System

Abstract

A system is provided.SOLUTION: A system comprising: an interactive means for entering a file name and corresponding metadata when a user creates a file; a storage means for storing the file name and metadata in a database; a search means for searching for a matching file from the database when a user enters a search query; a similarity calculation means for calculating a similarity between the search query and the metadata; and an output means for presenting a file with the highest similarity to a user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, 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] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] The problem is that business people spend as much as 150 hours a year searching for files, resulting in a lack of concentration and increased stress. Conventional file management systems do not effectively manage file metadata, making it difficult for users to quickly find the files they need. [Means for solving the problem]

[0005] The present invention provides a system that allows users to interactively input metadata when creating files and stores the metadata in a database. When the user enters a search query, the system calculates the similarity between the stored metadata and the search query and presents the most relevant files to the user. This allows users to quickly find the files they need, significantly reducing time and stress. Furthermore, by using a machine learning algorithm to calculate the similarity, the system provides highly accurate search results. It also provides an interactive means for editing and modifying metadata, improving management flexibility.

[0006] "User" means an individual or organization that uses the system to create, search, and manage files.

[0007] A "file name" is a name given to identify an individual file.

[0008] "Metadata" is data that briefly describes information related to a file and is used when searching the contents of a file.

[0009] "Interaction means" refers to the interface and prompt functions that allow the user to enter input while interacting with the system.

[0010] "Storage means" refers to a function that stores the file name and metadata entered by the user in storage such as a database.

[0011] A "database" is a system designed to store data in an organized manner and enable efficient retrieval and updating.

[0012] "Search facility" refers to the functionality that locates appropriate files in the database based on a search query entered by the user.

[0013] The "similarity calculation means" is a function that calculates the similarity between a search query and metadata in a database and evaluates the degree of relevance.

[0014] The "output means" is a function that presents the most relevant files to the user as search results.

[0015] A "machine learning algorithm" is a technology that learns patterns from large amounts of data and automatically evaluates the relationships between data.

[0016] "Editing means" refers to functionality that allows a user to edit or modify stored metadata. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10]1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0022] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 1, a 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.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the 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.

[0031] 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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process 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.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] The present invention is a system that allows users to interactively input, store, and search metadata to facilitate file management and retrieval, thereby saving users time and enabling them to efficiently find the files they need.

[0039] 1. Creating a file and entering metadata

[0040] When a user creates a new file, they decide on a file name, for example "Project Report.docx."

[0041] The terminal will prompt you to "Enter a description for this file."

[0042] The user enters metadata for a file such as "end of year project report."

[0043] 2. Data storage

[0044] The device sends the file name and metadata to the server.

[0045] The server stores the received data in a database: it opens a database connection and executes a SQL statement to insert the file name, metadata, and creation date into the database.

[0046] 3. Search for files

[0047] A user enters a search query to find a specific file, for example, "end of year report."

[0048] The terminal sends this search query to the server.

[0049] The server opens a database connection and executes a SQL statement to retrieve metadata for all files.

[0050] 4. Similarity calculation

[0051] The server calculates the similarity between the retrieved metadata and the user's search query, using a machine learning algorithm to generate a highly accurate similarity score.

[0052] The server identifies the most relevant files based on the calculated similarity scores.

[0053] 5. Presentation of search results

[0054] The server returns the most relevant filename to the terminal.

[0055] The device will display "Best file is: <filename>" to the user.

[0056] 6. Editing Metadata

[0057] If the user wishes, they can edit or modify the metadata that has already been saved.

[0058] The terminal provides an editing interface and receives new metadata from the user and sends it to the server.

[0059] The server updates the existing record in the database.

[0060] Specific examples

[0061] File creation example: When a user creates a new file "Project Plan.docx," the terminal prompts the user to "Enter a description for this file." The user enters "Project plan for next year," and the terminal sends this information to the server. The server stores this information in a database.

[0062] File search example: A user searches for "plan for next year" by entering search keywords into the device. The device sends this query to the server, which retrieves all metadata from the database and calculates similarity. The server identifies the most relevant file, "Project Plan.docx," and returns it to the device. The device displays to the user, "The best file is: Project Plan.docx."

[0063] Metadata editing example: If a user wants to change the metadata of "Project Plan.docx" to "Project Plan for Next Year", the terminal provides an editing interface. The user inputs new metadata and the terminal sends it to the server. The server updates the existing record in the database.

[0064] As described above, this system provides users with a means to efficiently manage and search for files, and in particular enables them to quickly find the files they need through metadata collection and similarity calculations.

[0065] The processing flow will be explained below.

[0066] Program processing flow (when creating a file)

[0067] Step 1:

[0068] When a user creates a new file, they decide on a file name, for example "Project Report.docx".

[0069] Step 2:

[0070] The terminal prompts the user to "Please enter a description for this file."

[0071] Step 3:

[0072] The user enters metadata about the file, for example "end of year project report."

[0073] Step 4:

[0074] The terminal transmits the file name and metadata input by the user to the server.

[0075] Step 5:

[0076] The server opens a database connection in preparation for storing the received filename and metadata in the database.

[0077] Step 6:

[0078] The server executes the SQL statement and inserts the file name, metadata, and creation date and time into the database.

[0079] Step 7:

[0080] The server confirms that the save was successful and sends that information to the device.

[0081] Step 8:

[0082] The terminal notifies the user that the file has been successfully saved.

[0083] Program processing flow (when searching for files)

[0084] Step 1:

[0085] A user enters a search query, for example, "year-end report."

[0086] Step 2:

[0087] The terminal sends a search query from the user to the server.

[0088] Step 3:

[0089] The server opens a database connection and executes a SQL statement to retrieve metadata for all files.

[0090] Step 4:

[0091] The server uses a machine learning algorithm to calculate the similarity between the metadata it has acquired and the user's search query.

[0092] Step 5:

[0093] The server calculates the similarity scores and identifies the most similar files.

[0094] Step 6:

[0095] The server returns the most relevant filename to the terminal.

[0096] Step 7:

[0097] The device will tell the user, "The best file is: <filename>."

[0098] Program processing flow (when editing metadata)

[0099] Step 1:

[0100] The user selects the file for which they wish to edit or modify the metadata.

[0101] Step 2:

[0102] The device displays an editing interface with the existing metadata.

[0103] Step 3:

[0104] The user enters new metadata, for example, changing it to "Project plan for next year."

[0105] Step 4:

[0106] The device sends the new metadata to the server.

[0107] Step 5:

[0108] The server opens a database connection and executes SQL statements to update existing metadata.

[0109] Step 6:

[0110] The server confirms that the update was successful and sends that information to the device.

[0111] Step 7:

[0112] The terminal notifies the user that the metadata update was successful.

[0113] Example 1

[0114] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0115] In modern electronic file management systems, the large number of files stored makes it difficult for users to quickly search for and access the files they need. In particular, if file metadata (e.g., descriptions and tags) is not properly managed, the accuracy of the search function will be significantly reduced. Furthermore, manually updating metadata is a cumbersome task, preventing users from working efficiently. To solve these problems, a system that enables efficient file search and management is needed.

[0116] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0117] In this invention, the server includes an interactive means for inputting file names and corresponding metadata when a user creates a file, a storage means for storing the file names and metadata in a database, a search means for searching the database for matching files when a user inputs a search query, a similarity calculation means for calculating the similarity between the search query and the metadata, an output means for presenting the most similar file to the user, and an interactive means for editing or correcting the metadata input by the user. This allows the user to efficiently input, edit, and search file metadata, thereby enabling the user to quickly find the file they need.

[0118] A "user" is an individual or organization that uses the system to create, search, and edit files.

[0119] A "file name" is an identifying character string that is assigned to each file created by a user.

[0120] "Metadata" is additional information entered by the user to describe the contents of a file and is used to improve search accuracy.

[0121] "Interaction means" refers to an interface that allows a user to interactively input data and perform operations with the system.

[0122] "Storage means" is a function for storing file names and metadata in a database.

[0123] A "database" is a system that stores file names and metadata in an organized manner and manages them so that they can be searched and edited.

[0124] A "search query" is a keyword or phrase that a user enters to locate a particular file.

[0125] The "search means" is a function that searches for matching files in the database based on a user's search query.

[0126] The "similarity calculation means" is a function that calculates the relevance between a user's search query and metadata in the database.

[0127] "Machine learning algorithms" are artificial intelligence techniques used to calculate similarity and automatically classify data.

[0128] "Output means" is a function that visually presents search results and other information to the user.

[0129] "Communication means" refers to a communication function via the Internet or a local network for sending and receiving user input data and search results from a server.

[0130] This invention relates to a system that allows users to efficiently manage, search, and edit files. This system shares file names and metadata between users, terminals, and servers, and realizes highly accurate file searches.

[0131] Hardware and software used

[0132] This system consists of a terminal (e.g., a PC or smartphone) that accepts user operations, a server for storing and processing data, and a database. It also uses machine learning algorithms (e.g., TF-IDF or Word2Vec) to calculate the similarity of metadata, and a communication method (e.g., HTTP protocol) to exchange data between the server and the terminal.

[0133] Creating a file and entering metadata

[0134] When a user creates a new file, they input the file name into the terminal. At this time, the terminal displays a prompt saying "Please enter a description for this file" and prompts the user to input metadata. For example, the user may input metadata such as "Year-end project report."

[0135] Data storage

[0136] The terminal sends the file name and metadata to the server. The server receives this data and stores it in a database. Specifically, the server uses SQL statements to insert the file name, metadata, and creation date and time into the database.

[0137] Searching for files

[0138] When a user wants to find a specific file, they enter a search query into their device, for example, searching for "year-end report." The device then sends this query to the server, which retrieves all the metadata from the database and calculates the similarity to the search query. This calculation is done using machine learning algorithms such as TF-IDF and Word2Vec.

[0139] Presenting search results

[0140] Based on the calculated similarity score, the server identifies the most relevant filenames and returns them to the device, which then displays them to the user as something like "The best file is: Project Report.docx."

[0141] Editing Metadata

[0142] If the user wants to edit or modify the already saved metadata, the terminal provides an editing interface and receives new metadata from the user, which the terminal sends to the server, which then updates the existing record in the database.

[0143] Specific examples

[0144] File creation example: A user creates a new file "Project Plan.docx" and the terminal prompts, "Please enter a description for this file." If the user enters "Project plan for next year," the terminal sends this information to the server, which stores it in a database.

[0145] File search example: If a user searches for "Plan for next year", they enter the search keyword into their device. The device sends this query to the server, which retrieves all the metadata in the database. It then calculates the similarity and identifies the most relevant file, "Project Plan.docx", and returns it to the device. The device displays "The best file is: Project Plan.docx".

[0146] Metadata editing example: If a user wants to change the metadata of "Project Plan.docx" to "Project Plan for Next Year", the terminal provides an editing interface. The user inputs new metadata and the terminal sends it to the server. The server updates the existing record in the database.

[0147] This system allows users to efficiently enter, edit, and search file metadata, enabling them to quickly find the files they need.

[0148] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0149] Step 1:

[0150] When a user creates a new file, they enter a filename into the terminal, for example "Project Report.docx". The input at this point is the "filename", the string the user types into the terminal. The output is the prompt that is displayed on the terminal.

[0151] Step 2:

[0152] The terminal displays a prompt saying "Please enter a description for this file" and prompts the user to enter metadata. The input is "metadata," and the user might enter, for example, "Year-end project report." The output is metadata stored in the terminal's temporary memory.

[0153] Step 3:

[0154] The device sends the filename and metadata to the server using an HTTP POST request. The input is the filename and metadata, and the output is the data sent to the server.

[0155] Step 4:

[0156] The server stores the received data in a database. First, the server opens a database connection. The input is the file name and metadata sent from the terminal, and the output is the record to be stored in the database. Specifically, it executes the SQL statement "INSERT INTO files (file_name, metadata, creation_date) VALUES ('Project report.docx', 'Year-end project report', '2023-10-23')".

[0157] Step 5:

[0158] A user enters a search query to find a specific file, for example, "year-end report." The input is the "search query," which the device sends to the server. The output is the search query sent to the server.

[0159] Step 6:

[0160] The server opens a database connection and retrieves all metadata by executing a SQL statement such as "SELECT file_name, metadata FROM files". The input is the query to the database and the output is a list of the retrieved metadata.

[0161] Step 7:

[0162] The server calculates the similarity between the retrieved metadata and the user's search query, using, for example, TF-IDF (Term Frequency-Inverse Document Frequency). The input is the search query and a list of metadata, and the output is a similarity score for each file.

[0163] Step 8:

[0164] The server identifies the most relevant files based on the calculated similarity scores: the input is the similarity score, and the output is the filename with the highest score.

[0165] Step 9:

[0166] The server returns the most relevant filename to the terminal. The input is the identified filename, and the output is the filename returned to the terminal. The returned data is in JSON format.

[0167] Step 10:

[0168] The terminal will display to the user, "The best file is: Project Report.docx." The input is the file name returned by the server, and the output is the search results presented to the user.

[0169] Step 11:

[0170] When a user edits or modifies already saved metadata, the terminal provides an editing interface and receives new metadata from the user. The input is the new metadata edited by the user, which the terminal sends to the server. The output is the new metadata sent to the server.

[0171] Step 12:

[0172] The server updates an existing record in the database. The input is the new metadata, specifically by executing the SQL statement "UPDATE files SET metadata = 'newmetadata' WHERE file_name = 'projectreport.docx'". The output is the updated database record.

[0173] (Application example 1)

[0174] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0175] In factories and other workplaces, managing and quickly searching a large number of documents is essential, and effective management methods are needed. However, current document management systems have the drawback of being time-consuming to operate, as metadata input and editing is cumbersome and search accuracy is insufficient. Factories, in particular, need systems that can efficiently input metadata using voice input and touch interfaces and quickly search for related documents.

[0176] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0177] In this invention, the server includes an interactive means for inputting file names and corresponding metadata when a user creates a file, a storage means for storing the file names and metadata in a database, a search means for searching the database for matching files when a user inputs a search query, a similarity calculation means for calculating the similarity between the search query and the metadata, an output means for presenting the most similar file to the user, and a means for inputting the user-entered metadata via voice or a touch interface. This allows document metadata to be efficiently entered and managed, improving search accuracy and enabling desired documents to be found quickly.

[0178] "User" means a person or end user who operates the system and inputs, searches, and edits data.

[0179] A "file name" is a text-based name set by the user to identify an individual file.

[0180] "Metadata" is data that represents additional information associated with a file, detailing the contents and characteristics of the file.

[0181] An "interaction means" is an interface used by a user to input and edit data, including in particular voice input and touch interfaces.

[0182] A "storage mechanism" is a mechanism for recording and maintaining file names and metadata in a database.

[0183] The "search means" is a function for searching for related files from the database based on a query entered by the user.

[0184] The "similarity calculation means" is an algorithm for calculating the similarity between a user's search query and metadata in the database.

[0185] The "output means" is a mechanism for providing the user with information on the most relevant file based on the calculated similarity.

[0186] The present invention relates to a system for efficiently managing and quickly searching for a large number of documents (such as blueprints, maintenance procedures, and operation manuals) used in a factory. Specific embodiments of the system will be described in detail below.

[0187] The system includes a means for users to interactively enter, store, and retrieve metadata.

[0188] Hardware and software used

[0189] Hardware: Robots deployed in factories (with voice recognition and touchscreen displays)

[0190] Software: Python, SQLite (for database management), Scikit-learn (machine learning library)

[0191] Details of data processing and calculation

[0192] 1. Database connection and metadata storage

[0193] The server connects to an SQLite database and creates a table to store document information. When a user creates a new document, the robot prompts the user, "Please enter a description for this document." The user provides metadata via voice input or touch panel input, and the robot sends the metadata to the server and stores it in the database.

[0194] 2. Metadata search and similarity calculation

[0195] When a user searches for a specific document, they input a search query into the robot (via voice or touch panel). The server sends this search query to the database and retrieves the stored metadata. It then uses Scikit-learn's TfidfVectorizer and cosine_similarity function to calculate the similarity between the search query and the stored metadata.

[0196] 3. Presentation of search results

[0197] The server identifies the most relevant document based on the calculated similarity and sends that information back to the robot, which displays to the user, "The best document is: <document name>."

[0198] 4. Editing Metadata

[0199] If a user wants to edit the metadata of an existing document, the robot provides an editing interface, and when the user enters new metadata, it sends it to the server, updating the existing record.

[0200] Specific examples

[0201] For example, if a user adds a new document called "Factory Machine Maintenance Procedures.pdf", the following happens:

[0202] 1. The robot displays the prompt, "Please enter a description of this document."

[0203] 2. The user speaks "Routine maintenance procedures."

[0204] 3. The robot sends this to the server and stores it in the database.

[0205] If a user searches for "maintenance procedures," the experience progresses as follows:

[0206] 1. A user enters the search query "maintenance procedures" into the robot.

[0207] 2. The server receives the query, retrieves the metadata from the database, and performs the similarity calculation.

[0208] 3. The server sends the most relevant document back to the robot, which then displays, "The best document is: Factory Machine Maintenance Procedures.pdf."

[0209] Prompt Sentence Examples

[0210] For example, it can be used as follows when executing a Python program:

[0211] python

[0212] Documentation

[0213] create_document("Factory Machine Maintenance Procedure.pdf", "Periodic Maintenance Procedure")

[0214] Document Search

[0215] print(search_documents("Maintenance Procedures"))

[0216] Metadata Editing

[0217] edit_metadata("Factory Machine Maintenance Procedure.pdf", "Monthly Scheduled Maintenance Procedure")

[0218] This allows the system to efficiently manage and quickly search a large number of documents within a factory.

[0219] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0220] Step 1:

[0221] When a user creates a new file, the robot (terminal) displays a prompt saying, "Please enter a description of this document." The user provides metadata via voice input or touch panel.

[0222] Input: User-entered file name and metadata (e.g., "Factory Machine Maintenance Procedures.pdf", "Routine Maintenance Procedures")

[0223] Output: Send collected filenames and metadata to the server

[0224] Step 2:

[0225] The server receives the file name and metadata sent from the device and stores them in an SQLite database by opening a database connection and inserting the file name, metadata, and creation date and time into a table.

[0226] Input: File name and metadata sent from the device (e.g., "Factory Machine Maintenance Procedures.pdf", "Routine Maintenance Procedures")

[0227] Output: New document information saved in the database

[0228] Step 3:

[0229] When a user enters a search query, the robot (terminal) receives the query from the user and sends it to the server.

[0230] Input: The search query entered by the user (e.g., "maintenance procedures")

[0231] Output: Sends the search query to the server

[0232] Step 4:

[0233] The server retrieves all metadata from the database and performs a similarity calculation to find metadata that matches the user's search query.

[0234] Input: User search query and metadata retrieved from the database

[0235] Data processing: Generate TF-IDF vectors for search queries and metadata

[0236] Data arithmetic: Calculate cosine similarity and identify the most relevant metadata

[0237] Output: Identify the most relevant files based on a similarity calculation

[0238] Step 5:

[0239] The server returns the most relevant filenames based on the calculated similarity to the robot (terminal).

[0240] Input: The most related filenames based on the similarity calculation

[0241] Output: Sends the most relevant filename to the terminal

[0242] Step 6:

[0243] The robot (terminal) displays the search results to the user, specifically displaying "The best document is: <Document name>."

[0244] Input: The file name returned by the server

[0245] Output: Displaying search results to the user

[0246] Step 7:

[0247] When a user edits or modifies already saved metadata, the robot (terminal) provides an editing interface, receives new metadata from the user, and sends it to the server.

[0248] Input: New metadata entered by the user (e.g., "Monthly scheduled maintenance procedures")

[0249] Output: Send the new metadata to the server

[0250] Step 8:

[0251] The server receives the new metadata sent from the device and updates the existing record in the SQLite database, specifically by replacing the metadata for the corresponding file name with the new one.

[0252] Input: New metadata sent from the device

[0253] Output: Metadata in the database is updated

[0254] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0255] The present invention is a system that uses an emotion engine to recognize a user's emotions when creating, managing, and searching for files, and provides an appropriate interface and search results according to those emotions. This system promotes file metadata input and adjusts search results based on the user's emotions, thereby achieving a better user experience.

[0256] 1. Emotion engine integration

[0257] The device is equipped with an emotion engine that recognizes emotions in real time from the user's facial expressions, tone of voice, and input method.

[0258] 2. Creating a file and entering metadata

[0259] When a user creates a new file, they set the file name, for example, "Project Report.docx."

[0260] The device will prompt you to "Enter a description for this file" and the emotion engine will analyze the user's current emotions.

[0261] If the emotion engine recognizes that the user is feeling stressed, the device will provide a relaxing interface and encourage input.

[0262] A user enters metadata such as "year-end project report."

[0263] 3. Data storage

[0264] The device sends the file name and metadata to the server.

[0265] To store the received data in a database, the server opens a database connection and executes an SQL statement to insert the file name, metadata, and creation date and time into the database.

[0266] 4. Search for files

[0267] A user enters a search query, for example, "year-end report."

[0268] The terminal sends a search query from the user to the server.

[0269] The server opens a database connection and executes a SQL statement to retrieve metadata for all files.

[0270] The server uses a machine learning algorithm to calculate the similarity between the acquired metadata and the user's search query.

[0271] The emotion engine analyzes the user's emotions, and if the user is in a hurry, for example, it prioritizes the information that needs to be returned most quickly and identifies the most relevant files.

[0272] The server returns the most relevant filename to the terminal.

[0273] The device will display "Best file is: <filename>" to the user.

[0274] 5. Editing Metadata

[0275] If the user wishes to edit or modify the metadata, the terminal provides an editing interface.

[0276] The user inputs new metadata, for example, changing it to "Next year's project plan."

[0277] The terminal sends the new metadata to the server.

[0278] The server opens a database connection and executes SQL statements to update the existing metadata.

[0279] The server confirms that the update was successful and sends it to the terminal, and the terminal notifies the user that the metadata update was successful.

[0280] Specific examples

[0281] File creation example: When a user creates a file called "Meeting minutes.docx," the device prompts the user, "Please enter a description for this file." If the emotion engine recognizes that the user is tired, it presents a friendly interface to assist input. The user enters "Monthly meeting minutes," and the device sends this information to the server, which stores it in a database.

[0282] File search example: When a user searches for "monthly meeting," the device sends this query to the server. The server retrieves metadata from the database and calculates similarity. If the emotion engine recognizes that the user is in a hurry, it prioritizes the most relevant files. The server identifies "Meeting Minutes.docx" and sends it back to the device. The device displays, "The best file is: Meeting Minutes.docx."

[0283] Metadata editing example: If a user wants to change the metadata of "Meeting Minutes.docx" to "Minutes of Quarterly Meeting", an editing interface is provided. The user enters new metadata and the terminal sends it to the server. The server updates the existing record in the database and notifies the terminal that the update was successful. The terminal notifies the user that the update was successful.

[0284] As described above, by integrating the emotion engine, we have created a system that can provide a flexible interface that responds to the user's emotional state and highly accurate search results.

[0285] The processing flow will be explained below.

[0286] Program processing flow (when creating a file)

[0287] Step 1:

[0288] The user decides to create a new file and enters a file name, for example "Project Report.docx."

[0289] Step 2:

[0290] The terminal receives the filename and displays the prompt "Please enter a description for this file."

[0291] Step 3:

[0292] The emotion engine built into the device analyzes the user's facial expressions and tone of voice to recognize emotions in real time.

[0293] Step 4:

[0294] The device provides an interface based on the user's emotions, for example, if the user is feeling stressed, it uses a relaxing interface.

[0295] Step 5:

[0296] The user enters a description for the file, for example, "End of Year Project Report."

[0297] Step 6:

[0298] The device sends the entered file name and metadata to the server.

[0299] Step 7:

[0300] The server opens a database connection and executes an SQL statement to insert the file name, metadata, and creation date into the database.

[0301] Step 8:

[0302] The server confirms that the save was successful and sends that information to the device.

[0303] Step 9:

[0304] The terminal notifies the user that the file has been successfully saved.

[0305] Program processing flow (when searching for files)

[0306] Step 1:

[0307] A user enters a search query to find a specific file, for example, "end of year report."

[0308] Step 2:

[0309] The terminal receives the search query and sends it to the server.

[0310] Step 3:

[0311] The server opens a database connection and executes a SQL statement to retrieve metadata for all files.

[0312] Step 4:

[0313] Using the metadata acquired by the server, a machine learning algorithm is used to calculate the similarity to the user's search query.

[0314] Step 5:

[0315] The emotion engine built into the device analyzes the user's current emotions and prioritizes displaying results quickly if, for example, the user is in a hurry.

[0316] Step 6:

[0317] The server calculates the similarity scores and identifies the most similar files.

[0318] Step 7:

[0319] The server sends the specified file name to the terminal.

[0320] Step 8:

[0321] The device displays "The best file is: <filename>" to the user.

[0322] Program processing flow (when editing metadata)

[0323] Step 1:

[0324] If the user wishes to edit or modify the metadata for an existing file, the user selects the file.

[0325] Step 2:

[0326] The device displays the existing metadata for the file and provides an editing interface.

[0327] Step 3:

[0328] The user enters new metadata, for example, changing it to "Project plan for next year."

[0329] Step 4:

[0330] The device sends the new metadata to the server.

[0331] Step 5:

[0332] The server opens a database connection and executes SQL statements to update the existing metadata.

[0333] Step 6:

[0334] The server confirms that the update was successful and sends that information to the device.

[0335] Step 7:

[0336] The terminal notifies the user that the metadata update was successful.

[0337] Emotion Engine Processing Flow

[0338] Step 1:

[0339] When a user operates the system, the device's built-in camera and microphone capture the user's facial expressions and tone of voice.

[0340] Step 2:

[0341] The device's emotion engine analyzes the captured data in real time to recognize the user's emotional state.

[0342] Step 3:

[0343] The device will provide an appropriate interface based on the recognized emotion, for example, using relaxing colors and fonts if the user is tired.

[0344] Step 4:

[0345] The device transmits the user's emotional state to the server, which is then taken into account when searching for files and entering metadata.

[0346] Step 5:

[0347] The server adjusts the parameters of the search algorithm based on the emotional data and returns the optimal results according to the user's situation.

[0348] As described above, by integrating an emotion engine, the system of the present invention can provide a flexible interface that responds to the user's emotions and highly accurate search results.

[0349] Example 2

[0350] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0351] The present invention aims to provide a better user experience by appropriately recognizing a user's emotions when creating, managing, and searching for files, and providing an interface and search results that reflect those emotions. Conventional systems do not respond to user emotions, which can cause users to feel stressed when creating or searching for files. Another problem is that it can be difficult for users to quickly find the right file when they are in a hurry.

[0352] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0353] In this invention, the server includes emotion recognition means for recognizing a user's emotion in real time, adjustment means for providing an interface according to the user's emotion, and similarity calculation means for calculating the similarity between the search query and metadata. This allows the interface and search results to be adjusted based on the user's emotion, enabling the user to quickly find or create the files they need without feeling stressed.

[0354] "User" means a person who uses the system to create, manage, and retrieve files.

[0355] A "file" is a piece of digital data, such as a document or image, that users create, store, and search.

[0356] "Metadata" is information associated with a file, including additional information such as the file name, description, and tags.

[0357] An "interaction means" is a means that provides an interface for a user to interact with the system and input information.

[0358] "Storage" refers to the mechanism by which filenames and metadata are stored in a database.

[0359] The "search means" is a function for searching files in the database and providing the user with results appropriate for the file.

[0360] "Similarity calculation means" refers to a mechanism for calculating the similarity between a user's search query and a file's metadata.

[0361] The "output means" is a means for presenting search results to the user.

[0362] "Emotion recognition means" refers to a system that recognizes emotions in real time from a user's facial expressions, tone of voice, input method, etc.

[0363] The "adjustment means" refers to a function that adjusts the interface and search results according to the user's emotions detected by the emotion recognition means.

[0364] A "machine learning algorithm" refers to an algorithm that analyzes data and learns patterns and rules to calculate similarity and optimize searches.

[0365] The present invention is a system that uses an emotion engine to recognize a user's emotions when creating, managing, and searching for files, and provides an appropriate interface and search results based on those emotions. This system promotes file metadata entry and adjusts search results based on the user's emotions, thereby achieving a better user experience.

[0366] Emotion engine integration

[0367] The device is equipped with an emotion engine that recognizes emotions in real time from the user's facial expressions, tone of voice, input method, etc. The emotion engine uses, for example, Microsoft's Azure Face API for facial recognition technology and Google Cloud Speech-to-Text for voice recognition technology.

[0368] Creating a file and entering metadata

[0369] When a user creates a new file, they set the file name, for example, "Project Report.docx."

[0370] The device will prompt you to "Enter a description for this file" and the emotion engine will analyze the user's current emotions.

[0371] If the emotion engine detects that the user is feeling stressed, the device will provide a relaxing interface and encourage input, such as changing the background color or playing relaxing music.

[0372] A user enters metadata such as "year-end project report."

[0373] Data storage

[0374] The device sends the file name and metadata to the server.

[0375] The server opens a database connection, executes a SQL statement that saves the file name, metadata, and creation date and time in the database, and saves the data.

[0376] Searching for files

[0377] A user enters a search query, for example, "year-end report."

[0378] The terminal sends a search query to the server.

[0379] The server opens a database connection and executes a SQL statement to retrieve metadata for all files.

[0380] The server uses a machine learning algorithm to calculate the similarity between the acquired metadata and the user's search query.

[0381] The emotion engine analyzes the user's emotions, and if the user is in a hurry, for example, it prioritizes the information that needs to be returned most quickly and identifies the most relevant files.

[0382] The server returns the most relevant filename to the terminal.

[0383] The device will display to the user "The best file is: Meeting Minutes.docx."

[0384] Editing Metadata

[0385] If the user wishes to edit or modify the metadata, the terminal provides an editing interface.

[0386] The user inputs new metadata, for example, changing it to "Next year's project plan."

[0387] The terminal sends the new metadata to the server.

[0388] The server executes a SQL statement to update an existing record in the database.

[0389] The server confirms that the update was successful and notifies the terminal.

[0390] The terminal notifies the user of the success of the update.

[0391] Specific examples

[0392] File creation example

[0393] When a user creates a file called "Meeting Minutes.docx," the device prompts the user, "Please enter a description for this file." If the emotion engine detects that the user is tired, it presents a friendly interface to assist input. The user types "Monthly Meeting Minutes," and the device sends this information to the server, which stores it in a database.

[0394] File search example

[0395] When a user searches for "monthly meeting," the device sends this query to the server. The server retrieves metadata from the database and calculates similarity. If the emotion engine recognizes that the user is in a hurry, it prioritizes the most relevant files. The server identifies "Meeting Minutes.docx" and sends it back to the device. The device displays, "The best file is: Meeting Minutes.docx."

[0396] Metadata editing example

[0397] If a user wants to change the metadata of "Meeting Minutes.docx" to "Minutes of Quarterly Meeting," an editing interface is provided. The user enters new metadata, and the terminal sends it to the server. The server updates the existing record in the database and notifies the terminal that the update was successful. The terminal notifies the user that the update was successful.

[0398] As described above, by integrating the emotion engine, we have created a system that provides a flexible interface and highly accurate search results that respond to the user's emotional state.

[0399] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0400] Step 1: Integrating the Emotion Engine

[0401] The device uses an emotion engine to recognize the user's facial expressions, tone of voice, and input method in real time. The emotion engine uses, for example, a general face recognition API for facial recognition technology or a voice recognition API for voice recognition technology. Specifically, it acquires data from the camera and microphone and inputs it into an emotion recognition model. The emotion model analyzes the data and outputs the user's emotional state (e.g., stressed, relaxed, etc.).

[0402] Input: Real-time data from camera and microphone

[0403] Data processing: Emotion analysis using face and voice recognition APIs

[0404] Output: User's emotional state

[0405] Step 2: Enter a file name

[0406] The terminal prompts the user to enter a file name when creating a new file, and the user enters the file name and sends it to the terminal (e.g., "Project Report.docx").

[0407] Input: The file name entered by the user

[0408] Output: Send filename to terminal

[0409] Step 3: Prompt for Metadata

[0410] The device displays a prompt saying, "Please enter a description for this file," and the emotion engine analyzes the user's current emotion. If the emotion engine determines that the user is feeling stressed, the device provides a relaxing interface (e.g., changing the background color, playing relaxing music) to encourage input.

[0411] Input: prompt after entering user's emotional state and file name

[0412] Data manipulation: adjusting the interface based on emotions

[0413] Output: Display interface and prompts to the user

[0414] Step 4: Entering Metadata

[0415] The user inputs metadata (e.g., "end of year project report"), and the device receives this input and begins the process of saving the data.

[0416] Input: User-entered metadata

[0417] Output: Sending metadata to the device

[0418] Step 5: Sending data

[0419] The device sends the entered file name and metadata to the server, which prepares to save the data.

[0420] Input: Filename and metadata

[0421] Output: Send data to the server

[0422] Step 6: Save your data

[0423] The server opens a database connection, executes a SQL statement to store the filename, metadata, and creation date and time in the database, and then saves the data. For example, it executes the SQL statement "INSERT INTO files (filename, metadata, created_at) VALUES ('Project report.docx', 'End of year project report', NOW())".

[0424] Input: Filename and metadata

[0425] Data processing: Generate SQL statements and save them to the database

[0426] Output: Confirmation saved in the database

[0427] Step 7: Enter a search query

[0428] A user enters a search query into a terminal (e.g., "year-end report"), and the terminal sends the search query to the server.

[0429] Input: The search query entered by the user

[0430] Output: Sending a search query to the server

[0431] Step 8: Retrieving Metadata from the Database

[0432] The server opens a database connection and executes a SQL statement to retrieve all file metadata, for example the SQL statement "SELECT filename, metadata FROM files" to retrieve all metadata.

[0433] Input: Search query

[0434] Data processing: SQL statement generation, metadata acquisition

[0435] Output: Retrieved metadata

[0436] Step 9: Calculate similarity

[0437] The server runs machine learning algorithms to calculate the similarity between the retrieved metadata and the user's search query. For example, it uses natural language processing models to evaluate the similarity between the search query and the metadata. An emotion engine analyzes the user's emotions and prioritizes the most relevant files if the user is in a hurry.

[0438] Input: Search query and retrieved metadata

[0439] Data processing: Similarity calculation using machine learning algorithms

[0440] Output: Identifying the most relevant files

[0441] Step 10: Output search results

[0442] The server returns the most relevant filename to the terminal, which displays the message "The best file is: <filename>" to the user.

[0443] Input: A specified file name

[0444] Output: Displayed to user as search result

[0445] Step 11: Editing Metadata

[0446] If the user wants to edit or modify the metadata, the terminal provides an editing interface. The user inputs new metadata (e.g., "Project plan for next year") and the terminal transmits the new metadata to the server.

[0447] Input: New metadata entered by the user

[0448] Output: Sending new metadata to the server

[0449] Step 12: Update the Metadata

[0450] The server executes SQL statements to update existing records in the database, for example, the SQL statement "UPDATE files SET metadata = 'Next Year's Project Plan' WHERE filename = 'Project Report.docx'".

[0451] Input: New Metadata

[0452] Data processing: SQL statement generation, database update

[0453] Output: Confirmation of successful database update

[0454] Step 13: Notification of successful update

[0455] The server confirms that the update was successful and notifies the terminal, which then notifies the user of the success of the update.

[0456] Input: Confirmation of successful database update

[0457] Output: Notify user that update was successful

[0458] (Application example 2)

[0459] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0460] In conventional file creation, management, and search systems, it was difficult to provide an appropriate interface or search results when the user was in an emotional state, such as when they were tired or stressed. As a result, the user's work efficiency decreased and it could even lead to incorrect file operations. Therefore, the purpose of this invention is to solve these problems and provide a system that provides a flexible interface and highly accurate search results that respond to the user's emotions.

[0461] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0462] In this invention, the server includes an interaction means for inputting a file name and corresponding metadata when a user creates a file, a storage means for storing the file name and metadata in a database, a search means for searching the database for matching files when a user inputs a search query, a similarity calculation means for calculating a similarity between the search query and the metadata, an output means for presenting the most similar file to the user, an emotion recognition means for analyzing the user's facial expression and tone of voice to recognize their emotion, and an emotion response means for adjusting the interface of the interaction means and the output means based on the user's emotion, thereby making it possible to provide an interface and adjust search results in accordance with the user's emotion.

[0463] The "interactive means" refers to a means for interacting with the user to prompt the user to enter input content when the user creates a file or inputs metadata.

[0464] The "storage means" is a means for storing the filenames and corresponding metadata created by the user in a database.

[0465] A "searching means" is a means for searching a database for matching files based on a search query entered by a user.

[0466] The "similarity calculation means" is a means for calculating the similarity between a search query and metadata.

[0467] The "output means" is a means for presenting the most similar file to the user.

[0468] The "emotion recognition means" is a means for analyzing the user's facial expressions and tone of voice to recognize the user's emotions.

[0469] The "emotion response means" is a means for adjusting the interface of the dialogue means and the output means based on the user's emotions.

[0470] This system recognizes a user's emotions and provides appropriate interfaces and search results based on those emotions. This system consists of smart glasses with an emotion engine and a file management and search system using a cloud database.

[0471] 1. System Configuration

[0472] This system consists of the following main components:

[0473] Smart glasses: Equipped with emotion recognition means that analyze the user's facial expressions and tone of voice in real time.

[0474] Cloud Database: Use a cloud service such as Firebase to store file names and metadata.

[0475] Machine learning algorithm: A machine learning library such as TENSORFLOW (registered trademark) is used to calculate the similarity between the search query and metadata.

[0476] 2. Data Creation and Management

[0477] When a user creates a new file, the smart glasses act as a "conversational tool." Specifically, they recognize the user's current emotion and display appropriate prompts accordingly. For example, if the user is feeling stressed, they will be prompted with a gentler tone. The generated file name and metadata are then stored in a cloud database.

[0478] 3. Searching for data

[0479] When a user enters a search query, the smart glasses and a cloud server work together to retrieve data. The cloud server calculates the similarity between the search query and all metadata in the database. During this process, the server analyzes the user's sentiment in real time and prioritizes highly relevant files to quickly display search results if the user is in a hurry.

[0480] 4. Editing Metadata

[0481] If the user wishes to edit or modify the metadata, the smart glasses act as an editing interface, again adapting to the user's emotional state. The new metadata is updated to the cloud database, and the success is confirmed.

[0482] Specific examples

[0483] File Creation Example: When a user creates a "Maintenance Report," the smart glasses prompt them to "Enter a description for this report." If the emotion engine recognizes that the user is tired, a gentle interface is presented to encourage input. Once the user completes the description, the data is saved to a cloud database.

[0484] File search example: When a user searches for "maintenance record," the smart glasses send this query to the cloud server. The server retrieves metadata from the database and calculates similarity. If the emotion engine recognizes that the user is in a hurry, it will prioritize the most relevant files. For example, "maintenance report" is identified and sent back to the smart glasses.

[0485] Metadata Editing Example: When a user changes the metadata of "Maintenance Report" to "Scheduled Maintenance Report", the emotion engine adjusts the editing interface based on the user's emotional state, enters the new metadata, and notifies the cloud database that the update was successful.

[0486] Prompt Sentence Examples

[0487] "Please explain the work log management and data search system for factory robots that uses an emotion engine. In particular, please explain in detail the specific methods and benefits of the work log input and search function based on user emotions."

[0488] The above is the "Mode for Carrying Out the Invention."

[0489] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0490] Step 1:

[0491] emotion recognition

[0492] Description: The device (smart glasses) analyzes image data (facial expressions) and audio data (tone of voice) collected from the user in real time to recognize the user's emotions. For this purpose, an emotion recognition API is used. It receives image data and audio data as input and generates analyzed emotional data as output.

[0493] Specific behavior:

[0494] 1. The device uses the camera and microphone to capture the user's facial and voice data.

[0495] 2. The acquired data is sent to the emotion recognition API, which runs an algorithm to analyze emotions.

[0496] 3. Receive a response from the emotion recognition API containing the user's emotional state (e.g., stress, joy, fatigue, etc.).

[0497] Step 2:

[0498] File creation and metadata entry

[0499] Description: The terminal provides a dialogue interface for the user to input a file name and corresponding metadata when creating a file. The tone of the interface is adjusted based on the result of emotion recognition. It receives emotion data and input to the user interface (file name, metadata) as input, and generates the input file name and metadata as output.

[0500] Specific behavior:

[0501] 1. The terminal will prompt you to "Enter a description for this file."

[0502] 2. The user enters a file name and metadata, for example, "End of Year Project Report."

[0503] 3. Collect input data from the dialogue interface and adjust tone based on emotion to encourage input.

[0504] Step 3:

[0505] Data storage

[0506] Description: The device sends the collected file name and metadata to the server, which then stores them in a cloud database (e.g., Firebase). It receives the file name and metadata as input and generates the database storage result (success or failure) as output.

[0507] Specific behavior:

[0508] 1. The device packages the filename and metadata and sends it to the server.

[0509] 2. The server connects to a cloud database and stores the file name and metadata.

[0510] 3. If the save is successful, the server notifies the device of the result.

[0511] Step 4:

[0512] Data Search

[0513] Description: When a user enters a search query, the device sends it to the server. The server retrieves metadata from a cloud database, calculates the similarity with the search query, and returns the best search results based on emotion recognition. It takes the search query and emotion data as input and generates search results as output.

[0514] Specific behavior:

[0515] 1. A user enters a search query into their device, for example, "year-end report."

[0516] 2. The device sends the search query to the server.

[0517] 3. The server queries the cloud database to retrieve all metadata matches.

[0518] 4. Using a similarity calculation means, calculate the similarity between the search query and the metadata.

[0519] 5. Based on the results of emotion recognition, the most relevant results are selected and sent back to the device as search results.

[0520] Step 5:

[0521] Metadata Editing

[0522] Description: When a user wants to edit or modify metadata, the terminal provides an editing interface. It receives new metadata as input and generates updated results as output. The interface is adjusted based on emotions to allow the user to easily edit.

[0523] Specific behavior:

[0524] 1. The user wishes to modify the metadata of an existing file on the device.

[0525] 2. The device recognizes emotions and adjusts the interface according to the user's emotions.

[0526] 3. The user enters new metadata, for example, "Project plan for next year."

[0527] 4. Send the new metadata to the server, which updates the existing record in the cloud database.

[0528] 5. The server notifies the user that the update was successful, and the device notifies the user of the result.

[0529] The above are the specific processing steps of the system that realizes the application example.

[0530] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0531] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0532] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0533] [Second embodiment]

[0534] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0535] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0536] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0537] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0538] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0539] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0540] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0541] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0542] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0543] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0544] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0545] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0546] The present invention is a system that allows users to interactively input, store, and search metadata to facilitate file management and retrieval, thereby saving users time and enabling them to efficiently find the files they need.

[0547] 1. Creating a file and entering metadata

[0548] When a user creates a new file, they decide on a file name, for example "Project Report.docx."

[0549] The terminal will prompt you to "Enter a description for this file."

[0550] The user enters metadata for a file such as "end of year project report."

[0551] 2. Data storage

[0552] The device sends the file name and metadata to the server.

[0553] The server stores the received data in a database: it opens a database connection and executes a SQL statement to insert the file name, metadata, and creation date into the database.

[0554] 3. Search for files

[0555] A user enters a search query to find a specific file, for example, "end of year report."

[0556] The terminal sends this search query to the server.

[0557] The server opens a database connection and executes a SQL statement to retrieve metadata for all files.

[0558] 4. Similarity calculation

[0559] The server calculates the similarity between the retrieved metadata and the user's search query, using a machine learning algorithm to generate a highly accurate similarity score.

[0560] The server identifies the most relevant files based on the calculated similarity scores.

[0561] 5. Presentation of search results

[0562] The server returns the most relevant filename to the terminal.

[0563] The device will display "Best file is: <filename>" to the user.

[0564] 6. Editing Metadata

[0565] If the user wishes, they can edit or modify the metadata that has already been saved.

[0566] The terminal provides an editing interface and receives new metadata from the user and sends it to the server.

[0567] The server updates the existing record in the database.

[0568] Specific examples

[0569] File creation example: When a user creates a new file "Project Plan.docx," the terminal prompts the user to "Enter a description for this file." The user enters "Project plan for next year," and the terminal sends this information to the server. The server stores this information in a database.

[0570] File search example: A user searches for "plan for next year" by entering search keywords into the device. The device sends this query to the server, which retrieves all metadata from the database and calculates similarity. The server identifies the most relevant file, "Project Plan.docx," and returns it to the device. The device displays to the user, "The best file is: Project Plan.docx."

[0571] Metadata editing example: If a user wants to change the metadata of "Project Plan.docx" to "Project Plan for Next Year", the terminal provides an editing interface. The user inputs new metadata and the terminal sends it to the server. The server updates the existing record in the database.

[0572] As described above, this system provides users with a means to efficiently manage and search for files, and in particular enables them to quickly find the files they need through metadata collection and similarity calculations.

[0573] The processing flow will be explained below.

[0574] Program processing flow (when creating a file)

[0575] Step 1:

[0576] When a user creates a new file, they decide on a file name, for example "Project Report.docx".

[0577] Step 2:

[0578] The terminal prompts the user to "Please enter a description for this file."

[0579] Step 3:

[0580] The user enters metadata about the file, for example "end of year project report."

[0581] Step 4:

[0582] The terminal transmits the file name and metadata input by the user to the server.

[0583] Step 5:

[0584] The server opens a database connection in preparation for storing the received filename and metadata in the database.

[0585] Step 6:

[0586] The server executes the SQL statement and inserts the file name, metadata, and creation date and time into the database.

[0587] Step 7:

[0588] The server confirms that the save was successful and sends that information to the device.

[0589] Step 8:

[0590] The terminal notifies the user that the file has been successfully saved.

[0591] Program processing flow (when searching for files)

[0592] Step 1:

[0593] A user enters a search query, for example, "year-end report."

[0594] Step 2:

[0595] The terminal sends a search query from the user to the server.

[0596] Step 3:

[0597] The server opens a database connection and executes a SQL statement to retrieve metadata for all files.

[0598] Step 4:

[0599] The server uses a machine learning algorithm to calculate the similarity between the metadata it has acquired and the user's search query.

[0600] Step 5:

[0601] The server calculates the similarity scores and identifies the most similar files.

[0602] Step 6:

[0603] The server returns the most relevant filename to the terminal.

[0604] Step 7:

[0605] The device will tell the user, "The best file is: <filename>."

[0606] Program processing flow (when editing metadata)

[0607] Step 1:

[0608] The user selects the file for which they wish to edit or modify the metadata.

[0609] Step 2:

[0610] The device displays an editing interface with the existing metadata.

[0611] Step 3:

[0612] The user enters new metadata, for example, changing it to "Project plan for next year."

[0613] Step 4:

[0614] The device sends the new metadata to the server.

[0615] Step 5:

[0616] The server opens a database connection and executes SQL statements to update existing metadata.

[0617] Step 6:

[0618] The server confirms that the update was successful and sends that information to the device.

[0619] Step 7:

[0620] The terminal notifies the user that the metadata update was successful.

[0621] Example 1

[0622] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0623] In modern electronic file management systems, the large number of files stored makes it difficult for users to quickly search for and access the files they need. In particular, if file metadata (e.g., descriptions and tags) is not properly managed, the accuracy of the search function will be significantly reduced. Furthermore, manually updating metadata is a cumbersome task, preventing users from working efficiently. To solve these problems, a system that enables efficient file search and management is needed.

[0624] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0625] In this invention, the server includes an interactive means for inputting file names and corresponding metadata when a user creates a file, a storage means for storing the file names and metadata in a database, a search means for searching the database for matching files when a user inputs a search query, a similarity calculation means for calculating the similarity between the search query and the metadata, an output means for presenting the most similar file to the user, and an interactive means for editing or correcting the metadata input by the user. This allows the user to efficiently input, edit, and search file metadata, thereby enabling the user to quickly find the file they need.

[0626] A "user" is an individual or organization that uses the system to create, search, and edit files.

[0627] A "file name" is an identifying character string that is assigned to each file created by a user.

[0628] "Metadata" is additional information entered by the user to describe the contents of a file and is used to improve search accuracy.

[0629] "Interaction means" refers to an interface that allows a user to interactively input data and perform operations with the system.

[0630] "Storage means" is a function for storing file names and metadata in a database.

[0631] A "database" is a system that stores file names and metadata in an organized manner and manages them so that they can be searched and edited.

[0632] A "search query" is a keyword or phrase that a user enters to locate a particular file.

[0633] The "search means" is a function that searches for matching files in the database based on a user's search query.

[0634] The "similarity calculation means" is a function that calculates the relevance between a user's search query and metadata in the database.

[0635] "Machine learning algorithms" are artificial intelligence techniques used to calculate similarity and automatically classify data.

[0636] "Output means" is a function that visually presents search results and other information to the user.

[0637] "Communication means" refers to a communication function via the Internet or a local network for sending and receiving user input data and search results from a server.

[0638] This invention relates to a system that allows users to efficiently manage, search, and edit files. This system shares file names and metadata between users, terminals, and servers, and realizes highly accurate file searches.

[0639] Hardware and software used

[0640] This system consists of a terminal (e.g., a PC or smartphone) that accepts user operations, a server for storing and processing data, and a database. It also uses machine learning algorithms (e.g., TF-IDF or Word2Vec) to calculate the similarity of metadata, and a communication method (e.g., HTTP protocol) to exchange data between the server and the terminal.

[0641] Creating a file and entering metadata

[0642] When a user creates a new file, they input the file name into the terminal. At this time, the terminal displays a prompt saying "Please enter a description for this file" and prompts the user to input metadata. For example, the user may input metadata such as "Year-end project report."

[0643] Data storage

[0644] The terminal sends the file name and metadata to the server. The server receives this data and stores it in a database. Specifically, the server uses SQL statements to insert the file name, metadata, and creation date and time into the database.

[0645] Searching for files

[0646] When a user wants to find a specific file, they enter a search query into their device, for example, searching for "year-end report." The device then sends this query to the server, which retrieves all the metadata from the database and calculates the similarity to the search query. This calculation is done using machine learning algorithms such as TF-IDF and Word2Vec.

[0647] Presenting search results

[0648] Based on the calculated similarity score, the server identifies the most relevant filenames and returns them to the device, which then displays them to the user as something like "The best file is: Project Report.docx."

[0649] Editing Metadata

[0650] If the user wants to edit or modify the already saved metadata, the terminal provides an editing interface and receives new metadata from the user, which the terminal sends to the server, which then updates the existing record in the database.

[0651] Specific examples

[0652] File creation example: A user creates a new file "Project Plan.docx" and the terminal prompts, "Please enter a description for this file." If the user enters "Project plan for next year," the terminal sends this information to the server, which stores it in a database.

[0653] File search example: If a user searches for "Plan for next year", they enter the search keyword into their device. The device sends this query to the server, which retrieves all the metadata in the database. It then calculates the similarity and identifies the most relevant file, "Project Plan.docx", and returns it to the device. The device displays "The best file is: Project Plan.docx".

[0654] Metadata editing example: If a user wants to change the metadata of "Project Plan.docx" to "Project Plan for Next Year", the terminal provides an editing interface. The user inputs new metadata and the terminal sends it to the server. The server updates the existing record in the database.

[0655] This system allows users to efficiently enter, edit, and search file metadata, enabling them to quickly find the files they need.

[0656] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0657] Step 1:

[0658] When a user creates a new file, they enter a filename into the terminal, for example "Project Report.docx". The input at this point is the "filename", the string the user types into the terminal. The output is the prompt that is displayed on the terminal.

[0659] Step 2:

[0660] The terminal displays a prompt saying "Please enter a description for this file" and prompts the user to enter metadata. The input is "metadata," and the user might enter, for example, "Year-end project report." The output is metadata stored in the terminal's temporary memory.

[0661] Step 3:

[0662] The device sends the filename and metadata to the server using an HTTP POST request. The input is the filename and metadata, and the output is the data sent to the server.

[0663] Step 4:

[0664] The server stores the received data in a database. First, the server opens a database connection. The input is the file name and metadata sent from the terminal, and the output is the record to be stored in the database. Specifically, it executes the SQL statement "INSERT INTO files (file_name, metadata, creation_date) VALUES ('Project report.docx', 'Year-end project report', '2023-10-23')".

[0665] Step 5:

[0666] A user enters a search query to find a specific file, for example, "year-end report." The input is the "search query," which the device sends to the server. The output is the search query sent to the server.

[0667] Step 6:

[0668] The server opens a database connection and retrieves all metadata by executing a SQL statement such as "SELECT file_name, metadata FROM files". The input is the query to the database and the output is a list of the retrieved metadata.

[0669] Step 7:

[0670] The server calculates the similarity between the retrieved metadata and the user's search query, using, for example, TF-IDF (Term Frequency-Inverse Document Frequency). The input is the search query and a list of metadata, and the output is a similarity score for each file.

[0671] Step 8:

[0672] The server identifies the most relevant files based on the calculated similarity scores: the input is the similarity score, and the output is the filename with the highest score.

[0673] Step 9:

[0674] The server returns the most relevant filename to the terminal. The input is the identified filename, and the output is the filename returned to the terminal. The returned data is in JSON format.

[0675] Step 10:

[0676] The terminal will display to the user, "The best file is: Project Report.docx." The input is the file name returned by the server, and the output is the search results presented to the user.

[0677] Step 11:

[0678] When a user edits or modifies already saved metadata, the terminal provides an editing interface and receives new metadata from the user. The input is the new metadata edited by the user, which the terminal sends to the server. The output is the new metadata sent to the server.

[0679] Step 12:

[0680] The server updates an existing record in the database. The input is the new metadata, specifically by executing the SQL statement "UPDATE files SET metadata = 'newmetadata' WHERE file_name = 'projectreport.docx'". The output is the updated database record.

[0681] (Application example 1)

[0682] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0683] In factories and other workplaces, managing and quickly searching a large number of documents is essential, and effective management methods are needed. However, current document management systems have the drawback of being time-consuming to operate, as metadata input and editing is cumbersome and search accuracy is insufficient. Factories, in particular, need systems that can efficiently input metadata using voice input and touch interfaces and quickly search for related documents.

[0684] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0685] In this invention, the server includes an interactive means for inputting file names and corresponding metadata when a user creates a file, a storage means for storing the file names and metadata in a database, a search means for searching the database for matching files when a user inputs a search query, a similarity calculation means for calculating the similarity between the search query and the metadata, an output means for presenting the most similar file to the user, and a means for inputting the user-entered metadata via voice or a touch interface. This allows document metadata to be efficiently entered and managed, improving search accuracy and enabling desired documents to be found quickly.

[0686] "User" means a person or end user who operates the system and inputs, searches, and edits data.

[0687] A "file name" is a text-based name set by the user to identify an individual file.

[0688] "Metadata" is data that represents additional information associated with a file, detailing the contents and characteristics of the file.

[0689] An "interaction means" is an interface used by a user to input and edit data, including in particular voice input and touch interfaces.

[0690] A "storage mechanism" is a mechanism for recording and maintaining file names and metadata in a database.

[0691] The "search means" is a function for searching for related files from the database based on a query entered by the user.

[0692] The "similarity calculation means" is an algorithm for calculating the similarity between a user's search query and metadata in the database.

[0693] The "output means" is a mechanism for providing the user with information on the most relevant file based on the calculated similarity.

[0694] The present invention relates to a system for efficiently managing and quickly searching for a large number of documents (such as blueprints, maintenance procedures, and operation manuals) used in a factory. Specific embodiments of the system will be described in detail below.

[0695] The system includes a means for users to interactively enter, store, and retrieve metadata.

[0696] Hardware and software used

[0697] Hardware: Robots deployed in factories (with voice recognition and touchscreen displays)

[0698] Software: Python, SQLite (for database management), Scikit-learn (machine learning library)

[0699] Details of data processing and calculation

[0700] 1. Database connection and metadata storage

[0701] The server connects to an SQLite database and creates a table to store document information. When a user creates a new document, the robot prompts the user, "Please enter a description for this document." The user provides metadata via voice input or touch panel input, and the robot sends the metadata to the server and stores it in the database.

[0702] 2. Metadata search and similarity calculation

[0703] When a user searches for a specific document, they input a search query into the robot (via voice or touch panel). The server sends this search query to the database and retrieves the stored metadata. It then uses Scikit-learn's TfidfVectorizer and cosine_similarity function to calculate the similarity between the search query and the stored metadata.

[0704] 3. Presentation of search results

[0705] The server identifies the most relevant document based on the calculated similarity and sends that information back to the robot, which displays to the user, "The best document is: <document name>."

[0706] 4. Editing Metadata

[0707] If a user wants to edit the metadata of an existing document, the robot provides an editing interface, and when the user enters new metadata, it sends it to the server, updating the existing record.

[0708] Specific examples

[0709] For example, if a user adds a new document called "Factory Machine Maintenance Procedures.pdf", the following happens:

[0710] 1. The robot displays the prompt, "Please enter a description of this document."

[0711] 2. The user speaks "Routine maintenance procedures."

[0712] 3. The robot sends this to the server and stores it in the database.

[0713] If a user searches for "maintenance procedures," the experience progresses as follows:

[0714] 1. A user enters the search query "maintenance procedures" into the robot.

[0715] 2. The server receives the query, retrieves the metadata from the database, and performs the similarity calculation.

[0716] 3. The server sends the most relevant document back to the robot, which then displays, "The best document is: Factory Machine Maintenance Procedures.pdf."

[0717] Prompt Sentence Examples

[0718] For example, it can be used as follows when executing a Python program:

[0719] python

[0720] Documentation

[0721] create_document("Factory Machine Maintenance Procedure.pdf", "Periodic Maintenance Procedure")

[0722] Document Search

[0723] print(search_documents("Maintenance Procedures"))

[0724] Metadata Editing

[0725] edit_metadata("Factory Machine Maintenance Procedure.pdf", "Monthly Scheduled Maintenance Procedure")

[0726] This allows the system to efficiently manage and quickly search a large number of documents within a factory.

[0727] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0728] Step 1:

[0729] When a user creates a new file, the robot (terminal) displays a prompt saying, "Please enter a description of this document." The user provides metadata via voice input or touch panel.

[0730] Input: User-entered file name and metadata (e.g., "Factory Machine Maintenance Procedures.pdf", "Routine Maintenance Procedures")

[0731] Output: Send collected filenames and metadata to the server

[0732] Step 2:

[0733] The server receives the file name and metadata sent from the device and stores them in an SQLite database by opening a database connection and inserting the file name, metadata, and creation date and time into a table.

[0734] Input: File name and metadata sent from the device (e.g., "Factory Machine Maintenance Procedures.pdf", "Routine Maintenance Procedures")

[0735] Output: New document information saved in the database

[0736] Step 3:

[0737] When a user enters a search query, the robot (terminal) receives the query from the user and sends it to the server.

[0738] Input: The search query entered by the user (e.g., "maintenance procedures")

[0739] Output: Sends the search query to the server

[0740] Step 4:

[0741] The server retrieves all metadata from the database and performs a similarity calculation to find metadata that matches the user's search query.

[0742] Input: User search query and metadata retrieved from the database

[0743] Data processing: Generate TF-IDF vectors for search queries and metadata

[0744] Data arithmetic: Calculate cosine similarity and identify the most relevant metadata

[0745] Output: Identify the most relevant files based on a similarity calculation

[0746] Step 5:

[0747] The server returns the most relevant filenames based on the calculated similarity to the robot (terminal).

[0748] Input: The most related filenames based on the similarity calculation

[0749] Output: Sends the most relevant filename to the terminal

[0750] Step 6:

[0751] The robot (terminal) displays the search results to the user, specifically displaying "The best document is: <Document name>."

[0752] Input: The file name returned by the server

[0753] Output: Displaying search results to the user

[0754] Step 7:

[0755] When a user edits or modifies already saved metadata, the robot (terminal) provides an editing interface, receives new metadata from the user, and sends it to the server.

[0756] Input: New metadata entered by the user (e.g., "Monthly scheduled maintenance procedures")

[0757] Output: Send the new metadata to the server

[0758] Step 8:

[0759] The server receives the new metadata sent from the device and updates the existing record in the SQLite database, specifically by replacing the metadata for the corresponding file name with the new one.

[0760] Input: New metadata sent from the device

[0761] Output: Metadata in the database is updated

[0762] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0763] The present invention is a system that uses an emotion engine to recognize a user's emotions when creating, managing, and searching for files, and provides an appropriate interface and search results according to those emotions. This system promotes file metadata input and adjusts search results based on the user's emotions, thereby achieving a better user experience.

[0764] 1. Emotion engine integration

[0765] The device is equipped with an emotion engine that recognizes emotions in real time from the user's facial expressions, tone of voice, and input method.

[0766] 2. Creating a file and entering metadata

[0767] When a user creates a new file, they set the file name, for example, "Project Report.docx."

[0768] The device will prompt you to "Enter a description for this file" and the emotion engine will analyze the user's current emotions.

[0769] If the emotion engine recognizes that the user is feeling stressed, the device will provide a relaxing interface and encourage input.

[0770] A user enters metadata such as "year-end project report."

[0771] 3. Data storage

[0772] The device sends the file name and metadata to the server.

[0773] To store the received data in a database, the server opens a database connection and executes an SQL statement to insert the file name, metadata, and creation date and time into the database.

[0774] 4. Search for files

[0775] A user enters a search query, for example, "year-end report."

[0776] The terminal sends a search query from the user to the server.

[0777] The server opens a database connection and executes a SQL statement to retrieve metadata for all files.

[0778] The server uses a machine learning algorithm to calculate the similarity between the acquired metadata and the user's search query.

[0779] The emotion engine analyzes the user's emotions, and if the user is in a hurry, for example, it prioritizes the information that needs to be returned most quickly and identifies the most relevant files.

[0780] The server returns the most relevant filename to the terminal.

[0781] The device will display "Best file is: <filename>" to the user.

[0782] 5. Editing Metadata

[0783] If the user wishes to edit or modify the metadata, the terminal provides an editing interface.

[0784] The user inputs new metadata, for example, changing it to "Next year's project plan."

[0785] The terminal sends the new metadata to the server.

[0786] The server opens a database connection and executes SQL statements to update the existing metadata.

[0787] The server confirms that the update was successful and sends it to the terminal, and the terminal notifies the user that the metadata update was successful.

[0788] Specific examples

[0789] File creation example: When a user creates a file called "Meeting minutes.docx," the device prompts the user, "Please enter a description for this file." If the emotion engine recognizes that the user is tired, it presents a friendly interface to assist input. The user enters "Monthly meeting minutes," and the device sends this information to the server, which stores it in a database.

[0790] File search example: When a user searches for "monthly meeting," the device sends this query to the server. The server retrieves metadata from the database and calculates similarity. If the emotion engine recognizes that the user is in a hurry, it prioritizes the most relevant files. The server identifies "Meeting Minutes.docx" and sends it back to the device. The device displays, "The best file is: Meeting Minutes.docx."

[0791] Metadata editing example: If a user wants to change the metadata of "Meeting Minutes.docx" to "Minutes of Quarterly Meeting", an editing interface is provided. The user enters new metadata and the terminal sends it to the server. The server updates the existing record in the database and notifies the terminal that the update was successful. The terminal notifies the user that the update was successful.

[0792] As described above, by integrating the emotion engine, we have created a system that can provide a flexible interface that responds to the user's emotional state and highly accurate search results.

[0793] The processing flow will be explained below.

[0794] Program processing flow (when creating a file)

[0795] Step 1:

[0796] The user decides to create a new file and enters a file name, for example "Project Report.docx."

[0797] Step 2:

[0798] The terminal receives the filename and displays the prompt "Please enter a description for this file."

[0799] Step 3:

[0800] The emotion engine built into the device analyzes the user's facial expressions and tone of voice to recognize emotions in real time.

[0801] Step 4:

[0802] The device provides an interface based on the user's emotions, for example, if the user is feeling stressed, it uses a relaxing interface.

[0803] Step 5:

[0804] The user enters a description for the file, for example, "End of Year Project Report."

[0805] Step 6:

[0806] The device sends the entered file name and metadata to the server.

[0807] Step 7:

[0808] The server opens a database connection and executes an SQL statement to insert the file name, metadata, and creation date into the database.

[0809] Step 8:

[0810] The server confirms that the save was successful and sends that information to the device.

[0811] Step 9:

[0812] The terminal notifies the user that the file has been successfully saved.

[0813] Program processing flow (when searching for files)

[0814] Step 1:

[0815] A user enters a search query to find a specific file, for example, "end of year report."

[0816] Step 2:

[0817] The terminal receives the search query and sends it to the server.

[0818] Step 3:

[0819] The server opens a database connection and executes a SQL statement to retrieve metadata for all files.

[0820] Step 4:

[0821] Using the metadata acquired by the server, a machine learning algorithm is used to calculate the similarity to the user's search query.

[0822] Step 5:

[0823] The emotion engine built into the device analyzes the user's current emotions and prioritizes displaying results quickly if, for example, the user is in a hurry.

[0824] Step 6:

[0825] The server calculates the similarity scores and identifies the most similar files.

[0826] Step 7:

[0827] The server sends the specified file name to the terminal.

[0828] Step 8:

[0829] The device displays "The best file is: <filename>" to the user.

[0830] Program processing flow (when editing metadata)

[0831] Step 1:

[0832] If the user wishes to edit or modify the metadata for an existing file, the user selects the file.

[0833] Step 2:

[0834] The device displays the existing metadata for the file and provides an editing interface.

[0835] Step 3:

[0836] The user enters new metadata, for example, changing it to "Project plan for next year."

[0837] Step 4:

[0838] The device sends the new metadata to the server.

[0839] Step 5:

[0840] The server opens a database connection and executes SQL statements to update the existing metadata.

[0841] Step 6:

[0842] The server confirms that the update was successful and sends that information to the device.

[0843] Step 7:

[0844] The terminal notifies the user that the metadata update was successful.

[0845] Emotion Engine Processing Flow

[0846] Step 1:

[0847] When a user operates the system, the device's built-in camera and microphone capture the user's facial expressions and tone of voice.

[0848] Step 2:

[0849] The device's emotion engine analyzes the captured data in real time to recognize the user's emotional state.

[0850] Step 3:

[0851] The device will provide an appropriate interface based on the recognized emotion, for example, using relaxing colors and fonts if the user is tired.

[0852] Step 4:

[0853] The device transmits the user's emotional state to the server, which is then taken into account when searching for files and entering metadata.

[0854] Step 5:

[0855] The server adjusts the parameters of the search algorithm based on the emotional data and returns the optimal results according to the user's situation.

[0856] As described above, by integrating an emotion engine, the system of the present invention can provide a flexible interface that responds to the user's emotions and highly accurate search results.

[0857] Example 2

[0858] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0859] The present invention aims to provide a better user experience by appropriately recognizing a user's emotions when creating, managing, and searching for files, and providing an interface and search results that reflect those emotions. Conventional systems do not respond to user emotions, which can cause users to feel stressed when creating or searching for files. Another problem is that it can be difficult for users to quickly find the right file when they are in a hurry.

[0860] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0861] In this invention, the server includes emotion recognition means for recognizing a user's emotion in real time, adjustment means for providing an interface according to the user's emotion, and similarity calculation means for calculating the similarity between the search query and metadata. This allows the interface and search results to be adjusted based on the user's emotion, enabling the user to quickly find or create the files they need without feeling stressed.

[0862] "User" means a person who uses the system to create, manage, and retrieve files.

[0863] A "file" is a piece of digital data, such as a document or image, that users create, store, and search.

[0864] "Metadata" is information associated with a file, including additional information such as the file name, description, and tags.

[0865] An "interaction means" is a means that provides an interface for a user to interact with the system and input information.

[0866] "Storage" refers to the mechanism by which filenames and metadata are stored in a database.

[0867] The "search means" is a function for searching files in the database and providing the user with results appropriate for the file.

[0868] "Similarity calculation means" refers to a mechanism for calculating the similarity between a user's search query and a file's metadata.

[0869] The "output means" is a means for presenting search results to the user.

[0870] "Emotion recognition means" refers to a system that recognizes emotions in real time from a user's facial expressions, tone of voice, input method, etc.

[0871] The "adjustment means" refers to a function that adjusts the interface and search results according to the user's emotions detected by the emotion recognition means.

[0872] A "machine learning algorithm" refers to an algorithm that analyzes data and learns patterns and rules to calculate similarity and optimize searches.

[0873] The present invention is a system that uses an emotion engine to recognize a user's emotions when creating, managing, and searching for files, and provides an appropriate interface and search results based on those emotions. This system promotes file metadata entry and adjusts search results based on the user's emotions, thereby achieving a better user experience.

[0874] Emotion engine integration

[0875] The device is equipped with an emotion engine that recognizes emotions in real time from the user's facial expressions, tone of voice, input method, etc. The emotion engine uses, for example, Microsoft's Azure Face API for facial recognition technology and Google Cloud Speech-to-Text for voice recognition technology.

[0876] Creating a file and entering metadata

[0877] When a user creates a new file, they set the file name, for example, "Project Report.docx."

[0878] The device will prompt you to "Enter a description for this file" and the emotion engine will analyze the user's current emotions.

[0879] If the emotion engine detects that the user is feeling stressed, the device will provide a relaxing interface and encourage input, such as changing the background color or playing relaxing music.

[0880] A user enters metadata such as "year-end project report."

[0881] Data storage

[0882] The device sends the file name and metadata to the server.

[0883] The server opens a database connection, executes a SQL statement that saves the file name, metadata, and creation date and time in the database, and saves the data.

[0884] Searching for files

[0885] A user enters a search query, for example, "year-end report."

[0886] The terminal sends a search query to the server.

[0887] The server opens a database connection and executes a SQL statement to retrieve metadata for all files.

[0888] The server uses a machine learning algorithm to calculate the similarity between the acquired metadata and the user's search query.

[0889] The emotion engine analyzes the user's emotions, and if the user is in a hurry, for example, it prioritizes the information that needs to be returned most quickly and identifies the most relevant files.

[0890] The server returns the most relevant filename to the terminal.

[0891] The device will display to the user "The best file is: Meeting Minutes.docx."

[0892] Editing Metadata

[0893] If the user wishes to edit or modify the metadata, the terminal provides an editing interface.

[0894] The user inputs new metadata, for example, changing it to "Next year's project plan."

[0895] The terminal sends the new metadata to the server.

[0896] The server executes a SQL statement to update an existing record in the database.

[0897] The server confirms that the update was successful and notifies the terminal.

[0898] The terminal notifies the user of the success of the update.

[0899] Specific examples

[0900] File creation example

[0901] When a user creates a file called "Meeting Minutes.docx," the device prompts the user, "Please enter a description for this file." If the emotion engine detects that the user is tired, it presents a friendly interface to assist input. The user types "Monthly Meeting Minutes," and the device sends this information to the server, which stores it in a database.

[0902] File search example

[0903] When a user searches for "monthly meeting," the device sends this query to the server. The server retrieves metadata from the database and calculates similarity. If the emotion engine recognizes that the user is in a hurry, it prioritizes the most relevant files. The server identifies "Meeting Minutes.docx" and sends it back to the device. The device displays, "The best file is: Meeting Minutes.docx."

[0904] Metadata editing example

[0905] If a user wants to change the metadata of "Meeting Minutes.docx" to "Minutes of Quarterly Meeting," an editing interface is provided. The user enters new metadata, and the terminal sends it to the server. The server updates the existing record in the database and notifies the terminal that the update was successful. The terminal notifies the user that the update was successful.

[0906] As described above, by integrating the emotion engine, we have created a system that provides a flexible interface and highly accurate search results that respond to the user's emotional state.

[0907] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0908] Step 1: Integrating the Emotion Engine

[0909] The device uses an emotion engine to recognize the user's facial expressions, tone of voice, and input method in real time. The emotion engine uses, for example, a general face recognition API for facial recognition technology or a voice recognition API for voice recognition technology. Specifically, it acquires data from the camera and microphone and inputs it into an emotion recognition model. The emotion model analyzes the data and outputs the user's emotional state (e.g., stressed, relaxed, etc.).

[0910] Input: Real-time data from camera and microphone

[0911] Data processing: Emotion analysis using face and voice recognition APIs

[0912] Output: User's emotional state

[0913] Step 2: Enter a file name

[0914] The terminal prompts the user to enter a file name when creating a new file, and the user enters the file name and sends it to the terminal (e.g., "Project Report.docx").

[0915] Input: The file name entered by the user

[0916] Output: Send filename to terminal

[0917] Step 3: Prompt for Metadata

[0918] The device displays a prompt saying, "Please enter a description for this file," and the emotion engine analyzes the user's current emotion. If the emotion engine determines that the user is feeling stressed, the device provides a relaxing interface (e.g., changing the background color, playing relaxing music) to encourage input.

[0919] Input: prompt after entering user's emotional state and file name

[0920] Data manipulation: adjusting the interface based on emotions

[0921] Output: Display interface and prompts to the user

[0922] Step 4: Entering Metadata

[0923] The user inputs metadata (e.g., "end of year project report"), and the device receives this input and begins the process of saving the data.

[0924] Input: User-entered metadata

[0925] Output: Sending metadata to the device

[0926] Step 5: Sending data

[0927] The device sends the entered file name and metadata to the server, which prepares to save the data.

[0928] Input: Filename and metadata

[0929] Output: Send data to the server

[0930] Step 6: Save your data

[0931] The server opens a database connection, executes a SQL statement to store the filename, metadata, and creation date and time in the database, and then saves the data. For example, it executes the SQL statement "INSERT INTO files (filename, metadata, created_at) VALUES ('Project report.docx', 'End of year project report', NOW())".

[0932] Input: Filename and metadata

[0933] Data processing: Generate SQL statements and save them to the database

[0934] Output: Confirmation saved in the database

[0935] Step 7: Enter a search query

[0936] A user enters a search query into a terminal (e.g., "year-end report"), and the terminal sends the search query to the server.

[0937] Input: The search query entered by the user

[0938] Output: Sending a search query to the server

[0939] Step 8: Retrieving Metadata from the Database

[0940] The server opens a database connection and executes a SQL statement to retrieve all file metadata, for example the SQL statement "SELECT filename, metadata FROM files" to retrieve all metadata.

[0941] Input: Search query

[0942] Data processing: SQL statement generation, metadata acquisition

[0943] Output: Retrieved metadata

[0944] Step 9: Calculate similarity

[0945] The server runs machine learning algorithms to calculate the similarity between the retrieved metadata and the user's search query. For example, it uses natural language processing models to evaluate the similarity between the search query and the metadata. An emotion engine analyzes the user's emotions and prioritizes the most relevant files if the user is in a hurry.

[0946] Input: Search query and retrieved metadata

[0947] Data processing: Similarity calculation using machine learning algorithms

[0948] Output: Identifying the most relevant files

[0949] Step 10: Output search results

[0950] The server returns the most relevant filename to the terminal, which displays the message "The best file is: <filename>" to the user.

[0951] Input: A specified file name

[0952] Output: Displayed to user as search result

[0953] Step 11: Editing Metadata

[0954] If the user wants to edit or modify the metadata, the terminal provides an editing interface. The user inputs new metadata (e.g., "Project plan for next year") and the terminal transmits the new metadata to the server.

[0955] Input: New metadata entered by the user

[0956] Output: Sending new metadata to the server

[0957] Step 12: Update the Metadata

[0958] The server executes SQL statements to update existing records in the database, for example, the SQL statement "UPDATE files SET metadata = 'Next Year's Project Plan' WHERE filename = 'Project Report.docx'".

[0959] Input: New Metadata

[0960] Data processing: SQL statement generation, database update

[0961] Output: Confirmation of successful database update

[0962] Step 13: Notification of successful update

[0963] The server confirms that the update was successful and notifies the terminal, which then notifies the user of the success of the update.

[0964] Input: Confirmation of successful database update

[0965] Output: Notify user that update was successful

[0966] (Application example 2)

[0967] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0968] In conventional file creation, management, and search systems, it was difficult to provide an appropriate interface or search results when the user was in an emotional state, such as when they were tired or stressed. As a result, the user's work efficiency decreased and it could even lead to incorrect file operations. Therefore, the purpose of this invention is to solve these problems and provide a system that provides a flexible interface and highly accurate search results that respond to the user's emotions.

[0969] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0970] In this invention, the server includes an interaction means for inputting a file name and corresponding metadata when a user creates a file, a storage means for storing the file name and metadata in a database, a search means for searching the database for matching files when a user inputs a search query, a similarity calculation means for calculating a similarity between the search query and the metadata, an output means for presenting the most similar file to the user, an emotion recognition means for analyzing the user's facial expression and tone of voice to recognize their emotion, and an emotion response means for adjusting the interface of the interaction means and the output means based on the user's emotion, thereby making it possible to provide an interface and adjust search results in accordance with the user's emotion.

[0971] The "interactive means" refers to a means for interacting with the user to prompt the user to enter input content when the user creates a file or inputs metadata.

[0972] The "storage means" is a means for storing the filenames and corresponding metadata created by the user in a database.

[0973] A "searching means" is a means for searching a database for matching files based on a search query entered by a user.

[0974] The "similarity calculation means" is a means for calculating the similarity between a search query and metadata.

[0975] The "output means" is a means for presenting the most similar file to the user.

[0976] The "emotion recognition means" is a means for analyzing the user's facial expressions and tone of voice to recognize the user's emotions.

[0977] The "emotion response means" is a means for adjusting the interface of the dialogue means and the output means based on the user's emotions.

[0978] This system recognizes a user's emotions and provides appropriate interfaces and search results based on those emotions. This system consists of smart glasses with an emotion engine and a file management and search system using a cloud database.

[0979] 1. System Configuration

[0980] This system consists of the following main components:

[0981] Smart glasses: Equipped with emotion recognition means that analyze the user's facial expressions and tone of voice in real time.

[0982] Cloud Database: Use a cloud service such as Firebase to store file names and metadata.

[0983] Machine learning algorithms: Use machine learning libraries such as TensorFlow to calculate the similarity between search queries and metadata.

[0984] 2. Data Creation and Management

[0985] When a user creates a new file, the smart glasses act as a "conversational tool." Specifically, they recognize the user's current emotion and display appropriate prompts accordingly. For example, if the user is feeling stressed, they will be prompted with a gentler tone. The generated file name and metadata are then stored in a cloud database.

[0986] 3. Searching for data

[0987] When a user enters a search query, the smart glasses and a cloud server work together to retrieve data. The cloud server calculates the similarity between the search query and all metadata in the database. During this process, the server analyzes the user's sentiment in real time and prioritizes highly relevant files to quickly display search results if the user is in a hurry.

[0988] 4. Editing Metadata

[0989] If the user wishes to edit or modify the metadata, the smart glasses act as an editing interface, again adapting to the user's emotional state. The new metadata is updated to the cloud database, and the success is confirmed.

[0990] Specific examples

[0991] File Creation Example: When a user creates a "Maintenance Report," the smart glasses prompt them to "Enter a description for this report." If the emotion engine recognizes that the user is tired, a gentle interface is presented to encourage input. Once the user completes the description, the data is saved to a cloud database.

[0992] File search example: When a user searches for "maintenance record," the smart glasses send this query to the cloud server. The server retrieves metadata from the database and calculates similarity. If the emotion engine recognizes that the user is in a hurry, it will prioritize the most relevant files. For example, "maintenance report" is identified and sent back to the smart glasses.

[0993] Metadata Editing Example: When a user changes the metadata of "Maintenance Report" to "Scheduled Maintenance Report", the emotion engine adjusts the editing interface based on the user's emotional state, enters the new metadata, and notifies the cloud database that the update was successful.

[0994] Prompt Sentence Examples

[0995] "Please explain the work log management and data search system for factory robots that uses an emotion engine. In particular, please explain in detail the specific methods and benefits of the work log input and search function based on user emotions."

[0996] The above is the "Mode for Carrying Out the Invention."

[0997] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0998] Step 1:

[0999] emotion recognition

[1000] Description: The device (smart glasses) analyzes image data (facial expressions) and audio data (tone of voice) collected from the user in real time to recognize the user's emotions. For this purpose, an emotion recognition API is used. It receives image data and audio data as input and generates analyzed emotional data as output.

[1001] Specific behavior:

[1002] 1. The device uses the camera and microphone to capture the user's facial and voice data.

[1003] 2. The acquired data is sent to the emotion recognition API, which runs an algorithm to analyze emotions.

[1004] 3. Receive a response from the emotion recognition API containing the user's emotional state (e.g., stress, joy, fatigue, etc.).

[1005] Step 2:

[1006] File creation and metadata entry

[1007] Description: The terminal provides a dialogue interface for the user to input a file name and corresponding metadata when creating a file. The tone of the interface is adjusted based on the result of emotion recognition. It receives emotion data and input to the user interface (file name, metadata) as input, and generates the input file name and metadata as output.

[1008] Specific behavior:

[1009] 1. The terminal will prompt you to "Enter a description for this file."

[1010] 2. The user enters a file name and metadata, for example, "End of Year Project Report."

[1011] 3. Collect input data from the dialogue interface and adjust tone based on emotion to encourage input.

[1012] Step 3:

[1013] Data storage

[1014] Description: The device sends the collected file name and metadata to the server, which then stores them in a cloud database (e.g., Firebase). It receives the file name and metadata as input and generates the database storage result (success or failure) as output.

[1015] Specific behavior:

[1016] 1. The device packages the filename and metadata and sends it to the server.

[1017] 2. The server connects to a cloud database and stores the file name and metadata.

[1018] 3. If the save is successful, the server notifies the device of the result.

[1019] Step 4:

[1020] Data Search

[1021] Description: When a user enters a search query, the device sends it to the server. The server retrieves metadata from a cloud database, calculates the similarity with the search query, and returns the best search results based on emotion recognition. It takes the search query and emotion data as input and generates search results as output.

[1022] Specific behavior:

[1023] 1. A user enters a search query into their device, for example, "year-end report."

[1024] 2. The device sends the search query to the server.

[1025] 3. The server queries the cloud database to retrieve all metadata matches.

[1026] 4. Using a similarity calculation means, calculate the similarity between the search query and the metadata.

[1027] 5. Based on the results of emotion recognition, the most relevant results are selected and sent back to the device as search results.

[1028] Step 5:

[1029] Metadata Editing

[1030] Description: When a user wants to edit or modify metadata, the terminal provides an editing interface. It receives new metadata as input and generates updated results as output. The interface is adjusted based on emotions to allow the user to easily edit.

[1031] Specific behavior:

[1032] 1. The user wishes to modify the metadata of an existing file on the device.

[1033] 2. The device recognizes emotions and adjusts the interface according to the user's emotions.

[1034] 3. The user enters new metadata, for example, "Project plan for next year."

[1035] 4. Send the new metadata to the server, which updates the existing record in the cloud database.

[1036] 5. The server notifies the user that the update was successful, and the device notifies the user of the result.

[1037] The above are the specific processing steps of the system that realizes the application example.

[1038] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1039] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1040] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1041] [Third embodiment]

[1042] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1043] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1044] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1045] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1046] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1047] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1048] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1049] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1050] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1051] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1052] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1053] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[1054] The present invention is a system that allows users to interactively input, store, and search metadata to facilitate file management and retrieval, thereby saving users time and enabling them to efficiently find the files they need.

[1055] 1. Creating a file and entering metadata

[1056] When a user creates a new file, they decide on a file name, for example "Project Report.docx."

[1057] The terminal will prompt you to "Enter a description for this file."

[1058] The user enters metadata for a file such as "end of year project report."

[1059] 2. Data storage

[1060] The device sends the file name and metadata to the server.

[1061] The server stores the received data in a database: it opens a database connection and executes a SQL statement to insert the file name, metadata, and creation date into the database.

[1062] 3. Search for files

[1063] A user enters a search query to find a specific file, for example, "end of year report."

[1064] The terminal sends this search query to the server.

[1065] The server opens a database connection and executes a SQL statement to retrieve metadata for all files.

[1066] 4. Similarity calculation

[1067] The server calculates the similarity between the retrieved metadata and the user's search query, using a machine learning algorithm to generate a highly accurate similarity score.

[1068] The server identifies the most relevant files based on the calculated similarity scores.

[1069] 5. Presentation of search results

[1070] The server returns the most relevant filename to the terminal.

[1071] The device will display "Best file is: <filename>" to the user.

[1072] 6. Editing Metadata

[1073] If the user wishes, they can edit or modify the metadata that has already been saved.

[1074] The terminal provides an editing interface and receives new metadata from the user and sends it to the server.

[1075] The server updates the existing record in the database.

[1076] Specific examples

[1077] File creation example: When a user creates a new file "Project Plan.docx," the terminal prompts the user to "Enter a description for this file." The user enters "Project plan for next year," and the terminal sends this information to the server. The server stores this information in a database.

[1078] File search example: A user searches for "plan for next year" by entering search keywords into the device. The device sends this query to the server, which retrieves all metadata from the database and calculates similarity. The server identifies the most relevant file, "Project Plan.docx," and returns it to the device. The device displays to the user, "The best file is: Project Plan.docx."

[1079] Metadata editing example: If a user wants to change the metadata of "Project Plan.docx" to "Project Plan for Next Year", the terminal provides an editing interface. The user inputs new metadata and the terminal sends it to the server. The server updates the existing record in the database.

[1080] As described above, this system provides users with a means to efficiently manage and search for files, and in particular enables them to quickly find the files they need through metadata collection and similarity calculations.

[1081] The processing flow will be explained below.

[1082] Program processing flow (when creating a file)

[1083] Step 1:

[1084] When a user creates a new file, they decide on a file name, for example "Project Report.docx".

[1085] Step 2:

[1086] The terminal prompts the user to "Please enter a description for this file."

[1087] Step 3:

[1088] The user enters metadata about the file, for example "end of year project report."

[1089] Step 4:

[1090] The terminal transmits the file name and metadata input by the user to the server.

[1091] Step 5:

[1092] The server opens a database connection in preparation for storing the received filename and metadata in the database.

[1093] Step 6:

[1094] The server executes the SQL statement and inserts the file name, metadata, and creation date and time into the database.

[1095] Step 7:

[1096] The server confirms that the save was successful and sends that information to the device.

[1097] Step 8:

[1098] The terminal notifies the user that the file has been successfully saved.

[1099] Program processing flow (when searching for files)

[1100] Step 1:

[1101] A user enters a search query, for example, "year-end report."

[1102] Step 2:

[1103] The terminal sends a search query from the user to the server.

[1104] Step 3:

[1105] The server opens a database connection and executes a SQL statement to retrieve metadata for all files.

[1106] Step 4:

[1107] The server uses a machine learning algorithm to calculate the similarity between the metadata it has acquired and the user's search query.

[1108] Step 5:

[1109] The server calculates the similarity scores and identifies the most similar files.

[1110] Step 6:

[1111] The server returns the most relevant filename to the terminal.

[1112] Step 7:

[1113] The device will tell the user, "The best file is: <filename>."

[1114] Program processing flow (when editing metadata)

[1115] Step 1:

[1116] The user selects the file for which they wish to edit or modify the metadata.

[1117] Step 2:

[1118] The device displays an editing interface with the existing metadata.

[1119] Step 3:

[1120] The user enters new metadata, for example, changing it to "Project plan for next year."

[1121] Step 4:

[1122] The device sends the new metadata to the server.

[1123] Step 5:

[1124] The server opens a database connection and executes SQL statements to update existing metadata.

[1125] Step 6:

[1126] The server confirms that the update was successful and sends that information to the device.

[1127] Step 7:

[1128] The terminal notifies the user that the metadata update was successful.

[1129] Example 1

[1130] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1131] In modern electronic file management systems, the large number of files stored makes it difficult for users to quickly search for and access the files they need. In particular, if file metadata (e.g., descriptions and tags) is not properly managed, the accuracy of the search function will be significantly reduced. Furthermore, manually updating metadata is a cumbersome task, preventing users from working efficiently. To solve these problems, a system that enables efficient file search and management is needed.

[1132] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1133] In this invention, the server includes an interactive means for inputting file names and corresponding metadata when a user creates a file, a storage means for storing the file names and metadata in a database, a search means for searching the database for matching files when a user inputs a search query, a similarity calculation means for calculating the similarity between the search query and the metadata, an output means for presenting the most similar file to the user, and an interactive means for editing or correcting the metadata input by the user. This allows the user to efficiently input, edit, and search file metadata, thereby enabling the user to quickly find the file they need.

[1134] A "user" is an individual or organization that uses the system to create, search, and edit files.

[1135] A "file name" is an identifying character string that is assigned to each file created by a user.

[1136] "Metadata" is additional information entered by the user to describe the contents of a file and is used to improve search accuracy.

[1137] "Interaction means" refers to an interface that allows a user to interactively input data and perform operations with the system.

[1138] "Storage means" is a function for storing file names and metadata in a database.

[1139] A "database" is a system that stores file names and metadata in an organized manner and manages them so that they can be searched and edited.

[1140] A "search query" is a keyword or phrase that a user enters to locate a particular file.

[1141] The "search means" is a function that searches for matching files in the database based on a user's search query.

[1142] The "similarity calculation means" is a function that calculates the relevance between a user's search query and metadata in the database.

[1143] "Machine learning algorithms" are artificial intelligence techniques used to calculate similarity and automatically classify data.

[1144] "Output means" is a function that visually presents search results and other information to the user.

[1145] "Communication means" refers to a communication function via the Internet or a local network for sending and receiving user input data and search results from a server.

[1146] This invention relates to a system that allows users to efficiently manage, search, and edit files. This system shares file names and metadata between users, terminals, and servers, and realizes highly accurate file searches.

[1147] Hardware and software used

[1148] This system consists of a terminal (e.g., a PC or smartphone) that accepts user operations, a server for storing and processing data, and a database. It also uses machine learning algorithms (e.g., TF-IDF or Word2Vec) to calculate the similarity of metadata, and a communication method (e.g., HTTP protocol) to exchange data between the server and the terminal.

[1149] Creating a file and entering metadata

[1150] When a user creates a new file, they input the file name into the terminal. At this time, the terminal displays a prompt saying "Please enter a description for this file" and prompts the user to input metadata. For example, the user may input metadata such as "Year-end project report."

[1151] Data storage

[1152] The terminal sends the file name and metadata to the server. The server receives this data and stores it in a database. Specifically, the server uses SQL statements to insert the file name, metadata, and creation date and time into the database.

[1153] Searching for files

[1154] When a user wants to find a specific file, they enter a search query into their device, for example, searching for "year-end report." The device then sends this query to the server, which retrieves all the metadata from the database and calculates the similarity to the search query. This calculation is done using machine learning algorithms such as TF-IDF and Word2Vec.

[1155] Presenting search results

[1156] Based on the calculated similarity score, the server identifies the most relevant filenames and returns them to the device, which then displays them to the user as something like "The best file is: Project Report.docx."

[1157] Editing Metadata

[1158] If the user wants to edit or modify the already saved metadata, the terminal provides an editing interface and receives new metadata from the user, which the terminal sends to the server, which then updates the existing record in the database.

[1159] Specific examples

[1160] File creation example: A user creates a new file "Project Plan.docx" and the terminal prompts, "Please enter a description for this file." If the user enters "Project plan for next year," the terminal sends this information to the server, which stores it in a database.

[1161] File search example: If a user searches for "Plan for next year", they enter the search keyword into their device. The device sends this query to the server, which retrieves all the metadata in the database. It then calculates the similarity and identifies the most relevant file, "Project Plan.docx", and returns it to the device. The device displays "The best file is: Project Plan.docx".

[1162] Metadata editing example: If a user wants to change the metadata of "Project Plan.docx" to "Project Plan for Next Year", the terminal provides an editing interface. The user inputs new metadata and the terminal sends it to the server. The server updates the existing record in the database.

[1163] This system allows users to efficiently enter, edit, and search file metadata, enabling them to quickly find the files they need.

[1164] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1165] Step 1:

[1166] When a user creates a new file, they enter a filename into the terminal, for example "Project Report.docx". The input at this point is the "filename", the string the user types into the terminal. The output is the prompt that is displayed on the terminal.

[1167] Step 2:

[1168] The terminal displays a prompt saying "Please enter a description for this file" and prompts the user to enter metadata. The input is "metadata," and the user might enter, for example, "Year-end project report." The output is metadata stored in the terminal's temporary memory.

[1169] Step 3:

[1170] The device sends the filename and metadata to the server using an HTTP POST request. The input is the filename and metadata, and the output is the data sent to the server.

[1171] Step 4:

[1172] The server stores the received data in a database. First, the server opens a database connection. The input is the file name and metadata sent from the terminal, and the output is the record to be stored in the database. Specifically, it executes the SQL statement "INSERT INTO files (file_name, metadata, creation_date) VALUES ('Project report.docx', 'Year-end project report', '2023-10-23')".

[1173] Step 5:

[1174] A user enters a search query to find a specific file, for example, "year-end report." The input is the "search query," which the device sends to the server. The output is the search query sent to the server.

[1175] Step 6:

[1176] The server opens a database connection and retrieves all metadata by executing a SQL statement such as "SELECT file_name, metadata FROM files". The input is the query to the database and the output is a list of the retrieved metadata.

[1177] Step 7:

[1178] The server calculates the similarity between the retrieved metadata and the user's search query, using, for example, TF-IDF (Term Frequency-Inverse Document Frequency). The input is the search query and a list of metadata, and the output is a similarity score for each file.

[1179] Step 8:

[1180] The server identifies the most relevant files based on the calculated similarity scores: the input is the similarity score, and the output is the filename with the highest score.

[1181] Step 9:

[1182] The server returns the most relevant filename to the terminal. The input is the identified filename, and the output is the filename returned to the terminal. The returned data is in JSON format.

[1183] Step 10:

[1184] The terminal will display to the user, "The best file is: Project Report.docx." The input is the file name returned by the server, and the output is the search results presented to the user.

[1185] Step 11:

[1186] When a user edits or modifies already saved metadata, the terminal provides an editing interface and receives new metadata from the user. The input is the new metadata edited by the user, which the terminal sends to the server. The output is the new metadata sent to the server.

[1187] Step 12:

[1188] The server updates an existing record in the database. The input is the new metadata, specifically by executing the SQL statement "UPDATE files SET metadata = 'newmetadata' WHERE file_name = 'projectreport.docx'". The output is the updated database record.

[1189] (Application example 1)

[1190] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1191] In factories and other workplaces, managing and quickly searching a large number of documents is essential, and effective management methods are needed. However, current document management systems have the drawback of being time-consuming to operate, as metadata input and editing is cumbersome and search accuracy is insufficient. Factories, in particular, need systems that can efficiently input metadata using voice input and touch interfaces and quickly search for related documents.

[1192] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1193] In this invention, the server includes an interactive means for inputting file names and corresponding metadata when a user creates a file, a storage means for storing the file names and metadata in a database, a search means for searching the database for matching files when a user inputs a search query, a similarity calculation means for calculating the similarity between the search query and the metadata, an output means for presenting the most similar file to the user, and a means for inputting the user-entered metadata via voice or a touch interface. This allows document metadata to be efficiently entered and managed, improving search accuracy and enabling desired documents to be found quickly.

[1194] "User" means a person or end user who operates the system and inputs, searches, and edits data.

[1195] A "file name" is a text-based name set by the user to identify an individual file.

[1196] "Metadata" is data that represents additional information associated with a file, detailing the contents and characteristics of the file.

[1197] An "interaction means" is an interface used by a user to input and edit data, including in particular voice input and touch interfaces.

[1198] A "storage mechanism" is a mechanism for recording and maintaining file names and metadata in a database.

[1199] The "search means" is a function for searching for related files from the database based on a query entered by the user.

[1200] The "similarity calculation means" is an algorithm for calculating the similarity between a user's search query and metadata in the database.

[1201] The "output means" is a mechanism for providing the user with information on the most relevant file based on the calculated similarity.

[1202] The present invention relates to a system for efficiently managing and quickly searching for a large number of documents (such as blueprints, maintenance procedures, and operation manuals) used in a factory. Specific embodiments of the system will be described in detail below.

[1203] The system includes a means for users to interactively enter, store, and retrieve metadata.

[1204] Hardware and software used

[1205] Hardware: Robots deployed in factories (with voice recognition and touchscreen displays)

[1206] Software: Python, SQLite (for database management), Scikit-learn (machine learning library)

[1207] Details of data processing and calculation

[1208] 1. Database connection and metadata storage

[1209] The server connects to an SQLite database and creates a table to store document information. When a user creates a new document, the robot prompts the user, "Please enter a description for this document." The user provides metadata via voice input or touch panel input, and the robot sends the metadata to the server and stores it in the database.

[1210] 2. Metadata search and similarity calculation

[1211] When a user searches for a specific document, they input a search query into the robot (via voice or touch panel). The server sends this search query to the database and retrieves the stored metadata. It then uses Scikit-learn's TfidfVectorizer and cosine_similarity function to calculate the similarity between the search query and the stored metadata.

[1212] 3. Presentation of search results

[1213] The server identifies the most relevant document based on the calculated similarity and sends that information back to the robot, which displays to the user, "The best document is: <document name>."

[1214] 4. Editing Metadata

[1215] If a user wants to edit the metadata of an existing document, the robot provides an editing interface, and when the user enters new metadata, it sends it to the server, updating the existing record.

[1216] Specific examples

[1217] For example, if a user adds a new document called "Factory Machine Maintenance Procedures.pdf", the following happens:

[1218] 1. The robot displays the prompt, "Please enter a description of this document."

[1219] 2. The user speaks "Routine maintenance procedures."

[1220] 3. The robot sends this to the server and stores it in the database.

[1221] If a user searches for "maintenance procedures," the experience progresses as follows:

[1222] 1. A user enters the search query "maintenance procedures" into the robot.

[1223] 2. The server receives the query, retrieves the metadata from the database, and performs the similarity calculation.

[1224] 3. The server sends the most relevant document back to the robot, which then displays, "The best document is: Factory Machine Maintenance Procedures.pdf."

[1225] Prompt Sentence Examples

[1226] For example, it can be used as follows when executing a Python program:

[1227] python

[1228] Documentation

[1229] create_document("Factory Machine Maintenance Procedure.pdf", "Periodic Maintenance Procedure")

[1230] Document Search

[1231] print(search_documents("Maintenance Procedures"))

[1232] Metadata Editing

[1233] edit_metadata("Factory Machine Maintenance Procedure.pdf", "Monthly Scheduled Maintenance Procedure")

[1234] This allows the system to efficiently manage and quickly search a large number of documents within a factory.

[1235] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1236] Step 1:

[1237] When a user creates a new file, the robot (terminal) displays a prompt saying, "Please enter a description of this document." The user provides metadata via voice input or touch panel.

[1238] Input: User-entered file name and metadata (e.g., "Factory Machine Maintenance Procedures.pdf", "Routine Maintenance Procedures")

[1239] Output: Send collected filenames and metadata to the server

[1240] Step 2:

[1241] The server receives the file name and metadata sent from the device and stores them in an SQLite database by opening a database connection and inserting the file name, metadata, and creation date and time into a table.

[1242] Input: File name and metadata sent from the device (e.g., "Factory Machine Maintenance Procedures.pdf", "Routine Maintenance Procedures")

[1243] Output: New document information saved in the database

[1244] Step 3:

[1245] When a user enters a search query, the robot (terminal) receives the query from the user and sends it to the server.

[1246] Input: The search query entered by the user (e.g., "maintenance procedures")

[1247] Output: Sends the search query to the server

[1248] Step 4:

[1249] The server retrieves all metadata from the database and performs a similarity calculation to find metadata that matches the user's search query.

[1250] Input: User search query and metadata retrieved from the database

[1251] Data processing: Generate TF-IDF vectors for search queries and metadata

[1252] Data arithmetic: Calculate cosine similarity and identify the most relevant metadata

[1253] Output: Identify the most relevant files based on a similarity calculation

[1254] Step 5:

[1255] The server returns the most relevant filenames based on the calculated similarity to the robot (terminal).

[1256] Input: The most related filenames based on the similarity calculation

[1257] Output: Sends the most relevant filename to the terminal

[1258] Step 6:

[1259] The robot (terminal) displays the search results to the user, specifically displaying "The best document is: <Document name>."

[1260] Input: The file name returned by the server

[1261] Output: Displaying search results to the user

[1262] Step 7:

[1263] When a user edits or modifies already saved metadata, the robot (terminal) provides an editing interface, receives new metadata from the user, and sends it to the server.

[1264] Input: New metadata entered by the user (e.g., "Monthly scheduled maintenance procedures")

[1265] Output: Send the new metadata to the server

[1266] Step 8:

[1267] The server receives the new metadata sent from the device and updates the existing record in the SQLite database, specifically by replacing the metadata for the corresponding file name with the new one.

[1268] Input: New metadata sent from the device

[1269] Output: Metadata in the database is updated

[1270] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1271] The present invention is a system that uses an emotion engine to recognize a user's emotions when creating, managing, and searching for files, and provides an appropriate interface and search results according to those emotions. This system promotes file metadata input and adjusts search results based on the user's emotions, thereby achieving a better user experience.

[1272] 1. Emotion engine integration

[1273] The device is equipped with an emotion engine that recognizes emotions in real time from the user's facial expressions, tone of voice, and input method.

[1274] 2. Creating a file and entering metadata

[1275] When a user creates a new file, they set the file name, for example, "Project Report.docx."

[1276] The device will prompt you to "Enter a description for this file" and the emotion engine will analyze the user's current emotions.

[1277] If the emotion engine recognizes that the user is feeling stressed, the device will provide a relaxing interface and encourage input.

[1278] A user enters metadata such as "year-end project report."

[1279] 3. Data storage

[1280] The device sends the file name and metadata to the server.

[1281] To store the received data in a database, the server opens a database connection and executes an SQL statement to insert the file name, metadata, and creation date and time into the database.

[1282] 4. Search for files

[1283] A user enters a search query, for example, "year-end report."

[1284] The terminal sends a search query from the user to the server.

[1285] The server opens a database connection and executes a SQL statement to retrieve metadata for all files.

[1286] The server uses a machine learning algorithm to calculate the similarity between the acquired metadata and the user's search query.

[1287] The emotion engine analyzes the user's emotions, and if the user is in a hurry, for example, it prioritizes the information that needs to be returned most quickly and identifies the most relevant files.

[1288] The server returns the most relevant filename to the terminal.

[1289] The device will display "Best file is: <filename>" to the user.

[1290] 5. Editing Metadata

[1291] If the user wishes to edit or modify the metadata, the terminal provides an editing interface.

[1292] The user inputs new metadata, for example, changing it to "Next year's project plan."

[1293] The terminal sends the new metadata to the server.

[1294] The server opens a database connection and executes SQL statements to update the existing metadata.

[1295] The server confirms that the update was successful and sends it to the terminal, and the terminal notifies the user that the metadata update was successful.

[1296] Specific examples

[1297] File creation example: When a user creates a file called "Meeting minutes.docx," the device prompts the user, "Please enter a description for this file." If the emotion engine recognizes that the user is tired, it presents a friendly interface to assist input. The user enters "Monthly meeting minutes," and the device sends this information to the server, which stores it in a database.

[1298] File search example: When a user searches for "monthly meeting," the device sends this query to the server. The server retrieves metadata from the database and calculates similarity. If the emotion engine recognizes that the user is in a hurry, it prioritizes the most relevant files. The server identifies "Meeting Minutes.docx" and sends it back to the device. The device displays, "The best file is: Meeting Minutes.docx."

[1299] Metadata editing example: If a user wants to change the metadata of "Meeting Minutes.docx" to "Minutes of Quarterly Meeting", an editing interface is provided. The user enters new metadata and the terminal sends it to the server. The server updates the existing record in the database and notifies the terminal that the update was successful. The terminal notifies the user that the update was successful.

[1300] As described above, by integrating the emotion engine, we have created a system that can provide a flexible interface that responds to the user's emotional state and highly accurate search results.

[1301] The processing flow will be explained below.

[1302] Program processing flow (when creating a file)

[1303] Step 1:

[1304] The user decides to create a new file and enters a file name, for example "Project Report.docx."

[1305] Step 2:

[1306] The terminal receives the filename and displays the prompt "Please enter a description for this file."

[1307] Step 3:

[1308] The emotion engine built into the device analyzes the user's facial expressions and tone of voice to recognize emotions in real time.

[1309] Step 4:

[1310] The device provides an interface based on the user's emotions, for example, if the user is feeling stressed, it uses a relaxing interface.

[1311] Step 5:

[1312] The user enters a description for the file, for example, "End of Year Project Report."

[1313] Step 6:

[1314] The device sends the entered file name and metadata to the server.

[1315] Step 7:

[1316] The server opens a database connection and executes an SQL statement to insert the file name, metadata, and creation date into the database.

[1317] Step 8:

[1318] The server confirms that the save was successful and sends that information to the device.

[1319] Step 9:

[1320] The terminal notifies the user that the file has been successfully saved.

[1321] Program processing flow (when searching for files)

[1322] Step 1:

[1323] A user enters a search query to find a specific file, for example, "end of year report."

[1324] Step 2:

[1325] The terminal receives the search query and sends it to the server.

[1326] Step 3:

[1327] The server opens a database connection and executes a SQL statement to retrieve metadata for all files.

[1328] Step 4:

[1329] Using the metadata acquired by the server, a machine learning algorithm is used to calculate the similarity to the user's search query.

[1330] Step 5:

[1331] The emotion engine built into the device analyzes the user's current emotions and prioritizes displaying results quickly if, for example, the user is in a hurry.

[1332] Step 6:

[1333] The server calculates the similarity scores and identifies the most similar files.

[1334] Step 7:

[1335] The server sends the specified file name to the terminal.

[1336] Step 8:

[1337] The device displays "The best file is: <filename>" to the user.

[1338] Program processing flow (when editing metadata)

[1339] Step 1:

[1340] If the user wishes to edit or modify the metadata for an existing file, the user selects the file.

[1341] Step 2:

[1342] The device displays the existing metadata for the file and provides an editing interface.

[1343] Step 3:

[1344] The user enters new metadata, for example, changing it to "Project plan for next year."

[1345] Step 4:

[1346] The device sends the new metadata to the server.

[1347] Step 5:

[1348] The server opens a database connection and executes SQL statements to update the existing metadata.

[1349] Step 6:

[1350] The server confirms that the update was successful and sends that information to the device.

[1351] Step 7:

[1352] The terminal notifies the user that the metadata update was successful.

[1353] Emotion Engine Processing Flow

[1354] Step 1:

[1355] When a user operates the system, the device's built-in camera and microphone capture the user's facial expressions and tone of voice.

[1356] Step 2:

[1357] The device's emotion engine analyzes the captured data in real time to recognize the user's emotional state.

[1358] Step 3:

[1359] The device will provide an appropriate interface based on the recognized emotion, for example, using relaxing colors and fonts if the user is tired.

[1360] Step 4:

[1361] The device transmits the user's emotional state to the server, which is then taken into account when searching for files and entering metadata.

[1362] Step 5:

[1363] The server adjusts the parameters of the search algorithm based on the emotional data and returns the optimal results according to the user's situation.

[1364] As described above, by integrating an emotion engine, the system of the present invention can provide a flexible interface that responds to the user's emotions and highly accurate search results.

[1365] Example 2

[1366] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1367] The present invention aims to provide a better user experience by appropriately recognizing a user's emotions when creating, managing, and searching for files, and providing an interface and search results that reflect those emotions. Conventional systems do not respond to user emotions, which can cause users to feel stressed when creating or searching for files. Another problem is that it can be difficult for users to quickly find the right file when they are in a hurry.

[1368] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1369] In this invention, the server includes emotion recognition means for recognizing a user's emotion in real time, adjustment means for providing an interface according to the user's emotion, and similarity calculation means for calculating the similarity between the search query and metadata. This allows the interface and search results to be adjusted based on the user's emotion, enabling the user to quickly find or create the files they need without feeling stressed.

[1370] "User" means a person who uses the system to create, manage, and retrieve files.

[1371] A "file" is a piece of digital data, such as a document or image, that users create, store, and search.

[1372] "Metadata" is information associated with a file, including additional information such as the file name, description, and tags.

[1373] An "interaction means" is a means that provides an interface for a user to interact with the system and input information.

[1374] "Storage" refers to the mechanism by which filenames and metadata are stored in a database.

[1375] The "search means" is a function for searching files in the database and providing the user with results appropriate for the file.

[1376] "Similarity calculation means" refers to a mechanism for calculating the similarity between a user's search query and a file's metadata.

[1377] The "output means" is a means for presenting search results to the user.

[1378] "Emotion recognition means" refers to a system that recognizes emotions in real time from a user's facial expressions, tone of voice, input method, etc.

[1379] The "adjustment means" refers to a function that adjusts the interface and search results according to the user's emotions detected by the emotion recognition means.

[1380] A "machine learning algorithm" refers to an algorithm that analyzes data and learns patterns and rules to calculate similarity and optimize searches.

[1381] The present invention is a system that uses an emotion engine to recognize a user's emotions when creating, managing, and searching for files, and provides an appropriate interface and search results based on those emotions. This system promotes file metadata entry and adjusts search results based on the user's emotions, thereby achieving a better user experience.

[1382] Emotion engine integration

[1383] The device is equipped with an emotion engine that recognizes emotions in real time from the user's facial expressions, tone of voice, input method, etc. The emotion engine uses, for example, Microsoft's Azure Face API for facial recognition technology and Google Cloud Speech-to-Text for voice recognition technology.

[1384] Creating a file and entering metadata

[1385] When a user creates a new file, they set the file name, for example, "Project Report.docx."

[1386] The device will prompt you to "Enter a description for this file" and the emotion engine will analyze the user's current emotions.

[1387] If the emotion engine detects that the user is feeling stressed, the device will provide a relaxing interface and encourage input, such as changing the background color or playing relaxing music.

[1388] A user enters metadata such as "year-end project report."

[1389] Data storage

[1390] The device sends the file name and metadata to the server.

[1391] The server opens a database connection, executes a SQL statement that saves the file name, metadata, and creation date and time in the database, and saves the data.

[1392] Searching for files

[1393] A user enters a search query, for example, "year-end report."

[1394] The terminal sends a search query to the server.

[1395] The server opens a database connection and executes a SQL statement to retrieve metadata for all files.

[1396] The server uses a machine learning algorithm to calculate the similarity between the acquired metadata and the user's search query.

[1397] The emotion engine analyzes the user's emotions, and if the user is in a hurry, for example, it prioritizes the information that needs to be returned most quickly and identifies the most relevant files.

[1398] The server returns the most relevant filename to the terminal.

[1399] The device will display to the user "The best file is: Meeting Minutes.docx."

[1400] Editing Metadata

[1401] If the user wishes to edit or modify the metadata, the terminal provides an editing interface.

[1402] The user inputs new metadata, for example, changing it to "Next year's project plan."

[1403] The terminal sends the new metadata to the server.

[1404] The server executes a SQL statement to update an existing record in the database.

[1405] The server confirms that the update was successful and notifies the terminal.

[1406] The terminal notifies the user of the success of the update.

[1407] Specific examples

[1408] File creation example

[1409] When a user creates a file called "Meeting Minutes.docx," the device prompts the user, "Please enter a description for this file." If the emotion engine detects that the user is tired, it presents a friendly interface to assist input. The user types "Monthly Meeting Minutes," and the device sends this information to the server, which stores it in a database.

[1410] File search example

[1411] When a user searches for "monthly meeting," the device sends this query to the server. The server retrieves metadata from the database and calculates similarity. If the emotion engine recognizes that the user is in a hurry, it prioritizes the most relevant files. The server identifies "Meeting Minutes.docx" and sends it back to the device. The device displays, "The best file is: Meeting Minutes.docx."

[1412] Metadata editing example

[1413] If a user wants to change the metadata of "Meeting Minutes.docx" to "Minutes of Quarterly Meeting," an editing interface is provided. The user enters new metadata, and the terminal sends it to the server. The server updates the existing record in the database and notifies the terminal that the update was successful. The terminal notifies the user that the update was successful.

[1414] As described above, by integrating the emotion engine, we have created a system that provides a flexible interface and highly accurate search results that respond to the user's emotional state.

[1415] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1416] Step 1: Integrating the Emotion Engine

[1417] The device uses an emotion engine to recognize the user's facial expressions, tone of voice, and input method in real time. The emotion engine uses, for example, a general face recognition API for facial recognition technology or a voice recognition API for voice recognition technology. Specifically, it acquires data from the camera and microphone and inputs it into an emotion recognition model. The emotion model analyzes the data and outputs the user's emotional state (e.g., stressed, relaxed, etc.).

[1418] Input: Real-time data from camera and microphone

[1419] Data processing: Emotion analysis using face and voice recognition APIs

[1420] Output: User's emotional state

[1421] Step 2: Enter a file name

[1422] The terminal prompts the user to enter a file name when creating a new file, and the user enters the file name and sends it to the terminal (e.g., "Project Report.docx").

[1423] Input: The file name entered by the user

[1424] Output: Send filename to terminal

[1425] Step 3: Prompt for Metadata

[1426] The device displays a prompt saying, "Please enter a description for this file," and the emotion engine analyzes the user's current emotion. If the emotion engine determines that the user is feeling stressed, the device provides a relaxing interface (e.g., changing the background color, playing relaxing music) to encourage input.

[1427] Input: prompt after entering user's emotional state and file name

[1428] Data manipulation: adjusting the interface based on emotions

[1429] Output: Display interface and prompts to the user

[1430] Step 4: Entering Metadata

[1431] The user inputs metadata (e.g., "end of year project report"), and the device receives this input and begins the process of saving the data.

[1432] Input: User-entered metadata

[1433] Output: Sending metadata to the device

[1434] Step 5: Sending data

[1435] The device sends the entered file name and metadata to the server, which prepares to save the data.

[1436] Input: Filename and metadata

[1437] Output: Send data to the server

[1438] Step 6: Save your data

[1439] The server opens a database connection, executes a SQL statement to store the filename, metadata, and creation date and time in the database, and then saves the data. For example, it executes the SQL statement "INSERT INTO files (filename, metadata, created_at) VALUES ('Project report.docx', 'End of year project report', NOW())".

[1440] Input: Filename and metadata

[1441] Data processing: Generate SQL statements and save them to the database

[1442] Output: Confirmation saved in the database

[1443] Step 7: Enter a search query

[1444] A user enters a search query into a terminal (e.g., "year-end report"), and the terminal sends the search query to the server.

[1445] Input: The search query entered by the user

[1446] Output: Sending a search query to the server

[1447] Step 8: Retrieving Metadata from the Database

[1448] The server opens a database connection and executes a SQL statement to retrieve all file metadata, for example the SQL statement "SELECT filename, metadata FROM files" to retrieve all metadata.

[1449] Input: Search query

[1450] Data processing: SQL statement generation, metadata acquisition

[1451] Output: Retrieved metadata

[1452] Step 9: Calculate similarity

[1453] The server runs machine learning algorithms to calculate the similarity between the retrieved metadata and the user's search query. For example, it uses natural language processing models to evaluate the similarity between the search query and the metadata. An emotion engine analyzes the user's emotions and prioritizes the most relevant files if the user is in a hurry.

[1454] Input: Search query and retrieved metadata

[1455] Data processing: Similarity calculation using machine learning algorithms

[1456] Output: Identifying the most relevant files

[1457] Step 10: Output search results

[1458] The server returns the most relevant filename to the terminal, which displays the message "The best file is: <filename>" to the user.

[1459] Input: A specified file name

[1460] Output: Displayed to user as search result

[1461] Step 11: Editing Metadata

[1462] If the user wants to edit or modify the metadata, the terminal provides an editing interface. The user inputs new metadata (e.g., "Project plan for next year") and the terminal transmits the new metadata to the server.

[1463] Input: New metadata entered by the user

[1464] Output: Sending new metadata to the server

[1465] Step 12: Update the Metadata

[1466] The server executes SQL statements to update existing records in the database, for example, the SQL statement "UPDATE files SET metadata = 'Next Year's Project Plan' WHERE filename = 'Project Report.docx'".

[1467] Input: New Metadata

[1468] Data processing: SQL statement generation, database update

[1469] Output: Confirmation of successful database update

[1470] Step 13: Notification of successful update

[1471] The server confirms that the update was successful and notifies the terminal, which then notifies the user of the success of the update.

[1472] Input: Confirmation of successful database update

[1473] Output: Notify user that update was successful

[1474] (Application example 2)

[1475] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1476] In conventional file creation, management, and search systems, it was difficult to provide an appropriate interface or search results when the user was in an emotional state, such as when they were tired or stressed. As a result, the user's work efficiency decreased and it could even lead to incorrect file operations. Therefore, the purpose of this invention is to solve these problems and provide a system that provides a flexible interface and highly accurate search results that respond to the user's emotions.

[1477] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1478] In this invention, the server includes an interaction means for inputting a file name and corresponding metadata when a user creates a file, a storage means for storing the file name and metadata in a database, a search means for searching the database for matching files when a user inputs a search query, a similarity calculation means for calculating a similarity between the search query and the metadata, an output means for presenting the most similar file to the user, an emotion recognition means for analyzing the user's facial expression and tone of voice to recognize their emotion, and an emotion response means for adjusting the interface of the interaction means and the output means based on the user's emotion, thereby making it possible to provide an interface and adjust search results in accordance with the user's emotion.

[1479] The "interactive means" refers to a means for interacting with the user to prompt the user to enter input content when the user creates a file or inputs metadata.

[1480] The "storage means" is a means for storing the filenames and corresponding metadata created by the user in a database.

[1481] A "searching means" is a means for searching a database for matching files based on a search query entered by a user.

[1482] The "similarity calculation means" is a means for calculating the similarity between a search query and metadata.

[1483] The "output means" is a means for presenting the most similar file to the user.

[1484] The "emotion recognition means" is a means for analyzing the user's facial expressions and tone of voice to recognize the user's emotions.

[1485] The "emotion response means" is a means for adjusting the interface of the dialogue means and the output means based on the user's emotions.

[1486] This system recognizes a user's emotions and provides appropriate interfaces and search results based on those emotions. This system consists of smart glasses with an emotion engine and a file management and search system using a cloud database.

[1487] 1. System Configuration

[1488] This system consists of the following main components:

[1489] Smart glasses: Equipped with emotion recognition means that analyze the user's facial expressions and tone of voice in real time.

[1490] Cloud Database: Use a cloud service such as Firebase to store file names and metadata.

[1491] Machine learning algorithms: Use machine learning libraries such as TensorFlow to calculate the similarity between search queries and metadata.

[1492] 2. Data Creation and Management

[1493] When a user creates a new file, the smart glasses act as a "conversational tool." Specifically, they recognize the user's current emotion and display appropriate prompts accordingly. For example, if the user is feeling stressed, they will be prompted with a gentler tone. The generated file name and metadata are then stored in a cloud database.

[1494] 3. Searching for data

[1495] When a user enters a search query, the smart glasses and a cloud server work together to retrieve data. The cloud server calculates the similarity between the search query and all metadata in the database. During this process, the server analyzes the user's sentiment in real time and prioritizes highly relevant files to quickly display search results if the user is in a hurry.

[1496] 4. Editing Metadata

[1497] If the user wishes to edit or modify the metadata, the smart glasses act as an editing interface, again adapting to the user's emotional state. The new metadata is updated to the cloud database, and the success is confirmed.

[1498] Specific examples

[1499] File Creation Example: When a user creates a "Maintenance Report," the smart glasses prompt them to "Enter a description for this report." If the emotion engine recognizes that the user is tired, a gentle interface is presented to encourage input. Once the user completes the description, the data is saved to a cloud database.

[1500] File search example: When a user searches for "maintenance record," the smart glasses send this query to the cloud server. The server retrieves metadata from the database and calculates similarity. If the emotion engine recognizes that the user is in a hurry, it will prioritize the most relevant files. For example, "maintenance report" is identified and sent back to the smart glasses.

[1501] Metadata Editing Example: When a user changes the metadata of "Maintenance Report" to "Scheduled Maintenance Report", the emotion engine adjusts the editing interface based on the user's emotional state, enters the new metadata, and notifies the cloud database that the update was successful.

[1502] Prompt Sentence Examples

[1503] "Please explain the work log management and data search system for factory robots that uses an emotion engine. In particular, please explain in detail the specific methods and benefits of the work log input and search function based on user emotions."

[1504] The above is the "Mode for Carrying Out the Invention."

[1505] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1506] Step 1:

[1507] emotion recognition

[1508] Description: The device (smart glasses) analyzes image data (facial expressions) and audio data (tone of voice) collected from the user in real time to recognize the user's emotions. For this purpose, an emotion recognition API is used. It receives image data and audio data as input and generates analyzed emotional data as output.

[1509] Specific behavior:

[1510] 1. The device uses the camera and microphone to capture the user's facial and voice data.

[1511] 2. The acquired data is sent to the emotion recognition API, which runs an algorithm to analyze emotions.

[1512] 3. Receive a response from the emotion recognition API containing the user's emotional state (e.g., stress, joy, fatigue, etc.).

[1513] Step 2:

[1514] File creation and metadata entry

[1515] Description: The terminal provides a dialogue interface for the user to input a file name and corresponding metadata when creating a file. The tone of the interface is adjusted based on the result of emotion recognition. It receives emotion data and input to the user interface (file name, metadata) as input, and generates the input file name and metadata as output.

[1516] Specific behavior:

[1517] 1. The terminal will prompt you to "Enter a description for this file."

[1518] 2. The user enters a file name and metadata, for example, "End of Year Project Report."

[1519] 3. Collect input data from the dialogue interface and adjust tone based on emotion to encourage input.

[1520] Step 3:

[1521] Data storage

[1522] Description: The device sends the collected file name and metadata to the server, which then stores them in a cloud database (e.g., Firebase). It receives the file name and metadata as input and generates the database storage result (success or failure) as output.

[1523] Specific behavior:

[1524] 1. The device packages the filename and metadata and sends it to the server.

[1525] 2. The server connects to a cloud database and stores the file name and metadata.

[1526] 3. If the save is successful, the server notifies the device of the result.

[1527] Step 4:

[1528] Data Search

[1529] Description: When a user enters a search query, the device sends it to the server. The server retrieves metadata from a cloud database, calculates the similarity with the search query, and returns the best search results based on emotion recognition. It takes the search query and emotion data as input and generates search results as output.

[1530] Specific behavior:

[1531] 1. A user enters a search query into their device, for example, "year-end report."

[1532] 2. The device sends the search query to the server.

[1533] 3. The server queries the cloud database to retrieve all metadata matches.

[1534] 4. Using a similarity calculation means, calculate the similarity between the search query and the metadata.

[1535] 5. Based on the results of emotion recognition, the most relevant results are selected and sent back to the device as search results.

[1536] Step 5:

[1537] Metadata Editing

[1538] Description: When a user wants to edit or modify metadata, the terminal provides an editing interface. It receives new metadata as input and generates updated results as output. The interface is adjusted based on emotions to allow the user to easily edit.

[1539] Specific behavior:

[1540] 1. The user wishes to modify the metadata of an existing file on the device.

[1541] 2. The device recognizes emotions and adjusts the interface according to the user's emotions.

[1542] 3. The user enters new metadata, for example, "Project plan for next year."

[1543] 4. Send the new metadata to the server, which updates the existing record in the cloud database.

[1544] 5. The server notifies the user that the update was successful, and the device notifies the user of the result.

[1545] The above are the specific processing steps of the system that realizes the application example.

[1546] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1547] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1548] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1549] [Fourth embodiment]

[1550] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1551] 7, a 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.

[1552] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1553] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1554] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1555] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1556] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1557] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1558] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1559] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1560] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1561] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1562] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1563] The present invention is a system that allows users to interactively input, store, and search metadata to facilitate file management and retrieval, thereby saving users time and enabling them to efficiently find the files they need.

[1564] 1. Creating a file and entering metadata

[1565] When a user creates a new file, they decide on a file name, for example "Project Report.docx."

[1566] The terminal will prompt you to "Enter a description for this file."

[1567] The user enters metadata for a file such as "end of year project report."

[1568] 2. Data storage

[1569] The device sends the file name and metadata to the server.

[1570] The server stores the received data in a database: it opens a database connection and executes a SQL statement to insert the file name, metadata, and creation date into the database.

[1571] 3. Search for files

[1572] A user enters a search query to find a specific file, for example, "end of year report."

[1573] The terminal sends this search query to the server.

[1574] The server opens a database connection and executes a SQL statement to retrieve metadata for all files.

[1575] 4. Similarity calculation

[1576] The server calculates the similarity between the retrieved metadata and the user's search query, using a machine learning algorithm to generate a highly accurate similarity score.

[1577] The server identifies the most relevant files based on the calculated similarity scores.

[1578] 5. Presentation of search results

[1579] The server returns the most relevant filename to the terminal.

[1580] The device will display "Best file is: <filename>" to the user.

[1581] 6. Editing Metadata

[1582] If the user wishes, they can edit or modify the metadata that has already been saved.

[1583] The terminal provides an editing interface and receives new metadata from the user and sends it to the server.

[1584] The server updates the existing record in the database.

[1585] Specific examples

[1586] File creation example: When a user creates a new file "Project Plan.docx," the terminal prompts the user to "Enter a description for this file." The user enters "Project plan for next year," and the terminal sends this information to the server. The server stores this information in a database.

[1587] File search example: A user searches for "plan for next year" by entering search keywords into the device. The device sends this query to the server, which retrieves all metadata from the database and calculates similarity. The server identifies the most relevant file, "Project Plan.docx," and returns it to the device. The device displays to the user, "The best file is: Project Plan.docx."

[1588] Metadata editing example: If a user wants to change the metadata of "Project Plan.docx" to "Project Plan for Next Year", the terminal provides an editing interface. The user inputs new metadata and the terminal sends it to the server. The server updates the existing record in the database.

[1589] As described above, this system provides users with a means to efficiently manage and search for files, and in particular enables them to quickly find the files they need through metadata collection and similarity calculations.

[1590] The processing flow will be explained below.

[1591] Program processing flow (when creating a file)

[1592] Step 1:

[1593] When a user creates a new file, they decide on a file name, for example "Project Report.docx".

[1594] Step 2:

[1595] The terminal prompts the user to "Please enter a description for this file."

[1596] Step 3:

[1597] The user enters metadata about the file, for example "end of year project report."

[1598] Step 4:

[1599] The terminal transmits the file name and metadata input by the user to the server.

[1600] Step 5:

[1601] The server opens a database connection in preparation for storing the received filename and metadata in the database.

[1602] Step 6:

[1603] The server executes the SQL statement and inserts the file name, metadata, and creation date and time into the database.

[1604] Step 7:

[1605] The server confirms that the save was successful and sends that information to the device.

[1606] Step 8:

[1607] The terminal notifies the user that the file has been successfully saved.

[1608] Program processing flow (when searching for files)

[1609] Step 1:

[1610] A user enters a search query, for example, "year-end report."

[1611] Step 2:

[1612] The terminal sends a search query from the user to the server.

[1613] Step 3:

[1614] The server opens a database connection and executes a SQL statement to retrieve metadata for all files.

[1615] Step 4:

[1616] The server uses a machine learning algorithm to calculate the similarity between the metadata it has acquired and the user's search query.

[1617] Step 5:

[1618] The server calculates the similarity scores and identifies the most similar files.

[1619] Step 6:

[1620] The server returns the most relevant filename to the terminal.

[1621] Step 7:

[1622] The device will tell the user, "The best file is: <filename>."

[1623] Program processing flow (when editing metadata)

[1624] Step 1:

[1625] The user selects the file for which they wish to edit or modify the metadata.

[1626] Step 2:

[1627] The device displays an editing interface with the existing metadata.

[1628] Step 3:

[1629] The user enters new metadata, for example, changing it to "Project plan for next year."

[1630] Step 4:

[1631] The device sends the new metadata to the server.

[1632] Step 5:

[1633] The server opens a database connection and executes SQL statements to update existing metadata.

[1634] Step 6:

[1635] The server confirms that the update was successful and sends that information to the device.

[1636] Step 7:

[1637] The terminal notifies the user that the metadata update was successful.

[1638] Example 1

[1639] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1640] In modern electronic file management systems, the large number of files stored makes it difficult for users to quickly search for and access the files they need. In particular, if file metadata (e.g., descriptions and tags) is not properly managed, the accuracy of the search function will be significantly reduced. Furthermore, manually updating metadata is a cumbersome task, preventing users from working efficiently. To solve these problems, a system that enables efficient file search and management is needed.

[1641] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1642] In this invention, the server includes an interactive means for inputting file names and corresponding metadata when a user creates a file, a storage means for storing the file names and metadata in a database, a search means for searching the database for matching files when a user inputs a search query, a similarity calculation means for calculating the similarity between the search query and the metadata, an output means for presenting the most similar file to the user, and an interactive means for editing or correcting the metadata input by the user. This allows the user to efficiently input, edit, and search file metadata, thereby enabling the user to quickly find the file they need.

[1643] A "user" is an individual or organization that uses the system to create, search, and edit files.

[1644] A "file name" is an identifying character string that is assigned to each file created by a user.

[1645] "Metadata" is additional information entered by the user to describe the contents of a file and is used to improve search accuracy.

[1646] "Interaction means" refers to an interface that allows a user to interactively input data and perform operations with the system.

[1647] "Storage means" is a function for storing file names and metadata in a database.

[1648] A "database" is a system that stores file names and metadata in an organized manner and manages them so that they can be searched and edited.

[1649] A "search query" is a keyword or phrase that a user enters to locate a particular file.

[1650] The "search means" is a function that searches for matching files in the database based on a user's search query.

[1651] The "similarity calculation means" is a function that calculates the relevance between a user's search query and metadata in the database.

[1652] "Machine learning algorithms" are artificial intelligence techniques used to calculate similarity and automatically classify data.

[1653] "Output means" is a function that visually presents search results and other information to the user.

[1654] "Communication means" refers to a communication function via the Internet or a local network for sending and receiving user input data and search results from a server.

[1655] This invention relates to a system that allows users to efficiently manage, search, and edit files. This system shares file names and metadata between users, terminals, and servers, and realizes highly accurate file searches.

[1656] Hardware and software used

[1657] This system consists of a terminal (e.g., a PC or smartphone) that accepts user operations, a server for storing and processing data, and a database. It also uses machine learning algorithms (e.g., TF-IDF or Word2Vec) to calculate the similarity of metadata, and a communication method (e.g., HTTP protocol) to exchange data between the server and the terminal.

[1658] Creating a file and entering metadata

[1659] When a user creates a new file, they input the file name into the terminal. At this time, the terminal displays a prompt saying "Please enter a description for this file" and prompts the user to input metadata. For example, the user may input metadata such as "Year-end project report."

[1660] Data storage

[1661] The terminal sends the file name and metadata to the server. The server receives this data and stores it in a database. Specifically, the server uses SQL statements to insert the file name, metadata, and creation date and time into the database.

[1662] Searching for files

[1663] When a user wants to find a specific file, they enter a search query into their device, for example, searching for "year-end report." The device then sends this query to the server, which retrieves all the metadata from the database and calculates the similarity to the search query. This calculation is done using machine learning algorithms such as TF-IDF and Word2Vec.

[1664] Presenting search results

[1665] Based on the calculated similarity score, the server identifies the most relevant filenames and returns them to the device, which then displays them to the user as something like "The best file is: Project Report.docx."

[1666] Editing Metadata

[1667] If the user wants to edit or modify the already saved metadata, the terminal provides an editing interface and receives new metadata from the user, which the terminal sends to the server, which then updates the existing record in the database.

[1668] Specific examples

[1669] File creation example: A user creates a new file "Project Plan.docx" and the terminal prompts, "Please enter a description for this file." If the user enters "Project plan for next year," the terminal sends this information to the server, which stores it in a database.

[1670] File search example: If a user searches for "Plan for next year", they enter the search keyword into their device. The device sends this query to the server, which retrieves all the metadata in the database. It then calculates the similarity and identifies the most relevant file, "Project Plan.docx", and returns it to the device. The device displays "The best file is: Project Plan.docx".

[1671] Metadata editing example: If a user wants to change the metadata of "Project Plan.docx" to "Project Plan for Next Year", the terminal provides an editing interface. The user inputs new metadata and the terminal sends it to the server. The server updates the existing record in the database.

[1672] This system allows users to efficiently enter, edit, and search file metadata, enabling them to quickly find the files they need.

[1673] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1674] Step 1:

[1675] When a user creates a new file, they enter a filename into the terminal, for example "Project Report.docx". The input at this point is the "filename", the string the user types into the terminal. The output is the prompt that is displayed on the terminal.

[1676] Step 2:

[1677] The terminal displays a prompt saying "Please enter a description for this file" and prompts the user to enter metadata. The input is "metadata," and the user might enter, for example, "Year-end project report." The output is metadata stored in the terminal's temporary memory.

[1678] Step 3:

[1679] The device sends the filename and metadata to the server using an HTTP POST request. The input is the filename and metadata, and the output is the data sent to the server.

[1680] Step 4:

[1681] The server stores the received data in a database. First, the server opens a database connection. The input is the file name and metadata sent from the terminal, and the output is the record to be stored in the database. Specifically, it executes the SQL statement "INSERT INTO files (file_name, metadata, creation_date) VALUES ('Project report.docx', 'Year-end project report', '2023-10-23')".

[1682] Step 5:

[1683] A user enters a search query to find a specific file, for example, "year-end report." The input is the "search query," which the device sends to the server. The output is the search query sent to the server.

[1684] Step 6:

[1685] The server opens a database connection and retrieves all metadata by executing a SQL statement such as "SELECT file_name, metadata FROM files". The input is the query to the database and the output is a list of the retrieved metadata.

[1686] Step 7:

[1687] The server calculates the similarity between the retrieved metadata and the user's search query, using, for example, TF-IDF (Term Frequency-Inverse Document Frequency). The input is the search query and a list of metadata, and the output is a similarity score for each file.

[1688] Step 8:

[1689] The server identifies the most relevant files based on the calculated similarity scores: the input is the similarity score, and the output is the filename with the highest score.

[1690] Step 9:

[1691] The server returns the most relevant filename to the terminal. The input is the identified filename, and the output is the filename returned to the terminal. The returned data is in JSON format.

[1692] Step 10:

[1693] The terminal will display to the user, "The best file is: Project Report.docx." The input is the file name returned by the server, and the output is the search results presented to the user.

[1694] Step 11:

[1695] When a user edits or modifies already saved metadata, the terminal provides an editing interface and receives new metadata from the user. The input is the new metadata edited by the user, which the terminal sends to the server. The output is the new metadata sent to the server.

[1696] Step 12:

[1697] The server updates an existing record in the database. The input is the new metadata, specifically by executing the SQL statement "UPDATE files SET metadata = 'newmetadata' WHERE file_name = 'projectreport.docx'". The output is the updated database record.

[1698] (Application example 1)

[1699] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1700] In factories and other workplaces, managing and quickly searching a large number of documents is essential, and effective management methods are needed. However, current document management systems have the drawback of being time-consuming to operate, as metadata input and editing is cumbersome and search accuracy is insufficient. Factories, in particular, need systems that can efficiently input metadata using voice input and touch interfaces and quickly search for related documents.

[1701] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1702] In this invention, the server includes an interactive means for inputting file names and corresponding metadata when a user creates a file, a storage means for storing the file names and metadata in a database, a search means for searching the database for matching files when a user inputs a search query, a similarity calculation means for calculating the similarity between the search query and the metadata, an output means for presenting the most similar file to the user, and a means for inputting the user-entered metadata via voice or a touch interface. This allows document metadata to be efficiently entered and managed, improving search accuracy and enabling desired documents to be found quickly.

[1703] "User" means a person or end user who operates the system and inputs, searches, and edits data.

[1704] A "file name" is a text-based name set by the user to identify an individual file.

[1705] "Metadata" is data that represents additional information associated with a file, detailing the contents and characteristics of the file.

[1706] An "interaction means" is an interface used by a user to input and edit data, including in particular voice input and touch interfaces.

[1707] A "storage mechanism" is a mechanism for recording and maintaining file names and metadata in a database.

[1708] The "search means" is a function for searching for related files from the database based on a query entered by the user.

[1709] The "similarity calculation means" is an algorithm for calculating the similarity between a user's search query and metadata in the database.

[1710] The "output means" is a mechanism for providing the user with information on the most relevant file based on the calculated similarity.

[1711] The present invention relates to a system for efficiently managing and quickly searching for a large number of documents (such as blueprints, maintenance procedures, and operation manuals) used in a factory. Specific embodiments of the system will be described in detail below.

[1712] The system includes a means for users to interactively enter, store, and retrieve metadata.

[1713] Hardware and software used

[1714] Hardware: Robots deployed in factories (with voice recognition and touchscreen displays)

[1715] Software: Python, SQLite (for database management), Scikit-learn (machine learning library)

[1716] Details of data processing and calculation

[1717] 1. Database connection and metadata storage

[1718] The server connects to an SQLite database and creates a table to store document information. When a user creates a new document, the robot prompts the user, "Please enter a description for this document." The user provides metadata via voice input or touch panel input, and the robot sends the metadata to the server and stores it in the database.

[1719] 2. Metadata search and similarity calculation

[1720] When a user searches for a specific document, they input a search query into the robot (via voice or touch panel). The server sends this search query to the database and retrieves the stored metadata. It then uses Scikit-learn's TfidfVectorizer and cosine_similarity function to calculate the similarity between the search query and the stored metadata.

[1721] 3. Presentation of search results

[1722] The server identifies the most relevant document based on the calculated similarity and sends that information back to the robot, which displays to the user, "The best document is: <document name>."

[1723] 4. Editing Metadata

[1724] If a user wants to edit the metadata of an existing document, the robot provides an editing interface, and when the user enters new metadata, it sends it to the server, updating the existing record.

[1725] Specific examples

[1726] For example, if a user adds a new document called "Factory Machine Maintenance Procedures.pdf", the following happens:

[1727] 1. The robot displays the prompt, "Please enter a description of this document."

[1728] 2. The user speaks "Routine maintenance procedures."

[1729] 3. The robot sends this to the server and stores it in the database.

[1730] If a user searches for "maintenance procedures," the experience progresses as follows:

[1731] 1. A user enters the search query "maintenance procedures" into the robot.

[1732] 2. The server receives the query, retrieves the metadata from the database, and performs the similarity calculation.

[1733] 3. The server sends the most relevant document back to the robot, which then displays, "The best document is: Factory Machine Maintenance Procedures.pdf."

[1734] Prompt Sentence Examples

[1735] For example, it can be used as follows when executing a Python program:

[1736] python

[1737] Documentation

[1738] create_document("Factory Machine Maintenance Procedure.pdf", "Periodic Maintenance Procedure")

[1739] Document Search

[1740] print(search_documents("Maintenance Procedures"))

[1741] Metadata Editing

[1742] edit_metadata("Factory Machine Maintenance Procedure.pdf", "Monthly Scheduled Maintenance Procedure")

[1743] This allows the system to efficiently manage and quickly search a large number of documents within a factory.

[1744] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1745] Step 1:

[1746] When a user creates a new file, the robot (terminal) displays a prompt saying, "Please enter a description of this document." The user provides metadata via voice input or touch panel.

[1747] Input: User-entered file name and metadata (e.g., "Factory Machine Maintenance Procedures.pdf", "Routine Maintenance Procedures")

[1748] Output: Send collected filenames and metadata to the server

[1749] Step 2:

[1750] The server receives the file name and metadata sent from the device and stores them in an SQLite database by opening a database connection and inserting the file name, metadata, and creation date and time into a table.

[1751] Input: File name and metadata sent from the device (e.g., "Factory Machine Maintenance Procedures.pdf", "Routine Maintenance Procedures")

[1752] Output: New document information saved in the database

[1753] Step 3:

[1754] When a user enters a search query, the robot (terminal) receives the query from the user and sends it to the server.

[1755] Input: The search query entered by the user (e.g., "maintenance procedures")

[1756] Output: Sends the search query to the server

[1757] Step 4:

[1758] The server retrieves all metadata from the database and performs a similarity calculation to find metadata that matches the user's search query.

[1759] Input: User search query and metadata retrieved from the database

[1760] Data processing: Generate TF-IDF vectors for search queries and metadata

[1761] Data arithmetic: Calculate cosine similarity and identify the most relevant metadata

[1762] Output: Identify the most relevant files based on a similarity calculation

[1763] Step 5:

[1764] The server returns the most relevant filenames based on the calculated similarity to the robot (terminal).

[1765] Input: The most related filenames based on the similarity calculation

[1766] Output: Sends the most relevant filename to the terminal

[1767] Step 6:

[1768] The robot (terminal) displays the search results to the user, specifically displaying "The best document is: <Document name>."

[1769] Input: The file name returned by the server

[1770] Output: Displaying search results to the user

[1771] Step 7:

[1772] When a user edits or modifies already saved metadata, the robot (terminal) provides an editing interface, receives new metadata from the user, and sends it to the server.

[1773] Input: New metadata entered by the user (e.g., "Monthly scheduled maintenance procedures")

[1774] Output: Send the new metadata to the server

[1775] Step 8:

[1776] The server receives the new metadata sent from the device and updates the existing record in the SQLite database, specifically by replacing the metadata for the corresponding file name with the new one.

[1777] Input: New metadata sent from the device

[1778] Output: Metadata in the database is updated

[1779] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1780] The present invention is a system that uses an emotion engine to recognize a user's emotions when creating, managing, and searching for files, and provides an appropriate interface and search results according to those emotions. This system promotes file metadata input and adjusts search results based on the user's emotions, thereby achieving a better user experience.

[1781] 1. Emotion engine integration

[1782] The device is equipped with an emotion engine that recognizes emotions in real time from the user's facial expressions, tone of voice, and input method.

[1783] 2. Creating a file and entering metadata

[1784] When a user creates a new file, they set the file name, for example, "Project Report.docx."

[1785] The device will prompt you to "Enter a description for this file" and the emotion engine will analyze the user's current emotions.

[1786] If the emotion engine recognizes that the user is feeling stressed, the device will provide a relaxing interface and encourage input.

[1787] A user enters metadata such as "year-end project report."

[1788] 3. Data storage

[1789] The device sends the file name and metadata to the server.

[1790] To store the received data in a database, the server opens a database connection and executes an SQL statement to insert the file name, metadata, and creation date and time into the database.

[1791] 4. Search for files

[1792] A user enters a search query, for example, "year-end report."

[1793] The terminal sends a search query from the user to the server.

[1794] The server opens a database connection and executes a SQL statement to retrieve metadata for all files.

[1795] The server uses a machine learning algorithm to calculate the similarity between the acquired metadata and the user's search query.

[1796] The emotion engine analyzes the user's emotions, and if the user is in a hurry, for example, it prioritizes the information that needs to be returned most quickly and identifies the most relevant files.

[1797] The server returns the most relevant filename to the terminal.

[1798] The device will display "Best file is: <filename>" to the user.

[1799] 5. Editing Metadata

[1800] If the user wishes to edit or modify the metadata, the terminal provides an editing interface.

[1801] The user inputs new metadata, for example, changing it to "Next year's project plan."

[1802] The terminal sends the new metadata to the server.

[1803] The server opens a database connection and executes SQL statements to update the existing metadata.

[1804] The server confirms that the update was successful and sends it to the terminal, and the terminal notifies the user that the metadata update was successful.

[1805] Specific examples

[1806] File creation example: When a user creates a file called "Meeting minutes.docx," the device prompts the user, "Please enter a description for this file." If the emotion engine recognizes that the user is tired, it presents a friendly interface to assist input. The user enters "Monthly meeting minutes," and the device sends this information to the server, which stores it in a database.

[1807] File search example: When a user searches for "monthly meeting," the device sends this query to the server. The server retrieves metadata from the database and calculates similarity. If the emotion engine recognizes that the user is in a hurry, it prioritizes the most relevant files. The server identifies "Meeting Minutes.docx" and sends it back to the device. The device displays, "The best file is: Meeting Minutes.docx."

[1808] Metadata editing example: If a user wants to change the metadata of "Meeting Minutes.docx" to "Minutes of Quarterly Meeting", an editing interface is provided. The user enters new metadata and the terminal sends it to the server. The server updates the existing record in the database and notifies the terminal that the update was successful. The terminal notifies the user that the update was successful.

[1809] As described above, by integrating the emotion engine, we have created a system that can provide a flexible interface that responds to the user's emotional state and highly accurate search results.

[1810] The processing flow will be explained below.

[1811] Program processing flow (when creating a file)

[1812] Step 1:

[1813] The user decides to create a new file and enters a file name, for example "Project Report.docx."

[1814] Step 2:

[1815] The terminal receives the filename and displays the prompt "Please enter a description for this file."

[1816] Step 3:

[1817] The emotion engine built into the device analyzes the user's facial expressions and tone of voice to recognize emotions in real time.

[1818] Step 4:

[1819] The device provides an interface based on the user's emotions, for example, if the user is feeling stressed, it uses a relaxing interface.

[1820] Step 5:

[1821] The user enters a description for the file, for example, "End of Year Project Report."

[1822] Step 6:

[1823] The device sends the entered file name and metadata to the server.

[1824] Step 7:

[1825] The server opens a database connection and executes an SQL statement to insert the file name, metadata, and creation date into the database.

[1826] Step 8:

[1827] The server confirms that the save was successful and sends that information to the device.

[1828] Step 9:

[1829] The terminal notifies the user that the file has been successfully saved.

[1830] Program processing flow (when searching for files)

[1831] Step 1:

[1832] A user enters a search query to find a specific file, for example, "end of year report."

[1833] Step 2:

[1834] The terminal receives the search query and sends it to the server.

[1835] Step 3:

[1836] The server opens a database connection and executes a SQL statement to retrieve metadata for all files.

[1837] Step 4:

[1838] Using the metadata acquired by the server, a machine learning algorithm is used to calculate the similarity to the user's search query.

[1839] Step 5:

[1840] The emotion engine built into the device analyzes the user's current emotions and prioritizes displaying results quickly if, for example, the user is in a hurry.

[1841] Step 6:

[1842] The server calculates the similarity scores and identifies the most similar files.

[1843] Step 7:

[1844] The server sends the specified file name to the terminal.

[1845] Step 8:

[1846] The device displays "The best file is: <filename>" to the user.

[1847] Program processing flow (when editing metadata)

[1848] Step 1:

[1849] If the user wishes to edit or modify the metadata for an existing file, the user selects the file.

[1850] Step 2:

[1851] The device displays the existing metadata for the file and provides an editing interface.

[1852] Step 3:

[1853] The user enters new metadata, for example, changing it to "Project plan for next year."

[1854] Step 4:

[1855] The device sends the new metadata to the server.

[1856] Step 5:

[1857] The server opens a database connection and executes SQL statements to update the existing metadata.

[1858] Step 6:

[1859] The server confirms that the update was successful and sends that information to the device.

[1860] Step 7:

[1861] The terminal notifies the user that the metadata update was successful.

[1862] Emotion Engine Processing Flow

[1863] Step 1:

[1864] When a user operates the system, the device's built-in camera and microphone capture the user's facial expressions and tone of voice.

[1865] Step 2:

[1866] The device's emotion engine analyzes the captured data in real time to recognize the user's emotional state.

[1867] Step 3:

[1868] The device will provide an appropriate interface based on the recognized emotion, for example, using relaxing colors and fonts if the user is tired.

[1869] Step 4:

[1870] The device transmits the user's emotional state to the server, which is then taken into account when searching for files and entering metadata.

[1871] Step 5:

[1872] The server adjusts the parameters of the search algorithm based on the emotional data and returns the optimal results according to the user's situation.

[1873] As described above, by integrating an emotion engine, the system of the present invention can provide a flexible interface that responds to the user's emotions and highly accurate search results.

[1874] Example 2

[1875] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1876] The present invention aims to provide a better user experience by appropriately recognizing a user's emotions when creating, managing, and searching for files, and providing an interface and search results that reflect those emotions. Conventional systems do not respond to user emotions, which can cause users to feel stressed when creating or searching for files. Another problem is that it can be difficult for users to quickly find the right file when they are in a hurry.

[1877] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1878] In this invention, the server includes emotion recognition means for recognizing a user's emotion in real time, adjustment means for providing an interface according to the user's emotion, and similarity calculation means for calculating the similarity between the search query and metadata. This allows the interface and search results to be adjusted based on the user's emotion, enabling the user to quickly find or create the files they need without feeling stressed.

[1879] "User" means a person who uses the system to create, manage, and retrieve files.

[1880] A "file" is a piece of digital data, such as a document or image, that users create, store, and search.

[1881] "Metadata" is information associated with a file, including additional information such as the file name, description, and tags.

[1882] An "interaction means" is a means that provides an interface for a user to interact with the system and input information.

[1883] "Storage" refers to the mechanism by which filenames and metadata are stored in a database.

[1884] The "search means" is a function for searching files in the database and providing the user with results appropriate for the file.

[1885] "Similarity calculation means" refers to a mechanism for calculating the similarity between a user's search query and a file's metadata.

[1886] The "output means" is a means for presenting search results to the user.

[1887] "Emotion recognition means" refers to a system that recognizes emotions in real time from a user's facial expressions, tone of voice, input method, etc.

[1888] The "adjustment means" refers to a function that adjusts the interface and search results according to the user's emotions detected by the emotion recognition means.

[1889] A "machine learning algorithm" refers to an algorithm that analyzes data and learns patterns and rules to calculate similarity and optimize searches.

[1890] The present invention is a system that uses an emotion engine to recognize a user's emotions when creating, managing, and searching for files, and provides an appropriate interface and search results based on those emotions. This system promotes file metadata entry and adjusts search results based on the user's emotions, thereby achieving a better user experience.

[1891] Emotion engine integration

[1892] The device is equipped with an emotion engine that recognizes emotions in real time from the user's facial expressions, tone of voice, input method, etc. The emotion engine uses, for example, Microsoft's Azure Face API for facial recognition technology and Google Cloud Speech-to-Text for voice recognition technology.

[1893] Creating a file and entering metadata

[1894] When a user creates a new file, they set the file name, for example, "Project Report.docx."

[1895] The device will prompt you to "Enter a description for this file" and the emotion engine will analyze the user's current emotions.

[1896] If the emotion engine detects that the user is feeling stressed, the device will provide a relaxing interface and encourage input, such as changing the background color or playing relaxing music.

[1897] A user enters metadata such as "year-end project report."

[1898] Data storage

[1899] The device sends the file name and metadata to the server.

[1900] The server opens a database connection, executes a SQL statement that saves the file name, metadata, and creation date and time in the database, and saves the data.

[1901] Searching for files

[1902] A user enters a search query, for example, "year-end report."

[1903] The terminal sends a search query to the server.

[1904] The server opens a database connection and executes a SQL statement to retrieve metadata for all files.

[1905] The server uses a machine learning algorithm to calculate the similarity between the acquired metadata and the user's search query.

[1906] The emotion engine analyzes the user's emotions, and if the user is in a hurry, for example, it prioritizes the information that needs to be returned most quickly and identifies the most relevant files.

[1907] The server returns the most relevant filename to the terminal.

[1908] The device will display to the user "The best file is: Meeting Minutes.docx."

[1909] Editing Metadata

[1910] If the user wishes to edit or modify the metadata, the terminal provides an editing interface.

[1911] The user inputs new metadata, for example, changing it to "Next year's project plan."

[1912] The terminal sends the new metadata to the server.

[1913] The server executes a SQL statement to update an existing record in the database.

[1914] The server confirms that the update was successful and notifies the terminal.

[1915] The terminal notifies the user of the success of the update.

[1916] Specific examples

[1917] File creation example

[1918] When a user creates a file called "Meeting Minutes.docx," the device prompts the user, "Please enter a description for this file." If the emotion engine detects that the user is tired, it presents a friendly interface to assist input. The user types "Monthly Meeting Minutes," and the device sends this information to the server, which stores it in a database.

[1919] File search example

[1920] When a user searches for "monthly meeting," the device sends this query to the server. The server retrieves metadata from the database and calculates similarity. If the emotion engine recognizes that the user is in a hurry, it prioritizes the most relevant files. The server identifies "Meeting Minutes.docx" and sends it back to the device. The device displays, "The best file is: Meeting Minutes.docx."

[1921] Metadata editing example

[1922] If a user wants to change the metadata of "Meeting Minutes.docx" to "Minutes of Quarterly Meeting," an editing interface is provided. The user enters new metadata, and the terminal sends it to the server. The server updates the existing record in the database and notifies the terminal that the update was successful. The terminal notifies the user that the update was successful.

[1923] As described above, by integrating the emotion engine, we have created a system that provides a flexible interface and highly accurate search results that respond to the user's emotional state.

[1924] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1925] Step 1: Integrating the Emotion Engine

[1926] The device uses an emotion engine to recognize the user's facial expressions, tone of voice, and input method in real time. The emotion engine uses, for example, a general face recognition API for facial recognition technology or a voice recognition API for voice recognition technology. Specifically, it acquires data from the camera and microphone and inputs it into an emotion recognition model. The emotion model analyzes the data and outputs the user's emotional state (e.g., stressed, relaxed, etc.).

[1927] Input: Real-time data from camera and microphone

[1928] Data processing: Emotion analysis using face and voice recognition APIs

[1929] Output: User's emotional state

[1930] Step 2: Enter a file name

[1931] The terminal prompts the user to enter a file name when creating a new file, and the user enters the file name and sends it to the terminal (e.g., "Project Report.docx").

[1932] Input: The file name entered by the user

[1933] Output: Send filename to terminal

[1934] Step 3: Prompt for Metadata

[1935] The device displays a prompt saying, "Please enter a description for this file," and the emotion engine analyzes the user's current emotion. If the emotion engine determines that the user is feeling stressed, the device provides a relaxing interface (e.g., changing the background color, playing relaxing music) to encourage input.

[1936] Input: prompt after entering user's emotional state and file name

[1937] Data manipulation: adjusting the interface based on emotions

[1938] Output: Display interface and prompts to the user

[1939] Step 4: Entering Metadata

[1940] The user inputs metadata (e.g., "end of year project report"), and the device receives this input and begins the process of saving the data.

[1941] Input: User-entered metadata

[1942] Output: Sending metadata to the device

[1943] Step 5: Sending data

[1944] The device sends the entered file name and metadata to the server, which prepares to save the data.

[1945] Input: Filename and metadata

[1946] Output: Send data to the server

[1947] Step 6: Save your data

[1948] The server opens a database connection, executes a SQL statement to store the filename, metadata, and creation date and time in the database, and then saves the data. For example, it executes the SQL statement "INSERT INTO files (filename, metadata, created_at) VALUES ('Project report.docx', 'End of year project report', NOW())".

[1949] Input: Filename and metadata

[1950] Data processing: Generate SQL statements and save them to the database

[1951] Output: Confirmation saved in the database

[1952] Step 7: Enter a search query

[1953] A user enters a search query into a terminal (e.g., "year-end report"), and the terminal sends the search query to the server.

[1954] Input: The search query entered by the user

[1955] Output: Sending a search query to the server

[1956] Step 8: Retrieving Metadata from the Database

[1957] The server opens a database connection and executes a SQL statement to retrieve all file metadata, for example the SQL statement "SELECT filename, metadata FROM files" to retrieve all metadata.

[1958] Input: Search query

[1959] Data processing: SQL statement generation, metadata acquisition

[1960] Output: Retrieved metadata

[1961] Step 9: Calculate similarity

[1962] The server runs machine learning algorithms to calculate the similarity between the retrieved metadata and the user's search query. For example, it uses natural language processing models to evaluate the similarity between the search query and the metadata. An emotion engine analyzes the user's emotions and prioritizes the most relevant files if the user is in a hurry.

[1963] Input: Search query and retrieved metadata

[1964] Data processing: Similarity calculation using machine learning algorithms

[1965] Output: Identifying the most relevant files

[1966] Step 10: Output search results

[1967] The server returns the most relevant filename to the terminal, which displays the message "The best file is: <filename>" to the user.

[1968] Input: A specified file name

[1969] Output: Displayed to user as search result

[1970] Step 11: Editing Metadata

[1971] If the user wants to edit or modify the metadata, the terminal provides an editing interface. The user inputs new metadata (e.g., "Project plan for next year") and the terminal transmits the new metadata to the server.

[1972] Input: New metadata entered by the user

[1973] Output: Sending new metadata to the server

[1974] Step 12: Update the Metadata

[1975] The server executes SQL statements to update existing records in the database, for example, the SQL statement "UPDATE files SET metadata = 'Next Year's Project Plan' WHERE filename = 'Project Report.docx'".

[1976] Input: New Metadata

[1977] Data processing: SQL statement generation, database update

[1978] Output: Confirmation of successful database update

[1979] Step 13: Notification of successful update

[1980] The server confirms that the update was successful and notifies the terminal, which then notifies the user of the success of the update.

[1981] Input: Confirmation of successful database update

[1982] Output: Notify user that update was successful

[1983] (Application example 2)

[1984] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1985] In conventional file creation, management, and search systems, it was difficult to provide an appropriate interface or search results when the user was in an emotional state, such as when they were tired or stressed. As a result, the user's work efficiency decreased and it could even lead to incorrect file operations. Therefore, the purpose of this invention is to solve these problems and provide a system that provides a flexible interface and highly accurate search results that respond to the user's emotions.

[1986] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1987] In this invention, the server includes an interaction means for inputting a file name and corresponding metadata when a user creates a file, a storage means for storing the file name and metadata in a database, a search means for searching the database for matching files when a user inputs a search query, a similarity calculation means for calculating a similarity between the search query and the metadata, an output means for presenting the most similar file to the user, an emotion recognition means for analyzing the user's facial expression and tone of voice to recognize their emotion, and an emotion response means for adjusting the interface of the interaction means and the output means based on the user's emotion, thereby making it possible to provide an interface and adjust search results in accordance with the user's emotion.

[1988] The "interactive means" refers to a means for interacting with the user to prompt the user to enter input content when the user creates a file or inputs metadata.

[1989] The "storage means" is a means for storing the filenames and corresponding metadata created by the user in a database.

[1990] A "searching means" is a means for searching a database for matching files based on a search query entered by a user.

[1991] The "similarity calculation means" is a means for calculating the similarity between a search query and metadata.

[1992] The "output means" is a means for presenting the most similar file to the user.

[1993] The "emotion recognition means" is a means for analyzing the user's facial expressions and tone of voice to recognize the user's emotions.

[1994] The "emotion response means" is a means for adjusting the interface of the dialogue means and the output means based on the user's emotions.

[1995] This system recognizes a user's emotions and provides appropriate interfaces and search results based on those emotions. This system consists of smart glasses with an emotion engine and a file management and search system using a cloud database.

[1996] 1. System Configuration

[1997] This system consists of the following main components:

[1998] Smart glasses: Equipped with emotion recognition means that analyze the user's facial expressions and tone of voice in real time.

[1999] Cloud Database: Use a cloud service such as Firebase to store file names and metadata.

[2000] Machine learning algorithms: Use machine learning libraries such as TensorFlow to calculate the similarity between search queries and metadata.

[2001] 2. Data Creation and Management

[2002] When a user creates a new file, the smart glasses act as a "conversational tool." Specifically, they recognize the user's current emotion and display appropriate prompts accordingly. For example, if the user is feeling stressed, they will be prompted with a gentler tone. The generated file name and metadata are then stored in a cloud database.

[2003] 3. Searching for data

[2004] When a user enters a search query, the smart glasses and a cloud server work together to retrieve data. The cloud server calculates the similarity between the search query and all metadata in the database. During this process, the server analyzes the user's sentiment in real time and prioritizes highly relevant files to quickly display search results if the user is in a hurry.

[2005] 4. Editing Metadata

[2006] If the user wishes to edit or modify the metadata, the smart glasses act as an editing interface, again adapting to the user's emotional state. The new metadata is updated to the cloud database, and the success is confirmed.

[2007] Specific examples

[2008] File Creation Example: When a user creates a "Maintenance Report," the smart glasses prompt them to "Enter a description for this report." If the emotion engine recognizes that the user is tired, a gentle interface is presented to encourage input. Once the user completes the description, the data is saved to a cloud database.

[2009] File search example: When a user searches for "maintenance record," the smart glasses send this query to the cloud server. The server retrieves metadata from the database and calculates similarity. If the emotion engine recognizes that the user is in a hurry, it will prioritize the most relevant files. For example, "maintenance report" is identified and sent back to the smart glasses.

[2010] Metadata Editing Example: When a user changes the metadata of "Maintenance Report" to "Scheduled Maintenance Report", the emotion engine adjusts the editing interface based on the user's emotional state, enters the new metadata, and notifies the cloud database that the update was successful.

[2011] Prompt Sentence Examples

[2012] "Please explain the work log management and data search system for factory robots that uses an emotion engine. In particular, please explain in detail the specific methods and benefits of the work log input and search function based on user emotions."

[2013] The above is the "Mode for Carrying Out the Invention."

[2014] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2015] Step 1:

[2016] emotion recognition

[2017] Description: The device (smart glasses) analyzes image data (facial expressions) and audio data (tone of voice) collected from the user in real time to recognize the user's emotions. For this purpose, an emotion recognition API is used. It receives image data and audio data as input and generates analyzed emotional data as output.

[2018] Specific behavior:

[2019] 1. The device uses the camera and microphone to capture the user's facial and voice data.

[2020] 2. The acquired data is sent to the emotion recognition API, which runs an algorithm to analyze emotions.

[2021] 3. Receive a response from the emotion recognition API containing the user's emotional state (e.g., stress, joy, fatigue, etc.).

[2022] Step 2:

[2023] File creation and metadata entry

[2024] Description: The terminal provides a dialogue interface for the user to input a file name and corresponding metadata when creating a file. The tone of the interface is adjusted based on the result of emotion recognition. It receives emotion data and input to the user interface (file name, metadata) as input, and generates the input file name and metadata as output.

[2025] Specific behavior:

[2026] 1. The terminal will prompt you to "Enter a description for this file."

[2027] 2. The user enters a file name and metadata, for example, "End of Year Project Report."

[2028] 3. Collect input data from the dialogue interface and adjust tone based on emotion to encourage input.

[2029] Step 3:

[2030] Data storage

[2031] Description: The device sends the collected file name and metadata to the server, which then stores them in a cloud database (e.g., Firebase). It receives the file name and metadata as input and generates the database storage result (success or failure) as output.

[2032] Specific behavior:

[2033] 1. The device packages the filename and metadata and sends it to the server.

[2034] 2. The server connects to a cloud database and stores the file name and metadata.

[2035] 3. If the save is successful, the server notifies the device of the result.

[2036] Step 4:

[2037] Data Search

[2038] Description: When a user enters a search query, the device sends it to the server. The server retrieves metadata from a cloud database, calculates the similarity with the search query, and returns the best search results based on emotion recognition. It takes the search query and emotion data as input and generates search results as output.

[2039] Specific behavior:

[2040] 1. A user enters a search query into their device, for example, "year-end report."

[2041] 2. The device sends the search query to the server.

[2042] 3. The server queries the cloud database to retrieve all metadata matches.

[2043] 4. Using a similarity calculation means, calculate the similarity between the search query and the metadata.

[2044] 5. Based on the results of emotion recognition, the most relevant results are selected and sent back to the device as search results.

[2045] Step 5:

[2046] Metadata Editing

[2047] Description: When a user wants to edit or modify metadata, the terminal provides an editing interface. It receives new metadata as input and generates updated results as output. The interface is adjusted based on emotions to allow the user to easily edit.

[2048] Specific behavior:

[2049] 1. The user wishes to modify the metadata of an existing file on the device.

[2050] 2. The device recognizes emotions and adjusts the interface according to the user's emotions.

[2051] 3. The user enters new metadata, for example, "Project plan for next year."

[2052] 4. Send the new metadata to the server, which updates the existing record in the cloud database.

[2053] 5. The server notifies the user that the update was successful, and the device notifies the user of the result.

[2054] The above are the specific processing steps of the system that realizes the application example.

[2055] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2056] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2057] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2058] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2059] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2060] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2061] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2062] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2063] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2064] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2065] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2066] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2067] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2068] 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.

[2069] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2070] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2071] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific processing may be a single processor.

[2072] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2073] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2074] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2075] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2076] The following is further disclosed regarding the above embodiment.

[2077] (Claim 1)

[2078] an interactive means for a user to input a file name and corresponding metadata when creating a file;

[2079] storage means for storing said filenames and metadata in a database;

[2080] search means for searching said database for matching files when a user enters a search query;

[2081] a similarity calculation means for calculating a similarity between the search query and metadata;

[2082] output means for presenting the most similar files to a user;

[2083] A system including:

[2084] (Claim 2)

[2085] 10. The system of claim 1, further comprising means for using a machine learning algorithm for metadata similarity calculation.

[2086] (Claim 3)

[2087] 10. The system of claim 1, further comprising an interaction means for editing or modifying the metadata entered by the user.

[2088] "Example 1"

[2089] (Claim 1)

[2090] an interactive means for a user to input a file name and corresponding metadata when creating a file;

[2091] storage means for storing said filenames and metadata in a database;

[2092] search means for searching said database for matching files when a user enters a search query;

[2093] a similarity calculation means for calculating a similarity between the search query and metadata;

[2094] output means for presenting the most similar files to a user;

[2095] interactive means for editing or modifying the metadata entered by the user;

[2096] A system including:

[2097] (Claim 2)

[2098] 10. The system of claim 1, further comprising means for using a machine learning algorithm for metadata similarity calculation.

[2099] (Claim 3)

[2100] 10. The system of claim 1, further comprising communication means for storing, transmitting, and receiving user-entered file names, metadata, and search queries.

[2101] "Application Example 1"

[2102] (Claim 1)

[2103] an interactive means for a user to input a file name and corresponding metadata when creating a file;

[2104] storage means for storing said filenames and metadata in a database;

[2105] search means for searching said database for matching files when a user enters a search query;

[2106] a similarity calculation means for calculating a similarity between the search query and metadata;

[2107] output means for presenting the most similar files to a user;

[2108] means for allowing user-entered metadata to be entered by voice or touch interface;

[2109] A system including:

[2110] (Claim 2)

[2111] 10. The system of claim 1, further comprising means for using a machine learning algorithm for metadata similarity calculation.

[2112] (Claim 3)

[2113] 10. The system of claim 1, further comprising an interaction means for editing or modifying the metadata entered by the user.

[2114] "Example 2: Combining Emotion Engines"

[2115] (Claim 1)

[2116] an interactive means for a user to input a file name and corresponding metadata when creating a file;

[2117] storage means for storing said filenames and metadata in a database;

[2118] search means for searching said database for matching files when a user enters a search query;

[2119] a similarity calculation means for calculating a similarity between the search query and metadata;

[2120] output means for presenting the most similar files to a user;

[2121] emotion recognition means for recognizing the user's emotions in real time;

[2122] an adjustment means for adjusting the interface and search results according to the user's emotions;

[2123] A system including:

[2124] (Claim 2)

[2125] 10. The system of claim 1, further comprising means for using a machine learning algorithm for metadata similarity calculation.

[2126] (Claim 3)

[2127] 10. The system of claim 1, further comprising an interaction means for editing or modifying the metadata entered by the user.

[2128] "Application example 2 when combining emotion engines"

[2129] Rewriting of claims

[2130] The original claims 1-3 are as follows:

[2131] 1. A system for inputting metadata when creating files and storing and searching them

[2132] 2. Calculating Metadata Similarity Using Machine Learning Algorithms

[2133] 3. Interactive means for editing or correcting metadata

[2134] Extracting new parts

[2135] The following new technological elements are extracted from the application examples:

[2136] 1. Providing dialogue and output methods that respond to emotions through emotion recognition

[2137] 2. Flexible provision of interfaces for work support

[2138] 3. Combining emotion recognition and machine learning to tailor search results

[2139] Thinking about the content of a new invention

[2140] By integrating an emotion engine, the system provides a flexible interface that responds to the user's emotions and assists in the creation, search, and editing of files, thereby improving work efficiency and reducing stress.

[2141] (Claim 1)

[2142] an interactive means for a user to input a file name and corresponding metadata when creating a file;

[2143] storage means for storing said filenames and metadata in a database;

[2144] search means for searching said database for matching files when a user enters a search query;

[2145] a similarity calculation means for calculating a similarity between the search query and metadata;

[2146] output means for presenting the most similar files to a user;

[2147] emotion recognition means for analyzing a user's facial expression and tone of voice to recognize emotions;

[2148] emotion response means for adjusting the interface of the dialogue means or the output means based on the emotion of the user;

[2149] A system including:

[2150] (Claim 2)

[2151] The system of claim 1, further comprising means for using the emotion recognition means and a machine learning algorithm to calculate a similarity between a user's search query and metadata in a database, and for adjusting search results according to the user's emotion.

[2152] (Claim 3)

[2153] 10. The system of claim 1, further comprising an interaction means for editing or modifying user-entered metadata based on emotion recognition.

[2154] The above is the scope of the revised patent claims. [Explanation of symbols]

[2155] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. an interactive means for a user to input a file name and corresponding metadata when creating a file; storage means for storing said filenames and metadata in a database; search means for searching said database for matching files when a user enters a search query; a similarity calculation means for calculating a similarity between the search query and metadata; output means for presenting the most similar files to a user; A system including:

2. The system of claim 1 , further comprising means for using a machine learning algorithm for metadata similarity calculation.

3. 10. The system of claim 1, further comprising an interaction means for editing or modifying the metadata entered by the user.

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