system

Abstract

Provide a system. 【Solution means】 Means for receiving different forms of digital information, Means for classifying the received digital information into symbolic data and video data, Means for analyzing and standardizing the classified symbolic data, Means for analyzing video data using video recognition technology and unifying the format, Means for integrating the standardized symbolic data and video data to generate consistent materials, Means for providing the generated materials to users, Means for acquiring digital video using a smart device and transmitting the video as digital data to a server, Means for identifying a standard information style from the digital data to facilitate the acquisition of digital information, A system including the above.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Technical documents and manuals used within a company are generally created in different formats for each provider manufacturer. For this reason, information is dispersed, making it difficult for engineers to quickly identify the information they need. In addition, there is a problem that the automation process is hindered due to differences in formats, resulting in a decrease in operation efficiency. Therefore, there is a need to unify different formats of documents into a consistent format.

Means for Solving the Problems

[0005] This invention provides a system that accepts information documents in different formats and classifies them into text data and image data. This system analyzes and standardizes the classified text data. Furthermore, it integrates the standardized text data and image data by analyzing and unifying the image data using image recognition technology. By generating and providing integrated, consistent documents to users, it enables rapid and efficient information access.

[0006] An "informational document" refers to a document that records specific knowledge or instructions, and is expressed in various forms such as text, diagrams, and images.

[0007] "Text data" refers to data that is primarily represented as character information within informational documents, and is subject to analysis and standardization using language models.

[0008] "Image data" refers to data that is represented as visual information within an informational document, and is analyzed and standardized in format using image recognition technology.

[0009] "Classification" refers to the act of organizing and distributing an object based on specific criteria, and includes the process of separating informational documents into text data and image data.

[0010] "Analysis" refers to the process of breaking down and understanding information for a specific purpose, and is a method for revealing the characteristics of text data and image data.

[0011] "Standardization" refers to the act of unifying information of different forms and content into a common format or style, with the aim of maintaining consistency throughout the document.

[0012] "Image recognition technology" refers to the technology that allows computers to understand and identify objects within an image, and involves methods for analyzing and standardizing the information in visual data.

[0013] "Integrating" refers to the act of combining separate pieces of information and data into a single entity, and includes the creation of consistent documents by combining standardized text data and image data.

[0014] "Providing to users" refers to the process of delivering the final product to users and making it available for practical use, and includes providing the completed document in a format that can be viewed and downloaded. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when a sentiment engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when a sentiment engine is combined.

Mode for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0019] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0035] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0036] This invention provides a system for unifying information documents of different formats into a consistent format. This system primarily consists of a server and terminals and is designed to allow users to efficiently utilize the information.

[0037] The server is responsible for receiving information documents uploaded by users and classifying them into text data and image data. Regardless of whether the received documents are PDF, Word files, or other digital formats, the server breaks them down into their constituent elements and prepares them for appropriate processing.

[0038] The terminal analyzes the classified text data using natural language processing techniques. In particular, it leverages large-scale language models (LLMs) to identify the hierarchical structure of documents and convert them into a standardized format. This ensures text consistency based on a common language style and glossary.

[0039] Furthermore, the device uses image recognition technology to analyze image data, identify its content, and standardize its format. This means that even if specific diagrams or product part drawings exist in different documents, they will be placed within the document with a consistent appearance.

[0040] As a concrete example, consider a scenario where a user uploads an operation manual for a piece of machinery to the system. The server identifies the text and images in the manual and performs appropriate analysis on each. The terminal then formats the operation procedure text into a standard format and rearranges the machine's design diagrams and images of control buttons in a unified format. The generated document is then provided to the user in a downloadable format.

[0041] In this way, information documents of different formats are unified into a consistent format, allowing users to access information quickly and efficiently.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] Users upload informational documents provided by manufacturers to the system. These documents are in PDF or Word file format, and the server receives this data. Once received, the data is broken down into its constituent elements, such as text and images.

[0045] Step 2:

[0046] The server classifies uploaded documents into text data and image data. It extracts text data from parts of the document that are represented as characters, and separates image data from parts that are treated as visual information.

[0047] Step 3:

[0048] The terminal acquires classified text data and analyzes it using natural language processing techniques. Specifically, it utilizes a large-scale language model (LLM) to recognize the hierarchical structure of the text (e.g., sections and subsections) and adds or modifies the text based on standard terminology and style.

[0049] Step 4:

[0050] The device uses image recognition technology to analyze image data. It identifies the content of each image and standardizes its arrangement and format. For example, even if diagrams of the same type of equipment differ, they are adjusted to be represented in a unified style.

[0051] Step 5:

[0052] The server combines parsed and standardized text data with formatted image data. The integrated information is then generated as a document according to a unified template. The terminal prepares to provide this completed document to the user.

[0053] Step 6:

[0054] Users can preview the generated, standardized document. They can provide feedback as needed, and the server will make final adjustments based on that feedback. The finalized document is then provided to the user for download.

[0055] (Example 1)

[0056] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0057] Information is often generated in various formats, making it difficult to organize it efficiently and consistently. This leads to inefficient information utilization and wasted time and effort.

[0058] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0059] In this invention, the server includes means for receiving information in different formats, means for classifying the received information into character data and visual data, and means for analyzing and standardizing the classified character data. This enables the information to be organized quickly, efficiently, and in a consistent format, making it easily accessible and usable by users.

[0060] "Different formats" refers to a state in which information exists in various digital formats.

[0061] "Information" refers to all digital content, including text and visual data.

[0062] "Character data" refers to the parts of information that are represented as characters or symbols.

[0063] "Visual data" refers to the parts of information that are visually represented as images or diagrams.

[0064] "Classification" refers to the process of separating information into text data and visual data.

[0065] "Analysis" refers to the process of understanding information or the content of its elements and deriving its structure.

[0066] "Standardization" refers to the process of unifying parsed character data into a common style or format.

[0067] "Visual recognition technology" refers to technologies used to identify the content of visual data and understand its meaning.

[0068] "Consistent information" refers to information that has been converted into a unified format.

[0069] "User" refers to the entity that uses the system to upload and download information.

[0070] This system is designed to unify information in different formats into a consistent format. This allows users to efficiently utilize information in various formats.

[0071] The server is responsible for receiving information from the user. The server first classifies the information into text data and visual data. For various file formats such as PDF and Word, it can use dedicated analysis libraries to decompose the data and extract its contents appropriately. For example, in the case of a PDF file, a PDF analysis library is used to extract text and images. This divides the information into its constituent elements, preparing it for the next processing step.

[0072] The terminal analyzes and standardizes the character data received from the server. Large-scale language models (LLMs) are used for natural language processing to improve the accuracy of the analysis. For example, a natural language processing framework is used as the language model to identify the hierarchical structure of the information. This analysis ensures that documents are standardized with common formatting and terminology.

[0073] Furthermore, the device uses visual recognition technology to analyze visual data. By recognizing objects in images and standardizing their format, it ensures visual consistency within documents. Cloud-based visual recognition services are used for visual recognition, and the analyzed images are standardized to a specific format.

[0074] A concrete example is a scenario where a user uploads an operation guide for a machine or device. The server receives the guide document and identifies the text and diagram portions. The terminal converts the operation procedure text into a standard format and rearranges the device diagrams and button images in a consistent style. As a result, the user can download a guide with a consistent format.

[0075] As an example of a prompt, you can enter instructions such as, "Please convert the following operation guide to a consistent format. Upload the PDF file." This organizes information in different formats, allowing users to utilize it efficiently.

[0076] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0077] Step 1:

[0078] The server receives information from the user. The input format of this information varies, including PDF and Word documents. To prepare the received information for analysis, the server first identifies the file format. Specifically, it uses an analysis library to classify the information into text data and visual data. Through this process, the server obtains output as a dataset of text and images.

[0079] Step 2:

[0080] The terminal receives character data from the server. The input character data is parsed using natural language processing techniques. The terminal applies a Large-Scale Language Model (LLM) to identify the hierarchical structure of the character data. Through parsing, information that forms the logical structure of the document (e.g., headings, paragraphs) is identified and converted into a standardized format. As a result, the terminal outputs unified text data.

[0081] Step 3:

[0082] The terminal receives visual data from the server and analyzes it using image recognition technology. By utilizing visual recognition technology, it identifies objects and figures within the image. Specifically, it obtains the analysis results from the visual recognition service and unifies the image format based on those results. Through this process, the visual data is output as image data in a unified format.

[0083] Step 4:

[0084] The terminal generates consistent documents based on standardized text data and unified visual data. Using unified text and image data as input, it creates integrated documents using a document generation library. This process generates documents formatted in a way that is easily readable by the user. The final output is a standardized, unified document provided to the user.

[0085] Step 5:

[0086] Users download the generated unified documents. By accessing the system and retrieving documents through the online platform, information in different formats becomes available in a consistent format. Specifically, users select generated documents via the user interface and save them to their devices.

[0087] (Application Example 1)

[0088] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0089] In today's digital information environment, there are many information documents in different formats, making it difficult to unify them into a consistent format that is easy for users to understand. Furthermore, in urban environments, information is diverse, and there is a particular need for systems that allow citizens and city officials to access information quickly and easily.

[0090] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0091] In this invention, the server includes means for receiving digital information in different formats, means for classifying it into symbolic data and image data, and means for integrating the standardized symbolic data and image data to generate consistent materials. This enables users to easily acquire digital information in a standardized form using smart devices, making it possible to utilize information in urban life.

[0092] "Different formats" refers to different file formats or digital formats, resulting in a variety of ways in which information documents can be represented.

[0093] "Digital information" refers to information that is stored or transmitted electronically, including text, images, audio, and video.

[0094] "Symbolic data" refers to data formats that are expressed in written form, such as text and character information.

[0095] "Video data" refers to data formats that are represented as visual information, such as images and videos.

[0096] "Standardization" is the process of converting information that exists in different formats or styles into a unified format or standard.

[0097] "Documents" refer to documents, reports, and other materials that contain organized information and data.

[0098] "Users" refers to individuals or groups who use the system or application, and in this context specifically includes citizens and city employees.

[0099] "Smart devices" refer to portable devices, glasses-type devices, and other devices that provide internet connectivity and a multi-functional platform.

[0100] The system realizing this invention consists of a smart device and a server, which unifies digital information into a consistent format and provides it to the user. The server accepts digital information in different formats. The digital information is classified into symbolic data and image data. The symbolic data is analyzed and standardized using natural language processing technology, and the image data is analyzed using image recognition technology and unified into a consistent format. This utilizes the Python language and Flask as a framework, the OpenAI® GPT model as a generative AI model, and the Google® Cloud Vision API for image analysis.

[0101] The server generates integrated data and provides it in a standardized format. Users can capture information documents using their smartphones or smart glasses and send them to the server. Users can then download the generated, consistent information and access it easily. For example, a citizen can take a picture of local event information with their smartphone and obtain the information in a standardized format.

[0102] Examples of prompts for the generative AI model include, "Please standardize this text document using standard Japanese legal terminology," and "Analyze the images in this report and categorize them appropriately." This makes it possible to organize even irregular documents into a consistent format.

[0103] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0104] Step 1:

[0105] Users capture digital information using smartphones or smart glasses. Input consists of digital documents and images, which are sent to a server. Output is the data uploaded to the server. This involves the specific actions of capturing information using the device's camera function and transmitting it over the network.

[0106] Step 2:

[0107] The server classifies received digital information into text data and image data. The input is digital information sent by the user, and the output is the result of classifying it into two types of data formats. The server analyzes the data format and performs calculations to separate it into symbolic data and image data.

[0108] Step 3:

[0109] The server analyzes and standardizes classified symbolic data using natural language processing techniques. The input is classified symbolic data, and the output is standardized text data. A generative AI model is used to identify the hierarchical structure of documents and unify them into a common format.

[0110] Step 4:

[0111] The server analyzes video data using video recognition technology and standardizes its format. The input is classified video data, and the output is standardized image data. This includes using video recognition technologies such as the Google Cloud Vision API to identify the content of images and format them into appropriate categories and styles.

[0112] Step 5:

[0113] The server integrates standardized text data and unified image data to generate consistent materials. The input is a set of standardized and unified data, and the output is the final, consistent material. The system performs calculations to combine text and image data and present it in a neat format.

[0114] Step 6:

[0115] The server provides users with unified generated documents. The input is unified documents, and the output is a digital file that users can download. It provides a concrete service that allows users to easily access and retrieve information via a web interface.

[0116] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0117] This invention provides a system that optimizes the user experience by combining a system for unifying information documents of different formats into a consistent format with an emotion engine that recognizes user emotions. This system consists of a server and terminals and is effectively operated in both document management and user interface aspects.

[0118] When a user uploads an informational document to the system, the server receives the information and classifies it into text data and image data. The classified data then undergoes appropriate analysis and standardization processes to be reconstructed into a consistent document. Up to this point, the information is organized through basic document unification processes.

[0119] A notable feature of this system is the emotion engine built into the terminal. This engine has the function of analyzing the user's emotions in real time based on the user's input and actions. Through this analysis, it is possible to capture emotional responses such as the user's interest and stress level while they are viewing text.

[0120] Specifically, when the emotion engine detects a change in the user's emotions, the server dynamically adjusts how standardized documents generated based on that information are presented. For example, if a user shows stress from certain content, the device can change the display order of the relevant sections or display additional explanations. Such adjustments are made automatically to improve the user experience.

[0121] Furthermore, for example, when a user is using a product's technical manual, if they indicate they are experiencing difficulty, the emotion engine will provide support by suggesting links to relevant tutorial videos or FAQs. This feature combines consistent information management with emotion-responsive interaction, enabling more personalized information delivery to users.

[0122] In this way, this system, which incorporates an emotion engine, goes beyond mere information unification and enables dynamic information presentation tailored to the user's emotional state. This increases usefulness and adaptability, promoting the effective use of information.

[0123] The following describes the processing flow.

[0124] Step 1:

[0125] Users upload informational documents in different formats to the system. The server accepts these documents and performs preprocessing according to the file format. For example, it extracts text and images from PDF and Word documents.

[0126] Step 2:

[0127] The server classifies the acquired data into text data and image data. Text data is recognized as character information, and image data is treated as visual information. An appropriate classification method is applied according to the various data formats.

[0128] Step 3:

[0129] The server analyzes the classified text data. Using a large-scale language model, it analyzes and standardizes the hierarchical structure of the document. For example, it identifies headings and bullet points within the text to clarify the document's structure.

[0130] Step 4:

[0131] The device uses image recognition technology to analyze image data. Specifically, it identifies objects within the image and resizes or rearranges them into a standard format. This ensures consistency across various images.

[0132] Step 5:

[0133] The terminal integrates the analyzed and standardized text and image data. The server then generates a consistent informational document based on this data and prepares it for delivery to the user.

[0134] Step 6:

[0135] While a user is viewing a generated document, the device's emotion engine monitors the user's emotional state in real time. For example, it estimates emotions based on factors such as the user's operation speed and the time spent at specific points in the document.

[0136] Step 7:

[0137] When the emotion engine detects a specific change in the user's emotion, the server dynamically adjusts how the document is presented based on that information. For example, if the user shows confusion, it will display a more detailed explanation of the relevant section or additional visual aids.

[0138] Step 8:

[0139] The user reviews the revised document again and provides feedback as needed. The server uses the feedback to further optimize the document and provides the user with the final version.

[0140] (Example 2)

[0141] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0142] When information documents exist in multiple formats, unifying them into a consistent format contributes to improving the user experience. However, traditional methods lack not only document uniformity but also dynamic information presentation that responds to the user's emotional reactions. As a result, users may not receive appropriate support when they encounter difficulties or stress with the document content, potentially leading to decreased user understanding and satisfaction.

[0143] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0144] In this invention, the server includes means for accepting information documents of different formats, means for classifying them into text data and image data, means for integrating the standardized text data and image data to generate a consistent document, means for analyzing the user's emotional state in real time, and means for dynamically adjusting the document presentation method based on the analysis results. This enables the unification of information documents as well as personalized information presentation that responds to the user's emotions.

[0145] "Information documents in different formats" refers to documents that have various data representation forms, including text format and image format.

[0146] "Text data" refers to data composed of strings of characters, and is the basic unit for representing documents and texts.

[0147] "Image data" refers to data that represents visual information recorded in digital format.

[0148] Standardization is the process of organizing data with different forms and contents into a unified format and structure.

[0149] "Image recognition technology" is a technology that allows computer systems to identify specific patterns or features from image data.

[0150] A "consistent document" is a document in which various forms of data are integrated and organized into a unified format.

[0151] "Emotional state" is a concept that describes the emotions and mental state a user is experiencing at a particular moment.

[0152] "Real-time analysis" refers to a process where data is processed instantly and results are obtained at the very moment the user inputs or performs an action.

[0153] "Dynamic adjustment" means flexibly changing the system's operation and output according to the situation and conditions.

[0154] As a form of implementing the invention, this system converts information documents of different formats into a unified format and provides personalized information based on the user's emotional state. Details are provided below.

[0155] The server features a user interface for uploading informational documents and classifies the documents received from users into text data and image data. Natural language processing (NLP) techniques are applied to analyze the text data, and image recognition techniques are used to analyze the image data. Machine learning models are utilized in these techniques. Based on the analysis results, the server standardizes the data and generates consistent documents.

[0156] The device is equipped with an emotion engine that analyzes the user's emotional state in real time based on their actions and inputs. This engine performs face tracking and analyzes operation patterns to determine the user's level of interest and stress. If the user experiences stress, the device sends that state to the server.

[0157] For example, if a user shows confusion while using a technical manual, the emotion engine will detect this emotion. The server can then prepare relevant tutorial videos and additional explanatory content to help the user understand better, and the device can display these.

[0158] Examples of prompts for a generative AI model are as follows:

[0159] "How can we analyze the emotions users experience when viewing product manuals and provide additional support information as needed?"

[0160] Such systems enable improved user experience and more efficient access to information.

[0161] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0162] Step 1:

[0163] Users upload informational documents to the system. Different file formats, such as PDFs and Word documents, are used as input. The server begins processing upon acceptance. The server detects the file from the user and sends a confirmation message to the user.

[0164] Step 2:

[0165] The server classifies the received document into text data and image data. At this stage, the input is the entire uploaded document. The server identifies and classifies the text information and images within the document. The text data and image data are output and stored internally.

[0166] Step 3:

[0167] The server analyzes the classified text data using natural language processing (NLP) techniques. Specifically, it analyzes the grammatical structure of the text and extracts keywords. The input is classified text data, and the output is standardized text data based on the analysis results.

[0168] Step 4:

[0169] The server analyzes and standardizes the classified image data using image recognition technology. The input is image data; it analyzes the shape, color, and patterns of the images and converts them into a consistent format. The output is image data in a unified format.

[0170] Step 5:

[0171] The server integrates standardized text and image data to generate a consistent document. The input consists of individual standardized data, and the output is a single, unified document. The server then prepares this generated document for the user.

[0172] Step 6:

[0173] The device uses an emotion engine to analyze the user's emotional state in real time. User operation data and facial expression data are used as input. The device converts this into an emotional state and detects a specific emotion. The output is the user's emotional data.

[0174] Step 7:

[0175] The server dynamically adjusts how generated documents are presented based on the emotional data received from the terminal. The input consists of emotional data and the generated documents. If the user is experiencing stress, the server adjusts to output additional relevant support information and explanations.

[0176] (Application Example 2)

[0177] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0178] While a vast amount of information is currently available on the internet, few systems consider the user's emotions when viewing this information. Users can be overwhelmed by the sheer volume of information, sometimes experiencing stress. Therefore, there is a need for technology that dynamically adjusts how information is displayed according to the user's emotions, thereby improving the user experience.

[0179] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0180] In this invention, the server includes means for accepting information documents of different formats, means for analyzing the user's emotional state, and means for dynamically adjusting the display order of documents based on the analyzed emotional state. This enables the presentation of information that is optimal to the user's emotions.

[0181] "Information documents in different formats" refers to a collection of information that exists in multiple formats, such as text data and image data.

[0182] A "means of acceptance" is a mechanism that allows a system to receive data from an external source and begin processing it.

[0183] A "means of classification" refers to a device or program that has the function of sorting received data into text data and image data according to its nature.

[0184] "Means of standardization" refer to methods and devices for transforming classified data into a consistent format and unifying it.

[0185] "Image recognition technology" refers to computer vision techniques used to analyze the content of image data and extract features.

[0186] A "consistent document" is a document in a standardized format that integrates data from different formats.

[0187] "Means of provision" refers to methods and devices for presenting a consistent set of generated documents to the user in a viewable format.

[0188] The "function to analyze the user's emotional state" is a technology that recognizes emotions based on the user's facial expressions and tone of voice.

[0189] "Means for dynamically adjusting the display order" refers to devices or programs that have the function of automatically changing the display order of content according to the user's emotions.

[0190] To implement this invention, a server, a terminal, and an interface to the user are required. The server first accepts information documents in different formats and classifies them into text data and image data. The classified data is then reconstructed into a consistent document through a standardization process.

[0191] The server uses the device's camera and microphone to collect the user's facial expressions and voice in order to analyze the user's emotional state. This data is processed using emotion analysis software such as Google Cloud Vision API or IBM Watson® Tone Analyzer. Based on the user's emotional state, processing is performed to dynamically adjust the display order and content of documents. Specifically, if the analysis indicates that the user is feeling stressed, the presentation order is changed so that positive content is displayed preferentially.

[0192] In this way, the system provides users with the most relevant information. For example, if sentiment analysis detects stress when a user is reading the morning news, the system will prioritize displaying articles about relaxing hobbies to alleviate their mood. At the same time, if the user shows interest in a particular topic, the system can use a generative AI model to generate new, relevant information.

[0193] An example of a prompt message would be: "Generate detailed information about a topic the user has shown interest in. For example, 'Generate an article that makes you feel positive about the latest sports news.'"

[0194] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0195] Step 1:

[0196] The server accepts information documents in various formats uploaded by users. The information documents are passed to the server as input and are classified into text data and image data. Preparations for text analysis and image analysis are then performed depending on the document format.

[0197] Step 2:

[0198] The server performs a process to standardize classified text data. The input is text data, which is then parsed to convert it into a consistent format. A language model is used to extract the document's hierarchical structure and key points, and the organized text data is output.

[0199] Step 3:

[0200] The server uses image recognition technology to analyze the image data. It receives image data as input, identifies elements within the image, and standardizes their format. During this process, the recognized content is output as structured data.

[0201] Step 4:

[0202] The server integrates standardized text data and unified image data to generate consistent documents. The input consists of pre-processed text and images, which are then merged to create a unified document. This document is output in a format viewable by the user.

[0203] Step 5:

[0204] The device acquires facial expressions and audio from its camera and microphone to analyze the user's emotional state. The input is a real-time video and audio stream, and the user's emotions are analyzed using emotion analysis software. As a result, emotional state data is output.

[0205] Step 6:

[0206] The server dynamically adjusts the display order of documents based on the analyzed emotional state. The input is emotional state data, and a display order algorithm is applied based on this data to output documents that take the user's emotions into consideration. This results in optimized information presentation that reflects the user's interests and stress levels.

[0207] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0208] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0209] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0210] [Second Embodiment]

[0211] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0212] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0213] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0214] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0215] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0216] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0217] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0218] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0219] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0220] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0221] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0222] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0223] This invention provides a system for unifying information documents of different formats into a consistent format. This system primarily consists of a server and terminals and is designed to allow users to efficiently utilize the information.

[0224] The server is responsible for receiving information documents uploaded by users and classifying them into text data and image data. Regardless of whether the received documents are PDF, Word files, or other digital formats, the server breaks them down into their constituent elements and prepares them for appropriate processing.

[0225] The terminal analyzes the classified text data using natural language processing techniques. In particular, it leverages large-scale language models (LLMs) to identify the hierarchical structure of documents and convert them into a standardized format. This ensures text consistency based on a common language style and glossary.

[0226] Furthermore, the device uses image recognition technology to analyze image data, identify its content, and standardize its format. This means that even if specific diagrams or product part drawings exist in different documents, they will be placed within the document with a consistent appearance.

[0227] As a concrete example, consider a scenario where a user uploads an operation manual for a piece of machinery to the system. The server identifies the text and images in the manual and performs appropriate analysis on each. The terminal then formats the operation procedure text into a standard format and rearranges the machine's design diagrams and images of control buttons in a unified format. The generated document is then provided to the user in a downloadable format.

[0228] In this way, information documents of different formats are unified into a consistent format, allowing users to access information quickly and efficiently.

[0229] The following describes the processing flow.

[0230] Step 1:

[0231] Users upload informational documents provided by manufacturers to the system. These documents are in PDF or Word file format, and the server receives this data. Once received, the data is broken down into its constituent elements, such as text and images.

[0232] Step 2:

[0233] The server classifies uploaded documents into text data and image data. It extracts text data from parts of the document that are represented as characters, and separates image data from parts that are treated as visual information.

[0234] Step 3:

[0235] The terminal acquires classified text data and analyzes it using natural language processing techniques. Specifically, it utilizes a large-scale language model (LLM) to recognize the hierarchical structure of the text (e.g., sections and subsections) and adds or modifies the text based on standard terminology and style.

[0236] Step 4:

[0237] The device uses image recognition technology to analyze image data. It identifies the content of each image and standardizes its arrangement and format. For example, even if diagrams of the same type of equipment differ, they are adjusted to be represented in a unified style.

[0238] Step 5:

[0239] The server combines parsed and standardized text data with formatted image data. The integrated information is then generated as a document according to a unified template. The terminal prepares to provide this completed document to the user.

[0240] Step 6:

[0241] Users can preview the generated, standardized document. They can provide feedback as needed, and the server will make final adjustments based on that feedback. The finalized document is then provided to the user for download.

[0242] (Example 1)

[0243] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0244] Information is often generated in various formats, making it difficult to organize it efficiently and consistently. This leads to inefficient information utilization and wasted time and effort.

[0245] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0246] In this invention, the server includes means for receiving information in different formats, means for classifying the received information into character data and visual data, and means for analyzing and standardizing the classified character data. This enables the information to be organized quickly, efficiently, and in a consistent format, making it easily accessible and usable by users.

[0247] "Different formats" refers to a state in which information exists in various digital formats.

[0248] "Information" refers to all digital content, including text and visual data.

[0249] "Character data" refers to the parts of information that are represented as characters or symbols.

[0250] "Visual data" refers to the parts of information that are visually represented as images or diagrams.

[0251] "Classification" refers to the process of separating information into text data and visual data.

[0252] "Analysis" refers to the process of understanding information or the content of its elements and deriving its structure.

[0253] "Standardization" refers to the process of unifying parsed character data into a common style or format.

[0254] "Visual recognition technology" refers to technologies used to identify the content of visual data and understand its meaning.

[0255] "Consistent information" refers to information that has been converted into a unified format.

[0256] "User" refers to the entity that uses the system to upload and download information.

[0257] This system is designed to unify information in different formats into a consistent format. This allows users to efficiently utilize information in various formats.

[0258] The server is responsible for receiving information from the user. The server first classifies the information into text data and visual data. For various file formats such as PDF and Word, it can use dedicated analysis libraries to decompose the data and extract its contents appropriately. For example, in the case of a PDF file, a PDF analysis library is used to extract text and images. This divides the information into its constituent elements, preparing it for the next processing step.

[0259] The terminal analyzes and standardizes the character data received from the server. Large-scale language models (LLMs) are used for natural language processing to improve the accuracy of the analysis. For example, a natural language processing framework is used as the language model to identify the hierarchical structure of the information. This analysis ensures that documents are standardized with common formatting and terminology.

[0260] Furthermore, the device uses visual recognition technology to analyze visual data. By recognizing objects in images and standardizing their format, it ensures visual consistency within documents. Cloud-based visual recognition services are used for visual recognition, and the analyzed images are standardized to a specific format.

[0261] A concrete example is a scenario where a user uploads an operation guide for a machine or device. The server receives the guide document and identifies the text and diagram portions. The terminal converts the operation procedure text into a standard format and rearranges the device diagrams and button images in a consistent style. As a result, the user can download a guide with a consistent format.

[0262] As an example of a prompt, you can enter instructions such as, "Please convert the following operation guide to a consistent format. Upload the PDF file." This organizes information in different formats, allowing users to utilize it efficiently.

[0263] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0264] Step 1:

[0265] The server receives information from the user. The input format of this information varies, including PDF and Word documents. To prepare the received information for analysis, the server first identifies the file format. Specifically, it uses an analysis library to classify the information into text data and visual data. Through this process, the server obtains output as a dataset of text and images.

[0266] Step 2:

[0267] The terminal receives character data from the server. The input character data is parsed using natural language processing techniques. The terminal applies a Large-Scale Language Model (LLM) to identify the hierarchical structure of the character data. Through parsing, information that forms the logical structure of the document (e.g., headings, paragraphs) is identified and converted into a standardized format. As a result, the terminal outputs unified text data.

[0268] Step 3:

[0269] The terminal receives visual data from the server and analyzes it using image recognition technology. By utilizing visual recognition technology, it identifies objects and figures within the image. Specifically, it obtains the analysis results from the visual recognition service and unifies the image format based on those results. Through this process, the visual data is output as image data in a unified format.

[0270] Step 4:

[0271] The terminal generates consistent documents based on standardized text data and unified visual data. Using unified text and image data as input, it creates integrated documents using a document generation library. This process generates documents formatted in a way that is easily readable by the user. The final output is a standardized, unified document provided to the user.

[0272] Step 5:

[0273] Users download the generated unified documents. By accessing the system and retrieving documents through the online platform, information in different formats becomes available in a consistent format. Specifically, users select generated documents via the user interface and save them to their devices.

[0274] (Application Example 1)

[0275] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0276] In today's digital information environment, there are many information documents in different formats, making it difficult to unify them into a consistent format that is easy for users to understand. Furthermore, in urban environments, information is diverse, and there is a particular need for systems that allow citizens and city officials to access information quickly and easily.

[0277] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0278] In this invention, the server includes means for receiving digital information in different formats, means for classifying it into symbol data and video data, and means for integrating the standardized symbol data and video data to generate consistent materials. As a result, users can easily obtain digital information in a standardized form using smart devices, enabling information utilization in urban life.

[0279] "Different formats" refers to different file formats or digital formats, indicating that the expression methods of information documents are diverse.

[0280] "Digital information" refers to information stored or transmitted electronically, including text, images, audio, video, etc.

[0281] "Symbol data" refers to a data format expressed by text, character information, etc.

[0282] "Video data" refers to a data format expressed as visual information such as images and videos.

[0283] "Standardizing" is a process of converting information with different formats or styles into a unified format or standard.

[0284] "Materials" refers to documents, reports, etc. containing organized information and data.

[0285] "Users" refers to individuals or groups who use a system or application, and in this context, particularly includes citizens and urban employees.

[0286] "Smart devices" refers to portable devices, glasses-type devices, etc. that provide an Internet connection and a multifunctional platform.

[0287] The system realizing this invention consists of a smart device and a server, which unifies digital information into a consistent format and provides it to the user. The server accepts digital information in different formats. The digital information is classified into symbolic data and image data. The symbolic data is analyzed and standardized using natural language processing technology, and the image data is analyzed using image recognition technology and unified into a consistent format. This utilizes the Python language and Flask as a framework, the OpenAI GPT model as a generative AI model, and the Google Cloud Vision API for image analysis.

[0288] The server generates integrated data and provides it in a standardized format. Users can capture information documents using their smartphones or smart glasses and send them to the server. Users can then download the generated, consistent information and access it easily. For example, a citizen can take a picture of local event information with their smartphone and obtain the information in a standardized format.

[0289] Examples of prompts for the generative AI model include, "Please standardize this text document using standard Japanese legal terminology," and "Analyze the images in this report and categorize them appropriately." This makes it possible to organize even irregular documents into a consistent format.

[0290] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0291] Step 1:

[0292] Users capture digital information using smartphones or smart glasses. Input consists of digital documents and images, which are sent to a server. Output is the data uploaded to the server. This involves the specific actions of capturing information using the device's camera function and transmitting it over the network.

[0293] Step 2:

[0294] The server classifies received digital information into text data and image data. The input is digital information sent by the user, and the output is the result of classifying it into two types of data formats. The server analyzes the data format and performs calculations to separate it into symbolic data and image data.

[0295] Step 3:

[0296] The server analyzes and standardizes classified symbolic data using natural language processing techniques. The input is classified symbolic data, and the output is standardized text data. A generative AI model is used to identify the hierarchical structure of documents and unify them into a common format.

[0297] Step 4:

[0298] The server analyzes video data using video recognition technology and standardizes its format. The input is classified video data, and the output is standardized image data. This includes using video recognition technologies such as the Google Cloud Vision API to identify the content of images and format them into appropriate categories and styles.

[0299] Step 5:

[0300] The server integrates standardized text data and unified image data to generate consistent materials. The input is a set of standardized and unified data, and the output is the final, consistent material. The system performs calculations to combine text and image data and present it in a neat format.

[0301] Step 6:

[0302] The server provides users with unified generated documents. The input is unified documents, and the output is a digital file that users can download. It provides a concrete service that allows users to easily access and retrieve information via a web interface.

[0303] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion recognition model 59 and perform specific processing using the user's emotion.

[0304] The present invention provides a system that optimizes the user experience by combining an emotion engine that recognizes the user's emotion with a system that unifies different formats of information documents into a consistent format. This system is composed of a server and a terminal and is effectively operated in both document management and user interface.

[0305] When the user uploads an information document to the system, the server receives the information and classifies the document into text data and image data. The classified data is reorganized into a consistent document through appropriate analysis and standardization processes. So far, information is organized by basic document unification processing.

[0306] What is remarkable about this system is the emotion engine installed on the terminal. This engine has a function of analyzing the user's emotion in real time based on the user's input and operations. Through this analysis, it is possible to capture emotional reactions such as the user's interest and stress level when viewing an article.

[0307] Specifically, when the emotion engine detects a change in the user's emotion, the server dynamically adjusts the presentation method of the standardized document generated based on this. For example, when the user shows stress about specific content, the terminal can change the display order of the corresponding section or display additional explanations. Such adjustments are automatically made to improve the user experience.

[0308] Furthermore, for example, when a user is using a product's technical manual, if they indicate they are experiencing difficulty, the emotion engine will provide support by suggesting links to relevant tutorial videos or FAQs. This feature combines consistent information management with emotion-responsive interaction, enabling more personalized information delivery to users.

[0309] In this way, this system, which incorporates an emotion engine, goes beyond mere information unification and enables dynamic information presentation tailored to the user's emotional state. This increases usefulness and adaptability, promoting the effective use of information.

[0310] The following describes the processing flow.

[0311] Step 1:

[0312] Users upload informational documents in different formats to the system. The server accepts these documents and performs preprocessing according to the file format. For example, it extracts text and images from PDF and Word documents.

[0313] Step 2:

[0314] The server classifies the acquired data into text data and image data. Text data is recognized as character information, and image data is treated as visual information. An appropriate classification method is applied according to the various data formats.

[0315] Step 3:

[0316] The server analyzes the classified text data. Using a large-scale language model, it analyzes and standardizes the hierarchical structure of the document. For example, it identifies headings and bullet points within the text to clarify the document's structure.

[0317] Step 4:

[0318] The device uses image recognition technology to analyze image data. Specifically, it identifies objects within the image and resizes or rearranges them into a standard format. This ensures consistency across various images.

[0319] Step 5:

[0320] The terminal integrates the analyzed and standardized text and image data. The server then generates a consistent informational document based on this data and prepares it for delivery to the user.

[0321] Step 6:

[0322] While a user is viewing a generated document, the device's emotion engine monitors the user's emotional state in real time. For example, it estimates emotions based on factors such as the user's operation speed and the time spent at specific points in the document.

[0323] Step 7:

[0324] When the emotion engine detects a specific change in the user's emotion, the server dynamically adjusts how the document is presented based on that information. For example, if the user shows confusion, it will display a more detailed explanation of the relevant section or additional visual aids.

[0325] Step 8:

[0326] The user reviews the revised document again and provides feedback as needed. The server uses the feedback to further optimize the document and provides the user with the final version.

[0327] (Example 2)

[0328] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0329] When information documents exist in multiple formats, unifying them into a consistent format contributes to improving the user experience. However, traditional methods lack not only document uniformity but also dynamic information presentation that responds to the user's emotional reactions. As a result, users may not receive appropriate support when they encounter difficulties or stress with the document content, potentially leading to decreased user understanding and satisfaction.

[0330] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0331] In this invention, the server includes means for accepting information documents of different formats, means for classifying them into text data and image data, means for integrating the standardized text data and image data to generate a consistent document, means for analyzing the user's emotional state in real time, and means for dynamically adjusting the document presentation method based on the analysis results. This enables the unification of information documents as well as personalized information presentation that responds to the user's emotions.

[0332] "Information documents in different formats" refers to documents that have various data representation forms, including text format and image format.

[0333] "Text data" refers to data composed of strings of characters, and is the basic unit for representing documents and texts.

[0334] "Image data" refers to data that represents visual information recorded in digital format.

[0335] Standardization is the process of organizing data with different forms and contents into a unified format and structure.

[0336] "Image recognition technology" is a technology that allows computer systems to identify specific patterns or features from image data.

[0337] A "consistent document" is a document in which various forms of data are integrated and organized into a unified format.

[0338] "Emotional state" is a concept that describes the emotions and mental state a user is experiencing at a particular moment.

[0339] "Real-time analysis" refers to a process where data is processed instantly and results are obtained at the very moment the user inputs or performs an action.

[0340] "Dynamic adjustment" means flexibly changing the system's operation and output according to the situation and conditions.

[0341] As a form of implementing the invention, this system converts information documents of different formats into a unified format and provides personalized information based on the user's emotional state. Details are provided below.

[0342] The server features a user interface for uploading informational documents and classifies the documents received from users into text data and image data. Natural language processing (NLP) techniques are applied to analyze the text data, and image recognition techniques are used to analyze the image data. Machine learning models are utilized in these techniques. Based on the analysis results, the server standardizes the data and generates consistent documents.

[0343] The device is equipped with an emotion engine that analyzes the user's emotional state in real time based on their actions and inputs. This engine performs face tracking and analyzes operation patterns to determine the user's level of interest and stress. If the user experiences stress, the device sends that state to the server.

[0344] For example, if a user shows confusion while using a technical manual, the emotion engine will detect this emotion. The server can then prepare relevant tutorial videos and additional explanatory content to help the user understand better, and the device can display these.

[0345] Examples of prompts for a generative AI model are as follows:

[0346] "How can we analyze the emotions users experience when viewing product manuals and provide additional support information as needed?"

[0347] Such systems enable improved user experience and more efficient access to information.

[0348] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0349] Step 1:

[0350] Users upload informational documents to the system. Different file formats, such as PDFs and Word documents, are used as input. The server begins processing upon acceptance. The server detects the file from the user and sends a confirmation message to the user.

[0351] Step 2:

[0352] The server classifies the received document into text data and image data. At this stage, the input is the entire uploaded document. The server identifies and classifies the text information and images within the document. The text data and image data are output and stored internally.

[0353] Step 3:

[0354] The server analyzes the classified text data using natural language processing (NLP) techniques. Specifically, it analyzes the grammatical structure of the text and extracts keywords. The input is classified text data, and the output is standardized text data based on the analysis results.

[0355] Step 4:

[0356] The server analyzes and standardizes the classified image data using image recognition technology. The input is image data; it analyzes the shape, color, and patterns of the images and converts them into a consistent format. The output is image data in a unified format.

[0357] Step 5:

[0358] The server integrates standardized text and image data to generate a consistent document. The input consists of individual standardized data, and the output is a single, unified document. The server then prepares this generated document for the user.

[0359] Step 6:

[0360] The device uses an emotion engine to analyze the user's emotional state in real time. User operation data and facial expression data are used as input. The device converts this into an emotional state and detects a specific emotion. The output is the user's emotional data.

[0361] Step 7:

[0362] The server dynamically adjusts how generated documents are presented based on the emotional data received from the terminal. The input consists of emotional data and the generated documents. If the user is experiencing stress, the server adjusts to output additional relevant support information and explanations.

[0363] (Application Example 2)

[0364] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0365] While a vast amount of information is currently available on the internet, few systems consider the user's emotions when viewing this information. Users can be overwhelmed by the sheer volume of information, sometimes experiencing stress. Therefore, there is a need for technology that dynamically adjusts how information is displayed according to the user's emotions, thereby improving the user experience.

[0366] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0367] In this invention, the server includes means for accepting information documents of different formats, means for analyzing the user's emotional state, and means for dynamically adjusting the display order of documents based on the analyzed emotional state. This enables the presentation of information that is optimal to the user's emotions.

[0368] "Information documents in different formats" refers to a collection of information that exists in multiple formats, such as text data and image data.

[0369] A "means of acceptance" is a mechanism that allows a system to receive data from an external source and begin processing it.

[0370] A "means of classification" refers to a device or program that has the function of sorting received data into text data and image data according to its nature.

[0371] "Means of standardization" refer to methods and devices for transforming classified data into a consistent format and unifying it.

[0372] "Image recognition technology" refers to computer vision techniques used to analyze the content of image data and extract features.

[0373] A "consistent document" is a document in a standardized format that integrates data from different formats.

[0374] "Means of provision" refers to methods and devices for presenting a consistent set of generated documents to the user in a viewable format.

[0375] The "function to analyze the user's emotional state" is a technology that recognizes emotions based on the user's facial expressions and tone of voice.

[0376] "Means for dynamically adjusting the display order" refers to devices or programs that have the function of automatically changing the display order of content according to the user's emotions.

[0377] To implement this invention, a server, a terminal, and an interface to the user are required. The server first accepts information documents in different formats and classifies them into text data and image data. The classified data is then reconstructed into a consistent document through a standardization process.

[0378] The server uses the device's camera and microphone to collect the user's facial expressions and voice in order to analyze the user's emotional state. This data is processed using emotion analysis software such as Google Cloud Vision API or IBM Watson Tone Analyzer. Based on the user's emotional state, processing is performed to dynamically adjust the display order and content of documents. Specifically, if the analysis indicates that the user is feeling stressed, the presentation order is changed so that positive content is displayed preferentially.

[0379] In this way, the system provides users with the most relevant information. For example, if sentiment analysis detects stress when a user is reading the morning news, the system will prioritize displaying articles about relaxing hobbies to alleviate their mood. At the same time, if the user shows interest in a particular topic, the system can use a generative AI model to generate new, relevant information.

[0380] An example of a prompt message would be: "Generate detailed information about a topic the user has shown interest in. For example, 'Generate an article that makes you feel positive about the latest sports news.'"

[0381] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0382] Step 1:

[0383] The server accepts information documents in various formats uploaded by users. The information documents are passed to the server as input and are classified into text data and image data. Preparations for text analysis and image analysis are then performed depending on the document format.

[0384] Step 2:

[0385] The server performs a process to standardize classified text data. The input is text data, which is then parsed to convert it into a consistent format. A language model is used to extract the document's hierarchical structure and key points, and the organized text data is output.

[0386] Step 3:

[0387] The server uses image recognition technology to analyze the image data. It receives image data as input, identifies elements within the image, and standardizes their format. During this process, the recognized content is output as structured data.

[0388] Step 4:

[0389] The server integrates standardized text data and unified image data to generate consistent documents. The input consists of pre-processed text and images, which are then merged to create a unified document. This document is output in a format viewable by the user.

[0390] Step 5:

[0391] The device acquires facial expressions and audio from its camera and microphone to analyze the user's emotional state. The input is a real-time video and audio stream, and the user's emotions are analyzed using emotion analysis software. As a result, emotional state data is output.

[0392] Step 6:

[0393] The server dynamically adjusts the display order of documents based on the analyzed emotional state. The input is emotional state data, and a display order algorithm is applied based on this data to output documents that take the user's emotions into consideration. This results in optimized information presentation that reflects the user's interests and stress levels.

[0394] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0395] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0396] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0397] [Third Embodiment]

[0398] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0399] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0400] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0401] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0402] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0403] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0404] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0405] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0406] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0407] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0408] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0409] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0410] This invention provides a system for unifying information documents of different formats into a consistent format. This system primarily consists of a server and terminals and is designed to allow users to efficiently utilize the information.

[0411] The server is responsible for receiving information documents uploaded by users and classifying them into text data and image data. Regardless of whether the received documents are PDF, Word files, or other digital formats, the server breaks them down into their constituent elements and prepares them for appropriate processing.

[0412] The terminal analyzes the classified text data using natural language processing techniques. In particular, it leverages large-scale language models (LLMs) to identify the hierarchical structure of documents and convert them into a standardized format. This ensures text consistency based on a common language style and glossary.

[0413] Furthermore, the device uses image recognition technology to analyze image data, identify its content, and standardize its format. This means that even if specific diagrams or product part drawings exist in different documents, they will be placed within the document with a consistent appearance.

[0414] As a concrete example, consider a scenario where a user uploads an operation manual for a piece of machinery to the system. The server identifies the text and images in the manual and performs appropriate analysis on each. The terminal then formats the operation procedure text into a standard format and rearranges the machine's design diagrams and images of control buttons in a unified format. The generated document is then provided to the user in a downloadable format.

[0415] In this way, information documents of different formats are unified into a consistent format, allowing users to access information quickly and efficiently.

[0416] The following describes the processing flow.

[0417] Step 1:

[0418] Users upload informational documents provided by manufacturers to the system. These documents are in PDF or Word file format, and the server receives this data. Once received, the data is broken down into its constituent elements, such as text and images.

[0419] Step 2:

[0420] The server classifies uploaded documents into text data and image data. It extracts text data from parts of the document that are represented as characters, and separates image data from parts that are treated as visual information.

[0421] Step 3:

[0422] The terminal acquires classified text data and analyzes it using natural language processing techniques. Specifically, it utilizes a large-scale language model (LLM) to recognize the hierarchical structure of the text (e.g., sections and subsections) and adds or modifies the text based on standard terminology and style.

[0423] Step 4:

[0424] The device uses image recognition technology to analyze image data. It identifies the content of each image and standardizes its arrangement and format. For example, even if diagrams of the same type of equipment differ, they are adjusted to be represented in a unified style.

[0425] Step 5:

[0426] The server combines parsed and standardized text data with formatted image data. The integrated information is then generated as a document according to a unified template. The terminal prepares to provide this completed document to the user.

[0427] Step 6:

[0428] Users can preview the generated, standardized document. They can provide feedback as needed, and the server will make final adjustments based on that feedback. The finalized document is then provided to the user for download.

[0429] (Example 1)

[0430] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0431] Information is often generated in various formats, making it difficult to organize it efficiently and consistently. This leads to inefficient information utilization and wasted time and effort.

[0432] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0433] In this invention, the server includes means for receiving information in different formats, means for classifying the received information into character data and visual data, and means for analyzing and standardizing the classified character data. This enables the information to be organized quickly, efficiently, and in a consistent format, making it easily accessible and usable by users.

[0434] "Different formats" refers to a state in which information exists in various digital formats.

[0435] "Information" refers to all digital content, including text and visual data.

[0436] "Character data" refers to the parts of information that are represented as characters or symbols.

[0437] "Visual data" refers to the parts of information that are visually represented as images or diagrams.

[0438] "Classification" refers to the process of separating information into text data and visual data.

[0439] "Analysis" refers to the process of understanding information or the content of its elements and deriving its structure.

[0440] "Standardization" refers to the process of unifying parsed character data into a common style or format.

[0441] "Visual recognition technology" refers to technologies used to identify the content of visual data and understand its meaning.

[0442] "Consistent information" refers to information that has been converted into a unified format.

[0443] "User" refers to the entity that uses the system to upload and download information.

[0444] This system is designed to unify information in different formats into a consistent format. This allows users to efficiently utilize information in various formats.

[0445] The server is responsible for receiving information from the user. The server first classifies the information into text data and visual data. For various file formats such as PDF and Word, it can use dedicated analysis libraries to decompose the data and extract its contents appropriately. For example, in the case of a PDF file, a PDF analysis library is used to extract text and images. This divides the information into its constituent elements, preparing it for the next processing step.

[0446] The terminal analyzes and standardizes the character data received from the server. Large-scale language models (LLMs) are used for natural language processing to improve the accuracy of the analysis. For example, a natural language processing framework is used as the language model to identify the hierarchical structure of the information. This analysis ensures that documents are standardized with common formatting and terminology.

[0447] Furthermore, the device uses visual recognition technology to analyze visual data. By recognizing objects in images and standardizing their format, it ensures visual consistency within documents. Cloud-based visual recognition services are used for visual recognition, and the analyzed images are standardized to a specific format.

[0448] A concrete example is a scenario where a user uploads an operation guide for a machine or device. The server receives the guide document and identifies the text and diagram portions. The terminal converts the operation procedure text into a standard format and rearranges the device diagrams and button images in a consistent style. As a result, the user can download a guide with a consistent format.

[0449] As an example of a prompt, you can enter instructions such as, "Please convert the following operation guide to a consistent format. Upload the PDF file." This organizes information in different formats, allowing users to utilize it efficiently.

[0450] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0451] Step 1:

[0452] The server receives information from the user. The input format of this information varies, including PDF and Word documents. To prepare the received information for analysis, the server first identifies the file format. Specifically, it uses an analysis library to classify the information into text data and visual data. Through this process, the server obtains output as a dataset of text and images.

[0453] Step 2:

[0454] The terminal receives character data from the server. The input character data is parsed using natural language processing techniques. The terminal applies a Large-Scale Language Model (LLM) to identify the hierarchical structure of the character data. Through parsing, information that forms the logical structure of the document (e.g., headings, paragraphs) is identified and converted into a standardized format. As a result, the terminal outputs unified text data.

[0455] Step 3:

[0456] The terminal receives visual data from the server and analyzes it using image recognition technology. By utilizing visual recognition technology, it identifies objects and figures within the image. Specifically, it obtains the analysis results from the visual recognition service and unifies the image format based on those results. Through this process, the visual data is output as image data in a unified format.

[0457] Step 4:

[0458] The terminal generates consistent documents based on standardized text data and unified visual data. Using unified text and image data as input, it creates integrated documents using a document generation library. This process generates documents formatted in a way that is easily readable by the user. The final output is a standardized, unified document provided to the user.

[0459] Step 5:

[0460] Users download the generated unified documents. By accessing the system and retrieving documents through the online platform, information in different formats becomes available in a consistent format. Specifically, users select generated documents via the user interface and save them to their devices.

[0461] (Application Example 1)

[0462] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0463] In today's digital information environment, there are many information documents in different formats, making it difficult to unify them into a consistent format that is easy for users to understand. Furthermore, in urban environments, information is diverse, and there is a particular need for systems that allow citizens and city officials to access information quickly and easily.

[0464] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0465] In this invention, the server includes means for receiving digital information in different formats, means for classifying it into symbolic data and image data, and means for integrating the standardized symbolic data and image data to generate consistent materials. This enables users to easily acquire digital information in a standardized form using smart devices, making it possible to utilize information in urban life.

[0466] "Different formats" refers to different file formats or digital formats, resulting in a variety of ways in which information documents can be represented.

[0467] "Digital information" refers to information that is stored or transmitted electronically, including text, images, audio, and video.

[0468] "Symbolic data" refers to data formats that are expressed in written form, such as text and character information.

[0469] "Video data" refers to data formats that are represented as visual information, such as images and videos.

[0470] "Standardization" is the process of converting information that exists in different formats or styles into a unified format or standard.

[0471] "Documents" refer to documents, reports, and other materials that contain organized information and data.

[0472] "Users" refers to individuals or groups who use the system or application, and in this context specifically includes citizens and city employees.

[0473] "Smart devices" refer to portable devices, glasses-type devices, and other devices that provide internet connectivity and a multi-functional platform.

[0474] The system realizing this invention consists of a smart device and a server, which unifies digital information into a consistent format and provides it to the user. The server accepts digital information in different formats. The digital information is classified into symbolic data and image data. The symbolic data is analyzed and standardized using natural language processing technology, and the image data is analyzed using image recognition technology and unified into a consistent format. This utilizes the Python language and Flask as a framework, the OpenAI GPT model as a generative AI model, and the Google Cloud Vision API for image analysis.

[0475] The server generates integrated data and provides it in a standardized format. Users can capture information documents using their smartphones or smart glasses and send them to the server. Users can then download the generated, consistent information and access it easily. For example, a citizen can take a picture of local event information with their smartphone and obtain the information in a standardized format.

[0476] Examples of prompts for the generative AI model include, "Please standardize this text document using standard Japanese legal terminology," and "Analyze the images in this report and categorize them appropriately." This makes it possible to organize even irregular documents into a consistent format.

[0477] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0478] Step 1:

[0479] Users capture digital information using smartphones or smart glasses. Input consists of digital documents and images, which are sent to a server. Output is the data uploaded to the server. This involves the specific actions of capturing information using the device's camera function and transmitting it over the network.

[0480] Step 2:

[0481] The server classifies received digital information into text data and image data. The input is digital information sent by the user, and the output is the result of classifying it into two types of data formats. The server analyzes the data format and performs calculations to separate it into symbolic data and image data.

[0482] Step 3:

[0483] The server analyzes and standardizes classified symbolic data using natural language processing techniques. The input is classified symbolic data, and the output is standardized text data. A generative AI model is used to identify the hierarchical structure of documents and unify them into a common format.

[0484] Step 4:

[0485] The server analyzes video data using video recognition technology and standardizes its format. The input is classified video data, and the output is standardized image data. This includes using video recognition technologies such as the Google Cloud Vision API to identify the content of images and format them into appropriate categories and styles.

[0486] Step 5:

[0487] The server integrates standardized text data and unified image data to generate consistent materials. The input is a set of standardized and unified data, and the output is the final, consistent material. The system performs calculations to combine text and image data and present it in a neat format.

[0488] Step 6:

[0489] The server provides users with unified generated documents. The input is unified documents, and the output is a digital file that users can download. It provides a concrete service that allows users to easily access and retrieve information via a web interface.

[0490] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0491] This invention provides a system that optimizes the user experience by combining a system for unifying information documents of different formats into a consistent format with an emotion engine that recognizes user emotions. This system consists of a server and terminals and is effectively operated in both document management and user interface aspects.

[0492] When a user uploads an informational document to the system, the server receives the information and classifies it into text data and image data. The classified data then undergoes appropriate analysis and standardization processes to be reconstructed into a consistent document. Up to this point, the information is organized through basic document unification processes.

[0493] A notable feature of this system is the emotion engine built into the terminal. This engine has the function of analyzing the user's emotions in real time based on the user's input and actions. Through this analysis, it is possible to capture emotional responses such as the user's interest and stress level while they are viewing text.

[0494] Specifically, when the emotion engine detects a change in the user's emotions, the server dynamically adjusts how standardized documents generated based on that information are presented. For example, if a user shows stress from certain content, the device can change the display order of the relevant sections or display additional explanations. Such adjustments are made automatically to improve the user experience.

[0495] Furthermore, for example, when a user is using a product's technical manual, if they indicate they are experiencing difficulty, the emotion engine will provide support by suggesting links to relevant tutorial videos or FAQs. This feature combines consistent information management with emotion-responsive interaction, enabling more personalized information delivery to users.

[0496] In this way, this system, which incorporates an emotion engine, goes beyond mere information unification and enables dynamic information presentation tailored to the user's emotional state. This increases usefulness and adaptability, promoting the effective use of information.

[0497] The following describes the processing flow.

[0498] Step 1:

[0499] Users upload informational documents in different formats to the system. The server accepts these documents and performs preprocessing according to the file format. For example, it extracts text and images from PDF and Word documents.

[0500] Step 2:

[0501] The server classifies the acquired data into text data and image data. Text data is recognized as character information, and image data is treated as visual information. An appropriate classification method is applied according to the various data formats.

[0502] Step 3:

[0503] The server analyzes the classified text data. Using a large-scale language model, it analyzes and standardizes the hierarchical structure of the document. For example, it identifies headings and bullet points within the text to clarify the document's structure.

[0504] Step 4:

[0505] The device uses image recognition technology to analyze image data. Specifically, it identifies objects within the image and resizes or rearranges them into a standard format. This ensures consistency across various images.

[0506] Step 5:

[0507] The terminal integrates the analyzed and standardized text and image data. The server then generates a consistent informational document based on this data and prepares it for delivery to the user.

[0508] Step 6:

[0509] While a user is viewing a generated document, the device's emotion engine monitors the user's emotional state in real time. For example, it estimates emotions based on factors such as the user's operation speed and the time spent at specific points in the document.

[0510] Step 7:

[0511] When the emotion engine detects a specific change in the user's emotion, the server dynamically adjusts how the document is presented based on that information. For example, if the user shows confusion, it will display a more detailed explanation of the relevant section or additional visual aids.

[0512] Step 8:

[0513] The user reviews the revised document again and provides feedback as needed. The server uses the feedback to further optimize the document and provides the user with the final version.

[0514] (Example 2)

[0515] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0516] When information documents exist in multiple formats, unifying them into a consistent format contributes to improving the user experience. However, traditional methods lack not only document uniformity but also dynamic information presentation that responds to the user's emotional reactions. As a result, users may not receive appropriate support when they encounter difficulties or stress with the document content, potentially leading to decreased user understanding and satisfaction.

[0517] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0518] In this invention, the server includes means for accepting information documents of different formats, means for classifying them into text data and image data, means for integrating the standardized text data and image data to generate a consistent document, means for analyzing the user's emotional state in real time, and means for dynamically adjusting the document presentation method based on the analysis results. This enables the unification of information documents as well as personalized information presentation that responds to the user's emotions.

[0519] "Information documents in different formats" refers to documents that have various data representation forms, including text format and image format.

[0520] "Text data" refers to data composed of strings of characters, and is the basic unit for representing documents and texts.

[0521] "Image data" refers to data that represents visual information recorded in digital format.

[0522] Standardization is the process of organizing data with different forms and contents into a unified format and structure.

[0523] "Image recognition technology" is a technology that allows computer systems to identify specific patterns or features from image data.

[0524] A "consistent document" is a document in which various forms of data are integrated and organized into a unified format.

[0525] "Emotional state" is a concept that describes the emotions and mental state a user is experiencing at a particular moment.

[0526] "Real-time analysis" refers to a process where data is processed instantly and results are obtained at the very moment the user inputs or performs an action.

[0527] "Dynamic adjustment" means flexibly changing the system's operation and output according to the situation and conditions.

[0528] As a form of implementing the invention, this system converts information documents of different formats into a unified format and provides personalized information based on the user's emotional state. Details are provided below.

[0529] The server features a user interface for uploading informational documents and classifies the documents received from users into text data and image data. Natural language processing (NLP) techniques are applied to analyze the text data, and image recognition techniques are used to analyze the image data. Machine learning models are utilized in these techniques. Based on the analysis results, the server standardizes the data and generates consistent documents.

[0530] The device is equipped with an emotion engine that analyzes the user's emotional state in real time based on their actions and inputs. This engine performs face tracking and analyzes operation patterns to determine the user's level of interest and stress. If the user experiences stress, the device sends that state to the server.

[0531] For example, if a user shows confusion while using a technical manual, the emotion engine will detect this emotion. The server can then prepare relevant tutorial videos and additional explanatory content to help the user understand better, and the device can display these.

[0532] Examples of prompts for a generative AI model are as follows:

[0533] "How can we analyze the emotions users experience when viewing product manuals and provide additional support information as needed?"

[0534] Such systems enable improved user experience and more efficient access to information.

[0535] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0536] Step 1:

[0537] Users upload informational documents to the system. Different file formats, such as PDFs and Word documents, are used as input. The server begins processing upon acceptance. The server detects the file from the user and sends a confirmation message to the user.

[0538] Step 2:

[0539] The server classifies the received document into text data and image data. At this stage, the input is the entire uploaded document. The server identifies and classifies the text information and images within the document. The text data and image data are output and stored internally.

[0540] Step 3:

[0541] The server analyzes the classified text data using natural language processing (NLP) techniques. Specifically, it analyzes the grammatical structure of the text and extracts keywords. The input is classified text data, and the output is standardized text data based on the analysis results.

[0542] Step 4:

[0543] The server analyzes and standardizes the classified image data using image recognition technology. The input is image data; it analyzes the shape, color, and patterns of the images and converts them into a consistent format. The output is image data in a unified format.

[0544] Step 5:

[0545] The server integrates standardized text and image data to generate a consistent document. The input consists of individual standardized data, and the output is a single, unified document. The server then prepares this generated document for the user.

[0546] Step 6:

[0547] The device uses an emotion engine to analyze the user's emotional state in real time. User operation data and facial expression data are used as input. The device converts this into an emotional state and detects a specific emotion. The output is the user's emotional data.

[0548] Step 7:

[0549] The server dynamically adjusts how generated documents are presented based on the emotional data received from the terminal. The input consists of emotional data and the generated documents. If the user is experiencing stress, the server adjusts to output additional relevant support information and explanations.

[0550] (Application Example 2)

[0551] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0552] While a vast amount of information is currently available on the internet, few systems consider the user's emotions when viewing this information. Users can be overwhelmed by the sheer volume of information, sometimes experiencing stress. Therefore, there is a need for technology that dynamically adjusts how information is displayed according to the user's emotions, thereby improving the user experience.

[0553] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0554] In this invention, the server includes means for accepting information documents of different formats, means for analyzing the user's emotional state, and means for dynamically adjusting the display order of documents based on the analyzed emotional state. This enables the presentation of information that is optimal to the user's emotions.

[0555] "Information documents in different formats" refers to a collection of information that exists in multiple formats, such as text data and image data.

[0556] A "means of acceptance" is a mechanism that allows a system to receive data from an external source and begin processing it.

[0557] A "means of classification" refers to a device or program that has the function of sorting received data into text data and image data according to its nature.

[0558] "Means of standardization" refer to methods and devices for transforming classified data into a consistent format and unifying it.

[0559] "Image recognition technology" refers to computer vision techniques used to analyze the content of image data and extract features.

[0560] A "consistent document" is a document in a standardized format that integrates data from different formats.

[0561] "Means of provision" refers to methods and devices for presenting a consistent set of generated documents to the user in a viewable format.

[0562] The "function to analyze the user's emotional state" is a technology that recognizes emotions based on the user's facial expressions and tone of voice.

[0563] "Means for dynamically adjusting the display order" refers to devices or programs that have the function of automatically changing the display order of content according to the user's emotions.

[0564] To implement this invention, a server, a terminal, and an interface to the user are required. The server first accepts information documents in different formats and classifies them into text data and image data. The classified data is then reconstructed into a consistent document through a standardization process.

[0565] The server uses the device's camera and microphone to collect the user's facial expressions and voice in order to analyze the user's emotional state. This data is processed using emotion analysis software such as Google Cloud Vision API or IBM Watson Tone Analyzer. Based on the user's emotional state, processing is performed to dynamically adjust the display order and content of documents. Specifically, if the analysis indicates that the user is feeling stressed, the presentation order is changed so that positive content is displayed preferentially.

[0566] In this way, the system provides users with the most relevant information. For example, if sentiment analysis detects stress when a user is reading the morning news, the system will prioritize displaying articles about relaxing hobbies to alleviate their mood. At the same time, if the user shows interest in a particular topic, the system can use a generative AI model to generate new, relevant information.

[0567] An example of a prompt message would be: "Generate detailed information about a topic the user has shown interest in. For example, 'Generate an article that makes you feel positive about the latest sports news.'"

[0568] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0569] Step 1:

[0570] The server accepts information documents in various formats uploaded by users. The information documents are passed to the server as input and are classified into text data and image data. Preparations for text analysis and image analysis are then performed depending on the document format.

[0571] Step 2:

[0572] The server performs a process to standardize classified text data. The input is text data, which is then parsed to convert it into a consistent format. A language model is used to extract the document's hierarchical structure and key points, and the organized text data is output.

[0573] Step 3:

[0574] The server uses image recognition technology to analyze the image data. It receives image data as input, identifies elements within the image, and standardizes their format. During this process, the recognized content is output as structured data.

[0575] Step 4:

[0576] The server integrates standardized text data and unified image data to generate consistent documents. The input consists of pre-processed text and images, which are then merged to create a unified document. This document is output in a format viewable by the user.

[0577] Step 5:

[0578] The device acquires facial expressions and audio from its camera and microphone to analyze the user's emotional state. The input is a real-time video and audio stream, and the user's emotions are analyzed using emotion analysis software. As a result, emotional state data is output.

[0579] Step 6:

[0580] The server dynamically adjusts the display order of documents based on the analyzed emotional state. The input is emotional state data, and a display order algorithm is applied based on this data to output documents that take the user's emotions into consideration. This results in optimized information presentation that reflects the user's interests and stress levels.

[0581] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0582] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0583] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0584] [Fourth Embodiment]

[0585] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0586] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0587] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0588] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0589] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0590] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0591] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0592] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0593] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0594] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0595] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0596] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0597] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0598] This invention provides a system for unifying information documents of different formats into a consistent format. This system primarily consists of a server and terminals and is designed to allow users to efficiently utilize the information.

[0599] The server is responsible for receiving information documents uploaded by users and classifying them into text data and image data. Regardless of whether the received documents are PDF, Word files, or other digital formats, the server breaks them down into their constituent elements and prepares them for appropriate processing.

[0600] The terminal analyzes the classified text data using natural language processing techniques. In particular, it leverages large-scale language models (LLMs) to identify the hierarchical structure of documents and convert them into a standardized format. This ensures text consistency based on a common language style and glossary.

[0601] Furthermore, the device uses image recognition technology to analyze image data, identify its content, and standardize its format. This means that even if specific diagrams or product part drawings exist in different documents, they will be placed within the document with a consistent appearance.

[0602] As a concrete example, consider a scenario where a user uploads an operation manual for a piece of machinery to the system. The server identifies the text and images in the manual and performs appropriate analysis on each. The terminal then formats the operation procedure text into a standard format and rearranges the machine's design diagrams and images of control buttons in a unified format. The generated document is then provided to the user in a downloadable format.

[0603] In this way, information documents of different formats are unified into a consistent format, allowing users to access information quickly and efficiently.

[0604] The following describes the processing flow.

[0605] Step 1:

[0606] Users upload informational documents provided by manufacturers to the system. These documents are in PDF or Word file format, and the server receives this data. Once received, the data is broken down into its constituent elements, such as text and images.

[0607] Step 2:

[0608] The server classifies uploaded documents into text data and image data. It extracts text data from parts of the document that are represented as characters, and separates image data from parts that are treated as visual information.

[0609] Step 3:

[0610] The terminal acquires classified text data and analyzes it using natural language processing techniques. Specifically, it utilizes a large-scale language model (LLM) to recognize the hierarchical structure of the text (e.g., sections and subsections) and adds or modifies the text based on standard terminology and style.

[0611] Step 4:

[0612] The device uses image recognition technology to analyze image data. It identifies the content of each image and standardizes its arrangement and format. For example, even if diagrams of the same type of equipment differ, they are adjusted to be represented in a unified style.

[0613] Step 5:

[0614] The server combines parsed and standardized text data with formatted image data. The integrated information is then generated as a document according to a unified template. The terminal prepares to provide this completed document to the user.

[0615] Step 6:

[0616] Users can preview the generated, standardized document. They can provide feedback as needed, and the server will make final adjustments based on that feedback. The finalized document is then provided to the user for download.

[0617] (Example 1)

[0618] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0619] Information is often generated in various formats, making it difficult to organize it efficiently and consistently. This leads to inefficient information utilization and wasted time and effort.

[0620] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0621] In this invention, the server includes means for receiving information in different formats, means for classifying the received information into character data and visual data, and means for analyzing and standardizing the classified character data. This enables the information to be organized quickly, efficiently, and in a consistent format, making it easily accessible and usable by users.

[0622] "Different formats" refers to a state in which information exists in various digital formats.

[0623] "Information" refers to all digital content, including text and visual data.

[0624] "Character data" refers to the parts of information that are represented as characters or symbols.

[0625] "Visual data" refers to the parts of information that are visually represented as images or diagrams.

[0626] "Classification" refers to the process of separating information into text data and visual data.

[0627] "Analysis" refers to the process of understanding information or the content of its elements and deriving its structure.

[0628] "Standardization" refers to the process of unifying parsed character data into a common style or format.

[0629] "Visual recognition technology" refers to technologies used to identify the content of visual data and understand its meaning.

[0630] "Consistent information" refers to information that has been converted into a unified format.

[0631] "User" refers to the entity that uses the system to upload and download information.

[0632] This system is designed to unify information in different formats into a consistent format. This allows users to efficiently utilize information in various formats.

[0633] The server is responsible for receiving information from the user. The server first classifies the information into text data and visual data. For various file formats such as PDF and Word, it can use dedicated analysis libraries to decompose the data and extract its contents appropriately. For example, in the case of a PDF file, a PDF analysis library is used to extract text and images. This divides the information into its constituent elements, preparing it for the next processing step.

[0634] The terminal analyzes and standardizes the character data received from the server. Large-scale language models (LLMs) are used for natural language processing to improve the accuracy of the analysis. For example, a natural language processing framework is used as the language model to identify the hierarchical structure of the information. This analysis ensures that documents are standardized with common formatting and terminology.

[0635] Furthermore, the device uses visual recognition technology to analyze visual data. By recognizing objects in images and standardizing their format, it ensures visual consistency within documents. Cloud-based visual recognition services are used for visual recognition, and the analyzed images are standardized to a specific format.

[0636] A concrete example is a scenario where a user uploads an operation guide for a machine or device. The server receives the guide document and identifies the text and diagram portions. The terminal converts the operation procedure text into a standard format and rearranges the device diagrams and button images in a consistent style. As a result, the user can download a guide with a consistent format.

[0637] As an example of a prompt, you can enter instructions such as, "Please convert the following operation guide to a consistent format. Upload the PDF file." This organizes information in different formats, allowing users to utilize it efficiently.

[0638] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0639] Step 1:

[0640] The server receives information from the user. The input format of this information varies, including PDF and Word documents. To prepare the received information for analysis, the server first identifies the file format. Specifically, it uses an analysis library to classify the information into text data and visual data. Through this process, the server obtains output as a dataset of text and images.

[0641] Step 2:

[0642] The terminal receives character data from the server. The input character data is parsed using natural language processing techniques. The terminal applies a Large-Scale Language Model (LLM) to identify the hierarchical structure of the character data. Through parsing, information that forms the logical structure of the document (e.g., headings, paragraphs) is identified and converted into a standardized format. As a result, the terminal outputs unified text data.

[0643] Step 3:

[0644] The terminal receives visual data from the server and analyzes it using image recognition technology. By utilizing visual recognition technology, it identifies objects and figures within the image. Specifically, it obtains the analysis results from the visual recognition service and unifies the image format based on those results. Through this process, the visual data is output as image data in a unified format.

[0645] Step 4:

[0646] The terminal generates consistent documents based on standardized text data and unified visual data. Using unified text and image data as input, it creates integrated documents using a document generation library. This process generates documents formatted in a way that is easily readable by the user. The final output is a standardized, unified document provided to the user.

[0647] Step 5:

[0648] Users download the generated unified documents. By accessing the system and retrieving documents through the online platform, information in different formats becomes available in a consistent format. Specifically, users select generated documents via the user interface and save them to their devices.

[0649] (Application Example 1)

[0650] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0651] In today's digital information environment, there are many information documents in different formats, making it difficult to unify them into a consistent format that is easy for users to understand. Furthermore, in urban environments, information is diverse, and there is a particular need for systems that allow citizens and city officials to access information quickly and easily.

[0652] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0653] In this invention, the server includes means for receiving digital information in different formats, means for classifying it into symbolic data and image data, and means for integrating the standardized symbolic data and image data to generate consistent materials. This enables users to easily acquire digital information in a standardized form using smart devices, making it possible to utilize information in urban life.

[0654] "Different formats" refers to different file formats or digital formats, resulting in a variety of ways in which information documents can be represented.

[0655] "Digital information" refers to information that is stored or transmitted electronically, including text, images, audio, and video.

[0656] "Symbolic data" refers to data formats that are expressed in written form, such as text and character information.

[0657] "Video data" refers to data formats that are represented as visual information, such as images and videos.

[0658] "Standardization" is the process of converting information that exists in different formats or styles into a unified format or standard.

[0659] "Documents" refer to documents, reports, and other materials that contain organized information and data.

[0660] "Users" refers to individuals or groups who use the system or application, and in this context specifically includes citizens and city employees.

[0661] "Smart devices" refer to portable devices, glasses-type devices, and other devices that provide internet connectivity and a multi-functional platform.

[0662] The system realizing this invention consists of a smart device and a server, which unifies digital information into a consistent format and provides it to the user. The server accepts digital information in different formats. The digital information is classified into symbolic data and image data. The symbolic data is analyzed and standardized using natural language processing technology, and the image data is analyzed using image recognition technology and unified into a consistent format. This utilizes the Python language and Flask as a framework, the OpenAI GPT model as a generative AI model, and the Google Cloud Vision API for image analysis.

[0663] The server generates integrated data and provides it in a standardized format. Users can capture information documents using their smartphones or smart glasses and send them to the server. Users can then download the generated, consistent information and access it easily. For example, a citizen can take a picture of local event information with their smartphone and obtain the information in a standardized format.

[0664] Examples of prompts for the generative AI model include, "Please standardize this text document using standard Japanese legal terminology," and "Analyze the images in this report and categorize them appropriately." This makes it possible to organize even irregular documents into a consistent format.

[0665] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0666] Step 1:

[0667] Users capture digital information using smartphones or smart glasses. Input consists of digital documents and images, which are sent to a server. Output is the data uploaded to the server. This involves the specific actions of capturing information using the device's camera function and transmitting it over the network.

[0668] Step 2:

[0669] The server classifies received digital information into text data and image data. The input is digital information sent by the user, and the output is the result of classifying it into two types of data formats. The server analyzes the data format and performs calculations to separate it into symbolic data and image data.

[0670] Step 3:

[0671] The server analyzes and standardizes classified symbolic data using natural language processing techniques. The input is classified symbolic data, and the output is standardized text data. A generative AI model is used to identify the hierarchical structure of documents and unify them into a common format.

[0672] Step 4:

[0673] The server analyzes video data using video recognition technology and standardizes its format. The input is classified video data, and the output is standardized image data. This includes using video recognition technologies such as the Google Cloud Vision API to identify the content of images and format them into appropriate categories and styles.

[0674] Step 5:

[0675] The server integrates standardized text data and unified image data to generate consistent materials. The input is a set of standardized and unified data, and the output is the final, consistent material. The system performs calculations to combine text and image data and present it in a neat format.

[0676] Step 6:

[0677] The server provides users with unified generated documents. The input is unified documents, and the output is a digital file that users can download. It provides a concrete service that allows users to easily access and retrieve information via a web interface.

[0678] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0679] This invention provides a system that optimizes the user experience by combining a system for unifying information documents of different formats into a consistent format with an emotion engine that recognizes user emotions. This system consists of a server and terminals and is effectively operated in both document management and user interface aspects.

[0680] When a user uploads an informational document to the system, the server receives the information and classifies it into text data and image data. The classified data then undergoes appropriate analysis and standardization processes to be reconstructed into a consistent document. Up to this point, the information is organized through basic document unification processes.

[0681] A notable feature of this system is the emotion engine built into the terminal. This engine has the function of analyzing the user's emotions in real time based on the user's input and actions. Through this analysis, it is possible to capture emotional responses such as the user's interest and stress level while they are viewing text.

[0682] Specifically, when the emotion engine detects a change in the user's emotions, the server dynamically adjusts how standardized documents generated based on that information are presented. For example, if a user shows stress from certain content, the device can change the display order of the relevant sections or display additional explanations. Such adjustments are made automatically to improve the user experience.

[0683] Furthermore, for example, when a user is using a product's technical manual, if they indicate they are experiencing difficulty, the emotion engine will provide support by suggesting links to relevant tutorial videos or FAQs. This feature combines consistent information management with emotion-responsive interaction, enabling more personalized information delivery to users.

[0684] In this way, this system, which incorporates an emotion engine, goes beyond mere information unification and enables dynamic information presentation tailored to the user's emotional state. This increases usefulness and adaptability, promoting the effective use of information.

[0685] The following describes the processing flow.

[0686] Step 1:

[0687] Users upload informational documents in different formats to the system. The server accepts these documents and performs preprocessing according to the file format. For example, it extracts text and images from PDF and Word documents.

[0688] Step 2:

[0689] The server classifies the acquired data into text data and image data. Text data is recognized as character information, and image data is treated as visual information. An appropriate classification method is applied according to the various data formats.

[0690] Step 3:

[0691] The server analyzes the classified text data. Using a large-scale language model, it analyzes and standardizes the hierarchical structure of the document. For example, it identifies headings and bullet points within the text to clarify the document's structure.

[0692] Step 4:

[0693] The device uses image recognition technology to analyze image data. Specifically, it identifies objects within the image and resizes or rearranges them into a standard format. This ensures consistency across various images.

[0694] Step 5:

[0695] The terminal integrates the analyzed and standardized text and image data. The server then generates a consistent informational document based on this data and prepares it for delivery to the user.

[0696] Step 6:

[0697] While a user is viewing a generated document, the device's emotion engine monitors the user's emotional state in real time. For example, it estimates emotions based on factors such as the user's operation speed and the time spent at specific points in the document.

[0698] Step 7:

[0699] When the emotion engine detects a specific change in the user's emotion, the server dynamically adjusts how the document is presented based on that information. For example, if the user shows confusion, it will display a more detailed explanation of the relevant section or additional visual aids.

[0700] Step 8:

[0701] The user reviews the revised document again and provides feedback as needed. The server uses the feedback to further optimize the document and provides the user with the final version.

[0702] (Example 2)

[0703] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0704] When information documents exist in multiple formats, unifying them into a consistent format contributes to improving the user experience. However, traditional methods lack not only document uniformity but also dynamic information presentation that responds to the user's emotional reactions. As a result, users may not receive appropriate support when they encounter difficulties or stress with the document content, potentially leading to decreased user understanding and satisfaction.

[0705] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0706] In this invention, the server includes means for accepting information documents of different formats, means for classifying them into text data and image data, means for integrating the standardized text data and image data to generate a consistent document, means for analyzing the user's emotional state in real time, and means for dynamically adjusting the document presentation method based on the analysis results. This enables the unification of information documents as well as personalized information presentation that responds to the user's emotions.

[0707] "Information documents in different formats" refers to documents that have various data representation forms, including text format and image format.

[0708] "Text data" refers to data composed of strings of characters, and is the basic unit for representing documents and texts.

[0709] "Image data" refers to data that represents visual information recorded in digital format.

[0710] Standardization is the process of organizing data with different forms and contents into a unified format and structure.

[0711] "Image recognition technology" is a technology that allows computer systems to identify specific patterns or features from image data.

[0712] A "consistent document" is a document in which various forms of data are integrated and organized into a unified format.

[0713] "Emotional state" is a concept that describes the emotions and mental state a user is experiencing at a particular moment.

[0714] "Real-time analysis" refers to a process where data is processed instantly and results are obtained at the very moment the user inputs or performs an action.

[0715] "Dynamic adjustment" means flexibly changing the system's operation and output according to the situation and conditions.

[0716] As a form of implementing the invention, this system converts information documents of different formats into a unified format and provides personalized information based on the user's emotional state. Details are provided below.

[0717] The server features a user interface for uploading informational documents and classifies the documents received from users into text data and image data. Natural language processing (NLP) techniques are applied to analyze the text data, and image recognition techniques are used to analyze the image data. Machine learning models are utilized in these techniques. Based on the analysis results, the server standardizes the data and generates consistent documents.

[0718] The device is equipped with an emotion engine that analyzes the user's emotional state in real time based on their actions and inputs. This engine performs face tracking and analyzes operation patterns to determine the user's level of interest and stress. If the user experiences stress, the device sends that state to the server.

[0719] For example, if a user shows confusion while using a technical manual, the emotion engine will detect this emotion. The server can then prepare relevant tutorial videos and additional explanatory content to help the user understand better, and the device can display these.

[0720] Examples of prompts for a generative AI model are as follows:

[0721] "How can we analyze the emotions users experience when viewing product manuals and provide additional support information as needed?"

[0722] Such systems enable improved user experience and more efficient access to information.

[0723] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0724] Step 1:

[0725] Users upload informational documents to the system. Different file formats, such as PDFs and Word documents, are used as input. The server begins processing upon acceptance. The server detects the file from the user and sends a confirmation message to the user.

[0726] Step 2:

[0727] The server classifies the received document into text data and image data. At this stage, the input is the entire uploaded document. The server identifies and classifies the text information and images within the document. The text data and image data are output and stored internally.

[0728] Step 3:

[0729] The server analyzes the classified text data using natural language processing (NLP) techniques. Specifically, it analyzes the grammatical structure of the text and extracts keywords. The input is classified text data, and the output is standardized text data based on the analysis results.

[0730] Step 4:

[0731] The server analyzes and standardizes the classified image data using image recognition technology. The input is image data; it analyzes the shape, color, and patterns of the images and converts them into a consistent format. The output is image data in a unified format.

[0732] Step 5:

[0733] The server integrates standardized text and image data to generate a consistent document. The input consists of individual standardized data, and the output is a single, unified document. The server then prepares this generated document for the user.

[0734] Step 6:

[0735] The device uses an emotion engine to analyze the user's emotional state in real time. User operation data and facial expression data are used as input. The device converts this into an emotional state and detects a specific emotion. The output is the user's emotional data.

[0736] Step 7:

[0737] The server dynamically adjusts how generated documents are presented based on the emotional data received from the terminal. The input consists of emotional data and the generated documents. If the user is experiencing stress, the server adjusts to output additional relevant support information and explanations.

[0738] (Application Example 2)

[0739] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0740] While a vast amount of information is currently available on the internet, few systems consider the user's emotions when viewing this information. Users can be overwhelmed by the sheer volume of information, sometimes experiencing stress. Therefore, there is a need for technology that dynamically adjusts how information is displayed according to the user's emotions, thereby improving the user experience.

[0741] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0742] In this invention, the server includes means for accepting information documents of different formats, means for analyzing the user's emotional state, and means for dynamically adjusting the display order of documents based on the analyzed emotional state. This enables the presentation of information that is optimal to the user's emotions.

[0743] "Information documents in different formats" refers to a collection of information that exists in multiple formats, such as text data and image data.

[0744] A "means of acceptance" is a mechanism that allows a system to receive data from an external source and begin processing it.

[0745] A "means of classification" refers to a device or program that has the function of sorting received data into text data and image data according to its nature.

[0746] "Means of standardization" refer to methods and devices for transforming classified data into a consistent format and unifying it.

[0747] "Image recognition technology" refers to computer vision techniques used to analyze the content of image data and extract features.

[0748] A "consistent document" is a document in a standardized format that integrates data from different formats.

[0749] "Means of provision" refers to methods and devices for presenting a consistent set of generated documents to the user in a viewable format.

[0750] The "function to analyze the user's emotional state" is a technology that recognizes emotions based on the user's facial expressions and tone of voice.

[0751] "Means for dynamically adjusting the display order" refers to devices or programs that have the function of automatically changing the display order of content according to the user's emotions.

[0752] To implement this invention, a server, a terminal, and an interface to the user are required. The server first accepts information documents in different formats and classifies them into text data and image data. The classified data is then reconstructed into a consistent document through a standardization process.

[0753] The server uses the device's camera and microphone to collect the user's facial expressions and voice in order to analyze the user's emotional state. This data is processed using emotion analysis software such as Google Cloud Vision API or IBM Watson Tone Analyzer. Based on the user's emotional state, processing is performed to dynamically adjust the display order and content of documents. Specifically, if the analysis indicates that the user is feeling stressed, the presentation order is changed so that positive content is displayed preferentially.

[0754] In this way, the system provides users with the most relevant information. For example, if sentiment analysis detects stress when a user is reading the morning news, the system will prioritize displaying articles about relaxing hobbies to alleviate their mood. At the same time, if the user shows interest in a particular topic, the system can use a generative AI model to generate new, relevant information.

[0755] An example of a prompt message would be: "Generate detailed information about a topic the user has shown interest in. For example, 'Generate an article that makes you feel positive about the latest sports news.'"

[0756] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0757] Step 1:

[0758] The server accepts information documents in various formats uploaded by users. The information documents are passed to the server as input and are classified into text data and image data. Preparations for text analysis and image analysis are then performed depending on the document format.

[0759] Step 2:

[0760] The server performs a process to standardize classified text data. The input is text data, which is then parsed to convert it into a consistent format. A language model is used to extract the document's hierarchical structure and key points, and the organized text data is output.

[0761] Step 3:

[0762] The server uses image recognition technology to analyze the image data. It receives image data as input, identifies elements within the image, and standardizes their format. During this process, the recognized content is output as structured data.

[0763] Step 4:

[0764] The server integrates standardized text data and unified image data to generate consistent documents. The input consists of pre-processed text and images, which are then merged to create a unified document. This document is output in a format viewable by the user.

[0765] Step 5:

[0766] The device acquires facial expressions and audio from its camera and microphone to analyze the user's emotional state. The input is a real-time video and audio stream, and the user's emotions are analyzed using emotion analysis software. As a result, emotional state data is output.

[0767] Step 6:

[0768] The server dynamically adjusts the display order of documents based on the analyzed emotional state. The input is emotional state data, and a display order algorithm is applied based on this data to output documents that take the user's emotions into consideration. This results in optimized information presentation that reflects the user's interests and stress levels.

[0769] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0770] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0771] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0772] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0773] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0774] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0775] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0776] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0777] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0778] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0779] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0780] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0781] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0782] 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.

[0783] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0784] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0785] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0786] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0787] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0788] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0789] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0790] The following is further disclosed regarding the embodiments described above.

[0791] (Claim 1)

[0792] Means for accepting information documents in different formats,

[0793] A means of classifying received information documents into text data and image data,

[0794] A means of analyzing and standardizing classified text data,

[0795] A means of analyzing image data using image recognition technology and standardizing its format,

[0796] A means of integrating standardized text data and image data to generate consistent documents,

[0797] A means of providing the generated documents to the user,

[0798] A system that includes this.

[0799] (Claim 2)

[0800] The system according to claim 1, comprising means for identifying the hierarchical structure of documents from classified text data using a language model.

[0801] (Claim 3)

[0802] The system according to claim 1, comprising means for analyzing image data and identifying specific content using image recognition technology.

[0803] "Example 1"

[0804] (Claim 1)

[0805] Means of accepting information in different formats,

[0806] A means of classifying the received information into text data and visual data,

[0807] A means of analyzing and standardizing classified character data,

[0808] A means of analyzing visual data using visual recognition technology and standardizing its format,

[0809] A means of integrating standardized text data and visual data to generate consistent information,

[0810] Means for providing the generated information to users,

[0811] A system that includes this.

[0812] (Claim 2)

[0813] The system according to claim 1, comprising means for identifying the hierarchical structure of information from classified character data using a language analysis model.

[0814] (Claim 3)

[0815] The system according to claim 1, comprising means for analyzing visual data and identifying specific content using visual recognition technology.

[0816] "Application Example 1"

[0817] (Claim 1)

[0818] Means of accepting different forms of digital information,

[0819] A means of classifying the received digital information into symbolic data and image data,

[0820] A means of analyzing and standardizing classified symbolic data,

[0821] A method for analyzing video data using video recognition technology and standardizing its format,

[0822] A means of integrating standardized symbolic data and image data to generate consistent materials,

[0823] Means of providing the generated materials to users,

[0824] A means for acquiring digital video using a smart device and transmitting said video as digital data to a server,

[0825] A means for identifying a standard information style from the digital data and enabling easy acquisition of the digital information,

[0826] A system that includes this.

[0827] (Claim 2)

[0828] The system according to claim 1, comprising means for identifying the hierarchical structure of a document from classified symbolic data using natural language technology, thereby facilitating information management in a smart city.

[0829] (Claim 3)

[0830] The system according to claim 1, comprising means for analyzing video data using video recognition technology to identify specific information and present urban planning information and event information to citizens.

[0831] "Example 2 of combining an emotion engine"

[0832] (Claim 1)

[0833] Means for accepting information documents in different formats,

[0834] A means of classifying received information documents into text data and image data,

[0835] A means of analyzing and standardizing classified text data,

[0836] A means of analyzing image data using image recognition technology and standardizing its format,

[0837] A means of integrating standardized text data and image data to generate consistent documents,

[0838] A means of analyzing the user's emotional state in real time,

[0839] A means for dynamically adjusting the presentation method of the generated documents based on the analysis results,

[0840] A system that includes this.

[0841] (Claim 2)

[0842] The system according to claim 1, comprising means for identifying the hierarchical structure of documents from classified text data using a language model.

[0843] (Claim 3)

[0844] The system according to claim 1, comprising means for analyzing image data and identifying specific content using image recognition technology.

[0845] "Application example 2 when combining with an emotional engine"

[0846] (Claim 1)

[0847] Means for accepting information documents in different formats,

[0848] A means of classifying received information documents into text data and image data,

[0849] A means of analyzing and standardizing classified text data,

[0850] A means of analyzing image data using image recognition technology and standardizing its format,

[0851] A means of integrating standardized text data and image data to generate consistent documents,

[0852] A means of providing the generated documents to the user,

[0853] A means having a function to analyze the user's emotional state,

[0854] A means for dynamically adjusting the display order of documents based on the analyzed emotional state,

[0855] A system that includes this.

[0856] (Claim 2)

[0857] The system according to claim 1, comprising means for recognizing the user's emotional state by analyzing their voice and facial expressions, and for presenting relevant information based on that information.

[0858] (Claim 3)

[0859] The system according to claim 1, comprising means for automatically changing the presentation order of generated documents based on emotional state. [Explanation of symbols]

[0860] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Means of accepting different forms of digital information, A means of classifying the received digital information into symbolic data and image data, A means of analyzing and standardizing classified symbolic data, A method for analyzing video data using video recognition technology and standardizing its format, A means of integrating standardized symbolic data and image data to generate consistent materials, Means of providing the generated materials to users, A means for acquiring digital video using a smart device and transmitting said video as digital data to a server, A means for identifying a standard information style from the digital data and enabling easy acquisition of the digital information, A system that includes this.

2. The system according to claim 1, comprising means for identifying the hierarchical structure of a document from classified symbolic data using natural language technology, thereby facilitating information management in a smart city.

3. The system according to claim 1, comprising means for analyzing video data using video recognition technology to identify specific information and present urban planning information and event information to citizens.

Images