budget," "Project B," and "Report." The server then automatically moves this file to the " / Shared Folder / Project B / Budget Report" folder. If a user searches for "Project B Budget Report," the desired file, "Project B Budget Report.xlsx," will be immediately returned as a search result. This system simplifies file classification and management, enabling more efficient work.

[1336] Example of a prompt

[1337] Example prompt message for when you upload "Project A progress report.doc":

[1338] A user uploaded "Project A Progress Report.doc" to the public folder. This file was converted to text using OCR technology, and then an automatic summary was generated. Relevant tags such as "Project A," "Progress," "Report," and "October 2023" were then added, and it was categorized into the appropriate folder. This allows users to quickly find the desired file by searching for "Project A Progress Report October 2023."

[1339] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1340] Processing flow of this system

[1341] Step 1: File Upload Detection

[1342] Users create files on their own devices and upload them to a public folder.

[1343] The device monitors changes to the public folder in real time and detects when new files are added.

[1344] Input: A file uploaded by the user to a public folder (e.g., "Project A Progress Report.doc")

[1345] Output: Notification that a file has been uploaded

[1346] Step 2: Metadata Notification

[1347] The terminal notifies the server of the file name and metadata (file path, creation date and time, etc.).

[1348] Input: Metadata of the uploaded file

[1349] Output: Metadata notification to the server

[1350] Step 3: Analyze the files

[1351] The server receives the upload notification and identifies the relevant file.

[1352] The server analyzes the file contents and extracts text data.

[1353] For PDF files, use OCR technology (e.g., Tesseract) to extract text from the image.

[1354] For DOC and XLSX files, use a text extraction library (e.g., Apache POI) to extract the text data.

[1355] Input: Uploaded file

[1356] Output: Extracted text data

[1357] Step 4: Summary Generation

[1358] The server inputs the extracted text data into a generative artificial intelligence (e.g., GPT-3) to generate a summary of its content.

[1359] The generated summary will include a report detailing the progress and future plans for Project A.

[1360] Input: Extracted text data

[1361] Output: Summary text

[1362] Step 5: Tag Extraction

[1363] The server extracts relevant tags based on the generated summary.

[1364] Using natural language processing technology (e.g., spaCy), tags such as "Project A," "Progress," and "Report" are automatically generated.

[1365] Input: Summary text

[1366] Output: Extracted tag list

[1367] Step 6: File classification and movement

[1368] The server identifies the appropriate folder based on the tags and moves the files to that folder.

[1369] Based on the tags, folders such as " / shared folder / project A / progress" are selected.

[1370] Input: Extracted tag list

[1371] Output: New path to the file

[1372] Step 7: Search for files

[1373] The user searches for files using the search interface.

[1374] Enter keywords such as "Project A Progress Report October 2023".

[1375] Input: User's search keywords

[1376] Output: Search query

[1377] Step 8: Parse the search query and return the results.

[1378] The server parses the search query, matches it with tags, identifies the relevant files, and returns the search results.

[1379] Input: Search query

[1380] Output: List of identified files

[1381] This system allows users to automatically organize and manage large amounts of files, enabling them to quickly access the information they need.

[1382] (Application Example 1)

[1383] 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".

[1384] Logistics centers generate a large volume of documents and data daily, making efficient management and retrieval a significant challenge. Manually classifying and storing paper-based documents and multiple digital files is time-consuming, labor-intensive, and prone to human error. Therefore, it is necessary to improve document management efficiency, reduce the workload on staff, and enable quick and accurate searching and access.

[1385] 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.

[1386] In this invention, the server includes means for detecting when a file is uploaded, means for analyzing the contents of the uploaded file and generating a summary, means for extracting relevant tags from the generated summary, means for classifying and moving files to appropriate shared folders based on the extracted tags, means for automatically creating and classifying folders based on the contents of the uploaded file, means for generating summaries and tags using generative artificial intelligence, and means for analyzing and storing data using a cloud server. This enables improved efficiency and accuracy in file management.

[1387] A "user terminal" is a computing device operated by a user, and is a device used for creating, editing, and uploading files.

[1388] A "file" is a form of electronic data, a recording medium that contains various types of information, such as documents, images, and spreadsheet data.

[1389] "Uploading" refers to the operation of sending data files from a local environment to a remote environment such as a server.

[1390] "Analysis" is the process of examining the contents of an uploaded file and understanding its structure and elements.

[1391] A "summary" is a concise, abbreviated version of the file's contents.

[1392] A "tag" is an identification label assigned to data to facilitate classification and searching.

[1393] A "shared folder" is a folder that can be accessed by multiple users and serves as a storage area for files.

[1394] A "cloud server" is a remote server accessible via the internet, used for data storage and analysis.

[1395] "Generative artificial intelligence" refers to artificial intelligence technology used to generate new information based on input data.

[1396] "Automatic creation" refers to a process where the system autonomously generates folders and other elements without user intervention.

[1397] "Classification" is the act of grouping files according to specific criteria.

[1398] "Moving" refers to the operation of physically or logically rearranging a file from one location to another.

[1399] This invention will now be described in terms of embodiments for carrying it out. This system is intended to efficiently manage documents and data files in a logistics center.

[1400] This system mainly consists of user terminals and cloud servers.

[1401] User terminal

[1402] User terminals are computing devices such as smartphones and tablets used by staff at the logistics center. Users can create and edit files from their own devices and upload them to the system.

[1403] server

[1404] Cloud servers are the core components that process uploaded files, handling a series of operations including analysis, summary generation, tagging, classification, and migration.

[1405] System operation procedure

[1406] 1. Upload files

[1407] When a user uploads a file from their smartphone, the device detects the upload and notifies the cloud server of the file's metadata, name, and other information.

[1408] 2. File analysis and summary generation

[1409] The cloud server receives the uploaded information and analyzes the contents of files such as Word documents and PDFs. It may also use OCR technology to extract text data from image files. Next, generative artificial intelligence is used based on the extracted text data to generate a summary of the content. For example, it might concisely summarize the contents of "Inventory List 2023.doc".

[1410] 3. Tag extraction

[1411] Based on the generated summary, the cloud server extracts relevant tags. For example, it automatically generates tags such as "inventory," "list," and "2023."

[1412] 4. File classification and movement

[1413] For tagged files, the cloud server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Inventory" and "List," it moves the files to the " / Logistics / Inventory" folder. Folders are automatically created as needed.

[1414] Hardware and software to use

[1415] Smartphone: Use it to upload and manage files.

[1416] Cloud server: Performs data analysis and storage.

[1417] Watchdog: A library for detecting file changes.

[1418] Transformers is a library that provides generative artificial intelligence models, performing summary generation and tagging.

[1419] Specific example

[1420] For example, if a staff member uploads "Inventory List 2023.pdf" from their smartphone, the cloud server receives the file and converts its contents into text using OCR technology. Next, it generates a summary using generative artificial intelligence and extracts tags such as "Inventory," "List," and "2023." Based on these tags, the cloud server then identifies the " / Logistics / Inventory" folder, automatically creates the folder if necessary, and moves the file there. When a user searches for "Inventory List 2023," they can immediately access the desired file.

[1421] Example of a prompt

[1422] Examples of prompts to input into a generative artificial intelligence are as follows:

[1423] "Please briefly summarize the contents of the 2023 inventory list."

[1424] In this way, this invention can achieve improved efficiency and accuracy in file management.

[1425] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1426] Step 1:

[1427] The user uploads a file from their smartphone.

[1428] Input: Created file

[1429] Operation: This involves a user at a logistics center saving new documents, reports, and other files to their smartphone and then uploading them to a cloud system.

[1430] Output: Upload event occurrence and file metadata

[1431] Step 2:

[1432] The device detects the file upload.

[1433] Input: Uploaded file

[1434] Operation: The user terminal detects the moment a file is uploaded to the system and retrieves the file's name and other metadata.

[1435] Output: File metadata and upload notification

[1436] Step 3:

[1437] The server receives the upload notification and analyzes the file contents.

[1438] Input: File metadata and actual file

[1439] Operation: The server retrieves the uploaded files and analyzes their contents. It uses OCR technology to convert image files into text data and reads the contents of document files as text.

[1440] Output: Analyzed text data

[1441] Step 4:

[1442] The server uses generative artificial intelligence to generate a summary from the analyzed text data.

[1443] Input: Parsed text data

[1444] Operation: The server supplies the analyzed text data as input to a generative artificial intelligence system, which then generates a summary. The prompt used is "Please summarize the content concisely."

[1445] Output: Generated summary

[1446] Step 5:

[1447] The server extracts relevant tags from the generated summary.

[1448] Input: Generated summary

[1449] Operation: The server analyzes the summary and uses generative artificial intelligence to extract relevant tags. For example, tags are determined based on keywords and important terms contained in the summary.

[1450] Output: Extracted tags

[1451] Step 6:

[1452] The server categorizes and moves files to the appropriate shared folder based on the extracted tags.

[1453] Input: Extracted tags

[1454] Operation: The server determines the file's storage location based on its tags. If the corresponding folder does not exist, it automatically creates a new folder as needed and moves the file into it. If the file is named "Inventory List 2023", it will be moved to the " / Logistics / Inventory" folder.

[1455] Output: Files moved to the appropriate folder

[1456] Step 7:

[1457] The user searches for files within the shared folder.

[1458] Input: Search keyword

[1459] Operation: Users use a search interface on their smartphones to search for necessary files. For example, they might search using the keyword "Inventory List 2023".

[1460] Output: List of related files

[1461] 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.

[1462] Embodiments of this invention will now be described. This system aims to facilitate file searching by efficiently managing user-created files and appropriately classifying and storing them within a shared folder. Furthermore, by incorporating an emotion engine that recognizes user emotions, more flexible and personalized file management becomes possible.

[1463] System Configuration

[1464] 1. User terminal

[1465] It is a computing device that allows users to create and edit files in their local environment and upload them to their public folder. It is equipped with an emotion engine that can detect the user's emotional state in real time.

[1466] 2. Server

[1467] It plays a central role in receiving uploaded files and performing a series of processes including analysis, summary generation, tagging, classification, and movement. It complements file management based on sentiment data obtained from the sentiment engine.

[1468] Program operation

[1469] File Upload

[1470] A user creates a file and uploads it to their public folder. For example, they might upload "Project A Progress Report.doc".

[1471] The device detects this upload and notifies the server of information such as the file name and metadata.

[1472] File analysis and summary generation

[1473] The server receives notification of the upload and identifies the file. Next, the server analyzes the file's contents. For example, in the case of a PDF file, it uses OCR technology to convert it into text data.

[1474] The server uses generative artificial intelligence to generate a summary of the content, using the converted text data as input. For example, it might concisely summarize the contents of a file titled "Project A Progress Report."

[1475] Tag extraction

[1476] Based on the generated summary, the server generates relevant tags. For example, it automatically generates tags such as "Project A," "Progress," "Report," and "October 2023."

[1477] Acquisition and reflection of emotional data

[1478] An emotion engine that recognizes user emotions detects the user's emotional state when creating or editing files and sends that data to the server. Emotion data includes states such as "stress," "concentration," and "excitement."

[1479] Based on this sentiment data, the server supplements and modifies the generated tags and summaries, and further reflects them in the file's metadata. For example, a file created by a user while highly focused will be tagged "focused" and judged to be of high importance.

[1480] File classification and movement

[1481] For tagged files, the server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Project A" and "Progress," the file might be moved to the " / sharedfolder / Project A / Progress" folder.

[1482] File Search

[1483] Users use the search interface to find the files they need within a shared folder. For example, they might search using the keyword "Project A Progress Report October 2023".

[1484] The server parses the search query, matches it with appropriate tags to identify the file, and returns the search results. As a result, the user can easily access the desired file.

[1485] Specific example

[1486] For example, suppose a user creates a file named "Project B Budget Report.xlsx" and uploads it to a shared folder. The server detects this file, analyzes its contents, and generates tags such as "Budget," "Project B," and "Report." The sentiment engine recognizes the user's "high stress" state and adds this information to the metadata as well. The server then automatically moves this file to the " / Shared Folder / Project B / Budget Report" folder. If a user searches for "Project B Budget Report," the search results will immediately return the desired file, "Project B Budget Report.xlsx."

[1487] This system simplifies file classification and management, enabling more efficient work. Furthermore, the introduction of an emotion engine allows for personalized file management that takes into account the user's emotional state.

[1488] The following describes the processing flow.

[1489] Step 1:

[1490] The user creates a file on their local device and uploads it to their public folder. For example, they might upload "Project A Progress Report.doc" to their public folder.

[1491] Step 2:

[1492] The device detects uploaded files and notifies the server of metadata such as file name, file path, and upload time.

[1493] Step 3:

[1494] The server receives the upload notification and confirms that the new file has been added to the public folder.

[1495] Step 4:

[1496] The server reads the file and converts its contents into text format. For example, in the case of a PDF, OCR technology is used to convert it into text data.

[1497] Step 5:

[1498] The server takes the converted text data as input and invokes a generative artificial intelligence to analyze its content. The generative AI then generates a summary from the analyzed text data.

[1499] Step 6:

[1500] The server generates relevant tags based on the summary results from the generative AI. For example, it might extract tags such as "Project A," "Progress," "Report," and "October 2023."

[1501] Step 7:

[1502] The server-generated tags are added as metadata to the file.

[1503] Step 8:

[1504] The emotion engine detects the user's emotional state in real time and sends that data to the server. Emotional data includes states such as "stress," "concentration," and "excitement."

[1505] Step 9:

[1506] The server receives sentiment data and uses it to supplement and modify tags and summaries generated from that data. For example, a file created by a user while highly focused will be tagged "focused" and judged to be of high importance.

[1507] Step 10:

[1508] Based on the extracted tags, the server identifies the appropriate subfolder within the shared folder. For example, based on the tags "Project A" and "Progress," it identifies the folder " / Shared Folder / Project A / Progress."

[1509] Step 11:

[1510] The server physically moves the files from the public folder to the appropriate shared folder.

[1511] Step 12:

[1512] Users use the search interface to find the files they need within the shared folder. For example, they might enter a keyword such as "Project A Progress Report October 2023".

[1513] Step 13:

[1514] The server analyzes the search query and finds highly relevant files within the shared folder.

[1515] Step 14:

[1516] The server returns relevant files to the user as search results, making it easy for the user to access the desired files.

[1517] This processing flow automates each step, allowing users to efficiently manage and search for files. Furthermore, the introduction of an emotion engine enables personalized file management that takes into account the user's emotional state. For example, when a user creates "Project B Budget Report.xlsx" and uploads it to a shared folder, the system detects that the user is in a high-stress state and adds this information to the metadata. Based on this information, the server determines the file is important, assigns appropriate tags, and moves it to " / shared folder / Project B / Budget Report". If the user then searches for "Project B Budget Report," the desired file is immediately returned as a search result.

[1518] (Example 2)

[1519] 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".

[1520] Traditional file management systems often require manual file classification and searching, which is time-consuming and labor-intensive. Furthermore, they fail to consider user work efficiency and emotional state, making efficient and flexible file management difficult. As a result, file locator and work comfort are compromised, leading to increased user burden.

[1521] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for detecting when a file is uploaded from a user terminal, means for analyzing the contents of the uploaded file and generating a summary, means for extracting relevant tags from the generated summary, means for detecting the user's emotional state in real time, means for transmitting the detected emotional data to the server, means for supplementing and correcting the tags and summaries generated based on the emotional data, and means for classifying and moving files to appropriate shared folders based on the extracted tags. This enables efficient automatic classification and searching of files, and in addition, personalized file management according to the user's emotional state.

[1522] A "user terminal" is a computing device that a user uses to create, edit, and upload files.

[1523] A "server" is a central computer system that receives, analyzes, summarizes, tags, classifies, moves, and processes sentiment data for uploaded files.

[1524] "Methods for analyzing file contents" refers to technologies that analyze the text and image data of uploaded files to summarize their contents and extract tags.

[1525] "Methods for generating summaries" refers to techniques that shorten the contents of a file and concisely summarize important information.

[1526] "Methods for extracting tags" refers to technologies that perform a process of automatically extracting relevant keywords from the contents of a file or the generated summary.

[1527] "Methods for detecting emotional states in real time" refers to technologies that analyze and detect a user's emotional state in real time based on their facial expressions, voice, and other factors.

[1528] "Means for transmitting emotional data" refers to communication technology for sending data about a user's emotional state to a server.

[1529] "Methods for supplementing and correcting tags and summaries" refers to technologies that perform the process of correcting and supplementing tags and summaries generated based on detected sentiment data.

[1530] "Methods for classifying and moving files to shared folders" refers to technologies for classifying files into appropriate subfolders based on generated tags and then moving them to those folders.

[1531] Embodiments of this invention will now be described. This system aims to facilitate file searching by efficiently managing user-created files and appropriately classifying and storing them within a shared folder. Furthermore, by incorporating an emotion engine that recognizes user emotions, more flexible and personalized file management becomes possible.

[1532] System Configuration

[1533] 1. User terminal

[1534] A user terminal is a computing device used by a user to create and edit files in their local environment. Examples include personal computers and smartphones. Terminals are equipped with an emotion engine that can detect the user's emotional state in real time from their facial expressions and voice. Specifically, facial recognition software and voice recognition software are used for this purpose.

[1535] 2. Server

[1536] The server receives files uploaded from user terminals, analyzes their content, and generates summaries. The software used includes OCR technology, natural language processing technology, and generative AI models (e.g., GPT-4). It also receives sentiment data from the sentiment engine and uses it to complete and modify tags and summaries. Specifically, OCR engines such as Tesseract are used for analyzing file content, and generative artificial intelligence (e.g., generative AI models) are used for summary generation.

[1537] Program operation

[1538] File Upload

[1539] A user creates a file and uploads it to their public folder. For example, they might upload "Project A Progress Report.doc". The device detects this upload and notifies the server of information such as the file name and metadata.

[1540] File analysis and summary generation

[1541] The server receives an upload notification and identifies the file. Next, the server analyzes the file's contents. For example, in the case of a PDF file, it uses OCR technology to convert it into text data. Using the converted text data as input, the server uses generative artificial intelligence to generate a summary of the content. For example, it might concisely summarize the contents of a file titled "Project A Progress Report."

[1542] Tag extraction

[1543] Based on the generated summary, the server generates relevant tags. For example, it automatically generates tags such as "Project A," "Progress," "Report," and "October 2023."

[1544] Acquisition and reflection of emotional data

[1545] An emotion engine that recognizes user emotions detects the user's emotional state when creating or editing files and sends that data to the server. This emotion data includes states such as "stress," "concentration," and "excitement." The server uses this emotion data to supplement and modify generated tags and summaries, and further reflects this in the file's metadata. For example, a file created by a user in a highly focused state will be tagged "concentration" and judged to be of high importance.

[1546] Specific example

[1547] For example, suppose a user creates a file named "Project B Budget Report.xlsx" and uploads it to a shared folder. The server detects this file, analyzes its contents, and generates tags such as "Budget," "Project B," and "Report." The sentiment engine recognizes the user's "high stress" state and adds this information to the metadata as well. The server then automatically moves this file to the " / Shared Folder / Project B / Budget Report" folder. If a user searches for "Project B Budget Report," the search results will immediately return the desired file, "Project B Budget Report.xlsx."

[1548] This system simplifies file classification and management, enabling more efficient work. Furthermore, the introduction of an emotion engine allows for personalized file management that takes into account the user's emotional state.

[1549] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1550] Program processing flow

[1551] Step 1: Create and upload files

[1552] The user creates a file, for example, "Project A Progress Report.doc". The input is a file created by the user on a device such as a PC or smartphone.

[1553] Users upload files they have created to their public folder. For example, they can drag and drop files into the public folder or click the upload button. The output is the file uploaded to the public folder.

[1554] Step 2: Upload detection and notification

[1555] The device detects when a new file has been uploaded to the public folder. Specifically, it uses a file system monitoring tool to periodically check for changes in the folder. The input is a list of files in the public folder.

[1556] The terminal notifies the server of information about the uploaded file (file name, size, metadata, etc.). The output is the file information sent to the server.

[1557] Step 3: File analysis and summary generation

[1558] The server receives the upload notification and retrieves the corresponding file. The input is the file information sent from the device.

[1559] The server analyzes the file's contents. For example, in the case of a PDF file, it uses OCR technology to convert it into text data. Specifically, it uses an OCR engine such as Tesseract. The output is the converted text data.

[1560] The server uses a generative artificial intelligence (e.g., GPT-4) as input to convert the text data and generates a summary of its contents. The output is a summary of the file's contents.

[1561] Step 4: Tag Extraction

[1562] The server generates relevant tags based on the generated summary. For example, it may use natural language processing techniques to extract keywords from the summary. The input is the generated summary.

[1563] The server generates relevant tags. For example, it extracts tags such as "Project A," "Progress," "Report," and "October 2023." The output is a list of the extracted tags.

[1564] Step 5: Acquisition and reflection of emotional data

[1565] The device uses an emotion engine to detect the user's emotional state in real time when creating or editing files. Specifically, it uses facial recognition software and speech recognition software. The input consists of the user's facial expressions and voice data.

[1566] The device sends detected emotional data to the server. This data may include states such as "stress," "concentration," and "excitement." The output is the emotional data sent to the server.

[1567] The server uses sentiment data to supplement and modify the generated tags and summaries. For example, it adds the "focused" tag to files deemed highly important. The output consists of the supplemented and modified tags and summary text.

[1568] Step 6: Classify and move files

[1569] The server identifies the appropriate subfolder within the shared folder based on the extracted tags. For example, based on the tags "Project A" and "Progress," it identifies the folder " / sharedfolder / Project A / Progress." The input is a list of tags.

[1570] The server moves the file to a specified subfolder. Specifically, it uses a file manipulation API to move the file. The output is the file moved to the appropriate subfolder.

[1571] Step 7: Search for files

[1572] When a user needs to find a file, they use the search interface. For example, they might enter the keyword "Project A Progress Report October 2023" into the search bar. The input is the search query entered by the user.

[1573] The server parses the search query and identifies files based on relevant tags. Specifically, it uses a full-text search engine to search for indexed tags and metadata. The output is a file list as search results.

[1574] The user accesses the desired file from the search results. For example, they click on "Project A Progress Report.doc" to open it.

[1575] (Application Example 2)

[1576] 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".

[1577] In today's digital society, file management and retrieval are critical challenges. Especially in environments where a large number of files are generated daily, proper classification and rapid searching are essential. Furthermore, file management that considers user emotions and context has the potential to further improve efficiency, but existing systems have lacked such functionality. Against this backdrop, there is a need for flexible file management methods that reflect user emotions.

[1578] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1579] In this invention, the server includes means for detecting when a file is uploaded from a user terminal, means for analyzing the contents of the uploaded file and generating a summary, means for extracting relevant tags from the generated summary, means for classifying and moving the file to an appropriate shared folder based on the extracted tags, means for processing the user's emotional data using an emotional recognition engine that recognizes the user's emotions, and means for supplementing and correcting the tags and summary generated based on the emotional data. This enables personalized file management that takes into account the user's emotional state.

[1580] A "user terminal" is a computing device used by a user to create, edit, and upload files.

[1581] "Means for detecting when a file is uploaded" refers to a function that recognizes when a file has been uploaded from a user's terminal to the server.

[1582] "Method for analyzing file contents and generating summaries" refers to a function that analyzes the contents of uploaded files, extracts important information, and summarizes it concisely.

[1583] "Method for extracting relevant tags" refers to a function that automatically extracts appropriate keywords and tags from the generated summary or file content.

[1584] "Method for classifying and moving files to appropriate shared folders" refers to a function that organizes and moves files to the most suitable folder based on extracted tags.

[1585] An "emotion recognition engine" is a technology for detecting and recognizing a user's emotional state in real time.

[1586] "Means for processing emotional data" refers to a function that processes the detected emotional state of a user as data.

[1587] "Means for supplementing and correcting generated tags and summaries" refers to functions that adjust and correct already generated tags and summaries based on information including sentiment data.

[1588] This invention is a file management system that primarily comprises a user terminal, a server, and an emotion recognition engine. Specific examples of each element are shown below.

[1589] System Configuration

[1590] User terminal

[1591] A user terminal is a computing device used by users to create, edit, and upload files. It is equipped with an emotion recognition engine that can detect the user's emotional state in real time. Emotional states can range from stress, concentration, and excitement.

[1592] server

[1593] The server receives files uploaded from user terminals, analyzes them, and generates summaries. It also extracts relevant tags from the generated summaries and, based on this information, classifies and moves the files to appropriate shared folders. Generative artificial intelligence is implemented on the server, which is used for file content analysis and summary generation.

[1594] Program operation

[1595] emotion recognition

[1596] The emotion recognition engine analyzes the user's video feed and detects emotions in real time. Emotional data reflects the user's mental state while creating or editing files. This data is used as a crucial element in the file management process.

[1597] File analysis and summary generation

[1598] When the server receives a file, it first analyzes its contents. For example, in the case of a PDF file, it uses OCR technology to convert it into text data. Then, it uses a generative artificial intelligence model to generate a summary of the content. This summary concisely summarizes the key points of the file.

[1599] Tag generation and classification movement

[1600] Based on the generated summary, the server automatically creates relevant tags. This process also takes sentiment data into consideration. For example, files created in a "focused" state will be tagged "important." Based on the tags, the files are then categorized and moved to the appropriate shared folder.

[1601] Specific example

[1602] For example, suppose a user creates a file named "Project B Budget Report.xlsx" and uploads it to a shared folder. At this point, the emotion recognition engine detects the user's "high stress" state. The file's contents are analyzed, and tags such as "Budget," "Project B," and "Report" are generated. Finally, the server automatically moves this file to the " / Shared Folder / Project B / Budget Report" folder. If the user searches for "Project B Budget Report," they can immediately access the desired file.

[1603] Example of a prompt

[1604] Please generate a summary of the files tagged "Project". The following is the content of the files:

[1605] ---

[1606] The Project A progress report details the progress up to October. The main challenges are...

[1607] ---

[1608] Emotional data: Concentration

[1609] In this way, file management that takes into account the user's emotional state becomes possible, resulting in a system that significantly improves the efficiency of file searching and management.

[1610] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1611] Step 1:

[1612] The user's device uploads files created or edited by the user to a public folder. At this time, the device detects emotions in real time via the user's video feed using an emotion recognition engine and collects the data. The input consists of the uploaded file and collected emotion data. The output consists of an upload notification and emotion data.

[1613] Step 2:

[1614] The device detects file uploads and sends upload notifications and sentiment data to the server. Specifically, it makes an API call to notify the server of the uploaded file path and sentiment data. The inputs are the upload notification and sentiment data, and the output is the notification sent to the server.

[1615] Step 3:

[1616] The server receives the upload notification and identifies the target file. Next, it analyzes the file's contents. For example, in the case of a PDF file, it uses OCR technology (e.g., the "ocrmypdf" library) to convert it into text data. The input is the uploaded file, and the output is text data.

[1617] Step 4:

[1618] The server uses a generative artificial intelligence model to generate a summary from text data. Specifically, it inputs prompt sentences into the generative AI model and generates a summary. The input is text data and prompt sentences, and the output is a summary sentence.

[1619] Step 5:

[1620] The server extracts relevant tags based on the generated summary. Specifically, it analyzes the summary to extract keywords and then completes the tags based on sentiment data. The input is the summary and sentiment data, and the output is the relevant tags.

[1621] Step 6:

[1622] The server categorizes and moves files to the appropriate shared folders based on the extracted tags. Specifically, it determines the folder path based on the tags and moves the files to that path. The input is the associated tags and files, and the output is the new save path for the files.

[1623] Step 7:

[1624] When a user searches for files within a shared folder, they enter a search query. The server parses the search query, matches it against relevant tags to identify the target files, and returns the search results. Specifically, it executes a database query to find files with the specified tags. The input is the search query, and the output is the search results.

[1625] In this way, personalized file management and searching that takes into account the user's emotional state are achieved.

[1626] 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.

[1627] 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.

[1628] 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.

[1629] 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.

[1630] 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.

[1631] 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.

[1632] 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.

[1633] 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.

[1634] 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."

[1635] 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.

[1636] 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.

[1637] 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.

[1638] 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.

[1639] 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.

[1640] 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.

[1641] 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.

[1642] 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.

[1643] 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.

[1644] 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.

[1645] 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.

[1646] 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.

[1647] The following is further disclosed regarding the embodiments described above.

[1648] (Claim 1)

[1649] A means for detecting when a file is uploaded from a user terminal,

[1650] A means of analyzing the contents of an uploaded file and generating a summary,

[1651] A means for extracting relevant tags from the generated summary,

[1652] A system that includes means for classifying and moving files to appropriate shared folders based on extracted tags.

[1653] (Claim 2)

[1654] A system according to claim 1, comprising means for using generative artificial intelligence to analyze the contents of a file.

[1655] (Claim 3)

[1656] A system according to claim 1, wherein the search system has means for identifying a file based on extracted tags.

[1657] "Example 1"

[1658] (Claim 1)

[1659] A means for detecting when a file is uploaded from a user terminal,

[1660] A means of notifying the server of the metadata of the uploaded file,

[1661] A means of analyzing the contents of an uploaded file and extracting text data,

[1662] A means of generating a summary using generative artificial intelligence with extracted text data,

[1663] A means for extracting relevant tags from the generated summary,

[1664] A means of classifying and moving files to the appropriate shared folder based on extracted tags,

[1665] A means for users to perform tag-based file searches using a search interface,

[1666] A means by which the server parses the search query, identifies the relevant file, and returns the search results,

[1667] A system that includes this.

[1668] (Claim 2)

[1669] The system according to claim 1, comprising means for using OCR technology and a text extraction library to analyze the contents of a file.

[1670] (Claim 3)

[1671] The system according to claim 1, wherein the search system has means for identifying files based on the generated summary and extracted tags.

[1672] "Application Example 1"

[1673] (Claim 1)

[1674] A means for detecting when a file is uploaded from a user terminal,

[1675] A means of analyzing the contents of an uploaded file and generating a summary,

[1676] A means for extracting relevant tags from the generated summary,

[1677] A means of classifying and moving files to the appropriate shared folder based on extracted tags,

[1678] A method for automatically creating folders and classifying files based on the contents of uploaded files,

[1679] A means of generating summaries and tags using generative artificial intelligence,

[1680] A system that includes means for analyzing and storing data using cloud servers.

[1681] (Claim 2)

[1682] The system according to claim 1, which moves uploaded files to the relevant folders based on a summary of those files.

[1683] (Claim 3)

[1684] The system according to claim 1, wherein the search system has means for identifying a file based on extracted tags.

[1685] "Example 2 of combining an emotion engine"

[1686] (Claim 1)

[1687] A means for detecting when a file is uploaded from a user terminal,

[1688] A means of analyzing the contents of an uploaded file and generating a summary,

[1689] A means for extracting relevant tags from the generated summary,

[1690] A means of detecting the user's emotional state in real time,

[1691] A means of sending detected emotion data to a server,

[1692] A means of supplementing and correcting tags and summaries generated based on sentiment data,

[1693] A system that includes means for classifying and moving files to appropriate shared folders based on extracted tags.

[1694] (Claim 2)

[1695] The system according to claim 1, comprising means for analyzing the contents of a file and generating a summary using generative artificial intelligence.

[1696] (Claim 3)

[1697] The system according to claim 1, wherein the search system has means for identifying files based on extracted tags.

[1698] "Application example 2 when combining with an emotional engine"

[1699] (Claim 1)

[1700] A means for detecting when a file is uploaded from a user terminal,

[1701] A means of analyzing the contents of an uploaded file and generating a summary,

[1702] A means for extracting relevant tags from the generated summary,

[1703] A means of classifying and moving files to the appropriate shared folder based on extracted tags,

[1704] A means for processing user emotion data using an emotion recognition engine that recognizes user emotions,

[1705] A system that includes means for supplementing and correcting tags and summaries generated based on sentiment data.

[1706] (Claim 2)

[1707] The system according to claim 1, comprising means for analyzing the contents of a file and generating a summary using generative artificial intelligence.

[1708] (Claim 3)

[1709] The system according to claim 1, wherein the search system has means for identifying files based on extracted tags. [Explanation of Symbols]

[1710] 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 detecting when a file is uploaded from a user terminal, A means of analyzing the contents of an uploaded file and generating a summary, A means for extracting relevant tags from the generated summary, A system that includes means for classifying and moving files to appropriate shared folders based on extracted tags.

2. A system according to claim 1, further comprising means for using generative artificial intelligence to analyze the contents of a file.

3. A system according to claim 1, wherein the search system is provided with means for identifying a file based on extracted tags.

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